ushakrishnan/SearchWithOpenAI
Quick start. Index multiple documents in a repository using HuggingFace embeddings. Save them in Chroma and / or FAISS for recall. Choose OpenAI or Azure OpenAI APIs to get answers to your questions - Q&A with OpenAI and Azure OpenAI.
This project helps you turn a collection of your own documents, like PDFs or text files, into a smart search engine. You feed in your files, and it creates a searchable knowledge base that you can then ask questions about. The output is direct answers to your questions, drawing information specifically from your uploaded documents, like having a personal expert for your content. This is for anyone who needs to quickly find answers or summarize information contained within their own specific library of documents.
No commits in the last 6 months.
Use this if you need to quickly get answers or summarize information from a large set of your own documents without manually sifting through them.
Not ideal if you're looking for a general-purpose search engine for the entire web, as its primary strength is querying your specific uploaded content.
Stars
42
Forks
10
Language
Python
License
MIT
Category
Last pushed
Aug 21, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/ushakrishnan/SearchWithOpenAI"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.