The job search that runs on your machine. AI job application framework built on Claude Code: evaluate postings, tailor CVs, write cover letters, prep interviews. Fork it and own it.
Independent Auditing of AI Agents. Run by human or the agent itself, to answer the most crucial question in the AI Agent Economy. Is the agent doing what is supposed to do? With iFixAi you can have this answer in less than 120 seconds.
DiscoveryRSI: Recursively Learning to Discover Valuable Hypotheses
An auditable, reversible, evaluable local agent runtime that turns feedback into skills β and ships them only when evidence and tests say so.
Offline multi-speaker meeting-speech toolkit: planted-ground-truth synthetic meeting factory, VAD, speaker embeddings, diarization (AHC/spectral/VB-HMM), overlap detection, CTC speaker-attributed ASR, cpWER/DER/JER evaluation, online streaming mode, deterministic reports. NumPy core, CPU-only torch extra.
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.
Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.
An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
The LLM Evaluation Framework
Gorilla: Training and Evaluating LLMs for Function Calls (Tool Calls)
BISHENG is an open LLM devops platform for next generation Enterprise AI applications. Powerful and comprehensive features include: GenAI workflow, RAG, Agent, Unified model management, Evaluation, SFT, Dataset Management, Enterprise-level System Management, Observability and more.
AI Observability & Evaluation
the LLM vulnerability scanner
Easily fine-tune (SFT/RL), evaluate, and deploy Qwen, Gemma, or any open agentic LLM/VLM!
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.
AI agent to evaluate and score resumes.
A full-stack AI Red Teaming platform securing AI ecosystems via Agent Scan, Skills Scan, MCP scan, AI Infra scan and LLM jailbreak evaluation.
Framework for evaluating and improving agents
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.
The CLI and skills that turn any coding assistant into an expert at creating, evaluating, and deploying AI agents on Google Cloud.
π’ Open-Source Evaluation & Testing library for LLM Agents
Transparent and Efficient Financial Analysis
Build, Evaluate, and Optimize AI Systems. Includes evals, RAG, agents, fine-tuning, synthetic data generation, dataset management, MCP, and more.
The open source research environment for AI researchers to seamlessly train, evaluate, and scale models from local hardware to GPU clusters.
Most popular metrics used to evaluate object detection algorithms.
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
Versioned Codex instruction deployment with preview, ownership manifests, hook isolation, scenario evaluation, and recovery.
One-for-All Multimodal Evaluation Toolkit Across Text, Image, Video, and Audio Tasks
Open-source evaluation toolkit of large multi-modality models (LMMs), support 220+ LMMs, 80+ benchmarks
Python package for the evaluation of odometry and SLAM
Code, Build and Evaluate agents - excellent Model and Skills/MCP/ACP/A2A Support
Evaluation and Tracking for LLM Experiments and AI Agents
A streamlined and customizable framework for efficient large model (LLM, VLM, AIGC) evaluation and performance benchmarking.
MTEB: State-of-the-art evaluation of embeddings across languages and modalities
Code for the paper "Evaluating Large Language Models Trained on Code"
A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.
[NeurIPS 2026] DataFlex: A Unified Benchmark and Evaluation Platform for Data-Centric Training of Large Language Models
Inspect: A framework for large language model evaluations
Lighteval is your all-in-one toolkit for evaluating LLMs across multiple backends
Fast numerical array expression evaluator for Python, NumPy, Pandas, PyTables and more
π€ Evaluate: A library for easily evaluating machine learning models and datasets.
AssetOpsBench - Industry 4.0: A unified benchmark and framework for building, orchestrating, and evaluating domain-specific AI agents for Industry 4.0 asset operations and maintenance, with 460+ scenarios, 5 specialist agents (IoT, FMSR, TSFM, Work Order,...), and multi-agent orchestration blueprints (MetaAgent, AgentHive) over MCP.
The Fable Workflow: how Claude Fable 5 worked, distilled into skills any model can run, with the eval that keeps it honest. Think / act / prove.
A platform for reproducible world model research and evaluation
Local typed decisions, contrastive data curation, and model evaluation.
Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications. Tracing Β· Evals Β· Simulations Β· Datasets Β· Gateway Β· Guardrails. Self-hostable. Apache 2.0.
:cloud: :rocket: :bar_chart: :chart_with_upwards_trend: Evaluating state of the art in AI
π€ A Python library for learning and evaluating knowledge graph embeddings
Agentic LLM Vulnerability Scanner / AI red teaming kit π§ͺ
This project aims to compare and evaluate the telemetry of various EDR products.
AI+ιθοΌιεοΌοΌ1.ε€ε εθ‘η₯¨ιεζ‘ζΆεΌζΊζη¨ 2.ε¦ηεδΈηηη»ε Έθ΅ζζΆε½ 3.AI + ιθηηΈε ³ε·₯δ½οΌε ζ¬LLM, Agent, benchmark(evaluation), etc.
AI on the way. An auto deep learning pipe dream. An RDBMS approach to deep learning. Declarative, explainable, scalable, optimizable, easy to deploy, all that good stuff.
Evaluate and Enhance Your LLM Deployments for Real-World Inference Needs
A PyTorch library and evaluation platform for end-to-end compression research
The living ecosystem where AI agents complete tasks through workflow loops, improve through iterative execution, are evaluated by mentor agents or humans in the loop, and turn completed work into reusable work experience and data to improve future agents.
Multi-class confusion matrix library in Python
A benchmark built to evaluate and improve agent capabilities for supporting legal work.
OpenOCR: An Open-Source Toolkit for General-OCR Research and Applications, integrates a unified training and evaluation benchmark, commercial-grade OCR and Document Parsing systems, and faithful reproductions of the core implementations from a wide range of academic papers.
Postgres, MySQL, or MariaDB to Elasticsearch/OpenSearch sync
Create, Evaluate, and Connect AI Skills