Show HN: ChainForge, a visual tool for prompt engineering and LLM evaluation (chainforge.ai)
Hi HN! We’re been working hard on this low-code tool for rapid prompt discovery, robustness testing and LLM evaluation. We’ve just released documentation to help new users learn how to use it and what it can already do. Let us know what you think! :)
32 comments
[ 3.0 ms ] story [ 86.0 ms ] threadI don't personally have a need for this right now, but I can really see the use for the parameterised queries, as well as comparisons across models.
Thanks for your efforts!
0: https://github.com/ianarawjo/ChainForge
EDIT: ah: "This work was partially funded by the NSF grant IIS-2107391." ok cool we the taxpayer funded it haha
That's outside of the MIT licence as far as I'm concerned
If I called it truly open source I half expected to get shot down.
I know where we stand now :)
Similar "we would appreciate citations" statement for (BSD-licensed) pandas: https://pandas.pydata.org/about/citing.html
8000+ pubs citing pandas: https://scholar.google.com/scholar?cites=9876954816936339312
https://github.com/logspace-ai/langflow
https://github.com/FlowiseAI/Flowise
https://devboard.gitsense.com/logspace-ai/langflow
https://devboard.gitsense.com/FlowiseAI/Flowise
https://devboard.gitsense.com/ianarawjo/ChainForge
Flowise currently has the largest active community (based on GitHub data)
Full Disclosure: This is my tool
thats what its like to blindly compare tools by github numbers
I'm not saying ChainForge is bad, but it will need to go against that kind of community engagement that other projects with a head start have. However, if you believe people contributing code (26) and participating in non code activity (150) in Flowise in the last 6 weeks are just novelty metrics, then yes, comparing numbers is silly.
Some CF users, for instance, might not be app builders at all —they just want to audit models.
I think both problems —prompt engineering and LLM app building —are hard, and deserve their own dedicated tools.
Can contact me here: https://twitter.com/IanArawjo Or find email on CV here: ianarawjo.com
At any rate, glad it was helpful!
Vertex AI has the same API as PaLM as far as I know. However, the authorization is through Google Cloud. So I use it like any other GCP API.
I love the idea of adding fine tuning as a node though. Here is the API for creating a model tuning job - https://cloud.google.com/vertex-ai/docs/generative-ai/models...
I wish I could use ChainForge nodes in Node Red.
E.g. this
> Compare response quality across prompt permutations, across models, and across model settings to choose the best prompt and model for your use case.
Feature/guidance request: how to actually call functions, how to loop on responses to resolve multiple function calls. I've managed to mock a response to get_current_weather using this contraption: https://pasteboard.co/aO9BmHG5qsFt.png . But it's messy and I can't see a way to actually evaluate function calls. And if I involve the Chat Turn node, the message sequences seem to get tangled with each other. Probably I'm holding it wrong!
As far as evaluating functions go, that’s unfortunately a ways off. But, we generally prioritize things based on how many people posted GitHub Issues about it/want it. (For instance, Chat Turn nodes came from an Issue.) If you post a feature request there, it’ll move up our priority list, and we can also clarify what the feature precisely should be.