Harness LLMs with Multi-Agent Programming

Penetration Testing AI Agent Assistant

AWS Generative AI CDK Constructs are sample implementations of AWS CDK for common generative AI patterns.

🔍 LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.

Elevate user interactions with ChatFAQ: your open-source chatbot solution, offering the full spectrum of ChatGPT capabilities. AI + LLM + CMS

RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.

LLMs prompt augmentation with RAG by integrating external custom data from a variety of sources, allowing chat with such documents

Build an efficient Python-based Retrieval-Augmented Generation (RAG) system for contextual query answering over personal data, all with natural language using ChatGoogleGenerativeAI (gemini-pro).

MongoDB Chatbot Framework. Powered by MongoDB and Atlas Vector Search.

BertChunker: Efficient and Trained Chunking for Unstructured documents. 训练Bert做文档语义分段.

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

The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense embedding, sparse embedding, tensor and full-text

Discover advanced AI techniques in my repository combining Multi-Hop Chain of Thought (CoT) and Retrieval-Augmented Generation (RAG) using DSPy and Indexify. Enhance complex problem-solving with multi-step reasoning and external knowledge integration. Perfect for AI enthusiasts and researchers.

Possibly futile attempt at grounding hype with theory and fundamentals

Distributed vector search for AI-native applications

The open source platform for AI-native application development.

A compute framework for turning complex data into vectors. Build multimodal vectors with ease and define weights at query time so you don't need a custom reranking algorithm to optimise results. Go straight from notebook to production with the same SDK.

RAG (Retrieval Augmented Generation) Framework for building modular, open source applications for production by TrueFoundry

TutorAI is a RAG system capable of assisting with learning academic subjects and using the curriculum and citing it. The project revolves around building an application that ingests a textbook in most formats and facilitates efficient learning of the course material.