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ChainForge

An open-source, extensible visual programming environment for developing prompt-analysis chains for LLMs.

ChainForge is a data flow programming environment for visualizing and developing "prompt chains" for LLMs. It integrates with Python code as its backend, such as LangChain, for calling LLMs and performing analysis on responses.

Our goal is to provide a basic architecture around prompt chaining that developers can build upon for their specific use cases. As such, we focus on extensibility and simplicity.

ChainForge is built on ReactFlow.

Developers

  • Ian Arawjo
  • Priyan Vaithilingam

Inspiration and Links

This project was inspired by own our use case, but also derives insights from two related (closed-source) research projects:

  • "PromptChainer: Chaining Large Language Model Prompts through Visual Programming" (Wu et al., CHI ’22 LBW) Video
  • "AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Prompts" (Wu et al., CHI ’22)

Unlike these projects, this project aspires to be open-source and remain in the public domain, as our ultimate goal is integration into other tools for the systematic evaluation and auditing of LLMs. We hope to help others who are developing prompt-analysis flows in LLMs, or otherwise auditing LLM outputs.