andrea-nuzzo/markdown-langchain-rag
🦜 🔗 Query and obtain data from Markdown documents with LangChain's RAG system
This tool helps you quickly find answers and insights hidden within a collection of your Markdown documents, like project notes, knowledge bases, or documentation. You provide your Markdown files and specific questions, and it extracts the most relevant information and generates direct answers. This is ideal for researchers, technical writers, or anyone who manages a lot of text-based information.
No commits in the last 6 months.
Use this if you need to quickly get specific answers from a large number of Markdown documents without manually sifting through each file.
Not ideal if your information is stored in formats other than Markdown, or if you require real-time, interactive chat capabilities.
Stars
50
Forks
9
Language
Python
License
—
Category
Last pushed
Feb 12, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/andrea-nuzzo/markdown-langchain-rag"
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)