The fast, precise document-intelligence engine for every language: text, tables and metadata from 100+ formats, with OCR, transcription and code intelligence.
- text-extraction
- document-intelligence
- metadata-extraction
- pdf-extraction
Repository Index
56,638 visible repositories in the index
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Open-source, high-performance AI gateway that works as your LLM gateway, MCP gateway and agent gateway. One OpenAI-compatible API for 10,000+ models, with failover, load balancing, semantic caching, virtual keys, budgets and MCP Code Mode. Works with any SDK or agent and adds under 200µs of overhead at 5k RPS.
- gateway
- llm-gateway
- guardrails
- mcp-gateway
Easily fine-tune (SFT/RL), evaluate, and deploy Qwen, Gemma, or any open agentic LLM/VLM!
The official repo for “Dolphin: Document Image Parsing via Heterogeneous Anchor Prompting”, ACL, 2025.
Awesome curated collection of images and prompts generated by gemini-2.5-flash-image (aka Nano Banana) state-of-the-art image generation and editing model. Explore AI generated visuals created with Gemini, showcasing Google’s advanced image generation capabilities.
The GEP-powered self-evolving engine for AI agents. Auditable evolution with Genes, Capsules, and Events. | evomap.ai
- a2a
- agent-evolution
- agent-framework
- agent-protocol
An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.
- chatgpt
- deep-learning
- instruction-following
- language-model
A Datacenter Scale Distributed Inference Serving Framework
- diffusion
- disaggregated-serving
- kubernetes
- llm-inference
A collection of libraries to optimise AI model performances
Awesome curated collection of images and prompts generated by GPT-4o and gpt-image-1. Explore AI generated visuals created with ChatGPT and Sora, showcasing OpenAI’s advanced image generation capabilities.
- ai-art
- awesome-list
- generative-art
- gpt-4o
LMDeploy is a toolkit for compressing, deploying, and serving LLMs.
- cuda-kernels
- deepspeed
- fastertransformer
- llm-inference
SoTA production-ready AI retrieval system. Agentic Retrieval-Augmented Generation (RAG) with a RESTful API.
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
- data-drift
- jupyter-notebook
- pandas-dataframe
- machine-learning
Stylish, intuitive and user-friendly prompts. Used by eslint, webpack, yarn, pm2, pnpm, RedwoodJS, FactorJS, salesforce, Cypress, Google Lighthouse, Generate, tencent cloudbase, lint-staged, gluegun, hygen, hardhat, AWS Amplify, GitHub Actions Toolkit, @airbnb/nimbus, and more! Please follow Enquirer's author: https://github.com/jonschlinkert
- prompt
- inquirer
- cli
- readline
Ingest, parse, and optimize any data format ➡️ from documents to multimedia ➡️ for enhanced compatibility with GenAI frameworks
- ingestion-api
- ocr
- omniparser
- parse-server
Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM
- artificial-intelligence
- attention-mechanisms
- deep-learning
- reinforcement-learning
Fast, flexible LLM inference
- llm
- rust
- uqff
Infrastructure for continually self‑improving agents
Open source inference engine that tunes its kernels on your hardware to find the fastest way to run each model. 2x faster than Ollama. Works on Apple Silicon, NVIDIA, AMD, Intel, or just a CPU.
ClawX is a desktop app that provides a graphical interface for OpenClaw AI agents. It turns CLI-based AI orchestration into a desktop experience without using the terminal. China website is https://clawx.com.cn.
OpenCompass is an LLM evaluation platform, supporting a wide range of models from OpenAI, Anthropic, Gemini, Qwen, GLM, DeepSeek, etc, across 100+ datasets covering knowledge, reasoning, coding, science, language, long-context, and safety.
- evaluation
- benchmark
- large-language-model
- llm
Open-source observability for your GenAI or LLM application, based on OpenTelemetry
- llmops
- observability
- open-telemetry
- metrics
Home of StarCoder: fine-tuning & inference!
TranslatedOpen-source manuscript of 《深入理解 AI Infra：量化分析与系统设计》 (In-Depth Understanding of AI Infra: Quantitative Analysis and System Design), by 李博杰 (Li Bojie): starting from hardware constraints and model architecture, it quantitatively derives the system design of LLM inference and training. Includes the full text of the book, a PDF, and companion calculation tools and experiments
- accelerator
- ai-infra
- ai-infrastructure
- book