An easy to use Neural Search Engine. Index latent vectors along with JSON metadata and do efficient k-NN search.
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Updated
May 6, 2024 - HTML
An easy to use Neural Search Engine. Index latent vectors along with JSON metadata and do efficient k-NN search.
Weaviate vector database – examples
Bedrock Knowledge Base and Agents for Retrieval Augmented Generation (RAG)
Sentence Transformers API: An OpenAI compatible embedding API server
Search on your images via text or image to image search. Uses OpenAI CLIP embedding and LanceDB
LangChain Documentation Helper
HACKTOBERFEST '23 Open Source Contribution to Weaviate: Implemented python version of Multi-Modal Search using Weaviate
Trained chat-gpt 3.5 turbo model on 1000+ FAQs for students by vectorizing data using Pinecone DB. Used Langchain API & Reddit API for embedding & querying data, hosted w/ AWS Elastic Beanstalk.
💬🤖 Build a better chatbot 🤖💬
This Python application creates a simple document assistant using Streamlit, pinecone (vector store) and a language model (openai) for generating responses to user queries.
An application that looks at input text to search for similar passages within given sources
The objective of this project is to create a chatbot that can be used to communicate with users to provide answers to their health issues. This is a RAG implementation using open source stack.
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