FastDatasets helps create training datasets for large language models.
Open source
24 alternativesianarawjo/ChainForge
An open-source visual programming environment for battle-testing prompts to LLMs.
About ianarawjo/ChainForge
ChainForge is an open-source visual data-flow environment for analyzing and evaluating responses from large language models. Users can query multiple models at once, compare outputs across prompt versions, models and settings, and define scoring functions with visualized results. It also provides generation of synthetic test tables and starter code for evaluations. The tool can be used on the web with a limited feature set, or installed locally. Local installation requires Python 3.10 or higher and user-supplied API keys, and enables Python-based evaluation and queries to locally hosted models via Ollama.
Key features
- Query multiple LLMs at once to test prompt variations
- Compare responses across prompts, models and settings
- Define scoring functions and visualize results across runs
- Generate synthetic tables and input examples for testing
- Write Python code to evaluate responses in local install
- Query locally hosted models via Ollama in local install
Best for: People developing prompts who need to compare outputs across models and measure variations systematically.
Good for
- Open source with example evaluation flows for reference
- Supports side-by-side testing across models, prompts and settings
- Local install loads API keys from environment variables and supports Python evaluation
Watch out for
- Web version has a limited feature set compared with local install
- Local install requires Python 3.10 or higher
- Full server-side RAG stack and FAISS require separate manual installs
ianarawjo/ChainForge at a glance
- Category
- AI & Machine Learning › AI Data & Analytics
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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ianarawjo/ChainForge FAQ
How do I run ChainForge locally?
Install Python 3.10 or higher, run pip install chainforge, then run chainforge serve and open localhost:8000 in Chrome, Firefox, Edge, or Brave.
How does the web version differ from a local install?
The web version has a limited feature set. A local install can load API keys from environment variables, run Python code to evaluate responses, and query locally hosted models via Ollama.
What is needed for retrieval-augmented generation features?
Upload, Chunk, Retrieval and Rerank nodes run in the browser with no extra installation. The server-side stack with hosted embedding providers, persistent LanceDB stores, TF-IDF and larger rerankers requires pip install chainforge[rag], and FAISS must be installed separately if needed.
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