Supercharge your AI agents with data from the web and beyond. Building the library for superintelligence. 🔥
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RAGFlow is an agent-native database: a Retrieval-Augmented Generation (RAG) engine that grew into context infrastructure.
Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 100+ languages.
- ocr
- chineseocr
- pdf2markdown
- pp-ocr
Official Crawl4AI Cloud: a hosted web scraping, extraction, and search API for AI agents. Free API key, 1,000 credits a month, no card. Fully open source: this repo is the Apache-2.0 crawler that powers it, and you can self-host it.
Transforms complex documents like PDFs and Office docs into LLM-ready markdown/JSON for your Agentic workflows.
Leaked system prompts of ChatGPT, Claude, Gemini and more. The hidden system prompt of every popular chatbot, in full, every version since May 2025. Also Anthropic Claude Code, OpenAI Codex, Google Antigravity, xAI Grok, Meta Muse, Moonshot Kimi, Alibaba Qwen, Z.ai GLM ZCode, MiniMax, Cursor, Perplexity, DeepSeek and 30+ others. Updated daily.
TranslatedLLM-powered multi-market stock analysis system with multi-source market data, real-time news, decision dashboard, automated notifications, and cost-free scheduled runs.
Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience
- rag
- localai
- vector-database
- llm
Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
- batch-processing
- kafka
- pathway
- python
A no-code RAG server that keeps answers in sync with your documents. Works with 8 vector databases. Built on Pathway.
LlamaIndex is the document processing platform for AI
- agents
- application
- data
- fine-tuning
Convert PDF to markdown + JSON quickly with high accuracy
:hedgehog: PostHog is the leading platform for building self-driving products. Our developer tools – AI observability, analytics, session replay, flags, experiments, error tracking, logs, and more – capture all the context agents need to diagnose problems, uncover opportunities, and ship fixes. Steer it all from Slack, web, desktop, or the MCP.
📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG
A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization.
Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory with small models for free
- ai
- cognitive-architecture
- vector-database
- ai-agents
PDF Parser for AI-ready data. Automate PDF accessibility. Open-source.
Code and documentation to train Stanford's Alpaca models, and generate the data.
- deep-learning
- instruction-following
- language-model
FastGPT is a knowledge-based platform built on the LLMs, offers a comprehensive suite of out-of-the-box capabilities such as data processing, RAG retrieval, and visual AI workflow orchestration, letting you easily develop and deploy complex question-answering systems without the need for extensive setup or configuration.
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
- machine-learning
- ai
- ml
- mlflow
Agent2Agent (A2A) is an open protocol enabling communication and interoperability between opaque agentic applications.
- a2a
- a2a-mcp
- a2a-protocol
- a2a-server
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
Open source observability platform for logs, metrics, traces, RUM (web, android, ios), Session replay, pipelines, SLO and LLM observability. A sophisticated, simple and highly performant alternative to Datadog, Splunk, and Elasticsearch with 140x lower storage costs and single binary deployment.