Repository: expectedparrot/edsl

Issue:
Scenario example with image not working
Responses appear to be static? New questions using the example scenario with `has_image=True` are not generating new responses:

https://www.expectedparrot.com/content/d91645c9-c74b-4b1f-98ab-733aff23605d

Discussion:
@rbyh: Also not working with scenario generated from local image using `from_image()` method:

https://www.expectedparrot.com/content/fb6e647b-87e8-4aa4-bae7-f0dfe75d26cc@johnjosephhorton: Great - catch - it's a caching bug - I'm on it. 

<img width="523" alt="Screenshot 2024-09-21 at 6 52 44 AM" src="https://github.com/user-attachments/assets/6a727a00-d07c-4789-89bd-ffb27b9c17a6">


Solution patch:
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 58dac7f90..91cfe9e40 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -47,6 +47,8 @@
 ### Changed
 - Improvements to exceptions reports. 
 
+- Improvements to the progress bar: `survey.run(progress_bar=True)`
+
 - Question validation methods no longer use JSON. This will eliminate exceptions relating to JSON errors previously common to certain models.
 
 - Base agent instructions template is not added to a job if no agent is used with a survey (reducing tokens).
diff --git a/docs/api_keys.rst b/docs/api_keys.rst
index 2754264c1..dd942bf79 100644
--- a/docs/api_keys.rst
+++ b/docs/api_keys.rst
@@ -42,7 +42,18 @@ Replace `your_key_here` with your actual API key for each service that you plan
    DEEP_INFRA_API_KEY='your_key_here'
    GOOGLE_API_KEY='your_key_here'
    GROQ_API_KEY='your_key_here'
+   MISTRAL_API_KEY='your_key_here'
    OPENAI_API_KEY='your_key_here'
+   REPLICATE_API_KEY='your_key_here'
+
+
+AWS Bedrock requires multiple keys:
+
+.. code-block:: python
+
+   AWS_ACCESS_KEY_ID='your_key_here'
+   AWS_SECRET_ACCESS_KEY='your_key_here'
+   AZURE_ENDPOINT_URL_AND_KEY='your_key_here'
 
 
 Using a `.env file` allows you to store your keys once and avoid repeatedly enter your API keys each time you start a session with EDSL.
@@ -56,11 +67,14 @@ This method stores the keys in your system's memory only for the duration of the
 .. code-block:: python
 
    import os
+
    os.environ['ANTHROPIC_API_KEY'] = 'your_key_here'
    os.environ['DEEP_INFRA_API_KEY'] = 'your_key_here'
    os.environ['GOOGLE_API_KEY'] = 'your_key_here'
    os.environ['GROQ_API_KEY'] = 'your_key_here'
+   os.environ['MISTRAL_API_KEY'] = 'your_key_here'
    os.environ['OPENAI_API_KEY'] = 'your_key_here'
+   os.environ['REPLICATE_API_KEY'] = 'your_key_here'
 
 
 Remember, if you restart your session, you will need to re-enter your API keys.
@@ -69,42 +83,47 @@ It is also important to remove your API keys from your code before sharing it wi
 
 Caution
 ~~~~~~~
+
 Treat your API keys as sensitive information, akin to passwords. 
 Never share them publicly or upload files containing your API keys to public repositories.
 
 
 Troubleshooting
 ~~~~~~~~~~~~~~~
+
 In addition to API keys, you must also have credits available on your account with a language model provider in order to run surveys with some models.
 
-If you do not specify a model to use for a survey, EDSL will attempt to run it with the default model; currently, this is GPT 4 Preview.
+If you do not specify a model to use for a survey, EDSL will attempt to run it with the default model.
 In practice, this means that the following sets of commands are equivalent:
 
 *Version 1*:
 
 .. code-block:: python
 
-   results = survey.run()
+   from edsl import Survey 
 
+   results = Survey.example().run()
 
-*Version 1*:
+
+*Version 2*:
 
 .. code-block:: python
 
-   from edsl import Model 
+   from edsl import Survey, Model 
 
-   results = survey.by(Model('gpt-4-1106-preview')).run()
+   results = Survey.example().by(Model()).run() 
 
 
-*Version 1*:
+*Version 3*:
 
 .. code-block:: python
 
-   from edsl import Model 
+   from edsl import Survey, Model 
 
-   model = Model('gpt-4-1106-preview')
+   s = Survey.example()
+   m = Model()
 
-   results = survey.by(model).run()
+   results = s.by(m).run()
 
 
 If you have not provided an API key for the default model you will receive an error message about an exception.
diff --git a/docs/exceptions.rst b/docs/exceptions.rst
index c7e8c252a..4caf72198 100644
--- a/docs/exceptions.rst
+++ b/docs/exceptions.rst
@@ -12,7 +12,7 @@ Help debugging
 
 If you would like help debugging an error that you are encountering, please feel free to share your code, objects and exceptions report with us.
 
-A simple way to do this is to post a notebook with your code to the :ref:`coop` and share the link with us at info@expectedparrot.com.
+An easy way to do this is to post a notebook with your code to the :ref:`coop` and share the link with us at info@expectedparrot.com.
 You can use the following code to generate a link to your notebook:
 
 .. code-block:: python
diff --git a/docs/filestore.rst b/docs/filestore.rst
new file mode 100644
index 000000000..968a79f9a
--- /dev/null
+++ b/docs/filestore.rst
@@ -0,0 +1,219 @@
+.. _filestore:
+
+File Store
+==========
+
+`FileStore` is a module for storing and sharing data on the Coop that you want to use in your EDSL projects, such as survey data, PDFs, CSVs or images.
+It can be particularly useful for storing files to be used as as `Scenario` objects with a survey, and allows you to include code for retrieving and processing the files in your EDSL project.
+
+
+File types 
+----------
+
+The following file types are supported by the FileStore:
+
+- CSV
+- PDF
+- PNG 
+
+
+Posting a file
+--------------
+
+To store a file, you need to create a `FileStore` object with the path to the file you want to store.
+You can then use the `push` method to store the file on the Coop and get a URL for accessing the file.
+
+CSV example:
+
+.. code-block:: python
+
+    from edsl.scenarios.FileStore import CSVFileStore
+
+    fs = CSVFileStore("example.csv")
+    info = fs.push()
+    print(info) # to display the URL and Coop uuid of the stored file to use for retriving it later
+
+
+Example output:
+
+.. code-block:: python
+
+    {'description': 'File: example.csv', 
+    'object_type': 'scenario', 
+    'url': 'https://www.expectedparrot.com/content/4531d6ac-5425-4c93-aa02-07c1fa64aaa3', 
+    'uuid': '4531d6ac-5425-4c93-aa02-07c1fa64aaa3', 
+    'version': '0.1.33.dev1', 
+    'visibility': 'unlisted'}
+
+
+PDF example:
+
+.. code-block:: python
+
+    from edsl.scenarios.FileStore import PDFFileStore
+
+    fs = PDFFileStore("top_secret.pdf")
+    info = fs.push()
+    print(info) # to display the URL and Coop uuid of the stored file to use for retriving it later
+
+
+Example output:
+
+.. code-block:: python
+
+    {'description': 'File: top_secret.pdf', 
+    'object_type': 'scenario', 
+    'url': 'https://www.expectedparrot.com/content/a6231668-3166-4741-93d8-f3248b91660f', 
+    'uuid': 'a6231668-3166-4741-93d8-f3248b91660f', 
+    'version': '0.1.33.dev1', 
+    'visibility': 'unlisted'}
+
+
+PNG example:
+
+.. code-block:: python
+
+    from edsl.scenarios.FileStore import PNGFileStore
+
+    fs = PNGFileStore("parrot_logo.png")
+    info = fs.push()
+    print(info) # to display the URL and Coop uuid of the stored file to use for retriving it later
+
+
+Example output:
+
+.. code-block:: python
+
+    {'description': 'File: parrot_logo.png', 
+    'object_type': 'scenario', 
+    'url': 'https://www.expectedparrot.com/content/148e6320-5642-486c-9332-a6d30be0daae', 
+    'uuid': '148e6320-5642-486c-9332-a6d30be0daae', 
+    'version': '0.1.33.dev1', 
+    'visibility': 'unlisted'}
+
+
+Retrieving and using a file
+---------------------------
+
+To retrieve a file, you need to create a `FileStore` object with the Coop uuid of the file you want to retrieve.
+You can then use the `pull` method to retrieve the file from the Coop.
+
+Once you have retrieved a file, you can use it in your EDSL project as a `Scenario` object.
+Each file type has a method for converting the file into a scenario:
+
+- `from_csv` for CSV files
+- `from_pdf` for PDF files
+- `from_image` for PNG files
+
+
+CSV example
+^^^^^^^^^^^
+
+For CSV files we use the `from_csv` method of the `ScenarioList` class.
+They keys are the column names of the CSV file, which can be modified with the `rename` method.
+
+.. code-block:: python
+
+    from edsl.scenarios.FileStore import CSVFileStore
+    from edsl import ScenarioList
+    
+    csv_file = CSVFileStore.pull("4531d6ac-5425-4c93-aa02-07c1fa64aaa3", expected_parrot_url="https://www.expectedparrot.com")
+
+    scenarios = ScenarioList.from_csv(csv_file.to_tempfile())
+
+
+PDF example
+^^^^^^^^^^^
+
+For PDF files we use the `from_pdf` method of the `ScenarioList` class.
+The default keys are `filename`, `page`, `text`, which can be modified with the `rename` method.
+
+.. code-block:: python
+
+    from edsl.scenarios.FileStore import PDFFileStore
+    from edsl import ScenarioList
+
+    pdf_file = PDFFileStore.pull("a6231668-3166-4741-93d8-f3248b91660f", expected_parrot_url="https://www.expectedparrot.com")
+    
+    scenario = ScenarioList.from_pdf(pdf_file.to_tempfile())
+
+
+To inspect the keys:
+
+.. code-block:: python
+
+    scenario.parameters
+
+
+Output:
+
+.. code-block:: python
+
+    {'filename', 'page', 'text'}
+
+
+PNG example
+^^^^^^^^^^^
+
+For PNG files we use the `from_image` method which takes the PNG file and (optionally) the name of a key to use for the scenario object.
+
+.. code-block:: python
+
+    from edsl.scenarios.FileStore import PNGFileStore
+    from edsl import Scenario
+    
+    png_file = PNGFileStore.pull("148e6320-5642-486c-9332-a6d30be0daae", expected_parrot_url="https://www.expectedparrot.com")
+
+    scenario = Scenario.from_image(png_file.to_tempfile(), "parrot_logo") # including a key for the scenario object
+
+
+Working with scenarios 
+----------------------
+
+Before using the scenario, verify the key and value of the scenario object (e.g., by printing), and rename the key as desired to use in survey questions.
+
+For a single `Scenario` we can check the key:
+
+.. code-block:: python
+
+    scenario.keys()
+
+
+(For a `ScenarioList` object, we can call the `parameters` method to get the keys.)
+
+If the key is `parrot_logo` and you want to rename it `logo`:
+
+.. code-block:: python
+
+    scenario = scenario.rename({"parrot_logo": "logo"})
+
+
+To use it in a question, the question should be parameterized with the key:
+
+.. code-block:: python
+
+    from edsl import QuestionFreeText 
+
+    q = QuestionFreeText(
+        question_name = "test",
+        question_text = "What is the logo of the company? {{ logo }}"
+    )
+
+    results = q.by(scenario).run()
+
+
+Example notebook
+----------------
+
+The following notebook at the Coop includes the above code examples: https://www.expectedparrot.com/content/e1a00873-dfc6-4383-9426-cc032296bab1
+
+
+FileStore class
+---------------
+
+.. automodule:: edsl.scenarios.FileStore
+   :members:
+   :undoc-members:
+   :show-inheritance:
+   :special-members: __init__
+   :exclude-members: 
\ No newline at end of file
diff --git a/docs/index.rst b/docs/index.rst
index a79028cf6..bc8dc59cd 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -156,8 +156,9 @@ Information about additional functionality for developers.
 
    coop
    notebooks
-   remote_caching
    remote_inference
+   remote_caching
+   filestore
 
 .. toctree::
    :maxdepth: 2
@@ -172,18 +173,18 @@ Information about additional functionality for developers.
    :hidden:
 
    notebooks/edsl_intro.ipynb
+   notebooks/edsl_components.ipynb
    notebooks/data_labeling_example.ipynb
+   notebooks/data_cleaning.ipynb
+   notebooks/scenario_from_pdf.ipynb
    notebooks/image_scenario_example.ipynb
    notebooks/question_loop_scenario.ipynb
    notebooks/scenario_list_wikipedia.ipynb
-   notebooks/scenario_from_pdf.ipynb
    notebooks/batching_results.ipynb
    notebooks/adding_metadata.ipynb
    notebooks/example_agent_dynamic_traits.ipynb
    notebooks/research_methods.ipynb
-   notebooks/edsl_components.ipynb
    notebooks/question_extract_example.ipynb
-   notebooks/data_cleaning.ipynb
 
 .. toctree::
    :maxdepth: 2
@@ -191,18 +192,18 @@ Information about additional functionality for developers.
    :hidden:
 
    notebooks/next_token_probs.ipynb
-   notebooks/scenariolist_unpivot.ipynb
-   notebooks/nps_survey.ipynb
    notebooks/agentifying_responses.ipynb
    notebooks/summarizing_transcripts.ipynb
-   notebooks/data_labeling_agent.ipynb
+   notebooks/analyze_evaluations.ipynb
+   notebooks/concept_induction.ipynb
    notebooks/conduct_interview.ipynb
    notebooks/qualitative_research.ipynb
+   notebooks/nps_survey.ipynb
+   notebooks/data_labeling_agent.ipynb
+   notebooks/scenariolist_unpivot.ipynb
    notebooks/random_numbers.ipynb
-   notebooks/concept_induction.ipynb
    notebooks/testing_training_data.ipynb
    notebooks/comparing_model_responses.ipynb
-   notebooks/analyze_evaluations.ipynb
    notebooks/evaluating_job_posts.ipynb
    notebooks/explore_llm_biases.ipynb
    notebooks/research_random_silicon_sampling.ipynb
diff --git a/docs/notebooks.rst b/docs/notebooks.rst
index 957a3070c..0382d8a10 100644
--- a/docs/notebooks.rst
+++ b/docs/notebooks.rst
@@ -3,7 +3,7 @@
 Notebooks
 =========
 
-The `Notebook` object allows you to share your .ipynb files with others by uploading them to Coop.
+The `Notebook` object allows you to share your *.ipynb* files by uploading them to Coop.
 You can also view and pull notebooks that other users have uploaded.
 
 Creating a `Notebook` object
@@ -11,19 +11,22 @@ Creating a `Notebook` object
 
 There are three ways to create a `Notebook` object:
 
-1. From file
-^^^^^^^^^^^^
-Pass the path to your .ipynb file to the constructor (you must include `path` as a keyword argument):
+
+1. From a file
+^^^^^^^^^^^^^^
+
+Pass the path to your *.ipynb* file to the constructor (*note:* you must include `path` as a keyword argument):
 
 .. code-block:: python
 
     from edsl import Notebook
 
-    notebook = Notebook(path="notebooks/test-notebook.ipynb")
+    notebook = Notebook(path="notebooks/test-notebook.ipynb") # replace with your file path
 
 
 2. From data
 ^^^^^^^^^^^^
+
 Your data must be a Python `dict` that conforms to the official Jupyter notebook format. 
 Learn more about the format `here <https://nbformat.readthedocs.io/en/latest/format_description.html>`_.
 
@@ -49,6 +52,7 @@ Learn more about the format `here <https://nbformat.readthedocs.io/en/latest/for
 
 3. From self
 ^^^^^^^^^^^^
+
 To create a `Notebook` for a notebook that you are currently working in:
 
 .. code-block:: python
@@ -60,6 +64,7 @@ To create a `Notebook` for a notebook that you are currently working in:
 
 
 .. warning::
+
     For now, this method only works if you are using the VS Code IDE. 
 
     
@@ -93,7 +98,7 @@ Or alternatively using the `Coop` client object:
 
 This will return a message with information about the object that was posted, and you will be able to view your notebook at the Coop: `My Content  <https://www.expectedparrot.com/home/content/>`_.
 
-.. code-block:: text
+.. code-block:: python
 
   {'description': 'This is a test notebook',
   'object_type': 'notebook',
@@ -106,10 +111,10 @@ This will return a message with information about the object that was posted, an
 Saving a Coop notebook to file
 ------------------------------
 
-You can access notebooks that other users have posted publicly at the `Explore <https://www.expectedparrot.com/explore/explore/>`_ page.
+You can access notebooks that other users have posted publicly at the Coop `Explore <https://www.expectedparrot.com/explore/explore/>`_ page.
 
 Notebooks can be copied and downloaded the same way as other EDSL objects: by calling the `pull()` method on the `Notebook` class or the `get` method on a `Coop` client object and passing the notebook's `uuid`.
-We can also use the `to_file()` method to save the notebook to a file:
+You can also use the `to_file()` method to save the notebook to a file:
 
 .. code-block:: python
 
diff --git a/docs/notebooks/comparing_model_responses.ipynb b/docs/notebooks/comparing_model_responses.ipynb
index 14f6d571b..a2014a57d 100644
--- a/docs/notebooks/comparing_model_responses.ipynb
+++ b/docs/notebooks/comparing_model_responses.ipynb
@@ -4,7 +4,12 @@
    "cell_type": "markdown",
    "metadata": {
     "cell_id": "d4d5c2583fc14fdb895e689f40ba6737",
-    "deepnote_cell_type": "markdown"
+    "deepnote_cell_type": "markdown",
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
    },
    "source": [
     "# Comparing model responses\n",
@@ -12,19 +17,8 @@
     "\n",
     "In a series of steps we select some models, prompt them to generate some content, then prompt them to evaluate each piece of content that was generated, and then analyze the results in datasets.\n",
     "\n",
-    "Before running this notebook please see details on [installing EDSL](https://docs.expectedparrot.com/en/latest/installation.html) and [getting started](https://docs.expectedparrot.com/en/latest/tutorial_getting_started.html) using the library."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {
-    "cell_id": "83ac608cf73d49f2a35d9cf45c2b7c75",
-    "deepnote_cell_type": "code"
-   },
-   "outputs": [],
-   "source": [
-    "# ! pip install edsl"
+    "[EDSL is an open-source libary](https://github.com/expectedparrot/edsl) for simulating surveys, experiments and other research with AI agents and large language models. \n",
+    "Before running the code below, please ensure that you have [installed the EDSL library](https://docs.expectedparrot.com/en/latest/installation.html) and either [activated remote inference](https://docs.expectedparrot.com/en/latest/remote_inference.html) from your [Coop account](https://docs.expectedparrot.com/en/latest/coop.html) or [stored API keys](https://docs.expectedparrot.com/en/latest/api_keys.html) for the language models that you want to use with EDSL. Please also see our [documentation page](https://docs.expectedparrot.com/) for tips and tutorials on getting started using EDSL."
    ]
   },
   {
@@ -32,12 +26,13 @@
    "metadata": {},
    "source": [
     "## Selecting language models\n",
-    "EDSL works with many popular models. (Please send us a request for a model you like that's missing!) We can see a current list of available models:"
+    "[EDSL works with many popular language models](https://docs.expectedparrot.com/en/latest/language_models.html). (Please send us a request for a model you like that's missing!) \n",
+    "We can check a current list of available models:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {
     "cell_id": "4fa4d5aa948642b1972b84993e35f685",
     "deepnote_cell_type": "code",
@@ -46,91 +41,11 @@
     "execution_start": 1709310900433,
     "source_hash": null
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[['01-ai/Yi-34B-Chat', 'deep_infra', 0],\n",
-       " ['Austism/chronos-hermes-13b-v2', 'deep_infra', 1],\n",
-       " ['Gryphe/MythoMax-L2-13b', 'deep_infra', 2],\n",
-       " ['Gryphe/MythoMax-L2-13b-turbo', 'deep_infra', 3],\n",
-       " ['HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1', 'deep_infra', 4],\n",
-       " ['Phind/Phind-CodeLlama-34B-v2', 'deep_infra', 5],\n",
-       " ['Qwen/Qwen2-72B-Instruct', 'deep_infra', 6],\n",
-       " ['Qwen/Qwen2-7B-Instruct', 'deep_infra', 7],\n",
-       " ['Sao10K/L3-70B-Euryale-v2.1', 'deep_infra', 8],\n",
-       " ['bigcode/starcoder2-15b', 'deep_infra', 9],\n",
-       " ['bigcode/starcoder2-15b-instruct-v0.1', 'deep_infra', 10],\n",
-       " ['claude-3-5-sonnet-20240620', 'anthropic', 11],\n",
-       " ['claude-3-haiku-20240307', 'anthropic', 12],\n",
-       " ['claude-3-opus-20240229', 'anthropic', 13],\n",
-       " ['claude-3-sonnet-20240229', 'anthropic', 14],\n",
-       " ['codellama/CodeLlama-34b-Instruct-hf', 'deep_infra', 15],\n",
-       " ['codellama/CodeLlama-70b-Instruct-hf', 'deep_infra', 16],\n",
-       " ['cognitivecomputations/dolphin-2.6-mixtral-8x7b', 'deep_infra', 17],\n",
-       " ['cognitivecomputations/dolphin-2.9.1-llama-3-70b', 'deep_infra', 18],\n",
-       " ['databricks/dbrx-instruct', 'deep_infra', 19],\n",
-       " ['deepinfra/airoboros-70b', 'deep_infra', 20],\n",
-       " ['gemini-pro', 'google', 21],\n",
-       " ['google/codegemma-7b-it', 'deep_infra', 22],\n",
-       " ['google/gemma-1.1-7b-it', 'deep_infra', 23],\n",
-       " ['google/gemma-2-27b-it', 'deep_infra', 24],\n",
-       " ['google/gemma-2-9b-it', 'deep_infra', 25],\n",
-       " ['gpt-3.5-turbo', 'openai', 26],\n",
-       " ['gpt-3.5-turbo-0125', 'openai', 27],\n",
-       " ['gpt-3.5-turbo-0301', 'openai', 28],\n",
-       " ['gpt-3.5-turbo-0613', 'openai', 29],\n",
-       " ['gpt-3.5-turbo-1106', 'openai', 30],\n",
-       " ['gpt-3.5-turbo-16k', 'openai', 31],\n",
-       " ['gpt-3.5-turbo-16k-0613', 'openai', 32],\n",
-       " ['gpt-3.5-turbo-instruct', 'openai', 33],\n",
-       " ['gpt-3.5-turbo-instruct-0914', 'openai', 34],\n",
-       " ['gpt-4', 'openai', 35],\n",
-       " ['gpt-4-0125-preview', 'openai', 36],\n",
-       " ['gpt-4-0613', 'openai', 37],\n",
-       " ['gpt-4-1106-preview', 'openai', 38],\n",
-       " ['gpt-4-1106-vision-preview', 'openai', 39],\n",
-       " ['gpt-4-turbo', 'openai', 40],\n",
-       " ['gpt-4-turbo-2024-04-09', 'openai', 41],\n",
-       " ['gpt-4-turbo-preview', 'openai', 42],\n",
-       " ['gpt-4-vision-preview', 'openai', 43],\n",
-       " ['gpt-4o', 'openai', 44],\n",
-       " ['gpt-4o-2024-05-13', 'openai', 45],\n",
-       " ['gpt-4o-mini', 'openai', 46],\n",
-       " ['gpt-4o-mini-2024-07-18', 'openai', 47],\n",
-       " ['lizpreciatior/lzlv_70b_fp16_hf', 'deep_infra', 48],\n",
-       " ['llava-hf/llava-1.5-7b-hf', 'deep_infra', 49],\n",
-       " ['meta-llama/Llama-2-13b-chat-hf', 'deep_infra', 50],\n",
-       " ['meta-llama/Llama-2-70b-chat-hf', 'deep_infra', 51],\n",
-       " ['meta-llama/Llama-2-7b-chat-hf', 'deep_infra', 52],\n",
-       " ['meta-llama/Meta-Llama-3-70B-Instruct', 'deep_infra', 53],\n",
-       " ['meta-llama/Meta-Llama-3-8B-Instruct', 'deep_infra', 54],\n",
-       " ['meta-llama/Meta-Llama-3.1-405B-Instruct', 'deep_infra', 55],\n",
-       " ['meta-llama/Meta-Llama-3.1-70B-Instruct', 'deep_infra', 56],\n",
-       " ['meta-llama/Meta-Llama-3.1-8B-Instruct', 'deep_infra', 57],\n",
-       " ['microsoft/Phi-3-medium-4k-instruct', 'deep_infra', 58],\n",
-       " ['microsoft/WizardLM-2-7B', 'deep_infra', 59],\n",
-       " ['microsoft/WizardLM-2-8x22B', 'deep_infra', 60],\n",
-       " ['mistralai/Mistral-7B-Instruct-v0.1', 'deep_infra', 61],\n",
-       " ['mistralai/Mistral-7B-Instruct-v0.2', 'deep_infra', 62],\n",
-       " ['mistralai/Mistral-7B-Instruct-v0.3', 'deep_infra', 63],\n",
-       " ['mistralai/Mixtral-8x22B-Instruct-v0.1', 'deep_infra', 64],\n",
-       " ['mistralai/Mixtral-8x22B-v0.1', 'deep_infra', 65],\n",
-       " ['mistralai/Mixtral-8x7B-Instruct-v0.1', 'deep_infra', 66],\n",
-       " ['nvidia/Nemotron-4-340B-Instruct', 'deep_infra', 67],\n",
-       " ['openchat/openchat-3.6-8b', 'deep_infra', 68],\n",
-       " ['openchat/openchat_3.5', 'deep_infra', 69]]"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from edsl import Model\n",
     "\n",
-    "Model.available()"
+    "# Model.available() # uncomment this code and run it to see a current list of available models"
    ]
   },
   {
@@ -140,7 +55,25 @@
     "deepnote_cell_type": "markdown"
    },
    "source": [
-    "We select models to use by creating `Model` objects that we will add to our survey when we run it. (If we do not specify a model, GPT 4 preview will be used by default.) Here we select 4 models and store them as a list in order to use them all together with our survey:"
+    "We select models to use by creating `Model` objects that we will add to our survey when we run it. \n",
+    "If we do not specify a model, the default model is used.\n",
+    "To check the current default model:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Model()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Here we select several models and store them as a list in order to use them all together with our survey:"
    ]
   },
   {
@@ -154,15 +87,7 @@
    "source": [
     "from edsl import ModelList\n",
     "\n",
-    "models = ModelList(\n",
-    "    Model(m)\n",
-    "    for m in (\n",
-    "        \"gpt-3.5-turbo\",\n",
-    "        \"gpt-4-1106-preview\",\n",
-    "        \"gemini-pro\",\n",
-    "        \"claude-3-opus-20240229\",\n",
-    "    )\n",
-    ")"
+    "models = ModelList(Model(m) for m in [\"gpt-4o\", \"gemini-pro\", \"claude-3-opus-20240229\"])"
    ]
   },
   {
@@ -170,7 +95,9 @@
    "metadata": {},
    "source": [
     "## Generating content\n",
-    "EDSL comes with a variety of standard survey question types (multiple choice, free text, etc.) that we can select to use based on the desired format of the response (e.g., a selection from a list of options, unstructured text, etc.). [See examples of all question types](https://docs.expectedparrot.com/en/latest/questions.html#question-type-classes). Here we use `QuestionList` in order to prompt the model to provide its response in the form of a list:"
+    "EDSL comes with a variety of standard survey question types that we can select to use based on the desired format of the response (multiple choice, free text, etc.) [See examples of all question types](https://docs.expectedparrot.com/en/latest/questions.html#question-type-classes). \n",
+    "\n",
+    "Here we use `QuestionList` in order to prompt a model to provide its response in the form of a list:"
    ]
   },
   {
@@ -182,11 +109,11 @@
    },
    "outputs": [],
    "source": [
-    "from edsl.questions import QuestionList, QuestionLinearScale\n",
+    "from edsl import QuestionList\n",
     "\n",
     "q_content = QuestionList(\n",
-    "    question_name=\"content\",\n",
-    "    question_text=\"What are recommended steps for conducting research with large language models?\",\n",
+    "    question_name = \"content\",\n",
+    "    question_text = \"What are recommended steps for conducting research with large language models?\",\n",
     ")"
    ]
   },
@@ -194,7 +121,8 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We generate a response by passing the question to a `Survey` object, adding the models, and then calling the `run` method. This will generate a `Results` object with a `Result` for each survey response:"
+    "We generate a response by passing the question to a `Survey` object, adding the models, and then calling the `run` method. \n",
+    "This will generate a `Results` object with a `Result` for each survey response:"
    ]
   },
   {
@@ -204,275 +132,7 @@
     "cell_id": "724ca2c7a38f4164a225ed4a8dcc2b1f",
     "deepnote_cell_type": "code"
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Attempt 1 failed with exception:Answer key 'answer' must be of type list;\n",
-      "                (got None) which is of type <class 'NoneType'>. now waiting 1.00 seconds before retrying.Parameters: start=1.0, max=60.0, max_attempts=5.\n",
-      "\n",
-      "\n",
-      "Attempt 2 failed with exception:Answer key 'answer' must be of type list;\n",
-      "                (got null) which is of type <class 'str'>. now waiting 2.00 seconds before retrying.Parameters: start=1.0, max=60.0, max_attempts=5.\n",
-      "\n",
-      "\n",
-      "Attempt 1 failed with exception:Answer must have an 'answer' key (got {'new_answer': None, 'new_comment': 'null', 'cache_used': False, 'cache_key': '2ad0b1e3f0b08ad239de86f824772964', 'usage': {'completion_tokens': 13, 'prompt_tokens': 530, 'total_tokens': 543}, 'raw_model_response': {'id': 'chatcmpl-9pmAVRM8TOSs64i96CXwMLV9cq0BT', 'choices': [{'finish_reason': 'stop', 'index': 0, 'logprobs': None, 'message': {'content': '{\"new_answer\": null, \"new_comment\": \"null\"}', 'role': 'assistant', 'function_call': None, 'tool_calls': None}}], 'created': 1722126915, 'model': 'gpt-4-1106-preview', 'object': 'chat.completion', 'service_tier': None, 'system_fingerprint': None, 'usage': {'completion_tokens': 13, 'prompt_tokens': 530, 'total_tokens': 543}}}). now waiting 1.00 seconds before retrying.Parameters: start=1.0, max=60.0, max_attempts=5.\n",
-      "\n",
-      "\n",
-      "Exceptions were raised in 1 out of 4 interviews.\n",
-      "\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "<a href=\"/files//Users/a16174/edsl/docs/notebooks/tmp62qsiv4d.html\" target=\"_blank\">Open report to see details.</a>"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "\"\n",
-       "            <iframe srcdoc=\"\n",
-       "        &lt;!DOCTYPE html&gt;\n",
-       "        &lt;html lang=&quot;en&quot;&gt;\n",
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-       "        &lt;meta name=&quot;viewport&quot; content=&quot;width=device-width, initial-scale=1.0&quot;&gt;\n",
-       "        &lt;title&gt;Exception Details&lt;/title&gt;\n",
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-       "        margin: 20px;\n",
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-       "\n",
-       "        .interview {\n",
-       "        font-size: 1.5em;\n",
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-       "        padding: 10px;\n",
-       "        background-color: #e3f2fd;\n",
-       "        border-left: 5px solid #2196f3;\n",
-       "        }\n",
-       "\n",
-       "        .question {\n",
-       "        font-size: 1.2em;\n",
-       "        margin-bottom: 10px;\n",
-       "        padding: 10px;\n",
-       "        background-color: #fff9c4;\n",
-       "        border-left: 5px solid #ffeb3b;\n",
-       "        }\n",
-       "\n",
-       "        .exception-detail {\n",
-       "        margin-bottom: 10px;\n",
-       "        padding: 10px;\n",
-       "        background-color: #ffebee;\n",
-       "        border-left: 5px solid #f44336;\n",
-       "        }\n",
-       "\n",
-       "        .question-detail {\n",
-       "           border: 3px solid black; /* Adjust the thickness by changing the number */\n",
-       "            padding: 10px; /* Optional: Adds some padding inside the border */\n",
-       "        }\n",
-       "\n",
-       "        .exception-detail div {\n",
-       "        margin-bottom: 5px;\n",
-       "        }\n",
-       "\n",
-       "        .exception-exception {\n",
-       "        font-weight: bold;\n",
-       "        color: #d32f2f;\n",
-       "        }\n",
-       "\n",
-       "        .exception-time,\n",
-       "        .exception-traceback {\n",
-       "        font-style: italic;\n",
-       "        color: #555;\n",
-       "        }\n",
-       "        \n",
-       "        &lt;/style&gt;\n",
-       "        &lt;/head&gt;\n",
-       "        &lt;body&gt;\n",
-       "            \n",
-       "                \n",
-       "                            \n",
-       "            \n",
-       "                \n",
-       "                            \n",
-       "            \n",
-       "                \n",
-       "                            \n",
-       "            \n",
-       "                \n",
-       "                   &lt;div class=&quot;interview&quot;&gt;Interview: 3 &lt;/div&gt;\n",
-       "                    &lt;h1&gt;Failing questions&lt;/h1&gt;\n",
-       "                \n",
-       "                \n",
-       "                    &lt;div class=&quot;question&quot;&gt;question_name: content&lt;/div&gt;\n",
-       "\n",
-       "                    &lt;h2&gt;Question&lt;/h2&gt;\n",
-       "                    &lt;div class=&quot;question-detail&quot;&gt; \n",
-       "                            \n",
-       "        &lt;div id=&quot;content&quot; class=&quot;survey_question&quot; data-type=&quot;list&quot;&gt;\n",
-       "            \n",
-       "            &lt;p class=&quot;question_text&quot;&gt;What are recommended steps for conducting research with large language models?&lt;/p&gt;\n",
-       "            \n",
-       "        &lt;div id=&quot;question-list-container&quot;&gt;\n",
-       "            &lt;div&gt;\n",
-       "                &lt;textarea name=&quot;content[]&quot; rows=&quot;1&quot; placeholder=&quot;Enter item&quot;&gt;&lt;/textarea&gt;\n",
-       "            &lt;/div&gt;\n",
-       "        &lt;/div&gt;\n",
-       "        &lt;button type=&quot;button&quot; onclick=&quot;addNewLine()&quot;&gt;Add another line&lt;/button&gt;\n",
-       "\n",
-       "        &lt;script&gt;\n",
-       "            function addNewLine() {\n",
-       "                var container = document.getElementById(&#x27;question-list-container&#x27;);\n",
-       "                var newLine = document.createElement(&#x27;div&#x27;);\n",
-       "                newLine.innerHTML = &#x27;&lt;textarea name=&quot;content[]&quot; rows=&quot;1&quot; placeholder=&quot;Enter item&quot;&gt;&lt;/textarea&gt;&#x27;;\n",
-       "                container.appendChild(newLine);\n",
-       "            }\n",
-       "        &lt;/script&gt;\n",
-       "        \n",
-       "        &lt;/div&gt;\n",
-       "        \n",
-       "                    &lt;/div&gt;        \n",
-       "\n",
-       "                    &lt;h2&gt;Scenario&lt;/h2&gt;                            \n",
-       "                    &lt;div class=&quot;scenario&quot;&gt; \n",
-       "                            &lt;div class=&quot;highlight&quot;&gt;&lt;pre&gt;&lt;span&gt;&lt;/span&gt;&lt;span class=&quot;p&quot;&gt;{}&lt;/span&gt;\n",
-       "&lt;/pre&gt;&lt;/div&gt;\n",
-       "\n",
-       "                    &lt;/div&gt;        \n",
-       "\n",
-       "                    &lt;h2&gt;Agent&lt;/h2&gt;\n",
-       "                    &lt;div class=&quot;agent&quot;&gt;\n",
-       "                            &lt;div class=&quot;highlight&quot;&gt;&lt;pre&gt;&lt;span&gt;&lt;/span&gt;&lt;span class=&quot;p&quot;&gt;{&lt;/span&gt;\n",
-       "&lt;span class=&quot;w&quot;&gt;    &lt;/span&gt;&lt;span class=&quot;nt&quot;&gt;&amp;quot;traits&amp;quot;&lt;/span&gt;&lt;span class=&quot;p&quot;&gt;:&lt;/span&gt;&lt;span class=&quot;w&quot;&gt; &lt;/span&gt;&lt;span class=&quot;p&quot;&gt;{}&lt;/span&gt;\n",
-       "&lt;span class=&quot;p&quot;&gt;}&lt;/span&gt;\n",
-       "&lt;/pre&gt;&lt;/div&gt;\n",
-       "\n",
-       "                    &lt;/div&gt;\n",
-       "\n",
-       "                    &lt;h2&gt;Model&lt;/h2&gt;\n",
-       "                    &lt;div class=&quot;model&quot;&gt;\n",
-       "                            &lt;div class=&quot;highlight&quot;&gt;&lt;pre&gt;&lt;span&gt;&lt;/span&gt;&lt;span class=&quot;p&quot;&gt;{&lt;/span&gt;\n",
-       "&lt;span class=&quot;w&quot;&gt;    &lt;/span&gt;&lt;span class=&quot;nt&quot;&gt;&amp;quot;model&amp;quot;&lt;/span&gt;&lt;span class=&quot;p&quot;&gt;:&lt;/span&gt;&lt;span class=&quot;w&quot;&gt; &lt;/span&gt;&lt;span class=&quot;s2&quot;&gt;&amp;quot;claude-3-opus-20240229&amp;quot;&lt;/span&gt;&lt;span class=&quot;p&quot;&gt;,&lt;/span&gt;\n",
-       "&lt;span class=&quot;w&quot;&gt;    &lt;/span&gt;&lt;span class=&quot;nt&quot;&gt;&amp;quot;parameters&amp;quot;&lt;/span&gt;&lt;span class=&quot;p&quot;&gt;:&lt;/span&gt;&lt;span class=&quot;w&quot;&gt; &lt;/span&gt;&lt;span class=&quot;p&quot;&gt;{&lt;/span&gt;\n",
-       "&lt;span class=&quot;w&quot;&gt;        &lt;/span&gt;&lt;span class=&quot;nt&quot;&gt;&amp;quot;temperature&amp;quot;&lt;/span&gt;&lt;span class=&quot;p&quot;&gt;:&lt;/span&gt;&lt;span class=&quot;w&quot;&gt; &lt;/span&gt;&lt;span class=&quot;mf&quot;&gt;0.5&lt;/span&gt;&lt;span class=&quot;p&quot;&gt;,&lt;/span&gt;\n",
-       "&lt;span class=&quot;w&quot;&gt;        &lt;/span&gt;&lt;span class=&quot;nt&quot;&gt;&amp;quot;max_tokens&amp;quot;&lt;/span&gt;&lt;span class=&quot;p&quot;&gt;:&lt;/span&gt;&lt;span class=&quot;w&quot;&gt; &lt;/span&gt;&lt;span class=&quot;mi&quot;&gt;1000&lt;/span&gt;&lt;span class=&quot;p&quot;&gt;,&lt;/span&gt;\n",
-       "&lt;span class=&quot;w&quot;&gt;        &lt;/span&gt;&lt;span class=&quot;nt&quot;&gt;&amp;quot;top_p&amp;quot;&lt;/span&gt;&lt;span class=&quot;p&quot;&gt;:&lt;/span&gt;&lt;span class=&quot;w&quot;&gt; &lt;/span&gt;&lt;span class=&quot;mi&quot;&gt;1&lt;/span&gt;&lt;span class=&quot;p&quot;&gt;,&lt;/span&gt;\n",
-       "&lt;span class=&quot;w&quot;&gt;        &lt;/span&gt;&lt;span class=&quot;nt&quot;&gt;&amp;quot;frequency_penalty&amp;quot;&lt;/span&gt;&lt;span class=&quot;p&quot;&gt;:&lt;/span&gt;&lt;span class=&quot;w&quot;&gt; &lt;/span&gt;&lt;span class=&quot;mi&quot;&gt;0&lt;/span&gt;&lt;span class=&quot;p&quot;&gt;,&lt;/span&gt;\n",
-       "&lt;span class=&quot;w&quot;&gt;        &lt;/span&gt;&lt;span class=&quot;nt&quot;&gt;&amp;quot;presence_penalty&amp;quot;&lt;/span&gt;&lt;span class=&quot;p&quot;&gt;:&lt;/span&gt;&lt;span class=&quot;w&quot;&gt; &lt;/span&gt;&lt;span class=&quot;mi&quot;&gt;0&lt;/span&gt;&lt;span class=&quot;p&quot;&gt;,&lt;/span&gt;\n",
-       "&lt;span class=&quot;w&quot;&gt;        &lt;/span&gt;&lt;span class=&quot;nt&quot;&gt;&amp;quot;logprobs&amp;quot;&lt;/span&gt;&lt;span class=&quot;p&quot;&gt;:&lt;/span&gt;&lt;span class=&quot;w&quot;&gt; &lt;/span&gt;&lt;span class=&quot;kc&quot;&gt;false&lt;/span&gt;&lt;span class=&quot;p&quot;&gt;,&lt;/span&gt;\n",
-       "&lt;span class=&quot;w&quot;&gt;        &lt;/span&gt;&lt;span class=&quot;nt&quot;&gt;&amp;quot;top_logprobs&amp;quot;&lt;/span&gt;&lt;span class=&quot;p&quot;&gt;:&lt;/span&gt;&lt;span class=&quot;w&quot;&gt; &lt;/span&gt;&lt;span class=&quot;mi&quot;&gt;3&lt;/span&gt;\n",
-       "&lt;span class=&quot;w&quot;&gt;    &lt;/span&gt;&lt;span class=&quot;p&quot;&gt;}&lt;/span&gt;\n",
-       "&lt;span class=&quot;p&quot;&gt;}&lt;/span&gt;\n",
-       "&lt;/pre&gt;&lt;/div&gt;\n",
-       "\n",
-       "                    &lt;/div&gt;\n",
-       "                            \n",
-       "                    &lt;h2&gt;Exception details&lt;/h2&gt;\n",
-       "\n",
-       "                    \n",
-       "                        &lt;div class=&quot;exception-detail&quot;&gt;\n",
-       "                            &lt;div class=&quot;exception-exception&quot;&gt;Exception: QuestionAnswerValidationError(&quot;Answer key &#x27;answer&#x27; must be of type list;\\n                (got None) which is of type &lt;class &#x27;NoneType&#x27;&gt;.&quot;)&lt;/div&gt;\n",
-       "                            &lt;div class=&quot;exception-time&quot;&gt;Time: 1722126893.801692&lt;/div&gt;\n",
-       "                            &lt;div class=&quot;exception-traceback&quot;&gt;Traceback: &lt;pre&gt;Traceback (most recent call last):\n",
-       "  File &quot;/Users/a16174/edsl/edsl/jobs/interviews/InterviewTaskBuildingMixin.py&quot;, line 213, in _attempt_to_answer_question\n",
-       "    return await asyncio.wait_for(\n",
-       "           ^^^^^^^^^^^^^^^^^^^^^^^\n",
-       "  File &quot;/Users/a16174/.pyenv/versions/3.11.7/lib/python3.11/asyncio/tasks.py&quot;, line 489, in wait_for\n",
-       "    return fut.result()\n",
-       "           ^^^^^^^^^^^^\n",
-       "  File &quot;/Users/a16174/.pyenv/versions/3.11.7/lib/python3.11/asyncio/futures.py&quot;, line 203, in result\n",
-       "    raise self._exception.with_traceback(self._exception_tb)\n",
-       "  File &quot;/Users/a16174/.pyenv/versions/3.11.7/lib/python3.11/asyncio/tasks.py&quot;, line 277, in __step\n",
-       "    result = coro.send(None)\n",
-       "             ^^^^^^^^^^^^^^^\n",
-       "  File &quot;/Users/a16174/edsl/edsl/agents/Invigilator.py&quot;, line 31, in async_answer_question\n",
-       "    response = self._format_raw_response(**data)\n",
-       "               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-       "  File &quot;/Users/a16174/edsl/edsl/agents/Invigilator.py&quot;, line 83, in _format_raw_response\n",
-       "    raise e\n",
-       "  File &quot;/Users/a16174/edsl/edsl/agents/Invigilator.py&quot;, line 79, in _format_raw_response\n",
-       "    response = question._validate_answer(raw_response)\n",
-       "               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-       "  File &quot;/Users/a16174/edsl/edsl/questions/QuestionList.py&quot;, line 38, in _validate_answer\n",
-       "    self._validate_answer_key_value(answer, &quot;answer&quot;, list)\n",
-       "  File &quot;/Users/a16174/edsl/edsl/questions/AnswerValidatorMixin.py&quot;, line 51, in _validate_answer_key_value\n",
-       "    raise QuestionAnswerValidationError(\n",
-       "edsl.exceptions.questions.QuestionAnswerValidationError: Answer key &#x27;answer&#x27; must be of type list;\n",
-       "                (got None) which is of type &lt;class &#x27;NoneType&#x27;&gt;.\n",
-       " &lt;/pre&gt;&lt;/div&gt;\n",
-       "                        &lt;/div&gt;\n",
-       "                    \n",
-       "                        &lt;div class=&quot;exception-detail&quot;&gt;\n",
-       "                            &lt;div class=&quot;exception-exception&quot;&gt;Exception: QuestionAnswerValidationError(&quot;Answer key &#x27;answer&#x27; must be of type list;\\n                (got null) which is of type &lt;class &#x27;str&#x27;&gt;.&quot;)&lt;/div&gt;\n",
-       "                            &lt;div class=&quot;exception-time&quot;&gt;Time: 1722126904.847809&lt;/div&gt;\n",
-       "                            &lt;div class=&quot;exception-traceback&quot;&gt;Traceback: &lt;pre&gt;Traceback (most recent call last):\n",
-       "  File &quot;/Users/a16174/edsl/edsl/jobs/interviews/InterviewTaskBuildingMixin.py&quot;, line 213, in _attempt_to_answer_question\n",
-       "    return await asyncio.wait_for(\n",
-       "           ^^^^^^^^^^^^^^^^^^^^^^^\n",
-       "  File &quot;/Users/a16174/.pyenv/versions/3.11.7/lib/python3.11/asyncio/tasks.py&quot;, line 489, in wait_for\n",
-       "    return fut.result()\n",
-       "           ^^^^^^^^^^^^\n",
-       "  File &quot;/Users/a16174/.pyenv/versions/3.11.7/lib/python3.11/asyncio/futures.py&quot;, line 203, in result\n",
-       "    raise self._exception.with_traceback(self._exception_tb)\n",
-       "  File &quot;/Users/a16174/.pyenv/versions/3.11.7/lib/python3.11/asyncio/tasks.py&quot;, line 277, in __step\n",
-       "    result = coro.send(None)\n",
-       "             ^^^^^^^^^^^^^^^\n",
-       "  File &quot;/Users/a16174/edsl/edsl/agents/Invigilator.py&quot;, line 31, in async_answer_question\n",
-       "    response = self._format_raw_response(**data)\n",
-       "               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-       "  File &quot;/Users/a16174/edsl/edsl/agents/Invigilator.py&quot;, line 83, in _format_raw_response\n",
-       "    raise e\n",
-       "  File &quot;/Users/a16174/edsl/edsl/agents/Invigilator.py&quot;, line 79, in _format_raw_response\n",
-       "    response = question._validate_answer(raw_response)\n",
-       "               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
-       "  File &quot;/Users/a16174/edsl/edsl/questions/QuestionList.py&quot;, line 38, in _validate_answer\n",
-       "    self._validate_answer_key_value(answer, &quot;answer&quot;, list)\n",
-       "  File &quot;/Users/a16174/edsl/edsl/questions/AnswerValidatorMixin.py&quot;, line 51, in _validate_answer_key_value\n",
-       "    raise QuestionAnswerValidationError(\n",
-       "edsl.exceptions.questions.QuestionAnswerValidationError: Answer key &#x27;answer&#x27; must be of type list;\n",
-       "                (got null) which is of type &lt;class &#x27;str&#x27;&gt;.\n",
-       " &lt;/pre&gt;&lt;/div&gt;\n",
-       "                        &lt;/div&gt;\n",
-       "                                \n",
-       "                            \n",
-       "            \n",
-       "                            \n",
-       "        &lt;h1&gt;Performance Plot&lt;/h1&gt;\n",
-       "        &lt;img 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&quot; alt=&quot;Plot&quot;&gt;\n",
-       "        &lt;/body&gt;\n",
-       "        &lt;/html&gt;\n",
-       "        \" style=\"width: 800px; height: 600px;\"></iframe>\n",
-       "            "
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Also see: https://docs.expectedparrot.com/en/latest/exceptions.html\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from edsl import Survey\n",
     "\n",
@@ -505,25 +165,16 @@
        "┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> model                  </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> answer                                                                                 </span>┃\n",
        "┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> .model                 </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> .content                                                                               </span>┃\n",
        "┡━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-3.5-turbo          </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research question', 'Collect and prepare data', 'Fine-tune the language       </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> model', 'Analyze results', 'Iterate and refine']                                       </span>│\n",
-       "├────────────────────────┼────────────────────────────────────────────────────────────────────────────────────────┤\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gemini-pro             </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research goals and objectives', 'Select an appropriate LLM and dataset',      </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Design and implement research methodology', 'Collect and analyze data', 'Interpret    </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> results and draw conclusions']                                                         </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-4o                 </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research objectives', 'Select the appropriate model', 'Prepare and preprocess </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> data', 'Design experiments', 'Evaluate model performance', 'Analyze results',          </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Document findings', 'Ensure ethical considerations']                                  </span>│\n",
        "├────────────────────────┼────────────────────────────────────────────────────────────────────────────────────────┤\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-4-1106-preview     </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research objectives', 'Choose a suitable large language model', 'Determine    </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> the scope of research', 'Develop a set of hypotheses or research questions', 'Design   </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> the research methodology', 'Collect data', 'Preprocess and clean the data', 'Fine-tune </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> the language model if necessary', 'Run experiments or simulations', 'Analyze the       </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> results', 'Interpret the findings', 'Consider the ethical implications', 'Document the </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> research process', 'Write the research paper or report', 'Peer review and validate     </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> findings', 'Publish or share the research outcomes']                                   </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gemini-pro             </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research objectives', 'Gather and prepare data', 'Select and train model',    </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Evaluate model performance', 'Interpret and communicate results']                     </span>│\n",
        "├────────────────────────┼────────────────────────────────────────────────────────────────────────────────────────┤\n",
        "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> claude-3-opus-20240229 </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research questions and hypotheses', 'Select appropriate language model(s)',   </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Collect high-quality training data', 'Fine-tune model on domain-specific data',       </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Develop evaluation metrics', 'Test model performance', 'Analyze results', 'Document   </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> methodology', 'Share findings']                                                        </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Collect and preprocess data', 'Fine-tune and evaluate models', 'Analyze results and   </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> draw conclusions', 'Document methodology and findings']                                </span>│\n",
        "└────────────────────────┴────────────────────────────────────────────────────────────────────────────────────────┘\n",
        "</pre>\n"
       ],
@@ -532,25 +183,16 @@
        "┃\u001b[1;35m \u001b[0m\u001b[1;35mmodel                 \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35manswer                                                                                \u001b[0m\u001b[1;35m \u001b[0m┃\n",
        "┃\u001b[1;35m \u001b[0m\u001b[1;35m.model                \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35m.content                                                                              \u001b[0m\u001b[1;35m \u001b[0m┃\n",
        "┡━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
-       "│\u001b[2m \u001b[0m\u001b[2mgpt-3.5-turbo         \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research question', 'Collect and prepare data', 'Fine-tune the language      \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mmodel', 'Analyze results', 'Iterate and refine']                                      \u001b[0m\u001b[2m \u001b[0m│\n",
-       "├────────────────────────┼────────────────────────────────────────────────────────────────────────────────────────┤\n",
-       "│\u001b[2m \u001b[0m\u001b[2mgemini-pro            \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research goals and objectives', 'Select an appropriate LLM and dataset',     \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Design and implement research methodology', 'Collect and analyze data', 'Interpret   \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mresults and draw conclusions']                                                        \u001b[0m\u001b[2m \u001b[0m│\n",
+       "│\u001b[2m \u001b[0m\u001b[2mgpt-4o                \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research objectives', 'Select the appropriate model', 'Prepare and preprocess\u001b[0m\u001b[2m \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mdata', 'Design experiments', 'Evaluate model performance', 'Analyze results',         \u001b[0m\u001b[2m \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Document findings', 'Ensure ethical considerations']                                 \u001b[0m\u001b[2m \u001b[0m│\n",
        "├────────────────────────┼────────────────────────────────────────────────────────────────────────────────────────┤\n",
-       "│\u001b[2m \u001b[0m\u001b[2mgpt-4-1106-preview    \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research objectives', 'Choose a suitable large language model', 'Determine   \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mthe scope of research', 'Develop a set of hypotheses or research questions', 'Design  \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mthe research methodology', 'Collect data', 'Preprocess and clean the data', 'Fine-tune\u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mthe language model if necessary', 'Run experiments or simulations', 'Analyze the      \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mresults', 'Interpret the findings', 'Consider the ethical implications', 'Document the\u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mresearch process', 'Write the research paper or report', 'Peer review and validate    \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mfindings', 'Publish or share the research outcomes']                                  \u001b[0m\u001b[2m \u001b[0m│\n",
+       "│\u001b[2m \u001b[0m\u001b[2mgemini-pro            \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research objectives', 'Gather and prepare data', 'Select and train model',   \u001b[0m\u001b[2m \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Evaluate model performance', 'Interpret and communicate results']                    \u001b[0m\u001b[2m \u001b[0m│\n",
        "├────────────────────────┼────────────────────────────────────────────────────────────────────────────────────────┤\n",
        "│\u001b[2m \u001b[0m\u001b[2mclaude-3-opus-20240229\u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research questions and hypotheses', 'Select appropriate language model(s)',  \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Collect high-quality training data', 'Fine-tune model on domain-specific data',      \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Develop evaluation metrics', 'Test model performance', 'Analyze results', 'Document  \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mmethodology', 'Share findings']                                                       \u001b[0m\u001b[2m \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Collect and preprocess data', 'Fine-tune and evaluate models', 'Analyze results and  \u001b[0m\u001b[2m \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mdraw conclusions', 'Document methodology and findings']                               \u001b[0m\u001b[2m \u001b[0m│\n",
        "└────────────────────────┴────────────────────────────────────────────────────────────────────────────────────────┘\n"
       ]
      },
@@ -581,6 +223,7 @@
        " 'agent.agent_name',\n",
        " 'answer.content',\n",
        " 'comment.content_comment',\n",
+       " 'generated_tokens.content_generated_tokens',\n",
        " 'iteration.iteration',\n",
        " 'model.frequency_penalty',\n",
        " 'model.logprobs',\n",
@@ -599,6 +242,8 @@
        " 'question_options.content_question_options',\n",
        " 'question_text.content_question_text',\n",
        " 'question_type.content_question_type',\n",
+       " 'raw_model_response.content_cost',\n",
+       " 'raw_model_response.content_one_usd_buys',\n",
        " 'raw_model_response.content_raw_model_response']"
       ]
      },
@@ -616,239 +261,21 @@
    "metadata": {},
    "source": [
     "## Accessing results\n",
-    "EDSL comes with a variety of built-in methods for working with results. [See details on methods](https://docs.expectedparrot.com/en/latest/results.html). For example, we can turn the results into a dataframe:"
+    "EDSL comes with a variety of built-in methods for working with results. [See details on methods](https://docs.expectedparrot.com/en/latest/results.html). \n",
+    "Here we extract components of the results that we'll use to conduct our by-model review of the content.\n",
+    "We create a `Scenario` object for each piece of content that we will add to a new question prompting a model to score it (a generalizable data labeling task). \n",
+    "We also track the model that drafted the content:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 8,
    "metadata": {},
-   "outputs": [
-    {
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-       "                                   agent_instruction agent_name  \\\n",
-       "0  You are answering questions as if you were a h...    Agent_3   \n",
-       "1  You are answering questions as if you were a h...    Agent_3   \n",
-       "2  You are answering questions as if you were a h...    Agent_3   \n",
-       "3  You are answering questions as if you were a h...    Agent_3   \n",
-       "\n",
-       "                                             content  \\\n",
-       "0  ['Define research question', 'Collect and prep...   \n",
-       "1  ['Define research goals and objectives', 'Sele...   \n",
-       "2  ['Define research objectives', 'Choose a suita...   \n",
-       "3  ['Define research questions and hypotheses', '...   \n",
-       "\n",
-       "                                     content_comment  \\\n",
-       "0  These steps are essential for conducting resea...   \n",
-       "1  These steps provide a general framework for co...   \n",
-       "2  This is a generalized list of steps for conduc...   \n",
-       "3  Conducting research with large language models...   \n",
-       "\n",
-       "   content_question_options  \\\n",
-       "0                       NaN   \n",
-       "1                       NaN   \n",
-       "2                       NaN   \n",
-       "3                       NaN   \n",
-       "\n",
-       "                               content_question_text content_question_type  \\\n",
-       "0  What are recommended steps for conducting rese...                  list   \n",
-       "1  What are recommended steps for conducting rese...                  list   \n",
-       "2  What are recommended steps for conducting rese...                  list   \n",
-       "3  What are recommended steps for conducting rese...                  list   \n",
-       "\n",
-       "                          content_raw_model_response  \\\n",
-       "0  {'id': 'chatcmpl-9pm9wjtFRxYSmxOccXg6HkGPn7M7D...   \n",
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-       "3  {'id': 'msg_01EWQkoSo1oj5qQV7fCz8qot', 'conten...   \n",
-       "\n",
-       "                               content_system_prompt  \\\n",
-       "0  You are answering questions as if you were a h...   \n",
-       "1  You are answering questions as if you were a h...   \n",
-       "2  You are answering questions as if you were a h...   \n",
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-       "\n",
-       "                                 content_user_prompt  ...  maxOutputTokens  \\\n",
-       "0  What are recommended steps for conducting rese...  ...              NaN   \n",
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-       "2  What are recommended steps for conducting rese...  ...              NaN   \n",
-       "3  What are recommended steps for conducting rese...  ...              NaN   \n",
-       "\n",
-       "   max_tokens                   model  presence_penalty  stopSequences  \\\n",
-       "0      1000.0           gpt-3.5-turbo               0.0            NaN   \n",
-       "1         NaN              gemini-pro               NaN             []   \n",
-       "2      1000.0      gpt-4-1106-preview               0.0            NaN   \n",
-       "3      1000.0  claude-3-opus-20240229               0.0            NaN   \n",
-       "\n",
-       "  temperature  topK topP  top_logprobs  top_p  \n",
-       "0         0.5   NaN  NaN           3.0    1.0  \n",
-       "1         0.5   1.0  1.0           NaN    NaN  \n",
-       "2         0.5   NaN  NaN           3.0    1.0  \n",
-       "3         0.5   NaN  NaN           3.0    1.0  \n",
-       "\n",
-       "[4 rows x 23 columns]"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df = results.to_pandas(remove_prefix=True)  # We can drop the column prefixes if we want\n",
-    "df"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
+   "outputs": [],
    "source": [
-    "Here we extract components of the results that we'll use to conduct our by-model review of the content:"
+    "from edsl import ScenarioList\n",
+    "\n",
+    "scenarios = results.select(\"model\", \"content\").to_scenario_list().rename({\"model\":\"drafting_model\"})"
    ]
   },
   {
@@ -858,11 +285,49 @@
    "outputs": [
     {
      "data": {
+      "text/html": [
+       "<div class=\"highlight\"><pre><span></span><span class=\"p\">{</span>\n",
+       "<span class=\"w\">    </span><span class=\"nt\">&quot;scenarios&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p\">[</span>\n",
+       "<span class=\"w\">        </span><span class=\"p\">{</span>\n",
+       "<span class=\"w\">            </span><span class=\"nt\">&quot;drafting_model&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s2\">&quot;gpt-4o&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">            </span><span class=\"nt\">&quot;content&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p\">[</span>\n",
+       "<span class=\"w\">                </span><span class=\"s2\">&quot;Define research objectives&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">                </span><span class=\"s2\">&quot;Select the appropriate model&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">                </span><span class=\"s2\">&quot;Prepare and preprocess data&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">                </span><span class=\"s2\">&quot;Design experiments&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">                </span><span class=\"s2\">&quot;Evaluate model performance&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">                </span><span class=\"s2\">&quot;Analyze results&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">                </span><span class=\"s2\">&quot;Document findings&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">                </span><span class=\"s2\">&quot;Ensure ethical considerations&quot;</span>\n",
+       "<span class=\"w\">            </span><span class=\"p\">]</span>\n",
+       "<span class=\"w\">        </span><span class=\"p\">},</span>\n",
+       "<span class=\"w\">        </span><span class=\"p\">{</span>\n",
+       "<span class=\"w\">            </span><span class=\"nt\">&quot;drafting_model&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s2\">&quot;gemini-pro&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">            </span><span class=\"nt\">&quot;content&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p\">[</span>\n",
+       "<span class=\"w\">                </span><span class=\"s2\">&quot;Define research objectives&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">                </span><span class=\"s2\">&quot;Gather and prepare data&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">                </span><span class=\"s2\">&quot;Select and train model&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">                </span><span class=\"s2\">&quot;Evaluate model performance&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">                </span><span class=\"s2\">&quot;Interpret and communicate results&quot;</span>\n",
+       "<span class=\"w\">            </span><span class=\"p\">]</span>\n",
+       "<span class=\"w\">        </span><span class=\"p\">},</span>\n",
+       "<span class=\"w\">        </span><span class=\"p\">{</span>\n",
+       "<span class=\"w\">            </span><span class=\"nt\">&quot;drafting_model&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s2\">&quot;claude-3-opus-20240229&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">            </span><span class=\"nt\">&quot;content&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p\">[</span>\n",
+       "<span class=\"w\">                </span><span class=\"s2\">&quot;Define research questions and hypotheses&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">                </span><span class=\"s2\">&quot;Select appropriate language model(s)&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">                </span><span class=\"s2\">&quot;Collect and preprocess data&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">                </span><span class=\"s2\">&quot;Fine-tune and evaluate models&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">                </span><span class=\"s2\">&quot;Analyze results and draw conclusions&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">                </span><span class=\"s2\">&quot;Document methodology and findings&quot;</span>\n",
+       "<span class=\"w\">            </span><span class=\"p\">]</span>\n",
+       "<span class=\"w\">        </span><span class=\"p\">}</span>\n",
+       "<span class=\"w\">    </span><span class=\"p\">]</span>\n",
+       "<span class=\"p\">}</span>\n",
+       "</pre></div>\n"
+      ],
       "text/plain": [
-       "{'gpt-3.5-turbo': \"['Define research question', 'Collect and prepare data', 'Fine-tune the language model', 'Analyze results', 'Iterate and refine']\",\n",
-       " 'gemini-pro': \"['Define research goals and objectives', 'Select an appropriate LLM and dataset', 'Design and implement research methodology', 'Collect and analyze data', 'Interpret results and draw conclusions']\",\n",
-       " 'gpt-4-1106-preview': \"['Define research objectives', 'Choose a suitable large language model', 'Determine the scope of research', 'Develop a set of hypotheses or research questions', 'Design the research methodology', 'Collect data', 'Preprocess and clean the data', 'Fine-tune the language model if necessary', 'Run experiments or simulations', 'Analyze the results', 'Interpret the findings', 'Consider the ethical implications', 'Document the research process', 'Write the research paper or report', 'Peer review and validate findings', 'Publish or share the research outcomes']\",\n",
-       " 'claude-3-opus-20240229': \"['Define research questions and hypotheses', 'Select appropriate language model(s)', 'Collect high-quality training data', 'Fine-tune model on domain-specific data', 'Develop evaluation metrics', 'Test model performance', 'Analyze results', 'Document methodology', 'Share findings']\"}"
+       "ScenarioList([Scenario({'drafting_model': 'gpt-4o', 'content': ['Define research objectives', 'Select the appropriate model', 'Prepare and preprocess data', 'Design experiments', 'Evaluate model performance', 'Analyze results', 'Document findings', 'Ensure ethical considerations']}), Scenario({'drafting_model': 'gemini-pro', 'content': ['Define research objectives', 'Gather and prepare data', 'Select and train model', 'Evaluate model performance', 'Interpret and communicate results']}), Scenario({'drafting_model': 'claude-3-opus-20240229', 'content': ['Define research questions and hypotheses', 'Select appropriate language model(s)', 'Collect and preprocess data', 'Fine-tune and evaluate models', 'Analyze results and draw conclusions', 'Document methodology and findings']})])"
       ]
      },
      "execution_count": 9,
@@ -871,19 +336,14 @@
     }
    ],
    "source": [
-    "content_dict = dict(zip(df[\"model\"], df[\"content\"]))\n",
-    "content_dict"
+    "scenarios"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "cell_id": "09c51c4a264248d3a6ca865d70844279",
-    "deepnote_cell_type": "markdown"
-   },
+   "metadata": {},
    "source": [
-    "## Conducting a review\n",
-    "Next we create a new question (in another appropriate question type) to have the models evaluate each piece of content that was generated. We do this by parameterizing a question with different \"scenarios\" of the content to be evaluated:"
+    "Next we construct the scoring question to take parameters for the `content` and `drafting_model`:"
    ]
   },
   {
@@ -892,77 +352,22 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from edsl.questions import QuestionLinearScale\n",
+    "from edsl import QuestionLinearScale\n",
     "\n",
     "q_score = QuestionLinearScale(\n",
-    "    question_name=\"score\",\n",
-    "    question_text=\"\"\"Consider the following response to the question\n",
+    "    question_name = \"score\",\n",
+    "    question_text = \"\"\"Consider the following response to the question\n",
     "    'What are recommended steps for conducting research with large language models?'\n",
     "    Response: {{ content }}\n",
     "    Score this response in terms of accuracy and completeness.\n",
     "    (Drafting model: {{ drafting_model }})\"\"\",\n",
-    "    question_options=[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10],\n",
-    "    option_labels={0: \"Terrible\", 10: \"Amazing\"},\n",
+    "    question_options = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10],\n",
+    "    option_labels = {0: \"Terrible\", 10: \"Amazing\"},\n",
     ")\n",
     "\n",
     "survey = Survey([q_score])"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We create a `Scenario` object for each piece of content that we will add to the question when we run it (a generalizable data labeling task). We also track the model that drafted the content for analysis of the results:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div class=\"highlight\"><pre><span></span><span class=\"p\">{</span>\n",
-       "<span class=\"w\">    </span><span class=\"nt\">&quot;scenarios&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p\">[</span>\n",
-       "<span class=\"w\">        </span><span class=\"p\">{</span>\n",
-       "<span class=\"w\">            </span><span class=\"nt\">&quot;drafting_model&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s2\">&quot;gpt-3.5-turbo&quot;</span><span class=\"p\">,</span>\n",
-       "<span class=\"w\">            </span><span class=\"nt\">&quot;content&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s2\">&quot;[&#39;Define research question&#39;, &#39;Collect and prepare data&#39;, &#39;Fine-tune the language model&#39;, &#39;Analyze results&#39;, &#39;Iterate and refine&#39;]&quot;</span>\n",
-       "<span class=\"w\">        </span><span class=\"p\">},</span>\n",
-       "<span class=\"w\">        </span><span class=\"p\">{</span>\n",
-       "<span class=\"w\">            </span><span class=\"nt\">&quot;drafting_model&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s2\">&quot;gemini-pro&quot;</span><span class=\"p\">,</span>\n",
-       "<span class=\"w\">            </span><span class=\"nt\">&quot;content&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s2\">&quot;[&#39;Define research goals and objectives&#39;, &#39;Select an appropriate LLM and dataset&#39;, &#39;Design and implement research methodology&#39;, &#39;Collect and analyze data&#39;, &#39;Interpret results and draw conclusions&#39;]&quot;</span>\n",
-       "<span class=\"w\">        </span><span class=\"p\">},</span>\n",
-       "<span class=\"w\">        </span><span class=\"p\">{</span>\n",
-       "<span class=\"w\">            </span><span class=\"nt\">&quot;drafting_model&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s2\">&quot;gpt-4-1106-preview&quot;</span><span class=\"p\">,</span>\n",
-       "<span class=\"w\">            </span><span class=\"nt\">&quot;content&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s2\">&quot;[&#39;Define research objectives&#39;, &#39;Choose a suitable large language model&#39;, &#39;Determine the scope of research&#39;, &#39;Develop a set of hypotheses or research questions&#39;, &#39;Design the research methodology&#39;, &#39;Collect data&#39;, &#39;Preprocess and clean the data&#39;, &#39;Fine-tune the language model if necessary&#39;, &#39;Run experiments or simulations&#39;, &#39;Analyze the results&#39;, &#39;Interpret the findings&#39;, &#39;Consider the ethical implications&#39;, &#39;Document the research process&#39;, &#39;Write the research paper or report&#39;, &#39;Peer review and validate findings&#39;, &#39;Publish or share the research outcomes&#39;]&quot;</span>\n",
-       "<span class=\"w\">        </span><span class=\"p\">},</span>\n",
-       "<span class=\"w\">        </span><span class=\"p\">{</span>\n",
-       "<span class=\"w\">            </span><span class=\"nt\">&quot;drafting_model&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s2\">&quot;claude-3-opus-20240229&quot;</span><span class=\"p\">,</span>\n",
-       "<span class=\"w\">            </span><span class=\"nt\">&quot;content&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s2\">&quot;[&#39;Define research questions and hypotheses&#39;, &#39;Select appropriate language model(s)&#39;, &#39;Collect high-quality training data&#39;, &#39;Fine-tune model on domain-specific data&#39;, &#39;Develop evaluation metrics&#39;, &#39;Test model performance&#39;, &#39;Analyze results&#39;, &#39;Document methodology&#39;, &#39;Share findings&#39;]&quot;</span>\n",
-       "<span class=\"w\">        </span><span class=\"p\">}</span>\n",
-       "<span class=\"w\">    </span><span class=\"p\">]</span>\n",
-       "<span class=\"p\">}</span>\n",
-       "</pre></div>\n"
-      ],
-      "text/plain": [
-       "ScenarioList([Scenario({'drafting_model': 'gpt-3.5-turbo', 'content': \"['Define research question', 'Collect and prepare data', 'Fine-tune the language model', 'Analyze results', 'Iterate and refine']\"}), Scenario({'drafting_model': 'gemini-pro', 'content': \"['Define research goals and objectives', 'Select an appropriate LLM and dataset', 'Design and implement research methodology', 'Collect and analyze data', 'Interpret results and draw conclusions']\"}), Scenario({'drafting_model': 'gpt-4-1106-preview', 'content': \"['Define research objectives', 'Choose a suitable large language model', 'Determine the scope of research', 'Develop a set of hypotheses or research questions', 'Design the research methodology', 'Collect data', 'Preprocess and clean the data', 'Fine-tune the language model if necessary', 'Run experiments or simulations', 'Analyze the results', 'Interpret the findings', 'Consider the ethical implications', 'Document the research process', 'Write the research paper or report', 'Peer review and validate findings', 'Publish or share the research outcomes']\"}), Scenario({'drafting_model': 'claude-3-opus-20240229', 'content': \"['Define research questions and hypotheses', 'Select appropriate language model(s)', 'Collect high-quality training data', 'Fine-tune model on domain-specific data', 'Develop evaluation metrics', 'Test model performance', 'Analyze results', 'Document methodology', 'Share findings']\"})])"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "from edsl import ScenarioList, Scenario\n",
-    "\n",
-    "scenarios = ScenarioList(\n",
-    "    Scenario({\"drafting_model\": m, \"content\": c}) for m, c in content_dict.items()\n",
-    ")\n",
-    "scenarios"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -972,7 +377,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -988,255 +393,129 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┓\n",
-       "┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> model                  </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> scenario               </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> scenario                                             </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> answer </span>┃\n",
-       "┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> .model                 </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> .drafting_model        </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> .content                                             </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> .score </span>┃\n",
-       "┡━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━┩\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> claude-3-opus-20240229 </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> claude-3-opus-20240229 </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research questions and hypotheses', 'Select </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 9      </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> appropriate language model(s)', 'Collect             </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> high-quality training data', 'Fine-tune model on     </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> domain-specific data', 'Develop evaluation metrics', </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Test model performance', 'Analyze results',         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Document methodology', 'Share findings']            </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> claude-3-opus-20240229 </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gemini-pro             </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research goals and objectives', 'Select an  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 8      </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> appropriate LLM and dataset', 'Design and implement  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> research methodology', 'Collect and analyze data',   </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Interpret results and draw conclusions']            </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> claude-3-opus-20240229 </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-3.5-turbo          </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research question', 'Collect and prepare    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 8      </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> data', 'Fine-tune the language model', 'Analyze      </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> results', 'Iterate and refine']                      </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> claude-3-opus-20240229 </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-4-1106-preview     </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research objectives', 'Choose a suitable    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 9      </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> large language model', 'Determine the scope of       </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> research', 'Develop a set of hypotheses or research  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> questions', 'Design the research methodology',       </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Collect data', 'Preprocess and clean the data',     </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Fine-tune the language model if necessary', 'Run    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> experiments or simulations', 'Analyze the results',  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Interpret the findings', 'Consider the ethical      </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> implications', 'Document the research process',      </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Write the research paper or report', 'Peer review   </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> and validate findings', 'Publish or share the        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> research outcomes']                                  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gemini-pro             </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> claude-3-opus-20240229 </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research questions and hypotheses', 'Select </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 9      </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> appropriate language model(s)', 'Collect             </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> high-quality training data', 'Fine-tune model on     </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> domain-specific data', 'Develop evaluation metrics', </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Test model performance', 'Analyze results',         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Document methodology', 'Share findings']            </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gemini-pro             </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gemini-pro             </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research goals and objectives', 'Select an  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 2      </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> appropriate LLM and dataset', 'Design and implement  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> research methodology', 'Collect and analyze data',   </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Interpret results and draw conclusions']            </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gemini-pro             </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-3.5-turbo          </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research question', 'Collect and prepare    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 4      </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> data', 'Fine-tune the language model', 'Analyze      </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> results', 'Iterate and refine']                      </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gemini-pro             </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-4-1106-preview     </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research objectives', 'Choose a suitable    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 10     </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> large language model', 'Determine the scope of       </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> research', 'Develop a set of hypotheses or research  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> questions', 'Design the research methodology',       </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Collect data', 'Preprocess and clean the data',     </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Fine-tune the language model if necessary', 'Run    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> experiments or simulations', 'Analyze the results',  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Interpret the findings', 'Consider the ethical      </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> implications', 'Document the research process',      </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Write the research paper or report', 'Peer review   </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> and validate findings', 'Publish or share the        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> research outcomes']                                  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-3.5-turbo          </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> claude-3-opus-20240229 </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research questions and hypotheses', 'Select </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 8      </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> appropriate language model(s)', 'Collect             </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> high-quality training data', 'Fine-tune model on     </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> domain-specific data', 'Develop evaluation metrics', </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Test model performance', 'Analyze results',         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Document methodology', 'Share findings']            </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-3.5-turbo          </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gemini-pro             </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research goals and objectives', 'Select an  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 8      </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> appropriate LLM and dataset', 'Design and implement  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> research methodology', 'Collect and analyze data',   </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Interpret results and draw conclusions']            </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-3.5-turbo          </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-3.5-turbo          </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research question', 'Collect and prepare    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 8      </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> data', 'Fine-tune the language model', 'Analyze      </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> results', 'Iterate and refine']                      </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-3.5-turbo          </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-4-1106-preview     </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research objectives', 'Choose a suitable    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 9      </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> large language model', 'Determine the scope of       </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> research', 'Develop a set of hypotheses or research  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> questions', 'Design the research methodology',       </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Collect data', 'Preprocess and clean the data',     </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Fine-tune the language model if necessary', 'Run    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> experiments or simulations', 'Analyze the results',  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Interpret the findings', 'Consider the ethical      </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> implications', 'Document the research process',      </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Write the research paper or report', 'Peer review   </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> and validate findings', 'Publish or share the        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> research outcomes']                                  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-4-1106-preview     </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> claude-3-opus-20240229 </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research questions and hypotheses', 'Select </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 8      </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> appropriate language model(s)', 'Collect             </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> high-quality training data', 'Fine-tune model on     </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> domain-specific data', 'Develop evaluation metrics', </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Test model performance', 'Analyze results',         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Document methodology', 'Share findings']            </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-4-1106-preview     </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gemini-pro             </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research goals and objectives', 'Select an  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 8      </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> appropriate LLM and dataset', 'Design and implement  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> research methodology', 'Collect and analyze data',   </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Interpret results and draw conclusions']            </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-4-1106-preview     </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-3.5-turbo          </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research question', 'Collect and prepare    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 7      </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> data', 'Fine-tune the language model', 'Analyze      </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> results', 'Iterate and refine']                      </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-4-1106-preview     </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-4-1106-preview     </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research objectives', 'Choose a suitable    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 9      </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> large language model', 'Determine the scope of       </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> research', 'Develop a set of hypotheses or research  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> questions', 'Design the research methodology',       </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Collect data', 'Preprocess and clean the data',     </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Fine-tune the language model if necessary', 'Run    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> experiments or simulations', 'Analyze the results',  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Interpret the findings', 'Consider the ethical      </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> implications', 'Document the research process',      </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Write the research paper or report', 'Peer review   </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> and validate findings', 'Publish or share the        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> research outcomes']                                  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">        </span>│\n",
-       "└────────────────────────┴────────────────────────┴──────────────────────────────────────────────────────┴────────┘\n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┓\n",
+       "┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> model.model            </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> scenario.drafting_model </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> scenario.content                              </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> answer.score </span>┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━┩\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> claude-3-opus-20240229 </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> claude-3-opus-20240229  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research questions and hypotheses',  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 8            </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Select appropriate language model(s)',       </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Collect and preprocess data', 'Fine-tune and </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> evaluate models', 'Analyze results and draw   </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> conclusions', 'Document methodology and       </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> findings']                                    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "├────────────────────────┼─────────────────────────┼───────────────────────────────────────────────┼──────────────┤\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> claude-3-opus-20240229 </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gemini-pro              </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research objectives', 'Gather and    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 8            </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> prepare data', 'Select and train model',      </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Evaluate model performance', 'Interpret and  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> communicate results']                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "├────────────────────────┼─────────────────────────┼───────────────────────────────────────────────┼──────────────┤\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> claude-3-opus-20240229 </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-4o                  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research objectives', 'Select the    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 8            </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> appropriate model', 'Prepare and preprocess   </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> data', 'Design experiments', 'Evaluate model  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> performance', 'Analyze results', 'Document    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> findings', 'Ensure ethical considerations']   </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "├────────────────────────┼─────────────────────────┼───────────────────────────────────────────────┼──────────────┤\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gemini-pro             </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> claude-3-opus-20240229  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research questions and hypotheses',  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 9            </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Select appropriate language model(s)',       </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Collect and preprocess data', 'Fine-tune and </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> evaluate models', 'Analyze results and draw   </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> conclusions', 'Document methodology and       </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> findings']                                    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "├────────────────────────┼─────────────────────────┼───────────────────────────────────────────────┼──────────────┤\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gemini-pro             </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gemini-pro              </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research objectives', 'Gather and    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 8            </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> prepare data', 'Select and train model',      </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Evaluate model performance', 'Interpret and  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> communicate results']                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "├────────────────────────┼─────────────────────────┼───────────────────────────────────────────────┼──────────────┤\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gemini-pro             </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-4o                  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research objectives', 'Select the    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 8            </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> appropriate model', 'Prepare and preprocess   </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> data', 'Design experiments', 'Evaluate model  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> performance', 'Analyze results', 'Document    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> findings', 'Ensure ethical considerations']   </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "├────────────────────────┼─────────────────────────┼───────────────────────────────────────────────┼──────────────┤\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-4o                 </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> claude-3-opus-20240229  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research questions and hypotheses',  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 9            </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Select appropriate language model(s)',       </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Collect and preprocess data', 'Fine-tune and </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> evaluate models', 'Analyze results and draw   </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> conclusions', 'Document methodology and       </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> findings']                                    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "├────────────────────────┼─────────────────────────┼───────────────────────────────────────────────┼──────────────┤\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-4o                 </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gemini-pro              </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research objectives', 'Gather and    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 8            </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> prepare data', 'Select and train model',      </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'Evaluate model performance', 'Interpret and  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> communicate results']                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "├────────────────────────┼─────────────────────────┼───────────────────────────────────────────────┼──────────────┤\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-4o                 </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> gpt-4o                  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['Define research objectives', 'Select the    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 8            </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> appropriate model', 'Prepare and preprocess   </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> data', 'Design experiments', 'Evaluate model  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> performance', 'Analyze results', 'Document    </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> findings', 'Ensure ethical considerations']   </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>│\n",
+       "└────────────────────────┴─────────────────────────┴───────────────────────────────────────────────┴──────────────┘\n",
        "</pre>\n"
       ],
       "text/plain": [
-       "┏━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┓\n",
-       "┃\u001b[1;35m \u001b[0m\u001b[1;35mmodel                 \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mscenario              \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mscenario                                            \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35manswer\u001b[0m\u001b[1;35m \u001b[0m┃\n",
-       "┃\u001b[1;35m \u001b[0m\u001b[1;35m.model                \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35m.drafting_model       \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35m.content                                            \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35m.score\u001b[0m\u001b[1;35m \u001b[0m┃\n",
-       "┡━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━┩\n",
-       "│\u001b[2m \u001b[0m\u001b[2mclaude-3-opus-20240229\u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mclaude-3-opus-20240229\u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research questions and hypotheses', 'Select\u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m9     \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mappropriate language model(s)', 'Collect            \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mhigh-quality training data', 'Fine-tune model on    \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mdomain-specific data', 'Develop evaluation metrics',\u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Test model performance', 'Analyze results',        \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Document methodology', 'Share findings']           \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│\u001b[2m \u001b[0m\u001b[2mclaude-3-opus-20240229\u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mgemini-pro            \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research goals and objectives', 'Select an \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m8     \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mappropriate LLM and dataset', 'Design and implement \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mresearch methodology', 'Collect and analyze data',  \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Interpret results and draw conclusions']           \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│\u001b[2m \u001b[0m\u001b[2mclaude-3-opus-20240229\u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mgpt-3.5-turbo         \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research question', 'Collect and prepare   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m8     \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mdata', 'Fine-tune the language model', 'Analyze     \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mresults', 'Iterate and refine']                     \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│\u001b[2m \u001b[0m\u001b[2mclaude-3-opus-20240229\u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mgpt-4-1106-preview    \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research objectives', 'Choose a suitable   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m9     \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mlarge language model', 'Determine the scope of      \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mresearch', 'Develop a set of hypotheses or research \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mquestions', 'Design the research methodology',      \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Collect data', 'Preprocess and clean the data',    \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Fine-tune the language model if necessary', 'Run   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mexperiments or simulations', 'Analyze the results', \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Interpret the findings', 'Consider the ethical     \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mimplications', 'Document the research process',     \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Write the research paper or report', 'Peer review  \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mand validate findings', 'Publish or share the       \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mresearch outcomes']                                 \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│\u001b[2m \u001b[0m\u001b[2mgemini-pro            \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mclaude-3-opus-20240229\u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research questions and hypotheses', 'Select\u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m9     \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mappropriate language model(s)', 'Collect            \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mhigh-quality training data', 'Fine-tune model on    \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mdomain-specific data', 'Develop evaluation metrics',\u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Test model performance', 'Analyze results',        \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Document methodology', 'Share findings']           \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│\u001b[2m \u001b[0m\u001b[2mgemini-pro            \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mgemini-pro            \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research goals and objectives', 'Select an \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m2     \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mappropriate LLM and dataset', 'Design and implement \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mresearch methodology', 'Collect and analyze data',  \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Interpret results and draw conclusions']           \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│\u001b[2m \u001b[0m\u001b[2mgemini-pro            \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mgpt-3.5-turbo         \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research question', 'Collect and prepare   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m4     \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mdata', 'Fine-tune the language model', 'Analyze     \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mresults', 'Iterate and refine']                     \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│\u001b[2m \u001b[0m\u001b[2mgemini-pro            \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mgpt-4-1106-preview    \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research objectives', 'Choose a suitable   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m10    \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mlarge language model', 'Determine the scope of      \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mresearch', 'Develop a set of hypotheses or research \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mquestions', 'Design the research methodology',      \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Collect data', 'Preprocess and clean the data',    \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Fine-tune the language model if necessary', 'Run   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mexperiments or simulations', 'Analyze the results', \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Interpret the findings', 'Consider the ethical     \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mimplications', 'Document the research process',     \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Write the research paper or report', 'Peer review  \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mand validate findings', 'Publish or share the       \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mresearch outcomes']                                 \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│\u001b[2m \u001b[0m\u001b[2mgpt-3.5-turbo         \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mclaude-3-opus-20240229\u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research questions and hypotheses', 'Select\u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m8     \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mappropriate language model(s)', 'Collect            \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mhigh-quality training data', 'Fine-tune model on    \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mdomain-specific data', 'Develop evaluation metrics',\u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Test model performance', 'Analyze results',        \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Document methodology', 'Share findings']           \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│\u001b[2m \u001b[0m\u001b[2mgpt-3.5-turbo         \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mgemini-pro            \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research goals and objectives', 'Select an \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m8     \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mappropriate LLM and dataset', 'Design and implement \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mresearch methodology', 'Collect and analyze data',  \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Interpret results and draw conclusions']           \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│\u001b[2m \u001b[0m\u001b[2mgpt-3.5-turbo         \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mgpt-3.5-turbo         \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research question', 'Collect and prepare   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m8     \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mdata', 'Fine-tune the language model', 'Analyze     \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mresults', 'Iterate and refine']                     \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│\u001b[2m \u001b[0m\u001b[2mgpt-3.5-turbo         \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mgpt-4-1106-preview    \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research objectives', 'Choose a suitable   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m9     \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mlarge language model', 'Determine the scope of      \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mresearch', 'Develop a set of hypotheses or research \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mquestions', 'Design the research methodology',      \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Collect data', 'Preprocess and clean the data',    \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Fine-tune the language model if necessary', 'Run   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mexperiments or simulations', 'Analyze the results', \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Interpret the findings', 'Consider the ethical     \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mimplications', 'Document the research process',     \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Write the research paper or report', 'Peer review  \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mand validate findings', 'Publish or share the       \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mresearch outcomes']                                 \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│\u001b[2m \u001b[0m\u001b[2mgpt-4-1106-preview    \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mclaude-3-opus-20240229\u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research questions and hypotheses', 'Select\u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m8     \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mappropriate language model(s)', 'Collect            \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mhigh-quality training data', 'Fine-tune model on    \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mdomain-specific data', 'Develop evaluation metrics',\u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Test model performance', 'Analyze results',        \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Document methodology', 'Share findings']           \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│\u001b[2m \u001b[0m\u001b[2mgpt-4-1106-preview    \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mgemini-pro            \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research goals and objectives', 'Select an \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m8     \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mappropriate LLM and dataset', 'Design and implement \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mresearch methodology', 'Collect and analyze data',  \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Interpret results and draw conclusions']           \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│\u001b[2m \u001b[0m\u001b[2mgpt-4-1106-preview    \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mgpt-3.5-turbo         \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research question', 'Collect and prepare   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m7     \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mdata', 'Fine-tune the language model', 'Analyze     \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mresults', 'Iterate and refine']                     \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "├────────────────────────┼────────────────────────┼──────────────────────────────────────────────────────┼────────┤\n",
-       "│\u001b[2m \u001b[0m\u001b[2mgpt-4-1106-preview    \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mgpt-4-1106-preview    \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research objectives', 'Choose a suitable   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m9     \u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mlarge language model', 'Determine the scope of      \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mresearch', 'Develop a set of hypotheses or research \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mquestions', 'Design the research methodology',      \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Collect data', 'Preprocess and clean the data',    \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Fine-tune the language model if necessary', 'Run   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mexperiments or simulations', 'Analyze the results', \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Interpret the findings', 'Consider the ethical     \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mimplications', 'Document the research process',     \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Write the research paper or report', 'Peer review  \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mand validate findings', 'Publish or share the       \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "│\u001b[2m                        \u001b[0m│\u001b[2m                        \u001b[0m│\u001b[2m \u001b[0m\u001b[2mresearch outcomes']                                 \u001b[0m\u001b[2m \u001b[0m│\u001b[2m        \u001b[0m│\n",
-       "└────────────────────────┴────────────────────────┴──────────────────────────────────────────────────────┴────────┘\n"
+       "┏━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┓\n",
+       "┃\u001b[1;35m \u001b[0m\u001b[1;35mmodel.model           \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mscenario.drafting_model\u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mscenario.content                             \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35manswer.score\u001b[0m\u001b[1;35m \u001b[0m┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━┩\n",
+       "│\u001b[2m \u001b[0m\u001b[2mclaude-3-opus-20240229\u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mclaude-3-opus-20240229 \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research questions and hypotheses', \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m8           \u001b[0m\u001b[2m \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Select appropriate language model(s)',      \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Collect and preprocess data', 'Fine-tune and\u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mevaluate models', 'Analyze results and draw  \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mconclusions', 'Document methodology and      \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mfindings']                                   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "├────────────────────────┼─────────────────────────┼───────────────────────────────────────────────┼──────────────┤\n",
+       "│\u001b[2m \u001b[0m\u001b[2mclaude-3-opus-20240229\u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mgemini-pro             \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research objectives', 'Gather and   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m8           \u001b[0m\u001b[2m \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mprepare data', 'Select and train model',     \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Evaluate model performance', 'Interpret and \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mcommunicate results']                        \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "├────────────────────────┼─────────────────────────┼───────────────────────────────────────────────┼──────────────┤\n",
+       "│\u001b[2m \u001b[0m\u001b[2mclaude-3-opus-20240229\u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mgpt-4o                 \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research objectives', 'Select the   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m8           \u001b[0m\u001b[2m \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mappropriate model', 'Prepare and preprocess  \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mdata', 'Design experiments', 'Evaluate model \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mperformance', 'Analyze results', 'Document   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mfindings', 'Ensure ethical considerations']  \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "├────────────────────────┼─────────────────────────┼───────────────────────────────────────────────┼──────────────┤\n",
+       "│\u001b[2m \u001b[0m\u001b[2mgemini-pro            \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mclaude-3-opus-20240229 \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research questions and hypotheses', \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m9           \u001b[0m\u001b[2m \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Select appropriate language model(s)',      \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Collect and preprocess data', 'Fine-tune and\u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mevaluate models', 'Analyze results and draw  \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mconclusions', 'Document methodology and      \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mfindings']                                   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "├────────────────────────┼─────────────────────────┼───────────────────────────────────────────────┼──────────────┤\n",
+       "│\u001b[2m \u001b[0m\u001b[2mgemini-pro            \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mgemini-pro             \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research objectives', 'Gather and   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m8           \u001b[0m\u001b[2m \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mprepare data', 'Select and train model',     \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Evaluate model performance', 'Interpret and \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mcommunicate results']                        \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "├────────────────────────┼─────────────────────────┼───────────────────────────────────────────────┼──────────────┤\n",
+       "│\u001b[2m \u001b[0m\u001b[2mgemini-pro            \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mgpt-4o                 \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research objectives', 'Select the   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m8           \u001b[0m\u001b[2m \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mappropriate model', 'Prepare and preprocess  \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mdata', 'Design experiments', 'Evaluate model \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mperformance', 'Analyze results', 'Document   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mfindings', 'Ensure ethical considerations']  \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "├────────────────────────┼─────────────────────────┼───────────────────────────────────────────────┼──────────────┤\n",
+       "│\u001b[2m \u001b[0m\u001b[2mgpt-4o                \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mclaude-3-opus-20240229 \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research questions and hypotheses', \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m9           \u001b[0m\u001b[2m \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Select appropriate language model(s)',      \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Collect and preprocess data', 'Fine-tune and\u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mevaluate models', 'Analyze results and draw  \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mconclusions', 'Document methodology and      \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mfindings']                                   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "├────────────────────────┼─────────────────────────┼───────────────────────────────────────────────┼──────────────┤\n",
+       "│\u001b[2m \u001b[0m\u001b[2mgpt-4o                \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mgemini-pro             \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research objectives', 'Gather and   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m8           \u001b[0m\u001b[2m \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mprepare data', 'Select and train model',     \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'Evaluate model performance', 'Interpret and \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mcommunicate results']                        \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "├────────────────────────┼─────────────────────────┼───────────────────────────────────────────────┼──────────────┤\n",
+       "│\u001b[2m \u001b[0m\u001b[2mgpt-4o                \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mgpt-4o                 \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['Define research objectives', 'Select the   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m8           \u001b[0m\u001b[2m \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mappropriate model', 'Prepare and preprocess  \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mdata', 'Design experiments', 'Evaluate model \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mperformance', 'Analyze results', 'Document   \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "│\u001b[2m                        \u001b[0m│\u001b[2m                         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mfindings', 'Ensure ethical considerations']  \u001b[0m\u001b[2m \u001b[0m│\u001b[2m              \u001b[0m│\n",
+       "└────────────────────────┴─────────────────────────┴───────────────────────────────────────────────┴──────────────┘\n"
       ]
      },
      "metadata": {},
@@ -1270,7 +549,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1303,7 +582,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -1335,31 +614,24 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>15</th>\n",
+       "      <th>8</th>\n",
        "      <td>claude-3-opus-20240229</td>\n",
        "      <td>claude-3-opus-20240229</td>\n",
-       "      <td>9</td>\n",
+       "      <td>8</td>\n",
        "      <td>Self score</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>14</th>\n",
+       "      <th>5</th>\n",
        "      <td>claude-3-opus-20240229</td>\n",
        "      <td>gemini-pro</td>\n",
        "      <td>8</td>\n",
-       "      <td>Lower</td>\n",
+       "      <td>Equal</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>13</th>\n",
+       "      <th>2</th>\n",
        "      <td>claude-3-opus-20240229</td>\n",
-       "      <td>gpt-3.5-turbo</td>\n",
+       "      <td>gpt-4o</td>\n",
        "      <td>8</td>\n",
-       "      <td>Lower</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>12</th>\n",
-       "      <td>claude-3-opus-20240229</td>\n",
-       "      <td>gpt-4-1106-preview</td>\n",
-       "      <td>9</td>\n",
        "      <td>Equal</td>\n",
        "    </tr>\n",
        "    <tr>\n",
@@ -1373,77 +645,35 @@
        "      <th>4</th>\n",
        "      <td>gemini-pro</td>\n",
        "      <td>gemini-pro</td>\n",
-       "      <td>2</td>\n",
+       "      <td>8</td>\n",
        "      <td>Self score</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>gemini-pro</td>\n",
-       "      <td>gpt-3.5-turbo</td>\n",
-       "      <td>4</td>\n",
-       "      <td>Higher</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>gemini-pro</td>\n",
-       "      <td>gpt-4-1106-preview</td>\n",
-       "      <td>10</td>\n",
-       "      <td>Higher</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>gpt-3.5-turbo</td>\n",
-       "      <td>claude-3-opus-20240229</td>\n",
-       "      <td>8</td>\n",
-       "      <td>Equal</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>gpt-3.5-turbo</td>\n",
        "      <td>gemini-pro</td>\n",
+       "      <td>gpt-4o</td>\n",
        "      <td>8</td>\n",
        "      <td>Equal</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>gpt-3.5-turbo</td>\n",
-       "      <td>gpt-3.5-turbo</td>\n",
-       "      <td>8</td>\n",
-       "      <td>Self score</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>gpt-3.5-turbo</td>\n",
-       "      <td>gpt-4-1106-preview</td>\n",
+       "      <th>6</th>\n",
+       "      <td>gpt-4o</td>\n",
+       "      <td>claude-3-opus-20240229</td>\n",
        "      <td>9</td>\n",
        "      <td>Higher</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>gpt-4-1106-preview</td>\n",
-       "      <td>claude-3-opus-20240229</td>\n",
-       "      <td>8</td>\n",
-       "      <td>Lower</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>11</th>\n",
-       "      <td>gpt-4-1106-preview</td>\n",
+       "      <th>3</th>\n",
+       "      <td>gpt-4o</td>\n",
        "      <td>gemini-pro</td>\n",
        "      <td>8</td>\n",
-       "      <td>Lower</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>gpt-4-1106-preview</td>\n",
-       "      <td>gpt-3.5-turbo</td>\n",
-       "      <td>7</td>\n",
-       "      <td>Lower</td>\n",
+       "      <td>Equal</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>gpt-4-1106-preview</td>\n",
-       "      <td>gpt-4-1106-preview</td>\n",
-       "      <td>9</td>\n",
+       "      <th>0</th>\n",
+       "      <td>gpt-4o</td>\n",
+       "      <td>gpt-4o</td>\n",
+       "      <td>8</td>\n",
        "      <td>Self score</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
@@ -1451,26 +681,19 @@
        "</div>"
       ],
       "text/plain": [
-       "                     model          drafting_model  score  comparison\n",
-       "15  claude-3-opus-20240229  claude-3-opus-20240229      9  Self score\n",
-       "14  claude-3-opus-20240229              gemini-pro      8       Lower\n",
-       "13  claude-3-opus-20240229           gpt-3.5-turbo      8       Lower\n",
-       "12  claude-3-opus-20240229      gpt-4-1106-preview      9       Equal\n",
-       "7               gemini-pro  claude-3-opus-20240229      9      Higher\n",
-       "4               gemini-pro              gemini-pro      2  Self score\n",
-       "6               gemini-pro           gpt-3.5-turbo      4      Higher\n",
-       "5               gemini-pro      gpt-4-1106-preview     10      Higher\n",
-       "1            gpt-3.5-turbo  claude-3-opus-20240229      8       Equal\n",
-       "0            gpt-3.5-turbo              gemini-pro      8       Equal\n",
-       "3            gpt-3.5-turbo           gpt-3.5-turbo      8  Self score\n",
-       "2            gpt-3.5-turbo      gpt-4-1106-preview      9      Higher\n",
-       "10      gpt-4-1106-preview  claude-3-opus-20240229      8       Lower\n",
-       "11      gpt-4-1106-preview              gemini-pro      8       Lower\n",
-       "9       gpt-4-1106-preview           gpt-3.5-turbo      7       Lower\n",
-       "8       gpt-4-1106-preview      gpt-4-1106-preview      9  Self score"
+       "                    model          drafting_model  score  comparison\n",
+       "8  claude-3-opus-20240229  claude-3-opus-20240229      8  Self score\n",
+       "5  claude-3-opus-20240229              gemini-pro      8       Equal\n",
+       "2  claude-3-opus-20240229                  gpt-4o      8       Equal\n",
+       "7              gemini-pro  claude-3-opus-20240229      9      Higher\n",
+       "4              gemini-pro              gemini-pro      8  Self score\n",
+       "1              gemini-pro                  gpt-4o      8       Equal\n",
+       "6                  gpt-4o  claude-3-opus-20240229      9      Higher\n",
+       "3                  gpt-4o              gemini-pro      8       Equal\n",
+       "0                  gpt-4o                  gpt-4o      8  Self score"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1486,7 +709,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1539,7 +762,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -1572,57 +795,42 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td>gpt-3.5-turbo</td>\n",
-       "      <td>[gpt-4-1106-preview]</td>\n",
+       "      <td>gpt-4o</td>\n",
+       "      <td>[claude-3-opus-20240229]</td>\n",
        "      <td>[]</td>\n",
-       "      <td>[gemini-pro, claude-3-opus-20240229, gpt-3.5-t...</td>\n",
+       "      <td>[gpt-4o, gemini-pro]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>gemini-pro</td>\n",
-       "      <td>[gpt-4-1106-preview, gpt-3.5-turbo, claude-3-o...</td>\n",
+       "      <td>[claude-3-opus-20240229]</td>\n",
        "      <td>[]</td>\n",
-       "      <td>[gemini-pro]</td>\n",
+       "      <td>[gpt-4o, gemini-pro]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>gpt-4-1106-preview</td>\n",
-       "      <td>[]</td>\n",
-       "      <td>[gpt-3.5-turbo, claude-3-opus-20240229, gemini...</td>\n",
-       "      <td>[gpt-4-1106-preview]</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
        "      <td>claude-3-opus-20240229</td>\n",
        "      <td>[]</td>\n",
-       "      <td>[gpt-3.5-turbo, gemini-pro]</td>\n",
-       "      <td>[gpt-4-1106-preview, claude-3-opus-20240229]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[gpt-4o, gemini-pro, claude-3-opus-20240229]</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                    model                                      better_models  \\\n",
-       "0           gpt-3.5-turbo                               [gpt-4-1106-preview]   \n",
-       "1              gemini-pro  [gpt-4-1106-preview, gpt-3.5-turbo, claude-3-o...   \n",
-       "2      gpt-4-1106-preview                                                 []   \n",
-       "3  claude-3-opus-20240229                                                 []   \n",
-       "\n",
-       "                                        worse_models  \\\n",
-       "0                                                 []   \n",
-       "1                                                 []   \n",
-       "2  [gpt-3.5-turbo, claude-3-opus-20240229, gemini...   \n",
-       "3                        [gpt-3.5-turbo, gemini-pro]   \n",
-       "\n",
-       "                                               equal  \n",
-       "0  [gemini-pro, claude-3-opus-20240229, gpt-3.5-t...  \n",
-       "1                                       [gemini-pro]  \n",
-       "2                               [gpt-4-1106-preview]  \n",
-       "3       [gpt-4-1106-preview, claude-3-opus-20240229]  "
+       "                    model             better_models worse_models  \\\n",
+       "0                  gpt-4o  [claude-3-opus-20240229]           []   \n",
+       "1              gemini-pro  [claude-3-opus-20240229]           []   \n",
+       "2  claude-3-opus-20240229                        []           []   \n",
+       "\n",
+       "                                          equal  \n",
+       "0                          [gpt-4o, gemini-pro]  \n",
+       "1                          [gpt-4o, gemini-pro]  \n",
+       "2  [gpt-4o, gemini-pro, claude-3-opus-20240229]  "
       ]
      },
-     "execution_count": 17,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1641,6 +849,143 @@
     "## Further analysis\n",
     "This code is readily editable to compare results for other models and questions. It can also be expanded to compare responses among AI agents with different traits and personas that we prompt the models to use to answer the questions. Please see our docs for [details on designing AI agents](https://docs.expectedparrot.com/en/latest/agents.html) and using them to simulate responses for audiences of interest."
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "source": [
+    "## Posting to the Coop\n",
+    "The [Coop](https://www.expectedparrot.com/explore) is a platform for creating, storing and sharing LLM-based research.\n",
+    "It is fully integrated with EDSL and accessible from your workspace or Coop account page.\n",
+    "Learn more about [creating an account](https://www.expectedparrot.com/login) and [using the Coop](https://docs.expectedparrot.com/en/latest/coop.html).\n",
+    "\n",
+    "Here we demonstrate how to post this notebook:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "skip-execution"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "from edsl import Notebook"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "skip-execution"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "n = Notebook(path = \"comparing_model_responses.ipynb\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "skip-execution"
+    ]
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'description': 'Example code for comparing model responses',\n",
+       " 'object_type': 'notebook',\n",
+       " 'url': 'https://www.expectedparrot.com/content/520e5573-30f1-4c7a-a0ae-f2098ae90abf',\n",
+       " 'uuid': '520e5573-30f1-4c7a-a0ae-f2098ae90abf',\n",
+       " 'version': '0.1.33.dev1',\n",
+       " 'visibility': 'public'}"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "n.push(description = \"Example code for comparing model responses\", visibility = \"public\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To update an object at the Coop:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "skip-execution"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "n = Notebook(path = \"comparing_model_responses.ipynb\") # resave"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "skip-execution"
+    ]
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'status': 'success'}"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "n.patch(uuid = \"520e5573-30f1-4c7a-a0ae-f2098ae90abf\", value = n)"
+   ]
   }
  ],
  "metadata": {
diff --git a/docs/notebooks/filestore_examples.ipynb b/docs/notebooks/filestore_examples.ipynb
new file mode 100644
index 000000000..3afebf57a
--- /dev/null
+++ b/docs/notebooks/filestore_examples.ipynb
@@ -0,0 +1,650 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "19b1b109-8704-406a-a79a-b2c7a899a580",
+   "metadata": {},
+   "source": [
+    "# FileStore examples\n",
+    "This notebook contains examples of methods for posting CSV, PDF and PNG files at the Coop to use with surveys. \n",
+    "\n",
+    "Please see more information in the [FileStore documentation page](https://docs.expectedparrot.com/filestore.html)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4ed1f6b9-329c-4719-bd1b-a949704f529f",
+   "metadata": {},
+   "source": [
+    "## CSV example"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "36b46c11-014d-4799-81f7-5148b652f119",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from edsl.scenarios.FileStore import CSVFileStore"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b06d37ad-2a7a-4dac-8a5a-6e0e8fe7a7ec",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "source": [
+    "#### Posting"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "1d8ce313-0d36-404b-8fee-46ee4e373328",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'description': 'File: example.csv', 'object_type': 'scenario', 'url': 'https://www.expectedparrot.com/content/4531d6ac-5425-4c93-aa02-07c1fa64aaa3', 'uuid': '4531d6ac-5425-4c93-aa02-07c1fa64aaa3', 'version': '0.1.33.dev1', 'visibility': 'unlisted'}\n"
+     ]
+    }
+   ],
+   "source": [
+    "fs = CSVFileStore(\"example.csv\")\n",
+    "info = fs.push()\n",
+    "\n",
+    "print(info)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "70918576-9f1a-439d-9f0a-0c46a8ab3ec3",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "source": [
+    "#### Retrieving"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "7a152897-85ab-4d96-b1c8-64011cfd876b",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "csv_file = CSVFileStore.pull(\"4531d6ac-5425-4c93-aa02-07c1fa64aaa3\", expected_parrot_url=\"https://www.expectedparrot.com\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7edb283e-6d36-4b7e-a856-5e0ebab99152",
+   "metadata": {},
+   "source": [
+    "#### Creating scenarios"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "b86e2701-2da3-42e8-ab1d-97e0025a7bb9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from edsl import ScenarioList"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "53d11b2a-908a-4c5d-bdc0-b533840f8961",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "scenarios = ScenarioList.from_csv(csv_file.to_tempfile())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d644f354-989c-4b53-a477-054238ba8f34",
+   "metadata": {},
+   "source": [
+    "#### Inspecting scenarios"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "87492ebf-052b-45c8-9a52-9a83894adaa7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div class=\"highlight\"><pre><span></span><span class=\"p\">{</span>\n",
+       "<span class=\"w\">    </span><span class=\"nt\">&quot;scenarios&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p\">[</span>\n",
+       "<span class=\"w\">        </span><span class=\"p\">{</span>\n",
+       "<span class=\"w\">            </span><span class=\"nt\">&quot;id&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s2\">&quot;1&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">            </span><span class=\"nt\">&quot;date&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s2\">&quot;2024-09-21&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">            </span><span class=\"nt\">&quot;message&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s2\">&quot;&#39;How are you?&#39;&quot;</span>\n",
+       "<span class=\"w\">        </span><span class=\"p\">},</span>\n",
+       "<span class=\"w\">        </span><span class=\"p\">{</span>\n",
+       "<span class=\"w\">            </span><span class=\"nt\">&quot;id&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s2\">&quot;2&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">            </span><span class=\"nt\">&quot;date&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s2\">&quot;2001-06-09&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">            </span><span class=\"nt\">&quot;message&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s2\">&quot;&#39;A day to remember!&#39;&quot;</span>\n",
+       "<span class=\"w\">        </span><span class=\"p\">},</span>\n",
+       "<span class=\"w\">        </span><span class=\"p\">{</span>\n",
+       "<span class=\"w\">            </span><span class=\"nt\">&quot;id&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s2\">&quot;3&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">            </span><span class=\"nt\">&quot;date&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s2\">&quot;1979-03-26&quot;</span><span class=\"p\">,</span>\n",
+       "<span class=\"w\">            </span><span class=\"nt\">&quot;message&quot;</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s2\">&quot;&#39;Happy birthday&#39;&quot;</span>\n",
+       "<span class=\"w\">        </span><span class=\"p\">}</span>\n",
+       "<span class=\"w\">    </span><span class=\"p\">]</span>\n",
+       "<span class=\"p\">}</span>\n",
+       "</pre></div>\n"
+      ],
+      "text/plain": [
+       "ScenarioList([Scenario({'id': '1', 'date': '2024-09-21', 'message': \"'How are you?'\"}), Scenario({'id': '2', 'date': '2001-06-09', 'message': \"'A day to remember!'\"}), Scenario({'id': '3', 'date': '1979-03-26', 'message': \"'Happy birthday'\"})])"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "scenarios"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "66517a28-57e5-490d-9b5c-19b7ff062db5",
+   "metadata": {},
+   "source": [
+    "## PDF example"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "08f4fc2d-a817-419d-875d-501835fd7826",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from edsl.scenarios.FileStore import PDFFileStore"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9401dc7f-7a9f-45c9-9c7b-7ca1f86ca362",
+   "metadata": {},
+   "source": [
+    "#### Posting"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "9c646b52-0cbb-447d-9d97-c5df5ce07a88",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'description': 'File: top_secret.pdf', 'object_type': 'scenario', 'url': 'https://www.expectedparrot.com/content/a6231668-3166-4741-93d8-f3248b91660f', 'uuid': 'a6231668-3166-4741-93d8-f3248b91660f', 'version': '0.1.33.dev1', 'visibility': 'unlisted'}\n"
+     ]
+    }
+   ],
+   "source": [
+    "fs = PDFFileStore(\"top_secret.pdf\")\n",
+    "info = fs.push()\n",
+    "\n",
+    "print(info)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "251a920d-587f-47d6-be3d-df6c88e2b9d4",
+   "metadata": {},
+   "source": [
+    "#### Retrieving"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "c2a6c85c-ea0a-44cc-8bf3-7ce3ce1e6753",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "pdf_file = PDFFileStore.pull(\"a6231668-3166-4741-93d8-f3248b91660f\", expected_parrot_url=\"https://www.expectedparrot.com\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bcfca6cc-9319-4e9e-9091-082ba278e69d",
+   "metadata": {},
+   "source": [
+    "#### Creating scenarios"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "e9b681da-db15-4ef4-a7ab-8763f64a45cb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from edsl import ScenarioList"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "214fd6f4-9996-4a06-939e-ed2c6b7a6ea3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "scenarios = ScenarioList.from_pdf(pdf_file.to_tempfile())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "74af3df7-7b33-4ba5-a0e8-c2c683559046",
+   "metadata": {},
+   "source": [
+    "#### Checking scenario keys"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "b2ff8a00-b6f3-46d9-944d-e567f37343a3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'filename', 'page', 'text'}"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "scenarios.parameters"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "92ce1247-b744-4cf0-8dcc-95c5e338003c",
+   "metadata": {},
+   "source": [
+    "## PNG example"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "1d286fb4-5aaf-4389-8dc1-c54d304c1478",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from edsl.scenarios.FileStore import PNGFileStore"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "99820285-d3d9-4716-ac0e-3f69c245e5f2",
+   "metadata": {},
+   "source": [
+    "#### Posting"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "3fe472d8-2c6f-482c-92cc-6f84503f3b83",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'description': 'File: parrot_logo.png', 'object_type': 'scenario', 'url': 'https://www.expectedparrot.com/content/148e6320-5642-486c-9332-a6d30be0daae', 'uuid': '148e6320-5642-486c-9332-a6d30be0daae', 'version': '0.1.33.dev1', 'visibility': 'unlisted'}\n"
+     ]
+    }
+   ],
+   "source": [
+    "fs = PNGFileStore(\"parrot_logo.png\")\n",
+    "info = fs.push()\n",
+    "\n",
+    "print(info)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b8829f67-f257-4519-b1a5-b3530d86c940",
+   "metadata": {},
+   "source": [
+    "#### Retrieving"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "382c843b-c357-4dc6-b14d-8c229a1218b6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "png_file = PNGFileStore.pull(\"148e6320-5642-486c-9332-a6d30be0daae\", expected_parrot_url=\"https://www.expectedparrot.com\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3add807d-1fe0-4352-b4d2-814c1cbaca3c",
+   "metadata": {},
+   "source": [
+    "#### Creating a scenario"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "007b0b85-62db-46a0-a977-60d061e22a4f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from edsl import Scenario"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "c2e9e10f-bc25-439a-bcf1-3a4ac859b548",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "scenario = Scenario.from_image(png_file.to_tempfile(), \"parrot_logo\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "826766db-c029-4877-b0a2-586db2e946bb",
+   "metadata": {},
+   "source": [
+    "#### Checking scenario keys"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "67833e2d-b368-4254-91c8-4d86de550f32",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['parrot_logo']"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "scenario.keys()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fb46b2da-322f-4d1f-952c-20fc2b76a673",
+   "metadata": {},
+   "source": [
+    "#### Renaming a scenario key"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "da4eeb05-d14e-48e7-b52f-425b05820128",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "scenario = scenario.rename({\"parrot_logo\": \"logo\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "1bb592d7-7c7b-48dc-aa05-a24a2e1ef361",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['logo']"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "scenario.keys()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5e9e7beb-f057-4ecc-99bf-8b6cd6cc79e2",
+   "metadata": {},
+   "source": [
+    "## Posting to the Coop"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "7c055a14-0344-4879-a185-bbcf04f83f9d",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "skip-execution"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "from edsl import Notebook"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "e24995b4-7b3c-474c-88a5-8c1da26ce7fc",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "skip-execution"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "n = Notebook(path = \"filestore_examples.ipynb\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "b6bc62cc-4e2c-4839-ad44-0b06dd1efafe",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "skip-execution"
+    ]
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'description': 'FileStore examples',\n",
+       " 'object_type': 'notebook',\n",
+       " 'url': 'https://www.expectedparrot.com/content/e1a00873-dfc6-4383-9426-cc032296bab1',\n",
+       " 'uuid': 'e1a00873-dfc6-4383-9426-cc032296bab1',\n",
+       " 'version': '0.1.33.dev1',\n",
+       " 'visibility': 'public'}"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "n.push(description = \"FileStore examples\", visibility = \"public\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1994f140-ff7f-4ab6-ad2e-b7d21a6e6548",
+   "metadata": {},
+   "source": [
+    "To update an object at the Coop:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "82686871-c1ab-4dc4-b9e2-2371b4a6b2ed",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "skip-execution"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "n = Notebook(path = \"filestore_examples.ipynb\") # resave"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "584a7aaa-b09d-4f77-8a33-ca921f9acc73",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "skip-execution"
+    ]
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'status': 'success'}"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "n.patch(uuid = \"e1a00873-dfc6-4383-9426-cc032296bab1\", value = n)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/docs/notebooks/image_scenario_example.ipynb b/docs/notebooks/image_scenario_example.ipynb
index cb2225345..4763507ab 100644
--- a/docs/notebooks/image_scenario_example.ipynb
+++ b/docs/notebooks/image_scenario_example.ipynb
@@ -33,12 +33,64 @@
    "metadata": {},
    "source": [
     "### Creating a scenario\n",
-    "We start by creating a `Scenario` for an image:"
+    "We start by creating a `Scenario` for an image.\n",
+    "For purposes of demonstration, we post a PNG image to the Coop, and then retrieve it as a scenario (this can be done by [any user with a Coop account](https://www.expectedparrot.com/login)).\n",
+    "\n",
+    "Code for posting a PNG file to the Coop (uncomment and replace with your own file):"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 1,
+   "id": "fe5e746e-d0ee-495a-a233-93855953452e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# from edsl.scenarios.FileStore import PNGFileStore\n",
+    "# fs = PNGFileStore(\"parrot_logo.png\")\n",
+    "# info = fs.push()\n",
+    "# print(info)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f30809fd-ef5c-48d2-835b-5435100b3a7d",
+   "metadata": {},
+   "source": [
+    "Retrieving a Coop file to use as a scenario (replace with the UUID of a desired object):"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "2a2380a9-0712-4ce9-8390-a1d8ec396bd1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from edsl.scenarios.FileStore import PNGFileStore"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "1f89b60a-bdb4-45b0-9c19-ad1e975cdd5d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "png_file = PNGFileStore.pull(\"e9edda74-d493-42df-92bc-34bf49c6d1bf\", expected_parrot_url=\"https://www.expectedparrot.com\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "136842bd-757d-409b-a2e6-6805f4447fd1",
+   "metadata": {},
+   "source": [
+    "Converting the retrieved file into a scenario:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
    "id": "bfcf703c-7440-4e16-ad91-1def92256962",
    "metadata": {},
    "outputs": [],
@@ -48,55 +100,53 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "id": "67285b06-6222-41d8-ac6b-0b6f338bb0f7",
+   "execution_count": 5,
+   "id": "3cb195af-740c-432b-9fda-f8646b0e295e",
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Code for generating from a local file:\n",
-    "# \n",
-    "# s = Scenario.from_image(\"logo.png\")"
+    "s = Scenario.from_image(png_file.to_tempfile(), \"parrot_logo\")"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "919d0866-7d46-4442-b394-4432ef96967d",
+   "id": "93713732-bf8b-465d-85ad-64b41c5a0cfb",
    "metadata": {},
    "source": [
-    "We can use the example scenario, which is the EP logo:"
+    "Alternative method for creating a scenario from a local file:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "id": "d602ee73-032c-4aee-846d-1201aaa88139",
+   "execution_count": 6,
+   "id": "67285b06-6222-41d8-ac6b-0b6f338bb0f7",
    "metadata": {},
    "outputs": [],
    "source": [
-    "s = Scenario.example(has_image = True)"
+    "# s = Scenario.from_image(\"parrot_logo.png\", \"parrot_logo\")"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "a9f3e0f1-2339-49eb-8c2c-a9e761301796",
+   "id": "aa90e27a-6ad9-4076-bbe5-884a8a5c3495",
    "metadata": {},
    "source": [
-    "The parameter that we will add to questions in order to include the image:"
+    "Verify the scenario keys to use in questions:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "id": "517784ea-af13-4699-8fa4-5e4db159ad16",
+   "execution_count": 7,
+   "id": "feef15a7-9d8e-47e8-ba2f-ae2b2e41c0fe",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "['logo']"
+       "['parrot_logo']"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -118,51 +168,83 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 8,
    "id": "ba35b5cd-23b7-4259-b571-666aea99ec21",
    "metadata": {},
    "outputs": [],
    "source": [
-    "from edsl import QuestionFreeText, Survey"
+    "from edsl import QuestionYesNo, QuestionFreeText, QuestionList, Survey"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 9,
+   "id": "c345c14c-d688-43c8-8574-600d62433d85",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "q1 = QuestionYesNo(\n",
+    "    question_name = \"animal\",\n",
+    "    question_text = \"Is there an animal in this image? {{ parrot_logo }}\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
    "id": "3cc43621-13f3-4588-b1ef-ec470794a5df",
    "metadata": {},
    "outputs": [],
    "source": [
-    "q = QuestionFreeText(\n",
-    "    question_name = \"identify_image\",\n",
-    "    question_text = \"What is this a picture of: {{ logo }}?\"\n",
+    "q2 = QuestionFreeText(\n",
+    "    question_name = \"identify\",\n",
+    "    question_text = \"Identify the animal in this image: {{ parrot_logo }}\"\n",
     ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 11,
    "id": "950c557d-6ba6-408d-b2e7-be7cf3c858df",
    "metadata": {},
    "outputs": [],
    "source": [
-    "q_follow_up = QuestionFreeText(\n",
-    "    question_name = \"id_animal\",\n",
-    "    question_text = \"\"\"\n",
-    "    You previously examined a logo, with the following conclusion: {{ identify_image.answer }}. \n",
-    "    What animal did you see?\n",
-    "    \"\"\", \n",
+    "q3 = QuestionList(\n",
+    "    question_name = \"colors\",\n",
+    "    question_text = \"What color(s) is the animal?\", \n",
     ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 12,
    "id": "0f7f0c3d-0a6f-4f68-a357-b302f6807b8d",
    "metadata": {},
    "outputs": [],
    "source": [
-    "survey = Survey(questions = [q, q_follow_up])"
+    "survey = Survey(questions = [q1, q2, q3])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "34cb623e-dccb-41cb-9549-65bdc0ef2576",
+   "metadata": {},
+   "source": [
+    "Adding logic and rules for adminitering the questions:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "736bc61b-7254-4f65-8740-5fbf3d3497c4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "survey = (\n",
+    "    survey\n",
+    "    .add_stop_rule(q1, \"animal == 'No'\")\n",
+    "    .add_targeted_memory(q3, q2)\n",
+    ")"
    ]
   },
   {
@@ -175,7 +257,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 14,
    "id": "d5e4a37a-90f5-4b24-8211-c23d8cb68926",
    "metadata": {},
    "outputs": [],
@@ -185,38 +267,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 15,
    "id": "acdf9eb5-ebf2-4ea1-991a-8bd69230ea0f",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓\n",
-       "┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> answer                                                                                        </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> answer          </span>┃\n",
-       "┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> .identify_image                                                                               </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> .id_animal      </span>┃\n",
-       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> This image is a visual pun or a play on words. It combines the mathematical notation for      </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> I saw a parrot. </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> \"expected value,\" denoted by \\( \\mathbb{E} \\left[ \\cdot \\right] \\), with an image of a        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                 </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> parrot. The expected value notation typically contains a random variable inside the brackets, </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                 </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> but here, the parrot is placed inside. This creates a humorous interpretation where the       </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                 </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> expected value is a \"parrot,\" playing on the similarity in the sounds of \"parrot\" and         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                 </span>│\n",
-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> \"parenthesis.\"                                                                                </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                 </span>│\n",
-       "└───────────────────────────────────────────────────────────────────────────────────────────────┴─────────────────┘\n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
+       "┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> answer  </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> answer                           </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> answer                           </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> comment                         </span>┃\n",
+       "┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> .animal </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> .identify                        </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> .colors                          </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> .colors_comment                 </span>┃\n",
+       "┡━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> Yes     </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> The animal in the image is a     </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> ['green', 'red', 'blue',         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> Comment: Parrots are often      </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> parrot.                          </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 'yellow']                        </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> brightly colored, and the most  </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                                  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                                  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> common colors for many parrot   </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                                  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                                  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> species include green, red,     </span>│\n",
+       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                                  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                                  </span>│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> blue, and yellow.               </span>│\n",
+       "└─────────┴──────────────────────────────────┴──────────────────────────────────┴─────────────────────────────────┘\n",
        "</pre>\n"
       ],
       "text/plain": [
-       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓\n",
-       "┃\u001b[1;35m \u001b[0m\u001b[1;35manswer                                                                                       \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35manswer         \u001b[0m\u001b[1;35m \u001b[0m┃\n",
-       "┃\u001b[1;35m \u001b[0m\u001b[1;35m.identify_image                                                                              \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35m.id_animal     \u001b[0m\u001b[1;35m \u001b[0m┃\n",
-       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩\n",
-       "│\u001b[2m \u001b[0m\u001b[2mThis image is a visual pun or a play on words. It combines the mathematical notation for     \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mI saw a parrot.\u001b[0m\u001b[2m \u001b[0m│\n",
-       "│\u001b[2m \u001b[0m\u001b[2m\"expected value,\" denoted by \\( \\mathbb{E} \\left[ \\cdot \\right] \\), with an image of a       \u001b[0m\u001b[2m \u001b[0m│\u001b[2m                 \u001b[0m│\n",
-       "│\u001b[2m \u001b[0m\u001b[2mparrot. The expected value notation typically contains a random variable inside the brackets,\u001b[0m\u001b[2m \u001b[0m│\u001b[2m                 \u001b[0m│\n",
-       "│\u001b[2m \u001b[0m\u001b[2mbut here, the parrot is placed inside. This creates a humorous interpretation where the      \u001b[0m\u001b[2m \u001b[0m│\u001b[2m                 \u001b[0m│\n",
-       "│\u001b[2m \u001b[0m\u001b[2mexpected value is a \"parrot,\" playing on the similarity in the sounds of \"parrot\" and        \u001b[0m\u001b[2m \u001b[0m│\u001b[2m                 \u001b[0m│\n",
-       "│\u001b[2m \u001b[0m\u001b[2m\"parenthesis.\"                                                                               \u001b[0m\u001b[2m \u001b[0m│\u001b[2m                 \u001b[0m│\n",
-       "└───────────────────────────────────────────────────────────────────────────────────────────────┴─────────────────┘\n"
+       "┏━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
+       "┃\u001b[1;35m \u001b[0m\u001b[1;35manswer \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35manswer                          \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35manswer                          \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mcomment                        \u001b[0m\u001b[1;35m \u001b[0m┃\n",
+       "┃\u001b[1;35m \u001b[0m\u001b[1;35m.animal\u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35m.identify                       \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35m.colors                         \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35m.colors_comment                \u001b[0m\u001b[1;35m \u001b[0m┃\n",
+       "┡━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
+       "│\u001b[2m \u001b[0m\u001b[2mYes    \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mThe animal in the image is a    \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m['green', 'red', 'blue',        \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mComment: Parrots are often     \u001b[0m\u001b[2m \u001b[0m│\n",
+       "│\u001b[2m         \u001b[0m│\u001b[2m \u001b[0m\u001b[2mparrot.                         \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2m'yellow']                       \u001b[0m\u001b[2m \u001b[0m│\u001b[2m \u001b[0m\u001b[2mbrightly colored, and the most \u001b[0m\u001b[2m \u001b[0m│\n",
+       "│\u001b[2m         \u001b[0m│\u001b[2m                                  \u001b[0m│\u001b[2m                                  \u001b[0m│\u001b[2m \u001b[0m\u001b[2mcommon colors for many parrot  \u001b[0m\u001b[2m \u001b[0m│\n",
+       "│\u001b[2m         \u001b[0m│\u001b[2m                                  \u001b[0m│\u001b[2m                                  \u001b[0m│\u001b[2m \u001b[0m\u001b[2mspecies include green, red,    \u001b[0m\u001b[2m \u001b[0m│\n",
+       "│\u001b[2m         \u001b[0m│\u001b[2m                                  \u001b[0m│\u001b[2m                                  \u001b[0m│\u001b[2m \u001b[0m\u001b[2mblue, and yellow.              \u001b[0m\u001b[2m \u001b[0m│\n",
+       "└─────────┴──────────────────────────────────┴──────────────────────────────────┴─────────────────────────────────┘\n"
       ]
      },
      "metadata": {},
@@ -224,15 +304,124 @@
     }
    ],
    "source": [
-    "results.select(\"identify_image\", \"id_animal\").print(format=\"rich\")"
+    "results.select(\"animal\", \"identify\", \"colors\", \"colors_comment\").print(format=\"rich\")"
    ]
   },
   {
-   "cell_type": "markdown",
-   "id": "5af65f3b-9706-4e8c-a2f1-f8654b4dd3e1",
-   "metadata": {},
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "de22063a-6430-4142-bf89-88221ed9bef6",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "skip-execution"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "from edsl import Notebook"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "3f9caf2f-4e27-4e97-ab2a-ac37f735a3e9",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "skip-execution"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "n = Notebook(path = \"image_scenario_example.ipynb\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "a434808e-26fd-49c4-80d7-c07aceaf6d6d",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "skip-execution"
+    ]
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'description': 'Using an image scenario',\n",
+       " 'object_type': 'notebook',\n",
+       " 'url': 'https://www.expectedparrot.com/content/50a000c8-d48c-49d6-a11b-2e13ad2e5c69',\n",
+       " 'uuid': '50a000c8-d48c-49d6-a11b-2e13ad2e5c69',\n",
+       " 'version': '0.1.33.dev1',\n",
+       " 'visibility': 'public'}"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "n.push(description = \"Using an image scenario\", visibility = \"public\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "d9ad14cb-e75c-46e0-9082-ee0f668f8520",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "skip-execution"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "n = Notebook(path = \"image_scenario_example.ipynb\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "8fafe297-25e2-47b4-b716-9a910bf3b067",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "skip-execution"
+    ]
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'status': 'success'}"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "Wrong answer, but a decent guess!"
+    "n.patch(uuid = \"50a000c8-d48c-49d6-a11b-2e13ad2e5c69\", value = n)"
    ]
   }
  ],
diff --git a/docs/requirements.txt b/docs/requirements.txt
index 21daae5d4..3a737825c 100644
--- a/docs/requirements.txt
+++ b/docs/requirements.txt
@@ -1,83 +1,98 @@
-aiohappyeyeballs==2.3.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:40a16ceffcf1fc9e142fd488123b2e218abc4188cf12ac20c67200e1579baa42 \
-    --hash=sha256:7e1ae8399c320a8adec76f6c919ed5ceae6edd4c3672f4d9eae2b27e37c80ff6
-aiohttp==3.10.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:03799a95402a7ed62671c4465e1eae51d749d5439dbc49edb6eee52ea165c50b \
-    --hash=sha256:0433795c4a8bafc03deb3e662192250ba5db347c41231b0273380d2f53c9ea0b \
-    --hash=sha256:06ef0135d7ab7fb0284342fbbf8e8ddf73b7fee8ecc55f5c3a3d0a6b765e6d8b \
-    --hash=sha256:0b0c0148d2a69b82ffe650c2ce235b431d49a90bde7dd2629bcb40314957acf6 \
-    --hash=sha256:0d85a173b4dbbaaad1900e197181ea0fafa617ca6656663f629a8a372fdc7d06 \
-    --hash=sha256:10f0d7894ddc6ff8f369e3fdc082ef1f940dc1f5b9003cd40945d24845477220 \
-    --hash=sha256:12c43dace645023583f3dd2337dfc3aa92c99fb943b64dcf2bc15c7aa0fb4a95 \
-    --hash=sha256:13679e11937d3f37600860de1f848e2e062e2b396d3aa79b38c89f9c8ab7e791 \
-    --hash=sha256:1c83977f7b6f4f4a96fab500f5a76d355f19f42675224a3002d375b3fb309174 \
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-    --hash=sha256:effafe5144aa32f0388e8f99b1b2692cf094ea2f6b7ceca384b54338b77b1f50 \
-    --hash=sha256:f1bc4d68b83966012813598fe39b35b4e6019b69d29385cf7ec1cb08e1ff829b \
-    --hash=sha256:f1cef548ee4e84264b78879de0c754bbe223193c6313beb242ce862f82eab184 \
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-    --hash=sha256:f3a1ea61d96146e9b9e5597069466e2e4d9e01e09381c5dd51659f890d5e29e7 \
-    --hash=sha256:f64d503c661864866c09806ac360b95457f872d639ca61719115a9f389b2ec90 \
-    --hash=sha256:f6fa7a42b78d8698491dc4ad388169de54cca551aa9900f750547372de396277 \
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-    --hash=sha256:f98f036eab11d2f90cdd01b9d1410de9d7eb520d070debeb2edadf158b758431 \
-    --hash=sha256:ff25d988fd6ce433b5c393094a5ca50df568bdccf90a8b340900e24e0d5fb45c
+aiohappyeyeballs==2.4.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:55a1714f084e63d49639800f95716da97a1f173d46a16dfcfda0016abb93b6b2 \
+    --hash=sha256:7ce92076e249169a13c2f49320d1967425eaf1f407522d707d59cac7628d62bd
+aiohttp==3.10.5 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:02594361128f780eecc2a29939d9dfc870e17b45178a867bf61a11b2a4367277 \
+    --hash=sha256:03f2645adbe17f274444953bdea69f8327e9d278d961d85657cb0d06864814c1 \
+    --hash=sha256:074d1bff0163e107e97bd48cad9f928fa5a3eb4b9d33366137ffce08a63e37fe \
+    --hash=sha256:0912b8a8fadeb32ff67a3ed44249448c20148397c1ed905d5dac185b4ca547bb \
+    --hash=sha256:0d277cfb304118079e7044aad0b76685d30ecb86f83a0711fc5fb257ffe832ca \
+    --hash=sha256:0d93400c18596b7dc4794d48a63fb361b01a0d8eb39f28800dc900c8fbdaca91 \
+    --hash=sha256:123dd5b16b75b2962d0fff566effb7a065e33cd4538c1692fb31c3bda2bfb972 \
+    --hash=sha256:17e997105bd1a260850272bfb50e2a328e029c941c2708170d9d978d5a30ad9a \
+    --hash=sha256:18a01eba2574fb9edd5f6e5fb25f66e6ce061da5dab5db75e13fe1558142e0a3 \
+    --hash=sha256:1923a5c44061bffd5eebeef58cecf68096e35003907d8201a4d0d6f6e387ccaa \
+    --hash=sha256:1942244f00baaacaa8155eca94dbd9e8cc7017deb69b75ef67c78e89fdad3c77 \
+    --hash=sha256:1b2c16a919d936ca87a3c5f0e43af12a89a3ce7ccbce59a2d6784caba945b68b \
+    --hash=sha256:1c19de68896747a2aa6257ae4cf6ef59d73917a36a35ee9d0a6f48cff0f94db8 \
+    --hash=sha256:1e72589da4c90337837fdfe2026ae1952c0f4a6e793adbbfbdd40efed7c63599 \
+    --hash=sha256:22c0a23a3b3138a6bf76fc553789cb1a703836da86b0f306b6f0dc1617398abc \
+    --hash=sha256:2c634a3207a5445be65536d38c13791904fda0748b9eabf908d3fe86a52941cf \
+    --hash=sha256:2d21ac12dc943c68135ff858c3a989f2194a709e6e10b4c8977d7fcd67dfd511 \
+    --hash=sha256:2f1f1c75c395991ce9c94d3e4aa96e5c59c8356a15b1c9231e783865e2772699 \
+    --hash=sha256:305be5ff2081fa1d283a76113b8df7a14c10d75602a38d9f012935df20731487 \
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+    --hash=sha256:391cc3a9c1527e424c6865e087897e766a917f15dddb360174a70467572ac6ce \
+    --hash=sha256:3a1c32a19ee6bbde02f1cb189e13a71b321256cc1d431196a9f824050b160d5a \
+    --hash=sha256:4120d7fefa1e2d8fb6f650b11489710091788de554e2b6f8347c7a20ceb003f5 \
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+    --hash=sha256:44b324a6b8376a23e6ba25d368726ee3bc281e6ab306db80b5819999c737d820 \
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+    --hash=sha256:4aff049b5e629ef9b3e9e617fa6e2dfeda1bf87e01bcfecaf3949af9e210105e \
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+    --hash=sha256:4f1c9866ccf48a6df2b06823e6ae80573529f2af3a0992ec4fe75b1a510df8a6 \
+    --hash=sha256:4f7acae3cf1a2a2361ec4c8e787eaaa86a94171d2417aae53c0cca6ca3118ff6 \
+    --hash=sha256:54d9ddea424cd19d3ff6128601a4a4d23d54a421f9b4c0fff740505813739a91 \
+    --hash=sha256:58718e181c56a3c02d25b09d4115eb02aafe1a732ce5714ab70326d9776457c3 \
+    --hash=sha256:5ede29d91a40ba22ac1b922ef510aab871652f6c88ef60b9dcdf773c6d32ad7a \
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+    --hash=sha256:8224f98be68a84b19f48e0bdc14224b5a71339aff3a27df69989fa47d01296f3 \
+    --hash=sha256:898715cf566ec2869d5cb4d5fb4be408964704c46c96b4be267442d265390f32 \
+    --hash=sha256:8989f46f3d7ef79585e98fa991e6ded55d2f48ae56d2c9fa5e491a6e4effb589 \
+    --hash=sha256:8ba01ebc6175e1e6b7275c907a3a36be48a2d487549b656aa90c8a910d9f3178 \
+    --hash=sha256:8c5c6fa16412b35999320f5c9690c0f554392dc222c04e559217e0f9ae244b92 \
+    --hash=sha256:8c6a4e5e40156d72a40241a25cc226051c0a8d816610097a8e8f517aeacd59a2 \
+    --hash=sha256:8eaf44ccbc4e35762683078b72bf293f476561d8b68ec8a64f98cf32811c323e \
+    --hash=sha256:8fb4fc029e135859f533025bc82047334e24b0d489e75513144f25408ecaf058 \
+    --hash=sha256:9093a81e18c45227eebe4c16124ebf3e0d893830c6aca7cc310bfca8fe59d857 \
+    --hash=sha256:94c4381ffba9cc508b37d2e536b418d5ea9cfdc2848b9a7fea6aebad4ec6aac1 \
+    --hash=sha256:94fac7c6e77ccb1ca91e9eb4cb0ac0270b9fb9b289738654120ba8cebb1189c6 \
+    --hash=sha256:95c4dc6f61d610bc0ee1edc6f29d993f10febfe5b76bb470b486d90bbece6b22 \
+    --hash=sha256:975218eee0e6d24eb336d0328c768ebc5d617609affaca5dbbd6dd1984f16ed0 \
+    --hash=sha256:ad146dae5977c4dd435eb31373b3fe9b0b1bf26858c6fc452bf6af394067e10b \
+    --hash=sha256:afe16a84498441d05e9189a15900640a2d2b5e76cf4efe8cbb088ab4f112ee57 \
+    --hash=sha256:b1c43eb1ab7cbf411b8e387dc169acb31f0ca0d8c09ba63f9eac67829585b44f \
+    --hash=sha256:b90078989ef3fc45cf9221d3859acd1108af7560c52397ff4ace8ad7052a132e \
+    --hash=sha256:b98e698dc34966e5976e10bbca6d26d6724e6bdea853c7c10162a3235aba6e16 \
+    --hash=sha256:ba5a8b74c2a8af7d862399cdedce1533642fa727def0b8c3e3e02fcb52dca1b1 \
+    --hash=sha256:c31ad0c0c507894e3eaa843415841995bf8de4d6b2d24c6e33099f4bc9fc0d4f \
+    --hash=sha256:c3b9162bab7e42f21243effc822652dc5bb5e8ff42a4eb62fe7782bcbcdfacf6 \
+    --hash=sha256:c58c6837a2c2a7cf3133983e64173aec11f9c2cd8e87ec2fdc16ce727bcf1a04 \
+    --hash=sha256:c83f7a107abb89a227d6c454c613e7606c12a42b9a4ca9c5d7dad25d47c776ae \
+    --hash=sha256:cde98f323d6bf161041e7627a5fd763f9fd829bcfcd089804a5fdce7bb6e1b7d \
+    --hash=sha256:ce91db90dbf37bb6fa0997f26574107e1b9d5ff939315247b7e615baa8ec313b \
+    --hash=sha256:d00f3c5e0d764a5c9aa5a62d99728c56d455310bcc288a79cab10157b3af426f \
+    --hash=sha256:d17920f18e6ee090bdd3d0bfffd769d9f2cb4c8ffde3eb203777a3895c128862 \
+    --hash=sha256:d55f011da0a843c3d3df2c2cf4e537b8070a419f891c930245f05d329c4b0689 \
+    --hash=sha256:d742c36ed44f2798c8d3f4bc511f479b9ceef2b93f348671184139e7d708042c \
+    --hash=sha256:d9a487ef090aea982d748b1b0d74fe7c3950b109df967630a20584f9a99c0683 \
+    --hash=sha256:d9ef084e3dc690ad50137cc05831c52b6ca428096e6deb3c43e95827f531d5ef \
+    --hash=sha256:da452c2c322e9ce0cfef392e469a26d63d42860f829026a63374fde6b5c5876f \
+    --hash=sha256:dc4826823121783dccc0871e3f405417ac116055bf184ac04c36f98b75aacd12 \
+    --hash=sha256:de7a5299827253023c55ea549444e058c0eb496931fa05d693b95140a947cb73 \
+    --hash=sha256:e04a1f2a65ad2f93aa20f9ff9f1b672bf912413e5547f60749fa2ef8a644e061 \
+    --hash=sha256:e1ca1ef5ba129718a8fc827b0867f6aa4e893c56eb00003b7367f8a733a9b072 \
+    --hash=sha256:ee40b40aa753d844162dcc80d0fe256b87cba48ca0054f64e68000453caead11 \
+    --hash=sha256:f071854b47d39591ce9a17981c46790acb30518e2f83dfca8db2dfa091178691 \
+    --hash=sha256:f29930bc2921cef955ba39a3ff87d2c4398a0394ae217f41cb02d5c26c8b1b77 \
+    --hash=sha256:f489a2c9e6455d87eabf907ac0b7d230a9786be43fbe884ad184ddf9e9c1e385 \
+    --hash=sha256:f5bf3ead3cb66ab990ee2561373b009db5bc0e857549b6c9ba84b20bc462e172 \
+    --hash=sha256:f6f18898ace4bcd2d41a122916475344a87f1dfdec626ecde9ee802a711bc569 \
+    --hash=sha256:f8112fb501b1e0567a1251a2fd0747baae60a4ab325a871e975b7bb67e59221f \
+    --hash=sha256:fd31f176429cecbc1ba499d4aba31aaccfea488f418d60376b911269d3b883c5
 aiosignal==1.3.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:54cd96e15e1649b75d6c87526a6ff0b6c1b0dd3459f43d9ca11d48c339b68cfc \
     --hash=sha256:f8376fb07dd1e86a584e4fcdec80b36b7f81aac666ebc724e2c090300dd83b17
@@ -90,9 +105,9 @@ annotated-types==0.7.0 ; python_full_version >= "3.9.1" and python_version < "3.
 anthropic==0.23.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:6dc5779dae83a5834864f4a4af0166c972b70f4cb8fd2765e1558282cc6d6242 \
     --hash=sha256:9325103702cbc96bb09d1b58c36bde75c726f6a01029fb4d85f41ebba07e9066
-anyio==4.4.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:5aadc6a1bbb7cdb0bede386cac5e2940f5e2ff3aa20277e991cf028e0585ce94 \
-    --hash=sha256:c1b2d8f46a8a812513012e1107cb0e68c17159a7a594208005a57dc776e1bdc7
+anyio==4.6.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:137b4559cbb034c477165047febb6ff83f390fc3b20bf181c1fc0a728cb8beeb \
+    --hash=sha256:c7d2e9d63e31599eeb636c8c5c03a7e108d73b345f064f1c19fdc87b79036a9a
 appnope==0.1.4 ; python_full_version >= "3.9.1" and python_version < "3.13" and platform_system == "Darwin" \
     --hash=sha256:1de3860566df9caf38f01f86f65e0e13e379af54f9e4bee1e66b48f2efffd1ee \
     --hash=sha256:502575ee11cd7a28c0205f379b525beefebab9d161b7c964670864014ed7213c
@@ -124,9 +139,9 @@ argon2-cffi==23.1.0 ; python_full_version >= "3.9.1" and python_version < "3.13"
 arrow==1.3.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:c728b120ebc00eb84e01882a6f5e7927a53960aa990ce7dd2b10f39005a67f80 \
     --hash=sha256:d4540617648cb5f895730f1ad8c82a65f2dad0166f57b75f3ca54759c4d67a85
-astroid==3.2.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:0e14202810b30da1b735827f78f5157be2bbd4a7a59b7707ca0bfc2fb4c0063a \
-    --hash=sha256:413658a61eeca6202a59231abb473f932038fbcbf1666587f66d482083413a25
+astroid==3.3.3 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:2d79acfd3c594b6a2d4141fea98a1d62ab4a52e54332b1f1ddcf07b652cc5c0f \
+    --hash=sha256:63f8c5370d9bad8294163c87b2d440a7fdf546be6c72bbeac0549c93244dbd72
 asttokens==2.4.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:051ed49c3dcae8913ea7cd08e46a606dba30b79993209636c4875bc1d637bc24 \
     --hash=sha256:b03869718ba9a6eb027e134bfdf69f38a236d681c83c160d510768af11254ba0
@@ -136,97 +151,124 @@ async-lru==2.0.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
 async-timeout==4.0.3 ; python_full_version >= "3.9.1" and python_version < "3.11" \
     --hash=sha256:4640d96be84d82d02ed59ea2b7105a0f7b33abe8703703cd0ab0bf87c427522f \
     --hash=sha256:7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028
-attrs==23.2.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:935dc3b529c262f6cf76e50877d35a4bd3c1de194fd41f47a2b7ae8f19971f30 \
-    --hash=sha256:99b87a485a5820b23b879f04c2305b44b951b502fd64be915879d77a7e8fc6f1
-babel==2.15.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:08706bdad8d0a3413266ab61bd6c34d0c28d6e1e7badf40a2cebe67644e2e1fb \
-    --hash=sha256:8daf0e265d05768bc6c7a314cf1321e9a123afc328cc635c18622a2f30a04413
+attrs==24.2.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:5cfb1b9148b5b086569baec03f20d7b6bf3bcacc9a42bebf87ffaaca362f6346 \
+    --hash=sha256:81921eb96de3191c8258c199618104dd27ac608d9366f5e35d011eae1867ede2
+azure-ai-inference==1.0.0b4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:5464404bef337338d4af6eefde3af903400ddb8e5c9e6820f902303542fa0f72 \
+    --hash=sha256:e2c949f91845a8cd96cb9a61ffd432b5b0f4ce236b9be8c29d10f38e0a327412
+azure-core==1.31.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:22954de3777e0250029360ef31d80448ef1be13b80a459bff80ba7073379e2cd \
+    --hash=sha256:656a0dd61e1869b1506b7c6a3b31d62f15984b1a573d6326f6aa2f3e4123284b
+babel==2.16.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:368b5b98b37c06b7daf6696391c3240c938b37767d4584413e8438c5c435fa8b \
+    --hash=sha256:d1f3554ca26605fe173f3de0c65f750f5a42f924499bf134de6423582298e316
 beautifulsoup4==4.12.3 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:74e3d1928edc070d21748185c46e3fb33490f22f52a3addee9aee0f4f7781051 \
     --hash=sha256:b80878c9f40111313e55da8ba20bdba06d8fa3969fc68304167741bbf9e082ed
-black[jupyter]==24.4.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:257d724c2c9b1660f353b36c802ccece186a30accc7742c176d29c146df6e474 \
-    --hash=sha256:37aae07b029fa0174d39daf02748b379399b909652a806e5708199bd93899da1 \
-    --hash=sha256:415e686e87dbbe6f4cd5ef0fbf764af7b89f9057b97c908742b6008cc554b9c0 \
-    --hash=sha256:48a85f2cb5e6799a9ef05347b476cce6c182d6c71ee36925a6c194d074336ef8 \
-    --hash=sha256:7768a0dbf16a39aa5e9a3ded568bb545c8c2727396d063bbaf847df05b08cd96 \
-    --hash=sha256:7e122b1c4fb252fd85df3ca93578732b4749d9be076593076ef4d07a0233c3e1 \
-    --hash=sha256:88c57dc656038f1ab9f92b3eb5335ee9b021412feaa46330d5eba4e51fe49b04 \
-    --hash=sha256:8e537d281831ad0e71007dcdcbe50a71470b978c453fa41ce77186bbe0ed6021 \
-    --hash=sha256:98e123f1d5cfd42f886624d84464f7756f60ff6eab89ae845210631714f6db94 \
-    --hash=sha256:accf49e151c8ed2c0cdc528691838afd217c50412534e876a19270fea1e28e2d \
-    --hash=sha256:b1530ae42e9d6d5b670a34db49a94115a64596bc77710b1d05e9801e62ca0a7c \
-    --hash=sha256:b9176b9832e84308818a99a561e90aa479e73c523b3f77afd07913380ae2eab7 \
-    --hash=sha256:bdde6f877a18f24844e381d45e9947a49e97933573ac9d4345399be37621e26c \
-    --hash=sha256:be8bef99eb46d5021bf053114442914baeb3649a89dc5f3a555c88737e5e98fc \
-    --hash=sha256:bf10f7310db693bb62692609b397e8d67257c55f949abde4c67f9cc574492cc7 \
-    --hash=sha256:c872b53057f000085da66a19c55d68f6f8ddcac2642392ad3a355878406fbd4d \
-    --hash=sha256:d36ed1124bb81b32f8614555b34cc4259c3fbc7eec17870e8ff8ded335b58d8c \
-    --hash=sha256:da33a1a5e49c4122ccdfd56cd021ff1ebc4a1ec4e2d01594fef9b6f267a9e741 \
-    --hash=sha256:dd1b5a14e417189db4c7b64a6540f31730713d173f0b63e55fabd52d61d8fdce \
-    --hash=sha256:e151054aa00bad1f4e1f04919542885f89f5f7d086b8a59e5000e6c616896ffb \
-    --hash=sha256:eaea3008c281f1038edb473c1aa8ed8143a5535ff18f978a318f10302b254063 \
-    --hash=sha256:ef703f83fc32e131e9bcc0a5094cfe85599e7109f896fe8bc96cc402f3eb4b6e
+black[jupyter]==24.8.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:09cdeb74d494ec023ded657f7092ba518e8cf78fa8386155e4a03fdcc44679e6 \
+    --hash=sha256:1f13f7f386f86f8121d76599114bb8c17b69d962137fc70efe56137727c7047e \
+    --hash=sha256:2500945420b6784c38b9ee885af039f5e7471ef284ab03fa35ecdde4688cd83f \
+    --hash=sha256:2b59b250fdba5f9a9cd9d0ece6e6d993d91ce877d121d161e4698af3eb9c1018 \
+    --hash=sha256:3c4285573d4897a7610054af5a890bde7c65cb466040c5f0c8b732812d7f0e5e \
+    --hash=sha256:505289f17ceda596658ae81b61ebbe2d9b25aa78067035184ed0a9d855d18afd \
+    --hash=sha256:62e8730977f0b77998029da7971fa896ceefa2c4c4933fcd593fa599ecbf97a4 \
+    --hash=sha256:649f6d84ccbae73ab767e206772cc2d7a393a001070a4c814a546afd0d423aed \
+    --hash=sha256:6e55d30d44bed36593c3163b9bc63bf58b3b30e4611e4d88a0c3c239930ed5b2 \
+    --hash=sha256:707a1ca89221bc8a1a64fb5e15ef39cd755633daa672a9db7498d1c19de66a42 \
+    --hash=sha256:72901b4913cbac8972ad911dc4098d5753704d1f3c56e44ae8dce99eecb0e3af \
+    --hash=sha256:73bbf84ed136e45d451a260c6b73ed674652f90a2b3211d6a35e78054563a9bb \
+    --hash=sha256:7c046c1d1eeb7aea9335da62472481d3bbf3fd986e093cffd35f4385c94ae368 \
+    --hash=sha256:81c6742da39f33b08e791da38410f32e27d632260e599df7245cccee2064afeb \
+    --hash=sha256:837fd281f1908d0076844bc2b801ad2d369c78c45cf800cad7b61686051041af \
+    --hash=sha256:972085c618ee94f402da1af548a4f218c754ea7e5dc70acb168bfaca4c2542ed \
+    --hash=sha256:9e84e33b37be070ba135176c123ae52a51f82306def9f7d063ee302ecab2cf47 \
+    --hash=sha256:b19c9ad992c7883ad84c9b22aaa73562a16b819c1d8db7a1a1a49fb7ec13c7d2 \
+    --hash=sha256:d6417535d99c37cee4091a2f24eb2b6d5ec42b144d50f1f2e436d9fe1916fe1a \
+    --hash=sha256:eab4dd44ce80dea27dc69db40dab62d4ca96112f87996bca68cd75639aeb2e4c \
+    --hash=sha256:f490dbd59680d809ca31efdae20e634f3fae27fba3ce0ba3208333b713bc3920 \
+    --hash=sha256:fb6e2c0b86bbd43dee042e48059c9ad7830abd5c94b0bc518c0eeec57c3eddc1
 bleach==6.1.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:0a31f1837963c41d46bbf1331b8778e1308ea0791db03cc4e7357b97cf42a8fe \
     --hash=sha256:3225f354cfc436b9789c66c4ee030194bee0568fbf9cbdad3bc8b5c26c5f12b6
-certifi==2024.7.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:5a1e7645bc0ec61a09e26c36f6106dd4cf40c6db3a1fb6352b0244e7fb057c7b \
-    --hash=sha256:c198e21b1289c2ab85ee4e67bb4b4ef3ead0892059901a8d5b622f24a1101e90
-cffi==1.16.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:0c9ef6ff37e974b73c25eecc13952c55bceed9112be2d9d938ded8e856138bcc \
-    --hash=sha256:131fd094d1065b19540c3d72594260f118b231090295d8c34e19a7bbcf2e860a \
-    --hash=sha256:1b8ebc27c014c59692bb2664c7d13ce7a6e9a629be20e54e7271fa696ff2b417 \
-    --hash=sha256:2c56b361916f390cd758a57f2e16233eb4f64bcbeee88a4881ea90fca14dc6ab \
-    --hash=sha256:2d92b25dbf6cae33f65005baf472d2c245c050b1ce709cc4588cdcdd5495b520 \
-    --hash=sha256:31d13b0f99e0836b7ff893d37af07366ebc90b678b6664c955b54561fc36ef36 \
-    --hash=sha256:32c68ef735dbe5857c810328cb2481e24722a59a2003018885514d4c09af9743 \
-    --hash=sha256:3686dffb02459559c74dd3d81748269ffb0eb027c39a6fc99502de37d501faa8 \
-    --hash=sha256:582215a0e9adbe0e379761260553ba11c58943e4bbe9c36430c4ca6ac74b15ed \
-    --hash=sha256:5b50bf3f55561dac5438f8e70bfcdfd74543fd60df5fa5f62d94e5867deca684 \
-    --hash=sha256:5bf44d66cdf9e893637896c7faa22298baebcd18d1ddb6d2626a6e39793a1d56 \
-    --hash=sha256:6602bc8dc6f3a9e02b6c22c4fc1e47aa50f8f8e6d3f78a5e16ac33ef5fefa324 \
-    --hash=sha256:673739cb539f8cdaa07d92d02efa93c9ccf87e345b9a0b556e3ecc666718468d \
-    --hash=sha256:68678abf380b42ce21a5f2abde8efee05c114c2fdb2e9eef2efdb0257fba1235 \
-    --hash=sha256:68e7c44931cc171c54ccb702482e9fc723192e88d25a0e133edd7aff8fcd1f6e \
-    --hash=sha256:6b3d6606d369fc1da4fd8c357d026317fbb9c9b75d36dc16e90e84c26854b088 \
-    --hash=sha256:748dcd1e3d3d7cd5443ef03ce8685043294ad6bd7c02a38d1bd367cfd968e000 \
-    --hash=sha256:7651c50c8c5ef7bdb41108b7b8c5a83013bfaa8a935590c5d74627c047a583c7 \
-    --hash=sha256:7b78010e7b97fef4bee1e896df8a4bbb6712b7f05b7ef630f9d1da00f6444d2e \
-    --hash=sha256:7e61e3e4fa664a8588aa25c883eab612a188c725755afff6289454d6362b9673 \
-    --hash=sha256:80876338e19c951fdfed6198e70bc88f1c9758b94578d5a7c4c91a87af3cf31c \
-    --hash=sha256:8895613bcc094d4a1b2dbe179d88d7fb4a15cee43c052e8885783fac397d91fe \
-    --hash=sha256:88e2b3c14bdb32e440be531ade29d3c50a1a59cd4e51b1dd8b0865c54ea5d2e2 \
-    --hash=sha256:8f8e709127c6c77446a8c0a8c8bf3c8ee706a06cd44b1e827c3e6a2ee6b8c098 \
-    --hash=sha256:9cb4a35b3642fc5c005a6755a5d17c6c8b6bcb6981baf81cea8bfbc8903e8ba8 \
-    --hash=sha256:9f90389693731ff1f659e55c7d1640e2ec43ff725cc61b04b2f9c6d8d017df6a \
-    --hash=sha256:a09582f178759ee8128d9270cd1344154fd473bb77d94ce0aeb2a93ebf0feaf0 \
-    --hash=sha256:a6a14b17d7e17fa0d207ac08642c8820f84f25ce17a442fd15e27ea18d67c59b \
-    --hash=sha256:a72e8961a86d19bdb45851d8f1f08b041ea37d2bd8d4fd19903bc3083d80c896 \
-    --hash=sha256:abd808f9c129ba2beda4cfc53bde801e5bcf9d6e0f22f095e45327c038bfe68e \
-    --hash=sha256:ac0f5edd2360eea2f1daa9e26a41db02dd4b0451b48f7c318e217ee092a213e9 \
-    --hash=sha256:b29ebffcf550f9da55bec9e02ad430c992a87e5f512cd63388abb76f1036d8d2 \
-    --hash=sha256:b2ca4e77f9f47c55c194982e10f058db063937845bb2b7a86c84a6cfe0aefa8b \
-    --hash=sha256:b7be2d771cdba2942e13215c4e340bfd76398e9227ad10402a8767ab1865d2e6 \
-    --hash=sha256:b84834d0cf97e7d27dd5b7f3aca7b6e9263c56308ab9dc8aae9784abb774d404 \
-    --hash=sha256:b86851a328eedc692acf81fb05444bdf1891747c25af7529e39ddafaf68a4f3f \
-    --hash=sha256:bcb3ef43e58665bbda2fb198698fcae6776483e0c4a631aa5647806c25e02cc0 \
-    --hash=sha256:c0f31130ebc2d37cdd8e44605fb5fa7ad59049298b3f745c74fa74c62fbfcfc4 \
-    --hash=sha256:c6a164aa47843fb1b01e941d385aab7215563bb8816d80ff3a363a9f8448a8dc \
-    --hash=sha256:d8a9d3ebe49f084ad71f9269834ceccbf398253c9fac910c4fd7053ff1386936 \
-    --hash=sha256:db8e577c19c0fda0beb7e0d4e09e0ba74b1e4c092e0e40bfa12fe05b6f6d75ba \
-    --hash=sha256:dc9b18bf40cc75f66f40a7379f6a9513244fe33c0e8aa72e2d56b0196a7ef872 \
-    --hash=sha256:e09f3ff613345df5e8c3667da1d918f9149bd623cd9070c983c013792a9a62eb \
-    --hash=sha256:e4108df7fe9b707191e55f33efbcb2d81928e10cea45527879a4749cbe472614 \
-    --hash=sha256:e6024675e67af929088fda399b2094574609396b1decb609c55fa58b028a32a1 \
-    --hash=sha256:e70f54f1796669ef691ca07d046cd81a29cb4deb1e5f942003f401c0c4a2695d \
-    --hash=sha256:e715596e683d2ce000574bae5d07bd522c781a822866c20495e52520564f0969 \
-    --hash=sha256:e760191dd42581e023a68b758769e2da259b5d52e3103c6060ddc02c9edb8d7b \
-    --hash=sha256:ed86a35631f7bfbb28e108dd96773b9d5a6ce4811cf6ea468bb6a359b256b1e4 \
-    --hash=sha256:ee07e47c12890ef248766a6e55bd38ebfb2bb8edd4142d56db91b21ea68b7627 \
-    --hash=sha256:fa3a0128b152627161ce47201262d3140edb5a5c3da88d73a1b790a959126956 \
-    --hash=sha256:fcc8eb6d5902bb1cf6dc4f187ee3ea80a1eba0a89aba40a5cb20a5087d961357
+boto3==1.35.24 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:97fcc1a14cbc759e4ba9535ced703a99fcf652c9c4b8dfcd06f292c80551684b \
+    --hash=sha256:be7807f30f26d6c0057e45cfd09dad5968e664488bf4f9138d0bb7a0f6d8ed40
+botocore==1.35.24 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:1e59b0f14f4890c4f70bd6a58a634b9464bed1c4c6171f87c8795d974ade614b \
+    --hash=sha256:eb9ccc068255cc3d24c36693fda6aec7786db05ae6c2b13bcba66dce6a13e2e3
+certifi==2024.8.30 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:922820b53db7a7257ffbda3f597266d435245903d80737e34f8a45ff3e3230d8 \
+    --hash=sha256:bec941d2aa8195e248a60b31ff9f0558284cf01a52591ceda73ea9afffd69fd9
+cffi==1.17.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:045d61c734659cc045141be4bae381a41d89b741f795af1dd018bfb532fd0df8 \
+    --hash=sha256:0984a4925a435b1da406122d4d7968dd861c1385afe3b45ba82b750f229811e2 \
+    --hash=sha256:0e2b1fac190ae3ebfe37b979cc1ce69c81f4e4fe5746bb401dca63a9062cdaf1 \
+    --hash=sha256:0f048dcf80db46f0098ccac01132761580d28e28bc0f78ae0d58048063317e15 \
+    --hash=sha256:1257bdabf294dceb59f5e70c64a3e2f462c30c7ad68092d01bbbfb1c16b1ba36 \
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+    --hash=sha256:28b16024becceed8c6dfbc75629e27788d8a3f9030691a1dbf9821a128b22c36 \
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+    --hash=sha256:cdf5ce3acdfd1661132f2a9c19cac174758dc2352bfe37d98aa7512c6b7178b3 \
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+    --hash=sha256:d01b12eeeb4427d3110de311e1774046ad344f5b1a7403101878976ecd7a10f3 \
+    --hash=sha256:d63afe322132c194cf832bfec0dc69a99fb9bb6bbd550f161a49e9e855cc78ff \
+    --hash=sha256:da95af8214998d77a98cc14e3a3bd00aa191526343078b530ceb0bd710fb48a5 \
+    --hash=sha256:dd398dbc6773384a17fe0d3e7eeb8d1a21c2200473ee6806bb5e6a8e62bb73dd \
+    --hash=sha256:de2ea4b5833625383e464549fec1bc395c1bdeeb5f25c4a3a82b5a8c756ec22f \
+    --hash=sha256:de55b766c7aa2e2a3092c51e0483d700341182f08e67c63630d5b6f200bb28e5 \
+    --hash=sha256:df8b1c11f177bc2313ec4b2d46baec87a5f3e71fc8b45dab2ee7cae86d9aba14 \
+    --hash=sha256:e03eab0a8677fa80d646b5ddece1cbeaf556c313dcfac435ba11f107ba117b5d \
+    --hash=sha256:e221cf152cff04059d011ee126477f0d9588303eb57e88923578ace7baad17f9 \
+    --hash=sha256:e31ae45bc2e29f6b2abd0de1cc3b9d5205aa847cafaecb8af1476a609a2f6eb7 \
+    --hash=sha256:edae79245293e15384b51f88b00613ba9f7198016a5948b5dddf4917d4d26382 \
+    --hash=sha256:f1e22e8c4419538cb197e4dd60acc919d7696e5ef98ee4da4e01d3f8cfa4cc5a \
+    --hash=sha256:f3a2b4222ce6b60e2e8b337bb9596923045681d71e5a082783484d845390938e \
+    --hash=sha256:f6a16c31041f09ead72d69f583767292f750d24913dadacf5756b966aacb3f1a \
+    --hash=sha256:f75c7ab1f9e4aca5414ed4d8e5c0e303a34f4421f8a0d47a4d019ceff0ab6af4 \
+    --hash=sha256:f79fc4fc25f1c8698ff97788206bb3c2598949bfe0fef03d299eb1b5356ada99 \
+    --hash=sha256:f7f5baafcc48261359e14bcd6d9bff6d4b28d9103847c9e136694cb0501aef87 \
+    --hash=sha256:fc48c783f9c87e60831201f2cce7f3b2e4846bf4d8728eabe54d60700b318a0b
 cfgv==3.4.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:b7265b1f29fd3316bfcd2b330d63d024f2bfd8bcb8b0272f8e19a504856c48f9 \
     --hash=sha256:e52591d4c5f5dead8e0f673fb16db7949d2cfb3f7da4582893288f0ded8fe560
@@ -330,130 +372,171 @@ colorama==0.4.6 ; python_full_version >= "3.9.1" and python_version < "3.13" and
 comm==0.2.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:3fd7a84065306e07bea1773df6eb8282de51ba82f77c72f9c85716ab11fe980e \
     --hash=sha256:e6fb86cb70ff661ee8c9c14e7d36d6de3b4066f1441be4063df9c5009f0a64d3
-contourpy==1.2.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
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-coverage==7.6.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
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-    --hash=sha256:f2501d60d7497fd55e391f423f965bbe9e650e9ffc3c627d5f0ac516026000b8 \
-    --hash=sha256:f7db0b6ae1f96ae41afe626095149ecd1b212b424626175a6633c2999eaad45b
+contourpy==1.3.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:00ccd0dbaad6d804ab259820fa7cb0b8036bda0686ef844d24125d8287178ce0 \
+    --hash=sha256:0be4d8425bfa755e0fd76ee1e019636ccc7c29f77a7c86b4328a9eb6a26d0639 \
+    --hash=sha256:0dce35502151b6bd35027ac39ba6e5a44be13a68f55735c3612c568cac3805fd \
+    --hash=sha256:0fa4c02abe6c446ba70d96ece336e621efa4aecae43eaa9b030ae5fb92b309ad \
+    --hash=sha256:14e262f67bd7e6eb6880bc564dcda30b15e351a594657e55b7eec94b6ef72843 \
+    --hash=sha256:167d6c890815e1dac9536dca00828b445d5d0df4d6a8c6adb4a7ec3166812fa8 \
+    --hash=sha256:1ec4dc6bf570f5b22ed0d7efba0dfa9c5b9e0431aeea7581aa217542d9e809a4 \
+    --hash=sha256:303c252947ab4b14c08afeb52375b26781ccd6a5ccd81abcdfc1fafd14cf93c1 \
+    --hash=sha256:31cd3a85dbdf1fc002280c65caa7e2b5f65e4a973fcdf70dd2fdcb9868069294 \
+    --hash=sha256:32b238b3b3b649e09ce9aaf51f0c261d38644bdfa35cbaf7b263457850957a84 \
+    --hash=sha256:33c92cdae89ec5135d036e7218e69b0bb2851206077251f04a6c4e0e21f03927 \
+    --hash=sha256:345af746d7766821d05d72cb8f3845dfd08dd137101a2cb9b24de277d716def8 \
+    --hash=sha256:3634b5385c6716c258d0419c46d05c8aa7dc8cb70326c9a4fb66b69ad2b52e09 \
+    --hash=sha256:364174c2a76057feef647c802652f00953b575723062560498dc7930fc9b1cb7 \
+    --hash=sha256:36e0cff201bcb17a0a8ecc7f454fe078437fa6bda730e695a92f2d9932bd507f \
+    --hash=sha256:36f965570cff02b874773c49bfe85562b47030805d7d8360748f3eca570f4cab \
+    --hash=sha256:3bb3808858a9dc68f6f03d319acd5f1b8a337e6cdda197f02f4b8ff67ad2057b \
+    --hash=sha256:3e1c7fa44aaae40a2247e2e8e0627f4bea3dd257014764aa644f319a5f8600e3 \
+    --hash=sha256:3faeb2998e4fcb256542e8a926d08da08977f7f5e62cf733f3c211c2a5586223 \
+    --hash=sha256:420d39daa61aab1221567b42eecb01112908b2cab7f1b4106a52caaec8d36973 \
+    --hash=sha256:4553c421929ec95fb07b3aaca0fae668b2eb5a5203d1217ca7c34c063c53d087 \
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+    --hash=sha256:4cfb5c62ce023dfc410d6059c936dcf96442ba40814aefbfa575425a3a7f19dc \
+    --hash=sha256:4d63ee447261e963af02642ffcb864e5a2ee4cbfd78080657a9880b8b1868e18 \
+    --hash=sha256:570ef7cf892f0afbe5b2ee410c507ce12e15a5fa91017a0009f79f7d93a1268f \
+    --hash=sha256:637f674226be46f6ba372fd29d9523dd977a291f66ab2a74fbeb5530bb3f445d \
+    --hash=sha256:68a32389b06b82c2fdd68276148d7b9275b5f5cf13e5417e4252f6d1a34f72a2 \
+    --hash=sha256:69375194457ad0fad3a839b9e29aa0b0ed53bb54db1bfb6c3ae43d111c31ce41 \
+    --hash=sha256:6cb6cc968059db9c62cb35fbf70248f40994dfcd7aa10444bbf8b3faeb7c2d67 \
+    --hash=sha256:710a26b3dc80c0e4febf04555de66f5fd17e9cf7170a7b08000601a10570bda6 \
+    --hash=sha256:732896af21716b29ab3e988d4ce14bc5133733b85956316fb0c56355f398099b \
+    --hash=sha256:75ee7cb1a14c617f34a51d11fa7524173e56551646828353c4af859c56b766e2 \
+    --hash=sha256:76a896b2f195b57db25d6b44e7e03f221d32fe318d03ede41f8b4d9ba1bff53c \
+    --hash=sha256:76c905ef940a4474a6289c71d53122a4f77766eef23c03cd57016ce19d0f7b42 \
+    --hash=sha256:7a52040312b1a858b5e31ef28c2e865376a386c60c0e248370bbea2d3f3b760d \
+    --hash=sha256:7ffa0db17717a8ffb127efd0c95a4362d996b892c2904db72428d5b52e1938a4 \
+    --hash=sha256:81cb5ed4952aae6014bc9d0421dec7c5835c9c8c31cdf51910b708f548cf58e5 \
+    --hash=sha256:834e0cfe17ba12f79963861e0f908556b2cedd52e1f75e6578801febcc6a9f49 \
+    --hash=sha256:87ddffef1dbe5e669b5c2440b643d3fdd8622a348fe1983fad7a0f0ccb1cd67b \
+    --hash=sha256:880ea32e5c774634f9fcd46504bf9f080a41ad855f4fef54f5380f5133d343c7 \
+    --hash=sha256:8ca947601224119117f7c19c9cdf6b3ab54c5726ef1d906aa4a69dfb6dd58102 \
+    --hash=sha256:90f73a5116ad1ba7174341ef3ea5c3150ddf20b024b98fb0c3b29034752c8aeb \
+    --hash=sha256:92f8557cbb07415a4d6fa191f20fd9d2d9eb9c0b61d1b2f52a8926e43c6e9af7 \
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+    --hash=sha256:9c0da700bf58f6e0b65312d0a5e695179a71d0163957fa381bb3c1f72972537c \
+    --hash=sha256:a11077e395f67ffc2c44ec2418cfebed032cd6da3022a94fc227b6faf8e2acb8 \
+    --hash=sha256:aea348f053c645100612b333adc5983d87be69acdc6d77d3169c090d3b01dc35 \
+    --hash=sha256:b11b39aea6be6764f84360fce6c82211a9db32a7c7de8fa6dd5397cf1d079c3b \
+    --hash=sha256:c6c7c2408b7048082932cf4e641fa3b8ca848259212f51c8c59c45aa7ac18f14 \
+    --hash=sha256:c6ec93afeb848a0845a18989da3beca3eec2c0f852322efe21af1931147d12cb \
+    --hash=sha256:cacd81e2d4b6f89c9f8a5b69b86490152ff39afc58a95af002a398273e5ce589 \
+    --hash=sha256:d402880b84df3bec6eab53cd0cf802cae6a2ef9537e70cf75e91618a3801c20c \
+    --hash=sha256:d51fca85f9f7ad0b65b4b9fe800406d0d77017d7270d31ec3fb1cc07358fdea0 \
+    --hash=sha256:d73f659398a0904e125280836ae6f88ba9b178b2fed6884f3b1f95b989d2c8da \
+    --hash=sha256:d78ab28a03c854a873787a0a42254a0ccb3cb133c672f645c9f9c8f3ae9d0800 \
+    --hash=sha256:da84c537cb8b97d153e9fb208c221c45605f73147bd4cadd23bdae915042aad6 \
+    --hash=sha256:dbc4c3217eee163fa3984fd1567632b48d6dfd29216da3ded3d7b844a8014a66 \
+    --hash=sha256:e12968fdfd5bb45ffdf6192a590bd8ddd3ba9e58360b29683c6bb71a7b41edca \
+    --hash=sha256:e1fd23e9d01591bab45546c089ae89d926917a66dceb3abcf01f6105d927e2cb \
+    --hash=sha256:e8134301d7e204c88ed7ab50028ba06c683000040ede1d617298611f9dc6240c \
+    --hash=sha256:eb8b141bb00fa977d9122636b16aa67d37fd40a3d8b52dd837e536d64b9a4d06 \
+    --hash=sha256:eca7e17a65f72a5133bdbec9ecf22401c62bcf4821361ef7811faee695799779 \
+    --hash=sha256:f317576606de89da6b7e0861cf6061f6146ead3528acabff9236458a6ba467f8 \
+    --hash=sha256:fd2a0fc506eccaaa7595b7e1418951f213cf8255be2600f1ea1b61e46a60c55f \
+    --hash=sha256:fe41b41505a5a33aeaed2a613dccaeaa74e0e3ead6dd6fd3a118fb471644fd6c
+coverage==7.6.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:06a737c882bd26d0d6ee7269b20b12f14a8704807a01056c80bb881a4b2ce6ca \
+    --hash=sha256:07e2ca0ad381b91350c0ed49d52699b625aab2b44b65e1b4e02fa9df0e92ad2d \
+    --hash=sha256:0c0420b573964c760df9e9e86d1a9a622d0d27f417e1a949a8a66dd7bcee7bc6 \
+    --hash=sha256:0dbde0f4aa9a16fa4d754356a8f2e36296ff4d83994b2c9d8398aa32f222f989 \
+    --hash=sha256:1125ca0e5fd475cbbba3bb67ae20bd2c23a98fac4e32412883f9bcbaa81c314c \
+    --hash=sha256:13b0a73a0896988f053e4fbb7de6d93388e6dd292b0d87ee51d106f2c11b465b \
+    --hash=sha256:166811d20dfea725e2e4baa71fffd6c968a958577848d2131f39b60043400223 \
+    --hash=sha256:170d444ab405852903b7d04ea9ae9b98f98ab6d7e63e1115e82620807519797f \
+    --hash=sha256:1f4aa8219db826ce6be7099d559f8ec311549bfc4046f7f9fe9b5cea5c581c56 \
+    --hash=sha256:225667980479a17db1048cb2bf8bfb39b8e5be8f164b8f6628b64f78a72cf9d3 \
+    --hash=sha256:260933720fdcd75340e7dbe9060655aff3af1f0c5d20f46b57f262ab6c86a5e8 \
+    --hash=sha256:2bdb062ea438f22d99cba0d7829c2ef0af1d768d1e4a4f528087224c90b132cb \
+    --hash=sha256:2c09f4ce52cb99dd7505cd0fc8e0e37c77b87f46bc9c1eb03fe3bc9991085388 \
+    --hash=sha256:3115a95daa9bdba70aea750db7b96b37259a81a709223c8448fa97727d546fe0 \
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+    --hash=sha256:4421712dbfc5562150f7554f13dde997a2e932a6b5f352edcce948a815efee6f \
+    --hash=sha256:44df346d5215a8c0e360307d46ffaabe0f5d3502c8a1cefd700b34baf31d411a \
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+    --hash=sha256:5621a9175cf9d0b0c84c2ef2b12e9f5f5071357c4d2ea6ca1cf01814f45d2391 \
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+    --hash=sha256:6878ef48d4227aace338d88c48738a4258213cd7b74fd9a3d4d7582bb1d8a155 \
+    --hash=sha256:6a89ecca80709d4076b95f89f308544ec8f7b4727e8a547913a35f16717856cb \
+    --hash=sha256:6db04803b6c7291985a761004e9060b2bca08da6d04f26a7f2294b8623a0c1a0 \
+    --hash=sha256:6e2cd258d7d927d09493c8df1ce9174ad01b381d4729a9d8d4e38670ca24774c \
+    --hash=sha256:6e81d7a3e58882450ec4186ca59a3f20a5d4440f25b1cff6f0902ad890e6748a \
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+    --hash=sha256:78b260de9790fd81e69401c2dc8b17da47c8038176a79092a89cb2b7d945d060 \
+    --hash=sha256:7bb65125fcbef8d989fa1dd0e8a060999497629ca5b0efbca209588a73356232 \
+    --hash=sha256:7dea0889685db8550f839fa202744652e87c60015029ce3f60e006f8c4462c93 \
+    --hash=sha256:8284cf8c0dd272a247bc154eb6c95548722dce90d098c17a883ed36e67cdb129 \
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+    --hash=sha256:8929543a7192c13d177b770008bc4e8119f2e1f881d563fc6b6305d2d0ebe9de \
+    --hash=sha256:8ae539519c4c040c5ffd0632784e21b2f03fc1340752af711f33e5be83a9d6c6 \
+    --hash=sha256:8f59d57baca39b32db42b83b2a7ba6f47ad9c394ec2076b084c3f029b7afca23 \
+    --hash=sha256:9054a0754de38d9dbd01a46621636689124d666bad1936d76c0341f7d71bf569 \
+    --hash=sha256:953510dfb7b12ab69d20135a0662397f077c59b1e6379a768e97c59d852ee51d \
+    --hash=sha256:95cae0efeb032af8458fc27d191f85d1717b1d4e49f7cb226cf526ff28179778 \
+    --hash=sha256:9bc572be474cafb617672c43fe989d6e48d3c83af02ce8de73fff1c6bb3c198d \
+    --hash=sha256:9c56863d44bd1c4fe2abb8a4d6f5371d197f1ac0ebdee542f07f35895fc07f36 \
+    --hash=sha256:9e0b2df163b8ed01d515807af24f63de04bebcecbd6c3bfeff88385789fdf75a \
+    --hash=sha256:a09ece4a69cf399510c8ab25e0950d9cf2b42f7b3cb0374f95d2e2ff594478a6 \
+    --hash=sha256:a1ac0ae2b8bd743b88ed0502544847c3053d7171a3cff9228af618a068ed9c34 \
+    --hash=sha256:a318d68e92e80af8b00fa99609796fdbcdfef3629c77c6283566c6f02c6d6704 \
+    --hash=sha256:a4acd025ecc06185ba2b801f2de85546e0b8ac787cf9d3b06e7e2a69f925b106 \
+    --hash=sha256:a6d3adcf24b624a7b778533480e32434a39ad8fa30c315208f6d3e5542aeb6e9 \
+    --hash=sha256:a78d169acd38300060b28d600344a803628c3fd585c912cacc9ea8790fe96862 \
+    --hash=sha256:a95324a9de9650a729239daea117df21f4b9868ce32e63f8b650ebe6cef5595b \
+    --hash=sha256:abd5fd0db5f4dc9289408aaf34908072f805ff7792632250dcb36dc591d24255 \
+    --hash=sha256:b06079abebbc0e89e6163b8e8f0e16270124c154dc6e4a47b413dd538859af16 \
+    --hash=sha256:b43c03669dc4618ec25270b06ecd3ee4fa94c7f9b3c14bae6571ca00ef98b0d3 \
+    --hash=sha256:b48f312cca9621272ae49008c7f613337c53fadca647d6384cc129d2996d1133 \
+    --hash=sha256:b5d7b556859dd85f3a541db6a4e0167b86e7273e1cdc973e5b175166bb634fdb \
+    --hash=sha256:b9f222de8cded79c49bf184bdbc06630d4c58eec9459b939b4a690c82ed05657 \
+    --hash=sha256:c3c02d12f837d9683e5ab2f3d9844dc57655b92c74e286c262e0fc54213c216d \
+    --hash=sha256:c44fee9975f04b33331cb8eb272827111efc8930cfd582e0320613263ca849ca \
+    --hash=sha256:cf4b19715bccd7ee27b6b120e7e9dd56037b9c0681dcc1adc9ba9db3d417fa36 \
+    --hash=sha256:d0c212c49b6c10e6951362f7c6df3329f04c2b1c28499563d4035d964ab8e08c \
+    --hash=sha256:d3296782ca4eab572a1a4eca686d8bfb00226300dcefdf43faa25b5242ab8a3e \
+    --hash=sha256:d85f5e9a5f8b73e2350097c3756ef7e785f55bd71205defa0bfdaf96c31616ff \
+    --hash=sha256:da511e6ad4f7323ee5702e6633085fb76c2f893aaf8ce4c51a0ba4fc07580ea7 \
+    --hash=sha256:e05882b70b87a18d937ca6768ff33cc3f72847cbc4de4491c8e73880766718e5 \
+    --hash=sha256:e61c0abb4c85b095a784ef23fdd4aede7a2628478e7baba7c5e3deba61070a02 \
+    --hash=sha256:e6a08c0be454c3b3beb105c0596ebdc2371fab6bb90c0c0297f4e58fd7e1012c \
+    --hash=sha256:e9a6e0eb86070e8ccaedfbd9d38fec54864f3125ab95419970575b42af7541df \
+    --hash=sha256:ed37bd3c3b063412f7620464a9ac1314d33100329f39799255fb8d3027da50d3 \
+    --hash=sha256:f1adfc8ac319e1a348af294106bc6a8458a0f1633cc62a1446aebc30c5fa186a \
+    --hash=sha256:f5796e664fe802da4f57a168c85359a8fbf3eab5e55cd4e4569fbacecc903959 \
+    --hash=sha256:fc5a77d0c516700ebad189b587de289a20a78324bc54baee03dd486f0855d234 \
+    --hash=sha256:fd21f6ae3f08b41004dfb433fa895d858f3f5979e7762d052b12aef444e29afc
 cycler==0.12.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:85cef7cff222d8644161529808465972e51340599459b8ac3ccbac5a854e0d30 \
     --hash=sha256:88bb128f02ba341da8ef447245a9e138fae777f6a23943da4540077d3601eb1c
-debugpy==1.8.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:0600faef1d0b8d0e85c816b8bb0cb90ed94fc611f308d5fde28cb8b3d2ff0fe3 \
-    --hash=sha256:1523bc551e28e15147815d1397afc150ac99dbd3a8e64641d53425dba57b0ff9 \
-    --hash=sha256:15bc2f4b0f5e99bf86c162c91a74c0631dbd9cef3c6a1d1329c946586255e859 \
-    --hash=sha256:16c8dcab02617b75697a0a925a62943e26a0330da076e2a10437edd9f0bf3755 \
-    --hash=sha256:16e16df3a98a35c63c3ab1e4d19be4cbc7fdda92d9ddc059294f18910928e0ca \
-    --hash=sha256:2cbd4d9a2fc5e7f583ff9bf11f3b7d78dfda8401e8bb6856ad1ed190be4281ad \
-    --hash=sha256:3f8c3f7c53130a070f0fc845a0f2cee8ed88d220d6b04595897b66605df1edd6 \
-    --hash=sha256:40f062d6877d2e45b112c0bbade9a17aac507445fd638922b1a5434df34aed02 \
-    --hash=sha256:5a019d4574afedc6ead1daa22736c530712465c0c4cd44f820d803d937531b2d \
-    --hash=sha256:5d3ccd39e4021f2eb86b8d748a96c766058b39443c1f18b2dc52c10ac2757835 \
-    --hash=sha256:62658aefe289598680193ff655ff3940e2a601765259b123dc7f89c0239b8cd3 \
-    --hash=sha256:7ee2e1afbf44b138c005e4380097d92532e1001580853a7cb40ed84e0ef1c3d2 \
-    --hash=sha256:7f8d57a98c5a486c5c7824bc0b9f2f11189d08d73635c326abef268f83950326 \
-    --hash=sha256:8a13417ccd5978a642e91fb79b871baded925d4fadd4dfafec1928196292aa0a \
-    --hash=sha256:95378ed08ed2089221896b9b3a8d021e642c24edc8fef20e5d4342ca8be65c00 \
-    --hash=sha256:acdf39855f65c48ac9667b2801234fc64d46778021efac2de7e50907ab90c634 \
-    --hash=sha256:bd11fe35d6fd3431f1546d94121322c0ac572e1bfb1f6be0e9b8655fb4ea941e \
-    --hash=sha256:c78ba1680f1015c0ca7115671fe347b28b446081dada3fedf54138f44e4ba031 \
-    --hash=sha256:cf327316ae0c0e7dd81eb92d24ba8b5e88bb4d1b585b5c0d32929274a66a5210 \
-    --hash=sha256:d3408fddd76414034c02880e891ea434e9a9cf3a69842098ef92f6e809d09afa \
-    --hash=sha256:e24ccb0cd6f8bfaec68d577cb49e9c680621c336f347479b3fce060ba7c09ec1 \
-    --hash=sha256:f179af1e1bd4c88b0b9f0fa153569b24f6b6f3de33f94703336363ae62f4bf47
+debugpy==1.8.5 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:0a1029a2869d01cb777216af8c53cda0476875ef02a2b6ff8b2f2c9a4b04176c \
+    --hash=sha256:1cd04a73eb2769eb0bfe43f5bfde1215c5923d6924b9b90f94d15f207a402226 \
+    --hash=sha256:28ced650c974aaf179231668a293ecd5c63c0a671ae6d56b8795ecc5d2f48d3c \
+    --hash=sha256:345d6a0206e81eb68b1493ce2fbffd57c3088e2ce4b46592077a943d2b968ca3 \
+    --hash=sha256:3df6692351172a42af7558daa5019651f898fc67450bf091335aa8a18fbf6f3a \
+    --hash=sha256:4413b7a3ede757dc33a273a17d685ea2b0c09dbd312cc03f5534a0fd4d40750a \
+    --hash=sha256:4fbb3b39ae1aa3e5ad578f37a48a7a303dad9a3d018d369bc9ec629c1cfa7408 \
+    --hash=sha256:55919dce65b471eff25901acf82d328bbd5b833526b6c1364bd5133754777a44 \
+    --hash=sha256:5b5c770977c8ec6c40c60d6f58cacc7f7fe5a45960363d6974ddb9b62dbee156 \
+    --hash=sha256:606bccba19f7188b6ea9579c8a4f5a5364ecd0bf5a0659c8a5d0e10dcee3032a \
+    --hash=sha256:7b0fe36ed9d26cb6836b0a51453653f8f2e347ba7348f2bbfe76bfeb670bfb1c \
+    --hash=sha256:7e4d594367d6407a120b76bdaa03886e9eb652c05ba7f87e37418426ad2079f7 \
+    --hash=sha256:8f913ee8e9fcf9d38a751f56e6de12a297ae7832749d35de26d960f14280750a \
+    --hash=sha256:a697beca97dad3780b89a7fb525d5e79f33821a8bc0c06faf1f1289e549743cf \
+    --hash=sha256:ad84b7cde7fd96cf6eea34ff6c4a1b7887e0fe2ea46e099e53234856f9d99a34 \
+    --hash=sha256:b2112cfeb34b4507399d298fe7023a16656fc553ed5246536060ca7bd0e668d0 \
+    --hash=sha256:b78c1250441ce893cb5035dd6f5fc12db968cc07f91cc06996b2087f7cefdd8e \
+    --hash=sha256:c0a65b00b7cdd2ee0c2cf4c7335fef31e15f1b7056c7fdbce9e90193e1a8c8cb \
+    --hash=sha256:c9f7c15ea1da18d2fcc2709e9f3d6de98b69a5b0fff1807fb80bc55f906691f7 \
+    --hash=sha256:db9fb642938a7a609a6c865c32ecd0d795d56c1aaa7a7a5722d77855d5e77f2b \
+    --hash=sha256:dd3811bd63632bb25eda6bd73bea8e0521794cda02be41fa3160eb26fc29e7ed \
+    --hash=sha256:e84c276489e141ed0b93b0af648eef891546143d6a48f610945416453a8ad406
 decorator==5.1.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:637996211036b6385ef91435e4fae22989472f9d571faba8927ba8253acbc330 \
     --hash=sha256:b8c3f85900b9dc423225913c5aace94729fe1fa9763b38939a95226f02d37186
@@ -472,21 +555,33 @@ distro==1.9.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
 docutils==0.20.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:96f387a2c5562db4476f09f13bbab2192e764cac08ebbf3a34a95d9b1e4a59d6 \
     --hash=sha256:f08a4e276c3a1583a86dce3e34aba3fe04d02bba2dd51ed16106244e8a923e3b
+et-xmlfile==1.1.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:8eb9e2bc2f8c97e37a2dc85a09ecdcdec9d8a396530a6d5a33b30b9a92da0c5c \
+    --hash=sha256:a2ba85d1d6a74ef63837eed693bcb89c3f752169b0e3e7ae5b16ca5e1b3deada
+eval-type-backport==0.2.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:68796cfbc7371ebf923f03bdf7bef415f3ec098aeced24e054b253a0e78f7b37 \
+    --hash=sha256:ac2f73d30d40c5a30a80b8739a789d6bb5e49fdffa66d7912667e2015d9c9933
 exceptiongroup==1.2.2 ; python_full_version >= "3.9.1" and python_version < "3.11" \
     --hash=sha256:3111b9d131c238bec2f8f516e123e14ba243563fb135d3fe885990585aa7795b \
     --hash=sha256:47c2edf7c6738fafb49fd34290706d1a1a2f4d1c6df275526b62cbb4aa5393cc
 execnet==2.1.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:26dee51f1b80cebd6d0ca8e74dd8745419761d3bef34163928cbebbdc4749fdc \
     --hash=sha256:5189b52c6121c24feae288166ab41b32549c7e2348652736540b9e6e7d4e72e3
-executing==2.0.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:35afe2ce3affba8ee97f2d69927fa823b08b472b7b994e36a52a964b93d16147 \
-    --hash=sha256:eac49ca94516ccc753f9fb5ce82603156e590b27525a8bc32cce8ae302eb61bc
+executing==2.1.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:8d63781349375b5ebccc3142f4b30350c0cd9c79f921cde38be2be4637e98eaf \
+    --hash=sha256:8ea27ddd260da8150fa5a708269c4a10e76161e2496ec3e587da9e3c0fe4b9ab
+faker==29.0.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:32d0ee7d42925ff06e4a7d906ee7efbf34f5052a41a2a1eb8bb174a422a5498f \
+    --hash=sha256:34e89aec594cad9773431ca479ee95c7ce03dd9f22fda2524e2373b880a2fa77
+fastapi==0.112.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:6d4f9c3301825d4620665cace8e2bc34e303f61c05a5382d1d61a048ea7f2f37 \
+    --hash=sha256:b1f72e1f72afe7902ccd639ba320abb5d57a309804f45c10ab0ce3693cadeb33
 fastjsonschema==2.20.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:3d48fc5300ee96f5d116f10fe6f28d938e6008f59a6a025c2649475b87f76a23 \
     --hash=sha256:5875f0b0fa7a0043a91e93a9b8f793bcbbba9691e7fd83dca95c28ba26d21f0a
-filelock==3.15.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:2207938cbc1844345cb01a5a95524dae30f0ce089eba5b00378295a17e3e90cb \
-    --hash=sha256:6ca1fffae96225dab4c6eaf1c4f4f28cd2568d3ec2a44e15a08520504de468e7
+filelock==3.16.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:2082e5703d51fbf98ea75855d9d5527e33d8ff23099bec374a134febee6946b0 \
+    --hash=sha256:c249fbfcd5db47e5e2d6d62198e565475ee65e4831e2561c8e313fa7eb961435
 fonttools==4.53.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:02569e9a810f9d11f4ae82c391ebc6fb5730d95a0657d24d754ed7763fb2d122 \
     --hash=sha256:0679a30b59d74b6242909945429dbddb08496935b82f91ea9bf6ad240ec23397 \
@@ -611,98 +706,116 @@ frozenlist==1.4.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:fbeb989b5cc29e8daf7f976b421c220f1b8c731cbf22b9130d8815418ea45887 \
     --hash=sha256:fde5bd59ab5357e3853313127f4d3565fc7dad314a74d7b5d43c22c6a5ed2ced \
     --hash=sha256:fe1a06da377e3a1062ae5fe0926e12b84eceb8a50b350ddca72dc85015873f74
-fsspec==2024.6.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:3cb443f8bcd2efb31295a5b9fdb02aee81d8452c80d28f97a6d0959e6cee101e \
-    --hash=sha256:fad7d7e209dd4c1208e3bbfda706620e0da5142bebbd9c384afb95b07e798e49
+fsspec==2024.9.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:4b0afb90c2f21832df142f292649035d80b421f60a9e1c027802e5a0da2b04e8 \
+    --hash=sha256:a0947d552d8a6efa72cc2c730b12c41d043509156966cca4fb157b0f2a0c574b
 gprof2dot==2024.6.6 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:45b14ad7ce64e299c8f526881007b9eb2c6b75505d5613e96e66ee4d5ab33696 \
     --hash=sha256:fa1420c60025a9eb7734f65225b4da02a10fc6dd741b37fa129bc6b41951e5ab
-greenlet==3.0.3 ; python_version < "3.13" and (platform_machine == "aarch64" or platform_machine == "ppc64le" or platform_machine == "x86_64" or platform_machine == "amd64" or platform_machine == "AMD64" or platform_machine == "win32" or platform_machine == "WIN32") and python_full_version >= "3.9.1" \
-    --hash=sha256:01bc7ea167cf943b4c802068e178bbf70ae2e8c080467070d01bfa02f337ee67 \
-    --hash=sha256:0448abc479fab28b00cb472d278828b3ccca164531daab4e970a0458786055d6 \
-    --hash=sha256:086152f8fbc5955df88382e8a75984e2bb1c892ad2e3c80a2508954e52295257 \
-    --hash=sha256:098d86f528c855ead3479afe84b49242e174ed262456c342d70fc7f972bc13c4 \
-    --hash=sha256:149e94a2dd82d19838fe4b2259f1b6b9957d5ba1b25640d2380bea9c5df37676 \
-    --hash=sha256:1551a8195c0d4a68fac7a4325efac0d541b48def35feb49d803674ac32582f61 \
-    --hash=sha256:15d79dd26056573940fcb8c7413d84118086f2ec1a8acdfa854631084393efcc \
-    --hash=sha256:1996cb9306c8595335bb157d133daf5cf9f693ef413e7673cb07e3e5871379ca \
-    --hash=sha256:1a7191e42732df52cb5f39d3527217e7ab73cae2cb3694d241e18f53d84ea9a7 \
-    --hash=sha256:1ea188d4f49089fc6fb283845ab18a2518d279c7cd9da1065d7a84e991748728 \
-    --hash=sha256:1f672519db1796ca0d8753f9e78ec02355e862d0998193038c7073045899f305 \
-    --hash=sha256:2516a9957eed41dd8f1ec0c604f1cdc86758b587d964668b5b196a9db5bfcde6 \
-    --hash=sha256:2797aa5aedac23af156bbb5a6aa2cd3427ada2972c828244eb7d1b9255846379 \
-    --hash=sha256:2dd6e660effd852586b6a8478a1d244b8dc90ab5b1321751d2ea15deb49ed414 \
-    --hash=sha256:3ddc0f794e6ad661e321caa8d2f0a55ce01213c74722587256fb6566049a8b04 \
-    --hash=sha256:3ed7fb269f15dc662787f4119ec300ad0702fa1b19d2135a37c2c4de6fadfd4a \
-    --hash=sha256:419b386f84949bf0e7c73e6032e3457b82a787c1ab4a0e43732898a761cc9dbf \
-    --hash=sha256:43374442353259554ce33599da8b692d5aa96f8976d567d4badf263371fbe491 \
-    --hash=sha256:52f59dd9c96ad2fc0d5724107444f76eb20aaccb675bf825df6435acb7703559 \
-    --hash=sha256:57e8974f23e47dac22b83436bdcf23080ade568ce77df33159e019d161ce1d1e \
-    --hash=sha256:5b51e85cb5ceda94e79d019ed36b35386e8c37d22f07d6a751cb659b180d5274 \
-    --hash=sha256:649dde7de1a5eceb258f9cb00bdf50e978c9db1b996964cd80703614c86495eb \
-    --hash=sha256:64d7675ad83578e3fc149b617a444fab8efdafc9385471f868eb5ff83e446b8b \
-    --hash=sha256:68834da854554926fbedd38c76e60c4a2e3198c6fbed520b106a8986445caaf9 \
-    --hash=sha256:6b66c9c1e7ccabad3a7d037b2bcb740122a7b17a53734b7d72a344ce39882a1b \
-    --hash=sha256:70fb482fdf2c707765ab5f0b6655e9cfcf3780d8d87355a063547b41177599be \
-    --hash=sha256:7170375bcc99f1a2fbd9c306f5be8764eaf3ac6b5cb968862cad4c7057756506 \
-    --hash=sha256:73a411ef564e0e097dbe7e866bb2dda0f027e072b04da387282b02c308807405 \
-    --hash=sha256:77457465d89b8263bca14759d7c1684df840b6811b2499838cc5b040a8b5b113 \
-    --hash=sha256:7f362975f2d179f9e26928c5b517524e89dd48530a0202570d55ad6ca5d8a56f \
-    --hash=sha256:81bb9c6d52e8321f09c3d165b2a78c680506d9af285bfccbad9fb7ad5a5da3e5 \
-    --hash=sha256:881b7db1ebff4ba09aaaeae6aa491daeb226c8150fc20e836ad00041bcb11230 \
-    --hash=sha256:894393ce10ceac937e56ec00bb71c4c2f8209ad516e96033e4b3b1de270e200d \
-    --hash=sha256:99bf650dc5d69546e076f413a87481ee1d2d09aaaaaca058c9251b6d8c14783f \
-    --hash=sha256:9da2bd29ed9e4f15955dd1595ad7bc9320308a3b766ef7f837e23ad4b4aac31a \
-    --hash=sha256:afaff6cf5200befd5cec055b07d1c0a5a06c040fe5ad148abcd11ba6ab9b114e \
-    --hash=sha256:b1b5667cced97081bf57b8fa1d6bfca67814b0afd38208d52538316e9422fc61 \
-    --hash=sha256:b37eef18ea55f2ffd8f00ff8fe7c8d3818abd3e25fb73fae2ca3b672e333a7a6 \
-    --hash=sha256:b542be2440edc2d48547b5923c408cbe0fc94afb9f18741faa6ae970dbcb9b6d \
-    --hash=sha256:b7dcbe92cc99f08c8dd11f930de4d99ef756c3591a5377d1d9cd7dd5e896da71 \
-    --hash=sha256:b7f009caad047246ed379e1c4dbcb8b020f0a390667ea74d2387be2998f58a22 \
-    --hash=sha256:bba5387a6975598857d86de9eac14210a49d554a77eb8261cc68b7d082f78ce2 \
-    --hash=sha256:c5e1536de2aad7bf62e27baf79225d0d64360d4168cf2e6becb91baf1ed074f3 \
-    --hash=sha256:c5ee858cfe08f34712f548c3c363e807e7186f03ad7a5039ebadb29e8c6be067 \
-    --hash=sha256:c9db1c18f0eaad2f804728c67d6c610778456e3e1cc4ab4bbd5eeb8e6053c6fc \
-    --hash=sha256:d353cadd6083fdb056bb46ed07e4340b0869c305c8ca54ef9da3421acbdf6881 \
-    --hash=sha256:d46677c85c5ba00a9cb6f7a00b2bfa6f812192d2c9f7d9c4f6a55b60216712f3 \
-    --hash=sha256:d4d1ac74f5c0c0524e4a24335350edad7e5f03b9532da7ea4d3c54d527784f2e \
-    --hash=sha256:d73a9fe764d77f87f8ec26a0c85144d6a951a6c438dfe50487df5595c6373eac \
-    --hash=sha256:da70d4d51c8b306bb7a031d5cff6cc25ad253affe89b70352af5f1cb68e74b53 \
-    --hash=sha256:daf3cb43b7cf2ba96d614252ce1684c1bccee6b2183a01328c98d36fcd7d5cb0 \
-    --hash=sha256:dca1e2f3ca00b84a396bc1bce13dd21f680f035314d2379c4160c98153b2059b \
-    --hash=sha256:dd4f49ae60e10adbc94b45c0b5e6a179acc1736cf7a90160b404076ee283cf83 \
-    --hash=sha256:e1f145462f1fa6e4a4ae3c0f782e580ce44d57c8f2c7aae1b6fa88c0b2efdb41 \
-    --hash=sha256:e3391d1e16e2a5a1507d83e4a8b100f4ee626e8eca43cf2cadb543de69827c4c \
-    --hash=sha256:fcd2469d6a2cf298f198f0487e0a5b1a47a42ca0fa4dfd1b6862c999f018ebbf \
-    --hash=sha256:fd096eb7ffef17c456cfa587523c5f92321ae02427ff955bebe9e3c63bc9f0da \
-    --hash=sha256:fe754d231288e1e64323cfad462fcee8f0288654c10bdf4f603a39ed923bef33
+greenlet==3.1.1 ; python_version < "3.13" and (platform_machine == "aarch64" or platform_machine == "ppc64le" or platform_machine == "x86_64" or platform_machine == "amd64" or platform_machine == "AMD64" or platform_machine == "win32" or platform_machine == "WIN32") and python_full_version >= "3.9.1" \
+    --hash=sha256:0153404a4bb921f0ff1abeb5ce8a5131da56b953eda6e14b88dc6bbc04d2049e \
+    --hash=sha256:03a088b9de532cbfe2ba2034b2b85e82df37874681e8c470d6fb2f8c04d7e4b7 \
+    --hash=sha256:04b013dc07c96f83134b1e99888e7a79979f1a247e2a9f59697fa14b5862ed01 \
+    --hash=sha256:05175c27cb459dcfc05d026c4232f9de8913ed006d42713cb8a5137bd49375f1 \
+    --hash=sha256:09fc016b73c94e98e29af67ab7b9a879c307c6731a2c9da0db5a7d9b7edd1159 \
+    --hash=sha256:0bbae94a29c9e5c7e4a2b7f0aae5c17e8e90acbfd3bf6270eeba60c39fce3563 \
+    --hash=sha256:0fde093fb93f35ca72a556cf72c92ea3ebfda3d79fc35bb19fbe685853869a83 \
+    --hash=sha256:1443279c19fca463fc33e65ef2a935a5b09bb90f978beab37729e1c3c6c25fe9 \
+    --hash=sha256:1776fd7f989fc6b8d8c8cb8da1f6b82c5814957264d1f6cf818d475ec2bf6395 \
+    --hash=sha256:1d3755bcb2e02de341c55b4fca7a745a24a9e7212ac953f6b3a48d117d7257aa \
+    --hash=sha256:23f20bb60ae298d7d8656c6ec6db134bca379ecefadb0b19ce6f19d1f232a942 \
+    --hash=sha256:275f72decf9932639c1c6dd1013a1bc266438eb32710016a1c742df5da6e60a1 \
+    --hash=sha256:2846930c65b47d70b9d178e89c7e1a69c95c1f68ea5aa0a58646b7a96df12441 \
+    --hash=sha256:3319aa75e0e0639bc15ff54ca327e8dc7a6fe404003496e3c6925cd3142e0e22 \
+    --hash=sha256:346bed03fe47414091be4ad44786d1bd8bef0c3fcad6ed3dee074a032ab408a9 \
+    --hash=sha256:36b89d13c49216cadb828db8dfa6ce86bbbc476a82d3a6c397f0efae0525bdd0 \
+    --hash=sha256:37b9de5a96111fc15418819ab4c4432e4f3c2ede61e660b1e33971eba26ef9ba \
+    --hash=sha256:396979749bd95f018296af156201d6211240e7a23090f50a8d5d18c370084dc3 \
+    --hash=sha256:3b2813dc3de8c1ee3f924e4d4227999285fd335d1bcc0d2be6dc3f1f6a318ec1 \
+    --hash=sha256:411f015496fec93c1c8cd4e5238da364e1da7a124bcb293f085bf2860c32c6f6 \
+    --hash=sha256:47da355d8687fd65240c364c90a31569a133b7b60de111c255ef5b606f2ae291 \
+    --hash=sha256:48ca08c771c268a768087b408658e216133aecd835c0ded47ce955381105ba39 \
+    --hash=sha256:4afe7ea89de619adc868e087b4d2359282058479d7cfb94970adf4b55284574d \
+    --hash=sha256:4ce3ac6cdb6adf7946475d7ef31777c26d94bccc377e070a7986bd2d5c515467 \
+    --hash=sha256:4ead44c85f8ab905852d3de8d86f6f8baf77109f9da589cb4fa142bd3b57b475 \
+    --hash=sha256:54558ea205654b50c438029505def3834e80f0869a70fb15b871c29b4575ddef \
+    --hash=sha256:5e06afd14cbaf9e00899fae69b24a32f2196c19de08fcb9f4779dd4f004e5e7c \
+    --hash=sha256:62ee94988d6b4722ce0028644418d93a52429e977d742ca2ccbe1c4f4a792511 \
+    --hash=sha256:63e4844797b975b9af3a3fb8f7866ff08775f5426925e1e0bbcfe7932059a12c \
+    --hash=sha256:6510bf84a6b643dabba74d3049ead221257603a253d0a9873f55f6a59a65f822 \
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+    --hash=sha256:7017b2be767b9d43cc31416aba48aab0d2309ee31b4dbf10a1d38fb7972bdf9d \
+    --hash=sha256:7124e16b4c55d417577c2077be379514321916d5790fa287c9ed6f23bd2ffd01 \
+    --hash=sha256:73aaad12ac0ff500f62cebed98d8789198ea0e6f233421059fa68a5aa7220145 \
+    --hash=sha256:77c386de38a60d1dfb8e55b8c1101d68c79dfdd25c7095d51fec2dd800892b80 \
+    --hash=sha256:7876452af029456b3f3549b696bb36a06db7c90747740c5302f74a9e9fa14b13 \
+    --hash=sha256:7939aa3ca7d2a1593596e7ac6d59391ff30281ef280d8632fa03d81f7c5f955e \
+    --hash=sha256:8320f64b777d00dd7ccdade271eaf0cad6636343293a25074cc5566160e4de7b \
+    --hash=sha256:85f3ff71e2e60bd4b4932a043fbbe0f499e263c628390b285cb599154a3b03b1 \
+    --hash=sha256:8b8b36671f10ba80e159378df9c4f15c14098c4fd73a36b9ad715f057272fbef \
+    --hash=sha256:93147c513fac16385d1036b7e5b102c7fbbdb163d556b791f0f11eada7ba65dc \
+    --hash=sha256:935e943ec47c4afab8965954bf49bfa639c05d4ccf9ef6e924188f762145c0ff \
+    --hash=sha256:94b6150a85e1b33b40b1464a3f9988dcc5251d6ed06842abff82e42632fac120 \
+    --hash=sha256:94ebba31df2aa506d7b14866fed00ac141a867e63143fe5bca82a8e503b36437 \
+    --hash=sha256:95ffcf719966dd7c453f908e208e14cde192e09fde6c7186c8f1896ef778d8cd \
+    --hash=sha256:98884ecf2ffb7d7fe6bd517e8eb99d31ff7855a840fa6d0d63cd07c037f6a981 \
+    --hash=sha256:99cfaa2110534e2cf3ba31a7abcac9d328d1d9f1b95beede58294a60348fba36 \
+    --hash=sha256:9e8f8c9cb53cdac7ba9793c276acd90168f416b9ce36799b9b885790f8ad6c0a \
+    --hash=sha256:a0dfc6c143b519113354e780a50381508139b07d2177cb6ad6a08278ec655798 \
+    --hash=sha256:b2795058c23988728eec1f36a4e5e4ebad22f8320c85f3587b539b9ac84128d7 \
+    --hash=sha256:b42703b1cf69f2aa1df7d1030b9d77d3e584a70755674d60e710f0af570f3761 \
+    --hash=sha256:b7cede291382a78f7bb5f04a529cb18e068dd29e0fb27376074b6d0317bf4dd0 \
+    --hash=sha256:b8a678974d1f3aa55f6cc34dc480169d58f2e6d8958895d68845fa4ab566509e \
+    --hash=sha256:b8da394b34370874b4572676f36acabac172602abf054cbc4ac910219f3340af \
+    --hash=sha256:c3a701fe5a9695b238503ce5bbe8218e03c3bcccf7e204e455e7462d770268aa \
+    --hash=sha256:c4aab7f6381f38a4b42f269057aee279ab0fc7bf2e929e3d4abfae97b682a12c \
+    --hash=sha256:ca9d0ff5ad43e785350894d97e13633a66e2b50000e8a183a50a88d834752d42 \
+    --hash=sha256:d0028e725ee18175c6e422797c407874da24381ce0690d6b9396c204c7f7276e \
+    --hash=sha256:d21e10da6ec19b457b82636209cbe2331ff4306b54d06fa04b7c138ba18c8a81 \
+    --hash=sha256:d5e975ca70269d66d17dd995dafc06f1b06e8cb1ec1e9ed54c1d1e4a7c4cf26e \
+    --hash=sha256:da7a9bff22ce038e19bf62c4dd1ec8391062878710ded0a845bcf47cc0200617 \
+    --hash=sha256:db32b5348615a04b82240cc67983cb315309e88d444a288934ee6ceaebcad6cc \
+    --hash=sha256:dcc62f31eae24de7f8dce72134c8651c58000d3b1868e01392baea7c32c247de \
+    --hash=sha256:dfc59d69fc48664bc693842bd57acfdd490acafda1ab52c7836e3fc75c90a111 \
+    --hash=sha256:e347b3bfcf985a05e8c0b7d462ba6f15b1ee1c909e2dcad795e49e91b152c383 \
+    --hash=sha256:e4d333e558953648ca09d64f13e6d8f0523fa705f51cae3f03b5983489958c70 \
+    --hash=sha256:ed10eac5830befbdd0c32f83e8aa6288361597550ba669b04c48f0f9a2c843c6 \
+    --hash=sha256:efc0f674aa41b92da8c49e0346318c6075d734994c3c4e4430b1c3f853e498e4 \
+    --hash=sha256:f1695e76146579f8c06c1509c7ce4dfe0706f49c6831a817ac04eebb2fd02011 \
+    --hash=sha256:f1d4aeb8891338e60d1ab6127af1fe45def5259def8094b9c7e34690c8858803 \
+    --hash=sha256:f406b22b7c9a9b4f8aa9d2ab13d6ae0ac3e85c9a809bd590ad53fed2bf70dc79 \
+    --hash=sha256:f6ff3b14f2df4c41660a7dec01045a045653998784bf8cfcb5a525bdffffbc8f
+groq==0.9.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:130ed5e35d3acfaab46b9e7a078eeaebf91052f4a9d71f86f87fb319b5fec332 \
+    --hash=sha256:d0e46f4ad645504672bb09c8100af3ced3a7db0d5119dc13e4aca535fc455874
 h11==0.14.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:8f19fbbe99e72420ff35c00b27a34cb9937e902a8b810e2c88300c6f0a3b699d \
     --hash=sha256:e3fe4ac4b851c468cc8363d500db52c2ead036020723024a109d37346efaa761
 httpcore==1.0.5 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:34a38e2f9291467ee3b44e89dd52615370e152954ba21721378a87b2960f7a61 \
     --hash=sha256:421f18bac248b25d310f3cacd198d55b8e6125c107797b609ff9b7a6ba7991b5
-httpx==0.27.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:71d5465162c13681bff01ad59b2cc68dd838ea1f10e51574bac27103f00c91a5 \
-    --hash=sha256:a0cb88a46f32dc874e04ee956e4c2764aba2aa228f650b06788ba6bda2962ab5
-huggingface-hub==0.24.5 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:7b45d6744dd53ce9cbf9880957de00e9d10a9ae837f1c9b7255fc8fa4e8264f3 \
-    --hash=sha256:d93fb63b1f1a919a22ce91a14518974e81fc4610bf344dfe7572343ce8d3aced
-identify==2.6.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:cb171c685bdc31bcc4c1734698736a7d5b6c8bf2e0c15117f4d469c8640ae5cf \
-    --hash=sha256:e79ae4406387a9d300332b5fd366d8994f1525e8414984e1a59e058b2eda2dd0
-idna==3.7 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:028ff3aadf0609c1fd278d8ea3089299412a7a8b9bd005dd08b9f8285bcb5cfc \
-    --hash=sha256:82fee1fc78add43492d3a1898bfa6d8a904cc97d8427f683ed8e798d07761aa0
+httpx==0.27.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:7bb2708e112d8fdd7829cd4243970f0c223274051cb35ee80c03301ee29a3df0 \
+    --hash=sha256:f7c2be1d2f3c3c3160d441802406b206c2b76f5947b11115e6df10c6c65e66c2
+huggingface-hub==0.25.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:e2f357b35d72d5012cfd127108c4e14abcd61ba4ebc90a5a374dc2456cb34e12 \
+    --hash=sha256:fb5fbe6c12fcd99d187ec7db95db9110fb1a20505f23040a5449a717c1a0db4d
+identify==2.6.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:53863bcac7caf8d2ed85bd20312ea5dcfc22226800f6d6881f232d861db5a8f0 \
+    --hash=sha256:91478c5fb7c3aac5ff7bf9b4344f803843dc586832d5f110d672b19aa1984c98
+idna==3.10 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9 \
+    --hash=sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3
 imagesize==1.4.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:0d8d18d08f840c19d0ee7ca1fd82490fdc3729b7ac93f49870406ddde8ef8d8b \
     --hash=sha256:69150444affb9cb0d5cc5a92b3676f0b2fb7cd9ae39e947a5e11a36b4497cd4a
-importlib-metadata==8.2.0 ; python_full_version >= "3.9.1" and python_version < "3.10" \
-    --hash=sha256:11901fa0c2f97919b288679932bb64febaeacf289d18ac84dd68cb2e74213369 \
-    --hash=sha256:72e8d4399996132204f9a16dcc751af254a48f8d1b20b9ff0f98d4a8f901e73d
-importlib-resources==6.4.0 ; python_full_version >= "3.9.1" and python_version < "3.10" \
-    --hash=sha256:50d10f043df931902d4194ea07ec57960f66a80449ff867bfe782b4c486ba78c \
-    --hash=sha256:cdb2b453b8046ca4e3798eb1d84f3cce1446a0e8e7b5ef4efb600f19fc398145
+importlib-metadata==8.5.0 ; python_full_version >= "3.9.1" and python_version < "3.10" \
+    --hash=sha256:45e54197d28b7a7f1559e60b95e7c567032b602131fbd588f1497f47880aa68b \
+    --hash=sha256:71522656f0abace1d072b9e5481a48f07c138e00f079c38c8f883823f9c26bd7
+importlib-resources==6.4.5 ; python_full_version >= "3.9.1" and python_version < "3.10" \
+    --hash=sha256:980862a1d16c9e147a59603677fa2aa5fd82b87f223b6cb870695bcfce830065 \
+    --hash=sha256:ac29d5f956f01d5e4bb63102a5a19957f1b9175e45649977264a1416783bb717
 iniconfig==2.0.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3 \
     --hash=sha256:b6a85871a79d2e3b22d2d1b94ac2824226a63c6b741c88f7ae975f18b6778374
@@ -712,9 +825,12 @@ ipykernel==6.29.5 ; python_full_version >= "3.9.1" and python_version < "3.13" \
 ipython==8.18.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:ca6f079bb33457c66e233e4580ebfc4128855b4cf6370dddd73842a9563e8a27 \
     --hash=sha256:e8267419d72d81955ec1177f8a29aaa90ac80ad647499201119e2f05e99aa397
-ipywidgets==8.1.3 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:efafd18f7a142248f7cb0ba890a68b96abd4d6e88ddbda483c9130d12667eaf2 \
-    --hash=sha256:f5f9eeaae082b1823ce9eac2575272952f40d748893972956dc09700a6392d9c
+ipywidgets==8.1.5 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:3290f526f87ae6e77655555baba4f36681c555b8bdbbff430b70e52c34c86245 \
+    --hash=sha256:870e43b1a35656a80c18c9503bbf2d16802db1cb487eec6fab27d683381dde17
+isodate==0.6.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:0751eece944162659049d35f4f549ed815792b38793f07cf73381c1c87cbed96 \
+    --hash=sha256:48c5881de7e8b0a0d648cb024c8062dc84e7b840ed81e864c7614fd3c127bde9
 isoduration==20.11.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:ac2f9015137935279eac671f94f89eb00584f940f5dc49462a0c4ee692ba1bd9 \
     --hash=sha256:b2904c2a4228c3d44f409c8ae8e2370eb21a26f7ac2ec5446df141dde3452042
@@ -727,9 +843,80 @@ jedi==0.19.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
 jinja2==3.1.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:4a3aee7acbbe7303aede8e9648d13b8bf88a429282aa6122a993f0ac800cb369 \
     --hash=sha256:bc5dd2abb727a5319567b7a813e6a2e7318c39f4f487cfe6c89c6f9c7d25197d
+jiter==0.5.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:044f2f1148b5248ad2c8c3afb43430dccf676c5a5834d2f5089a4e6c5bbd64df \
+    --hash=sha256:04d461ad0aebf696f8da13c99bc1b3e06f66ecf6cfd56254cc402f6385231c06 \
+    --hash=sha256:0af3838cfb7e6afee3f00dc66fa24695199e20ba87df26e942820345b0afc566 \
+    --hash=sha256:1c834133e59a8521bc87ebcad773608c6fa6ab5c7a022df24a45030826cf10bc \
+    --hash=sha256:1d916ba875bcab5c5f7d927df998c4cb694d27dceddf3392e58beaf10563368a \
+    --hash=sha256:1ece0a115c05efca597c6d938f88c9357c843f8c245dbbb53361a1c01afd7148 \
+    --hash=sha256:26351cc14507bdf466b5f99aba3df3143a59da75799bf64a53a3ad3155ecded9 \
+    --hash=sha256:2a063f71c4b06225543dddadbe09d203dc0c95ba352d8b85f1221173480a71d5 \
+    --hash=sha256:2cec323a853c24fd0472517113768c92ae0be8f8c384ef4441d3632da8baa646 \
+    --hash=sha256:308fce789a2f093dca1ff91ac391f11a9f99c35369117ad5a5c6c4903e1b3e3a \
+    --hash=sha256:335942557162ad372cc367ffaf93217117401bf930483b4b3ebdb1223dbddfa7 \
+    --hash=sha256:368084d8d5c4fc40ff7c3cc513c4f73e02c85f6009217922d0823a48ee7adf61 \
+    --hash=sha256:44dfc9ddfb9b51a5626568ef4e55ada462b7328996294fe4d36de02fce42721f \
+    --hash=sha256:462a52be85b53cd9bffd94e2d788a09984274fe6cebb893d6287e1c296d50653 \
+    --hash=sha256:4829df14d656b3fb87e50ae8b48253a8851c707da9f30d45aacab2aa2ba2d614 \
+    --hash=sha256:489875bf1a0ffb3cb38a727b01e6673f0f2e395b2aad3c9387f94187cb214bbf \
+    --hash=sha256:503b2c27d87dfff5ab717a8200fbbcf4714516c9d85558048b1fc14d2de7d8dc \
+    --hash=sha256:5206144578831a6de278a38896864ded4ed96af66e1e63ec5dd7f4a1fce38a3a \
+    --hash=sha256:5280e68e7740c8c128d3ae5ab63335ce6d1fb6603d3b809637b11713487af9e6 \
+    --hash=sha256:528d742dcde73fad9d63e8242c036ab4a84389a56e04efd854062b660f559544 \
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+    --hash=sha256:583c57fc30cc1fec360e66323aadd7fc3edeec01289bfafc35d3b9dcb29495e4 \
+    --hash=sha256:63314832e302cc10d8dfbda0333a384bf4bcfce80d65fe99b0f3c0da8945a91a \
+    --hash=sha256:649b0ee97a6e6da174bffcb3c8c051a5935d7d4f2f52ea1583b5b3e7822fbf14 \
+    --hash=sha256:6baa88334e7af3f4d7a5c66c3a63808e5efbc3698a1c57626541ddd22f8e4fbf \
+    --hash=sha256:6d1f3d27cce923713933a844872d213d244e09b53ec99b7a7fdf73d543529d6d \
+    --hash=sha256:6f1223f88b6d76b519cb033a4d3687ca157c272ec5d6015c322fc5b3074d8a5e \
+    --hash=sha256:6f433a4169ad22fcb550b11179bb2b4fd405de9b982601914ef448390b2954f3 \
+    --hash=sha256:702e3520384c88b6e270c55c772d4bd6d7b150608dcc94dea87ceba1b6391248 \
+    --hash=sha256:7f5ad4a7c6b0d90776fdefa294f662e8a86871e601309643de30bf94bb93a64e \
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+    --hash=sha256:8cf80e5fe6ab582c82f0c3331df27a7e1565e2dcf06265afd5173d809cdbf9ba \
+    --hash=sha256:8ea18e01f785c6667ca15407cd6dabbe029d77474d53595a189bdc813347218e \
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+    --hash=sha256:a25fbd8a5a58061e433d6fae6d5298777c0814a8bcefa1e5ecfff20c594bd749 \
+    --hash=sha256:a42a4bdcf7307b86cb863b2fb9bb55029b422d8f86276a50487982d99eed7c6e \
+    --hash=sha256:a586832f70c3f1481732919215f36d41c59ca080fa27a65cf23d9490e75b2ef5 \
+    --hash=sha256:aa1db0967130b5cab63dfe4d6ff547c88b2a394c3410db64744d491df7f069bb \
+    --hash=sha256:aa9d2b85b2ed7dc7697597dcfaac66e63c1b3028652f751c81c65a9f220899ae \
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+    --hash=sha256:acc0d5b8b3dd12e91dd184b87273f864b363dfabc90ef29a1092d269f18c7e28 \
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+    --hash=sha256:b250ca2594f5599ca82ba7e68785a669b352156260c5362ea1b4e04a0f3e2389 \
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+    --hash=sha256:b599f4e89b3def9a94091e6ee52e1d7ad7bc33e238ebb9c4c63f211d74822c3f \
+    --hash=sha256:c22541f0b672f4d741382a97c65609332a783501551445ab2df137ada01e019e \
+    --hash=sha256:c451f7922992751a936b96c5f5b9bb9312243d9b754c34b33d0cb72c84669f4e \
+    --hash=sha256:c59614b225d9f434ea8fc0d0bec51ef5fa8c83679afedc0433905994fb36d631 \
+    --hash=sha256:c6f16e21276074a12d8421692515b3fd6d2ea9c94fd0734c39a12960a20e85f3 \
+    --hash=sha256:c95980207b3998f2c3b3098f357994d3fd7661121f30669ca7cb945f09510a87 \
+    --hash=sha256:cccd3af9c48ac500c95e1bcbc498020c87e1781ff0345dd371462d67b76643eb \
+    --hash=sha256:ce03f7b4129eb72f1687fa11300fbf677b02990618428934662406d2a76742a1 \
+    --hash=sha256:d4c8e1ed0ef31ad29cae5ea16b9e41529eb50a7fba70600008e9f8de6376d553 \
+    --hash=sha256:e3bbe3910c724b877846186c25fe3c802e105a2c1fc2b57d6688b9f8772026e4 \
+    --hash=sha256:e6375923c5f19888c9226582a124b77b622f8fd0018b843c45eeb19d9701c403 \
+    --hash=sha256:ea189db75f8eca08807d02ae27929e890c7d47599ce3d0a6a5d41f2419ecf338 \
+    --hash=sha256:f04bc2fc50dc77be9d10f73fcc4e39346402ffe21726ff41028f36e179b587e6 \
+    --hash=sha256:f16ca8f10e62f25fd81d5310e852df6649af17824146ca74647a018424ddeccf \
+    --hash=sha256:f4be354c5de82157886ca7f5925dbda369b77344b4b4adf2723079715f823989
+jmespath==1.0.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:02e2e4cc71b5bcab88332eebf907519190dd9e6e82107fa7f83b1003a6252980 \
+    --hash=sha256:90261b206d6defd58fdd5e85f478bf633a2901798906be2ad389150c5c60edbe
+json-repair==0.28.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:b3e138735b25773a7c02b42498c80aa7d6b7aec168a3ee100473f7c5e22334e5 \
+    --hash=sha256:b7f1c48d8bc9e18a24e2b05459e8afb0a82cade5a242382422a9b065a6762578
 json5==0.9.25 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:34ed7d834b1341a86987ed52f3f76cd8ee184394906b6e22a1e0deb9ab294e8f \
     --hash=sha256:548e41b9be043f9426776f05df8635a00fe06104ea51ed24b67f908856e151ae
+jsonpath-python==1.0.6 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:1e3b78df579f5efc23565293612decee04214609208a2335884b3ee3f786b575 \
+    --hash=sha256:dd5be4a72d8a2995c3f583cf82bf3cd1a9544cfdabf2d22595b67aff07349666
 jsonpointer==3.0.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:13e088adc14fca8b6aa8177c044e12701e6ad4b28ff10e65f2267a90109c9942 \
     --hash=sha256:2b2d729f2091522d61c3b31f82e11870f60b68f43fbc705cb76bf4b832af59ef
@@ -742,9 +929,9 @@ jsonschema==4.23.0 ; python_full_version >= "3.9.1" and python_version < "3.13"
 jsonschema[format-nongpl]==4.23.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:d71497fef26351a33265337fa77ffeb82423f3ea21283cd9467bb03999266bc4 \
     --hash=sha256:fbadb6f8b144a8f8cf9f0b89ba94501d143e50411a1278633f56a7acf7fd5566
-jupyter-client==8.6.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:2bda14d55ee5ba58552a8c53ae43d215ad9868853489213f37da060ced54d8df \
-    --hash=sha256:50cbc5c66fd1b8f65ecb66bc490ab73217993632809b6e505687de18e9dea39f
+jupyter-client==8.6.3 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:35b3a0947c4a6e9d589eb97d7d4cd5e90f910ee73101611f01283732bd6d9419 \
+    --hash=sha256:e8a19cc986cc45905ac3362915f410f3af85424b4c0905e94fa5f2cb08e8f23f
 jupyter-console==6.6.3 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:309d33409fcc92ffdad25f0bcdf9a4a9daa61b6f341177570fdac03de5352485 \
     --hash=sha256:566a4bf31c87adbfadf22cdf846e3069b59a71ed5da71d6ba4d8aaad14a53539
@@ -763,270 +950,275 @@ jupyter-server-terminals==0.5.3 ; python_full_version >= "3.9.1" and python_vers
 jupyter-server==2.14.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
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     --hash=sha256:66095021aa9638ced276c248b1d81862e4c50f292d575920bbe960de1c56b12b
-jupyter==1.0.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:3e1f86076bbb7c8c207829390305a2b1fe836d471ed54be66a3b8c41e7f46cc7 \
-    --hash=sha256:5b290f93b98ffbc21c0c7e749f054b3267782166d72fa5e3ed1ed4eaf34a2b78 \
-    --hash=sha256:d9dc4b3318f310e34c82951ea5d6683f67bed7def4b259fafbfe4f1beb1d8e5f
+jupyter==1.1.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:7a59533c22af65439b24bbe60373a4e95af8f16ac65a6c00820ad378e3f7cc83 \
+    --hash=sha256:d55467bceabdea49d7e3624af7e33d59c37fff53ed3a350e1ac957bed731de7a
 jupyterlab-pygments==0.3.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
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     --hash=sha256:841a89020971da1d8693f1a99997aefc5dc424bb1b251fd6322462a1b8842780
 jupyterlab-server==2.27.3 ; python_full_version >= "3.9.1" and python_version < "3.13" \
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     --hash=sha256:eb36caca59e74471988f0ae25c77945610b887f777255aa21f8065def9e51ed4
-jupyterlab-widgets==3.0.11 ; python_full_version >= "3.9.1" and python_version < "3.13" \
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-jupyterlab==4.2.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
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+    --hash=sha256:a2966d385328c1942b683a8cd96b89b8dd82c8b8f81dda902bb2bc06d46f5bed \
+    --hash=sha256:e3cda2c233ce144192f1e29914ad522b2f4c40e77214b0cc97377ca3d323db54
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+    --hash=sha256:73b6e0775d41a9fee7ee756c80f58a6bed4040869ccc21411dc559818874d321 \
+    --hash=sha256:ae7f3a1b8cb88b4f55009ce79fa7c06f99d70cd63601ee4aa91815d054f46f75
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+    --hash=sha256:f2901429da1e645ce548bf9171784c0f74f0718c3f6150ce166be39e4dd66c3e \
+    --hash=sha256:f422a209d2455c56849442ae42f25dbaaba1c6c3f501d58761c619c7836642ec \
+    --hash=sha256:f65e5120863c2b266dbcc927b306c5b78e502c71edf3295dfcb9501ec96e5fc7 \
+    --hash=sha256:f7d4a670107d75dfe5ad080bed6c341d18c4442f9378c9f58e5851e86eb79965 \
+    --hash=sha256:f914c03e6a31deb632e2daa881fe198461f4d06e57ac3d0e05bbcab8eae01945 \
+    --hash=sha256:fb66442c2546446944437df74379e9cf9e9db353e61301d1a0e26482f43f0dd8
 markdown-it-py==3.0.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:355216845c60bd96232cd8d8c40e8f9765cc86f46880e43a8fd22dc1a1a8cab1 \
     --hash=sha256:e3f60a94fa066dc52ec76661e37c851cb232d92f9886b15cb560aaada2df8feb
@@ -1097,170 +1289,174 @@ markupsafe==2.1.5 ; python_full_version >= "3.9.1" and python_version < "3.13" \
 matplotlib-inline==0.1.7 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:8423b23ec666be3d16e16b60bdd8ac4e86e840ebd1dd11a30b9f117f2fa0ab90 \
     --hash=sha256:df192d39a4ff8f21b1895d72e6a13f5fcc5099f00fa84384e0ea28c2cc0653ca
-matplotlib==3.9.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:0000354e32efcfd86bda75729716b92f5c2edd5b947200be9881f0a671565c33 \
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-    --hash=sha256:f1f2e5d29e9435c97ad4c36fb6668e89aee13d48c75893e25cef064675038ac9
+matplotlib==3.8.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:1c13f041a7178f9780fb61cc3a2b10423d5e125480e4be51beaf62b172413b67 \
+    --hash=sha256:232ce322bfd020a434caaffbd9a95333f7c2491e59cfc014041d95e38ab90d1c \
+    --hash=sha256:493e9f6aa5819156b58fce42b296ea31969f2aab71c5b680b4ea7a3cb5c07d94 \
+    --hash=sha256:50bac6e4d77e4262c4340d7a985c30912054745ec99756ce213bfbc3cb3808eb \
+    --hash=sha256:606e3b90897554c989b1e38a258c626d46c873523de432b1462f295db13de6f9 \
+    --hash=sha256:6209e5c9aaccc056e63b547a8152661324404dd92340a6e479b3a7f24b42a5d0 \
+    --hash=sha256:6485ac1f2e84676cff22e693eaa4fbed50ef5dc37173ce1f023daef4687df616 \
+    --hash=sha256:6addbd5b488aedb7f9bc19f91cd87ea476206f45d7116fcfe3d31416702a82fa \
+    --hash=sha256:72f9322712e4562e792b2961971891b9fbbb0e525011e09ea0d1f416c4645661 \
+    --hash=sha256:7a6769f58ce51791b4cb8b4d7642489df347697cd3e23d88266aaaee93b41d9a \
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+    --hash=sha256:90df07db7b599fe7035d2f74ab7e438b656528c68ba6bb59b7dc46af39ee48ef \
+    --hash=sha256:9bb0189011785ea794ee827b68777db3ca3f93f3e339ea4d920315a0e5a78d54 \
+    --hash=sha256:a0e47eda4eb2614300fc7bb4657fced3e83d6334d03da2173b09e447418d499f \
+    --hash=sha256:abc9d838f93583650c35eca41cfcec65b2e7cb50fd486da6f0c49b5e1ed23014 \
+    --hash=sha256:ac24233e8f2939ac4fd2919eed1e9c0871eac8057666070e94cbf0b33dd9c338 \
+    --hash=sha256:b12ba985837e4899b762b81f5b2845bd1a28f4fdd1a126d9ace64e9c4eb2fb25 \
+    --hash=sha256:b7a2a253d3b36d90c8993b4620183b55665a429da8357a4f621e78cd48b2b30b \
+    --hash=sha256:c7064120a59ce6f64103c9cefba8ffe6fba87f2c61d67c401186423c9a20fd35 \
+    --hash=sha256:c89ee9314ef48c72fe92ce55c4e95f2f39d70208f9f1d9db4e64079420d8d732 \
+    --hash=sha256:cc4ccdc64e3039fc303defd119658148f2349239871db72cd74e2eeaa9b80b71 \
+    --hash=sha256:ce1edd9f5383b504dbc26eeea404ed0a00656c526638129028b758fd43fc5f10 \
+    --hash=sha256:ecd79298550cba13a43c340581a3ec9c707bd895a6a061a78fa2524660482fc0 \
+    --hash=sha256:f51c4c869d4b60d769f7b4406eec39596648d9d70246428745a681c327a8ad30 \
+    --hash=sha256:fb44f53af0a62dc80bba4443d9b27f2fde6acfdac281d95bc872dc148a6509cc
 mccabe==0.7.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:348e0240c33b60bbdf4e523192ef919f28cb2c3d7d5c7794f74009290f236325 \
     --hash=sha256:6c2d30ab6be0e4a46919781807b4f0d834ebdd6c6e3dca0bda5a15f863427b6e
-mdit-py-plugins==0.4.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:1020dfe4e6bfc2c79fb49ae4e3f5b297f5ccd20f010187acc52af2921e27dc6a \
-    --hash=sha256:834b8ac23d1cd60cec703646ffd22ae97b7955a6d596eb1d304be1e251ae499c
+mdit-py-plugins==0.4.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:0c673c3f889399a33b95e88d2f0d111b4447bdfea7f237dab2d488f459835636 \
+    --hash=sha256:5f2cd1fdb606ddf152d37ec30e46101a60512bc0e5fa1a7002c36647b09e26b5
 mdurl==0.1.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8 \
     --hash=sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba
+mistralai==1.1.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:9d1fe778e0e8c6ddab714e6a64c6096bd39cfe119ff38ceb5019d8e089df08ba \
+    --hash=sha256:eea0938975195f331d0ded12d14e3c982f09f1b68210200ed4ff0c6b9b22d0fb
 mistune==3.0.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:71481854c30fdbc938963d3605b72501f5c10a9320ecd412c121c163a1c7d205 \
     --hash=sha256:fc7f93ded930c92394ef2cb6f04a8aabab4117a91449e72dcc8dfa646a508be8
-multidict==6.0.5 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:01265f5e40f5a17f8241d52656ed27192be03bfa8764d88e8220141d1e4b3556 \
-    --hash=sha256:0275e35209c27a3f7951e1ce7aaf93ce0d163b28948444bec61dd7badc6d3f8c \
-    --hash=sha256:04bde7a7b3de05732a4eb39c94574db1ec99abb56162d6c520ad26f83267de29 \
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+    --hash=sha256:e27bbb6d14416713a8bd7aaa1313c0fc8d44ee48d74497a0ff4c3a1b6ccb5167 \
+    --hash=sha256:e617fb6b0b6953fffd762669610c1c4ffd05632c138d61ac7e14ad187870669c \
+    --hash=sha256:e9aa71e15d9d9beaad2c6b9319edcdc0a49a43ef5c0a4c8265ca9ee7d6c67774 \
+    --hash=sha256:ec2abea24d98246b94913b76a125e855eb5c434f7c46546046372fe60f666351 \
+    --hash=sha256:f179dee3b863ab1c59580ff60f9d99f632f34ccb38bf67a33ec6b3ecadd0fd76 \
+    --hash=sha256:f4c035da3f544b1882bac24115f3e2e8760f10a0107614fc9839fd232200b875 \
+    --hash=sha256:f67f217af4b1ff66c68a87318012de788dd95fcfeb24cc889011f4e1c7454dfd \
+    --hash=sha256:f90c822a402cb865e396a504f9fc8173ef34212a342d92e362ca498cad308e28 \
+    --hash=sha256:ff3827aef427c89a25cc96ded1759271a93603aba9fb977a6d264648ebf989db
 mypy-extensions==1.0.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:4392f6c0eb8a5668a69e23d168ffa70f0be9ccfd32b5cc2d26a34ae5b844552d \
     --hash=sha256:75dbf8955dc00442a438fc4d0666508a9a97b6bd41aa2f0ffe9d2f2725af0782
-mypy==1.11.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:0624bdb940255d2dd24e829d99a13cfeb72e4e9031f9492148f410ed30bcab54 \
-    --hash=sha256:0bc71d1fb27a428139dd78621953effe0d208aed9857cb08d002280b0422003a \
-    --hash=sha256:0bd53faf56de9643336aeea1c925012837432b5faf1701ccca7fde70166ccf72 \
-    --hash=sha256:11965c2f571ded6239977b14deebd3f4c3abd9a92398712d6da3a772974fad69 \
-    --hash=sha256:1a81cf05975fd61aec5ae16501a091cfb9f605dc3e3c878c0da32f250b74760b \
-    --hash=sha256:2684d3f693073ab89d76da8e3921883019ea8a3ec20fa5d8ecca6a2db4c54bbe \
-    --hash=sha256:2c63350af88f43a66d3dfeeeb8d77af34a4f07d760b9eb3a8697f0386c7590b4 \
-    --hash=sha256:45df906e8b6804ef4b666af29a87ad9f5921aad091c79cc38e12198e220beabd \
-    --hash=sha256:4c956b49c5d865394d62941b109728c5c596a415e9c5b2be663dd26a1ff07bc0 \
-    --hash=sha256:64f4a90e3ea07f590c5bcf9029035cf0efeae5ba8be511a8caada1a4893f5525 \
-    --hash=sha256:749fd3213916f1751fff995fccf20c6195cae941dc968f3aaadf9bb4e430e5a2 \
-    --hash=sha256:79c07eb282cb457473add5052b63925e5cc97dfab9812ee65a7c7ab5e3cb551c \
-    --hash=sha256:7b6343d338390bb946d449677726edf60102a1c96079b4f002dedff375953fc5 \
-    --hash=sha256:886c9dbecc87b9516eff294541bf7f3655722bf22bb898ee06985cd7269898de \
-    --hash=sha256:a2b43895a0f8154df6519706d9bca8280cda52d3d9d1514b2d9c3e26792a0b74 \
-    --hash=sha256:a32fc80b63de4b5b3e65f4be82b4cfa362a46702672aa6a0f443b4689af7008c \
-    --hash=sha256:a707ec1527ffcdd1c784d0924bf5cb15cd7f22683b919668a04d2b9c34549d2e \
-    --hash=sha256:a831671bad47186603872a3abc19634f3011d7f83b083762c942442d51c58d58 \
-    --hash=sha256:b639dce63a0b19085213ec5fdd8cffd1d81988f47a2dec7100e93564f3e8fb3b \
-    --hash=sha256:b868d3bcff720dd7217c383474008ddabaf048fad8d78ed948bb4b624870a417 \
-    --hash=sha256:c1952f5ea8a5a959b05ed5f16452fddadbaae48b5d39235ab4c3fc444d5fd411 \
-    --hash=sha256:d44be7551689d9d47b7abc27c71257adfdb53f03880841a5db15ddb22dc63edb \
-    --hash=sha256:e1e30dc3bfa4e157e53c1d17a0dad20f89dc433393e7702b813c10e200843b03 \
-    --hash=sha256:e4fe9f4e5e521b458d8feb52547f4bade7ef8c93238dfb5bbc790d9ff2d770ca \
-    --hash=sha256:f39918a50f74dc5969807dcfaecafa804fa7f90c9d60506835036cc1bc891dc8 \
-    --hash=sha256:f404a0b069709f18bbdb702eb3dcfe51910602995de00bd39cea3050b5772d08 \
-    --hash=sha256:fca4a60e1dd9fd0193ae0067eaeeb962f2d79e0d9f0f66223a0682f26ffcc809
+mypy==1.11.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:06d26c277962f3fb50e13044674aa10553981ae514288cb7d0a738f495550b36 \
+    --hash=sha256:2ff93107f01968ed834f4256bc1fc4475e2fecf6c661260066a985b52741ddce \
+    --hash=sha256:36383a4fcbad95f2657642a07ba22ff797de26277158f1cc7bd234821468b1b6 \
+    --hash=sha256:37c7fa6121c1cdfcaac97ce3d3b5588e847aa79b580c1e922bb5d5d2902df19b \
+    --hash=sha256:3a66169b92452f72117e2da3a576087025449018afc2d8e9bfe5ffab865709ca \
+    --hash=sha256:3f14cd3d386ac4d05c5a39a51b84387403dadbd936e17cb35882134d4f8f0d24 \
+    --hash=sha256:41ea707d036a5307ac674ea172875f40c9d55c5394f888b168033177fce47383 \
+    --hash=sha256:478db5f5036817fe45adb7332d927daa62417159d49783041338921dcf646fc7 \
+    --hash=sha256:4a8a53bc3ffbd161b5b2a4fff2f0f1e23a33b0168f1c0778ec70e1a3d66deb86 \
+    --hash=sha256:539c570477a96a4e6fb718b8d5c3e0c0eba1f485df13f86d2970c91f0673148d \
+    --hash=sha256:57555a7715c0a34421013144a33d280e73c08df70f3a18a552938587ce9274f4 \
+    --hash=sha256:6e658bd2d20565ea86da7d91331b0eed6d2eee22dc031579e6297f3e12c758c8 \
+    --hash=sha256:6e7184632d89d677973a14d00ae4d03214c8bc301ceefcdaf5c474866814c987 \
+    --hash=sha256:75746e06d5fa1e91bfd5432448d00d34593b52e7e91a187d981d08d1f33d4385 \
+    --hash=sha256:7f9993ad3e0ffdc95c2a14b66dee63729f021968bff8ad911867579c65d13a79 \
+    --hash=sha256:801780c56d1cdb896eacd5619a83e427ce436d86a3bdf9112527f24a66618fef \
+    --hash=sha256:801ca29f43d5acce85f8e999b1e431fb479cb02d0e11deb7d2abb56bdaf24fd6 \
+    --hash=sha256:969ea3ef09617aff826885a22ece0ddef69d95852cdad2f60c8bb06bf1f71f70 \
+    --hash=sha256:a976775ab2256aadc6add633d44f100a2517d2388906ec4f13231fafbb0eccca \
+    --hash=sha256:af8d155170fcf87a2afb55b35dc1a0ac21df4431e7d96717621962e4b9192e70 \
+    --hash=sha256:b499bc07dbdcd3de92b0a8b29fdf592c111276f6a12fe29c30f6c417dd546d12 \
+    --hash=sha256:cd953f221ac1379050a8a646585a29574488974f79d8082cedef62744f0a0104 \
+    --hash=sha256:d42a6dd818ffce7be66cce644f1dff482f1d97c53ca70908dff0b9ddc120b77a \
+    --hash=sha256:e8960dbbbf36906c5c0b7f4fbf2f0c7ffb20f4898e6a879fcf56a41a08b0d318 \
+    --hash=sha256:edb91dded4df17eae4537668b23f0ff6baf3707683734b6a818d5b9d0c0c31a1 \
+    --hash=sha256:ee23de8530d99b6db0573c4ef4bd8f39a2a6f9b60655bf7a1357e585a3486f2b \
+    --hash=sha256:f7821776e5c4286b6a13138cc935e2e9b6fde05e081bdebf5cdb2bb97c9df81d
 myst-parser==3.0.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:6457aaa33a5d474aca678b8ead9b3dc298e89c68e67012e73146ea6fd54babf1 \
     --hash=sha256:88f0cb406cb363b077d176b51c476f62d60604d68a8dcdf4832e080441301a87
@@ -1273,9 +1469,9 @@ nbconvert==7.16.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
 nbformat==5.10.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:322168b14f937a5d11362988ecac2a4952d3d8e3a2cbeb2319584631226d5b3a \
     --hash=sha256:3b48d6c8fbca4b299bf3982ea7db1af21580e4fec269ad087b9e81588891200b
-nbsphinx==0.9.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:042a60806fc23d519bc5bef59d95570713913fe442fda759d53e3aaf62104794 \
-    --hash=sha256:22cb1d974a8300e8118ca71aea1f649553743c0c5830a54129dcd446e6a8ba17
+nbsphinx==0.9.5 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:736916e7b0dab28fc904f4a9ae3b53a9a50c29fccc6329c052fcc7485abcf2b7 \
+    --hash=sha256:d82f71084425db1f48e72515f15c25b4de8652ceaab513ee462ac05f1b8eae0a
 nest-asyncio==1.6.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:6f172d5449aca15afd6c646851f4e31e02c598d553a667e38cafa997cfec55fe \
     --hash=sha256:87af6efd6b5e897c81050477ef65c62e2b2f35d51703cae01aff2905b1852e1c
@@ -1285,9 +1481,9 @@ nodeenv==1.9.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
 notebook-shim==0.2.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:411a5be4e9dc882a074ccbcae671eda64cceb068767e9a3419096986560e1cef \
     --hash=sha256:b4b2cfa1b65d98307ca24361f5b30fe785b53c3fd07b7a47e89acb5e6ac638cb
-notebook==7.2.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:4287b6da59740b32173d01d641f763d292f49c30e7a51b89c46ba8473126341e \
-    --hash=sha256:f45489a3995746f2195a137e0773e2130960b51c9ac3ce257dbc2705aab3a6ca
+notebook==7.2.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:2ef07d4220421623ad3fe88118d687bc0450055570cdd160814a59cf3a1c516e \
+    --hash=sha256:c89264081f671bc02eec0ed470a627ed791b9156cad9285226b31611d3e9fe1c
 numpy==1.26.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:03a8c78d01d9781b28a6989f6fa1bb2c4f2d51201cf99d3dd875df6fbd96b23b \
     --hash=sha256:08beddf13648eb95f8d867350f6a018a4be2e5ad54c8d8caed89ebca558b2818 \
@@ -1325,45 +1521,61 @@ numpy==1.26.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:edd8b5fe47dab091176d21bb6de568acdd906d1887a4584a15a9a96a1dca06ef \
     --hash=sha256:f870204a840a60da0b12273ef34f7051e98c3b5961b61b0c2c1be6dfd64fbcd3 \
     --hash=sha256:ffa75af20b44f8dba823498024771d5ac50620e6915abac414251bd971b4529f
-openai==1.37.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:9a6adda0d6ae8fce02d235c5671c399cfa40d6a281b3628914c7ebf244888ee3 \
-    --hash=sha256:faf87206785a6b5d9e34555d6a3242482a6852bc802e453e2a891f68ee04ce55
+openai==1.47.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:6e14d6f77c8cf546646afcd87a2ef752505b3710d2564a2e433e17307dfa86a0 \
+    --hash=sha256:9ccc8737dfa791f7bd903db4758c176b8544a8cd89d3a3d2add3cea02a34c3a0
+openpyxl==3.1.5 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:5282c12b107bffeef825f4617dc029afaf41d0ea60823bbb665ef3079dc79de2 \
+    --hash=sha256:cf0e3cf56142039133628b5acffe8ef0c12bc902d2aadd3e0fe5878dc08d1050
 overrides==7.7.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:55158fa3d93b98cc75299b1e67078ad9003ca27945c76162c1c0766d6f91820a \
     --hash=sha256:c7ed9d062f78b8e4c1a7b70bd8796b35ead4d9f510227ef9c5dc7626c60d7e49
 packaging==24.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:026ed72c8ed3fcce5bf8950572258698927fd1dbda10a5e981cdf0ac37f4f002 \
     --hash=sha256:5b8f2217dbdbd2f7f384c41c628544e6d52f2d0f53c6d0c3ea61aa5d1d7ff124
-pandas==2.2.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:001910ad31abc7bf06f49dcc903755d2f7f3a9186c0c040b827e522e9cef0863 \
-    --hash=sha256:0ca6377b8fca51815f382bd0b697a0814c8bda55115678cbc94c30aacbb6eff2 \
-    --hash=sha256:0cace394b6ea70c01ca1595f839cf193df35d1575986e484ad35c4aeae7266c1 \
-    --hash=sha256:1cb51fe389360f3b5a4d57dbd2848a5f033350336ca3b340d1c53a1fad33bcad \
-    --hash=sha256:2925720037f06e89af896c70bca73459d7e6a4be96f9de79e2d440bd499fe0db \
-    --hash=sha256:3e374f59e440d4ab45ca2fffde54b81ac3834cf5ae2cdfa69c90bc03bde04d76 \
-    --hash=sha256:40ae1dffb3967a52203105a077415a86044a2bea011b5f321c6aa64b379a3f51 \
-    --hash=sha256:43498c0bdb43d55cb162cdc8c06fac328ccb5d2eabe3cadeb3529ae6f0517c32 \
-    --hash=sha256:4abfe0be0d7221be4f12552995e58723c7422c80a659da13ca382697de830c08 \
-    --hash=sha256:58b84b91b0b9f4bafac2a0ac55002280c094dfc6402402332c0913a59654ab2b \
-    --hash=sha256:640cef9aa381b60e296db324337a554aeeb883ead99dc8f6c18e81a93942f5f4 \
-    --hash=sha256:66b479b0bd07204e37583c191535505410daa8df638fd8e75ae1b383851fe921 \
-    --hash=sha256:696039430f7a562b74fa45f540aca068ea85fa34c244d0deee539cb6d70aa288 \
-    --hash=sha256:6d2123dc9ad6a814bcdea0f099885276b31b24f7edf40f6cdbc0912672e22eee \
-    --hash=sha256:8635c16bf3d99040fdf3ca3db669a7250ddf49c55dc4aa8fe0ae0fa8d6dcc1f0 \
-    --hash=sha256:873d13d177501a28b2756375d59816c365e42ed8417b41665f346289adc68d24 \
-    --hash=sha256:8e5a0b00e1e56a842f922e7fae8ae4077aee4af0acb5ae3622bd4b4c30aedf99 \
-    --hash=sha256:8e90497254aacacbc4ea6ae5e7a8cd75629d6ad2b30025a4a8b09aa4faf55151 \
-    --hash=sha256:9057e6aa78a584bc93a13f0a9bf7e753a5e9770a30b4d758b8d5f2a62a9433cd \
-    --hash=sha256:90c6fca2acf139569e74e8781709dccb6fe25940488755716d1d354d6bc58bce \
-    --hash=sha256:92fd6b027924a7e178ac202cfbe25e53368db90d56872d20ffae94b96c7acc57 \
-    --hash=sha256:9dfde2a0ddef507a631dc9dc4af6a9489d5e2e740e226ad426a05cabfbd7c8ef \
-    --hash=sha256:9e79019aba43cb4fda9e4d983f8e88ca0373adbb697ae9c6c43093218de28b54 \
-    --hash=sha256:a77e9d1c386196879aa5eb712e77461aaee433e54c68cf253053a73b7e49c33a \
-    --hash=sha256:c7adfc142dac335d8c1e0dcbd37eb8617eac386596eb9e1a1b77791cf2498238 \
-    --hash=sha256:d187d355ecec3629624fccb01d104da7d7f391db0311145817525281e2804d23 \
-    --hash=sha256:ddf818e4e6c7c6f4f7c8a12709696d193976b591cc7dc50588d3d1a6b5dc8772 \
-    --hash=sha256:e9b79011ff7a0f4b1d6da6a61aa1aa604fb312d6647de5bad20013682d1429ce \
-    --hash=sha256:eee3a87076c0756de40b05c5e9a6069c035ba43e8dd71c379e68cab2c20f16ad
+pandas==2.2.3 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:062309c1b9ea12a50e8ce661145c6aab431b1e99530d3cd60640e255778bd43a \
+    --hash=sha256:15c0e1e02e93116177d29ff83e8b1619c93ddc9c49083f237d4312337a61165d \
+    --hash=sha256:1948ddde24197a0f7add2bdc4ca83bf2b1ef84a1bc8ccffd95eda17fd836ecb5 \
+    --hash=sha256:1db71525a1538b30142094edb9adc10be3f3e176748cd7acc2240c2f2e5aa3a4 \
+    --hash=sha256:22a9d949bfc9a502d320aa04e5d02feab689d61da4e7764b62c30b991c42c5f0 \
+    --hash=sha256:29401dbfa9ad77319367d36940cd8a0b3a11aba16063e39632d98b0e931ddf32 \
+    --hash=sha256:31d0ced62d4ea3e231a9f228366919a5ea0b07440d9d4dac345376fd8e1477ea \
+    --hash=sha256:3508d914817e153ad359d7e069d752cdd736a247c322d932eb89e6bc84217f28 \
+    --hash=sha256:37e0aced3e8f539eccf2e099f65cdb9c8aa85109b0be6e93e2baff94264bdc6f \
+    --hash=sha256:381175499d3802cde0eabbaf6324cce0c4f5d52ca6f8c377c29ad442f50f6348 \
+    --hash=sha256:38cf8125c40dae9d5acc10fa66af8ea6fdf760b2714ee482ca691fc66e6fcb18 \
+    --hash=sha256:3b71f27954685ee685317063bf13c7709a7ba74fc996b84fc6821c59b0f06468 \
+    --hash=sha256:3fc6873a41186404dad67245896a6e440baacc92f5b716ccd1bc9ed2995ab2c5 \
+    --hash=sha256:4850ba03528b6dd51d6c5d273c46f183f39a9baf3f0143e566b89450965b105e \
+    --hash=sha256:4f18ba62b61d7e192368b84517265a99b4d7ee8912f8708660fb4a366cc82667 \
+    --hash=sha256:56534ce0746a58afaf7942ba4863e0ef81c9c50d3f0ae93e9497d6a41a057645 \
+    --hash=sha256:59ef3764d0fe818125a5097d2ae867ca3fa64df032331b7e0917cf5d7bf66b13 \
+    --hash=sha256:5dbca4c1acd72e8eeef4753eeca07de9b1db4f398669d5994086f788a5d7cc30 \
+    --hash=sha256:5de54125a92bb4d1c051c0659e6fcb75256bf799a732a87184e5ea503965bce3 \
+    --hash=sha256:61c5ad4043f791b61dd4752191d9f07f0ae412515d59ba8f005832a532f8736d \
+    --hash=sha256:6374c452ff3ec675a8f46fd9ab25c4ad0ba590b71cf0656f8b6daa5202bca3fb \
+    --hash=sha256:63cc132e40a2e084cf01adf0775b15ac515ba905d7dcca47e9a251819c575ef3 \
+    --hash=sha256:66108071e1b935240e74525006034333f98bcdb87ea116de573a6a0dccb6c039 \
+    --hash=sha256:6dfcb5ee8d4d50c06a51c2fffa6cff6272098ad6540aed1a76d15fb9318194d8 \
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+    --hash=sha256:bc6b93f9b966093cb0fd62ff1a7e4c09e6d546ad7c1de191767baffc57628f39 \
+    --hash=sha256:c124333816c3a9b03fbeef3a9f230ba9a737e9e5bb4060aa2107a86cc0a497fc \
+    --hash=sha256:cd8d0c3be0515c12fed0bdbae072551c8b54b7192c7b1fda0ba56059a0179698 \
+    --hash=sha256:d9c45366def9a3dd85a6454c0e7908f2b3b8e9c138f5dc38fed7ce720d8453ed \
+    --hash=sha256:f00d1345d84d8c86a63e476bb4955e46458b304b9575dcf71102b5c705320015 \
+    --hash=sha256:f3a255b2c19987fbbe62a9dfd6cff7ff2aa9ccab3fc75218fd4b7530f01efa24 \
+    --hash=sha256:fffb8ae78d8af97f849404f21411c95062db1496aeb3e56f146f0355c9989319
 pandocfilters==1.5.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:002b4a555ee4ebc03f8b66307e287fa492e4a77b4ea14d3f934328297bb4939e \
     --hash=sha256:93be382804a9cdb0a7267585f157e5d1731bbe5545a85b268d6f5fe6232de2bc
@@ -1457,18 +1669,21 @@ pillow==10.4.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:f7baece4ce06bade126fb84b8af1c33439a76d8a6fd818970215e0560ca28c27 \
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     --hash=sha256:ff337c552345e95702c5fde3158acb0625111017d0e5f24bf3acdb9cc16b90d1
-platformdirs==4.2.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
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-    --hash=sha256:38b7b51f512eed9e84a22788b4bce1de17c0adb134d6becb09836e37d8654cd3
+platformdirs==4.3.6 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:357fb2acbc885b0419afd3ce3ed34564c13c9b95c89360cd9563f73aa5e2b907 \
+    --hash=sha256:73e575e1408ab8103900836b97580d5307456908a03e92031bab39e4554cc3fb
 pluggy==1.5.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:2cffa88e94fdc978c4c574f15f9e59b7f4201d439195c3715ca9e2486f1d0cf1 \
     --hash=sha256:44e1ad92c8ca002de6377e165f3e0f1be63266ab4d554740532335b9d75ea669
+polyfactory==2.16.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:6d0d90deb85e5bb1733ea8744c2d44eea2b31656e11b4fa73832d2e2ab5422da \
+    --hash=sha256:e5eaf97358fee07d0d8de86a93e81dc56e3be1e1514d145fea6c5f486cda6ea1
 pre-commit==3.8.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
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-prometheus-client==0.20.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
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-    --hash=sha256:cde524a85bce83ca359cc837f28b8c0db5cac7aa653a588fd7e84ba061c329e7
+prometheus-client==0.21.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:4fa6b4dd0ac16d58bb587c04b1caae65b8c5043e85f778f42f5f632f6af2e166 \
+    --hash=sha256:96c83c606b71ff2b0a433c98889d275f51ffec6c5e267de37c7a2b5c9aa9233e
 prompt-toolkit==3.0.47 ; python_full_version >= "3.9.1" and python_version < "3.13" \
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     --hash=sha256:1e1b29cb58080b1e69f207c893a1a7bf16d127a5c30c9d17a25a5d77792e5360
@@ -1499,99 +1714,99 @@ pure-eval==0.2.3 ; python_full_version >= "3.9.1" and python_version < "3.13" \
 pycparser==2.22 ; python_full_version >= "3.9.1" and python_version < "3.13" \
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+pydantic-core==2.23.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:0a7df63886be5e270da67e0966cf4afbae86069501d35c8c1b3b6c168f42cb36 \
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+    --hash=sha256:d97683ddee4723ae8c95d1eddac7c192e8c552da0c73a925a89fa8649bf13eea \
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+    --hash=sha256:df933278128ea1cd77772673c73954e53a1c95a4fdf41eef97c2b779271bd0bd \
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+    --hash=sha256:e55541f756f9b3ee346b840103f32779c695a19826a4c442b7954550a0972040 \
+    --hash=sha256:ec4e55f79b1c4ffb2eecd8a0cfba9955a2588497d96851f4c8f99aa4a1d39b12 \
+    --hash=sha256:ed1a53de42fbe34853ba90513cea21673481cd81ed1be739f7f2efb931b24916 \
+    --hash=sha256:ed541d70698978a20eb63d8c5d72f2cc6d7079d9d90f6b50bad07826f1320f5f \
+    --hash=sha256:f09e2ff1f17c2b51f2bc76d1cc33da96298f0a036a137f5440ab3ec5360b624f \
+    --hash=sha256:f220b0eea5965dec25480b6333c788fb72ce5f9129e8759ef876a1d805d00801 \
+    --hash=sha256:f3e0da4ebaef65158d4dfd7d3678aad692f7666877df0002b8a522cdf088f231 \
+    --hash=sha256:f455ee30a9d61d3e1a15abd5068827773d6e4dc513e795f380cdd59932c782d5 \
+    --hash=sha256:f5ef8f42bec47f21d07668a043f077d507e5bf4e668d5c6dfe6aaba89de1a5b8 \
+    --hash=sha256:f69a8e0b033b747bb3e36a44e7732f0c99f7edd5cea723d45bc0d6e95377ffee \
+    --hash=sha256:ff02b6d461a6de369f07ec15e465a88895f3223eb75073ffea56b84d9331f607
+pydantic==2.9.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:d155cef71265d1e9807ed1c32b4c8deec042a44a50a4188b25ac67ecd81a9c0f \
+    --hash=sha256:f048cec7b26778210e28a0459867920654d48e5e62db0958433636cde4254f12
 pydocstyle==6.3.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:118762d452a49d6b05e194ef344a55822987a462831ade91ec5c06fd2169d019 \
     --hash=sha256:7ce43f0c0ac87b07494eb9c0b462c0b73e6ff276807f204d6b53edc72b7e44e1
@@ -1601,58 +1816,58 @@ pydot==2.0.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
 pygments==2.18.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:786ff802f32e91311bff3889f6e9a86e81505fe99f2735bb6d60ae0c5004f199 \
     --hash=sha256:b8e6aca0523f3ab76fee51799c488e38782ac06eafcf95e7ba832985c8e7b13a
-pylint==3.2.6 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:03c8e3baa1d9fb995b12c1dbe00aa6c4bcef210c2a2634374aedeb22fb4a8f8f \
-    --hash=sha256:a5d01678349454806cff6d886fb072294f56a58c4761278c97fb557d708e1eb3
-pymupdf==1.24.9 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:00499b864a56a2168254dce3d0f12048b96e9b3bdd43fecace18a1572342c8d4 \
-    --hash=sha256:042ad205c7ef615d9fbab7078f6fa8d14f020ed2dfe3a79d803b6171318565b5 \
-    --hash=sha256:13d06161176e1d4e337f5b5e053b628e4531bab5effb269a83dc38d4deb8e659 \
-    --hash=sha256:241913d0c76aacb05acdd8a0e82b1105883ffe6ef3bb4d9742b41d3c5e84d2db \
-    --hash=sha256:3692a5e824f10dc09bbddabab207f7cd5979831e48dd2f4de1be21e441767473 \
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-    --hash=sha256:ff70e26625b6cdd036e2c63b5d6c1897949c0e8b205cd756276f27baadaad340
-pymupdfb==1.24.9 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:198f6b3713b6f980fa96c1099be0d5459c7d43c593299948f0ba528577e6bf46 \
-    --hash=sha256:20ea17fd5799dcf7813ec099c0ce303f763e6e4ba8d0f54d5f84e4df90c3a340 \
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-    --hash=sha256:eb5b38f588963a239a8c0bca99d3d912f0c04674e3c6e7199e44cebd22840061
-pyparsing==3.1.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:a1bac0ce561155ecc3ed78ca94d3c9378656ad4c94c1270de543f621420f94ad \
-    --hash=sha256:f9db75911801ed778fe61bb643079ff86601aca99fcae6345aa67292038fb742
+pylint==3.3.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:02dce1845f68974b9b03045894eb3bf05a8b3c7da9fd10af4de3c91e69eb92f1 \
+    --hash=sha256:c685fe3c061ee5fb0ce7c29436174ab84a2f525fce2a268b1986e921e083fe22
+pymupdf==1.24.10 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:05b8d360766b87f4abd186eba16a56b92bae513b2361b13f633fe6256329292e \
+    --hash=sha256:0e3969c2fdff682b3b2c6a2b463adde068d6d8e20e2133ef6c8503469259646a \
+    --hash=sha256:0edcd093db05991e9d32dd2687db408b40895214f9cecd50672cd6b79fee188f \
+    --hash=sha256:117b8a2220ec31142f6a5e4ac0235b56f239d88e57e5cef3aa047bc70e4cd1e9 \
+    --hash=sha256:1a87440a6cbc0d5ad513425baa0f4747841898fca6e37350ca3e6b29e5f40c01 \
+    --hash=sha256:1e5413e1aeab2f18e1ca1b3ff17057a4a7c5cbf4ff14abc93203da88fc1a1dd8 \
+    --hash=sha256:227a4473fce8fa32b9268da68781048795503b67dc045867fc201e1334204bf1 \
+    --hash=sha256:2b14dbdf7c415bb0fa849527abbe7b4f1f55ae23b9355d132951f634438c59ac \
+    --hash=sha256:2e95f5c379dc086eaa5a2af73f2e62a0bae95e05b19963603cdf800ca51e65a6 \
+    --hash=sha256:49f83556cd1a7d05b36a54ccc01fce324da8a4e6854e36cc5cd94d321e428565 \
+    --hash=sha256:50d2972558d25ce46a8634b58787b28dbeff9b3fe4299530fc9c8c9921061e83 \
+    --hash=sha256:5608a60c601ab34988f96ce122d7c19d0773e57e7bbb30c7b3ced1f5b0da74cf \
+    --hash=sha256:5fbd67cce759fc0126902137409cf9da6313b776c4d5ff0d5200f336350f86a3 \
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+    --hash=sha256:a320d44a96f0cc69364c4d7384205fdae57a511edb07e68627108546cfd3ca7d \
+    --hash=sha256:bbd618078c2caab742d34291bd4a4c660981bef3988dfaaadf5d534081abd8ec \
+    --hash=sha256:bd3ebd6d3fb8a845582098362f885bfb0a31ae4272587efc2c55c5e29fe7327a \
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+    --hash=sha256:c0d1ccdc062ea9961063790831e838bc43fcf9a8436a8b9f55898addf97c0f86 \
+    --hash=sha256:c3405e120249e2849daac4d52e25433bb0b5da4695ce8edea6cfb9cc819985c4 \
+    --hash=sha256:c8db06b0d5fbcf9b0e8949415771bd4771c820f43b052b42bce2db44c100e384 \
+    --hash=sha256:ccda6f26985347e9f52444c64b35e243f03d8c51106e8c0709f0b0c0b80b669a \
+    --hash=sha256:cd078bf6c5a016bb34dea0ed75030edaae1b00ca273f1fe41100c8c35a101abe \
+    --hash=sha256:cd78ee1ebefdfe72bc36fd4b731cc8c694eb8ef5337d8ea956b0e94cd88751fc \
+    --hash=sha256:d31c09e2af29f778249fe93beb4e44657ed2c0f385ccd5906e84b2b6a747ba9a \
+    --hash=sha256:dda94921c9daf0416fe77b1366200c970a1b8519f826c30be7148df6a147eb1a \
+    --hash=sha256:e52cc55055f08d9411cd991693fb1e6c7f665e92f7b79cdfa0c3d526b2e7f9bb \
+    --hash=sha256:e6a6458a3a6e7ec371176be17535825ca860d8eab5f8999958b2ac639777df5f \
+    --hash=sha256:f323aa7bb55e0214e632bfe24fa140bd5dcfeac2d3977bdce46e760385140513 \
+    --hash=sha256:f68671363be5a2ba104ab7d3bad821d2994cbe3f3408538bbc27d32e6dc9f923
+pymupdfb==1.24.10 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:007b91fa9b528c5c0eecea2e49c486ac02e878274f9e31522bdd948adc5f8327 \
+    --hash=sha256:27ea65c701608b6b7632703339ca33ea6d513843b26dbe9bdefb2f56f7b9b196 \
+    --hash=sha256:2d231b42fe3bf79837df235e7fbdf7ff8b46bf4ca1346d0f0124fb1cdd343ce8 \
+    --hash=sha256:409f1270ef2e70d845e80149ff3db9cfed578274042316cba55cc3e3882421ea \
+    --hash=sha256:4f50a7472f9bb10cbc7a1cd589ee4626ca030b8a4a02749f9a29eb6f00c0e0db \
+    --hash=sha256:aca96b6e9ee3096a26810592f4d899f4d3cf3cf0c902ae7e8cca09bce4d946c4 \
+    --hash=sha256:cd6b24630d90dce9ab3e59d06c5e616686f8d7ec626be1311721fcb062aa0078 \
+    --hash=sha256:fda2c34b206f724b1b5685b67188e2a57bcaa5c99bc40a0a5bc62057514c5cdf
+pyparsing==3.1.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:a6a7ee4235a3f944aa1fa2249307708f893fe5717dc603503c6c7969c070fb7c \
+    --hash=sha256:f86ec8d1a83f11977c9a6ea7598e8c27fc5cddfa5b07ea2241edbbde1d7bc032
 pyreadstat==1.2.7 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:0e21c94514d02ac46d8e9f9008f99b0760478df90ca59f95be8705ba1a48a514 \
     --hash=sha256:0fe67f8f8c92f1861a0e044bc275644de552231e9a28960d54c6c5ca4cb285cf \
@@ -1704,9 +1919,9 @@ pytest-xdist==3.6.1 ; python_full_version >= "3.9.1" and python_version < "3.13"
 pytest==7.4.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:2cf0005922c6ace4a3e2ec8b4080eb0d9753fdc93107415332f50ce9e7994280 \
     --hash=sha256:b090cdf5ed60bf4c45261be03239c2c1c22df034fbffe691abe93cd80cea01d8
-python-dateutil==2.9.0.post0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:37dd54208da7e1cd875388217d5e00ebd4179249f90fb72437e91a35459a0ad3 \
-    --hash=sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427
+python-dateutil==2.8.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:0123cacc1627ae19ddf3c27a5de5bd67ee4586fbdd6440d9748f8abb483d3e86 \
+    --hash=sha256:961d03dc3453ebbc59dbdea9e4e11c5651520a876d0f4db161e8674aae935da9
 python-docx==1.1.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:08c20d6058916fb19853fcf080f7f42b6270d89eac9fa5f8c15f691c0017fabe \
     --hash=sha256:0cf1f22e95b9002addca7948e16f2cd7acdfd498047f1941ca5d293db7762efd
@@ -1716,9 +1931,9 @@ python-dotenv==1.0.1 ; python_full_version >= "3.9.1" and python_version < "3.13
 python-json-logger==2.0.7 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:23e7ec02d34237c5aa1e29a070193a4ea87583bb4e7f8fd06d3de8264c4b2e1c \
     --hash=sha256:f380b826a991ebbe3de4d897aeec42760035ac760345e57b812938dc8b35e2bd
-pytz==2024.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:2a29735ea9c18baf14b448846bde5a48030ed267578472d8955cd0e7443a9812 \
-    --hash=sha256:328171f4e3623139da4983451950b28e95ac706e13f3f2630a879749e7a8b319
+pytz==2024.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:2aa355083c50a0f93fa581709deac0c9ad65cca8a9e9beac660adcbd493c798a \
+    --hash=sha256:31c7c1817eb7fae7ca4b8c7ee50c72f93aa2dd863de768e1ef4245d426aa0725
 pywin32==306 ; sys_platform == "win32" and platform_python_implementation != "PyPy" and python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:06d3420a5155ba65f0b72f2699b5bacf3109f36acbe8923765c22938a69dfc8d \
     --hash=sha256:1c73ea9a0d2283d889001998059f5eaaba3b6238f767c9cf2833b13e6a685f65 \
@@ -1741,275 +1956,295 @@ pywinpty==2.0.13 ; python_full_version >= "3.9.1" and python_version < "3.13" an
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     --hash=sha256:c34e32351a3313ddd0d7da23d27f835c860d32fe4ac814d372a3ea9594f41dde
-pyyaml==6.0.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
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-pyzmq==26.0.3 ; python_full_version >= "3.9.1" and python_version < "3.13" \
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+    --hash=sha256:9edda2df81daa129b25a39b86cb57dfdfe16f7ec15b42b19bfac503360d27a93 \
+    --hash=sha256:a2224fa4a4c2ee872886ed00a571f5e967c85e078e8e8c2530a2fb01b3309b88 \
+    --hash=sha256:a4f96f0d88accc3dbe4a9025f785ba830f968e21e3e2c6321ccdfc9aef755115 \
+    --hash=sha256:aedd5dd8692635813368e558a05266b995d3d020b23e49581ddd5bbe197a8ab6 \
+    --hash=sha256:aee22939bb6075e7afededabad1a56a905da0b3c4e3e0c45e75810ebe3a52672 \
+    --hash=sha256:b1d464cb8d72bfc1a3adc53305a63a8e0cac6bc8c5a07e8ca190ab8d3faa43c2 \
+    --hash=sha256:b8f86dd868d41bea9a5f873ee13bf5551c94cf6bc51baebc6f85075971fe6eea \
+    --hash=sha256:bc6bee759a6bddea5db78d7dcd609397449cb2d2d6587f48f3ca613b19410cfc \
+    --hash=sha256:bea2acdd8ea4275e1278350ced63da0b166421928276c7c8e3f9729d7402a57b \
+    --hash=sha256:bfa832bfa540e5b5c27dcf5de5d82ebc431b82c453a43d141afb1e5d2de025fa \
+    --hash=sha256:c0e6091b157d48cbe37bd67233318dbb53e1e6327d6fc3bb284afd585d141003 \
+    --hash=sha256:c3789bd5768ab5618ebf09cef6ec2b35fed88709b104351748a63045f0ff9797 \
+    --hash=sha256:c530e1eecd036ecc83c3407f77bb86feb79916d4a33d11394b8234f3bd35b940 \
+    --hash=sha256:c811cfcd6a9bf680236c40c6f617187515269ab2912f3d7e8c0174898e2519db \
+    --hash=sha256:c92d73464b886931308ccc45b2744e5968cbaade0b1d6aeb40d8ab537765f5bc \
+    --hash=sha256:cccba051221b916a4f5e538997c45d7d136a5646442b1231b916d0164067ea27 \
+    --hash=sha256:cdeabcff45d1c219636ee2e54d852262e5c2e085d6cb476d938aee8d921356b3 \
+    --hash=sha256:ced65e5a985398827cc9276b93ef6dfabe0273c23de8c7931339d7e141c2818e \
+    --hash=sha256:d049df610ac811dcffdc147153b414147428567fbbc8be43bb8885f04db39d98 \
+    --hash=sha256:dacd995031a01d16eec825bf30802fceb2c3791ef24bcce48fa98ce40918c27b \
+    --hash=sha256:ddf33d97d2f52d89f6e6e7ae66ee35a4d9ca6f36eda89c24591b0c40205a3629 \
+    --hash=sha256:ded0fc7d90fe93ae0b18059930086c51e640cdd3baebdc783a695c77f123dcd9 \
+    --hash=sha256:e3e0210287329272539eea617830a6a28161fbbd8a3271bf4150ae3e58c5d0e6 \
+    --hash=sha256:e6fa2e3e683f34aea77de8112f6483803c96a44fd726d7358b9888ae5bb394ec \
+    --hash=sha256:ea0eb6af8a17fa272f7b98d7bebfab7836a0d62738e16ba380f440fceca2d951 \
+    --hash=sha256:ea7f69de383cb47522c9c208aec6dd17697db7875a4674c4af3f8cfdac0bdeae \
+    --hash=sha256:eac5174677da084abf378739dbf4ad245661635f1600edd1221f150b165343f4 \
+    --hash=sha256:fc4f7a173a5609631bb0c42c23d12c49df3966f89f496a51d3eb0ec81f4519d6 \
+    --hash=sha256:fdb5b3e311d4d4b0eb8b3e8b4d1b0a512713ad7e6a68791d0923d1aec433d919
 referencing==0.35.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:25b42124a6c8b632a425174f24087783efb348a6f1e0008e63cd4466fedf703c \
     --hash=sha256:eda6d3234d62814d1c64e305c1331c9a3a6132da475ab6382eaa997b21ee75de
 requests==2.32.3 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:55365417734eb18255590a9ff9eb97e9e1da868d4ccd6402399eaf68af20a760 \
     --hash=sha256:70761cfe03c773ceb22aa2f671b4757976145175cdfca038c02654d061d6dcc6
-restrictedpython==7.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:56d0c73e5de1757702053383601b0fcd3fb2e428039ee1df860409ad67b17d2b \
-    --hash=sha256:875aeb51c139d78e34cef8605dc65309b449168060dd08551a1fe9edb47cb9a5
+restrictedpython==7.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:139cb41da6e57521745a566d05825f7a09e6a884f7fa922568cff0a70b84ce6b \
+    --hash=sha256:4d1d30f709a6621ca7c4236f08b67b732a651c8099145f137078c7dd4bed3d21
 rfc3339-validator==0.1.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:138a2abdf93304ad60530167e51d2dfb9549521a836871b88d7f4695d0022f6b \
     --hash=sha256:24f6ec1eda14ef823da9e36ec7113124b39c04d50a4d3d3a3c2859577e7791fa
 rfc3986-validator==0.1.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:2f235c432ef459970b4306369336b9d5dbdda31b510ca1e327636e01f528bfa9 \
     --hash=sha256:3d44bde7921b3b9ec3ae4e3adca370438eccebc676456449b145d533b240d055
-rich==13.7.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:4edbae314f59eb482f54e9e30bf00d33350aaa94f4bfcd4e9e3110e64d0d7222 \
-    --hash=sha256:9be308cb1fe2f1f57d67ce99e95af38a1e2bc71ad9813b0e247cf7ffbcc3a432
-rpds-py==0.19.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:01227f8b3e6c8961490d869aa65c99653df80d2f0a7fde8c64ebddab2b9b02fd \
-    --hash=sha256:08ce9c95a0b093b7aec75676b356a27879901488abc27e9d029273d280438505 \
-    --hash=sha256:0b02dd77a2de6e49078c8937aadabe933ceac04b41c5dde5eca13a69f3cf144e \
-    --hash=sha256:0d4b52811dcbc1aba08fd88d475f75b4f6db0984ba12275d9bed1a04b2cae9b5 \
-    --hash=sha256:13e6d4840897d4e4e6b2aa1443e3a8eca92b0402182aafc5f4ca1f5e24f9270a \
-    --hash=sha256:1a129c02b42d46758c87faeea21a9f574e1c858b9f358b6dd0bbd71d17713175 \
-    --hash=sha256:1a8dfa125b60ec00c7c9baef945bb04abf8ac772d8ebefd79dae2a5f316d7850 \
-    --hash=sha256:1c32e41de995f39b6b315d66c27dea3ef7f7c937c06caab4c6a79a5e09e2c415 \
-    --hash=sha256:1d494887d40dc4dd0d5a71e9d07324e5c09c4383d93942d391727e7a40ff810b \
-    --hash=sha256:1d4af2eb520d759f48f1073ad3caef997d1bfd910dc34e41261a595d3f038a94 \
-    --hash=sha256:1fb93d3486f793d54a094e2bfd9cd97031f63fcb5bc18faeb3dd4b49a1c06523 \
-    --hash=sha256:24f8ae92c7fae7c28d0fae9b52829235df83f34847aa8160a47eb229d9666c7b \
-    --hash=sha256:24fc5a84777cb61692d17988989690d6f34f7f95968ac81398d67c0d0994a897 \
-    --hash=sha256:26ab43b6d65d25b1a333c8d1b1c2f8399385ff683a35ab5e274ba7b8bb7dc61c \
-    --hash=sha256:271accf41b02687cef26367c775ab220372ee0f4925591c6796e7c148c50cab5 \
-    --hash=sha256:2ddd50f18ebc05ec29a0d9271e9dbe93997536da3546677f8ca00b76d477680c \
-    --hash=sha256:31dd5794837f00b46f4096aa8ccaa5972f73a938982e32ed817bb520c465e520 \
-    --hash=sha256:31e450840f2f27699d014cfc8865cc747184286b26d945bcea6042bb6aa4d26e \
-    --hash=sha256:32e0db3d6e4f45601b58e4ac75c6f24afbf99818c647cc2066f3e4b192dabb1f \
-    --hash=sha256:346557f5b1d8fd9966059b7a748fd79ac59f5752cd0e9498d6a40e3ac1c1875f \
-    --hash=sha256:34bca66e2e3eabc8a19e9afe0d3e77789733c702c7c43cd008e953d5d1463fde \
-    --hash=sha256:3511f6baf8438326e351097cecd137eb45c5f019944fe0fd0ae2fea2fd26be39 \
-    --hash=sha256:35af5e4d5448fa179fd7fff0bba0fba51f876cd55212f96c8bbcecc5c684ae5c \
-    --hash=sha256:3837c63dd6918a24de6c526277910e3766d8c2b1627c500b155f3eecad8fad65 \
-    --hash=sha256:39d67896f7235b2c886fb1ee77b1491b77049dcef6fbf0f401e7b4cbed86bbd4 \
-    --hash=sha256:3b823be829407393d84ee56dc849dbe3b31b6a326f388e171555b262e8456cc1 \
-    --hash=sha256:3c73254c256081704dba0a333457e2fb815364018788f9b501efe7c5e0ada401 \
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-    --hash=sha256:c7af6f7b80f687b33a4cdb0a785a5d4de1fb027a44c9a049d8eb67d5bfe8a687 \
-    --hash=sha256:c7b07959866a6afb019abb9564d8a55046feb7a84506c74a6f197cbcdf8a208e \
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-    --hash=sha256:ce757c7c90d35719b38fa3d4ca55654a76a40716ee299b0865f2de21c146801c \
-    --hash=sha256:d1fa67ef839bad3815124f5f57e48cd50ff392f4911a9f3cf449d66fa3df62a5 \
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-    --hash=sha256:de1f7cd5b6b351e1afd7568bdab94934d656abe273d66cda0ceea43bbc02a0c2 \
-    --hash=sha256:df7c841813f6265e636fe548a49664c77af31ddfa0085515326342a751a6ba51 \
-    --hash=sha256:e0f9d268b19e8f61bf42a1da48276bcd05f7ab5560311f541d22557f8227b866 \
-    --hash=sha256:e2d66eb41ffca6cc3c91d8387509d27ba73ad28371ef90255c50cb51f8953301 \
-    --hash=sha256:e429fc517a1c5e2a70d576077231538a98d59a45dfc552d1ac45a132844e6dfb \
-    --hash=sha256:e4d2b88efe65544a7d5121b0c3b003ebba92bfede2ea3577ce548b69c5235185 \
-    --hash=sha256:e76c902d229a3aa9d5ceb813e1cbcc69bf5bda44c80d574ff1ac1fa3136dea71 \
-    --hash=sha256:ef07a0a1d254eeb16455d839cef6e8c2ed127f47f014bbda64a58b5482b6c836 \
-    --hash=sha256:f09529d2332264a902688031a83c19de8fda5eb5881e44233286b9c9ec91856d \
-    --hash=sha256:f0a6d4a93d2a05daec7cb885157c97bbb0be4da739d6f9dfb02e101eb40921cd \
-    --hash=sha256:f0cf2a0dbb5987da4bd92a7ca727eadb225581dd9681365beba9accbe5308f7d \
-    --hash=sha256:f2671cb47e50a97f419a02cd1e0c339b31de017b033186358db92f4d8e2e17d8 \
-    --hash=sha256:f35b34a5184d5e0cc360b61664c1c06e866aab077b5a7c538a3e20c8fcdbf90b \
-    --hash=sha256:f3d73022990ab0c8b172cce57c69fd9a89c24fd473a5e79cbce92df87e3d9c48 \
-    --hash=sha256:f5b8353ea1a4d7dfb59a7f45c04df66ecfd363bb5b35f33b11ea579111d4655f \
-    --hash=sha256:f809a17cc78bd331e137caa25262b507225854073fd319e987bd216bed911b7c \
-    --hash=sha256:f9bc4161bd3b970cd6a6fcda70583ad4afd10f2750609fb1f3ca9505050d4ef3 \
-    --hash=sha256:fdf4890cda3b59170009d012fca3294c00140e7f2abe1910e6a730809d0f3f9b
+rich==13.8.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:1760a3c0848469b97b558fc61c85233e3dafb69c7a071b4d60c38099d3cd4c06 \
+    --hash=sha256:8260cda28e3db6bf04d2d1ef4dbc03ba80a824c88b0e7668a0f23126a424844a
+rpds-py==0.20.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:06db23d43f26478303e954c34c75182356ca9aa7797d22c5345b16871ab9c45c \
+    --hash=sha256:0e13e6952ef264c40587d510ad676a988df19adea20444c2b295e536457bc585 \
+    --hash=sha256:11ef6ce74616342888b69878d45e9f779b95d4bd48b382a229fe624a409b72c5 \
+    --hash=sha256:1259c7b3705ac0a0bd38197565a5d603218591d3f6cee6e614e380b6ba61c6f6 \
+    --hash=sha256:18d7585c463087bddcfa74c2ba267339f14f2515158ac4db30b1f9cbdb62c8ef \
+    --hash=sha256:1e0f80b739e5a8f54837be5d5c924483996b603d5502bfff79bf33da06164ee2 \
+    --hash=sha256:1e5f3cd7397c8f86c8cc72d5a791071431c108edd79872cdd96e00abd8497d29 \
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+    --hash=sha256:fcaeb7b57f1a1e071ebd748984359fef83ecb026325b9d4ca847c95bc7311c92 \
+    --hash=sha256:fd2d84f40633bc475ef2d5490b9c19543fbf18596dcb1b291e3a12ea5d722f7a \
+    --hash=sha256:fdfc3a892927458d98f3d55428ae46b921d1f7543b89382fdb483f5640daaec8
+s3transfer==0.10.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:0711534e9356d3cc692fdde846b4a1e4b0cb6519971860796e6bc4c7aea00ef6 \
+    --hash=sha256:eca1c20de70a39daee580aef4986996620f365c4e0fda6a86100231d62f1bf69
 send2trash==1.8.3 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:0c31227e0bd08961c7665474a3d1ef7193929fedda4233843689baa056be46c9 \
     --hash=sha256:b18e7a3966d99871aefeb00cfbcfdced55ce4871194810fc71f4aa484b953abf
@@ -2028,9 +2263,9 @@ sniffio==1.3.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
 snowballstemmer==2.2.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:09b16deb8547d3412ad7b590689584cd0fe25ec8db3be37788be3810cbf19cb1 \
     --hash=sha256:c8e1716e83cc398ae16824e5572ae04e0d9fc2c6b985fb0f900f5f0c96ecba1a
-soupsieve==2.5 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:5663d5a7b3bfaeee0bc4372e7fc48f9cff4940b3eec54a6451cc5299f1097690 \
-    --hash=sha256:eaa337ff55a1579b6549dc679565eac1e3d000563bcb1c8ab0d0fefbc0c2cdc7
+soupsieve==2.6 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:e2e68417777af359ec65daac1057404a3c8a5455bb8abc36f1a9866ab1a51abb \
+    --hash=sha256:e72c4ff06e4fb6e4b5a9f0f55fe6e81514581fca1515028625d0f299c602ccc9
 sphinx-copybutton==0.5.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:4cf17c82fb9646d1bc9ca92ac280813a3b605d8c421225fd9913154103ee1fbd \
     --hash=sha256:fb543fd386d917746c9a2c50360c7905b605726b9355cd26e9974857afeae06e
@@ -2063,59 +2298,62 @@ sphinxcontrib-qthelp==2.0.0 ; python_full_version >= "3.9.1" and python_version
 sphinxcontrib-serializinghtml==2.0.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
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     --hash=sha256:e9d912827f872c029017a53f0ef2180b327c3f7fd23c87229f7a8e8b70031d4d
-sqlalchemy==2.0.31 ; python_full_version >= "3.9.1" and python_version < "3.13" \
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-    --hash=sha256:fa4b1af3e619b5b0b435e333f3967612db06351217c58bfb50cee5f003db2a5a \
-    --hash=sha256:fc6b14e8602f59c6ba893980bea96571dd0ed83d8ebb9c4479d9ed5425d562e9
+sqlalchemy==2.0.35 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:016b2e665f778f13d3c438651dd4de244214b527a275e0acf1d44c05bc6026a9 \
+    --hash=sha256:032d979ce77a6c2432653322ba4cbeabf5a6837f704d16fa38b5a05d8e21fa00 \
+    --hash=sha256:0375a141e1c0878103eb3d719eb6d5aa444b490c96f3fedab8471c7f6ffe70ee \
+    --hash=sha256:042622a5306c23b972192283f4e22372da3b8ddf5f7aac1cc5d9c9b222ab3ff6 \
+    --hash=sha256:05c3f58cf91683102f2f0265c0db3bd3892e9eedabe059720492dbaa4f922da1 \
+    --hash=sha256:0630774b0977804fba4b6bbea6852ab56c14965a2b0c7fc7282c5f7d90a1ae72 \
+    --hash=sha256:0f9f3f9a3763b9c4deb8c5d09c4cc52ffe49f9876af41cc1b2ad0138878453cf \
+    --hash=sha256:1b56961e2d31389aaadf4906d453859f35302b4eb818d34a26fab72596076bb8 \
+    --hash=sha256:22b83aed390e3099584b839b93f80a0f4a95ee7f48270c97c90acd40ee646f0b \
+    --hash=sha256:25b0f63e7fcc2a6290cb5f7f5b4fc4047843504983a28856ce9b35d8f7de03cc \
+    --hash=sha256:2a275a806f73e849e1c309ac11108ea1a14cd7058577aba962cd7190e27c9e3c \
+    --hash=sha256:2ab3f0336c0387662ce6221ad30ab3a5e6499aab01b9790879b6578fd9b8faa1 \
+    --hash=sha256:2e795c2f7d7249b75bb5f479b432a51b59041580d20599d4e112b5f2046437a3 \
+    --hash=sha256:3655af10ebcc0f1e4e06c5900bb33e080d6a1fa4228f502121f28a3b1753cde5 \
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+    --hash=sha256:4c31943b61ed8fdd63dfd12ccc919f2bf95eefca133767db6fbbd15da62078ec \
+    --hash=sha256:4fdcd72a789c1c31ed242fd8c1bcd9ea186a98ee8e5408a50e610edfef980d71 \
+    --hash=sha256:627dee0c280eea91aed87b20a1f849e9ae2fe719d52cbf847c0e0ea34464b3f7 \
+    --hash=sha256:67219632be22f14750f0d1c70e62f204ba69d28f62fd6432ba05ab295853de9b \
+    --hash=sha256:6921ee01caf375363be5e9ae70d08ce7ca9d7e0e8983183080211a062d299468 \
+    --hash=sha256:69683e02e8a9de37f17985905a5eca18ad651bf592314b4d3d799029797d0eb3 \
+    --hash=sha256:6a93c5a0dfe8d34951e8a6f499a9479ffb9258123551fa007fc708ae2ac2bc5e \
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+    --hash=sha256:7befc148de64b6060937231cbff8d01ccf0bfd75aa26383ffdf8d82b12ec04ff \
+    --hash=sha256:890da8cd1941fa3dab28c5bac3b9da8502e7e366f895b3b8e500896f12f94d11 \
+    --hash=sha256:89b64cd8898a3a6f642db4eb7b26d1b28a497d4022eccd7717ca066823e9fb01 \
+    --hash=sha256:8a6219108a15fc6d24de499d0d515c7235c617b2540d97116b663dade1a54d62 \
+    --hash=sha256:8cdf1a0dbe5ced887a9b127da4ffd7354e9c1a3b9bb330dce84df6b70ccb3a8d \
+    --hash=sha256:8d625eddf7efeba2abfd9c014a22c0f6b3796e0ffb48f5d5ab106568ef01ff5a \
+    --hash=sha256:93a71c8601e823236ac0e5d087e4f397874a421017b3318fd92c0b14acf2b6db \
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+    --hash=sha256:a62dd5d7cc8626a3634208df458c5fe4f21200d96a74d122c83bc2015b333bc1 \
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+    --hash=sha256:aee110e4ef3c528f3abbc3c2018c121e708938adeeff9006428dd7c8555e9b3f \
+    --hash=sha256:b76d63495b0508ab9fc23f8152bac63205d2a704cd009a2b0722f4c8e0cba8e0 \
+    --hash=sha256:c0d8326269dbf944b9201911b0d9f3dc524d64779a07518199a58384c3d37a44 \
+    --hash=sha256:c41411e192f8d3ea39ea70e0fae48762cd11a2244e03751a98bd3c0ca9a4e936 \
+    --hash=sha256:c68fe3fcde03920c46697585620135b4ecfdfc1ed23e75cc2c2ae9f8502c10b8 \
+    --hash=sha256:cb8bea573863762bbf45d1e13f87c2d2fd32cee2dbd50d050f83f87429c9e1ea \
+    --hash=sha256:cc32b2990fc34380ec2f6195f33a76b6cdaa9eecf09f0c9404b74fc120aef36f \
+    --hash=sha256:ccae5de2a0140d8be6838c331604f91d6fafd0735dbdcee1ac78fc8fbaba76b4 \
+    --hash=sha256:d299797d75cd747e7797b1b41817111406b8b10a4f88b6e8fe5b5e59598b43b0 \
+    --hash=sha256:e04b622bb8a88f10e439084486f2f6349bf4d50605ac3e445869c7ea5cf0fa8c \
+    --hash=sha256:e11d7ea4d24f0a262bccf9a7cd6284c976c5369dac21db237cff59586045ab9f \
+    --hash=sha256:e21f66748ab725ade40fa7af8ec8b5019c68ab00b929f6643e1b1af461eddb60 \
+    --hash=sha256:eb60b026d8ad0c97917cb81d3662d0b39b8ff1335e3fabb24984c6acd0c900a2 \
+    --hash=sha256:f021d334f2ca692523aaf7bbf7592ceff70c8594fad853416a81d66b35e3abf9 \
+    --hash=sha256:f552023710d4b93d8fb29a91fadf97de89c5926c6bd758897875435f2a939f33
 stack-data==0.6.3 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:836a778de4fec4dcd1dcd89ed8abff8a221f58308462e1c4aa2a3cf30148f0b9 \
     --hash=sha256:d5558e0c25a4cb0853cddad3d77da9891a08cb85dd9f9f91b9f8cd66e511e695
+starlette==0.38.5 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:04a92830a9b6eb1442c766199d62260c3d4dc9c4f9188360626b1e0273cb7077 \
+    --hash=sha256:632f420a9d13e3ee2a6f18f437b0a9f1faecb0bc42e1942aa2ea0e379a4c4206
 tenacity==8.5.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:8bc6c0c8a09b31e6cad13c47afbed1a567518250a9a171418582ed8d9c20ca78 \
     --hash=sha256:b594c2a5945830c267ce6b79a166228323ed52718f30302c1359836112346687
@@ -2125,110 +2363,110 @@ terminado==0.18.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
 tinycss2==1.3.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:152f9acabd296a8375fbca5b84c961ff95971fcfc32e79550c8df8e29118c54d \
     --hash=sha256:54a8dbdffb334d536851be0226030e9505965bb2f30f21a4a82c55fb2a80fae7
-tokenize-rt==5.2.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:9fe80f8a5c1edad2d3ede0f37481cc0cc1538a2f442c9c2f9e4feacd2792d054 \
-    --hash=sha256:b79d41a65cfec71285433511b50271b05da3584a1da144a0752e9c621a285289
-tokenizers==0.19.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:01d62812454c188306755c94755465505836fd616f75067abcae529c35edeb57 \
-    --hash=sha256:02e81bf089ebf0e7f4df34fa0207519f07e66d8491d963618252f2e0729e0b46 \
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-    --hash=sha256:f3bbb7a0c5fcb692950b041ae11067ac54826204318922da754f908d95619fbc \
-    --hash=sha256:f8a9c828277133af13f3859d1b6bf1c3cb6e9e1637df0e45312e6b7c2e622b1f \
-    --hash=sha256:f97660f6c43efd3e0bfd3f2e3e5615bf215680bad6ee3d469df6454b8c6e8256 \
-    --hash=sha256:f9939ca7e58c2758c01b40324a59c034ce0cebad18e0d4563a9b1beab3018243
+tokenize-rt==6.0.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:b9711bdfc51210211137499b5e355d3de5ec88a85d2025c520cbb921b5194367 \
+    --hash=sha256:d4ff7ded2873512938b4f8cbb98c9b07118f01d30ac585a30d7a88353ca36d22
+tokenizers==0.20.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:010ec7f3f7a96adc4c2a34a3ada41fa14b4b936b5628b4ff7b33791258646c6b \
+    --hash=sha256:053c37ecee482cc958fdee53af3c6534286a86f5d35aac476f7c246830e53ae5 \
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+    --hash=sha256:a07eaa8799a92e6af6f472c21a75bf71575de2af3c0284120b7a09297c0de2f3 \
+    --hash=sha256:a11435780f2acd89e8fefe5e81cecf01776f6edb9b3ac95bcb76baee76b30b90 \
+    --hash=sha256:a1158c7174f427182e08baa2a8ded2940f2b4a3e94969a85cc9cfd16004cbcea \
+    --hash=sha256:a4bb8b40ba9eefa621fdcabf04a74aa6038ae3be0c614c6458bd91a4697a452f \
+    --hash=sha256:aa2d4a6fed2a7e3f860c7fc9d48764bb30f2649d83915d66150d6340e06742b8 \
+    --hash=sha256:b3dc750def789cb1de1b5a37657919545e1d9ffa667658b3fa9cb7862407a1b8 \
+    --hash=sha256:b52aa3fd14b2a07588c00a19f66511cff5cca8f7266ca3edcdd17f3512ad159f \
+    --hash=sha256:b5ef0f814084a897e9071fc4a868595f018c5c92889197bdc4bf19018769b148 \
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+    --hash=sha256:baf5d0e1ff44710a95eefc196dd87666ffc609fd447c5e5b68272a7c3d342a1d \
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+    --hash=sha256:c375c6a889aeab44734028bc65cc070acf93ccb0f9368be42b67a98e1063d3f6 \
+    --hash=sha256:c8842c7be2fadb9c9edcee233b1b7fe7ade406c99b0973f07439985c1c1d0683 \
+    --hash=sha256:c8da0fba4d179ddf2607821575998df3c294aa59aa8df5a6646dc64bc7352bce \
+    --hash=sha256:ca4d54260ebe97d59dfa9a30baa20d0c4dd9137d99a8801700055c561145c24e \
+    --hash=sha256:ca6557ac3b83d912dfbb1f70ab56bd4b0594043916688e906ede09f42e192401 \
+    --hash=sha256:cce124264903a8ea6f8f48e1cc7669e5ef638c18bd4ab0a88769d5f92debdf7f \
+    --hash=sha256:d68e15f1815357b059ec266062340c343ea7f98f7f330602df81ffa3474b6122 \
+    --hash=sha256:d7dfd796ab9d909f76fb93080e1c7c8309f196ecb316eb130718cd5e34231c69 \
+    --hash=sha256:d90188d12afd0c75e537f9a1d92f9c7375650188ee4f48fdc76f9e38afbd2251 \
+    --hash=sha256:d98b01a309d4387f3b1c1dd68a8b8136af50376cf146c1b7e8d8ead217a5be4b \
+    --hash=sha256:da06e397182ff53789c506c7833220c192952c57e1581a53f503d8d953e2d67e \
+    --hash=sha256:df6b819c9a19831ebec581e71a7686a54ab45d90faf3842269a10c11d746de0c \
+    --hash=sha256:e13eb000ef540c2280758d1b9cfa5fe424b0424ae4458f440e6340a4f18b2638 \
+    --hash=sha256:e26e6c755ae884c2ea6135cd215bdd0fccafe4ee62405014b8c3cd19954e3ab9 \
+    --hash=sha256:e3144b8acebfa6ae062e8f45f7ed52e4b50fb6c62f93afc8871b525ab9fdcab3 \
+    --hash=sha256:e359f852328e254f070bbd09a19a568421d23388f04aad9f2fb7da7704c7228d \
+    --hash=sha256:e47a82355511c373a4a430c4909dc1e518e00031207b1fec536c49127388886b \
+    --hash=sha256:e48afb75e50449848964e4a67b0da01261dd3aa8df8daecf10db8fd7f5b076eb \
+    --hash=sha256:e5d4069e4714e3f7ba0a4d3d44f9d84a432cd4e4aa85c3d7dd1f51440f12e4a1 \
+    --hash=sha256:e5e56df0e8ed23ba60ae3848c3f069a0710c4b197218fe4f89e27eba38510768 \
+    --hash=sha256:e738cfd80795fcafcef89c5731c84b05638a4ab3f412f97d5ed7765466576eb1 \
+    --hash=sha256:ec53e5ecc142a82432f9c6c677dbbe5a2bfee92b8abf409a9ecb0d425ee0ce75 \
+    --hash=sha256:ef703efedf4c20488a8eb17637b55973745b27997ff87bad88ed499b397d1144 \
+    --hash=sha256:f18661ece72e39c0dfaa174d6223248a15b457dbd4b0fc07809b8e6d3ca1a234 \
+    --hash=sha256:f7065b1084d8d1a03dc89d9aad69bcbc8415d4bc123c367063eb32958cd85054 \
+    --hash=sha256:f830b318ee599e3d0665b3e325f85bc75ee2d2ca6285f52e439dc22b64691580 \
+    --hash=sha256:fab3cf066ff426f7e6d70435dc28a9ff01b2747be83810e397cba106f39430b0 \
+    --hash=sha256:fada996d6da8cf213f6e3c91c12297ad4f6cdf7a85c2fadcd05ec32fa6846fcd \
+    --hash=sha256:fc1e1b791e8c3bf4c4f265f180dadaff1c957bf27129e16fdd5e5d43c2d3762c
 toml-sort==0.23.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:69ae60de9c4d67478533697eb4119092e2b30ddffe5ca09bbad3912905c935a0 \
     --hash=sha256:833728c48b0f8d509aecd9ae8347768ca3a9332977b32c9fd2002932f0eb9c90
@@ -2238,9 +2476,9 @@ toml==0.10.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
 tomli==2.0.1 ; python_full_version >= "3.9.1" and python_version < "3.11" \
     --hash=sha256:939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc \
     --hash=sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f
-tomlkit==0.13.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:08ad192699734149f5b97b45f1f18dad7eb1b6d16bc72ad0c2335772650d7b72 \
-    --hash=sha256:7075d3042d03b80f603482d69bf0c8f345c2b30e41699fd8883227f89972b264
+tomlkit==0.13.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:7a974427f6e119197f670fbbbeae7bef749a6c14e793db934baefc1b5f03efde \
+    --hash=sha256:fff5fe59a87295b278abd31bec92c15d9bc4a06885ab12bcea52c71119392e79
 tornado==6.4.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:163b0aafc8e23d8cdc3c9dfb24c5368af84a81e3364745ccb4427669bf84aec8 \
     --hash=sha256:25486eb223babe3eed4b8aecbac33b37e3dd6d776bc730ca14e1bf93888b979f \
@@ -2253,136 +2491,144 @@ tornado==6.4.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:b24b8982ed444378d7f21d563f4180a2de31ced9d8d84443907a0a64da2072e7 \
     --hash=sha256:d9a566c40b89757c9aa8e6f032bcdb8ca8795d7c1a9762910c722b1635c9de4d \
     --hash=sha256:e2e20b9113cd7293f164dc46fffb13535266e713cdb87bd2d15ddb336e96cfc4
-tqdm==4.66.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:b75ca56b413b030bc3f00af51fd2c1a1a5eac6a0c1cca83cbb37a5c52abce644 \
-    --hash=sha256:e4d936c9de8727928f3be6079590e97d9abfe8d39a590be678eb5919ffc186bb
+tqdm==4.66.5 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:90279a3770753eafc9194a0364852159802111925aa30eb3f9d85b0e805ac7cd \
+    --hash=sha256:e1020aef2e5096702d8a025ac7d16b1577279c9d63f8375b63083e9a5f0fcbad
 traitlets==5.14.3 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:9ed0579d3502c94b4b3732ac120375cda96f923114522847de4b3bb98b96b6b7 \
     --hash=sha256:b74e89e397b1ed28cc831db7aea759ba6640cb3de13090ca145426688ff1ac4f
-types-python-dateutil==2.9.0.20240316 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:5d2f2e240b86905e40944dd787db6da9263f0deabef1076ddaed797351ec0202 \
-    --hash=sha256:6b8cb66d960771ce5ff974e9dd45e38facb81718cc1e208b10b1baccbfdbee3b
+types-python-dateutil==2.9.0.20240906 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:27c8cc2d058ccb14946eebcaaa503088f4f6dbc4fb6093d3d456a49aef2753f6 \
+    --hash=sha256:9706c3b68284c25adffc47319ecc7947e5bb86b3773f843c73906fd598bc176e
 typing-extensions==4.12.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d \
     --hash=sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8
+typing-inspect==0.9.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:9ee6fc59062311ef8547596ab6b955e1b8aa46242d854bfc78f4f6b0eff35f9f \
+    --hash=sha256:b23fc42ff6f6ef6954e4852c1fb512cdd18dbea03134f91f856a95ccc9461f78
 tzdata==2024.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:2674120f8d891909751c38abcdfd386ac0a5a1127954fbc332af6b5ceae07efd \
     --hash=sha256:9068bc196136463f5245e51efda838afa15aaeca9903f49050dfa2679db4d252
 uri-template==1.3.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:0e00f8eb65e18c7de20d595a14336e9f337ead580c70934141624b6d1ffdacc7 \
     --hash=sha256:a44a133ea12d44a0c0f06d7d42a52d71282e77e2f937d8abd5655b8d56fc1363
-urllib3==2.2.2 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:a448b2f64d686155468037e1ace9f2d2199776e17f0a46610480d311f73e3472 \
-    --hash=sha256:dd505485549a7a552833da5e6063639d0d177c04f23bc3864e41e5dc5f612168
-virtualenv==20.26.3 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:4c43a2a236279d9ea36a0d76f98d84bd6ca94ac4e0f4a3b9d46d05e10fea542a \
-    --hash=sha256:8cc4a31139e796e9a7de2cd5cf2489de1217193116a8fd42328f1bd65f434589
+urllib3==1.26.20 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:0ed14ccfbf1c30a9072c7ca157e4319b70d65f623e91e7b32fadb2853431016e \
+    --hash=sha256:40c2dc0c681e47eb8f90e7e27bf6ff7df2e677421fd46756da1161c39ca70d32
+uvicorn==0.30.6 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:4b15decdda1e72be08209e860a1e10e92439ad5b97cf44cc945fcbee66fc5788 \
+    --hash=sha256:65fd46fe3fda5bdc1b03b94eb634923ff18cd35b2f084813ea79d1f103f711b5
+virtualenv==20.26.5 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:4f3ac17b81fba3ce3bd6f4ead2749a72da5929c01774948e243db9ba41df4ff6 \
+    --hash=sha256:ce489cac131aa58f4b25e321d6d186171f78e6cb13fafbf32a840cee67733ff4
 wcwidth==0.2.13 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859 \
     --hash=sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5
-webcolors==24.6.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:1d160d1de46b3e81e58d0a280d0c78b467dc80f47294b91b1ad8029d2cedb55b \
-    --hash=sha256:8cf5bc7e28defd1d48b9e83d5fc30741328305a8195c29a8e668fa45586568a1
+webcolors==24.8.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:08b07af286a01bcd30d583a7acadf629583d1f79bfef27dd2c2c5c263817277d \
+    --hash=sha256:fc4c3b59358ada164552084a8ebee637c221e4059267d0f8325b3b560f6c7f0a
 webencodings==0.5.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78 \
     --hash=sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923
 websocket-client==1.8.0 ; python_full_version >= "3.9.1" and python_version < "3.13" \
     --hash=sha256:17b44cc997f5c498e809b22cdf2d9c7a9e71c02c8cc2b6c56e7c2d1239bfa526 \
     --hash=sha256:3239df9f44da632f96012472805d40a23281a991027ce11d2f45a6f24ac4c3da
-widgetsnbextension==4.0.11 ; python_full_version >= "3.9.1" and python_version < "3.13" \
-    --hash=sha256:55d4d6949d100e0d08b94948a42efc3ed6dfdc0e9468b2c4b128c9a2ce3a7a36 \
-    --hash=sha256:8b22a8f1910bfd188e596fe7fc05dcbd87e810c8a4ba010bdb3da86637398474
-yarl==1.9.4 ; python_full_version >= "3.9.1" and python_version < "3.13" \
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-zipp==3.19.2 ; python_full_version >= "3.9.1" and python_version < "3.10" \
-    --hash=sha256:bf1dcf6450f873a13e952a29504887c89e6de7506209e5b1bcc3460135d4de19 \
-    --hash=sha256:f091755f667055f2d02b32c53771a7a6c8b47e1fdbc4b72a8b9072b3eef8015c
+widgetsnbextension==4.0.13 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:74b2692e8500525cc38c2b877236ba51d34541e6385eeed5aec15a70f88a6c71 \
+    --hash=sha256:ffcb67bc9febd10234a362795f643927f4e0c05d9342c727b65d2384f8feacb6
+yarl==1.11.1 ; python_full_version >= "3.9.1" and python_version < "3.13" \
+    --hash=sha256:01a8697ec24f17c349c4f655763c4db70eebc56a5f82995e5e26e837c6eb0e49 \
+    --hash=sha256:02da8759b47d964f9173c8675710720b468aa1c1693be0c9c64abb9d8d9a4867 \
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+    --hash=sha256:69721b8effdb588cb055cc22f7c5105ca6fdaa5aeb3ea09021d517882c4a904c \
+    --hash=sha256:6d23754b9939cbab02c63434776df1170e43b09c6a517585c7ce2b3d449b7318 \
+    --hash=sha256:7175a87ab8f7fbde37160a15e58e138ba3b2b0e05492d7351314a250d61b1591 \
+    --hash=sha256:72bf26f66456baa0584eff63e44545c9f0eaed9b73cb6601b647c91f14c11f38 \
+    --hash=sha256:74db2ef03b442276d25951749a803ddb6e270d02dda1d1c556f6ae595a0d76a8 \
+    --hash=sha256:750f656832d7d3cb0c76be137ee79405cc17e792f31e0a01eee390e383b2936e \
+    --hash=sha256:75e0ae31fb5ccab6eda09ba1494e87eb226dcbd2372dae96b87800e1dcc98804 \
+    --hash=sha256:768ecc550096b028754ea28bf90fde071c379c62c43afa574edc6f33ee5daaec \
+    --hash=sha256:7d51324a04fc4b0e097ff8a153e9276c2593106a811704025bbc1d6916f45ca6 \
+    --hash=sha256:7e975a2211952a8a083d1b9d9ba26472981ae338e720b419eb50535de3c02870 \
+    --hash=sha256:8215f6f21394d1f46e222abeb06316e77ef328d628f593502d8fc2a9117bde83 \
+    --hash=sha256:8258c86f47e080a258993eed877d579c71da7bda26af86ce6c2d2d072c11320d \
+    --hash=sha256:8418c053aeb236b20b0ab8fa6bacfc2feaaf7d4683dd96528610989c99723d5f \
+    --hash=sha256:87f020d010ba80a247c4abc335fc13421037800ca20b42af5ae40e5fd75e7909 \
+    --hash=sha256:884eab2ce97cbaf89f264372eae58388862c33c4f551c15680dd80f53c89a269 \
+    --hash=sha256:8a336eaa7ee7e87cdece3cedb395c9657d227bfceb6781295cf56abcd3386a26 \
+    --hash=sha256:8aef1b64da41d18026632d99a06b3fefe1d08e85dd81d849fa7c96301ed22f1b \
+    --hash=sha256:8aef97ba1dd2138112890ef848e17d8526fe80b21f743b4ee65947ea184f07a2 \
+    --hash=sha256:8ed653638ef669e0efc6fe2acb792275cb419bf9cb5c5049399f3556995f23c7 \
+    --hash=sha256:9361628f28f48dcf8b2f528420d4d68102f593f9c2e592bfc842f5fb337e44fd \
+    --hash=sha256:946eedc12895873891aaceb39bceb484b4977f70373e0122da483f6c38faaa68 \
+    --hash=sha256:94d0caaa912bfcdc702a4204cd5e2bb01eb917fc4f5ea2315aa23962549561b0 \
+    --hash=sha256:964a428132227edff96d6f3cf261573cb0f1a60c9a764ce28cda9525f18f7786 \
+    --hash=sha256:999bfee0a5b7385a0af5ffb606393509cfde70ecca4f01c36985be6d33e336da \
+    --hash=sha256:a08ea567c16f140af8ddc7cb58e27e9138a1386e3e6e53982abaa6f2377b38cc \
+    --hash=sha256:a28b70c9e2213de425d9cba5ab2e7f7a1c8ca23a99c4b5159bf77b9c31251447 \
+    --hash=sha256:a34e1e30f1774fa35d37202bbeae62423e9a79d78d0874e5556a593479fdf239 \
+    --hash=sha256:a4264515f9117be204935cd230fb2a052dd3792789cc94c101c535d349b3dab0 \
+    --hash=sha256:a7915ea49b0c113641dc4d9338efa9bd66b6a9a485ffe75b9907e8573ca94b84 \
+    --hash=sha256:aac44097d838dda26526cffb63bdd8737a2dbdf5f2c68efb72ad83aec6673c7e \
+    --hash=sha256:b91044952da03b6f95fdba398d7993dd983b64d3c31c358a4c89e3c19b6f7aef \
+    --hash=sha256:ba444bdd4caa2a94456ef67a2f383710928820dd0117aae6650a4d17029fa25e \
+    --hash=sha256:c2dc4250fe94d8cd864d66018f8344d4af50e3758e9d725e94fecfa27588ff82 \
+    --hash=sha256:c35f493b867912f6fda721a59cc7c4766d382040bdf1ddaeeaa7fa4d072f4675 \
+    --hash=sha256:c92261eb2ad367629dc437536463dc934030c9e7caca861cc51990fe6c565f26 \
+    --hash=sha256:ce928c9c6409c79e10f39604a7e214b3cb69552952fbda8d836c052832e6a979 \
+    --hash=sha256:d95b52fbef190ca87d8c42f49e314eace4fc52070f3dfa5f87a6594b0c1c6e46 \
+    --hash=sha256:dae7bd0daeb33aa3e79e72877d3d51052e8b19c9025ecf0374f542ea8ec120e4 \
+    --hash=sha256:e286580b6511aac7c3268a78cdb861ec739d3e5a2a53b4809faef6b49778eaff \
+    --hash=sha256:e4b53f73077e839b3f89c992223f15b1d2ab314bdbdf502afdc7bb18e95eae27 \
+    --hash=sha256:e8f63904df26d1a66aabc141bfd258bf738b9bc7bc6bdef22713b4f5ef789a4c \
+    --hash=sha256:f3a6d90cab0bdf07df8f176eae3a07127daafcf7457b997b2bf46776da2c7eb7 \
+    --hash=sha256:f41fa79114a1d2eddb5eea7b912d6160508f57440bd302ce96eaa384914cd265 \
+    --hash=sha256:f46f81501160c28d0c0b7333b4f7be8983dbbc161983b6fb814024d1b4952f79 \
+    --hash=sha256:f61db3b7e870914dbd9434b560075e0366771eecbe6d2b5561f5bc7485f39efd
+zipp==3.20.2 ; python_full_version >= "3.9.1" and python_version < "3.10" \
+    --hash=sha256:a817ac80d6cf4b23bf7f2828b7cabf326f15a001bea8b1f9b49631780ba28350 \
+    --hash=sha256:bc9eb26f4506fda01b81bcde0ca78103b6e62f991b381fec825435c836edbc29
diff --git a/docs/results.rst b/docs/results.rst
index 80b18a631..6d800849f 100644
--- a/docs/results.rst
+++ b/docs/results.rst
@@ -1272,8 +1272,9 @@ See the :ref:`exceptions` section for more information on exceptions.
 
 Result class
 ------------
+
 .. automodule:: edsl.results.Result
-   :members: rich_print, 
+   :members:  
    :inherited-members:
    :exclude-members: 
    :undoc-members:
@@ -1281,6 +1282,7 @@ Result class
 
 Results class
 -------------
+
 .. automodule:: edsl.results.Results
    :members:
    :inherited-members:
diff --git a/docs/token_usage.rst b/docs/token_usage.rst
index 98d9ae7ff..5edd837fa 100644
--- a/docs/token_usage.rst
+++ b/docs/token_usage.rst
@@ -241,6 +241,8 @@ Here we also pass the parameter `include_comment = False`:
 
 Output:
 
+.. code-block:: text
+
     ┏━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
     ┃ question_index    ┃ user_prompt                                                                                 ┃
     ┡━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
@@ -293,6 +295,8 @@ The prompts can also be inspected after the survey is run:
 
 Output:
 
+.. code-block:: text
+
     ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
     ┃ prompt                    ┃ generated_tokens           ┃ prompt                    ┃ generated_tokens           ┃
     ┃ .income_pref_user_prompt  ┃ .income_pref_generated_to… ┃ .income_pref_coded_user_… ┃ .income_pref_coded_genera… ┃
diff --git a/edsl/agents/PromptConstructor.py b/edsl/agents/PromptConstructor.py
index 63618644d..f2b0e563f 100644
--- a/edsl/agents/PromptConstructor.py
+++ b/edsl/agents/PromptConstructor.py
@@ -220,6 +220,11 @@ def agent_persona_prompt(self) -> Prompt:
 
         """
         if not hasattr(self, "_agent_persona_prompt"):
+            from edsl import Agent
+
+            if self.agent == Agent():  # if agent is empty, then return an empty prompt
+                return Prompt(text="")
+
             if not hasattr(self.agent, "agent_persona"):
                 applicable_prompts = prompt_lookup(
                     component_type="agent_persona",
diff --git a/edsl/data_transfer_models.py b/edsl/data_transfer_models.py
index f65b4e4ea..b4a33865a 100644
--- a/edsl/data_transfer_models.py
+++ b/edsl/data_transfer_models.py
@@ -1,5 +1,7 @@
 from typing import NamedTuple, Dict, List, Optional, Any
-from dataclasses import dataclass
+from dataclasses import dataclass, fields
+import reprlib
+
 
 
 class ModelInputs(NamedTuple):
@@ -54,77 +56,19 @@ class ImageInfo:
     file_size: int
     encoded_image: str
 
+    def __repr__(self):
+        reprlib_instance = reprlib.Repr()
+        reprlib_instance.maxstring = 30  # Limit the string length for the encoded image
+
+        # Get all fields except encoded_image
+        field_reprs = [
+            f"{f.name}={getattr(self, f.name)!r}"
+            for f in fields(self)
+            if f.name != "encoded_image"
+        ]
+
+        # Add the reprlib-restricted encoded_image field
+        field_reprs.append(f"encoded_image={reprlib_instance.repr(self.encoded_image)}")
 
-# from collections import UserDict
-
-
-# class AgentResponseDict(UserDict):
-#     """A dictionary to store the response of the agent to a question."""
-
-#     def __init__(
-#         self,
-#         *,
-#         question_name,
-#         answer,
-#         prompts,
-#         generated_tokens: str,
-#         usage=None,
-#         comment=None,
-#         cached_response=None,
-#         raw_model_response=None,
-#         simple_model_raw_response=None,
-#         cache_used=None,
-#         cache_key=None,
-#     ):
-#         """Initialize the AgentResponseDict object."""
-#         usage = usage or {"prompt_tokens": 0, "completion_tokens": 0}
-#         if generated_tokens is None:
-#             raise ValueError("generated_tokens must be provided")
-#         self.data = {
-#             "answer": answer,
-#             "comment": comment,
-#             "question_name": question_name,
-#             "prompts": prompts,
-#             "usage": usage,
-#             "cached_response": cached_response,
-#             "raw_model_response": raw_model_response,
-#             "simple_model_raw_response": simple_model_raw_response,
-#             "cache_used": cache_used,
-#             "cache_key": cache_key,
-#             "generated_tokens": generated_tokens,
-#         }
-
-#     @property
-#     def data(self):
-#         return self._data
-
-#     @data.setter
-#     def data(self, value):
-#         self._data = value
-
-#     def __getitem__(self, key):
-#         return self.data.get(key, None)
-
-#     def __setitem__(self, key, value):
-#         self.data[key] = value
-
-#     def __delitem__(self, key):
-#         del self.data[key]
-
-#     def __iter__(self):
-#         return iter(self.data)
-
-#     def __len__(self):
-#         return len(self.data)
-
-#     def keys(self):
-#         return self.data.keys()
-
-#     def values(self):
-#         return self.data.values()
-
-#     def items(self):
-#         return self.data.items()
-
-#     def is_this_same_model(self):
-#         return True
+        # Join everything to create the repr
+        return f"{self.__class__.__name__}({', '.join(field_reprs)})"
diff --git a/edsl/inference_services/TestService.py b/edsl/inference_services/TestService.py
index 8fe54db30..474b953bf 100644
--- a/edsl/inference_services/TestService.py
+++ b/edsl/inference_services/TestService.py
@@ -56,10 +56,14 @@ def _canned_response(self):
                     return "Hello, world"
 
             async def async_execute_model_call(
-                self, user_prompt: str, system_prompt: str
+                self,
+                user_prompt: str,
+                system_prompt: str,
+                encoded_image=None,
             ) -> dict[str, Any]:
                 await asyncio.sleep(0.1)
                 # return {"message": """{"answer": "Hello, world"}"""}
+
                 if hasattr(self, "throw_exception") and self.throw_exception:
                     if hasattr(self, "exception_probability"):
                         p = self.exception_probability
diff --git a/edsl/language_models/LanguageModel.py b/edsl/language_models/LanguageModel.py
index 36abc0011..3289b3d00 100644
--- a/edsl/language_models/LanguageModel.py
+++ b/edsl/language_models/LanguageModel.py
@@ -465,12 +465,13 @@ async def _async_get_intended_model_call_outcome(
         if encoded_image:
             # the image has is appended to the user_prompt for hash-lookup purposes
             image_hash = hashlib.md5(encoded_image.encode()).hexdigest()
+            user_prompt += f" {image_hash}"
 
         cache_call_params = {
             "model": str(self.model),
             "parameters": self.parameters,
             "system_prompt": system_prompt,
-            "user_prompt": user_prompt + "" if not encoded_image else f" {image_hash}",
+            "user_prompt": user_prompt,
             "iteration": iteration,
         }
         cached_response, cache_key = cache.fetch(**cache_call_params)
diff --git a/edsl/surveys/Survey.py b/edsl/surveys/Survey.py
index fb7ecc10d..8cf94d8ae 100644
--- a/edsl/surveys/Survey.py
+++ b/edsl/surveys/Survey.py
@@ -866,6 +866,7 @@ def add_stop_rule(
 
     def clear_non_default_rules(self) -> Survey:
         """Remove all non-default rules from the survey.
+
         >>> Survey.example().show_rules()
         ┏━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━┓
         ┃ current_q ┃ expression  ┃ next_q ┃ priority ┃ before_rule ┃
diff --git a/poetry.lock b/poetry.lock
index 878afe11d..ec222146e 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
 
 [[package]]
 name = "aiohappyeyeballs"
@@ -185,13 +185,13 @@ vertex = ["google-auth (>=2,<3)"]
 
 [[package]]
 name = "anyio"
-version = "4.4.0"
+version = "4.6.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.4.0-py3-none-any.whl", hash = "sha256:c1b2d8f46a8a812513012e1107cb0e68c17159a7a594208005a57dc776e1bdc7"},
-    {file = "anyio-4.4.0.tar.gz", hash = "sha256:5aadc6a1bbb7cdb0bede386cac5e2940f5e2ff3aa20277e991cf028e0585ce94"},
+    {file = "anyio-4.6.0-py3-none-any.whl", hash = "sha256:c7d2e9d63e31599eeb636c8c5c03a7e108d73b345f064f1c19fdc87b79036a9a"},
+    {file = "anyio-4.6.0.tar.gz", hash = "sha256:137b4559cbb034c477165047febb6ff83f390fc3b20bf181c1fc0a728cb8beeb"},
 ]
 
 [package.dependencies]
@@ -201,9 +201,9 @@ sniffio = ">=1.1"
 typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
 
 [package.extras]
-doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
-test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
-trio = ["trio (>=0.23)"]
+doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.21.0b1)"]
+trio = ["trio (>=0.26.1)"]
 
 [[package]]
 name = "appnope"
@@ -294,13 +294,13 @@ test = ["dateparser (==1.*)", "pre-commit", "pytest", "pytest-cov", "pytest-mock
 
 [[package]]
 name = "astroid"
-version = "3.2.4"
+version = "3.3.3"
 description = "An abstract syntax tree for Python with inference support."
 optional = false
-python-versions = ">=3.8.0"
+python-versions = ">=3.9.0"
 files = [
-    {file = "astroid-3.2.4-py3-none-any.whl", hash = "sha256:413658a61eeca6202a59231abb473f932038fbcbf1666587f66d482083413a25"},
-    {file = "astroid-3.2.4.tar.gz", hash = "sha256:0e14202810b30da1b735827f78f5157be2bbd4a7a59b7707ca0bfc2fb4c0063a"},
+    {file = "astroid-3.3.3-py3-none-any.whl", hash = "sha256:2d79acfd3c594b6a2d4141fea98a1d62ab4a52e54332b1f1ddcf07b652cc5c0f"},
+    {file = "astroid-3.3.3.tar.gz", hash = "sha256:63f8c5370d9bad8294163c87b2d440a7fdf546be6c72bbeac0549c93244dbd72"},
 ]
 
 [package.dependencies]
@@ -386,13 +386,13 @@ typing-extensions = ">=4.6.0"
 
 [[package]]
 name = "azure-core"
-version = "1.30.2"
+version = "1.31.0"
 description = "Microsoft Azure Core Library for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "azure-core-1.30.2.tar.gz", hash = "sha256:a14dc210efcd608821aa472d9fb8e8d035d29b68993819147bc290a8ac224472"},
-    {file = "azure_core-1.30.2-py3-none-any.whl", hash = "sha256:cf019c1ca832e96274ae85abd3d9f752397194d9fea3b41487290562ac8abe4a"},
+    {file = "azure_core-1.31.0-py3-none-any.whl", hash = "sha256:22954de3777e0250029360ef31d80448ef1be13b80a459bff80ba7073379e2cd"},
+    {file = "azure_core-1.31.0.tar.gz", hash = "sha256:656a0dd61e1869b1506b7c6a3b31d62f15984b1a573d6326f6aa2f3e4123284b"},
 ]
 
 [package.dependencies]
@@ -506,17 +506,17 @@ css = ["tinycss2 (>=1.1.0,<1.3)"]
 
 [[package]]
 name = "boto3"
-version = "1.35.17"
+version = "1.35.24"
 description = "The AWS SDK for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "boto3-1.35.17-py3-none-any.whl", hash = "sha256:67268aa6c4043e9fdeb4ab3c1e9032f44a6fa168c789af5e351f63f1f8880a2f"},
-    {file = "boto3-1.35.17.tar.gz", hash = "sha256:4a32db8793569ee5f13c5bf3efb260193353cb8946bf6426e3c330b61c68e59d"},
+    {file = "boto3-1.35.24-py3-none-any.whl", hash = "sha256:97fcc1a14cbc759e4ba9535ced703a99fcf652c9c4b8dfcd06f292c80551684b"},
+    {file = "boto3-1.35.24.tar.gz", hash = "sha256:be7807f30f26d6c0057e45cfd09dad5968e664488bf4f9138d0bb7a0f6d8ed40"},
 ]
 
 [package.dependencies]
-botocore = ">=1.35.17,<1.36.0"
+botocore = ">=1.35.24,<1.36.0"
 jmespath = ">=0.7.1,<2.0.0"
 s3transfer = ">=0.10.0,<0.11.0"
 
@@ -525,13 +525,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.35.17"
+version = "1.35.24"
 description = "Low-level, data-driven core of boto 3."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "botocore-1.35.17-py3-none-any.whl", hash = "sha256:a93f773ca93139529b5d36730b382dbee63ab4c7f26129aa5c84835255ca999d"},
-    {file = "botocore-1.35.17.tar.gz", hash = "sha256:0d35d03ea647b5d464c7f77bdab6fb23ae5d49752b13cf97ab84444518c7b1bd"},
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+[[package]]
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+description = "Like `typing._eval_type`, but lets older Python versions use newer typing features."
+optional = false
+python-versions = ">=3.8"
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+
+[package.extras]
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+
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@@ -1126,13 +1140,13 @@ tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipyth
 
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+version = "29.0.0"
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 [[package]]
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@@ -1557,13 +1578,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
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+version = "0.25.0"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
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 python-versions = ">=3.8.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -1591,13 +1612,13 @@ typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "t
 
 [[package]]
 name = "identify"
-version = "2.6.0"
+version = "2.6.1"
 description = "File identification library for Python"
 optional = false
 python-versions = ">=3.8"
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 ]
 
 [package.extras]
@@ -1605,15 +1626,18 @@ license = ["ukkonen"]
 
 [[package]]
 name = "idna"
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+version = "3.10"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.6"
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 ]
 
+[package.extras]
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+
 [[package]]
 name = "imagesize"
 version = "1.4.1"
@@ -2039,13 +2063,13 @@ notebook = "*"
 
 [[package]]
 name = "jupyter-client"
-version = "8.6.2"
+version = "8.6.3"
 description = "Jupyter protocol implementation and client libraries"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -2775,20 +2799,21 @@ files = [
 
 [[package]]
 name = "mistralai"
-version = "1.0.3"
+version = "1.1.0"
 description = "Python Client SDK for the Mistral AI API."
 optional = false
 python-versions = "<4.0,>=3.8"
 files = [
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 [package.dependencies]
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 httpx = ">=0.27.0,<0.28.0"
 jsonpath-python = ">=1.0.6,<2.0.0"
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 typing-inspect = ">=0.9.0,<0.10.0"
 
 [package.extras]
@@ -3202,13 +3227,13 @@ files = [
 
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 python-versions = ">=3.7.1"
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 ]
 
 [package.dependencies]
@@ -3483,13 +3521,13 @@ xmp = ["defusedxml"]
 
 [[package]]
 name = "platformdirs"
-version = "4.3.2"
+version = "4.3.6"
 description = "A small Python package for determining appropriate platform-specific dirs, e.g. a `user data dir`."
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.extras]
@@ -3556,13 +3594,13 @@ virtualenv = ">=20.10.0"
 
 [[package]]
 name = "prometheus-client"
-version = "0.20.0"
+version = "0.21.0"
 description = "Python client for the Prometheus monitoring system."
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.extras]
@@ -3649,119 +3687,120 @@ files = [
 
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 description = "Data validation using Python type hints"
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 python-versions = ">=3.8"
 files = [
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+    {file = "SQLAlchemy-2.0.35-cp38-cp38-win32.whl", hash = "sha256:d299797d75cd747e7797b1b41817111406b8b10a4f88b6e8fe5b5e59598b43b0"},
+    {file = "SQLAlchemy-2.0.35-cp38-cp38-win_amd64.whl", hash = "sha256:0375a141e1c0878103eb3d719eb6d5aa444b490c96f3fedab8471c7f6ffe70ee"},
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+    {file = "SQLAlchemy-2.0.35-cp39-cp39-win_amd64.whl", hash = "sha256:aee110e4ef3c528f3abbc3c2018c121e708938adeeff9006428dd7c8555e9b3f"},
+    {file = "SQLAlchemy-2.0.35-py3-none-any.whl", hash = "sha256:2ab3f0336c0387662ce6221ad30ab3a5e6499aab01b9790879b6578fd9b8faa1"},
+    {file = "sqlalchemy-2.0.35.tar.gz", hash = "sha256:e11d7ea4d24f0a262bccf9a7cd6284c976c5369dac21db237cff59586045ab9f"},
 ]
 
 [package.dependencies]
@@ -5429,13 +5468,13 @@ standard = ["colorama (>=0.4)", "httptools (>=0.5.0)", "python-dotenv (>=0.13)",
 
 [[package]]
 name = "virtualenv"
-version = "20.26.4"
+version = "20.26.5"
 description = "Virtual Python Environment builder"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "virtualenv-20.26.4-py3-none-any.whl", hash = "sha256:48f2695d9809277003f30776d155615ffc11328e6a0a8c1f0ec80188d7874a55"},
-    {file = "virtualenv-20.26.4.tar.gz", hash = "sha256:c17f4e0f3e6036e9f26700446f85c76ab11df65ff6d8a9cbfad9f71aabfcf23c"},
+    {file = "virtualenv-20.26.5-py3-none-any.whl", hash = "sha256:4f3ac17b81fba3ce3bd6f4ead2749a72da5929c01774948e243db9ba41df4ff6"},
+    {file = "virtualenv-20.26.5.tar.gz", hash = "sha256:ce489cac131aa58f4b25e321d6d186171f78e6cb13fafbf32a840cee67733ff4"},
 ]
 
 [package.dependencies]
@@ -5618,13 +5657,13 @@ multidict = ">=4.0"
 
 [[package]]
 name = "zipp"
-version = "3.20.1"
+version = "3.20.2"
 description = "Backport of pathlib-compatible object wrapper for zip files"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "zipp-3.20.1-py3-none-any.whl", hash = "sha256:9960cd8967c8f85a56f920d5d507274e74f9ff813a0ab8889a5b5be2daf44064"},
-    {file = "zipp-3.20.1.tar.gz", hash = "sha256:c22b14cc4763c5a5b04134207736c107db42e9d3ef2d9779d465f5f1bcba572b"},
+    {file = "zipp-3.20.2-py3-none-any.whl", hash = "sha256:a817ac80d6cf4b23bf7f2828b7cabf326f15a001bea8b1f9b49631780ba28350"},
+    {file = "zipp-3.20.2.tar.gz", hash = "sha256:bc9eb26f4506fda01b81bcde0ca78103b6e62f991b381fec825435c836edbc29"},
 ]
 
 [package.extras]
diff --git a/pyproject.toml b/pyproject.toml
index ad4f57359..76ede47ee 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -47,6 +47,7 @@ azure-ai-inference = "^1.0.0b3"
 openpyxl = "^3.1.5"
 json-repair = "^0.28.4"
 mistralai = "^1.0.2"
+urllib3 = ">=1.25.4,<1.27"
 
 [tool.poetry.dependencies.black]
 extras = ["jupyter"]


Test patch:
diff --git a/tests/language_models/test_LanguageModel.py b/tests/language_models/test_LanguageModel.py
index 31c39f703..0659335cd 100644
--- a/tests/language_models/test_LanguageModel.py
+++ b/tests/language_models/test_LanguageModel.py
@@ -37,15 +37,56 @@ def test_tokens(self):
     def test_execute_model_call(self):
         from edsl.data.Cache import Cache
 
+        example_cache = Cache()
+
         m = LanguageModel.example(test_model=True, canned_response="Hello, world!")
         imco = m._get_intended_model_call_outcome(
             user_prompt="Hello world",
             system_prompt="You are a helpful agent",
-            cache=Cache(),
+            cache=example_cache,
         )
         self.assertEqual(imco.response["message"][0]["text"], "Hello, world!")
         self.assertEqual(imco.cached_response, None)
 
+        self.assertEqual(len(example_cache), 1)
+
+        self.assertEqual(
+            list(example_cache.data.values())[0]["user_prompt"], "Hello world"
+        )
+
+        imco = m._get_intended_model_call_outcome(
+            user_prompt="Hello world",
+            system_prompt="You are a helpful agent",
+            cache=example_cache,
+        )
+
+        self.assertEqual(len(example_cache), 1)
+
+    def test_image_hash_append(self):
+        m = LanguageModel.example(test_model=True, canned_response="oh, a picture!")
+        from edsl import Scenario, QuestionFreeText, Cache
+
+        image_cache = Cache()
+        scenario = Scenario.example(has_image=True)
+        q = QuestionFreeText(
+            question_text="What is this image {{ logo }} about?",
+            question_name="example_question",
+        )
+        results = q.by(m).by(scenario).run(cache=image_cache)
+        import hashlib
+
+        image_hash = str(
+            hashlib.md5(scenario["logo"].encoded_image.encode()).hexdigest()
+        )
+        assert image_hash in list(image_cache.data.values())[0]["user_prompt"]
+
+        # with no agent, should be empty
+        assert list(image_cache.data.values())[0]["system_prompt"] == ""
+
+        # breakpoint()
+
+        # self.assertEqual(m.image_hash, "hello")
+
     # def test_get_response(self):
     #     from edsl.data.Cache import Cache