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[RFC] Run Evaluator Chains #5618

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[RFC] Run Evaluator Chains #5618

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vowelparrot
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@vowelparrot vowelparrot commented Jun 2, 2023

Will try to land #5750 first
Pros:

  • Fits many but not all feedback applications.
  • Maintains a flexible base with configurable implementations.
  • Doesn't implement THAT many new classes for the core logic

Cons:

  • doesn't handle pairwise/group evals
  • trajectory evals are a bit hacky ( you have to remember to turn on when tracing rather than building it from the run object)
  • possibly too opinionated by forcing an input mapper and output parser?
  • Doesn't (yet) allow easy composability of the reasoning step (most do COT built in)
  • Most of the scores are binary - no nuance or more advanced logic. Doesn't (yet) decouple the scoring logic from the core of the prompt
  • Not sure if the creation functions are actually much better than creating a child and making a complicated constructor

Example making 5 different evaluators:

image

vowelparrot added a commit to langchain-ai/langsmith-sdk that referenced this pull request Jun 2, 2023
See: langchain-ai/langchain#5618 for example
LangChain implementations


I think we'll want some simple non-langchain completion function
evaluators if we want this core interface to be of much use outside the
OSS project. I also don't think I want to land the StringEvaluator class
but put it up as an example of one approach (that contrasts with the
ones above)

Co-authored-by: Nuno Campos <nuno@boringbits.io>
@vowelparrot vowelparrot closed this Jun 5, 2023
vowelparrot added a commit that referenced this pull request Jun 6, 2023
Clean up a bit and only implement the QA and reference free
implementations from #5618
Undertone0809 pushed a commit to Undertone0809/langchain that referenced this pull request Jun 19, 2023
Clean up a bit and only implement the QA and reference free
implementations from langchain-ai#5618
kacperlukawski pushed a commit to kacperlukawski/langchain that referenced this pull request Jun 29, 2023
Clean up a bit and only implement the QA and reference free
implementations from langchain-ai#5618
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