mirror of
https://github.com/crewAIInc/crewAI.git
synced 2026-05-06 01:32:36 +00:00
Added functionality to have any llm run test functionality
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@@ -1125,19 +1125,20 @@ class Crew(BaseModel):
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def test(
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self,
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n_iterations: int,
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openai_model_name: Optional[str] = None,
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eval_llm: Union[str, InstanceOf[LLM], Any] = Field(description="Language model that will run the agent.", default=None),
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inputs: Optional[Dict[str, Any]] = None,
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) -> None:
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"""Test and evaluate the Crew with the given inputs for n iterations concurrently using concurrent.futures."""
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test_crew = self.copy()
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eval_llm = create_llm(eval_llm)
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self._test_execution_span = test_crew._telemetry.test_execution_span(
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test_crew,
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n_iterations,
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inputs,
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openai_model_name, # type: ignore[arg-type]
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eval_llm.model, # type: ignore[arg-type]
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) # type: ignore[arg-type]
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evaluator = CrewEvaluator(test_crew, openai_model_name) # type: ignore[arg-type]
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evaluator = CrewEvaluator(test_crew, eval_llm) # type: ignore[arg-type]
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for i in range(1, n_iterations + 1):
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evaluator.set_iteration(i)
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@@ -1,6 +1,6 @@
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from collections import defaultdict
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from pydantic import BaseModel, Field
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from pydantic import BaseModel, Field, InstanceOf
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from rich.box import HEAVY_EDGE
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from rich.console import Console
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from rich.table import Table
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@@ -9,6 +9,7 @@ from crewai.agent import Agent
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from crewai.task import Task
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from crewai.tasks.task_output import TaskOutput
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from crewai.telemetry import Telemetry
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from crewai.llm import LLM
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class TaskEvaluationPydanticOutput(BaseModel):
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@@ -32,9 +33,9 @@ class CrewEvaluator:
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run_execution_times: defaultdict = defaultdict(list)
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iteration: int = 0
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def __init__(self, crew, openai_model_name: str):
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def __init__(self, crew, eval_llm: InstanceOf[LLM]):
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self.crew = crew
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self.openai_model_name = openai_model_name
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self.llm = eval_llm
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self._telemetry = Telemetry()
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self._setup_for_evaluating()
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@@ -51,7 +52,7 @@ class CrewEvaluator:
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),
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backstory="Evaluator agent for crew evaluation with precise capabilities to evaluate the performance of the agents in the crew based on the tasks they have performed",
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verbose=False,
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llm=self.openai_model_name,
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llm=self.llm,
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)
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def _evaluation_task(
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@@ -181,7 +182,7 @@ class CrewEvaluator:
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self.crew,
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evaluation_result.pydantic.quality,
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current_task.execution_duration,
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self.openai_model_name,
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self.llm.model,
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)
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self.tasks_scores[self.iteration].append(evaluation_result.pydantic.quality)
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self.run_execution_times[self.iteration].append(
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