github.com/Kiln-AI/Kiln @v1.0.3 sqlite

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A free app and open-source library to build better AI products.

Highlights • Evals • Auto-Optimize • RAG • Agents • Fine-Tuning • Synthetic Data • All Docs

What is Kiln?

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, or go fully offline with Ollama.

Highlights

Iterate, optimize, and collaborate

• 🖥️ Intuitive app - Easy-to-use apps for Mac, Windows, and Linux. One-click install.
• 📊 Eval Builder - Auto-generate evals (judge + synthetic eval dataset), and align to your preference in ~10 minutes.
• 🚀 Auto-Optimize - Automatically find the best way to run your AI task, optimizing prompt, model selection, tools, skills, subagents, parameters, and more.
• 💬 AI Assistant - Your AI data-science partner. Kiln Assistant proposes improvements, optimizes prompts, runs experiments, creates evals, and more.
• 🤝 Git-native collaboration - The app syncs to Git automatically — even for teammates who don't know what Git is.

Build & ship agents

• 🔍 RAG - Drag-and-drop docs (PDF, image, video, audio) to create a RAG. Auto-generated RAG evals from your own documents.
• 🤖 Subagents - Compose multi-agent hierarchies. Each runs in its own focused context window.
• 🪄 Synthetic Data Generation - Generate data for evals or fine-tuning in minutes.
• 🎛️ Fine-Tuning - Zero-code fine-tuning across 60+ models (Qwen, Llama, GPT, Gemini, …) on Fireworks, Together, and Vertex. Serverless deployment included.
• 🐍 Open Python library - Agents built in the app can be deployed to production. MIT open-source.
• 🧰 …and more - Tools & MCP, Skills, structured outputs, reasoning models, model library (190+ tested).

App Quickstart

Get started in minutes - one-click install.

Download Kiln Desktop for macOS, Windows, or Linux, then follow the 5-minute quickstart to run your first task.

Prefer to start in code? See the Python library quickstart.

Demo

Watch a 2-minute overview, or our end-to-end project demo (20 minutes).

Why Kiln?

Most AI tooling forces a tradeoff: a code-only framework that covers one slice (orchestration or evals or RAG), or a paid SaaS that locks in your data and can't be extended. Kiln is a free, local-first workbench where a single task and dataset flow through evals, prompt optimization, fine-tuning, RAG, agents, and synthetic data — all in one tool.

• One dataset, every technique. Define a task once. Eval it, optimize the prompt, fine-tune a model, generate synthetic data, add RAG — all against the same dataset, with results that compound across stages.

• Track every axis. Move fast. Don't regress. Keeping agents running well is hard — a prompt change quietly regresses behavior three steps downstream; a model upgrade improves five things and breaks two. Kiln tracks quality across every dimension you care about, so you iterate without breaking what already works.

  

• Optimization, not just evaluation. Other tools tell you how a prompt scores, but not how to fix it. Kiln's Auto-Optimize searches across hundreds of prompt mutations and models to find what works best for every eval dimension.

• GUI for the whole team, library for engineers. Kiln's desktop app lets PMs rate outputs, SMEs add training examples, and QA flag regressions — without a terminal. Engineers ship the same tasks via an MIT-licensed Python library. Data scientists can use the library in notebooks and experiments.

• Local-first. Most AI platforms are SaaS-only. Kiln runs entirely on your machine. Bring your own API keys, or go fully offline with Ollama. Your data never leaves your control. Team-sync is provided via Git infrastructure you already own.

• 190+ models tested across every provider. Skip the guesswork — we've tested every model's capabilities across all major providers. OpenAI, Anthropic, Gemini, Bedrock, Ollama, OpenRouter, Fireworks, Groq, any OpenAI-compatible endpoint, and more. Swap models with confidence.

Open-source Python Library

Build AI tasks in the app. Deploy with the open-source library. Same engine, same project files, no rewrite. The MIT-licensed kiln-ai library is the same library used in the app. Load Kiln projects, run tasks, build fine-tunes, work in notebooks, integrate Pandas/Polars dataframes, and more.

pip install kiln-ai

📚 Library docs · REST API · PyPI

Docs

Full docs at docs.kiln.tech. Common starting points:

• Quickstart — run your first task in 5 minutes
• Evals
• Auto-Optimize
• RAG
• Agents
• Fine-Tuning
• Python Library
• End-to-end project demo (20-min video)

Community

• Chat with the community on Discord.
• Subscribe to the newsletter for new features.
• File issues, request features, or open a discussion on GitHub.

Contributing

See CONTRIBUTING.md for development setup and contribution guidelines.

License & Trademarks

Kiln's core Python library and REST server are MIT-licensed. The desktop app is source-available, free to use, and built on the fair-code model — so Kiln stays free for individuals while remaining sustainable.

Datasets are open JSON. You own and control your datasets.

Kiln Pro is our service that adds the AI Assistant, Auto-Optimize, and the Eval Builder. It's opt-in, and the core Kiln app remains fully functional without it.

The Kiln name and logos are trademarks of Chesterfield Laboratories Inc.

Copyright 2024 — Chesterfield Laboratories Inc.