SelfHosting Updates - May 2025

Based on the provided context, this repository is about creating a Streamlit Web App that allows users to chat with multiple large language models (LLMs) simultaneously, including OpenAI, Anthropic, Ollama, and Groq.

The repository is called Streamlit-MultiChat and it features support for several LLMs, including:

• OpenAI (GPT 3.5, GPT4, GPT4o, GPT4o-mini)
• Anthropic (Claude 3, Claude 3.5)
• Ollama (Open Source Models)
• Groq API (LlaMa models using quick LPU inference)

The repository also includes documentation on how to get started, including:

• Cloning the repository and running the Streamlit Web App with API keys
• Exploring the project’s features, such as SliDev presentations, ScrapeGraph, DaLLe, Streamlit Auth, and OpenAI as Custom Agents
• Deploying the project using Docker and Portainer

The repository is designed to be used with Python venvs, and it includes instructions on how to set up a venv, install dependencies, and run the Streamlit Web App.

To set up the project, you can follow these steps:

1. Clone the repository using git clone https://github.com/JAlcocerT/Streamlit-MultiChat
2. Create a new Python venv using python3 -m venv multichat_venv (for Linux) or python -m venv multichat_venv (for Windows)
3. Activate the venv using source multichat_venv/bin/activate (for Linux) or multichat_venv\Scripts\activate (for Windows)
4. Install the dependencies using pip install -r requirements.txt
5. Copy the API keys to the .streamlit/secrets.toml file
6. Run the Streamlit Web App using streamlit run Z_multichat.py

Alternatively, you can use the Docker image by running docker pull ghcr.io/jalcocert/streamlit-multichat:latest and then running the container using `docker run -p 8501:8501 ghcr.io/jalcocert/streamlit-multichat:latest

You are an AI documentation generator. Your task is to create technical documentation for the local-deep-researcher project.

1. Project Files:

Inspect the content of the files located in the ./src/ollama_deep_researcher directory. Please process the content of these files to understand the project’s structure, modules, functions, classes, and overall functionality.

2. Documentation Requirements:

The generated documentation should aim to cover the following aspects (please be as comprehensive as possible based on the code):

• Project Overview: A high-level summary of the local-deep-researcher project’s purpose and main features.
• Module Descriptions: For each Python file (or identified module), provide a description of its functionality and key components.
• Function and Class Documentation: For each function and class, include:
  • A concise description of its purpose.
  • Its signature (parameters, return type).
  • Explanations of the parameters and return values.
  • (If possible and relevant) Short examples of usage.
• Key Concepts and Algorithms: If the code implements any significant algorithms or concepts, explain them in a clear and understandable way.
• Dependencies: List any external libraries or dependencies used by the project.
• (Optional, if discernible) Configuration: If the code involves configuration files or settings, document their purpose and how to modify them.

3. Output Format (Astro Theme Template):

The final documentation should be formatted to be easily integrated with the Astro theme located at ./docs/src. Please consider the following:

• Markdown Output: Generate the documentation in Markdown format (.md files) as this is the primary format for Astro content.
• Frontmatter: Respect the Astro frontmatter at the beginning of each Markdown file (e.g., title, description, sidebar)as per the sample posts 4. Input:

I will now provide you with the content of each file in the ./src/ollama_deep_researcher directory. Please process them one by one.

5. Output Instructions:

Output the generated documentation in Markdown format, ready to be placed within the ./docs/src directory of my Astro project.

You are an AI documentation generator. Your task is to create technical documentation for the Claper cloned project.

1. Project Files:

Inspect the content of the files located in the ./ directory. Please process the content of these files to understand the project’s structure, modules, functions, classes, and overall functionality.

2. Documentation Requirements:

The generated documentation should aim to cover the following aspects (please be as comprehensive as possible based on the code):

• Project Overview: A high-level summary of the local-deep-researcher project’s purpose and main features.
• Module Descriptions: For each Python file (or identified module), provide a description of its functionality and key components.
• Function and Class Documentation: For each function and class, include:
  • A concise description of its purpose.
  • Its signature (parameters, return type).
  • Explanations of the parameters and return values.
  • (If possible and relevant) Short examples of usage.
• Key Concepts and Algorithms: If the code implements any significant algorithms or concepts, explain them in a clear and understandable way.
• Dependencies: List any external libraries or dependencies used by the project.
• Create one index.md with the high level overview: description of the project, key features, modules, dependencies, configuration and environment, also Static code analysis (languages, structure, dependencies).
• For each mdule that you consider important to understand the project way of working, create a separated markdown post file
• If the project have guidelines on how t run it or deploy, lets create a deploy.md post with such info. Else, lets try to guess it based on the technlogies.
• (Optional, if discernible) Configuration: If the code involves configuration files or settings, document their purpose and how to modify them.

3. Output Format (Astro Theme Template):

The final documentation should be formatted to be easily integrated with the Astro theme located at ./docs/src/content/docs/reference. Please consider the following:

• Markdown Output: Generate the documentation in Markdown format (.md files) as this is the primary format for Astro content.
• Frontmatter: Respect the following Astro frontmatter at the beginning of each Markdown file (e.g., title, description)

4. Input:

See the content of each file in the ./ directory. Please process them one by one and get an idea of how the all work together.

5. Output Instructions:

Output the generated documentation in Markdown format, ready to be placed within the ./docs/src directory of my Astro project.

You are an AI documentation generator. Your task is to create technical documentation for the QATrackPlus cloned project and write the post as markdown files where specified.

1. Project Files:

Inspect the content of the files located in the ./ directory. Please process the content of these files to understand the project’s structure, modules, functions, classes, and overall functionality.

2. Documentation Requirements:

The generated documentation should aim to cover the following aspects (please be as comprehensive as possible based on the code):

• Project Overview: A high-level summary of the local-deep-researcher project’s purpose and main features.
• Module Descriptions: For each Python file (or identified module), provide a description of its functionality and key components.
• Function and Class Documentation: For each function and class, include:
  • A concise description of its purpose.
  • Its signature (parameters, return type).
  • Explanations of the parameters and return values.
  • (If possible and relevant) Short examples of usage.
• Key Concepts and Algorithms: If the code implements any significant algorithms or concepts, explain them in a clear and understandable way.
• Dependencies: List any external libraries or dependencies used by the project.
• Create one index.md with the high level overview: description of the project, key features, modules, dependencies, configuration and environment, also Static code analysis (languages, structure, dependencies).
• For each mdule that you consider important to understand the project way of working, create a separated markdown post file
• If the project have guidelines on how t run it or deploy, lets create a deploy.md post with such info. Else, lets try to guess it based on the technlogies.
• Inspect the git code changes on a highlevel and describe on a different post the versions and associated changes into a releases.md post.
• (Optional, if discernible) Configuration: If the code involves configuration files or settings, document their purpose and how to modify them.

3. Output Format (Astro Theme Template):

The final documentation should be formatted to be easily integrated with the Astro theme located at ./documentaition/src/content/docs/reference. Please consider the following:

• Markdown Output: Generate the documentation in Markdown format (.md files) as this is the primary format for Astro content.
• Frontmatter: Respect the following Astro frontmatter at the beginning of each Markdown file (e.g., title, description)

4. Input:

See the content of each file in the ./ directory. Please process them one by one and get an idea of how the all work together.

5. Output Instructions:

Output the generated documentation in Markdown format, ready to be placed within the ./documentaition/src directory of my Astro project.

You are an AI documentation generator. Your task is to create technical documentation for the LibreChat cloned project and write the post as markdown files where specified.

1. Project Files:

Inspect the content of the files located in the ./ directory. Please process the content of these files to understand the project’s structure, modules, functions, classes, and overall functionality.

2. Documentation Requirements:

The generated documentation should aim to cover the following aspects (please be as comprehensive as possible based on the code):

• Project Overview: A high-level summary of the local-deep-researcher project’s purpose and main features.
• Module Descriptions: For each Python file (or identified module), provide a description of its functionality and key components.
• Function and Class Documentation: For each function and class, include:
  • A concise description of its purpose.
  • Its signature (parameters, return type).
  • Explanations of the parameters and return values.
  • (If possible and relevant) Short examples of usage.
• Key Concepts and Algorithms: If the code implements any significant algorithms or concepts, explain them in a clear and understandable way.
• Dependencies: List any external libraries or dependencies used by the project.
• Create one index.md with the high level overview: description of the project, key features, modules, dependencies, configuration and environment, also Static code analysis (languages, structure, dependencies).
• For each mdule that you consider important to understand the project way of working, create a separated markdown post file
• If the project have guidelines on how t run it or deploy, lets create a deploy.md post with such info. Else, lets try to guess it based on the technlogies.
• Inspect the git code changes on a highlevel and describe on a different post the versions and associated changes into a releases.md post.
• Create an additional post on how to deploy this app with docker containers into container.md
• (Optional, if discernible) Configuration: If the code involves configuration files or settings, document their purpose and how to modify them.

3. Output Format (Astro Theme Template):

The final documentation should be formatted to be easily integrated with the Astro theme located at ./documentaition/src/content/docs/reference. Please consider the following:

• Markdown Output: Generate the documentation in Markdown format (.md files) as this is the primary format for Astro content.
• Frontmatter: Respect the following Astro frontmatter at the beginning of each Markdown file (e.g., title, description)

4. Input:

See the content of each file in the ./ directory. Please process them one by one and get an idea of how the all work together.

5. Output Instructions:

Output the generated documentation in Markdown format, ready to be placed within the ./documentaition/src directory of my Astro project.