Comments (2)
@lbux : I like your idea but just to be clear, what I'm asking for is to see the literal input and output of the LLM at runtime.
I also believe that that's what the unit of caching should be.
I do also like the idea of being able to read and write the prompt, however.
Or subclass.
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I think it would make sense to be able to return/print the prompt for the respective metric.
Perhaps even having a getter/setter would work (the setter for when we want to make minor changes to the built in prompt without having to write a whole new metric.
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Related Issues (20)
- Remove unconditional, uncontrollable output statements
- deepeval should return non-zero exitCode on failure HOT 1
- Dramatically simpler and more reliable cache
- Synthesizer generates goldens but a dataset loads as test cases
- Synthesizer only takes one document in list of documents for some edge cases
- RagasMetric breaks when used with dataset HOT 1
- Suggestion for Future Improvement: Enable Function Calling for Consistent JSON Output
- No response after processing few prompts.
- ProxySchemeUnknown: Proxy URL had no scheme, should start with http:// or https://
- `check_for_update` should not happen on package load HOT 1
- Error in Faithfulness metric: KeyError: 'claims' in `a_generate_claims` HOT 3
- Selective records failure instead of Complete Job Failure HOT 2
- `ignore_errors` doesn't work as expected if `show_indicator` is set to False HOT 2
- accuracy always comes 0, might be a bug in my code i am unable to find.
- Message about nest_asyncio Should Not Be Printed HOT 2
- Add Support for `Gemini` Models HOT 4
- Conversation Evaluations
- MMLU stopped working
- Invalid value for 'top_logprobs': must be less than or equal to 5 for AzureOpenAi Models
- AuthenticationError HOT 2
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