Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
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Updated
Jan 20, 2024 - Python
Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
Score documents using embedding-vectors dot-product or cosine-similarity with ES Lucene engine
Extract knowledge from all information sources using gpt and other language models. Index and make Q&A session with information sources.
A FastAPI service for semantic text search using precomputed embeddings and advanced similarity measures, with built-in support for various file types through textract.
DadmaTools is a Persian NLP tools developed by Dadmatech Co.
RAG with langchain using Amazon Bedrock and Amazon OpenSearch
Plugin that lets you use LM Studio to ask questions about your documents including audio and video files.
Vector Storage is a vector database that enables semantic similarity searches on text documents in the browser's local storage. It uses OpenAI embeddings to convert documents into vectors and allows searching for similar documents based on cosine similarity.
langchain-chat is an AI-driven Q&A system that leverages OpenAI's GPT-4 model and FAISS for efficient document indexing. It loads and splits documents from websites or PDFs, remembers conversations, and provides accurate, context-aware answers based on the indexed data. Easy to set up and extend.
Ruby wrapper for the Weaviate vector search database API
⚡ GUI for editing LLM vector embeddings. No more blind chunking. Upload content in any file extension, join and split chunks, edit metadata and embedding tokens + remove stop-words and punctuation with one click, add images, and download in .veml to share it with your team.
The Fast Vector Similarity Library is designed to provide efficient computation of various similarity measures between vectors.
Sentiment analyzer for your tweets.
Upload personal docs and Chat with your PDF files with this GPT4-powered app. Built with LangChain, Pinecone Vector Database, deployed on Streamlit
Personalize ChatGPT using LangChain, and get answers from your own documents and knowledge base.
A client side vector search library that can embed, store, search, and cache vectors. Works on the browser and node. It outperforms OpenAI's text-embedding-ada-002 and is way faster than Pinecone and other VectorDBs.
Ruby wrapper for the Qdrant vector search database API
LLM Chatbot w/ Retrieval Augmented Generation using Llamaindex. It demonstrates how to impl. chunking, indexing, and source citation.
A monolingual and cross-lingual meta-embedding generation and evaluation framework
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