o i@sdZddlZddlmZddlmZddlmZddlmZddlmZddlm Z dd lm Z Gd d d eZ Gd d d eZ dS)z(Format validation evaluators for LLMObs.N)Any)Callable)Optional)Union) BaseEvaluator)EvaluatorContext)EvaluatorResultc seZdZdZ     ddeedeededeeegeefdeef fd d Z d ed efd dZ de d e fddZ ZS)LengthEvaluatoraEvaluator that validates output length constraints. Checks if the output_data length falls within specified min/max bounds. Useful for ensuring responses meet length requirements, preventing overly verbose or too brief outputs. Example:: # Ensure response is between 50-200 characters evaluator = LengthEvaluator(min_length=50, max_length=200, count_type="characters") result = evaluator.evaluate(context) # Returns: True if within bounds, False otherwise # Validate length of extracted field evaluator = LengthEvaluator( min_length=10, max_length=100, output_extractor=lambda x: x.get("summary", "") if isinstance(x, dict) else str(x) ) # Validates the length of the "summary" field :param min_length: Minimum allowed length (inclusive), None for no minimum :param max_length: Maximum allowed length (inclusive), None for no maximum :param count_type: What to count - 'characters', 'words', or 'lines' :param output_extractor: Optional function to extract/transform output_data before validation. Must return a str or None. (default: None) :param name: Optional custom name for the evaluator N characters min_length max_length count_typeoutput_extractornamecstj|d|dvrtd||dur!|dkr!td||dur0|dkr0td||durG|durG||krGtd|d |d |durS|durStd |dur_t|s_td ||_||_||_||_dS) a(Initialize the LengthEvaluator evaluator. :param min_length: Minimum allowed length (None for no minimum) :param max_length: Maximum allowed length (None for no maximum) :param count_type: One of 'characters', 'words', or 'lines' :param output_extractor: Optional function to extract/transform output_data before validation. Must return a str or None. :param name: Optional custom name for the evaluator :raises ValueError: If count_type is invalid or min > max r)r wordslinesz;count_type must be 'characters', 'words', or 'lines', got: Nrz&min_length must be non-negative, got: z&max_length must be non-negative, got: z min_length (z%) cannot be greater than max_length ()z:At least one of min_length or max_length must be specified,output_extractor must be a callable function) super__init__ ValueErrorcallable TypeErrorr r r r)selfr r r rr __class__U/home/ubuntu/.local/lib/python3.10/site-packages/ddtrace/llmobs/_evaluators/format.pyr,s" zLengthEvaluator.__init__textreturncCs>|jdkr t|S|jdkrtdd|DSt|S)zzCalculate length based on count_type. :param text: The text to measure :return: The length value r rcSsg|]}|r|qSrr).0wordrrr `sz5LengthEvaluator._calculate_length..)r lensplit splitlines)rrrrr_calculate_lengthWs   z!LengthEvaluator._calculate_lengthcontextcCs|j}|jdur ||}|durtdddS|t|}|jdur.||jkr.tdddS|jdur>||jkr>tdddStdddS)zPerform length validation. :param context: The evaluation context :return: EvaluatorResult with boolean value and pass/fail assessment NFfailvalue assessmentTpass) output_datarrr'strr r )rr(outputlengthrrrevaluateds      zLengthEvaluator.evaluate)NNr NN)__name__ __module__ __qualname____doc__rintr/rrrr'rrr2 __classcell__rrrrr s(+ r c sjeZdZdZ   d deedeeegee e edffdee ffdd Z de d e fd d ZZS) JSONEvaluatoraEvaluator that validates if output is valid JSON. Checks if the output_data can be parsed as valid JSON. Optionally validates against a specific schema structure. Example:: # Just validate JSON syntax evaluator = JSONEvaluator() result = evaluator.evaluate(context) # Returns: True if valid JSON, False otherwise # Validate required keys evaluator = JSONEvaluator(required_keys=["name", "age"]) result = evaluator.evaluate(context) # Returns: True if valid JSON with all required keys, False otherwise # Validate JSON in extracted field evaluator = JSONEvaluator( required_keys=["status"], output_extractor=lambda x: x.get("response", "") if isinstance(x, dict) else str(x) ) # Validates the "response" field as JSON :param required_keys: Optional list of keys that must be present in the JSON object :param output_extractor: Optional function to extract/transform output_data before validation. Must return a str, dict, list, or None. (default: None) :param name: Optional custom name for the evaluator N required_keysrrcs:tj|d|durt|std|pg|_||_dS)apInitialize the JSONEvaluator evaluator. :param required_keys: list of keys that must be present in the parsed JSON :param output_extractor: Optional function to extract/transform output_data before validation. Must return a str, dict, list, or None. :param name: Optional custom name for the evaluator rNr)rrrrr:r)rr:rrrrrrs    zJSONEvaluator.__init__r(r c Cs|j}|jdur ||}|durtdddSt|ttfr!|}nt|}zt|}Wntj t t fy?tdddYSw|j rZt|trZ|j D]}||vrYtdddSqKtdddS)zPerform JSON validation. :param context: The evaluation context :return: EvaluatorResult with boolean value and pass/fail assessment NFr)r*Tr-) r.rr isinstancedictlistr/jsonloadsJSONDecodeErrorrrr:)rr(r0 parsed_data output_strkeyrrrr2s&     zJSONEvaluator.evaluate)NNN)r3r4r5r6rr=rrrr/r<rrrr2r8rrrrr9}s r9) r6r>typingrrrrddtrace.llmobs._experimentrrrr r9rrrrs       o