diff --git a/agenta-backend/agenta_backend/migrations/v0_12_0_to_v0_15_0/20240509122536_evaluation_scenario_correct_answer.py b/agenta-backend/agenta_backend/migrations/v0_12_0_to_v0_15_0/20240509122536_evaluation_scenario_correct_answer.py new file mode 100644 index 0000000000..fba396e27b --- /dev/null +++ b/agenta-backend/agenta_backend/migrations/v0_12_0_to_v0_15_0/20240509122536_evaluation_scenario_correct_answer.py @@ -0,0 +1,345 @@ +from datetime import datetime, timezone +from typing import Any, Dict, List, Optional + +from pydantic import BaseModel, Field +from beanie import Document, Link, PydanticObjectId, iterative_migration + + +class UserDB(Document): + uid: str = Field(default="0", unique=True, index=True) + username: str = Field(default="agenta") + email: str = Field(default="demo@agenta.ai", unique=True) + created_at: Optional[datetime] = Field(default=datetime.now(timezone.utc)) + updated_at: Optional[datetime] = Field(default=datetime.now(timezone.utc)) + + class Settings: + name = "users" + + +class ImageDB(Document): + """Defines the info needed to get an image and connect it to the app variant""" + + type: Optional[str] = Field(default="image") + template_uri: Optional[str] + docker_id: Optional[str] = Field(index=True) + tags: Optional[str] + deletable: bool = Field(default=True) + user: Link[UserDB] + created_at: Optional[datetime] = Field(default=datetime.now(timezone.utc)) + updated_at: Optional[datetime] = Field(default=datetime.now(timezone.utc)) + + class Settings: + name = "docker_images" + + +class AppDB(Document): + app_name: str + user: Link[UserDB] + created_at: Optional[datetime] = Field(default=datetime.now(timezone.utc)) + updated_at: Optional[datetime] = Field(default=datetime.now(timezone.utc)) + + class Settings: + name = "app_db" + + +class DeploymentDB(Document): + app: Link[AppDB] + user: Link[UserDB] + container_name: Optional[str] + container_id: Optional[str] + uri: Optional[str] + status: str + created_at: Optional[datetime] = Field(default=datetime.now(timezone.utc)) + updated_at: Optional[datetime] = Field(default=datetime.now(timezone.utc)) + + class Settings: + name = "deployments" + + +class VariantBaseDB(Document): + app: Link[AppDB] + user: Link[UserDB] + base_name: str + image: Link[ImageDB] + deployment: Optional[PydanticObjectId] # Link to deployment + created_at: Optional[datetime] = Field(default=datetime.now(timezone.utc)) + updated_at: Optional[datetime] = Field(default=datetime.now(timezone.utc)) + + class Settings: + name = "bases" + + +class ConfigDB(BaseModel): + config_name: str + parameters: Dict[str, Any] = Field(default_factory=dict) + + +class AppVariantDB(Document): + app: Link[AppDB] + variant_name: str + revision: int + image: Link[ImageDB] + user: Link[UserDB] + modified_by: Link[UserDB] + parameters: Dict[str, Any] = Field(default=dict) # TODO: deprecated. remove + previous_variant_name: Optional[str] # TODO: deprecated. remove + base_name: Optional[str] + base: Link[VariantBaseDB] + config_name: Optional[str] + config: ConfigDB + created_at: Optional[datetime] = Field(default=datetime.now(timezone.utc)) + updated_at: Optional[datetime] = Field(default=datetime.now(timezone.utc)) + + is_deleted: bool = Field( # TODO: deprecated. remove + default=False + ) # soft deletion for using the template variants + + class Settings: + name = "app_variants" + + +class AppVariantRevisionsDB(Document): + variant: Link[AppVariantDB] + revision: int + modified_by: Link[UserDB] + base: Link[VariantBaseDB] + config: ConfigDB + created_at: datetime + updated_at: Optional[datetime] = Field(default=datetime.now(timezone.utc)) + + class Settings: + name = "app_variant_revisions" + + +class AppEnvironmentDB(Document): + app: Link[AppDB] + name: str + user: Link[UserDB] + revision: int + deployed_app_variant: Optional[PydanticObjectId] + deployed_app_variant_revision: Optional[Link[AppVariantRevisionsDB]] + deployment: Optional[PydanticObjectId] # reference to deployment + created_at: Optional[datetime] = Field(default=datetime.now(timezone.utc)) + + class Settings: + name = "environments" + + +class AppEnvironmentRevisionDB(Document): + environment: Link[AppEnvironmentDB] + revision: int + modified_by: Link[UserDB] + deployed_app_variant_revision: Optional[PydanticObjectId] + deployment: Optional[PydanticObjectId] # reference to deployment + created_at: datetime + + class Settings: + name = "environments_revisions" + + +class TemplateDB(Document): + type: Optional[str] = Field(default="image") + template_uri: Optional[str] + tag_id: Optional[int] + name: str = Field(unique=True) # tag name of image + repo_name: Optional[str] + title: str + description: str + size: Optional[int] + digest: Optional[str] # sha256 hash of image digest + last_pushed: Optional[datetime] + + class Settings: + name = "templates" + + +class TestSetDB(Document): + name: str + app: Link[AppDB] + csvdata: List[Dict[str, str]] + user: Link[UserDB] + created_at: Optional[datetime] = Field(default=datetime.now(timezone.utc)) + updated_at: Optional[datetime] = Field(default=datetime.now(timezone.utc)) + + class Settings: + name = "testsets" + + +class EvaluatorConfigDB(Document): + app: Link[AppDB] + user: Link[UserDB] + name: str + evaluator_key: str + settings_values: Dict[str, Any] = Field(default=dict) + created_at: datetime = Field(default=datetime.now(timezone.utc)) + updated_at: datetime = Field(default=datetime.now(timezone.utc)) + + class Settings: + name = "evaluators_configs" + + +class Error(BaseModel): + message: str + stacktrace: Optional[str] = None + + +class Result(BaseModel): + type: str + value: Optional[Any] = None + error: Optional[Error] = None + + +class InvokationResult(BaseModel): + result: Result + cost: Optional[float] = None + latency: Optional[float] = None + + +class EvaluationScenarioResult(BaseModel): + evaluator_config: PydanticObjectId + result: Result + + +class AggregatedResult(BaseModel): + evaluator_config: PydanticObjectId + result: Result + + +class EvaluationScenarioInputDB(BaseModel): + name: str + type: str + value: str + + +class EvaluationScenarioOutputDB(BaseModel): + result: Result + cost: Optional[float] = None + latency: Optional[float] = None + + +class HumanEvaluationScenarioInput(BaseModel): + input_name: str + input_value: str + + +class HumanEvaluationScenarioOutput(BaseModel): + variant_id: str + variant_output: str + + +class HumanEvaluationDB(Document): + app: Link[AppDB] + user: Link[UserDB] + status: str + evaluation_type: str + variants: List[PydanticObjectId] + variants_revisions: List[PydanticObjectId] + testset: Link[TestSetDB] + created_at: Optional[datetime] = Field(default=datetime.now(timezone.utc)) + updated_at: Optional[datetime] = Field(default=datetime.now(timezone.utc)) + + class Settings: + name = "human_evaluations" + + +class HumanEvaluationScenarioDB(Document): + user: Link[UserDB] + evaluation: Link[HumanEvaluationDB] + inputs: List[HumanEvaluationScenarioInput] + outputs: List[HumanEvaluationScenarioOutput] + vote: Optional[str] + score: Optional[Any] + correct_answer: Optional[str] + created_at: Optional[datetime] = Field(default=datetime.now(timezone.utc)) + updated_at: Optional[datetime] = Field(default=datetime.now(timezone.utc)) + is_pinned: Optional[bool] + note: Optional[str] + + class Settings: + name = "human_evaluations_scenarios" + + +class EvaluationDB(Document): + app: Link[AppDB] + user: Link[UserDB] + status: Result + testset: Link[TestSetDB] + variant: PydanticObjectId + variant_revision: PydanticObjectId + evaluators_configs: List[PydanticObjectId] + aggregated_results: List[AggregatedResult] + average_cost: Optional[Result] = None + total_cost: Optional[Result] = None + average_latency: Optional[Result] = None + created_at: datetime = Field(default=datetime.now(timezone.utc)) + updated_at: datetime = Field(default=datetime.now(timezone.utc)) + + class Settings: + name = "new_evaluations" + + +class CorrectAnswer(BaseModel): + key: str + value: str + + +class EvaluationScenarioDB(Document): + user: Link[UserDB] + evaluation: Link[EvaluationDB] + variant_id: PydanticObjectId + inputs: List[EvaluationScenarioInputDB] + outputs: List[EvaluationScenarioOutputDB] + correct_answers: Optional[List[CorrectAnswer]] + is_pinned: Optional[bool] + note: Optional[str] + evaluators_configs: List[PydanticObjectId] + results: List[EvaluationScenarioResult] + latency: Optional[int] = None + cost: Optional[int] = None + created_at: datetime = Field(default=datetime.now(timezone.utc)) + updated_at: datetime = Field(default=datetime.now(timezone.utc)) + + class Settings: + name = "new_evaluation_scenarios" + + +class OldEvaluationScenarioDB(Document): + user: Link[UserDB] + evaluation: Link[EvaluationDB] + variant_id: PydanticObjectId + inputs: List[EvaluationScenarioInputDB] + outputs: List[EvaluationScenarioOutputDB] + correct_answer: Optional[str] + is_pinned: Optional[bool] + note: Optional[str] + evaluators_configs: List[PydanticObjectId] + results: List[EvaluationScenarioResult] + latency: Optional[int] = None + cost: Optional[int] = None + created_at: datetime = Field(default=datetime.now(timezone.utc)) + updated_at: datetime = Field(default=datetime.now(timezone.utc)) + + class Settings: + name = "new_evaluation_scenarios" + + +class Forward: + @iterative_migration() + async def migrate_correct_answers( + self, + input_document: OldEvaluationScenarioDB, + output_document: EvaluationScenarioDB, + ): + if input_document.correct_answer: + output_document.correct_answers = [ + CorrectAnswer(key="correct_answer", value=input_document.correct_answer) + ] + else: + output_document.correct_answers = [] + + if "correct_answer" in input_document.dict(): + del input_document.__dict__["correct_answer"] + + +class Backward: + ... diff --git a/agenta-backend/agenta_backend/models/api/evaluation_model.py b/agenta-backend/agenta_backend/models/api/evaluation_model.py index cce2d7db7e..0313022409 100644 --- a/agenta-backend/agenta_backend/models/api/evaluation_model.py +++ b/agenta-backend/agenta_backend/models/api/evaluation_model.py @@ -158,13 +158,18 @@ class HumanEvaluationScenarioUpdate(BaseModel): note: Optional[str] +class CorrectAnswer(BaseModel): + key: str + value: str + + class EvaluationScenario(BaseModel): id: Optional[str] evaluation_id: str inputs: List[EvaluationScenarioInput] outputs: List[EvaluationScenarioOutput] evaluation: Optional[str] - correct_answer: Optional[str] + correct_answers: Optional[List[CorrectAnswer]] is_pinned: Optional[bool] note: Optional[str] results: List[EvaluationScenarioResult] diff --git a/agenta-backend/agenta_backend/models/converters.py b/agenta-backend/agenta_backend/models/converters.py index de7c6dabfb..cb73ea5976 100644 --- a/agenta-backend/agenta_backend/models/converters.py +++ b/agenta-backend/agenta_backend/models/converters.py @@ -9,6 +9,7 @@ from agenta_backend.utils.common import isCloudEE from agenta_backend.models.api.user_models import User from agenta_backend.models.api.evaluation_model import ( + CorrectAnswer, Evaluation, HumanEvaluation, EvaluatorConfig, @@ -253,7 +254,10 @@ def evaluation_scenario_db_to_pydantic( EvaluationScenarioOutput(**scenario_output.dict()) for scenario_output in evaluation_scenario_db.outputs ], - correct_answer=evaluation_scenario_db.correct_answer, + correct_answers=[ + CorrectAnswer(**correct_answer.dict()) + for correct_answer in evaluation_scenario_db.correct_answers + ], is_pinned=evaluation_scenario_db.is_pinned or False, note=evaluation_scenario_db.note or "", results=evaluation_scenarios_results_to_pydantic( diff --git a/agenta-backend/agenta_backend/models/db_models.py b/agenta-backend/agenta_backend/models/db_models.py index e67c8b42ce..85877bb20c 100644 --- a/agenta-backend/agenta_backend/models/db_models.py +++ b/agenta-backend/agenta_backend/models/db_models.py @@ -278,13 +278,18 @@ class Settings: name = "new_evaluations" +class CorrectAnswer(BaseModel): + key: str + value: str + + class EvaluationScenarioDB(Document): user: Link[UserDB] evaluation: Link[EvaluationDB] variant_id: PydanticObjectId inputs: List[EvaluationScenarioInputDB] outputs: List[EvaluationScenarioOutputDB] - correct_answer: Optional[str] + correct_answers: Optional[List[CorrectAnswer]] is_pinned: Optional[bool] note: Optional[str] evaluators_configs: List[PydanticObjectId] diff --git a/agenta-backend/agenta_backend/resources/evaluators/evaluators.py b/agenta-backend/agenta_backend/resources/evaluators/evaluators.py index effa7d417e..8e94d2c24e 100644 --- a/agenta-backend/agenta_backend/resources/evaluators/evaluators.py +++ b/agenta-backend/agenta_backend/resources/evaluators/evaluators.py @@ -4,18 +4,22 @@ "key": "auto_exact_match", "direct_use": True, "settings_template": { - "label": "Exact Match Settings", - "description": "Settings for the Exact Match evaluator", + "correct_answer_key": { + "label": "Expected Answer Column", + "default": "correct_answer", + "type": "string", + "advanced": True, # Tells the frontend that this setting is advanced and should be hidden by default + "ground_truth_key": True, # Tells the frontend that is the name of the column in the test set that should be shown as a ground truth to the user + "description": "The name of the column in the test data that contains the correct answer", + }, }, + "description": "Exact Match evaluator determines if the output exactly matches the specified correct answer, ensuring precise alignment with expected results.", }, { "name": "Contains Json", "key": "auto_contains_json", "direct_use": True, - "settings_template": { - "label": "Single Model Testing Settings", - "description": "Checks if the JSON output contains the specified JSON structure.", - }, + "settings_template": {}, "description": "Contains Json evaluator checks if the output contains the specified JSON structure.", }, { @@ -31,7 +35,15 @@ "min": 0, "max": 1, "required": True, - } + }, + "correct_answer_key": { + "label": "Expected Answer Column", + "default": "correct_answer", + "type": "string", + "advanced": True, # Tells the frontend that this setting is advanced and should be hidden by default + "ground_truth_key": True, # Tells the frontend that is the name of the column in the test set that should be shown as a ground truth to the user + "description": "The name of the column in the test data that contains the correct answer", + }, }, "description": "Similarity Match evaluator checks if the generated answer is similar to the expected answer. You need to provide the similarity threshold. It uses the Jaccard similarity to compare the answers.", }, @@ -67,7 +79,15 @@ "default": "", "description": "The name of the field in the JSON output that you wish to evaluate", "required": True, - } + }, + "correct_answer_key": { + "label": "Expected Answer Column", + "default": "correct_answer", + "type": "string", + "advanced": True, # Tells the frontend that this setting is advanced and should be hidden by default + "ground_truth_key": True, # Tells the frontend that is the name of the column in the test set that should be shown as a ground truth to the user + "description": "The name of the column in the test data that contains the correct answer", + }, }, "description": "JSON Field Match evaluator compares specific fields within JSON (JavaScript Object Notation) data. This matching can involve finding similarities or correspondences between fields in different JSON objects.", }, @@ -79,10 +99,18 @@ "prompt_template": { "label": "Prompt Template", "type": "text", - "default": "We have an LLM App that we want to evaluate its outputs. Based on the prompt and the parameters provided below evaluate the output based on the evaluation strategy below:\nEvaluation strategy: 0 to 10 0 is very bad and 10 is very good.\nPrompt: {llm_app_prompt_template}\nInputs: country: {country}\nCorrect Answer:{correct_answer}\nEvaluate this: {variant_output}\n\nAnswer ONLY with one of the given grading or evaluation options.", + "default": "We have an LLM App that we want to evaluate its outputs. Based on the prompt and the parameters provided below evaluate the output based on the evaluation strategy below:\nEvaluation strategy: 0 to 10 0 is very bad and 10 is very good.\nPrompt: {llm_app_prompt_template}\nInputs: country: {country}\nExpected Answer Column:{correct_answer}\nEvaluate this: {variant_output}\n\nAnswer ONLY with one of the given grading or evaluation options.", "description": "Template for AI critique prompts", "required": True, - } + }, + "correct_answer_key": { + "label": "Expected Answer Column", + "default": "correct_answer", + "type": "string", + "advanced": True, # Tells the frontend that this setting is advanced and should be hidden by default + "ground_truth_key": True, # Tells the frontend that is the name of the column in the test set that should be shown as a ground truth to the user + "description": "The name of the column in the test data that contains the correct answer", + }, }, "description": "AI Critique evaluator sends the generated answer and the correct_answer to an LLM model and uses it to evaluate the correctness of the answer. You need to provide the evaluation prompt (or use the default prompt).", }, @@ -112,39 +140,33 @@ "description": "https://your-webhook-url.com", "required": True, }, + "correct_answer_key": { + "label": "Expected Answer Column", + "default": "correct_answer", + "type": "string", + "advanced": True, # Tells the frontend that this setting is advanced and should be hidden by default + "ground_truth_key": True, # Tells the frontend that is the name of the column in the test set that should be shown as a ground truth to the user + "description": "The name of the column in the test data that contains the correct answer", + }, }, "description": "Webhook test evaluator sends the generated answer and the correct_answer to a webhook and expects a response indicating the correctness of the answer. You need to provide the URL of the webhook and the response of the webhook must be between 0 and 1.", }, - { - "name": "A/B Test", - "key": "human_a_b_testing", - "direct_use": False, - "settings_template": { - "label": "A/B Testing Settings", - "description": "Settings for A/B testing configurations", - }, - }, - { - "name": "Single Model Test", - "key": "human_single_model_test", - "direct_use": False, - "settings_template": { - "label": "Single Model Testing Settings", - "description": "Settings for single model testing configurations", - }, - }, { "name": "Starts With", "key": "auto_starts_with", "direct_use": False, "settings_template": { - "label": "Single Model Testing Settings", - "description": "Checks if the output starts with the specified prefix.", - "prefix": {"label": "prefix", "type": "string", "required": True}, + "prefix": { + "label": "prefix", + "type": "string", + "required": True, + "description": "The string to match at the start of the output.", + }, "case_sensitive": { "label": "Case Sensitive", "type": "boolean", "default": True, + "description": "If the evaluation should be case sensitive.", }, }, "description": "Starts With evaluator checks if the output starts with a specified prefix, considering case sensitivity based on the settings.", @@ -154,8 +176,6 @@ "key": "auto_ends_with", "direct_use": False, "settings_template": { - "label": "Single Model Testing Settings", - "description": "Checks if the output ends with the specified suffix.", "case_sensitive": { "label": "Case Sensitive", "type": "boolean", @@ -176,8 +196,6 @@ "key": "auto_contains", "direct_use": False, "settings_template": { - "label": "Single Model Testing Settings", - "description": "Checks if the output contains the specified substring.", "case_sensitive": { "label": "Case Sensitive", "type": "boolean", @@ -198,8 +216,6 @@ "key": "auto_contains_any", "direct_use": False, "settings_template": { - "label": "Single Model Testing Settings", - "description": "Checks if the output contains any of the specified substrings.", "case_sensitive": { "label": "Case Sensitive", "type": "boolean", @@ -220,8 +236,6 @@ "key": "auto_contains_all", "direct_use": False, "settings_template": { - "label": "Single Model Testing Settings", - "description": "Checks if the output contains all of the specified substrings.", "case_sensitive": { "label": "Case Sensitive", "type": "boolean", @@ -242,9 +256,20 @@ "key": "auto_levenshtein_distance", "direct_use": False, "settings_template": { - "label": "Levenshtein Distance Settings", - "description": "Evaluates the Levenshtein distance between the output and the correct answer. If a threshold is specified, it checks if the distance is below this threshold and returns a boolean value. If no threshold is specified, it returns the numerical Levenshtein distance.", - "threshold": {"label": "Threshold", "type": "number", "required": False}, + "threshold": { + "label": "Threshold", + "type": "number", + "required": False, + "description": "The maximum allowed Levenshtein distance between the output and the correct answer.", + }, + "correct_answer_key": { + "label": "Expected Answer Column", + "default": "correct_answer", + "type": "string", + "advanced": True, # Tells the frontend that this setting is advanced and should be hidden by default + "ground_truth_key": True, # Tells the frontend that is the name of the column in the test set that should be shown as a ground truth to the user + "description": "The name of the column in the test data that contains the correct answer", + }, }, "description": "This evaluator calculates the Levenshtein distance between the output and the correct answer. If a threshold is provided in the settings, it returns a boolean indicating whether the distance is within the threshold. If no threshold is provided, it returns the actual Levenshtein distance as a numerical value.", }, diff --git a/agenta-backend/agenta_backend/routers/evaluation_router.py b/agenta-backend/agenta_backend/routers/evaluation_router.py index a8552b73db..cb71942398 100644 --- a/agenta-backend/agenta_backend/routers/evaluation_router.py +++ b/agenta-backend/agenta_backend/routers/evaluation_router.py @@ -119,11 +119,6 @@ async def create_evaluation( return response evaluations = [] - correct_answer_column = ( - "correct_answer" - if payload.correct_answer_column is None - else payload.correct_answer_column - ) for variant_id in payload.variant_ids: evaluation = await evaluation_service.create_new_evaluation( @@ -141,7 +136,6 @@ async def create_evaluation( evaluation_id=evaluation.id, rate_limit_config=payload.rate_limit.dict(), lm_providers_keys=payload.lm_providers_keys, - correct_answer_column=correct_answer_column, ) evaluations.append(evaluation) diff --git a/agenta-backend/agenta_backend/services/db_manager.py b/agenta-backend/agenta_backend/services/db_manager.py index acf8c358cb..dc813026c3 100644 --- a/agenta-backend/agenta_backend/services/db_manager.py +++ b/agenta-backend/agenta_backend/services/db_manager.py @@ -59,6 +59,7 @@ ) from agenta_backend.models.db_models import ( ConfigDB, + CorrectAnswer, TemplateDB, AggregatedResult, AppVariantRevisionsDB, @@ -1907,7 +1908,7 @@ async def create_new_evaluation_scenario( variant_id: str, inputs: List[EvaluationScenarioInputDB], outputs: List[EvaluationScenarioOutputDB], - correct_answer: Optional[str], + correct_answers: Optional[List[CorrectAnswer]], is_pinned: Optional[bool], note: Optional[str], evaluators_configs: List[EvaluatorConfigDB], @@ -1925,7 +1926,7 @@ async def create_new_evaluation_scenario( variant_id=ObjectId(variant_id), inputs=inputs, outputs=outputs, - correct_answer=correct_answer, + correct_answers=correct_answers, is_pinned=is_pinned, note=note, evaluators_configs=evaluators_configs, diff --git a/agenta-backend/agenta_backend/services/evaluator_manager.py b/agenta-backend/agenta_backend/services/evaluator_manager.py index c86a4ef946..c4cc49ace3 100644 --- a/agenta-backend/agenta_backend/services/evaluator_manager.py +++ b/agenta-backend/agenta_backend/services/evaluator_manager.py @@ -17,6 +17,7 @@ from agenta_backend.models.converters import evaluator_config_db_to_pydantic from agenta_backend.resources.evaluators.evaluators import get_all_evaluators from agenta_backend.models.api.evaluation_model import Evaluator, EvaluatorConfig +from agenta_backend.resources.evaluators import evaluators def get_evaluators() -> Optional[List[Evaluator]]: @@ -79,6 +80,7 @@ async def create_evaluator_config( EvaluatorConfigDB: The newly created evaluator configuration object. """ app = await db_manager.fetch_app_by_id(app_id) + evaluator_config = await db_manager.create_evaluator_config( app=app, organization=app.organization if isCloudEE() else None, # noqa, @@ -139,13 +141,22 @@ async def create_ready_to_use_evaluators(app: AppDB): Returns: Nothing. The function works by side effect, modifying the database. """ - evaluators = get_evaluators() - direct_use_evaluators = [ - evaluator for evaluator in evaluators if evaluator.get("direct_use") + evaluator for evaluator in get_evaluators() if evaluator.get("direct_use") ] for evaluator in direct_use_evaluators: + settings_values = { + setting_name: setting.get("default") + for setting_name, setting in evaluator.get("settings_template", {}).items() + if setting.get("ground_truth_key") is True and setting.get("default", "") + } + + for setting_name, default_value in settings_values.items(): + assert ( + default_value != "" + ), f"Default value for ground truth key '{setting_name}' in Evaluator is empty" + await db_manager.create_evaluator_config( app=app, organization=app.organization if isCloudEE() else None, # noqa, @@ -153,7 +164,7 @@ async def create_ready_to_use_evaluators(app: AppDB): user=app.user, name=evaluator["name"], evaluator_key=evaluator["key"], - settings_values={}, + settings_values=settings_values, ) diff --git a/agenta-backend/agenta_backend/services/evaluators_service.py b/agenta-backend/agenta_backend/services/evaluators_service.py index 6a8219e056..d73a4229d9 100644 --- a/agenta-backend/agenta_backend/services/evaluators_service.py +++ b/agenta-backend/agenta_backend/services/evaluators_service.py @@ -1,81 +1,96 @@ -import re import json +import logging +import re +from typing import Any, Dict, List, Tuple + import httpx -from typing import Any, Dict, Tuple +from openai import OpenAI -from agenta_backend.services.security import sandbox from agenta_backend.models.db_models import Error, Result - -from langchain.llms import OpenAI -from langchain.chains import LLMChain -from langchain.prompts import PromptTemplate -import logging +from agenta_backend.services.security import sandbox logger = logging.getLogger(__name__) logger.setLevel(logging.DEBUG) +def get_correct_answer( + data_point: Dict[str, Any], settings_values: Dict[str, Any] +) -> Any: + """ + Helper function to retrieve the correct answer from the data point based on the settings values. + + Args: + data_point (Dict[str, Any]): The data point containing the correct answer. + settings_values (Dict[str, Any]): The settings values containing the key for the correct answer. + + Returns: + Any: The correct answer from the data point. + + Raises: + ValueError: If the correct answer key is not provided or not found in the data point. + """ + correct_answer_key = settings_values.get("correct_answer_key") + if correct_answer_key is None: + raise ValueError("No correct answer keys provided.") + if correct_answer_key not in data_point: + raise ValueError( + f"Correct answer column '{correct_answer_key}' not found in the test set." + ) + return data_point[correct_answer_key] + + def auto_exact_match( - inputs: Dict[str, Any], + inputs: Dict[str, Any], # pylint: disable=unused-argument output: str, - correct_answer: str, - app_params: Dict[str, Any], + data_point: Dict[str, Any], # pylint: disable=unused-argument + app_params: Dict[str, Any], # pylint: disable=unused-argument settings_values: Dict[str, Any], - lm_providers_keys: Dict[str, Any], + lm_providers_keys: Dict[str, Any], # pylint: disable=unused-argument ) -> Result: + """ + Evaluator function to determine if the output exactly matches the correct answer. + + Args: + inputs (Dict[str, Any]): The inputs for the evaluation. + output (str): The output generated by the model. + data_point (Dict[str, Any]): The data point containing the correct answer. + app_params (Dict[str, Any]): The application parameters. + settings_values (Dict[str, Any]): The settings values containing the key for the correct answer. + lm_providers_keys (Dict[str, Any]): The language model provider keys. + + Returns: + Result: A Result object containing the evaluation result. + """ try: + correct_answer = get_correct_answer(data_point, settings_values) exact_match = True if output == correct_answer else False result = Result(type="bool", value=exact_match) return result - except Exception as e: + except ValueError as e: return Result( type="error", value=None, error=Error( - message="Error during Auto Exact Match evaluation", stacktrace=str(e) + message=str(e), ), ) - - -def auto_similarity_match( - inputs: Dict[str, Any], - output: str, - correct_answer: str, - app_params: Dict[str, Any], - settings_values: Dict[str, Any], - lm_providers_keys: Dict[str, Any], -) -> Result: - try: - set1 = set(output.split()) - set2 = set(correct_answer.split()) - intersect = set1.intersection(set2) - union = set1.union(set2) - - similarity = len(intersect) / len(union) - - is_similar = ( - True if similarity > settings_values["similarity_threshold"] else False - ) - result = Result(type="bool", value=is_similar) - return result - except Exception as e: + except Exception as e: # pylint: disable=broad-except return Result( type="error", value=None, error=Error( - message="Error during Auto Similarity Match evaluation", - stacktrace=str(e), + message="Error during Auto Exact Match evaluation", stacktrace=str(e) ), ) def auto_regex_test( - inputs: Dict[str, Any], + inputs: Dict[str, Any], # pylint: disable=unused-argument output: str, - correct_answer: str, - app_params: Dict[str, Any], + data_point: Dict[str, Any], # pylint: disable=unused-argument + app_params: Dict[str, Any], # pylint: disable=unused-argument settings_values: Dict[str, Any], - lm_providers_keys: Dict[str, Any], + lm_providers_keys: Dict[str, Any], # pylint: disable=unused-argument ) -> Result: try: re_pattern = re.compile(settings_values["regex_pattern"], re.IGNORECASE) @@ -83,7 +98,7 @@ def auto_regex_test( bool(re_pattern.search(output)) == settings_values["regex_should_match"] ) return Result(type="bool", value=result) - except Exception as e: + except Exception as e: # pylint: disable=broad-except return Result( type="error", value=None, @@ -94,31 +109,42 @@ def auto_regex_test( def field_match_test( - inputs: Dict[str, Any], + inputs: Dict[str, Any], # pylint: disable=unused-argument output: str, - correct_answer: str, - app_params: Dict[str, Any], + data_point: Dict[str, Any], + app_params: Dict[str, Any], # pylint: disable=unused-argument settings_values: Dict[str, Any], - lm_providers_keys: Dict[str, Any], + lm_providers_keys: Dict[str, Any], # pylint: disable=unused-argument ) -> Result: try: + correct_answer = get_correct_answer(data_point, settings_values) output_json = json.loads(output) result = output_json[settings_values["json_field"]] == correct_answer return Result(type="bool", value=result) - except Exception as e: - logging.debug("Field Match Test Failed because of Error: " + str(e)) + except ValueError as e: + return Result( + type="error", + value=None, + error=Error( + message=str(e), + ), + ) + except Exception as e: # pylint: disable=broad-except + logging.debug("Field Match Test Failed because of Error: %s", str(e)) return Result(type="bool", value=False) def auto_webhook_test( inputs: Dict[str, Any], output: str, - correct_answer: str, - app_params: Dict[str, Any], + data_point: Dict[str, Any], + app_params: Dict[str, Any], # pylint: disable=unused-argument settings_values: Dict[str, Any], - lm_providers_keys: Dict[str, Any], + lm_providers_keys: Dict[str, Any], # pylint: disable=unused-argument ) -> Result: try: + correct_answer = get_correct_answer(data_point, settings_values) + with httpx.Client() as client: payload = { "correct_answer": correct_answer, @@ -146,6 +172,14 @@ def auto_webhook_test( ), ) return Result(type="number", value=score) + except ValueError as e: + return Result( + type="error", + value=None, + error=Error( + message=str(e), + ), + ) except httpx.HTTPError as e: return Result( type="error", @@ -155,7 +189,7 @@ def auto_webhook_test( stacktrace=str(e), ), ) - except Exception as e: + except Exception as e: # pylint: disable=broad-except return Result( type="error", value=None, @@ -168,21 +202,21 @@ def auto_webhook_test( def auto_custom_code_run( inputs: Dict[str, Any], output: str, - correct_answer: str, + data_point: Dict[str, Any], app_params: Dict[str, Any], settings_values: Dict[str, Any], - lm_providers_keys: Dict[str, Any], + lm_providers_keys: Dict[str, Any], # pylint: disable=unused-argument ) -> Result: try: result = sandbox.execute_code_safely( app_params=app_params, inputs=inputs, output=output, - correct_answer=correct_answer, + data_point=data_point, code=settings_values["code"], ) return Result(type="number", value=result) - except Exception as e: + except Exception as e: # pylint: disable=broad-except return Result( type="error", value=None, @@ -195,31 +229,28 @@ def auto_custom_code_run( def auto_ai_critique( inputs: Dict[str, Any], output: str, - correct_answer: str, + data_point: Dict[str, Any], app_params: Dict[str, Any], settings_values: Dict[str, Any], lm_providers_keys: Dict[str, Any], -) -> str: +) -> Result: """ Evaluate a response using an AI critique based on provided inputs, output, correct answer, app parameters, and settings. Args: inputs (Dict[str, Any]): Input parameters for the LLM app variant. output (str): The output of the LLM app variant. - correct_answer (str): Correct answer for evaluation. + correct_answer_key (str): The key name of the correct answer in the datapoint. app_params (Dict[str, Any]): Application parameters. settings_values (Dict[str, Any]): Settings for the evaluation. lm_providers_keys (Dict[str, Any]): Keys for language model providers. Returns: - str: Evaluation result. + Result: Evaluation result. """ try: - llm = OpenAI( - openai_api_key=lm_providers_keys["OPENAI_API_KEY"], - temperature=0.8, - model="gpt-3.5-turbo-instruct", - ) + correct_answer = get_correct_answer(data_point, settings_values) + openai_api_key = lm_providers_keys["OPENAI_API_KEY"] chain_run_args = { "llm_app_prompt_template": app_params.get("prompt_user", ""), @@ -230,18 +261,21 @@ def auto_ai_critique( for key, value in inputs.items(): chain_run_args[key] = value - prompt = PromptTemplate( - input_variables=list( - chain_run_args.keys() - ), # Use the keys from chain_run_args - template=settings_values["prompt_template"], + prompt_template = settings_values["prompt_template"] + messages = [ + {"role": "system", "content": prompt_template}, + {"role": "user", "content": str(chain_run_args)}, + ] + + client = OpenAI(api_key=openai_api_key) + response = client.chat.completions.create( + model="gpt-3.5-turbo", messages=messages, temperature=0.8 ) - chain = LLMChain(llm=llm, prompt=prompt) - evaluation_output = chain.run(**chain_run_args) + evaluation_output = response.choices[0].message["content"].strip() - return Result(type="text", value=evaluation_output.strip()) - except Exception as e: + return Result(type="text", value=evaluation_output) + except Exception as e: # pylint: disable=broad-except return Result( type="error", value=None, @@ -250,12 +284,12 @@ def auto_ai_critique( def auto_starts_with( - inputs: Dict[str, Any], + inputs: Dict[str, Any], # pylint: disable=unused-argument output: str, - correct_answer: str, - app_params: Dict[str, Any], + data_point: Dict[str, Any], # pylint: disable=unused-argument + app_params: Dict[str, Any], # pylint: disable=unused-argument settings_values: Dict[str, Any], - lm_providers_keys: Dict[str, Any], + lm_providers_keys: Dict[str, Any], # pylint: disable=unused-argument ) -> Result: try: prefix = settings_values.get("prefix", "") @@ -267,7 +301,7 @@ def auto_starts_with( result = Result(type="bool", value=output.startswith(prefix)) return result - except Exception as e: + except Exception as e: # pylint: disable=broad-except return Result( type="error", value=None, @@ -278,12 +312,12 @@ def auto_starts_with( def auto_ends_with( - inputs: Dict[str, Any], + inputs: Dict[str, Any], # pylint: disable=unused-argument output: str, - correct_answer: str, + data_point: Dict[str, Any], # pylint: disable=unused-argument app_params: Dict[str, Any], settings_values: Dict[str, Any], - lm_providers_keys: Dict[str, Any], + lm_providers_keys: Dict[str, Any], # pylint: disable=unused-argument ) -> Result: try: suffix = settings_values.get("suffix", "") @@ -295,7 +329,7 @@ def auto_ends_with( result = Result(type="bool", value=output.endswith(suffix)) return result - except Exception as e: + except Exception as e: # pylint: disable=broad-except return Result( type="error", value=None, @@ -304,12 +338,12 @@ def auto_ends_with( def auto_contains( - inputs: Dict[str, Any], + inputs: Dict[str, Any], # pylint: disable=unused-argument output: str, - correct_answer: str, - app_params: Dict[str, Any], + data_point: Dict[str, Any], # pylint: disable=unused-argument + app_params: Dict[str, Any], # pylint: disable=unused-argument settings_values: Dict[str, Any], - lm_providers_keys: Dict[str, Any], + lm_providers_keys: Dict[str, Any], # pylint: disable=unused-argument ) -> Result: try: substring = settings_values.get("substring", "") @@ -321,7 +355,7 @@ def auto_contains( result = Result(type="bool", value=substring in output) return result - except Exception as e: + except Exception as e: # pylint: disable=broad-except return Result( type="error", value=None, @@ -330,12 +364,12 @@ def auto_contains( def auto_contains_any( - inputs: Dict[str, Any], + inputs: Dict[str, Any], # pylint: disable=unused-argument output: str, - correct_answer: str, - app_params: Dict[str, Any], + data_point: Dict[str, Any], # pylint: disable=unused-argument + app_params: Dict[str, Any], # pylint: disable=unused-argument settings_values: Dict[str, Any], - lm_providers_keys: Dict[str, Any], + lm_providers_keys: Dict[str, Any], # pylint: disable=unused-argument ) -> Result: try: substrings_str = settings_values.get("substrings", "") @@ -350,7 +384,7 @@ def auto_contains_any( type="bool", value=any(substring in output for substring in substrings) ) return result - except Exception as e: + except Exception as e: # pylint: disable=broad-except return Result( type="error", value=None, @@ -361,12 +395,12 @@ def auto_contains_any( def auto_contains_all( - inputs: Dict[str, Any], + inputs: Dict[str, Any], # pylint: disable=unused-argument output: str, - correct_answer: str, - app_params: Dict[str, Any], + data_point: Dict[str, Any], # pylint: disable=unused-argument + app_params: Dict[str, Any], # pylint: disable=unused-argument settings_values: Dict[str, Any], - lm_providers_keys: Dict[str, Any], + lm_providers_keys: Dict[str, Any], # pylint: disable=unused-argument ) -> Result: try: substrings_str = settings_values.get("substrings", "") @@ -381,7 +415,7 @@ def auto_contains_all( type="bool", value=all(substring in output for substring in substrings) ) return result - except Exception as e: + except Exception as e: # pylint: disable=broad-except return Result( type="error", value=None, @@ -392,12 +426,12 @@ def auto_contains_all( def auto_contains_json( - inputs: Dict[str, Any], + inputs: Dict[str, Any], # pylint: disable=unused-argument output: str, - correct_answer: str, - app_params: Dict[str, Any], - settings_values: Dict[str, Any], - lm_providers_keys: Dict[str, Any], + data_point: Dict[str, Any], # pylint: disable=unused-argument + app_params: Dict[str, Any], # pylint: disable=unused-argument + settings_values: Dict[str, Any], # pylint: disable=unused-argument + lm_providers_keys: Dict[str, Any], # pylint: disable=unused-argument ) -> Result: try: try: @@ -411,7 +445,7 @@ def auto_contains_json( contains_json = False return Result(type="bool", value=contains_json) - except Exception as e: + except Exception as e: # pylint: disable=broad-except return Result( type="error", value=None, @@ -423,7 +457,7 @@ def auto_contains_json( def levenshtein_distance(s1, s2): if len(s1) < len(s2): - return levenshtein_distance(s2, s1) + return levenshtein_distance(s2, s1) # pylint: disable=arguments-out-of-order if len(s2) == 0: return len(s1) @@ -442,14 +476,16 @@ def levenshtein_distance(s1, s2): def auto_levenshtein_distance( - inputs: Dict[str, Any], + inputs: Dict[str, Any], # pylint: disable=unused-argument output: str, - correct_answer: str, - app_params: Dict[str, Any], + data_point: Dict[str, Any], + app_params: Dict[str, Any], # pylint: disable=unused-argument settings_values: Dict[str, Any], - lm_providers_keys: Dict[str, Any], + lm_providers_keys: Dict[str, Any], # pylint: disable=unused-argument ) -> Result: try: + correct_answer = get_correct_answer(data_point, settings_values) + distance = levenshtein_distance(output, correct_answer) if "threshold" in settings_values: @@ -459,7 +495,15 @@ def auto_levenshtein_distance( return Result(type="number", value=distance) - except Exception as e: + except ValueError as e: + return Result( + type="error", + value=None, + error=Error( + message=str(e), + ), + ) + except Exception as e: # pylint: disable=broad-except return Result( type="error", value=None, @@ -470,28 +514,98 @@ def auto_levenshtein_distance( ) +def auto_similarity_match( + inputs: Dict[str, Any], + output: str, + data_point: Dict[str, Any], + app_params: Dict[str, Any], + settings_values: Dict[str, Any], + lm_providers_keys: Dict[str, Any], +) -> Result: + try: + correct_answer = get_correct_answer(data_point, settings_values) + set1 = set(output.split()) + set2 = set(correct_answer.split()) + intersect = set1.intersection(set2) + union = set1.union(set2) + + similarity = len(intersect) / len(union) + + is_similar = ( + True if similarity > settings_values["similarity_threshold"] else False + ) + result = Result(type="bool", value=is_similar) + return result + except ValueError as e: + return Result( + type="error", + value=None, + error=Error( + message=str(e), + ), + ) + except Exception as e: # pylint: disable=broad-except + return Result( + type="error", + value=None, + error=Error( + message="Error during Auto Similarity Match evaluation", + stacktrace=str(e), + ), + ) + + +EVALUATOR_FUNCTIONS = { + "auto_exact_match": auto_exact_match, + "auto_regex_test": auto_regex_test, + "field_match_test": field_match_test, + "auto_webhook_test": auto_webhook_test, + "auto_custom_code_run": auto_custom_code_run, + "auto_ai_critique": auto_ai_critique, + "auto_starts_with": auto_starts_with, + "auto_ends_with": auto_ends_with, + "auto_contains": auto_contains, + "auto_contains_any": auto_contains_any, + "auto_contains_all": auto_contains_all, + "auto_contains_json": auto_contains_json, + "auto_levenshtein_distance": auto_levenshtein_distance, + "auto_similarity_match": auto_similarity_match, +} + + def evaluate( evaluator_key: str, inputs: Dict[str, Any], output: str, - correct_answer: str, + data_point: Dict[str, Any], app_params: Dict[str, Any], settings_values: Dict[str, Any], lm_providers_keys: Dict[str, Any], ) -> Result: - evaluation_function = globals().get(evaluator_key, None) + evaluation_function = EVALUATOR_FUNCTIONS.get(evaluator_key, None) if not evaluation_function: - raise ValueError(f"Evaluation method '{evaluator_key}' not found.") + return Result( + type="error", + value=None, + error=Error( + message=f"Evaluation method '{evaluator_key}' not found.", + ), + ) try: return evaluation_function( inputs, output, - correct_answer, + data_point, app_params, settings_values, lm_providers_keys, ) except Exception as exc: - raise RuntimeError( - f"Error occurred while running {evaluator_key} evaluation. Exception: {str(exc)}" + return Result( + type="error", + value=None, + error=Error( + message="Error occurred while running {evaluator_key} evaluation. ", + stacktrace=str(exc), + ), ) diff --git a/agenta-backend/agenta_backend/tasks/evaluations.py b/agenta-backend/agenta_backend/tasks/evaluations.py index 5dd602de6e..15a055b825 100644 --- a/agenta-backend/agenta_backend/tasks/evaluations.py +++ b/agenta-backend/agenta_backend/tasks/evaluations.py @@ -3,20 +3,23 @@ import asyncio import logging import traceback - from typing import Any, Dict, List + from celery import shared_task, states from agenta_backend.utils.common import isCloudEE from agenta_backend.models.db_engine import DBEngine -from agenta_backend.services import evaluators_service, llm_apps_service - -from agenta_backend.models.api.evaluation_model import ( - EvaluationStatusEnum, +from agenta_backend.services import ( + evaluators_service, + llm_apps_service, + deployment_manager, + aggregation_service, ) +from agenta_backend.models.api.evaluation_model import EvaluationStatusEnum from agenta_backend.models.db_models import ( AggregatedResult, AppDB, + CorrectAnswer, EvaluationScenarioInputDB, EvaluationScenarioOutputDB, EvaluationScenarioResult, @@ -24,12 +27,6 @@ Error, Result, ) -from agenta_backend.services import ( - evaluators_service, - llm_apps_service, - deployment_manager, - aggregation_service, -) from agenta_backend.services.db_manager import ( create_new_evaluation_scenario, fetch_app_by_id, @@ -43,23 +40,28 @@ EvaluationScenarioResult, check_if_evaluation_contains_failed_evaluation_scenarios, ) +from agenta_backend.services.evaluator_manager import get_evaluators if isCloudEE(): from agenta_backend.commons.models.db_models import AppDB_ as AppDB else: from agenta_backend.models.db_models import AppDB -from agenta_backend.models.db_models import ( - Result, - AggregatedResult, - EvaluationScenarioResult, - EvaluationScenarioInputDB, - EvaluationScenarioOutputDB, -) # Set logger logger = logging.getLogger(__name__) logger.setLevel(logging.DEBUG) +# Fetch all evaluators and precompute ground truth keys +all_evaluators = get_evaluators() +ground_truth_keys_dict = { + evaluator["key"]: [ + key + for key, value in evaluator.get("settings_template", {}).items() + if value.get("ground_truth_key") is True + ] + for evaluator in all_evaluators +} + @shared_task(queue="agenta_backend.tasks.evaluations.evaluate", bind=True) def evaluate( @@ -71,19 +73,19 @@ def evaluate( evaluation_id: str, rate_limit_config: Dict[str, int], lm_providers_keys: Dict[str, Any], - correct_answer_column: str, ): """ - Evaluate function that performs the evaluation of an app variant using the provided evaluators and testset. - Saves the results in the Database + Evaluates an app variant using the provided evaluators and testset, and saves the results in the database. Args: + self: The task instance. app_id (str): The ID of the app. variant_id (str): The ID of the app variant. evaluators_config_ids (List[str]): The IDs of the evaluators configurations to be used. testset_id (str): The ID of the testset. - rate_limit_config (Dict[str,int]): See LLMRunRateLimit - correct_answer_column (str): The name of the column in the testset that contains the correct answer. + evaluation_id (str): The ID of the evaluation. + rate_limit_config (Dict[str, int]): Configuration for rate limiting. + lm_providers_keys (Dict[str, Any]): Keys for language model providers. Returns: None @@ -178,11 +180,6 @@ def evaluate( ) for evaluator_config_db in evaluator_config_dbs ] - correct_answer = ( - data_point[correct_answer_column] - if correct_answer_column in data_point - else "" - ) loop.run_until_complete( create_new_evaluation_scenario( @@ -195,7 +192,7 @@ def evaluate( inputs=inputs, is_pinned=False, note="", - correct_answer=correct_answer, + correct_answer=None, outputs=[ EvaluationScenarioOutputDB( result=Result( @@ -214,27 +211,29 @@ def evaluate( continue # 3. We evaluate - evaluators_results: [EvaluationScenarioResult] = [] + evaluators_results: List[EvaluationScenarioResult] = [] + + # Loop over each evaluator configuration to gather the correct answers and evaluate + ground_truth_column_names = [] for evaluator_config_db in evaluator_config_dbs: + ground_truth_keys = ground_truth_keys_dict.get( + evaluator_config_db.evaluator_key, [] + ) + ground_truth_column_names.extend( + evaluator_config_db.settings_values.get(key, "") + for key in ground_truth_keys + ) logger.debug(f"Evaluating with evaluator: {evaluator_config_db}") - if correct_answer_column in data_point: - result = evaluators_service.evaluate( - evaluator_key=evaluator_config_db.evaluator_key, - output=app_output.result.value, - correct_answer=data_point[correct_answer_column], - settings_values=evaluator_config_db.settings_values, - app_params=app_variant_parameters, - inputs=data_point, - lm_providers_keys=lm_providers_keys, - ) - else: - result = Result( - type="error", - value=None, - error=Error( - message=f"No {correct_answer_column} column in test set" - ), - ) + + result = evaluators_service.evaluate( + evaluator_key=evaluator_config_db.evaluator_key, + output=app_output.result.value, + data_point=data_point, + settings_values=evaluator_config_db.settings_values, + app_params=app_variant_parameters, + inputs=data_point, + lm_providers_keys=lm_providers_keys, + ) # Update evaluators aggregated data evaluator_results: List[Result] = evaluators_aggregated_data[ @@ -249,12 +248,17 @@ def evaluate( logger.debug(f"Result: {result_object}") evaluators_results.append(result_object) + all_correct_answers = [ + CorrectAnswer( + key=ground_truth_column_name, + value=data_point[ground_truth_column_name], + ) + if ground_truth_column_name in data_point + else CorrectAnswer(key=ground_truth_column_name, value="") + for ground_truth_column_name in ground_truth_column_names + ] # 4. We save the result of the eval scenario in the db - correct_answer = ( - data_point[correct_answer_column] - if correct_answer_column in data_point - else "" - ) + loop.run_until_complete( create_new_evaluation_scenario( user=app.user, @@ -264,7 +268,7 @@ def evaluate( inputs=inputs, is_pinned=False, note="", - correct_answer=correct_answer, + correct_answers=all_correct_answers, outputs=[ EvaluationScenarioOutputDB( result=Result(type="text", value=app_output.result.value), diff --git a/agenta-backend/agenta_backend/tests/unit/test_evaluators.py b/agenta-backend/agenta_backend/tests/unit/test_evaluators.py index f76dd9e6fb..ff70bbfd9b 100644 --- a/agenta-backend/agenta_backend/tests/unit/test_evaluators.py +++ b/agenta-backend/agenta_backend/tests/unit/test_evaluators.py @@ -12,17 +12,54 @@ @pytest.mark.parametrize( - "output, prefix, case_sensitive, expected", + "output, settings_values, expected", [ - ("Hello world", "He", True, True), - ("hello world", "He", False, True), - ("Hello world", "he", False, True), - ("Hello world", "world", True, False), + ( + "Hello world", + { + "prefix": "He", + "case_sensitive": True, + "correct_answer_keys": ["correct_answer"], + }, + True, + ), + ( + "hello world", + { + "prefix": "He", + "case_sensitive": False, + "correct_answer_keys": ["correct_answer"], + }, + True, + ), + ( + "Hello world", + { + "prefix": "he", + "case_sensitive": False, + "correct_answer_keys": ["correct_answer"], + }, + True, + ), + ( + "Hello world", + { + "prefix": "world", + "case_sensitive": True, + "correct_answer_keys": ["correct_answer"], + }, + False, + ), ], ) -def test_auto_starts_with(output, prefix, case_sensitive, expected): +def test_auto_starts_with(output, settings_values, expected): result = auto_starts_with( - {}, output, "", {}, {"prefix": prefix, "case_sensitive": case_sensitive}, {} + inputs={}, + output=output, + data_point={}, + app_params={}, + settings_values=settings_values, + lm_providers_keys={}, ) assert result.value == expected @@ -41,7 +78,12 @@ def test_auto_starts_with(output, prefix, case_sensitive, expected): ) def test_auto_ends_with(output, suffix, case_sensitive, expected): result = auto_ends_with( - {}, output, "", {}, {"suffix": suffix, "case_sensitive": case_sensitive}, {} + {}, + output, + {}, + {}, + {"suffix": suffix, "case_sensitive": case_sensitive}, + {}, ) assert result.value == expected @@ -61,7 +103,7 @@ def test_auto_contains(output, substring, case_sensitive, expected): result = auto_contains( {}, output, - "", + {}, {}, {"substring": substring, "case_sensitive": case_sensitive}, {}, @@ -85,7 +127,7 @@ def test_auto_contains_any(output, substrings, case_sensitive, expected): result = auto_contains_any( {}, output, - "", + {}, {}, {"substrings": substrings, "case_sensitive": case_sensitive}, {}, @@ -109,7 +151,7 @@ def test_auto_contains_all(output, substrings, case_sensitive, expected): result = auto_contains_all( {}, output, - "", + {}, {}, {"substrings": substrings, "case_sensitive": case_sensitive}, {}, @@ -128,24 +170,58 @@ def test_auto_contains_all(output, substrings, case_sensitive, expected): ], ) def test_auto_contains_json(output, expected): - result = auto_contains_json({}, output, "", {}, {}, {}) + result = auto_contains_json({}, output, {}, {}, {}, {}) assert result.value == expected @pytest.mark.parametrize( - "output, correct_answer, threshold, expected", + "output, data_point, settings_values, expected", [ - ("hello world", "hello world", 5, True), - ("hello world", "hola mundo", 5, False), - ("hello world", "hello world!", 2, True), - ("hello world", "hello wor", 10, True), - ("hello world", "hello worl", None, 1), - ("hello world", "helo world", None, 1), + ( + "hello world", + {"correct_answer": "hello world"}, + {"threshold": 5, "correct_answer_key": "correct_answer"}, + True, + ), + ( + "hello world", + {"correct_answer": "hola mundo"}, + {"threshold": 5, "correct_answer_key": "correct_answer"}, + False, + ), + ( + "hello world", + {"correct_answer": "hello world!"}, + {"threshold": 2, "correct_answer_key": "correct_answer"}, + True, + ), + ( + "hello world", + {"correct_answer": "hello wor"}, + {"threshold": 10, "correct_answer_key": "correct_answer"}, + True, + ), + ( + "hello world", + {"correct_answer": "hello worl"}, + {"correct_answer_key": "correct_answer"}, + 1, + ), + ( + "hello world", + {"correct_answer": "helo world"}, + {"correct_answer_key": "correct_answer"}, + 1, + ), ], ) -def test_auto_levenshtein_distance(output, correct_answer, threshold, expected): - settings_values = {"threshold": threshold} if threshold is not None else {} +def test_auto_levenshtein_distance(output, data_point, settings_values, expected): result = auto_levenshtein_distance( - {}, output, correct_answer, {}, settings_values, {} + inputs={}, + output=output, + data_point=data_point, + app_params={}, + settings_values=settings_values, + lm_providers_keys={}, ) assert result.value == expected diff --git a/agenta-backend/agenta_backend/tests/variants_main_router/test_variant_evaluators_router.py b/agenta-backend/agenta_backend/tests/variants_main_router/test_variant_evaluators_router.py index e45b17fbda..9ff8ad60b2 100644 --- a/agenta-backend/agenta_backend/tests/variants_main_router/test_variant_evaluators_router.py +++ b/agenta-backend/agenta_backend/tests/variants_main_router/test_variant_evaluators_router.py @@ -59,6 +59,7 @@ async def test_create_auto_exact_match_evaluator_config( app = await AppDB.find_one(AppDB.app_name == APP_NAME) payload = auto_exact_match_evaluator_config payload["app_id"] = str(app.id) + payload["settings_values"]["correct_answer_key"] = "correct_answer" response = await test_client.post( f"{BACKEND_API_HOST}/evaluators/configs/", json=payload, timeout=timeout @@ -75,6 +76,7 @@ async def test_create_auto_similarity_match_evaluator_config( app = await AppDB.find_one(AppDB.app_name == APP_NAME) payload = auto_similarity_match_evaluator_config payload["app_id"] = str(app.id) + payload["settings_values"]["correct_answer_key"] = "correct_answer" response = await test_client.post( f"{BACKEND_API_HOST}/evaluators/configs/", json=payload, timeout=timeout @@ -92,6 +94,7 @@ async def test_create_auto_regex_test_evaluator_config( payload = auto_regex_test_evaluator_config payload["app_id"] = str(app.id) payload["settings_values"]["regex_pattern"] = "^ig\\d{3}$" + payload["settings_values"]["correct_answer_key"] = "correct_answer" response = await test_client.post( f"{BACKEND_API_HOST}/evaluators/configs/", json=payload, timeout=timeout @@ -108,6 +111,7 @@ async def test_create_auto_webhook_test_evaluator_config( app = await AppDB.find_one(AppDB.app_name == APP_NAME) payload = auto_webhook_test_evaluator_config payload["app_id"] = str(app.id) + payload["settings_values"]["correct_answer_key"] = "correct_answer" response = await test_client.post( f"{BACKEND_API_HOST}/evaluators/configs/", json=payload, timeout=timeout @@ -124,6 +128,7 @@ async def test_create_auto_ai_critique_evaluator_config( app = await AppDB.find_one(AppDB.app_name == APP_NAME) payload = auto_ai_critique_evaluator_config payload["app_id"] = str(app.id) + payload["settings_values"]["correct_answer_key"] = "correct_answer" response = await test_client.post( f"{BACKEND_API_HOST}/evaluators/configs/", json=payload, timeout=timeout @@ -145,7 +150,31 @@ async def test_get_evaluator_configs(): @pytest.mark.asyncio -async def test_create_evaluation(): +async def test_create_evaluation_auto_exact_match(): + await create_evaluation_with_evaluator("auto_exact_match_evaluator_config") + + +@pytest.mark.asyncio +async def test_create_evaluation_auto_similarity_match(): + await create_evaluation_with_evaluator("auto_similarity_match_evaluator_config") + + +@pytest.mark.asyncio +async def test_create_evaluation_auto_regex_test(): + await create_evaluation_with_evaluator("auto_regex_test_evaluator_config") + + +@pytest.mark.asyncio +async def test_create_evaluation_auto_webhook_test(): + await create_evaluation_with_evaluator("auto_webhook_test_evaluator_config") + + +@pytest.mark.asyncio +async def test_create_evaluation_auto_ai_critique(): + await create_evaluation_with_evaluator("auto_ai_critique_evaluator_config") + + +async def create_evaluation_with_evaluator(evaluator_config_name): # Fetch app, app_variant and testset app = await AppDB.find_one(AppDB.app_name == APP_NAME) app_variant = await AppVariantDB.find_one(AppVariantDB.app.id == app.id) @@ -174,7 +203,8 @@ async def test_create_evaluation(): list_of_configs_ids = [] evaluator_configs = response.json() for evaluator_config in evaluator_configs: - list_of_configs_ids.append(evaluator_config["id"]) + if evaluator_config["evaluator_key"] == evaluator_config_name: + list_of_configs_ids.append(evaluator_config["id"]) # Update payload with list of configs ids payload["evaluators_configs"] = list_of_configs_ids @@ -196,20 +226,20 @@ async def test_create_evaluation(): ) assert response_data is not None + # Wait for evaluation to finish + evaluation_id = response_data["id"] + await wait_for_evaluation_to_finish(evaluation_id) + + # Fetch evaluation results + await fetch_evaluation_results(evaluation_id) -@pytest.mark.asyncio -async def test_fetch_evaluation_status(): - evaluations = ( - await EvaluationDB.find().to_list() - ) # will return only one in this case - evaluation = evaluations[0] - # Prepare and start short-polling request +async def wait_for_evaluation_to_finish(evaluation_id): max_attempts = 12 intervals = 5 # seconds for _ in range(max_attempts): response = await test_client.get( - f"{BACKEND_API_HOST}/evaluations/{str(evaluation.id)}/status/", + f"{BACKEND_API_HOST}/evaluations/{evaluation_id}/status/", timeout=timeout, ) response_data = response.json() @@ -223,21 +253,14 @@ async def test_fetch_evaluation_status(): ), f"Evaluation status did not become '{EvaluationStatusEnum.EVALUATION_FINISHED}' within the specified polling time" -@pytest.mark.asyncio -async def test_fetch_evaluation_results(): - evaluations = ( - await EvaluationDB.find().to_list() - ) # will return only one in this case - evaluation = evaluations[0] - +async def fetch_evaluation_results(evaluation_id): response = await test_client.get( - f"{BACKEND_API_HOST}/evaluations/{str(evaluation.id)}/results/", timeout=timeout + f"{BACKEND_API_HOST}/evaluations/{evaluation_id}/results/", timeout=timeout ) response_data = response.json() assert response.status_code == 200 - assert response_data["evaluation_id"] == str(evaluation.id) - assert len(response_data["results"]) == 7 + assert response_data["evaluation_id"] == evaluation_id @pytest.mark.asyncio diff --git a/agenta-backend/poetry.lock b/agenta-backend/poetry.lock index 468b8ca1e6..09fe882771 100644 --- a/agenta-backend/poetry.lock +++ b/agenta-backend/poetry.lock @@ -1,9 +1,10 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand. [[package]] name = "aioboto3" version = "12.4.0" description = "Async boto3 wrapper" +category = "main" optional = false python-versions = "<4.0,>=3.8" files = [ @@ -22,6 +23,7 @@ s3cse = ["cryptography (>=2.3.1)"] name = "aiobotocore" version = "2.12.3" description = "Async client for aws services using botocore and aiohttp" +category = "main" optional = false python-versions = ">=3.8" files = [ @@ -44,6 +46,7 @@ boto3 = ["boto3 (>=1.34.41,<1.34.70)"] name = "aiodocker" version = "0.21.0" description = "Docker API client for asyncio" +category = "main" optional = false python-versions = ">=3.6" files = [ @@ -59,6 +62,7 @@ typing-extensions = ">=3.6.5" name = "aiohttp" version = "3.9.5" description = "Async http client/server framework (asyncio)" +category = "main" optional = false python-versions = ">=3.8" files = [ @@ -155,6 +159,7 @@ speedups = ["Brotli", "aiodns", "brotlicffi"] name = "aioitertools" version = "0.11.0" description = "itertools and builtins for AsyncIO and mixed iterables" +category = "main" optional = false python-versions = ">=3.6" files = [ @@ -169,6 +174,7 @@ typing_extensions = {version = ">=4.0", markers = "python_version < \"3.10\""} name = "aiosignal" version = "1.3.1" description = "aiosignal: a list of registered asynchronous callbacks" +category = "main" optional = false python-versions = ">=3.7" files = [ @@ -183,6 +189,7 @@ frozenlist = ">=1.1.0" name = "aiosmtplib" version = "1.1.6" description = "asyncio SMTP client" +category = "main" optional = false python-versions = ">=3.5.2,<4.0.0" files = [ @@ -198,6 +205,7 @@ uvloop = ["uvloop (>=0.13,<0.15)"] name = "amqp" version = "5.2.0" description = "Low-level AMQP client for Python (fork of amqplib)." +category = "main" optional = false python-versions = ">=3.6" files = [ @@ -212,6 +220,7 @@ vine = ">=5.0.0,<6.0.0" name = "anyio" version = "3.7.1" description = "High level compatibility layer for multiple asynchronous event loop implementations" +category = "main" optional = false python-versions = ">=3.7" files = [ @@ -229,10 +238,23 @@ doc = ["Sphinx", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd- test = ["anyio[trio]", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"] trio = ["trio (<0.22)"] +[[package]] +name = "appdirs" +version = "1.4.4" +description = "A small Python module for determining appropriate platform-specific dirs, e.g. a \"user data dir\"." +category = "main" +optional = false +python-versions = "*" +files = [ + {file = "appdirs-1.4.4-py2.py3-none-any.whl", hash = "sha256:a841dacd6b99318a741b166adb07e19ee71a274450e68237b4650ca1055ab128"}, + {file = "appdirs-1.4.4.tar.gz", hash = "sha256:7d5d0167b2b1ba821647616af46a749d1c653740dd0d2415100fe26e27afdf41"}, +] + [[package]] name = "asgiref" version = "3.8.1" description = "ASGI specs, helper code, and adapters" +category = "main" optional = false python-versions = ">=3.8" files = [ @@ -250,6 +272,7 @@ tests = ["mypy (>=0.800)", "pytest", "pytest-asyncio"] name = "async-timeout" version = "4.0.3" description = "Timeout context manager for asyncio programs" +category = "main" optional = false python-versions = ">=3.7" files = [ @@ -261,6 +284,7 @@ files = [ name = "asyncer" version = "0.0.2" description = "Asyncer, async and await, focused on developer experience." +category = "main" optional = false python-versions = ">=3.6.2,<4.0.0" files = [ @@ -275,6 +299,7 @@ anyio = ">=3.4.0,<4.0.0" name = "attrs" version = "23.2.0" description = "Classes Without Boilerplate" +category = "main" optional = false python-versions = ">=3.7" files = [ @@ -294,6 +319,7 @@ tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "p name = "backoff" version = "2.2.1" description = "Function decoration for backoff and retry" +category = "main" optional = false python-versions = ">=3.7,<4.0" files = [ @@ -305,6 +331,7 @@ files = [ name = "beanie" version = "1.26.0" description = "Asynchronous Python ODM for MongoDB" +category = "main" optional = false python-versions = "<4.0,>=3.7" files = [ @@ -329,6 +356,7 @@ test = ["asgi-lifespan (>=1.0.1)", "dnspython (>=2.1.0)", "fastapi (>=0.100)", " name = "billiard" version = "4.2.0" description = "Python multiprocessing fork with improvements and bugfixes" +category = "main" optional = false python-versions = ">=3.7" files = [ @@ -340,6 +368,7 @@ files = [ name = "boto3" version = "1.34.69" description = "The AWS SDK for Python" +category = "main" optional = false python-versions = ">=3.8" files = [ @@ -359,6 +388,7 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"] name = "botocore" version = "1.34.69" description = "Low-level, data-driven core of boto 3." +category = "main" optional = false python-versions = ">=3.8" files = [ @@ -381,6 +411,7 @@ crt = ["awscrt (==0.19.19)"] name = "cachetools" version = "5.3.3" description = "Extensible memoizing collections and decorators" +category = "main" optional = false python-versions = ">=3.7" files = [ @@ -392,6 +423,7 @@ files = [ name = "celery" version = "5.4.0" description = "Distributed Task Queue." +category = "main" optional = false python-versions = ">=3.8" files = [ @@ -448,6 +480,7 @@ zstd = ["zstandard (==0.22.0)"] name = "certifi" version = "2024.2.2" description = "Python package for providing Mozilla's CA Bundle." +category = "main" optional = false python-versions = ">=3.6" files = [ @@ -459,6 +492,7 @@ files = [ name = "cffi" version = "1.16.0" description = "Foreign Function Interface for Python calling C code." +category = "main" optional = false python-versions = ">=3.8" files = [ @@ -523,6 +557,7 @@ pycparser = "*" name = "charset-normalizer" version = "3.3.2" description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet." +category = "main" optional = false python-versions = ">=3.7.0" files = [ @@ -622,6 +657,7 @@ files = [ name = "click" version = "8.1.7" description = "Composable command line interface toolkit" +category = "main" optional = false python-versions = ">=3.7" files = [ @@ -636,6 +672,7 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""} name = "click-didyoumean" version = "0.3.1" description = "Enables git-like *did-you-mean* feature in click" +category = "main" optional = false python-versions = ">=3.6.2" files = [ @@ -650,6 +687,7 @@ click = ">=7" name = "click-plugins" version = "1.1.1" description = "An extension module for click to enable registering CLI commands via setuptools entry-points." +category = "main" optional = false python-versions = "*" files = [ @@ -667,6 +705,7 @@ dev = ["coveralls", "pytest (>=3.6)", "pytest-cov", "wheel"] name = "click-repl" version = "0.3.0" description = "REPL plugin for Click" +category = "main" optional = false python-versions = ">=3.6" files = [ @@ -685,6 +724,7 @@ testing = ["pytest (>=7.2.1)", "pytest-cov (>=4.0.0)", "tox (>=4.4.3)"] name = "colorama" version = "0.4.6" description = "Cross-platform colored terminal text." +category = "main" optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7" files = [ @@ -696,6 +736,7 @@ files = [ name = "cryptography" version = "42.0.7" description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers." +category = "main" optional = false python-versions = ">=3.7" files = [ @@ -750,6 +791,7 @@ test-randomorder = ["pytest-randomly"] name = "dataclasses-json" version = "0.6.6" description = "Easily serialize dataclasses to and from JSON." +category = "main" optional = false python-versions = "<4.0,>=3.7" files = [ @@ -761,10 +803,56 @@ files = [ marshmallow = ">=3.18.0,<4.0.0" typing-inspect = ">=0.4.0,<1" +[[package]] +name = "datasets" +version = "2.19.1" +description = "HuggingFace community-driven open-source library of datasets" +category = "main" +optional = false +python-versions = ">=3.8.0" +files = [ + {file = "datasets-2.19.1-py3-none-any.whl", hash = "sha256:f7a78d15896f45004ccac1c298f3c7121f92f91f6f2bfbd4e4f210f827e6e411"}, + {file = "datasets-2.19.1.tar.gz", hash = "sha256:0df9ef6c5e9138cdb996a07385220109ff203c204245578b69cca905eb151d3a"}, +] + +[package.dependencies] +aiohttp = "*" +dill = ">=0.3.0,<0.3.9" +filelock = "*" +fsspec = {version = ">=2023.1.0,<=2024.3.1", extras = ["http"]} +huggingface-hub = ">=0.21.2" +multiprocess = "*" +numpy = ">=1.17" +packaging = "*" +pandas = "*" +pyarrow = ">=12.0.0" +pyarrow-hotfix = "*" +pyyaml = ">=5.1" +requests = ">=2.19.0" +tqdm = ">=4.62.1" +xxhash = "*" + +[package.extras] +apache-beam = ["apache-beam (>=2.26.0)"] +audio = ["librosa", "soundfile (>=0.12.1)"] +benchmarks = ["tensorflow (==2.12.0)", "torch (==2.0.1)", "transformers (==4.30.1)"] +dev = ["Pillow (>=6.2.1)", "absl-py", "apache-beam (>=2.26.0)", "elasticsearch (<8.0.0)", "faiss-cpu (>=1.6.4)", "jax (>=0.3.14)", "jaxlib (>=0.3.14)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "polars[timezone] (>=0.20.0)", "protobuf (<4.0.0)", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "ruff (>=0.3.0)", "s3fs", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "sqlalchemy", "tensorflow (>=2.6.0)", "tiktoken", "torch", "torch (>=2.0.0)", "transformers", "typing-extensions (>=4.6.1)", "zstandard"] +docs = ["s3fs", "tensorflow (>=2.6.0)", "torch", "transformers"] +jax = ["jax (>=0.3.14)", "jaxlib (>=0.3.14)"] +metrics-tests = ["Werkzeug (>=1.0.1)", "accelerate", "bert-score (>=0.3.6)", "jiwer", "langdetect", "mauve-text", "nltk", "requests-file (>=1.5.1)", "rouge-score", "sacrebleu", "sacremoses", "scikit-learn", "scipy", "sentencepiece", "seqeval", "six (>=1.15.0,<1.16.0)", "spacy (>=3.0.0)", "texttable 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a/agenta-backend/pyproject.toml b/agenta-backend/pyproject.toml index bb0be6a2ee..c52c5e7277 100644 --- a/agenta-backend/pyproject.toml +++ b/agenta-backend/pyproject.toml @@ -10,7 +10,7 @@ packages = [{include = "agenta_backend"}] python = "^3.9" fastapi = "^0.109.1" pydantic = "^1.10.7" -docker = "^6.1.1" +docker = "7.1.0" toml = "^0.10.2" uvicorn = "^0.22.0" sqlmodel = "^0.0.8" @@ -19,8 +19,6 @@ python-multipart = "^0.0.7" backoff = "^2.2.1" redis = "^4.6.0" aiodocker = "^0.21.0" -openai = "^0.27.8" -langchain = "^0.0.329" supertokens-python = "^0.15.1" sendgrid = "^6.10.0" restrictedpython = { version = "^6.2", python = ">=3.9,<3.12" } @@ -35,6 +33,8 @@ watchdog = {extras = ["watchmedo"], version = "^3.0.0"} beanie = "^1.25.0" newrelic = "^9.8.0" aioboto3 = "^12.4.0" +ragas = "^0.1.8" +openai = "^1.30.4" [tool.poetry.group.dev.dependencies] pytest = "^7.3.1" diff --git a/agenta-web/src/components/pages/evaluations/FilterColumns/FilterColumns.tsx b/agenta-web/src/components/pages/evaluations/FilterColumns/FilterColumns.tsx new file mode 100644 index 0000000000..884a43b15f --- /dev/null +++ b/agenta-web/src/components/pages/evaluations/FilterColumns/FilterColumns.tsx @@ -0,0 +1,88 @@ +import {JSSTheme} from "@/lib/Types" +import {CheckOutlined, DownOutlined} from "@ant-design/icons" +import {Button, Dropdown, Space} from "antd" +import {ItemType} from "antd/es/menu/hooks/useItems" +import React from "react" +import {createUseStyles} from "react-jss" +import {ColDef} from "ag-grid-community" + +const useStyles = createUseStyles((theme: JSSTheme) => ({ + dropdownMenu: { + "&>.ant-dropdown-menu-item": { + "& .anticon-check": { + display: "none", + }, + }, + "&>.ant-dropdown-menu-item-selected": { + "&:not(:hover)": { + backgroundColor: "transparent !important", + }, + "& .anticon-check": { + display: "inline-flex !important", + }, + }, + }, +})) + +export const generateFilterItems = (colDefs: ColDef[]) => { + return colDefs.map((configs) => ({ + key: configs.headerName as string, + label: ( + + + <>{configs.headerName} + + ), + })) +} + +interface FilterColumnsProps { + isOpen: boolean + handleOpenChange: ( + open: boolean, + info: { + source: "trigger" | "menu" + }, + ) => void + shownCols: string[] + items: ItemType[] + onClick: ({key}: {key: string}) => void + buttonText?: string +} + +const FilterColumns = ({ + isOpen, + handleOpenChange, + shownCols, + items, + onClick, + buttonText, +}: FilterColumnsProps) => { + const classes = useStyles() + + return ( + + + + ) +} + +export default FilterColumns diff --git a/agenta-web/src/components/pages/evaluations/evaluationCompare/EvaluationCompare.tsx b/agenta-web/src/components/pages/evaluations/evaluationCompare/EvaluationCompare.tsx index 050c6d091d..be9a2d5ad3 100644 --- a/agenta-web/src/components/pages/evaluations/evaluationCompare/EvaluationCompare.tsx +++ b/agenta-web/src/components/pages/evaluations/evaluationCompare/EvaluationCompare.tsx @@ -11,18 +11,12 @@ import { import {fetchAllComparisonResults} from "@/services/evaluations" import {ColDef} from "ag-grid-community" import {AgGridReact} from "ag-grid-react" -import {Button, Dropdown, DropdownProps, Space, Spin, Switch, Tag, Tooltip, Typography} from "antd" +import {Button, DropdownProps, Space, Spin, Tag, Tooltip, Typography} from "antd" import React, {useEffect, useMemo, useRef, useState} from "react" import {createUseStyles} from "react-jss" -import {getFilterParams, getTypedValue} from "@/lib/helpers/evaluate" +import {getFilterParams, getTypedValue, removeCorrectAnswerPrefix} from "@/lib/helpers/evaluate" import {getColorFromStr, getRandomColors} from "@/lib/helpers/colors" -import { - CheckOutlined, - CloseCircleOutlined, - DownOutlined, - DownloadOutlined, - UndoOutlined, -} from "@ant-design/icons" +import {CheckOutlined, CloseCircleOutlined, DownloadOutlined, UndoOutlined} from "@ant-design/icons" import {getAppValues} from "@/contexts/app.context" import {useQueryParam} from "@/hooks/useQuery" import {LongTextCellRenderer} from "../cellRenderers/cellRenderers" @@ -32,7 +26,8 @@ import {useAtom} from "jotai" import {evaluatorsAtom} from "@/lib/atoms/evaluation" import CompareOutputDiff from "@/components/CompareOutputDiff/CompareOutputDiff" import {formatCurrency, formatLatency} from "@/lib/helpers/formatters" -import {useLocalStorage} from "usehooks-ts" +import FilterColumns, {generateFilterItems} from "../FilterColumns/FilterColumns" +import _ from "lodash" const useStyles = createUseStyles((theme: JSSTheme) => ({ table: { @@ -82,17 +77,24 @@ const EvaluationCompareMode: React.FC = () => { const evaluationIdsArray = evaluationIdsStr.split(",").filter((item) => !!item) const [evalIds, setEvalIds] = useState(evaluationIdsArray) const [hiddenVariants, setHiddenVariants] = useState([]) - const [showDiff, setShowDiff] = useLocalStorage("showDiff", "show") const [fetching, setFetching] = useState(false) const [rows, setRows] = useState([]) const [testset, setTestset] = useState() const [evaluators] = useAtom(evaluatorsAtom) const gridRef = useRef>() - const [filterColsDropdown, setFilterColsDropdown] = useState(false) + const [isFilterColsDropdownOpen, setIsFilterColsDropdownOpen] = useState(false) + const [isDiffDropdownOpen, setIsDiffDropdownOpen] = useState(false) + const [selectedCorrectAnswer, setSelectedCorrectAnswer] = useState(["noDiffColumnIsSelected"]) - const handleOpenChange: DropdownProps["onOpenChange"] = (nextOpen, info) => { + const handleOpenChangeDiff: DropdownProps["onOpenChange"] = (nextOpen, info) => { if (info.source === "trigger" || nextOpen) { - setFilterColsDropdown(nextOpen) + setIsDiffDropdownOpen(nextOpen) + } + } + + const handleOpenChangeFilterCols: DropdownProps["onOpenChange"] = (nextOpen, info) => { + if (info.source === "trigger" || nextOpen) { + setIsFilterColsDropdownOpen(nextOpen) } } @@ -122,9 +124,19 @@ const EvaluationCompareMode: React.FC = () => { if (!rows.length || !variants.length) return [] - inputs.forEach((ip, ix) => { + inputs.forEach((input, ix) => { colDefs.push({ - headerName: `Input: ${ip.name}`, + headerName: `Input: ${input.name}`, + headerComponent: (props: any) => { + return ( + + + {input.name} + Input + + + ) + }, minWidth: 200, flex: 1, field: `inputs.${ix}.value` as any, @@ -134,15 +146,29 @@ const EvaluationCompareMode: React.FC = () => { }) }) - colDefs.push({ - headerName: "Expected Output", - minWidth: 280, - flex: 1, - field: "correctAnswer", - ...getFilterParams("text"), - pinned: "left", - cellRenderer: (params: any) => LongTextCellRenderer(params), - }) + Object.keys(rows[0]) + .filter((item) => item.startsWith("correctAnswer_")) + .forEach((key) => + colDefs.push({ + headerName: `${removeCorrectAnswerPrefix(key)}`, + hide: hiddenVariants.includes(`${removeCorrectAnswerPrefix(key)}`), + headerComponent: (props: any) => { + return ( + + + {removeCorrectAnswerPrefix(key)} + Ground Truth + + + ) + }, + minWidth: 280, + flex: 1, + field: key, + ...getFilterParams("text"), + cellRenderer: (params: any) => LongTextCellRenderer(params), + }), + ) variants.forEach((variant, vi) => { colDefs.push({ @@ -159,11 +185,11 @@ const EvaluationCompareMode: React.FC = () => { flex: 1, field: `variants.${vi}.output` as any, ...getFilterParams("text"), - hide: !evalIds.includes(variant.evaluationId) || hiddenVariants.includes("Output"), + hide: hiddenVariants.includes("Output"), cellRenderer: (params: any) => { return ( <> - {showDiff === "show" + {selectedCorrectAnswer[0] !== "noDiffColumnIsSelected" ? LongTextCellRenderer( params, = () => { item.evaluationId === variant.evaluationId, )?.output?.result, )} - expectedOutput={params.data?.correctAnswer} + expectedOutput={ + params.data[selectedCorrectAnswer[0]] || "" + } />, ) : LongTextCellRenderer( @@ -189,28 +217,10 @@ const EvaluationCompareMode: React.FC = () => { ) }, valueGetter: (params) => { - return ( - <> - {showDiff === "show" ? ( - - - item.evaluationId === variant.evaluationId, - )?.output?.result, - )} - expectedOutput={params.data?.correctAnswer} - /> - - ) : ( - getTypedValue( - params.data?.variants.find( - (item) => item.evaluationId === variant.evaluationId, - )?.output?.result, - ) - )} - + return getTypedValue( + params.data?.variants.find( + (item) => item.evaluationId === variant.evaluationId, + )?.output?.result, ) }, }) @@ -251,9 +261,7 @@ const EvaluationCompareMode: React.FC = () => { headerName: config.name, field: "variants.0.evaluatorConfigs.0.result" as any, ...getFilterParams("text"), - hide: - !evalIds.includes(variant.evaluationId) || - hiddenVariants.includes(config.name), + hide: hiddenVariants.includes(config.name), valueGetter: (params) => { return getTypedValue( params.data?.variants @@ -277,7 +285,7 @@ const EvaluationCompareMode: React.FC = () => { ), - hide: !evalIds.includes(variant.evaluationId) || hiddenVariants.includes("Latency"), + hide: hiddenVariants.includes("Latency"), minWidth: 120, headerName: "Latency", flex: 1, @@ -316,7 +324,7 @@ const EvaluationCompareMode: React.FC = () => { }) return colDefs - }, [rows, showDiff, hiddenVariants, evalIds]) + }, [rows, hiddenVariants, evalIds, selectedCorrectAnswer]) const fetcher = () => { setFetching(true) @@ -435,51 +443,56 @@ const EvaluationCompareMode: React.FC = () => { - - Show Difference: - setShowDiff(showDiff === "show" ? "hide" : "show")} - /> - - - !item.headerName?.startsWith("Input") && - !item.headerName?.includes("Expected Output"), - ) - .reduce((acc, curr) => { - if (curr.headerName && !acc.includes(curr.headerName)) { - acc.push(curr.headerName) - } - return acc - }, [] as string[]) - .map((configs) => ({ - key: configs as string, - label: ( - - - <>{configs} - - ), - })), - onClick: ({key}) => { - handleToggleVariantVisibility(key) - setFilterColsDropdown(true) - }, - className: classes.dropdownMenu, + !item.headerName?.startsWith("Input")), + "headerName", + ), + )} + isOpen={isFilterColsDropdownOpen} + handleOpenChange={handleOpenChangeFilterCols} + shownCols={shownCols} + onClick={({key}) => { + handleToggleVariantVisibility(key) + setIsFilterColsDropdownOpen(true) }} - > - - + /> + {!!rows.length && ( +
+ Apply difference with: + item.startsWith("correctAnswer_")) + .map((key) => ({ + key: key as string, + label: ( + + + <>{removeCorrectAnswerPrefix(key)} + + ), + }))} + buttonText={ + removeCorrectAnswerPrefix(selectedCorrectAnswer[0]) === + "noDiffColumnIsSelected" + ? "Select Ground Truth" + : removeCorrectAnswerPrefix(selectedCorrectAnswer[0]) + } + isOpen={isDiffDropdownOpen} + handleOpenChange={handleOpenChangeDiff} + shownCols={selectedCorrectAnswer} + onClick={({key}) => { + if (key === selectedCorrectAnswer[0]) { + setSelectedCorrectAnswer(["noDiffColumnIsSelected"]) + } else { + setSelectedCorrectAnswer([key]) + } + setIsDiffDropdownOpen(true) + }} + /> +
+ )} - + /> diff --git a/agenta-web/src/components/pages/evaluations/evaluationScenarios/EvaluationScenarios.tsx b/agenta-web/src/components/pages/evaluations/evaluationScenarios/EvaluationScenarios.tsx index e375c46e9d..908ada0e0c 100644 --- a/agenta-web/src/components/pages/evaluations/evaluationScenarios/EvaluationScenarios.tsx +++ b/agenta-web/src/components/pages/evaluations/evaluationScenarios/EvaluationScenarios.tsx @@ -1,15 +1,15 @@ import {useAppTheme} from "@/components/Layout/ThemeContextProvider" import {useAppId} from "@/hooks/useAppId" -import {JSSTheme, _Evaluation, _EvaluationScenario} from "@/lib/Types" +import {CorrectAnswer, JSSTheme, _Evaluation, _EvaluationScenario} from "@/lib/Types" import { deleteEvaluations, fetchAllEvaluationScenarios, fetchAllEvaluators, } from "@/services/evaluations" -import {DeleteOutlined, DownloadOutlined} from "@ant-design/icons" +import {CheckOutlined, DeleteOutlined, DownloadOutlined} from "@ant-design/icons" import {ColDef} from "ag-grid-community" import {AgGridReact} from "ag-grid-react" -import {Space, Spin, Switch, Tag, Tooltip, Typography} from "antd" +import {DropdownProps, Space, Spin, Tag, Tooltip, Typography} from "antd" import {useRouter} from "next/router" import React, {useEffect, useMemo, useRef, useState} from "react" import {createUseStyles} from "react-jss" @@ -23,7 +23,8 @@ import {useAtom} from "jotai" import {evaluatorsAtom} from "@/lib/atoms/evaluation" import CompareOutputDiff from "@/components/CompareOutputDiff/CompareOutputDiff" import {formatCurrency, formatLatency} from "@/lib/helpers/formatters" -import {useLocalStorage} from "usehooks-ts" +import _ from "lodash" +import FilterColumns, {generateFilterItems} from "../FilterColumns/FilterColumns" const useStyles = createUseStyles((theme: JSSTheme) => ({ infoRow: { @@ -56,7 +57,27 @@ const EvaluationScenarios: React.FC = () => { const [evaluators, setEvaluators] = useAtom(evaluatorsAtom) const gridRef = useRef>() const evalaution = scenarios[0]?.evaluation - const [showDiff, setShowDiff] = useLocalStorage("showDiff", "show") + const [selectedCorrectAnswer, setSelectedCorrectAnswer] = useState(["noDiffColumnIsSelected"]) + const [isFilterColsDropdownOpen, setIsFilterColsDropdownOpen] = useState(false) + const [isDiffDropdownOpen, setIsDiffDropdownOpen] = useState(false) + const [hiddenCols, setHiddenCols] = useState([]) + + const handleOpenChangeFilterCols: DropdownProps["onOpenChange"] = (nextOpen, info) => { + if (info.source === "trigger" || nextOpen) { + setIsFilterColsDropdownOpen(nextOpen) + } + } + + const handleOpenChangeDiff: DropdownProps["onOpenChange"] = (nextOpen, info) => { + if (info.source === "trigger" || nextOpen) { + setIsDiffDropdownOpen(nextOpen) + } + } + + const uniqueCorrectAnswers: CorrectAnswer[] = _.uniqBy( + scenarios[0]?.correct_answers || [], + "key", + ) const colDefs = useMemo(() => { const colDefs: ColDef<_EvaluationScenario>[] = [] @@ -67,6 +88,17 @@ const EvaluationScenarios: React.FC = () => { flex: 1, minWidth: 240, headerName: `Input: ${input.name}`, + hide: hiddenCols.includes(`Input: ${input.name}`), + headerComponent: (props: any) => { + return ( + + + {input.name} + Input + + + ) + }, ...getFilterParams(input.type === "number" ? "number" : "text"), field: `inputs.${index}`, valueGetter: (params) => { @@ -75,25 +107,41 @@ const EvaluationScenarios: React.FC = () => { cellRenderer: (params: any) => LongTextCellRenderer(params), }) }) - colDefs.push({ - flex: 1, - minWidth: 300, - headerName: "Expected Output", - field: "correct_answer", - ...getFilterParams("text"), - valueGetter: (params) => { - return params.data?.correct_answer?.toString() || "" - }, - cellRenderer: (params: any) => LongTextCellRenderer(params), + + uniqueCorrectAnswers.forEach((answer: CorrectAnswer, index: number) => { + colDefs.push({ + headerName: answer.key, + hide: hiddenCols.includes(answer.key), + headerComponent: (props: any) => { + return ( + + + {answer.key} + Ground Truth + + + ) + }, + minWidth: 200, + flex: 1, + ...getFilterParams("text"), + valueGetter: (params) => params.data?.correct_answers?.[index]?.value || "", + cellRenderer: (params: any) => LongTextCellRenderer(params), + }) }) evalaution?.variants.forEach((_, index) => { colDefs.push({ flex: 1, minWidth: 300, headerName: "Output", + hide: hiddenCols.includes("Output"), ...getFilterParams("text"), field: `outputs.0`, cellRenderer: (params: any) => { + const correctAnswer = params?.data?.correct_answers?.find( + (item: any) => item.key === selectedCorrectAnswer[0], + ) + const result = params.data?.outputs[index].result if (result && result.type == "error") { return LongTextCellRenderer( @@ -101,12 +149,12 @@ const EvaluationScenarios: React.FC = () => { `${result?.error?.message}\n${result?.error?.stacktrace}`, ) } - return showDiff === "show" + return selectedCorrectAnswer[0] !== "noDiffColumnIsSelected" ? LongTextCellRenderer( params, , ) : LongTextCellRenderer(params) @@ -120,6 +168,7 @@ const EvaluationScenarios: React.FC = () => { scenarios[0]?.evaluators_configs.forEach((config, index) => { colDefs.push({ headerName: config?.name, + hide: hiddenCols.includes(config.name), headerComponent: (props: any) => { const evaluator = evaluators.find((item) => item.key === config?.evaluator_key)! return ( @@ -147,6 +196,7 @@ const EvaluationScenarios: React.FC = () => { flex: 1, minWidth: 120, headerName: "Cost", + hide: hiddenCols.includes("Cost"), ...getFilterParams("text"), valueGetter: (params) => { return params.data?.outputs[0].cost == undefined @@ -159,6 +209,7 @@ const EvaluationScenarios: React.FC = () => { flex: 1, minWidth: 120, headerName: "Latency", + hide: hiddenCols.includes("Latency"), ...getFilterParams("text"), valueGetter: (params) => { return params.data?.outputs[0].latency == undefined @@ -167,7 +218,23 @@ const EvaluationScenarios: React.FC = () => { }, }) return colDefs - }, [evalaution, scenarios, showDiff]) + }, [evalaution, scenarios, selectedCorrectAnswer, hiddenCols]) + + const shownCols = useMemo( + () => + colDefs + .map((item) => item.headerName) + .filter((item) => item !== undefined && !hiddenCols.includes(item)) as string[], + [colDefs], + ) + + const onToggleEvaluatorVisibility = (evalConfigId: string) => { + if (!hiddenCols.includes(evalConfigId)) { + setHiddenCols([...hiddenCols, evalConfigId]) + } else { + setHiddenCols(hiddenCols.filter((item) => item !== evalConfigId)) + } + } const fetcher = () => { setFetching(true) @@ -241,13 +308,48 @@ const EvaluationScenarios: React.FC = () => { - - Show Difference: - setShowDiff(showDiff === "show" ? "hide" : "show")} - /> - + { + onToggleEvaluatorVisibility(key) + setIsFilterColsDropdownOpen(true) + }} + /> + {!!scenarios.length && !!scenarios[0].correct_answers?.length && ( +
+ Apply difference with: + ({ + key: answer.key as string, + label: ( + + + <>{answer.key} + + ), + }))} + buttonText={ + selectedCorrectAnswer[0] === "noDiffColumnIsSelected" + ? "Select Ground Truth" + : selectedCorrectAnswer[0] + } + isOpen={isDiffDropdownOpen} + handleOpenChange={handleOpenChangeDiff} + shownCols={selectedCorrectAnswer} + onClick={({key}) => { + if (key === selectedCorrectAnswer[0]) { + setSelectedCorrectAnswer(["noDiffColumnIsSelected"]) + } else { + setSelectedCorrectAnswer([key]) + } + setIsDiffDropdownOpen(true) + }} + /> +
+ )} diff --git a/agenta-web/src/components/pages/evaluations/evaluators/AdvancedSettings.tsx b/agenta-web/src/components/pages/evaluations/evaluators/AdvancedSettings.tsx new file mode 100644 index 0000000000..9e3c4ea4a4 --- /dev/null +++ b/agenta-web/src/components/pages/evaluations/evaluators/AdvancedSettings.tsx @@ -0,0 +1,95 @@ +import React from "react" +import {Form, Input, InputNumber, Switch, Tooltip, Collapse, theme} from "antd" +import {CaretRightOutlined, InfoCircleOutlined} from "@ant-design/icons" +import {createUseStyles} from "react-jss" +import {Editor} from "@monaco-editor/react" +import {useAppTheme} from "@/components/Layout/ThemeContextProvider" + +const useStyles = createUseStyles((theme: any) => ({ + label: { + display: "flex", + alignItems: "center", + gap: "0.5rem", + }, + editor: { + border: `1px solid ${theme.colorBorder}`, + borderRadius: theme.borderRadius, + overflow: "hidden", + }, +})) + +type AdvancedSettingsProps = { + settings: Record[] +} + +const AdvancedSettings: React.FC = ({settings}) => { + const classes = useStyles() + const {appTheme} = useAppTheme() + const {token} = theme.useToken() + + return ( + } + className={"my-[10px]"} + > + + {settings.map((field) => { + const rules = [ + {required: field.required ?? true, message: "This field is required"}, + ] + + return ( + + {field.label} + {field.description && ( + + + + )} + + } + initialValue={field.default} + rules={rules} + > + {field.type === "string" || field.type === "regex" ? ( + + ) : field.type === "number" ? ( + + ) : field.type === "boolean" || field.type === "bool" ? ( + + ) : field.type === "text" ? ( + + ) : field.type === "code" ? ( + + ) : field.type === "object" ? ( + + ) : null} + + ) + })} + + + ) +} + +export default AdvancedSettings diff --git a/agenta-web/src/components/pages/evaluations/evaluators/EvaluatorCard.tsx b/agenta-web/src/components/pages/evaluations/evaluators/EvaluatorCard.tsx index ddf540e463..bd3550bd0b 100644 --- a/agenta-web/src/components/pages/evaluations/evaluators/EvaluatorCard.tsx +++ b/agenta-web/src/components/pages/evaluations/evaluators/EvaluatorCard.tsx @@ -84,22 +84,14 @@ const EvaluatorCard: React.FC = ({evaluatorConfig, onEdit, onSuccessDelet return ( , - , - ] - } + actions={[ + , + , + ]} data-cy="evaluator-card" >
diff --git a/agenta-web/src/components/pages/evaluations/evaluators/NewEvaluatorModal.tsx b/agenta-web/src/components/pages/evaluations/evaluators/NewEvaluatorModal.tsx index 6ea154af35..5fd8fc1bf8 100644 --- a/agenta-web/src/components/pages/evaluations/evaluators/NewEvaluatorModal.tsx +++ b/agenta-web/src/components/pages/evaluations/evaluators/NewEvaluatorModal.tsx @@ -10,7 +10,7 @@ import { } from "@/services/evaluations" import {ArrowLeftOutlined, EditOutlined, InfoCircleOutlined, PlusOutlined} from "@ant-design/icons" import {Editor} from "@monaco-editor/react" -import {Button, Form, Input, InputNumber, Modal, Switch, Table, Tag, Tooltip, theme} from "antd" +import {Button, Form, Input, InputNumber, Modal, Switch, Table, Tooltip, theme} from "antd" import {Rule} from "antd/es/form" import {useAtom} from "jotai" import Image from "next/image" @@ -18,6 +18,7 @@ import Link from "next/link" import React, {useEffect, useMemo, useState} from "react" import {createUseStyles} from "react-jss" import {ColumnsType} from "antd/es/table" +import AdvancedSettings from "./AdvancedSettings" const useStyles = createUseStyles((theme: JSSTheme) => ({ label: { @@ -124,6 +125,7 @@ const DynamicFormField: React.FC = ({ const {appTheme} = useAppTheme() const classes = useStyles() const {token} = theme.useToken() + const [showAdvancedSettings, setShowAdvancedSettings] = useState(false) const rules: Rule[] = [{required: required ?? true, message: "This field is required"}] if (type === "regex") @@ -152,48 +154,51 @@ const DynamicFormField: React.FC = ({ return ( <> - - {label} - {description && ( - - - - )} -
- } - initialValue={defaultVal} - rules={rules} - > - {type === "string" || type === "regex" ? ( - - ) : type === "number" ? ( - - ) : type === "boolean" || type === "bool" ? ( - - ) : type === "text" ? ( - - ) : type === "code" ? ( - - ) : type === "object" ? ( - - ) : null} - + {label !== "Correct Answer" && ( + + {label} + {description && ( + + + + )} + + } + initialValue={defaultVal} + rules={rules} + > + {type === "string" || type === "regex" ? ( + + ) : type === "number" ? ( + + ) : type === "boolean" || type === "bool" ? ( + + ) : type === "text" ? ( + + ) : type === "code" ? ( + + ) : type === "object" ? ( + + ) : null} + + )} + {ExternalHelpInfo} ) @@ -218,7 +223,7 @@ const NewEvaluatorModal: React.FC = ({ ...props }) => { const classes = useStyles() - const evaluators = useAtom(evaluatorsAtom)[0].filter((item) => !item.direct_use) + const evaluators = useAtom(evaluatorsAtom)[0] const [selectedEval, setSelectedEval] = useState(null) const [submitLoading, setSubmitLoading] = useState(false) const [searchTerm, setSearchTerm] = useState("") @@ -244,6 +249,7 @@ const NewEvaluatorModal: React.FC = ({ .map((key) => ({ key, ...selectedEval?.settings_template[key]!, + advanced: selectedEval?.settings_template[key]?.advanced || false, })), [selectedEval], ) @@ -258,13 +264,28 @@ const NewEvaluatorModal: React.FC = ({ } }, [newEvalModalConfigOpen]) + const advancedSettingsFields = evalFields.filter((field) => field.advanced) + const basicSettingsFields = evalFields.filter((field) => !field.advanced) + console.log(evalFields) + console.log(basicSettingsFields) + const onSubmit = (values: CreateEvaluationConfigData) => { setSubmitLoading(true) if (!selectedEval?.key) throw new Error("No selected key") + const settingsValues = values.settings_values || {} + + if ( + !settingsValues.correct_answer_key && + selectedEval.settings_template.correct_answer_key.default + ) { + settingsValues["correct_answer_key"] = + selectedEval.settings_template.correct_answer_key.default + } + const data = { ...values, evaluator_key: selectedEval.key, - settings_values: values.settings_values || {}, + settings_values: settingsValues, } ;(editMode ? updateEvaluatorConfig(initialValues?.id!, data) @@ -394,7 +415,7 @@ const NewEvaluatorModal: React.FC = ({ - {evalFields.map((field) => ( + {basicSettingsFields.map((field) => ( = ({ /> ))} + {advancedSettingsFields.length > 0 && ( + + )} +
{!editMode && ( diff --git a/agenta-web/src/lib/Types.ts b/agenta-web/src/lib/Types.ts index 93915a99cb..c742244029 100644 --- a/agenta-web/src/lib/Types.ts +++ b/agenta-web/src/lib/Types.ts @@ -339,6 +339,7 @@ export interface EvaluationSettingsTemplate { min?: number max?: number required?: boolean + advanced?: boolean } export interface Evaluator { @@ -383,6 +384,11 @@ export enum EvaluationStatusType { ERROR = "error", } +export interface CorrectAnswer { + key: string + value: string +} + export interface _Evaluation { id: string appId: string @@ -421,7 +427,7 @@ export interface _EvaluationScenario { evaluators_configs: EvaluatorConfig[] inputs: (TypedValue & {name: string})[] outputs: {result: TypedValue; cost?: number; latency?: number}[] - correct_answer?: string + correct_answers?: CorrectAnswer[] is_pinned?: boolean note?: string results: {evaluator_config: string; result: TypedValue & {error: null | EvaluationError}}[] @@ -452,7 +458,6 @@ export interface AnnotationScenario { export type ComparisonResultRow = { inputs: {name: string; value: string}[] - correctAnswer: string variants: { variantId: string variantName: string @@ -464,7 +469,7 @@ export type ComparisonResultRow = { }[] }[] id: string -} +} & {[key: string]: any} export type RequestMetadata = { cost: number diff --git a/agenta-web/src/lib/helpers/evaluate.ts b/agenta-web/src/lib/helpers/evaluate.ts index 55edfe758d..915bc44ed0 100644 --- a/agenta-web/src/lib/helpers/evaluate.ts +++ b/agenta-web/src/lib/helpers/evaluate.ts @@ -338,3 +338,7 @@ const getCustomComparator = (type: CellDataType) => (valueA: string, valueB: str if (type === "number") return getNumber(valueA) - getNumber(valueB) return 0 } + +export const removeCorrectAnswerPrefix = (str: string) => { + return str.replace(/^correctAnswer_/, "") +} diff --git a/agenta-web/src/services/evaluations/index.ts b/agenta-web/src/services/evaluations/index.ts index c672840052..625c7d4645 100644 --- a/agenta-web/src/services/evaluations/index.ts +++ b/agenta-web/src/services/evaluations/index.ts @@ -25,6 +25,7 @@ import dayjs from "dayjs" import {loadTestset} from "@/lib/services/api" import {runningStatuses} from "@/components/pages/evaluations/cellRenderers/cellRenderers" import {calcEvalDuration} from "@/lib/helpers/evaluate" +import _ from "lodash" //Prefix convention: // - fetch: GET single entity from server @@ -225,6 +226,11 @@ export const fetchAllComparisonResults = async (evaluationIds: string[]) => { const inputNames = Array.from(inputsNameSet) const inputValuesSet = new Set() const variants = scenarioGroups.map((group) => group[0].evaluation.variants[0]) + const correctAnswers = _.uniqBy( + scenarioGroups.map((group) => group[0].correct_answers).flat(), + "key", + ) + for (const data of testset.csvdata) { const inputValues = inputNames .filter((name) => data[name] !== undefined) @@ -238,7 +244,9 @@ export const fetchAllComparisonResults = async (evaluationIds: string[]) => { inputs: inputNames .map((name) => ({name, value: data[name]})) .filter((ip) => ip.value !== undefined), - correctAnswer: data.correct_answer || "", + ...correctAnswers.reduce((acc, curr) => { + return {...acc, [`correctAnswer_${curr?.key}`]: data[curr?.key!]} + }, {}), variants: variants.map((variant, ix) => { const group = scenarioGroups[ix] const scenario = group.find((scenario) =>