Popular GitHub Repositories for Documentation Framework

An Open Source Machine Learning Framework for Everyone

Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.

Elixir implementation of a LangChain style framework that lets Elixir projects integrate with and leverage LLMs.

? Lobe Chat - an open-source, modern-design AI chat framework. Supports Multi AI Providers( OpenAI / Claude 3 / Gemini / Ollama / DeepSeek / Qwen), Knowledge Base (file upload / knowledge management / RAG ), Multi-Modals (Plugins/Artifacts) and Thinking. One-click FREE deployment of your private ChatGPT/ Claude / DeepSeek application.

? The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming

A programming framework for agentic AI ? PyPi: autogen-agentchat Discord: https://aka.ms/autogen-discord Office Hour: https://aka.ms/autogen-officehour

The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, No-code agent builder, and more.

Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.

10 Lessons to Get Started Building AI Agents

LlamaIndex is the leading framework for building LLM-powered agents over your data.

Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.

Opiniated RAG for integrating GenAI in your apps ? Focus on your product rather than the RAG. Easy integration in existing products with customisation! Any LLM: GPT4, Groq, Llama. Any Vectorstore: PGVector, Faiss. Any Files. Anyway you want.

Low-code platform for building business applications. Connect to databases, cloud storages, GraphQL, API endpoints, Airtable, Google sheets, OpenAI, etc and build apps using drag and drop application builder. Built using JavaScript/TypeScript. ?

fabric is an open-source framework for augmenting humans using AI. It provides a modular framework for solving specific problems using a crowdsourced set of AI prompts that can be used anywhere.

Caffe: a fast open framework for deep learning.

Cross-platform, customizable ML solutions for live and streaming media.

Code and documentation to train Stanford's Alpaca models, and generate the data.

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

TradingAgents: Multi-Agents LLM Financial Trading Framework

AI 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.