Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype to production without rebuilding the stack.
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Your AI second brain. Self-hostable. Get answers from the web or your docs. Build custom agents, schedule automations, do deep research. Turn any online or local LLM into your personal, autonomous AI (gpt, claude, gemini, llama, qwen, mistral). Get started - free.
- semantic-search
- emacs
- obsidian-md
- chat
The #1 AI Harness for Building Resumes, PDFs, Cover Letters & more, locally with 100+ LLMs support.
- text-similarity
- natural-language-processing
- word-embeddings
- python
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.
- semantic-search
- information-retrieval
- ai
- python
Translated🔥 MaxKB is an open-source platform for building enterprise-grade agents. A powerful and easy-to-use open-source enterprise-grade agent platform.
Production-grade platform for building agentic IM bots - 生产级多平台智能机器人开发平台/ Agent、知识库编排、插件系统 / Bots for Discord / Slack / LINE / Telegram / WeChat(企业微信, 企微智能机器人, 公众号) / 飞书 / 钉钉 / QQ / Matrix e.g. Integrated with ChatGPT(GPT), DeepSeek, Dify, n8n, Langflow, Coze, Claude, Gemini, GLM, Ollama, SiliconFlow, Kimi, openclaw / hermes agent, deerflow
Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support, and API connectivity for agents.
Build a portrait of your life. Assistants that know you. Clones that talk like you.
Unified framework for building enterprise RAG pipelines with small, specialized models
- parsing
- retrieval-augmented-generation
- agents
- generative-ai-tools
Low-code framework for building custom LLMs, neural networks, and other AI models
Pocket Flow: 100-line LLM framework. Let Agents build Agents!
- agents
- flow-based-programming
- flow-engineering
- llm-agent
Build high-quality LLM apps - from prototyping, testing to production deployment and monitoring.
The AI Compute Platform for frontier teams. SkyPilot turns fragmented AI compute into one AI supercomputer, so frontier AI teams build custom intelligence faster.
- cloud-computing
- deep-learning
- gpu
- hyperparameter-tuning
Build, Manage and Deploy AI/ML Systems
- machine-learning
- model-management
- ai
- ml
Python & Command-line tool to gather text and metadata on the Web: Crawling, scraping, extraction, output as CSV, JSON, HTML, MD, TXT, XML
- web-scraping
- text-extraction
- nlp
- html2text
Superduper: End-to-end framework for building custom AI applications and agents.
- ai
- mlops
- torch
- transformers
A framework to build Slack apps using Python
- slack
- slack-api
- bolt
- web-api
Build AI phone agents on your own computer and test every change with an AI caller. Open source, runs free with no API keys, cents per call with your own keys. Imports Dialogflow CX.
- agents-as-code
- contact-center
- conversational-ai
- cx-agent-studio
Build AI text detectors whose decisions are mechanistically grounded and human-auditable (EMNLP 2026)
- ai-text-detection
- explainable-ai
- interpretability
- mechanistic-interpretability
A unified framework for building, evaluating, and recursively improving embodied agents. 🚀 Code release coming soon.
🧱 Experimental library for building inference engines
This is the official repo for paper InteractiveWorld A Verifiable Human-Centric Environment for Building Better Interactive MLLM Assistants
Friendly Environment for Neural Networks (fenn) is a simple Python framework for building ML/DL workflows and LLM agents faster, with prebuilt trainers, agent templates, logging, configuration management, and much more.
- beginner-friendly
- beginner-project
- deep-learning
- deep-neural-networks
Trust metadata for AI agents — a stamp costs ~15 tokens, re-verifying costs 15,000. Agents stamp what they verify; the next agent runs 'akf check' and builds on it. pip install akf