All-in-one infrastructure for building search, recommendations, and RAG. Trieve combines search language models with tools for tuning ranking and relevance.

Java Examples using LangChain4J for Generative AI using ChatGPT LLM, RAG and other open source LLMs. Sentiment Analysis, Application Context based ChatBots. Custom Data Handling. LLMs - GPT 4o, Llama3, PHI-3, Gemma, Falcon 2, Mistral.

Chrome Extension to Summarize or Chat with Web Pages/Local Documents Using locally running LLMs. Keep all of your data and conversations private. 🔐

Train and Infer Powerful Sentence Embeddings with AnglE | 🔥 SOTA on STS and MTEB Leaderboard

🧑‍🚀 全世界最好的中文LLM资料总结

Gemini Pro LLM and Pinecone Vector Database for fast and performant Retrieval Augmented Generation (RAG) with LlamaIndex

Harness LLMs with Multi-Agent Programming

Plugin that creates a ChromaDB vector database to work with LM Studio running in server mode!

In this project I have built an end to end langchain project using hugging face open source llm models such as Mistral and also open source embedding models.

ChatGPT, embedding search, and retrieval-augmented generation for Squeak/Smalltalk

The AI-native database built for LLM applications, providing incredibly fast full-text and vector search

Fractal Graph Desktop for Ai-Agents, Web-Browsing, Note-Taking, and Code.

Setup and run a local LLM and Chatbot using consumer grade hardware.

Minimalist web-searching app with an AI assistant that runs directly from your browser. Uses Web-LLM, Ratchet-ML, Wllama and SearXNG. Demo: https://felladrin-minisearch.hf.space

GemmaLLM RAG chatbot

AI-based search engine done right

The open source platform for AI-native application development.

💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows

"Chat with Databases using RAG" is a cutting-edge project that seamlessly integrates natural language inputs with database interactions. By leveraging advanced techniques like RAG and few-shot learning, it generates SQL queries from plain text and retrieves human-like responses from the database, revolutionizing the way we interact with data.

An AI-powered application that can guess movie titles based on plot summaries. Built using LangChain, Google Palm LLM, CSVLoader, RetrievalQA, Google Palm Embeddings, and FAISS. Deployed on Streamlit for an interactive user experience, allowing you to enter a plot summary and receive a predicted movie title.