[Feature] Add support for RAG evaluation (#1154)
Co-authored-by: Deven Patel <deven298@yahoo.com> Co-authored-by: Deshraj Yadav <deshrajdry@gmail.com>
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92
embedchain/config/eval/base.py
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92
embedchain/config/eval/base.py
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from typing import Optional
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from embedchain.config.base_config import BaseConfig
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ANSWER_RELEVANCY_PROMPT = """
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Please provide $num_gen_questions questions from the provided answer.
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You must provide the complete question, if are not able to provide the complete question, return empty string ("").
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Please only provide one question per line without numbers or bullets to distinguish them.
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You must only provide the questions and no other text.
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$answer
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""" # noqa:E501
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CONTEXT_RELEVANCY_PROMPT = """
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Please extract relevant sentences from the provided context that is required to answer the given question.
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If no relevant sentences are found, or if you believe the question cannot be answered from the given context, return the empty string ("").
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While extracting candidate sentences you're not allowed to make any changes to sentences from given context or make up any sentences.
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You must only provide sentences from the given context and nothing else.
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Context: $context
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Question: $question
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""" # noqa:E501
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GROUNDEDNESS_ANSWER_CLAIMS_PROMPT = """
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Please provide one or more statements from each sentence of the provided answer.
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You must provide the symantically equivalent statements for each sentence of the answer.
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You must provide the complete statement, if are not able to provide the complete statement, return empty string ("").
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Please only provide one statement per line WITHOUT numbers or bullets.
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If the question provided is not being answered in the provided answer, return empty string ("").
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You must only provide the statements and no other text.
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$question
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$answer
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""" # noqa:E501
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GROUNDEDNESS_CLAIMS_INFERENCE_PROMPT = """
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Given the context and the provided claim statements, please provide a verdict for each claim statement whether it can be completely infered from the given context or not.
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Use only "1" (yes), "0" (no) and "-1" (null) for "yes", "no" or "null" respectively.
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You must provide one verdict per line, ONLY WITH "1", "0" or "-1" as per your verdict to the given statement and nothing else.
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You must provide the verdicts in the same order as the claim statements.
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Contexts:
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$context
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Claim statements:
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$claim_statements
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""" # noqa:E501
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class GroundednessConfig(BaseConfig):
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def __init__(
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self,
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model: str = "gpt-4",
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api_key: Optional[str] = None,
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answer_claims_prompt: str = GROUNDEDNESS_ANSWER_CLAIMS_PROMPT,
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claims_inference_prompt: str = GROUNDEDNESS_CLAIMS_INFERENCE_PROMPT,
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):
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self.model = model
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self.api_key = api_key
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self.answer_claims_prompt = answer_claims_prompt
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self.claims_inference_prompt = claims_inference_prompt
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class AnswerRelevanceConfig(BaseConfig):
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def __init__(
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self,
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model: str = "gpt-4",
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embedder: str = "text-embedding-ada-002",
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api_key: Optional[str] = None,
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num_gen_questions: int = 1,
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prompt: str = ANSWER_RELEVANCY_PROMPT,
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):
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self.model = model
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self.embedder = embedder
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self.api_key = api_key
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self.num_gen_questions = num_gen_questions
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self.prompt = prompt
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class ContextRelevanceConfig(BaseConfig):
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def __init__(
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self,
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model: str = "gpt-4",
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api_key: Optional[str] = None,
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language: str = "en",
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prompt: str = CONTEXT_RELEVANCY_PROMPT,
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):
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self.model = model
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self.api_key = api_key
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self.language = language
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self.prompt = prompt
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