BenderScript/ragtime
RAG Course using LangChain and OpenAI
This course teaches you how to build advanced AI applications that can answer complex questions by combining information retrieval with generative AI. You'll learn to take external data, like documents or articles, and use it to create highly accurate and contextually relevant AI responses. This is for AI enthusiasts, software developers, and researchers eager to develop next-generation AI solutions like smart chatbots or advanced search engines.
No commits in the last 6 months.
Use this if you want to integrate up-to-date, external information into your AI models to generate more accurate and context-aware responses.
Not ideal if you are looking for a plug-and-play AI solution rather than wanting to learn the underlying architecture and build applications yourself.
Stars
10
Forks
—
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 01, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/BenderScript/ragtime"
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)