mfmezger/ollama-rag-chainlit
🏗️ Frameworkmfmezger
A local RAG conversational agent template using Ollama, LangChain, and Chainlit for private document interaction.
The ollama-rag-chainlit repository serves as a robust starter kit for developers aiming to deploy local RAG pipelines. By leveraging LangChain, the project handles complex document loading, text splitting, and vector store integration, allowing the agent to retrieve context from local files effectively. The inclusion of Chainlit provides a production-ready UI out of the box, featuring chat history management and real-time streaming responses.
Technically, the project demonstrates how to bridge local LLMs with document retrieval systems. It is highly modular, allowing users to swap out embedding models or vector databases as needed. It serves as a companion to the author's broader conversational-agent-langchain project, focusing specifically on the RAG implementation layer. This tool is ideal for prototyping private AI assistants that need to process sensitive documents while maintaining full control over the infrastructure and data residency.
💡Highlights
- ├─Local RAG with Ollama integration
- ├─Chainlit-based chat interface
- └─LangChain-powered orchestration
🎯For
- ├─AI Developers
- └─Privacy-focused Engineers