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Author SHA1 Message Date
Devin AI
7c98269a79 style: Fix code formatting and improve readability
Co-Authored-By: Joe Moura <joao@crewai.com>
2025-02-22 16:56:47 +00:00
Devin AI
9207133413 chore: trigger CI checks
Co-Authored-By: Joe Moura <joao@crewai.com>
2025-02-22 16:52:33 +00:00
Devin AI
30bdf25a6b refactor: Improve code quality based on review feedback
- Add type hints and model version comments in constants.py
- Add API key validation helper function in utils.py
- Improve error handling for file operations
- Add test constants and parameterized tests for Mistral provider

Co-Authored-By: Joe Moura <joao@crewai.com>
2025-02-22 16:51:23 +00:00
Devin AI
dc765e6491 fix: Add Mistral provider configuration and tests (#2200)
- Add Mistral provider to constants.py with API key config
- Add Mistral models to available models list
- Fix env file creation to only write when API keys are provided
- Add tests for Mistral provider setup with and without API key

Fixes #2200

Co-Authored-By: Joe Moura <joao@crewai.com>
2025-02-22 16:36:25 +00:00
9 changed files with 277 additions and 290 deletions

View File

@@ -1,10 +1,18 @@
ENV_VARS = {
from typing import Dict, List
ENV_VARS: Dict[str, List[Dict[str, str]]] = {
"openai": [
{
"prompt": "Enter your OPENAI API key (press Enter to skip)",
"key_name": "OPENAI_API_KEY",
}
],
"mistral": [
{
"prompt": "Enter your MISTRAL API key (press Enter to skip)",
"key_name": "MISTRAL_API_KEY",
}
],
"anthropic": [
{
"prompt": "Enter your ANTHROPIC API key (press Enter to skip)",
@@ -88,7 +96,7 @@ ENV_VARS = {
}
PROVIDERS = [
PROVIDERS: List[str] = [
"openai",
"anthropic",
"gemini",
@@ -98,10 +106,17 @@ PROVIDERS = [
"bedrock",
"azure",
"cerebras",
"mistral", # Added in v0.86.0
]
MODELS = {
MODELS: Dict[str, List[str]] = {
"openai": ["gpt-4", "gpt-4o", "gpt-4o-mini", "o1-mini", "o1-preview"],
"mistral": [
"mistral-tiny", # 7B model optimized for speed
"mistral-small", # 7B model balanced for performance
"mistral-medium", # 8x7B model for enhanced capabilities
"mistral-large", # Latest model with highest performance
],
"anthropic": [
"claude-3-5-sonnet-20240620",
"claude-3-sonnet-20240229",

View File

@@ -10,7 +10,12 @@ from crewai.cli.provider import (
select_model,
select_provider,
)
from crewai.cli.utils import copy_template, load_env_vars, write_env_file
from crewai.cli.utils import (
copy_template,
load_env_vars,
validate_api_keys,
write_env_file,
)
def create_folder_structure(name, parent_folder=None):
@@ -162,9 +167,13 @@ def create_crew(name, provider=None, skip_provider=False, parent_folder=None):
if api_key_value.strip():
env_vars[key_name] = api_key_value
if env_vars:
write_env_file(folder_path, env_vars)
click.secho("API keys and model saved to .env file", fg="green")
if validate_api_keys(env_vars):
try:
write_env_file(folder_path, env_vars)
click.secho("API keys and model saved to .env file", fg="green")
except IOError as e:
click.secho(f"Error writing .env file: {str(e)}", fg="red")
raise
else:
click.secho(
"No API keys provided. Skipping .env file creation.", fg="yellow"

View File

@@ -2,6 +2,7 @@ import os
import shutil
import sys
from functools import reduce
from pathlib import Path
from typing import Any, Dict, List
import click
@@ -235,15 +236,39 @@ def update_env_vars(env_vars, provider, model):
return env_vars
def write_env_file(folder_path, env_vars):
def validate_api_keys(env_vars: Dict[str, str]) -> bool:
"""
Validates that at least one API key is present and non-empty in the environment variables.
Args:
env_vars (Dict[str, str]): Dictionary of environment variables
Returns:
bool: True if at least one API key is present and non-empty
"""
api_keys = ["MISTRAL_API_KEY", "OPENAI_API_KEY", "ANTHROPIC_API_KEY"]
return any(
key in env_vars and env_vars[key].strip()
for key in api_keys
)
def write_env_file(folder_path: Path, env_vars: Dict[str, str]) -> None:
"""
Writes environment variables to a .env file in the specified folder.
Args:
- folder_path (Path): The path to the folder where the .env file will be written.
- env_vars (dict): A dictionary of environment variables to write.
folder_path (Path): The path to the folder where the .env file will be written.
env_vars (Dict[str, str]): A dictionary of environment variables to write.
Raises:
IOError: If there is an error writing to the .env file
"""
env_file_path = folder_path / ".env"
with open(env_file_path, "w") as file:
for key, value in env_vars.items():
file.write(f"{key}={value}\n")
try:
with open(env_file_path, "w") as file:
for key, value in env_vars.items():
file.write(f"{key}={value}\n")
except IOError as e:
click.secho(f"Error writing .env file: {str(e)}", fg="red")
raise

View File

@@ -16,8 +16,6 @@ from pydantic import (
field_validator,
model_validator,
)
from crewai.llm import LLM
from pydantic_core import PydanticCustomError
from crewai.agent import Agent
@@ -1078,32 +1076,18 @@ class Crew(BaseModel):
self,
n_iterations: int,
openai_model_name: Optional[str] = None,
llm: Optional[Union[str, LLM]] = None,
inputs: Optional[Dict[str, Any]] = None,
) -> None:
"""Test and evaluate the Crew with the given inputs for n iterations concurrently using concurrent.futures.
Args:
n_iterations: Number of iterations to run the test
openai_model_name: Name of OpenAI model to use (deprecated, use llm instead)
llm: LLM instance or model name to use for evaluation
inputs: Optional inputs to pass to the crew
"""
"""Test and evaluate the Crew with the given inputs for n iterations concurrently using concurrent.futures."""
test_crew = self.copy()
# Convert string to LLM instance if needed
if isinstance(llm, str):
llm = LLM(model=llm)
elif openai_model_name:
llm = LLM(model=openai_model_name)
self._test_execution_span = test_crew._telemetry.test_execution_span(
test_crew,
n_iterations,
inputs,
getattr(llm, "model", openai_model_name),
)
evaluator = CrewEvaluator(test_crew, llm)
openai_model_name, # type: ignore[arg-type]
) # type: ignore[arg-type]
evaluator = CrewEvaluator(test_crew, openai_model_name) # type: ignore[arg-type]
for i in range(1, n_iterations + 1):
evaluator.set_iteration(i)

View File

@@ -1,5 +1,4 @@
from collections import defaultdict
from typing import Union
from pydantic import BaseModel, Field
from rich.box import HEAVY_EDGE
@@ -7,7 +6,6 @@ from rich.console import Console
from rich.table import Table
from crewai.agent import Agent
from crewai.llm import LLM
from crewai.task import Task
from crewai.tasks.task_output import TaskOutput
from crewai.telemetry import Telemetry
@@ -34,9 +32,9 @@ class CrewEvaluator:
run_execution_times: defaultdict = defaultdict(list)
iteration: int = 0
def __init__(self, crew, llm: Union[str, LLM]):
def __init__(self, crew, openai_model_name: str):
self.crew = crew
self.llm = llm if isinstance(llm, LLM) else LLM(model=llm)
self.openai_model_name = openai_model_name
self._telemetry = Telemetry()
self._setup_for_evaluating()
@@ -53,7 +51,7 @@ class CrewEvaluator:
),
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",
verbose=False,
llm=self.llm,
llm=self.openai_model_name,
)
def _evaluation_task(
@@ -183,7 +181,7 @@ class CrewEvaluator:
self.crew,
evaluation_result.pydantic.quality,
current_task._execution_time,
getattr(self.llm, "model", None),
self.openai_model_name,
)
self.tasks_scores[self.iteration].append(evaluation_result.pydantic.quality)
self.run_execution_times[self.iteration].append(

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View File

@@ -2,6 +2,7 @@ from pathlib import Path
from unittest import mock
import pytest
import click
from click.testing import CliRunner
from crewai.cli.cli import (
@@ -20,6 +21,14 @@ from crewai.cli.cli import (
)
from crewai.cli.cli import create
TEST_CONSTANTS = {
"CREW_NAME": "test_crew",
"MISTRAL_API_KEY": "mistral_api_key_123",
"MISTRAL_MODEL": "mistral-tiny",
"EMPTY_KEY": "",
}
@pytest.fixture
def runner():
return CliRunner()
@@ -309,6 +318,114 @@ def test_flow_add_crew(mock_path_exists, mock_create_embedded_crew, runner):
assert isinstance(call_kwargs["parent_folder"], Path)
@pytest.mark.parametrize(
"provider,model,api_key,has_valid_keys,expected_outputs",
[
(
"mistral",
TEST_CONSTANTS["MISTRAL_MODEL"],
TEST_CONSTANTS["MISTRAL_API_KEY"],
True,
["API keys and model saved", f"Selected model: {TEST_CONSTANTS['MISTRAL_MODEL']}"]
),
(
"mistral",
TEST_CONSTANTS["MISTRAL_MODEL"],
TEST_CONSTANTS["EMPTY_KEY"],
False,
["No API keys provided", f"Selected model: {TEST_CONSTANTS['MISTRAL_MODEL']}"]
),
(
"mistral",
None,
TEST_CONSTANTS["EMPTY_KEY"],
False,
["No model selected"]
),
]
)
@mock.patch("crewai.cli.create_crew.validate_api_keys")
@mock.patch("crewai.cli.create_crew.write_env_file")
@mock.patch("crewai.cli.create_crew.load_env_vars")
@mock.patch("crewai.cli.create_crew.get_provider_data")
@mock.patch("crewai.cli.create_crew.select_model")
@mock.patch("crewai.cli.create_crew.select_provider")
@mock.patch("crewai.cli.create_crew.click.confirm")
@mock.patch("crewai.cli.create_crew.click.prompt")
def test_create_crew_scenarios(
mock_prompt, mock_confirm, mock_select_provider, mock_select_model,
mock_get_provider_data, mock_load_env_vars, mock_write_env_file, mock_validate_api_keys,
runner, provider, model, api_key, has_valid_keys, expected_outputs
):
"""Test different scenarios for crew creation with provider configuration.
Args:
mock_*: Mock objects for various dependencies
runner: Click test runner
provider: Provider to test (e.g. "mistral")
model: Model to select (e.g. "mistral-tiny")
api_key: API key to provide
has_valid_keys: Whether the API key validation should pass
expected_output: Expected message in the output
"""
mock_confirm.return_value = True
mock_get_provider_data.return_value = {"mistral": [TEST_CONSTANTS["MISTRAL_MODEL"]]}
mock_load_env_vars.return_value = {}
mock_select_provider.return_value = provider
mock_select_model.return_value = model
mock_prompt.return_value = api_key
mock_validate_api_keys.return_value = has_valid_keys
# When model is None, simulate model selection being cancelled
if model is None:
mock_select_model.side_effect = click.UsageError("No model selected")
result = runner.invoke(create, ["crew", TEST_CONSTANTS["CREW_NAME"]], input="y\n")
# For model=None case, we expect error message
if model is None:
assert result.exit_code == 2 # UsageError exit code
assert "No model selected" in result.output
else:
assert result.exit_code == 0
for expected_output in expected_outputs:
assert expected_output in result.output
@mock.patch("crewai.cli.create_crew.validate_api_keys")
@mock.patch("crewai.cli.create_crew.write_env_file")
@mock.patch("crewai.cli.create_crew.load_env_vars")
@mock.patch("crewai.cli.create_crew.get_provider_data")
@mock.patch("crewai.cli.create_crew.select_model")
@mock.patch("crewai.cli.create_crew.select_provider")
@mock.patch("crewai.cli.create_crew.click.confirm")
@mock.patch("crewai.cli.create_crew.click.prompt")
def test_create_crew_with_file_error(
mock_prompt, mock_confirm, mock_select_provider, mock_select_model,
mock_get_provider_data, mock_load_env_vars, mock_write_env_file, mock_validate_api_keys,
runner
):
# Mock folder override confirmation
mock_confirm.return_value = True
# Mock provider data
mock_get_provider_data.return_value = {"mistral": [TEST_CONSTANTS["MISTRAL_MODEL"]]}
# Mock empty env vars
mock_load_env_vars.return_value = {}
# Mock provider and model selection
mock_select_provider.return_value = "mistral"
mock_select_model.return_value = TEST_CONSTANTS["MISTRAL_MODEL"]
# Mock API key input
mock_prompt.return_value = TEST_CONSTANTS["MISTRAL_API_KEY"]
# Mock API key validation
mock_validate_api_keys.return_value = True
# Mock file write error
mock_write_env_file.side_effect = IOError("Permission denied")
result = runner.invoke(create, ["crew", TEST_CONSTANTS["CREW_NAME"]], input="y\n")
assert result.exit_code == 1
assert "Error writing .env file: Permission denied" in result.output
assert mock_write_env_file.called
def test_add_crew_to_flow_not_in_root(runner):
# Simulate not being in the root of a flow project
with mock.patch("pathlib.Path.exists", autospec=True) as mock_exists:

View File

@@ -14,7 +14,6 @@ from crewai.agent import Agent
from crewai.agents.cache import CacheHandler
from crewai.crew import Crew
from crewai.crews.crew_output import CrewOutput
from crewai.llm import LLM
from crewai.memory.contextual.contextual_memory import ContextualMemory
from crewai.process import Process
from crewai.task import Task
@@ -1124,7 +1123,7 @@ def test_kickoff_for_each_empty_input():
assert results == []
@pytest.mark.vcr(filter_headeruvs=["authorization"])
@pytest.mark.vcr(filter_headers=["authorization"])
def test_kickoff_for_each_invalid_input():
"""Tests if kickoff_for_each raises TypeError for invalid input types."""
@@ -2813,11 +2812,10 @@ def test_conditional_should_execute():
@mock.patch("crewai.crew.CrewEvaluator")
@mock.patch("crewai.crew.Crew.copy")
@mock.patch("crewai.crew.Crew.kickoff")
def test_crew_testing_function_with_openai_model_name(kickoff_mock, copy_mock, crew_evaluator):
"""Test backward compatibility with openai_model_name parameter."""
def test_crew_testing_function(kickoff_mock, copy_mock, crew_evaluator):
task = Task(
description="Test task",
expected_output="Test output",
description="Come up with a list of 5 interesting ideas to explore for an article, then write one amazing paragraph highlight for each idea that showcases how good an article about this topic could be. Return the list of ideas with their paragraph and your notes.",
expected_output="5 bullet points with a paragraph for each idea.",
agent=researcher,
)
@@ -2826,87 +2824,20 @@ def test_crew_testing_function_with_openai_model_name(kickoff_mock, copy_mock, c
tasks=[task],
)
# Create a mock for the copied crew
copy_mock.return_value = crew
n_iterations = 2
crew.test(n_iterations, openai_model_name="gpt-4o-mini", inputs={"topic": "AI"})
# Ensure kickoff is called on the copied crew
kickoff_mock.assert_has_calls(
[mock.call(inputs={"topic": "AI"}), mock.call(inputs={"topic": "AI"})]
)
crew_evaluator.assert_has_calls(
[
mock.call(crew, mock.ANY), # ANY because we convert to LLM instance
mock.call().set_iteration(1),
mock.call().set_iteration(2),
mock.call().print_crew_evaluation_result(),
]
)
@mock.patch("crewai.crew.CrewEvaluator")
@mock.patch("crewai.crew.Crew.copy")
@mock.patch("crewai.crew.Crew.kickoff")
def test_crew_testing_function_with_llm_instance(kickoff_mock, copy_mock, crew_evaluator):
"""Test using LLM instance parameter."""
task = Task(
description="Test task",
expected_output="Test output",
agent=researcher,
)
crew = Crew(
agents=[researcher],
tasks=[task],
)
copy_mock.return_value = crew
llm = LLM(model="gpt-4o-mini")
n_iterations = 2
crew.test(n_iterations, llm=llm, inputs={"topic": "AI"})
kickoff_mock.assert_has_calls(
[mock.call(inputs={"topic": "AI"}), mock.call(inputs={"topic": "AI"})]
)
crew_evaluator.assert_has_calls(
[
mock.call(crew, llm),
mock.call().set_iteration(1),
mock.call().set_iteration(2),
mock.call().print_crew_evaluation_result(),
]
)
@mock.patch("crewai.crew.CrewEvaluator")
@mock.patch("crewai.crew.Crew.copy")
@mock.patch("crewai.crew.Crew.kickoff")
def test_crew_testing_function_with_llm_string(kickoff_mock, copy_mock, crew_evaluator):
"""Test using LLM string parameter."""
task = Task(
description="Test task",
expected_output="Test output",
agent=researcher,
)
crew = Crew(
agents=[researcher],
tasks=[task],
)
copy_mock.return_value = crew
n_iterations = 2
crew.test(n_iterations, llm="gpt-4o-mini", inputs={"topic": "AI"})
kickoff_mock.assert_has_calls(
[mock.call(inputs={"topic": "AI"}), mock.call(inputs={"topic": "AI"})]
)
crew_evaluator.assert_has_calls(
[
mock.call(crew, mock.ANY), # ANY because we don't care about the LLM instance details
mock.call(crew, "gpt-4o-mini"),
mock.call().set_iteration(1),
mock.call().set_iteration(2),
mock.call().print_crew_evaluation_result(),
@@ -3194,4 +3125,4 @@ def test_multimodal_agent_live_image_analysis():
# Verify we got a meaningful response
assert isinstance(result.raw, str)
assert len(result.raw) > 100 # Expecting a detailed analysis
assert "error" not in result.raw.lower() # No error messages in response
assert "error" not in result.raw.lower() # No error messages in response

68
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@@ -308,7 +300,7 @@ name = "build"
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{ name = "importlib-metadata", marker = "python_full_version < '3.10.2'" },
{ name = "packaging" },
{ name = "pyproject-hooks" },
@@ -543,7 +535,7 @@ name = "click"
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@@ -650,6 +642,7 @@ tools = [
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{ name = "crewai-tools" },
{ name = "mkdocs" },
{ name = "mkdocs-material" },
{ name = "mkdocs-material-extensions" },
@@ -703,6 +696,7 @@ requires-dist = [
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{ name = "crewai-tools", specifier = ">=0.17.0" },
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{ name = "mkdocs-material", specifier = ">=9.5.7" },
{ name = "mkdocs-material-extensions", specifier = ">=1.3.1" },
@@ -2468,7 +2462,7 @@ version = "1.6.1"
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