RAG Application\
A demo of Retrieval-Augmented Generation (RAG) application with MCP server integration.\ \ Screenshot\ \
Features\
- MCP server integration\
- Document retrieval using vector search with ChromaDB\
- Context-aware prompt generation\
- Integration with LLM APIs\
\
Installation\
pip install -r requirements.txt\\
Usage\
Connect to the MCP server with Claude Desktop, Cursor, or your preferred IDE.\ \ Use the process_query tool to ask questions about the company.\ \
Configuration\
Set up your environment variables in .env:\
OPENAI_API_KEY=your_api_key\\
Project Structure\
app/retrieval.py: Document retrieval functionality\ app/context.py: Context management\ app/llm_client.py: LLM API integration\ app/prompt_builder.py: Prompt construction\ \
License\
MIT