Comments (5)
@AndresPrez Agreed with the embedding + similarity bit. Have you tried using GEval for this with strict=true
? I'm sure it will give good results.
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@penguine-ip g-eval is actually pretty nice! thanks for the advise ❤️
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@AndresPrez No problem! I'm actually going to push out more tutorials soon on the documentation page, I feel like the full capabilities of deepeval mostly go undiscovered 😅 Be including Answer Correctness for sure
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@penguine-ip - thanks for the explanation on this - I too got a bit fooled just because the docs state that ragas metrics are supported, and AnswerCorrectness is one of ragas metrics - bit of internal translation to do to get there.
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@gtmtech Yes but we eventually deleted most of it except for the flagship ragas metrics since they weren't very good n well maintained
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Related Issues (20)
- Knowledge Retention metric discrepancy HOT 3
- No test cases found error HOT 4
- Is context recall and context precision returns categorical output? HOT 1
- Cant use HuggingFace Model for evaluation HOT 5
- Unable to disable telemetry HOT 2
- Crash with ContextualRelevancyVerdict HOT 3
- 'Did not find openai_api_key' When using azure openai HOT 4
- .generate_raw_response(prompt) gives an attribute error HOT 6
- Corrupted cache can make it impossible to run deepeval
- 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
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