Optimize prompts, code, and more with AI-powered Reflective Optimization
- agent-skills
- coding-agent
- discovery
- distributed-evolutionary-algorithms
Repository Index
77,353 visible repositories in the index
49–72 of 180 · Most stars
DeepSpec: a full-stack codebase for training and evaluating speculative decoding algorithms
Framework for evaluating and improving agents
- evals
- rl-environments
- terminal-bench
Modeling, training, eval, and inference code for OLMo
Translated非线智能 NoneLinear (Non-linear Intelligence) - ReLE evaluation: capability evaluation of Chinese AI large models (continuously updated): it currently covers 374 large models, including commercial models such as chatgpt, gpt-5.4, Google gemini-3.1-pro, Claude-4.6, 文心 ERNIE-X1.1, ERNIE-5.0, qwen3.6-max, qwen3.6-plus, Baichuan, iFlytek Spark, and SenseTime senseChat, as well as open-source large models such as step3.5-flash, kimi-k2.6, ernie4.5, MiniMax-M2.7, deepseek-v4, Qwen3.6, llama4, Zhipu GLM-5.1, MiMo-V2, LongCat, gemma4, and mistral. It provides not only leaderboards but also a large model defect library with more than 2,000,000 entries! This makes it convenient for the broad community to research, analyze, and improve large models.
- agentic-ai
- artificial-intelligence
- llm-agent
- llm-evaluation
Agent OS: the agent gets smarter on its own. We just hold the line: Interview-gated, staged evaluation, budgeted evolution loop. MCP server, 14 runtimes: Claude Code, Codex CLI, Gemini CLI, OpenCode, Copilot, Kiro and more.
- ai-agent
- agent-os
- llm-orchestration
- agentic-ai
The CLI and skills that turn any coding assistant into an expert at creating, evaluating, and deploying AI agents on Google Cloud.
- adk
- agent-development-kit
- agents
- coding-agent
Train and evaluate embeddings for similarity search with PyTorch. Includes contrastive losses, hard example mining, samplers, and retrieval metrics.
- metric-learning
- deep-learning
- computer-vision
- machine-learning
🧊 Open source LLM observability platform. One line of code to monitor, evaluate, and experiment. YC W23 🍓
- large-language-models
- prompt-engineering
- agent-monitoring
- analytics
Chinese version of CLIP which achieves Chinese cross-modal retrieval and representation generation.
- chinese
- computer-vision
- multi-modal-learning
- nlp
Python SDK for AI agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks including CrewAI, Agno, OpenAI Agents SDK, Langchain, Autogen, AG2, and CamelAI
🐢 Open-Source Evaluation & Testing library for LLM Agents
- mlops
- ml-validation
- ml-testing
- ai-testing
Next-generation AI Agent Optimization Platform: Cozeloop addresses challenges in AI agent development by providing full-lifecycle management capabilities from development, debugging, and evaluation to monitoring.
[ICLR'24 spotlight] An open platform for training, serving, and evaluating large language model for tool learning.
Your Personal Librarian Agent. Ask anything on your computer, organize files, remember important info and files.
- document-parser
- embeddings
- llm
- open-source
A framework for serving and evaluating LLM routers - save LLM costs without compromising quality
A large-scale 7B pretraining language model developed by BaiChuan-Inc.
The open source platform for AI-native application development.
- ai
- ai-native
- generative-ai
- gpt
The ultimate RAG for your monorepo. Query, understand, and edit multi-language codebases with the power of AI and knowledge graphs
- ai
- ast
- claude-code
- code-analysis
Build, Evaluate, and Optimize AI Systems. Includes evals, RAG, agents, fine-tuning, synthetic data generation, dataset management, MCP, and more.
- ai
- chain-of-thought
- collaboration
- dataset-generation
The open source research environment for AI researchers to seamlessly train, evaluate, and scale models from local hardware to GPU clusters.
Open-Source Agent Observability & Evals for AI Platform teams. Trace, test, route and govern every agent & coding assistant in the company.
Kodezi Chronos is a debugging-first language model that achieves state-of-the-art results on SWE-bench Lite (80.33%) and 67% real-world fix accuracy, over six times better than GPT-4. Built with Adaptive Graph-Guided Retrieval and Persistent Debug Memory. Model available Q1 2026 via Kodezi OS.
- artificial-intelligence
- benchmark
- benchmark-report
- bug-fixing
OpenKB: Open LLM Knowledge Base