playground/analysis/task1.txt

*****TASK LIST*****

1: Make a todo list

*****NEXT TASK*****

1: Make a todo list
message='Request to OpenAI API' method=post path=https://api.openai.com/v1/engines/text-embedding-ada-002/embeddings
api_version=None data='{"input": ["\\nPlease make a web GUI for using HTTP API server. \\nThe name of it is Swarms. \\nYou can check the server code at ./main.py. \\nThe server is served on localhost:8000. \\nUsers should be able to write text input as \'query\' and url array as \'files\', and check the response. \\nUsers input form should be delivered in JSON format. \\nI want it to have neumorphism-style. Serve it on port 4500.\\n\\n"], "encoding_format": "base64"}' message='Post details'
Converted retries value: 2 -> Retry(total=2, connect=None, read=None, redirect=None, status=None)
Starting new HTTPS connection (1): api.openai.com:443
https://api.openai.com:443 "POST /v1/engines/text-embedding-ada-002/embeddings HTTP/1.1" 200 None
message='OpenAI API response' path=https://api.openai.com/v1/engines/text-embedding-ada-002/embeddings processing_ms=168 request_id=6b1f8e81a95d5f4ec48a65a2b0bc7a29 response_code=200


> Entering new  chain...
message='Request to OpenAI API' method=post path=https://api.openai.com/v1/completions
api_version=None data='{"prompt": ["You are an Boss in a swarm who performs one task based on the following objective: \\nPlease make a web GUI for using HTTP API server. \\nThe name of it is Swarms. \\nYou can check the server code at ./main.py. \\nThe server is served on localhost:8000. \\nUsers should be able to write text input as \'query\' and url array as \'files\', and check the response. \\nUsers input form should be delivered in JSON format. \\nI want it to have neumorphism-style. Serve it on port 4500.\\n\\n. Take into account these previously completed tasks: .\\n \\n\\nTODO: useful for when you need to come up with todo lists. Input: an objective to create a todo list for. Output: a todo list for that objective. Please be very clear what the objective is!\\nWorkerNode AI Agent: Input: an objective with a todo list for that objective. Output: your task completed: Please be very clear what the objective and task instructions are. The Swarm worker agent is Useful for when you need to spawn an autonomous agent instance as a worker to accomplish any complex tasks, it can search the internet or write code or spawn child multi-modality models to process and generate images and text or audio and so on\\n\\nUse the following format:\\n\\nQuestion: the input question you must answer\\nThought: you should always think about what to do\\nAction: the action to take, should be one of [TODO, WorkerNode AI Agent]\\nAction Input: the input to the action\\nObservation: the result of the action\\n... (this Thought/Action/Action Input/Observation can repeat N times)\\nThought: I now know the final answer\\nFinal Answer: the final answer to the original input question\\n\\nQuestion: Make a todo list\\n"], "model": "text-davinci-003", "temperature": 0.5, "max_tokens": 256, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "n": 1, "logit_bias": {}, "stop": ["\\nObservation:", "\\n\\tObservation:"]}' message='Post details'
https://api.openai.com:443 "POST /v1/completions HTTP/1.1" 200 None
message='OpenAI API response' path=https://api.openai.com/v1/completions processing_ms=3128 request_id=802132ab4ecdd632506f28a95d3c185a response_code=200
Thought: What do I need to do?
Action: TODO
Action Input: Make a web GUI for using HTTP API server. The name of it is Swarms. You can check the server code at ./main.py. The server is served on localhost:8000. Users should be able to write text input as 'query' and url array as 'files', and check the response. Users input form should be delivered in JSON format. I want it to have neumorphism-style. Serve it on port 4500.message='Request to OpenAI API' method=post path=https://api.openai.com/v1/completions
api_version=None data='{"prompt": ["You are a boss planer in a swarm who is an expert at coming up with a todo list for a given objective and then creating an worker to help you accomplish your task. Come up with a todo list for this objective: Make a web GUI for using HTTP API server. The name of it is Swarms. You can check the server code at ./main.py. The server is served on localhost:8000. Users should be able to write text input as \'query\' and url array as \'files\', and check the response. Users input form should be delivered in JSON format. I want it to have neumorphism-style. Serve it on port 4500. and then spawn a worker agent to complete the task for you."], "model": "text-davinci-003", "temperature": 0.5, "max_tokens": 256, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "n": 1, "logit_bias": {}}' message='Post details'
https://api.openai.com:443 "POST /v1/completions HTTP/1.1" 200 None
message='OpenAI API response' path=https://api.openai.com/v1/completions processing_ms=6119 request_id=9ec8b1aad373258657cdf5663721f398 response_code=200

Observation: 

Todo List:

1. Create a basic HTML page with a simple form for user input
2. Add a text input field and url array field to the form
3. Create a JavaScript function to capture and format the user input into JSON
4. Create a JavaScript function to make an AJAX call to the HTTP API server
5. Create a JavaScript function to process the response from the server and display it to the user
6. Add neumorphism-style styling to the HTML page
7. Create a Python script to run the server on port 4500
8. Create a worker agent to complete the task

Once the worker agent is created, it will be responsible for completing the task by following the todo list. It will be able to execute the HTML page, JavaScript functions, and Python script to make the web GUI for using the HTTP API server.
Thought:message='Request to OpenAI API' method=post path=https://api.openai.com/v1/completions
api_version=None data='{"prompt": ["You are an Boss in a swarm who performs one task based on the following objective: \\nPlease make a web GUI for using HTTP API server. \\nThe name of it is Swarms. \\nYou can check the server code at ./main.py. \\nThe server is served on localhost:8000. \\nUsers should be able to write text input as \'query\' and url array as \'files\', and check the response. \\nUsers input form should be delivered in JSON format. \\nI want it to have neumorphism-style. Serve it on port 4500.\\n\\n. Take into account these previously completed tasks: .\\n \\n\\nTODO: useful for when you need to come up with todo lists. Input: an objective to create a todo list for. Output: a todo list for that objective. Please be very clear what the objective is!\\nWorkerNode AI Agent: Input: an objective with a todo list for that objective. Output: your task completed: Please be very clear what the objective and task instructions are. The Swarm worker agent is Useful for when you need to spawn an autonomous agent instance as a worker to accomplish any complex tasks, it can search the internet or write code or spawn child multi-modality models to process and generate images and text or audio and so on\\n\\nUse the following format:\\n\\nQuestion: the input question you must answer\\nThought: you should always think about what to do\\nAction: the action to take, should be one of [TODO, WorkerNode AI Agent]\\nAction Input: the input to the action\\nObservation: the result of the action\\n... (this Thought/Action/Action Input/Observation can repeat N times)\\nThought: I now know the final answer\\nFinal Answer: the final answer to the original input question\\n\\nQuestion: Make a todo list\\nThought: What do I need to do?\\nAction: TODO\\nAction Input: Make a web GUI for using HTTP API server. The name of it is Swarms. You can check the server code at ./main.py. The server is served on localhost:8000. Users should be able to write text input as \'query\' and url array as \'files\', and check the response. Users input form should be delivered in JSON format. I want it to have neumorphism-style. Serve it on port 4500.\\nObservation: \\n\\nTodo List:\\n\\n1. Create a basic HTML page with a simple form for user input\\n2. Add a text input field and url array field to the form\\n3. Create a JavaScript function to capture and format the user input into JSON\\n4. Create a JavaScript function to make an AJAX call to the HTTP API server\\n5. Create a JavaScript function to process the response from the server and display it to the user\\n6. Add neumorphism-style styling to the HTML page\\n7. Create a Python script to run the server on port 4500\\n8. Create a worker agent to complete the task\\n\\nOnce the worker agent is created, it will be responsible for completing the task by following the todo list. It will be able to execute the HTML page, JavaScript functions, and Python script to make the web GUI for using the HTTP API server.\\nThought:"], "model": "text-davinci-003", "temperature": 0.5, "max_tokens": 256, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "n": 1, "logit_bias": {}, "stop": ["\\nObservation:", "\\n\\tObservation:"]}' message='Post details'
https://api.openai.com:443 "POST /v1/completions HTTP/1.1" 200 None
message='OpenAI API response' path=https://api.openai.com/v1/completions processing_ms=1153 request_id=3af455f0446ff21257b66034aa4671d2 response_code=200
 I now know the final answer
Final Answer: Create a todo list for making a web GUI for using HTTP API server with neumorphism-style styling served on port 4500.

> Finished chain.

*****TASK RESULT*****

Create a todo list for making a web GUI for using HTTP API server with neumorphism-style styling served on port 4500.
message='Request to OpenAI API' method=post path=https://api.openai.com/v1/engines/text-embedding-ada-002/embeddings
api_version=None data='{"input": ["Create a todo list for making a web GUI for using HTTP API server with neumorphism-style styling served on port 4500."], "encoding_format": "base64"}' message='Post details'
https://api.openai.com:443 "POST /v1/engines/text-embedding-ada-002/embeddings HTTP/1.1" 200 None
message='OpenAI API response' path=https://api.openai.com/v1/engines/text-embedding-ada-002/embeddings processing_ms=202 request_id=9325c5cc5cb825438e25d8f5618b2774 response_code=200
message='Request to OpenAI API' method=post path=https://api.openai.com/v1/completions
api_version=None data='{"prompt": ["You are an task creation AI that uses the result of an execution agent to create new tasks with the following objective: \\nPlease make a web GUI for using HTTP API server. \\nThe name of it is Swarms. \\nYou can check the server code at ./main.py. \\nThe server is served on localhost:8000. \\nUsers should be able to write text input as \'query\' and url array as \'files\', and check the response. \\nUsers input form should be delivered in JSON format. \\nI want it to have neumorphism-style. Serve it on port 4500.\\n\\n, The last completed task has the result: Create a todo list for making a web GUI for using HTTP API server with neumorphism-style styling served on port 4500.. This result was based on this task description: Make a todo list. These are incomplete tasks: . Based on the result, create new tasks to be completed by the AI system that do not overlap with incomplete tasks. Return the tasks as an array."], "model": "text-davinci-003", "temperature": 0.5, "max_tokens": 256, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "n": 1, "logit_bias": {}}' message='Post details'
https://api.openai.com:443 "POST /v1/completions HTTP/1.1" 200 None
message='OpenAI API response' path=https://api.openai.com/v1/completions processing_ms=4343 request_id=ddd5dc301576bac56271e4a666194222 response_code=200
message='Request to OpenAI API' method=post path=https://api.openai.com/v1/completions
api_version=None data='{"prompt": ["You are a task prioritization AI tasked with cleaning the formatting of and reprioritizing the following tasks: Tasks: , 1. Create the HTML structure for the web GUI. , 2. Design the web GUI with neumorphism-style styling. , 3. Create the JavaScript code to capture user input., 4. Create the JavaScript code to send the user input to the server., 5. Create the JavaScript code to capture the server response., 6. Create the JavaScript code to display the response to the user., 7. Test the web GUI on port 4500.. Consider the ultimate objective of your team: \\nPlease make a web GUI for using HTTP API server. \\nThe name of it is Swarms. \\nYou can check the server code at ./main.py. \\nThe server is served on localhost:8000. \\nUsers should be able to write text input as \'query\' and url array as \'files\', and check the response. \\nUsers input form should be delivered in JSON format. \\nI want it to have neumorphism-style. Serve it on port 4500.\\n\\n. Do not remove any tasks. Return the result as a numbered list, like: #. First task #. Second task Start the task list with number 2."], "model": "text-davinci-003", "temperature": 0.5, "max_tokens": 256, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "n": 1, "logit_bias": {}}' message='Post details'
https://api.openai.com:443 "POST /v1/completions HTTP/1.1" 200 None
message='OpenAI API response' path=https://api.openai.com/v1/completions processing_ms=3085 request_id=a4981199d3ca81a0251b3e60a1410c48 response_code=200

*****TASK LIST*****

1: Create the JavaScript code to capture user input.
2: Create the JavaScript code to send the user input to the server.
3: Create the JavaScript code to capture the server response.
4: Create the JavaScript code to display the response to the user.
5: Test the web GUI on port 4500.
6: Create the HTML structure for the web GUI.
7: Design the web GUI with neumorphism-style styling.

*****NEXT TASK*****

1: Create the JavaScript code to capture user input.
message='Request to OpenAI API' method=post path=https://api.openai.com/v1/engines/text-embedding-ada-002/embeddings
api_version=None data='{"input": ["\\nPlease make a web GUI for using HTTP API server. \\nThe name of it is Swarms. \\nYou can check the server code at ./main.py. \\nThe server is served on localhost:8000. \\nUsers should be able to write text input as \'query\' and url array as \'files\', and check the response. \\nUsers input form should be delivered in JSON format. \\nI want it to have neumorphism-style. Serve it on port 4500.\\n\\n"], "encoding_format": "base64"}' message='Post details'
https://api.openai.com:443 "POST /v1/engines/text-embedding-ada-002/embeddings HTTP/1.1" 200 None
message='OpenAI API response' path=https://api.openai.com/v1/engines/text-embedding-ada-002/embeddings processing_ms=37 request_id=46c1a49e639c2221cde74735999d1ff2 response_code=200


> Entering new  chain...
message='Request to OpenAI API' method=post path=https://api.openai.com/v1/completions
api_version=None data='{"prompt": ["You are an Boss in a swarm who performs one task based on the following objective: \\nPlease make a web GUI for using HTTP API server. \\nThe name of it is Swarms. \\nYou can check the server code at ./main.py. \\nThe server is served on localhost:8000. \\nUsers should be able to write text input as \'query\' and url array as \'files\', and check the response. \\nUsers input form should be delivered in JSON format. \\nI want it to have neumorphism-style. Serve it on port 4500.\\n\\n. Take into account these previously completed tasks: Make a todo list.\\n \\n\\nTODO: useful for when you need to come up with todo lists. Input: an objective to create a todo list for. Output: a todo list for that objective. Please be very clear what the objective is!\\nWorkerNode AI Agent: Input: an objective with a todo list for that objective. Output: your task completed: Please be very clear what the objective and task instructions are. The Swarm worker agent is Useful for when you need to spawn an autonomous agent instance as a worker to accomplish any complex tasks, it can search the internet or write code or spawn child multi-modality models to process and generate images and text or audio and so on\\n\\nUse the following format:\\n\\nQuestion: the input question you must answer\\nThought: you should always think about what to do\\nAction: the action to take, should be one of [TODO, WorkerNode AI Agent]\\nAction Input: the input to the action\\nObservation: the result of the action\\n... (this Thought/Action/Action Input/Observation can repeat N times)\\nThought: I now know the final answer\\nFinal Answer: the final answer to the original input question\\n\\nQuestion: Create the JavaScript code to capture user input.\\n"], "model": "text-davinci-003", "temperature": 0.5, "max_tokens": 256, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "n": 1, "logit_bias": {}, "stop": ["\\nObservation:", "\\n\\tObservation:"]}' message='Post details'
https://api.openai.com:443 "POST /v1/completions HTTP/1.1" 200 None
message='OpenAI API response' path=https://api.openai.com/v1/completions processing_ms=3908 request_id=29c7aa85577bb9a38555c4462f3c0fa5 response_code=200
Thought: I need to create a web GUI for user input.
Action: TODO
Action Input: Create a web GUI for using HTTP API server. The name of it is Swarms. Users should be able to write text input as 'query' and url array as 'files', and check the response. Users input form should be delivered in JSON format. I want it to have neumorphism-style. Serve it on port 4500.message='Request to OpenAI API' method=post path=https://api.openai.com/v1/completions
api_version=None data='{"prompt": ["You are a boss planer in a swarm who is an expert at coming up with a todo list for a given objective and then creating an worker to help you accomplish your task. Come up with a todo list for this objective: Create a web GUI for using HTTP API server. The name of it is Swarms. Users should be able to write text input as \'query\' and url array as \'files\', and check the response. Users input form should be delivered in JSON format. I want it to have neumorphism-style. Serve it on port 4500. and then spawn a worker agent to complete the task for you."], "model": "text-davinci-003", "temperature": 0.5, "max_tokens": 256, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "n": 1, "logit_bias": {}}' message='Post details'
https://api.openai.com:443 "POST /v1/completions HTTP/1.1" 200 None
message='OpenAI API response' path=https://api.openai.com/v1/completions processing_ms=8743 request_id=6d79af97400c608b91d7402f5641fdb2 response_code=200

Observation: 

Todo List:

1. Research neumorphism-style and decide on best design for the web GUI.

2. Create HTML/CSS files for the web GUI.

3. Create JavaScript files for the web GUI.

4. Create a server to host the web GUI on port 4500.

5. Create an HTTP API server to handle user input and deliver JSON response.

6. Create a worker agent to handle the server side logic.

7. Test the web GUI for functionality and performance.

8. Deploy the web GUI on port 4500.
Thought:message='Request to OpenAI API' method=post path=https://api.openai.com/v1/completions
api_version=None data='{"prompt": ["You are an Boss in a swarm who performs one task based on the following objective: \\nPlease make a web GUI for using HTTP API server. \\nThe name of it is Swarms. \\nYou can check the server code at ./main.py. \\nThe server is served on localhost:8000. \\nUsers should be able to write text input as \'query\' and url array as \'files\', and check the response. \\nUsers input form should be delivered in JSON format. \\nI want it to have neumorphism-style. Serve it on port 4500.\\n\\n. Take into account these previously completed tasks: Make a todo list.\\n \\n\\nTODO: useful for when you need to come up with todo lists. Input: an objective to create a todo list for. Output: a todo list for that objective. Please be very clear what the objective is!\\nWorkerNode AI Agent: Input: an objective with a todo list for that objective. Output: your task completed: Please be very clear what the objective and task instructions are. The Swarm worker agent is Useful for when you need to spawn an autonomous agent instance as a worker to accomplish any complex tasks, it can search the internet or write code or spawn child multi-modality models to process and generate images and text or audio and so on\\n\\nUse the following format:\\n\\nQuestion: the input question you must answer\\nThought: you should always think about what to do\\nAction: the action to take, should be one of [TODO, WorkerNode AI Agent]\\nAction Input: the input to the action\\nObservation: the result of the action\\n... (this Thought/Action/Action Input/Observation can repeat N times)\\nThought: I now know the final answer\\nFinal Answer: the final answer to the original input question\\n\\nQuestion: Create the JavaScript code to capture user input.\\nThought: I need to create a web GUI for user input.\\nAction: TODO\\nAction Input: Create a web GUI for using HTTP API server. The name of it is Swarms. Users should be able to write text input as \'query\' and url array as \'files\', and check the response. Users input form should be delivered in JSON format. I want it to have neumorphism-style. Serve it on port 4500.\\nObservation: \\n\\nTodo List:\\n\\n1. Research neumorphism-style and decide on best design for the web GUI.\\n\\n2. Create HTML/CSS files for the web GUI.\\n\\n3. Create JavaScript files for the web GUI.\\n\\n4. Create a server to host the web GUI on port 4500.\\n\\n5. Create an HTTP API server to handle user input and deliver JSON response.\\n\\n6. Create a worker agent to handle the server side logic.\\n\\n7. Test the web GUI for functionality and performance.\\n\\n8. Deploy the web GUI on port 4500.\\nThought:"], "model": "text-davinci-003", "temperature": 0.5, "max_tokens": 256, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "n": 1, "logit_bias": {}, "stop": ["\\nObservation:", "\\n\\tObservation:"]}' message='Post details'
https://api.openai.com:443 "POST /v1/completions HTTP/1.1" 200 None
message='OpenAI API response' path=https://api.openai.com/v1/completions processing_ms=1278 request_id=01dc3693e3251ae99575abd4e6577ee8 response_code=200
 I now know the final answer
Final Answer: Create the JavaScript code to capture user input and deploy the web GUI on port 4500.

> Finished chain.

*****TASK RESULT*****

Create the JavaScript code to capture user input and deploy the web GUI on port 4500.
message='Request to OpenAI API' method=post path=https://api.openai.com/v1/engines/text-embedding-ada-002/embeddings
api_version=None data='{"input": ["Create the JavaScript code to capture user input and deploy the web GUI on port 4500."], "encoding_format": "base64"}' message='Post details'
https://api.openai.com:443 "POST /v1/engines/text-embedding-ada-002/embeddings HTTP/1.1" 200 None
message='OpenAI API response' path=https://api.openai.com/v1/engines/text-embedding-ada-002/embeddings processing_ms=40 request_id=d5225adb1208b38e2639a23afcccf29d response_code=200
An error occurred in run: Tried to add ids that already exist: {'result_1'}
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ /content/swarms/example.py:26 in <module>                                                        │
│                                                                                                  │
│   23 """                                                                                         │
│   24                                                                                             │
│   25 # Run Swarms                                                                                │
│ ❱ 26 task = swarm.run(objective)                                                          │
│   27                                                                                             │
│   28 print(task)                                                                                 │
│   29                                                                                             │
│                                                                                                  │
│ /content/swarms/swarms/swarms.py:79 in run                                                │
│                                                                                                  │
│    76 │   │   │   boss_node = self.initialize_boss_node(vectorstore, worker_node)                │
│    77 │   │   │                                                                                  │
│    78 │   │   │   task = boss_node.create_task(objective)                                        │
│ ❱  79 │   │   │   return boss_node.execute_task(task)                                            │
│    80 │   │   except Exception as e:                                                             │
│    81 │   │   │   logging.error(f"An error occurred in run: {e}")                         │
│    82 │   │   │   raise                                                                          │
│                                                                                                  │
│ /content/swarms/swarms/agents/boss/boss_agent.py:27 in execute_task                              │
│                                                                                                  │
│   24 │   │   return {"objective": objective}                                                     │
│   25 │                                                                                           │
│   26 │   def execute_task(self, task):                                                           │
│ ❱ 27 │   │   self.baby_agi(task)                                                                 │
│   28                                                                                             │
│                                                                                                  │
│ /usr/local/lib/python3.10/dist-packages/langchain/chains/base.py:181 in __call__                 │
│                                                                                                  │
│   178 │   │   │   )                                                                              │
│   179 │   │   except (KeyboardInterrupt, Exception) as e:                                        │
│   180 │   │   │   run_manager.on_chain_error(e)                                                  │
│ ❱ 181 │   │   │   raise e                                                                        │
│   182 │   │   run_manager.on_chain_end(outputs)                                                  │
│   183 │   │   final_outputs: Dict[str, Any] = self.prep_outputs(                                 │
│   184 │   │   │   inputs, outputs, return_only_outputs                                           │
│                                                                                                  │
│ /usr/local/lib/python3.10/dist-packages/langchain/chains/base.py:175 in __call__                 │
│                                                                                                  │
│   172 │   │   )                                                                                  │
│   173 │   │   try:                                                                               │
│   174 │   │   │   outputs = (                                                                    │
│ ❱ 175 │   │   │   │   self._call(inputs, run_manager=run_manager)                                │
│   176 │   │   │   │   if new_arg_supported                                                       │
│   177 │   │   │   │   else self._call(inputs)                                                    │
│   178 │   │   │   )                                                                              │
│                                                                                                  │
│ /usr/local/lib/python3.10/dist-packages/langchain/experimental/autonomous_agents/baby_agi/baby_a │
│ gi.py:142 in _call                                                                               │
│                                                                                                  │
│   139 │   │   │   │                                                                              │
│   140 │   │   │   │   # Step 3: Store the result in Pinecone                                     │
│   141 │   │   │   │   result_id = f"result_{task['task_id']}"                                    │
│ ❱ 142 │   │   │   │   self.vectorstore.add_texts(                                                │
│   143 │   │   │   │   │   texts=[result],                                                        │
│   144 │   │   │   │   │   metadatas=[{"task": task["task_name"]}],                               │
│   145 │   │   │   │   │   ids=[result_id],                                                       │
│                                                                                                  │
│ /usr/local/lib/python3.10/dist-packages/langchain/vectorstores/faiss.py:150 in add_texts         │
│                                                                                                  │
│   147 │   │   │   )                                                                              │
│   148 │   │   # Embed and create the documents.                                                  │
│   149 │   │   embeddings = [self.embedding_function(text) for text in texts]                     │
│ ❱ 150 │   │   return self.__add(texts, embeddings, metadatas=metadatas, ids=ids, **kwargs)       │
│   151 │                                                                                          │
│   152 │   def add_embeddings(                                                                    │
│   153 │   │   self,                                                                              │
│                                                                                                  │
│ /usr/local/lib/python3.10/dist-packages/langchain/vectorstores/faiss.py:121 in __add             │
│                                                                                                  │
│   118 │   │   # Get list of index, id, and docs.                                                 │
│   119 │   │   full_info = [(starting_len + i, ids[i], doc) for i, doc in enumerate(documents)]   │
│   120 │   │   # Add information to docstore and index.                                           │
│ ❱ 121 │   │   self.docstore.add({_id: doc for _, _id, doc in full_info})                         │
│   122 │   │   index_to_id = {index: _id for index, _id, _ in full_info}                          │
│   123 │   │   self.index_to_docstore_id.update(index_to_id)                                      │
│   124 │   │   return [_id for _, _id, _ in full_info]                                            │
│                                                                                                  │
│ /usr/local/lib/python3.10/dist-packages/langchain/docstore/in_memory.py:19 in add                │
│                                                                                                  │
│   16 │   │   """Add texts to in memory dictionary."""                                            │
│   17 │   │   overlapping = set(texts).intersection(self._dict)                                   │
│   18 │   │   if overlapping:                                                                     │
│ ❱ 19 │   │   │   raise ValueError(f"Tried to add ids that already exist: {overlapping}")         │
│   20 │   │   self._dict = {**self._dict, **texts}                                                │
│   21 │                                                                                           │
│   22 │   def search(self, search: str) -> Union[str, Document]:                                  │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
ValueError: Tried to add ids that already exist: {'result_1'}
/content/swarms# 
[0] 0:bash*                                                                                      "802396df995c" 18:44 06-Jul-23