yussufbiyik/langchain-chromadb-rag-example
My attempt at implementing retreival augmented generation on Ollama and other LLM services using chromadb and langchain while also providing an easy to understand, clean code for others since nobody else does
This project helps Python developers implement Retrieval Augmented Generation (RAG) using Ollama and ChromaDB. It takes in various document types (PDF, TXT, CSV, DOCX) from a specified folder, uses them to build a knowledge base, and then allows an LLM to generate more informed and context-aware responses. Python developers looking to integrate RAG into their applications would use this.
No commits in the last 6 months.
Use this if you are a Python developer who wants a clear, example-driven way to set up Retrieval Augmented Generation (RAG) with local LLMs via Ollama and a vector database like ChromaDB.
Not ideal if you are an end-user without programming experience, as this is a developer tool requiring Python and command-line execution.
Stars
50
Forks
10
Language
Python
License
—
Category
Last pushed
Oct 12, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/yussufbiyik/langchain-chromadb-rag-example"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
run-llama/llama_index
LlamaIndex is the leading document agent and OCR platform
emarco177/documentation-helper
Reference implementation of a RAG-based documentation helper using LangChain, Pinecone, and Tavily..
janus-llm/janus-llm
Leveraging LLMs for modernization through intelligent chunking, iterative prompting and...
JetXu-LLM/llama-github
Llama-github is an open-source Python library that empowers LLM Chatbots, AI Agents, and...
Vasallo94/ObsidianRAG
RAG system to query your Obsidian notes using LangGraph and local LLMs (Ollama)