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@ -8,8 +8,8 @@ ChainForge is built on [ReactFlow](https://reactflow.dev) and is in active devel
# Features
A key goal of ChainForge is facilitating **comparison** and **evaluation** of prompts and models, and (in the near future) prompt chains. Basic features are:
- **Prompt permutations**: Setup a prompt template and feed it variations of input variables. ChainForge will prompt all selected LLMs with all possible permutations of the input prompt, so that you can get a better sense of prompt quality.
- **Evaluation nodes**: Probe LLM responses in a chain and test them for some desired behavior. Initially, Python script based.
- **Prompt permutations**: Setup a prompt template and feed it variations of input variables. ChainForge will prompt all selected LLMs with all possible permutations of the input prompt, so that you can get a better sense of prompt quality. You can also chain prompt templates at arbitrary depth (e.g., to compare templates).
- **Evaluation nodes**: Probe LLM responses in a chain and test them (classically) for some desired behavior. At a basic level, this is Python script based. We plan to add preset evaluator nodes for common use cases in the near future (e.g., name-entity recognition). Note that you can also chain LLM responses into prompt templates to help evaluate outputs cheaply before more extensive evaluation methods.
- **Visualization nodes**: Visualize evaluation results on plots like box-and-whisker and 3D scatterplots.
Taken together, these three features let you easily:
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All ChainForge node graphs are importable/exportable as JSON specs. You can freely share prompt chains you develop (alongside any custom analysis code), whether to the public or within your organization.
## Example: Test LLM robustness to prompt injection
...
# Development
ChainForge is developed by research scientists at Harvard University in the [Harvard HCI](https://hci.seas.harvard.edu) group: