Kiln

by Kiln-AI · Python · ★ 4,937

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#evals#evaluation#evaluation-framework#fine-tuning#machine-learning#macos#mcp#ml#ollama#openai#prompt#prompt-engineering#python#rlhf#synthetic-data#windows

Install

pip install git+https://github.com/Kiln-AI/Kiln.git

Auto-generated from the repo's primary language — check the repo's own README for its exact install instructions.

Claude Desktop config

A starting point for your claude_desktop_config.json (auto-generated — the repo's README may specify a published package name or required env vars):

{
  "mcpServers": {
    "kiln": {
      "command": "uvx",
      "args": [
        "git+https://github.com/Kiln-AI/Kiln.git"
      ]
    }
  }
}

From the README

A free app and open-source library to build better AI products. Highlights • Evals • Auto-Optimize • RAG • Agents • Fine-Tuning • Synthetic Data • All Docs Kiln is a workbench for the full AI development loop: evals, optimization, prompts, RAG, fine-tuning, synthetic data, agents, and tools - all working together. The desktop app lets your whole team contribute (PMs, subject-experts, and QA can rate outputs and add data without writing code). The MIT-licensed Python library ships the same tasks to production. Runs locally - bring your own API keys…

Read full README on GitHub →

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