Add code for the first version

.gitignore

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+client_secret.json
+credentials.json
+token.json
+*.pptx
+
+
+### Python template
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+

.idea/.gitignore

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+# Default ignored files
+/shelf/
+/workspace.xml

.idea/inspectionProfiles/Project_Default.xml

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+<component name="InspectionProjectProfileManager">
+  <profile version="1.0">
+    <option name="myName" value="Project Default" />
+    <inspection_tool class="PyPackageRequirementsInspection" enabled="true" level="WARNING" enabled_by_default="true">
+      <option name="ignoredPackages">
+        <value>
+          <list size="1">
+            <item index="0" class="java.lang.String" itemvalue="numpy" />
+          </list>
+        </value>
+      </option>
+    </inspection_tool>
+  </profile>
+</component>

.idea/inspectionProfiles/profiles_settings.xml

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+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.10 (slide-deck-ai)" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/slide-deck-ai.iml" filepath="$PROJECT_DIR$/.idea/slide-deck-ai.iml" />
+    </modules>
+  </component>
+</project>

.idea/slide-deck-ai.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$">
+      <excludeFolder url="file://$MODULE_DIR$/venv" />
+    </content>
+    <orderEntry type="inheritedJdk" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+  <component name="PyDocumentationSettings">
+    <option name="format" value="PLAIN" />
+    <option name="myDocStringFormat" value="Plain" />
+  </component>
+</module>

.idea/vcs.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+  </component>
+</project>

app.py

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+import json5
+import time
+import streamlit as st
+import streamlit.runtime.scriptrunner as st_sr
+
+import llm_helper
+import pptx_helper
+from global_config import GlobalConfig
+
+
+APP_TEXT = json5.loads(open(GlobalConfig.APP_STRINGS_FILE, 'r').read())
+
+
+def build_ui():
+    """
+    Display the input elements for content generation. Only covers the first step.
+    """
+
+    st.title(APP_TEXT['app_name'])
+    st.subheader(APP_TEXT['caption'])
+    st.divider()
+
+    st.header(APP_TEXT['section_headers'][0])
+    st.caption(APP_TEXT['section_captions'][0])
+
+    try:
+        with open(GlobalConfig.PRELOAD_DATA_FILE, 'r') as in_file:
+            preload_data = json5.loads(in_file.read())
+    except (FileExistsError, FileNotFoundError):
+        preload_data = {'topic': '', 'audience': ''}
+
+    topic = st.text_area(
+        APP_TEXT['input_labels'][0],
+        value=preload_data['topic']
+    )
+
+    # Button with callback function
+    st.button(APP_TEXT['button_labels'][0], on_click=button_clicked, args=[0])
+
+    if st.session_state.clicked[0]:
+        progress_text = 'Generating your presentation slides...give it a moment'
+        progress_bar = st.progress(0, text=progress_text)
+
+        topic_txt = topic.strip()
+        process_topic_inputs(topic_txt, progress_bar)
+
+
+def process_topic_inputs(topic: str, progress_bar):
+    """
+    Process the inputs to generate contents for the slides.
+
+    :param topic: The presentation topic
+    :param progress_bar: Progress bar from the page
+    :return:
+    """
+
+    topic_length = len(topic)
+    print(f'Input length:: topic: {topic_length}')
+
+    if topic_length > 10:
+        print(
+            f'Topic: {topic}\n'
+        )
+        print('=' * 20)
+
+        target_length = min(topic_length, GlobalConfig.LLM_MODEL_MAX_INPUT_LENGTH)
+
+        try:
+            slides_content = llm_helper.generate_slides_content(topic[:target_length]).strip()
+            content_length = len(slides_content)
+
+            print('=' * 20)
+            print(f'Slides content:\n{slides_content}')
+            print(f'Content length: {content_length}')
+            print('=' * 20)
+            st.write(f'''Slides content:\n{slides_content}''')
+            progress_bar.progress(100, text='Done!')
+
+            if content_length == 0:
+                st.error(APP_TEXT['content_generation_failure_error'])
+                return
+
+            st.info(
+                'The generated content doesn\'t look so great?'
+                ' Need alternatives? Just change your description text and try again.'
+                ' For example, you can start describing like "Create a slide deck on..."',
+                icon="ℹ️"
+            )
+
+            # Move on to step 2
+            st.divider()
+            st.header(APP_TEXT['section_headers'][1])
+            st.caption(APP_TEXT['section_captions'][1])
+
+            # Streamlit multiple buttons work in a weird way!
+            # Click on any button, the page just reloads!
+            # Buttons are not "stateful"
+            # https://blog.streamlit.io/10-most-common-explanations-on-the-streamlit-forum/#1-buttons-aren%E2%80%99t-stateful
+            # Apparently, "nested button click" needs to be handled differently
+            # https://playground.streamlit.app/?q=triple-button
+
+            st.button(APP_TEXT['button_labels'][1], on_click=button_clicked, args=[1])
+
+            if st.session_state.clicked[1]:
+                progress_text = 'Converting...give it a moment'
+                progress_bar = st.progress(0, text=progress_text)
+
+                process_slides_contents(slides_content, progress_bar)
+        except ValueError as ve:
+            st.error(f'Unfortunately, an error occurred: {ve}! '
+                     f'Please change the text, try again later, or report it, sharing your inputs.')
+
+    else:
+        st.error('Not enough information provided! Please be little more descriptive :)')
+
+
+def process_slides_contents(text: str, progress_bar: st.progress):
+    """
+    Convert given text into structured data and display. Update the UI.
+
+    :param text: The contents generated for the slides
+    :param progress_bar: Progress bar for this step
+    """
+
+    print('JSON button clicked')
+    json_str = llm_helper.text_to_json(text)
+    # yaml_str = llm_helper.text_to_yaml(text)
+    print('=' * 20)
+    print(f'JSON:\n{json_str}')
+    print('=' * 20)
+    st.code(json_str, language='json')
+
+    progress_bar.progress(100, text='Done!')
+
+    # Now, step 3
+    st.divider()
+    st.header(APP_TEXT['section_headers'][2])
+    st.caption(APP_TEXT['section_captions'][2])
+
+    st.button(APP_TEXT['button_labels'][2], on_click=button_clicked, args=[2])
+
+    if st.session_state.clicked[2]:
+        progress_text = 'Creating the slide deck...give it a moment'
+        progress_bar = st.progress(0, text=progress_text)
+
+        # Get a unique name for the file to save -- use the session ID
+        ctx = st_sr.get_script_run_ctx()
+        session_id = ctx.session_id
+        timestamp = time.time()
+        output_file_name = f'{session_id}_{timestamp}.pptx'
+
+        pptx_helper.generate_powerpoint_presentation(json_str, as_yaml=False, output_file_name=output_file_name)
+        st.progress(100, text='Done!')
+
+        # st.download_button('Download file', binary_contents)  # Defaults to 'application/octet-stream'
+
+        with open(output_file_name, 'rb') as f:
+            st.download_button('Download PPTX file', f, file_name=output_file_name)
+
+
+def button_clicked(button):
+    """
+    Update the button clicked value in session state.
+    """
+
+    st.session_state.clicked[button] = True
+
+
+def main():
+    # Initialize the key in session state to manage the nested buttons states
+    if 'clicked' not in st.session_state:
+        st.session_state.clicked = {0: False, 1: False, 2: False}
+
+    build_ui()
+
+
+if __name__ == '__main__':
+    main()

clarifai_grpc_helper.py

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+from global_config import GlobalConfig
+
+######################################################################################################
+# In this section, we set the user authentication, user and app ID, model details, and the URL of
+# the text we want as an input. Change these strings to run your own example.
+######################################################################################################
+
+# Your PAT (Personal Access Token) can be found in the portal under Authentification
+PAT = '7244fc3df026429d819f9df31309ab9d'
+# Specify the correct user_id/app_id pairings
+# Since you're making inferences outside your app's scope
+USER_ID = 'meta'
+APP_ID = 'Llama-2'
+# Change these to whatever model and text URL you want to use
+MODEL_ID = 'llama2-13b-chat'
+MODEL_VERSION_ID = '79a1af31aa8249a99602fc05687e8f40'
+TEXT_FILE_URL = 'https://samples.clarifai.com/negative_sentence_12.txt'
+
+############################################################################
+# YOU DO NOT NEED TO CHANGE ANYTHING BELOW THIS LINE TO RUN THIS EXAMPLE
+############################################################################
+
+from clarifai_grpc.channel.clarifai_channel import ClarifaiChannel
+from clarifai_grpc.grpc.api import resources_pb2, service_pb2, service_pb2_grpc
+from clarifai_grpc.grpc.api.status import status_code_pb2
+
+channel = ClarifaiChannel.get_grpc_channel()
+stub = service_pb2_grpc.V2Stub(channel)
+
+metadata = (
+    ('authorization', 'Key ' + GlobalConfig.CLARIFAI_PAT),
+    # ('temp', '0.9'),  # Does not work
+)
+
+userDataObject = resources_pb2.UserAppIDSet(
+    user_id=GlobalConfig.CLARIFAI_USER_ID,
+    app_id=GlobalConfig.CLARIFAI_APP_ID
+)
+
+RAW_TEXT = '''You are a helpful, intelligent chatbot. 
+Create the slides for a presentation on the given topic. 
+Include main headings for each slide, detailed bullet points for each slide. 
+Add relevant content to each slide.
+The output should be complete, coherent, and have maximum 255 tokens.
+
+Topic:
+Talk about AI, covering what it is and how it works. Add its pros, cons, and future prospects. Also, cover its job prospects.
+'''
+
+post_model_outputs_response = stub.PostModelOutputs(
+    service_pb2.PostModelOutputsRequest(
+        user_app_id=userDataObject,  # The userDataObject is created in the overview and is required when using a PAT
+        model_id=GlobalConfig.CLARIFAI_MODEL_ID,
+        # version_id=MODEL_VERSION_ID,  # This is optional. Defaults to the latest model version
+        inputs=[
+            resources_pb2.Input(
+                data=resources_pb2.Data(
+                    text=resources_pb2.Text(
+                        # url=TEXT_FILE_URL,
+                        raw=RAW_TEXT
+                    )
+                )
+            )
+        ]
+    ),
+    metadata=metadata
+)
+if post_model_outputs_response.status.code != status_code_pb2.SUCCESS:
+    print(post_model_outputs_response.status)
+    raise Exception(f"Post model outputs failed, status: {post_model_outputs_response.status.description}")
+
+# Since we have one input, one output will exist here
+output = post_model_outputs_response.outputs[0]
+
+print("Completion:\n")
+print(output.data.text.raw)

examples/example_01.json

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+{
+    "topic": "Create slides for a tutorial on Python, covering the basic data types, conditions, and loops.",
+    "audience": "People with no technology background"
+}

examples/example_01_structured_output.json

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+{
+    "title": "Introduction to Python Programming",
+    "slides": [
+        {
+            "heading": "Slide 1: Introduction",
+            "bullet_points": [
+                "Brief overview of Python and its importance",
+                "Purpose of the tutorial"
+            ]
+        },
+        {
+            "heading": "Slide 2: Basic Data Types",
+            "bullet_points": [
+                "Strings (e.g. \"hello\")",
+                "Integers (e.g. 42)",
+                "Floats (e.g. 3.14)",
+                "Booleans (e.g. True/False)",
+                "Lists (e.g. [1, 2, 3])",
+                "Tuples (e.g. (1, 2, 3))"
+            ]
+        },
+        {
+            "heading": "Slide 3: Strings",
+            "bullet_points": [
+                "String literals (e.g. \"hello\")",
+                "String concatenation (e.g. \"hello\" + \" world\")",
+                "String slicing (e.g. \"hello\"[0] = h)"
+            ]
+        },
+        {
+            "heading": "Slide 4: Integers",
+            "bullet_points": [
+                "Integer literals (e.g. 42)",
+                "Arithmetic operations (e.g. 2 + 3 = 5)"
+            ]
+        },
+        {
+            "heading": "Slide 5: Floats",
+            "bullet_points": [
+                "Floating-point literals (e.g."
+            ]
+        }
+    ]
+}

examples/example_02.json

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+{
+    "topic": "Talk about AI, covering what it is and how it works. Add its pros, cons, and future prospects. Also, cover its job prospects.",
+    "audience": "I am a teacher and want to present these slides to college students."
+}

examples/example_02_structured_output.json

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+{
+    "title": "Understanding AI: Introduction to Artificial Intelligence",
+    "slides": [
+        {
+            "heading": "Slide 1: Introduction",
+            "bullet_points": [
+                "Brief overview of AI",
+                "Importance of understanding AI"
+            ]
+        },
+        {
+            "heading": "Slide 2: What is AI?",
+            "bullet_points": [
+                "Definition of AI",
+                "Types of AI",
+                [
+                    "Narrow or weak AI",
+                    "General or strong AI"
+                ],
+                "Differences between AI and machine learning"
+            ]
+        },
+        {
+            "heading": "Slide 3: How AI Works",
+            "bullet_points": [
+                "Overview of AI algorithms",
+                "Types of AI algorithms",
+                [
+                    "Rule-based systems",
+                    "Decision tree systems",
+                    "Neural networks"
+                ],
+                "How AI processes data"
+            ]
+        },
+        {
+            "heading": "Slide 4: Pros of AI",
+            "bullet_points": [
+                "Increased efficiency and productivity",
+                "Improved accuracy and precision",
+                "Enhanced decision-making capabilities",
+                "Personalized experiences"
+            ]
+        },
+        {
+            "heading": "Slide 5: Cons of AI",
+            "bullet_points": [
+                "Job displacement and loss of employment",
+                "Bias and discrimination",
+                "Privacy and security concerns",
+                "Dependence on technology"
+            ]
+        },
+        {
+            "heading": "Slide 6: Future Prospects of AI",
+            "bullet_points": [
+                "Advancements in fields such as healthcare and finance",
+                "Increased use"
+            ]
+        }
+    ]
+}

global_config.py

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+from dataclasses import dataclass
+from dotenv import load_dotenv
+import os
+
+
+load_dotenv()
+
+
+@dataclass(frozen=True)
+class GlobalConfig:
+    CLARIFAI_PAT = os.environ.get('CLARIFAI_PAT', '')
+    CLARIFAI_USER_ID = 'meta'
+    CLARIFAI_APP_ID = 'Llama-2'
+    CLARIFAI_MODEL_ID = 'llama2-13b-chat'
+
+    CLARIFAI_USER_ID_GPT = 'openai'
+    CLARIFAI_APP_ID_GPT = 'chat-completion'
+    CLARIFAI_MODEL_ID_GPT = 'GPT-3_5-turbo'
+
+    # LLM_MODEL_TEMPERATURE: float = 0.5
+    LLM_MODEL_MIN_OUTPUT_LENGTH: int = 50
+    LLM_MODEL_MAX_OUTPUT_LENGTH: int = 2000
+    LLM_MODEL_MAX_INPUT_LENGTH: int = 1000
+
+    APP_STRINGS_FILE = 'strings.json'
+    PRELOAD_DATA_FILE = 'examples/example_02.json'
+    SLIDES_TEMPLATE_FILE = 'langchain_templates/template_07.txt'
+

langchain_templates/template_07.txt

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+You are a helpful, intelligent chatbot. Create the slides for a presentation on the given topic. Include main headings for each slide, detailed bullet points for each slide. Add relevant content to each slide. Do not output any blank line.
+
+
+Topic:
+{topic}

llm_helper.py

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+from langchain import PromptTemplate
+from langchain.llms import Clarifai
+
+from global_config import GlobalConfig
+
+
+prompt = None
+llm_contents = None
+llm_yaml = None
+
+
+def get_llm(use_gpt: bool) -> Clarifai:
+    """
+    Get a large language model.
+
+    :param use_gpt: True if GPT-3.5 is required; False is Llama 2 is required
+    """
+
+    if use_gpt:
+        llm = Clarifai(
+            pat=GlobalConfig.CLARIFAI_PAT,
+            user_id=GlobalConfig.CLARIFAI_USER_ID_GPT,
+            app_id=GlobalConfig.CLARIFAI_APP_ID_GPT,
+            model_id=GlobalConfig.CLARIFAI_MODEL_ID_GPT,
+            verbose=True,
+            # temperature=0.1,
+        )
+    else:
+        llm = Clarifai(
+            pat=GlobalConfig.CLARIFAI_PAT,
+            user_id=GlobalConfig.CLARIFAI_USER_ID,
+            app_id=GlobalConfig.CLARIFAI_APP_ID,
+            model_id=GlobalConfig.CLARIFAI_MODEL_ID,
+            verbose=True,
+            # temperature=0.1,
+        )
+    print(llm)
+
+    return llm
+
+
+def generate_slides_content(topic: str) -> str:
+    """
+    Generate the outline/contents of slides for a presentation on a given topic.
+
+    :param topic: Topic/subject matter/idea on which slides are to be generated
+    :return: The content
+    """
+
+    global prompt
+    global llm_contents
+
+    if prompt is None:
+        with open(GlobalConfig.SLIDES_TEMPLATE_FILE, 'r') as in_file:
+            template_txt = in_file.read().strip()
+
+        prompt = PromptTemplate.from_template(template_txt)
+
+    formatted_prompt = prompt.format(topic=topic)
+    print(f'formatted_prompt:\n{formatted_prompt}')
+
+    if llm_contents is None:
+        llm_contents = get_llm(use_gpt=False)
+
+    slides_content = llm_contents(formatted_prompt, verbose=True)
+
+    return slides_content
+
+
+def text_to_json(content: str) -> str:
+    """
+    Convert input text into structured JSON representation.
+
+    :param content: Input text
+    :return: JSON string
+    """
+
+    global llm_yaml
+
+    content = content.replace('```', '')
+
+    # f-string is not used in order to prevent interpreting the brackets
+    text = '''
+Convert the given slide deck text into structured JSON output.
+Also, generate and add an engaging presentation title. 
+The output should be only correct and valid JSON having the following structure:
+
+{
+    "title": "...",
+    "slides": [
+        {
+            "heading": "...",
+            "bullet_points": [
+                "...",
+                [
+                    "...",
+                    "..."
+                ]
+            ]
+        },
+        {
+            ...
+        },
+    ]
+}
+
+
+Text:
+'''
+    text += content
+    text += '''
+
+
+Output:
+```json
+'''
+
+    text = text.strip()
+    print(text)
+
+    if llm_yaml is None:
+        llm_yaml = get_llm(use_gpt=True)
+
+    output = llm_yaml(text, verbose=True)
+    output = output.strip()
+
+    first_index = max(0, output.find('{'))
+    last_index = min(output.rfind('}'), len(output))
+    output = output[first_index: last_index + 1]
+
+    return output
+
+
+def text_to_yaml(content: str) -> str:
+    """
+    Convert input text into structured YAML representation.
+
+    :param content: Input text
+    :return: JSON string
+    """
+
+    global llm_yaml
+
+    content = content.replace('```', '')
+
+    # f-string is not used in order to prevent interpreting the brackets
+    text = '''
+You are a helpful AI assistant.
+Convert the given slide deck text into structured YAML output.
+Also, generate and add an engaging presentation title. 
+The output should be only correct and valid YAML having the following structure:
+
+title: "..."
+slides:
+  - heading: "..."
+    bullet_points:
+      - "..."
+      - "..."
+  - heading: "..."
+    bullet_points:
+      - "..."
+      - "...":  # This line ends with a colon because it has a sub-block
+        - "..."
+      - "..."
+
+
+Text:
+'''
+    text += content
+    text += '''
+
+
+
+
+Output:
+```yaml
+'''
+
+    text = text.strip()
+    print(text)
+
+    if llm_yaml is None:
+        llm_yaml = get_llm(use_gpt=True)
+
+    output = llm_yaml(text, verbose=True)
+    output = output.strip()
+
+    # first_index = max(0, output.find('{'))
+    # last_index = min(output.rfind('}'), len(output))
+    # output = output[first_index: last_index + 1]
+
+    return output
+
+
+if __name__ == '__main__':
+    pass
+

pptx_helper.py

@@ -0,0 +1,99 @@
+import json5
+import pptx
+import re
+import yaml
+
+from pptx.dml.color import RGBColor
+
+PATTERN = re.compile(r"^slide[ ]+\d+:", re.IGNORECASE)
+
+
+def remove_slide_number_from_heading(header: str) -> str:
+    if PATTERN.match(header):
+        idx = header.find(':')
+        header = header[idx + 1:]
+
+    return header
+
+
+def generate_powerpoint_presentation(structured_data: str, as_yaml: bool, output_file_name: str):
+    """
+    Create and save a PowerPoint presentation file containing the contents in JSON or YAML format.
+
+    :param structured_data: The presentation contents as "JSON" (may contain trailing commas) or YAML
+    :param as_yaml: True if the input data is in YAML format; False if it is in JSON format
+    :param output_file_name: The name of the PPTX file to save as
+    """
+
+    if as_yaml:
+        # Avoid YAML mode: nested bullets can lead to incorrect YAML generation
+        try:
+            parsed_data = yaml.safe_load(structured_data)
+        except yaml.parser.ParserError as ype:
+            print(f'*** YAML parse error: {ype}')
+            parsed_data = {'title': '', 'slides': []}
+    else:
+        # The structured "JSON" might contain trailing commas, so using json5
+        parsed_data = json5.loads(structured_data)
+
+    presentation = pptx.Presentation()
+
+    # The title slide
+    title_slide_layout = presentation.slide_layouts[0]
+    slide = presentation.slides.add_slide(title_slide_layout)
+    title = slide.shapes.title
+    subtitle = slide.placeholders[1]
+    title.text = parsed_data['title']
+    print(f'Title is: {title.text}')
+    subtitle.text = 'by Myself and SlideDeck AI :)'
+
+    background = slide.background
+    background.fill.solid()
+    background.fill.fore_color.rgb = RGBColor.from_string('C0C0C0')  # Silver
+    title.text_frame.paragraphs[0].font.color.rgb = RGBColor(0, 0, 128)  # Navy blue
+
+    # Add contents in a loop
+    for a_slide in parsed_data['slides']:
+        bullet_slide_layout = presentation.slide_layouts[1]
+        slide = presentation.slides.add_slide(bullet_slide_layout)
+        shapes = slide.shapes
+
+        title_shape = shapes.title
+        body_shape = shapes.placeholders[1]
+        title_shape.text = remove_slide_number_from_heading(a_slide['heading'])
+        text_frame = body_shape.text_frame
+
+        for an_item in a_slide['bullet_points']:
+            item_type = type(an_item)
+            # print('Bullet point type:', item_type)
+
+            if item_type is str:
+                paragraph = text_frame.add_paragraph()
+                paragraph.text = an_item
+                paragraph.level = 0
+            elif item_type is list:
+                for sub_item in an_item:
+                    if type(sub_item) is str:
+                        paragraph = text_frame.add_paragraph()
+                        paragraph.text = sub_item
+                        paragraph.level = 1
+
+        background = slide.background
+        background.fill.gradient()
+        background.fill.gradient_angle = -225.0
+
+    # The thank-you slide
+    last_slide_layout = presentation.slide_layouts[0]
+    slide = presentation.slides.add_slide(last_slide_layout)
+    title = slide.shapes.title
+    title.text = 'Thank you!'
+
+    presentation.save(output_file_name)
+
+
+if __name__ == '__main__':
+    generate_powerpoint_presentation(
+        json5.loads(open('examples/example_02_structured_output.json', 'r').read()),
+        as_yaml=False,
+        output_file_name='test.pptx'
+    )

requirements.txt

@@ -0,0 +1,9 @@
+python-dotenv[cli]~=1.0.0
+langchain~=0.0.273
+# huggingface_hub
+streamlit~=1.26.0
+clarifai==9.7.4
+
+python-pptx
+json5~=0.9.14
+PyYAML~=6.0.1

strings.json

@@ -0,0 +1,23 @@
+{
+    "app_name": "SlideDeck AI",
+    "caption": "*:green[Co-create your next PowerPoint slide deck with AI]*",
+    "section_headers": [
+        "Step 1: Generate your content",
+        "Step 2: Make it structured",
+        "Step 3: Create the slides",
+    ],
+    "section_captions": [
+        "Let\'s start by generating some contents for your slides",
+        "Let\'s now convert the above generated contents into JSON",
+        "Let\'s now create the slides for you",
+    ],
+    "input_labels": [
+        "**Describe the topic of the presentation. Avoid mentioning the count of slides.**\n*Note: the output may be short or truncated due to API limitations.*",
+    ],
+    "button_labels": [
+        "Generate slides content",
+        "Generate JSON",
+        "Make the slides"
+    ],
+    "content_generation_failure_error": "Unfortunately, SlideDeck AI failed to generate any content for you! Please try again later."
+}