Llama MCP Streamlit

What is LLaMa-MCP-Streamlit?

LLaMa-MCP-Streamlit is an interactive AI assistant built using Streamlit, NVIDIA NIM (LLaMa 3.3:70B), and Model Control Protocol (MCP). It allows users to interact with a large language model (LLM) to execute real-time external tools, retrieve data, and perform various actions seamlessly.

How to use LLaMa-MCP-Streamlit?

To use the assistant, you can run the Streamlit app after configuring the necessary API keys in the .env file. You can either use Poetry or Docker to set up and run the application.

Key features of LLaMa-MCP-Streamlit?

• Custom model selection from NVIDIA NIM or Ollama.
• API configuration for different backends.
• Tool integration via MCP for enhanced usability.
• User-friendly chat-based interface.

Use cases of LLaMa-MCP-Streamlit?

1. Executing real-time data processing tasks.
2. Interacting with various LLMs for different applications.
3. Enhancing productivity through seamless tool integration.

FAQ from LLaMa-MCP-Streamlit?

• Can I use my own models?
  Yes! You can select custom models from NVIDIA NIM or Ollama.

• Is Docker required to run the project?
  No, Docker is optional. You can run the project using Poetry as well.

• How do I configure the MCP server?
  You can modify the utils/mcp_server.py file to change the MCP server configuration.