Multi-User Chatbot with Langchain and Pinecone in Next.JS
🤖 An intelligent, context-aware chatbot that can be utilized to answer questions about your own documented data.
A library for efficient similarity search and clustering of dense vectors.
A cloud-native vector database, storage for next generation AI applications
A command-line tool that ingests documents and generates instant answers to your questions about those documents using ChatGPT, giving you the Sheldon Cooper you never had at your fingertips.
Basic Vector DB DataStorage For Images/Audio/Text Embeddings. for nlp with vb.net
Q & A with multiple pdf App is a Python application that allows you to ask questions about the PDFs you upload using natural language model to generate accurate answers to your queries.
Harnessing the Memory Power of the Camelids
A set of Node-RED nodes for interfacing with Couchbase services.
LLM powered ChatAI system. Added support for HF Embeddings and Models too
Orchestrating the interaction between users and Large Language Models
React Hook for indexed-vector-store package
The AI Assistant uses OpenAI's GPT models and Langchain for agent management and memory handling. With a Streamlit interface, it offers interactive responses and supports efficient document search with FAISS. Users can upload and search pdf, docx, and txt files, making it a versatile tool for answering questions and retrieving content.
Final Project for Information Retrival, this is an implementation that uses numpy of a vector store and a RAG PoC with ollama
Incorporar distintos tipos de documentos simultáneamente a la base de datos de embeddings Chroma con LangChain.
just testing langchain with llama cpp documents embeddings
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