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14 Commits

Author SHA1 Message Date
Lorenze Jay
1589230833 Merge branch 'main' of github.com:crewAIInc/crewAI into fix/memory-embedder-config 2024-10-22 12:28:07 -07:00
Lorenze Jay
6d0251224e Merge branch 'fix/memory-embedder-config' of github.com:crewAIInc/crewAI into fix/memory-embedder-config 2024-10-22 12:27:50 -07:00
Lorenze Jay
e2f70cb53f updates to add more docs and correct imports with huggingface embedding server enabled 2024-10-22 12:27:47 -07:00
Brandon Hancock
0dd522ddff Merge branch 'main' into fix/memory-embedder-config 2024-10-21 19:41:45 -04:00
Lorenze Jay
5803b3fb69 fixed run types 2024-10-21 16:04:42 -07:00
Lorenze Jay
31c3082740 fixed docs 2024-10-21 14:29:11 -07:00
Lorenze Jay
21afc46c0d Merge branch 'main' of github.com:crewAIInc/crewAI into fix/memory-embedder-config 2024-10-21 14:24:35 -07:00
Lorenze Jay
78882c6de2 rm prints 2024-10-21 14:24:26 -07:00
Lorenze Jay
2786086974 fixes 2024-10-21 14:24:07 -07:00
Lorenze Jay
6b12ac9c0b Merge branch 'main' of github.com:crewAIInc/crewAI into fix/memory-embedder-config 2024-10-21 09:31:56 -07:00
Lorenze Jay
266ecff395 WIP: brandons notes 2024-10-21 09:31:39 -07:00
Lorenze Jay
34d748d18e raise error on unsupported provider 2024-10-21 08:37:42 -07:00
Lorenze Jay
79f527576b some fixes 2024-10-20 18:26:24 -07:00
Lorenze Jay
3fc83c624b ensure original embedding config works 2024-10-20 18:12:57 -07:00
14 changed files with 155 additions and 256 deletions

View File

@@ -6,7 +6,7 @@ icon: terminal
# CrewAI CLI Documentation
The CrewAI CLI provides a set of commands to interact with CrewAI, allowing you to create, train, run, and manage crews & flows.
The CrewAI CLI provides a set of commands to interact with CrewAI, allowing you to create, train, run, and manage crews and pipelines.
## Installation
@@ -146,34 +146,3 @@ crewai run
Make sure to run these commands from the directory where your CrewAI project is set up.
Some commands may require additional configuration or setup within your project structure.
</Note>
### 9. API Keys
When running ```crewai create crew``` command, the CLI will first show you the top 5 most common LLM providers and ask you to select one.
Once you've selected an LLM provider, you will be prompted for API keys.
#### Initial API key providers
The CLI will initially prompt for API keys for the following services:
* OpenAI
* Groq
* Anthropic
* Google Gemini
When you select a provider, the CLI will prompt you to enter your API key.
#### Other Options
If you select option 6, you will be able to select from a list of LiteLLM supported providers.
When you select a provider, the CLI will prompt you to enter the Key name and the API key.
See the following link for each provider's key name:
* [LiteLLM Providers](https://docs.litellm.ai/docs/providers)

View File

@@ -1,6 +1,6 @@
[project]
name = "crewai"
version = "0.75.1"
version = "0.74.2"
description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
readme = "README.md"
requires-python = ">=3.10,<=3.13"

View File

@@ -14,5 +14,5 @@ warnings.filterwarnings(
category=UserWarning,
module="pydantic.main",
)
__version__ = "0.75.1"
__version__ = "0.74.2"
__all__ = ["Agent", "Crew", "Process", "Task", "Pipeline", "Router", "LLM", "Flow"]

View File

@@ -32,11 +32,10 @@ def crewai():
@crewai.command()
@click.argument("type", type=click.Choice(["crew", "pipeline", "flow"]))
@click.argument("name")
@click.option("--provider", type=str, help="The provider to use for the crew")
def create(type, name, provider):
def create(type, name):
"""Create a new crew, pipeline, or flow."""
if type == "crew":
create_crew(name, provider)
create_crew(name)
elif type == "pipeline":
create_pipeline(name)
elif type == "flow":

View File

@@ -1,16 +1,8 @@
import sys
from pathlib import Path
import click
from crewai.cli.constants import ENV_VARS
from crewai.cli.provider import (
PROVIDERS,
get_provider_data,
select_model,
select_provider,
)
from crewai.cli.utils import copy_template, load_env_vars, write_env_file
from crewai.cli.provider import get_provider_data, select_provider, PROVIDERS
from crewai.cli.constants import ENV_VARS
def create_folder_structure(name, parent_folder=None):
@@ -22,19 +14,11 @@ def create_folder_structure(name, parent_folder=None):
else:
folder_path = Path(folder_name)
if folder_path.exists():
if not click.confirm(
f"Folder {folder_name} already exists. Do you want to override it?"
):
click.secho("Operation cancelled.", fg="yellow")
sys.exit(0)
click.secho(f"Overriding folder {folder_name}...", fg="green", bold=True)
else:
click.secho(
f"Creating {'crew' if parent_folder else 'folder'} {folder_name}...",
fg="green",
bold=True,
)
click.secho(
f"Creating {'crew' if parent_folder else 'folder'} {folder_name}...",
fg="green",
bold=True,
)
if not folder_path.exists():
folder_path.mkdir(parents=True)
@@ -43,6 +27,11 @@ def create_folder_structure(name, parent_folder=None):
(folder_path / "src" / folder_name).mkdir(parents=True)
(folder_path / "src" / folder_name / "tools").mkdir(parents=True)
(folder_path / "src" / folder_name / "config").mkdir(parents=True)
else:
click.secho(
f"\tFolder {folder_name} already exists.",
fg="yellow",
)
return folder_path, folder_name, class_name
@@ -85,73 +74,33 @@ def create_crew(name, parent_folder=None):
folder_path, folder_name, class_name = create_folder_structure(name, parent_folder)
env_vars = load_env_vars(folder_path)
existing_provider = None
for provider, env_keys in ENV_VARS.items():
if any(key in env_vars for key in env_keys):
existing_provider = provider
break
if existing_provider:
if not click.confirm(
f"Found existing environment variable configuration for {existing_provider.capitalize()}. Do you want to override it?"
):
click.secho("Keeping existing provider configuration.", fg="yellow")
return
provider_models = get_provider_data()
if not provider_models:
return
while True:
selected_provider = select_provider(provider_models)
if selected_provider is None: # User typed 'q'
click.secho("Exiting...", fg="yellow")
sys.exit(0)
if selected_provider: # Valid selection
break
click.secho(
"No provider selected. Please try again or press 'q' to exit.", fg="red"
)
selected_provider = select_provider(provider_models)
if not selected_provider:
return
provider = selected_provider
while True:
selected_model = select_model(selected_provider, provider_models)
if selected_model is None: # User typed 'q'
click.secho("Exiting...", fg="yellow")
sys.exit(0)
if selected_model: # Valid selection
break
click.secho(
"No model selected. Please try again or press 'q' to exit.", fg="red"
)
# selected_model = select_model(provider, provider_models)
# if not selected_model:
# return
# model = selected_model
if selected_provider in PROVIDERS:
api_key_var = ENV_VARS[selected_provider][0]
if provider in PROVIDERS:
api_key_var = ENV_VARS[provider][0]
else:
api_key_var = click.prompt(
f"Enter the environment variable name for your {selected_provider.capitalize()} API key",
f"Enter the environment variable name for your {provider.capitalize()} API key",
type=str,
default="",
)
api_key_value = ""
click.echo(
f"Enter your {selected_provider.capitalize()} API key (press Enter to skip): ",
nl=False,
)
try:
api_key_value = input()
except (KeyboardInterrupt, EOFError):
api_key_value = ""
env_vars = {api_key_var: "YOUR_API_KEY_HERE"}
write_env_file(folder_path, env_vars)
if api_key_value.strip():
env_vars = {api_key_var: api_key_value}
write_env_file(folder_path, env_vars)
click.secho("API key saved to .env file", fg="green")
else:
click.secho("No API key provided. Skipping .env file creation.", fg="yellow")
env_vars["MODEL"] = selected_model
click.secho(f"Selected model: {selected_model}", fg="green")
# env_vars['MODEL'] = model
# click.secho(f"Selected model: {model}", fg="green")
package_dir = Path(__file__).parent
templates_dir = package_dir / "templates" / "crew"

View File

@@ -1,91 +1,67 @@
import json
import time
from collections import defaultdict
from pathlib import Path
import click
import requests
from crewai.cli.constants import JSON_URL, MODELS, PROVIDERS
from collections import defaultdict
import click
from pathlib import Path
from crewai.cli.constants import PROVIDERS, MODELS, JSON_URL
def select_choice(prompt_message, choices):
"""
Presents a list of choices to the user and prompts them to select one.
Args:
- prompt_message (str): The message to display to the user before presenting the choices.
- choices (list): A list of options to present to the user.
Returns:
- str: The selected choice from the list, or None if the user chooses to quit.
- str: The selected choice from the list, or None if the operation is aborted or an invalid selection is made.
"""
provider_models = get_provider_data()
if not provider_models:
return
click.secho(prompt_message, fg="cyan")
for idx, choice in enumerate(choices, start=1):
click.secho(f"{idx}. {choice}", fg="cyan")
click.secho("q. Quit", fg="cyan")
while True:
choice = click.prompt(
"Enter the number of your choice or 'q' to quit", type=str
)
if choice.lower() == "q":
return None
try:
selected_index = int(choice) - 1
if 0 <= selected_index < len(choices):
return choices[selected_index]
except ValueError:
pass
click.secho(
"Invalid selection. Please select a number between 1 and 6 or 'q' to quit.",
fg="red",
)
try:
selected_index = click.prompt("Enter the number of your choice", type=int) - 1
except click.exceptions.Abort:
click.secho("Operation aborted by the user.", fg="red")
return None
if not (0 <= selected_index < len(choices)):
click.secho("Invalid selection.", fg="red")
return None
return choices[selected_index]
def select_provider(provider_models):
"""
Presents a list of providers to the user and prompts them to select one.
Args:
- provider_models (dict): A dictionary of provider models.
Returns:
- str: The selected provider
- None: If user explicitly quits
- str: The selected provider, or None if the operation is aborted or an invalid selection is made.
"""
predefined_providers = [p.lower() for p in PROVIDERS]
all_providers = sorted(set(predefined_providers + list(provider_models.keys())))
provider = select_choice(
"Select a provider to set up:", predefined_providers + ["other"]
)
if provider is None: # User typed 'q'
provider = select_choice("Select a provider to set up:", predefined_providers + ['other'])
if not provider:
return None
provider = provider.lower()
if provider == "other":
if provider == 'other':
provider = select_choice("Select a provider from the full list:", all_providers)
if provider is None: # User typed 'q'
if not provider:
return None
return provider.lower() if provider else False
return provider
def select_model(provider, provider_models):
"""
Presents a list of models for a given provider to the user and prompts them to select one.
Args:
- provider (str): The provider for which to select a model.
- provider_models (dict): A dictionary of provider models.
Returns:
- str: The selected model, or None if the operation is aborted or an invalid selection is made.
"""
@@ -100,49 +76,37 @@ def select_model(provider, provider_models):
click.secho(f"No models available for provider '{provider}'.", fg="red")
return None
selected_model = select_choice(
f"Select a model to use for {provider.capitalize()}:", available_models
)
selected_model = select_choice(f"Select a model to use for {provider.capitalize()}:", available_models)
return selected_model
def load_provider_data(cache_file, cache_expiry):
"""
Loads provider data from a cache file if it exists and is not expired. If the cache is expired or corrupted, it fetches the data from the web.
Args:
- cache_file (Path): The path to the cache file.
- cache_expiry (int): The cache expiry time in seconds.
Returns:
- dict or None: The loaded provider data or None if the operation fails.
"""
current_time = time.time()
if (
cache_file.exists()
and (current_time - cache_file.stat().st_mtime) < cache_expiry
):
if cache_file.exists() and (current_time - cache_file.stat().st_mtime) < cache_expiry:
data = read_cache_file(cache_file)
if data:
return data
click.secho(
"Cache is corrupted. Fetching provider data from the web...", fg="yellow"
)
click.secho("Cache is corrupted. Fetching provider data from the web...", fg="yellow")
else:
click.secho(
"Cache expired or not found. Fetching provider data from the web...",
fg="cyan",
)
click.secho("Cache expired or not found. Fetching provider data from the web...", fg="cyan")
return fetch_provider_data(cache_file)
def read_cache_file(cache_file):
"""
Reads and returns the JSON content from a cache file. Returns None if the file contains invalid JSON.
Args:
- cache_file (Path): The path to the cache file.
Returns:
- dict or None: The JSON content of the cache file or None if the JSON is invalid.
"""
@@ -152,14 +116,13 @@ def read_cache_file(cache_file):
except json.JSONDecodeError:
return None
def fetch_provider_data(cache_file):
"""
Fetches provider data from a specified URL and caches it to a file.
Args:
- cache_file (Path): The path to the cache file.
Returns:
- dict or None: The fetched provider data or None if the operation fails.
"""
@@ -176,42 +139,38 @@ def fetch_provider_data(cache_file):
click.secho("Error parsing provider data. Invalid JSON format.", fg="red")
return None
def download_data(response):
"""
Downloads data from a given HTTP response and returns the JSON content.
Args:
- response (requests.Response): The HTTP response object.
Returns:
- dict: The JSON content of the response.
"""
total_size = int(response.headers.get("content-length", 0))
total_size = int(response.headers.get('content-length', 0))
block_size = 8192
data_chunks = []
with click.progressbar(
length=total_size, label="Downloading", show_pos=True
) as progress_bar:
with click.progressbar(length=total_size, label='Downloading', show_pos=True) as progress_bar:
for chunk in response.iter_content(block_size):
if chunk:
data_chunks.append(chunk)
progress_bar.update(len(chunk))
data_content = b"".join(data_chunks)
return json.loads(data_content.decode("utf-8"))
data_content = b''.join(data_chunks)
return json.loads(data_content.decode('utf-8'))
def get_provider_data():
"""
Retrieves provider data from a cache file, filters out models based on provider criteria, and returns a dictionary of providers mapped to their models.
Returns:
- dict or None: A dictionary of providers mapped to their models or None if the operation fails.
"""
cache_dir = Path.home() / ".crewai"
cache_dir = Path.home() / '.crewai'
cache_dir.mkdir(exist_ok=True)
cache_file = cache_dir / "provider_cache.json"
cache_expiry = 24 * 3600
cache_file = cache_dir / 'provider_cache.json'
cache_expiry = 24 * 3600
data = load_provider_data(cache_file, cache_expiry)
if not data:
@@ -220,8 +179,8 @@ def get_provider_data():
provider_models = defaultdict(list)
for model_name, properties in data.items():
provider = properties.get("litellm_provider", "").strip().lower()
if "http" in provider or provider == "other":
if 'http' in provider or provider == 'other':
continue
if provider:
provider_models[provider].append(model_name)
return provider_models
return provider_models

View File

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
authors = [{ name = "Your Name", email = "you@example.com" }]
requires-python = ">=3.10,<=3.13"
dependencies = [
"crewai[tools]>=0.75.1,<1.0.0"
"crewai[tools]>=0.74.2,<1.0.0"
]
[project.scripts]

View File

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
authors = [{ name = "Your Name", email = "you@example.com" }]
requires-python = ">=3.10,<=3.13"
dependencies = [
"crewai[tools]>=0.75.1,<1.0.0",
"crewai[tools]>=0.74.2,<1.0.0",
]
[project.scripts]

View File

@@ -6,7 +6,7 @@ authors = ["Your Name <you@example.com>"]
[tool.poetry.dependencies]
python = ">=3.10,<=3.13"
crewai = { extras = ["tools"], version = ">=0.75.1,<1.0.0" }
crewai = { extras = ["tools"], version = ">=0.74.2,<1.0.0" }
asyncio = "*"
[tool.poetry.scripts]

View File

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
authors = ["Your Name <you@example.com>"]
requires-python = ">=3.10,<=3.13"
dependencies = [
"crewai[tools]>=0.75.1,<1.0.0"
"crewai[tools]>=0.74.2,<1.0.0"
]
[project.scripts]

View File

@@ -5,6 +5,6 @@ description = "Power up your crews with {{folder_name}}"
readme = "README.md"
requires-python = ">=3.10,<=3.13"
dependencies = [
"crewai[tools]>=0.75.1"
"crewai[tools]>=0.74.2"
]

View File

@@ -435,16 +435,15 @@ class Crew(BaseModel):
self, n_iterations: int, filename: str, inputs: Optional[Dict[str, Any]] = {}
) -> None:
"""Trains the crew for a given number of iterations."""
train_crew = self.copy()
train_crew._setup_for_training(filename)
self._setup_for_training(filename)
for n_iteration in range(n_iterations):
train_crew._train_iteration = n_iteration
train_crew.kickoff(inputs=inputs)
self._train_iteration = n_iteration
self.kickoff(inputs=inputs)
training_data = CrewTrainingHandler(TRAINING_DATA_FILE).load()
for agent in train_crew.agents:
for agent in self.agents:
result = TaskEvaluator(agent).evaluate_training_data(
training_data=training_data, agent_id=str(agent.id)
)
@@ -988,19 +987,17 @@ class Crew(BaseModel):
inputs: Optional[Dict[str, Any]] = None,
) -> None:
"""Test and evaluate the Crew with the given inputs for n iterations concurrently using concurrent.futures."""
test_crew = self.copy()
self._test_execution_span = test_crew._telemetry.test_execution_span(
test_crew,
self._test_execution_span = self._telemetry.test_execution_span(
self,
n_iterations,
inputs,
openai_model_name, # type: ignore[arg-type]
) # type: ignore[arg-type]
evaluator = CrewEvaluator(test_crew, openai_model_name) # type: ignore[arg-type]
evaluator = CrewEvaluator(self, openai_model_name) # type: ignore[arg-type]
for i in range(1, n_iterations + 1):
evaluator.set_iteration(i)
test_crew.kickoff(inputs=inputs)
self.kickoff(inputs=inputs)
evaluator.print_crew_evaluation_result()

View File

@@ -9,7 +9,6 @@ from unittest.mock import MagicMock, patch
import instructor
import pydantic_core
import pytest
from crewai.agent import Agent
from crewai.agents.cache import CacheHandler
from crewai.crew import Crew
@@ -498,7 +497,6 @@ def test_cache_hitting_between_agents():
@pytest.mark.vcr(filter_headers=["authorization"])
def test_api_calls_throttling(capsys):
from unittest.mock import patch
from crewai_tools import tool
@tool
@@ -781,14 +779,11 @@ def test_async_task_execution_call_count():
list_important_history.output = mock_task_output
write_article.output = mock_task_output
with (
patch.object(
Task, "execute_sync", return_value=mock_task_output
) as mock_execute_sync,
patch.object(
Task, "execute_async", return_value=mock_future
) as mock_execute_async,
):
with patch.object(
Task, "execute_sync", return_value=mock_task_output
) as mock_execute_sync, patch.object(
Task, "execute_async", return_value=mock_future
) as mock_execute_async:
crew.kickoff()
assert mock_execute_async.call_count == 2
@@ -1110,7 +1105,6 @@ def test_dont_set_agents_step_callback_if_already_set():
@pytest.mark.vcr(filter_headers=["authorization"])
def test_crew_function_calling_llm():
from unittest.mock import patch
from crewai_tools import tool
llm = "gpt-4o"
@@ -1454,6 +1448,52 @@ def test_crew_does_not_interpolate_without_inputs():
interpolate_task_inputs.assert_not_called()
# def test_crew_partial_inputs():
# agent = Agent(
# role="{topic} Researcher",
# goal="Express hot takes on {topic}.",
# backstory="You have a lot of experience with {topic}.",
# )
# task = Task(
# description="Give me an analysis around {topic}.",
# expected_output="{points} bullet points about {topic}.",
# )
# crew = Crew(agents=[agent], tasks=[task], inputs={"topic": "AI"})
# inputs = {"topic": "AI"}
# crew._interpolate_inputs(inputs=inputs) # Manual call for now
# assert crew.tasks[0].description == "Give me an analysis around AI."
# assert crew.tasks[0].expected_output == "{points} bullet points about AI."
# assert crew.agents[0].role == "AI Researcher"
# assert crew.agents[0].goal == "Express hot takes on AI."
# assert crew.agents[0].backstory == "You have a lot of experience with AI."
# def test_crew_invalid_inputs():
# agent = Agent(
# role="{topic} Researcher",
# goal="Express hot takes on {topic}.",
# backstory="You have a lot of experience with {topic}.",
# )
# task = Task(
# description="Give me an analysis around {topic}.",
# expected_output="{points} bullet points about {topic}.",
# )
# crew = Crew(agents=[agent], tasks=[task], inputs={"subject": "AI"})
# inputs = {"subject": "AI"}
# crew._interpolate_inputs(inputs=inputs) # Manual call for now
# assert crew.tasks[0].description == "Give me an analysis around {topic}."
# assert crew.tasks[0].expected_output == "{points} bullet points about {topic}."
# assert crew.agents[0].role == "{topic} Researcher"
# assert crew.agents[0].goal == "Express hot takes on {topic}."
# assert crew.agents[0].backstory == "You have a lot of experience with {topic}."
def test_task_callback_on_crew():
from unittest.mock import MagicMock, patch
@@ -1730,10 +1770,7 @@ def test_manager_agent_with_tools_raises_exception():
@patch("crewai.crew.Crew.kickoff")
@patch("crewai.crew.CrewTrainingHandler")
@patch("crewai.crew.TaskEvaluator")
@patch("crewai.crew.Crew.copy")
def test_crew_train_success(
copy_mock, task_evaluator, crew_training_handler, kickoff_mock
):
def test_crew_train_success(task_evaluator, crew_training_handler, kickoff):
task = Task(
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.",
@@ -1744,19 +1781,9 @@ def test_crew_train_success(
agents=[researcher, writer],
tasks=[task],
)
# Create a mock for the copied crew
copy_mock.return_value = crew
crew.train(
n_iterations=2, inputs={"topic": "AI"}, filename="trained_agents_data.pkl"
)
# Ensure kickoff is called on the copied crew
kickoff_mock.assert_has_calls(
[mock.call(inputs={"topic": "AI"}), mock.call(inputs={"topic": "AI"})]
)
task_evaluator.assert_has_calls(
[
mock.call(researcher),
@@ -1795,6 +1822,10 @@ def test_crew_train_success(
]
)
kickoff.assert_has_calls(
[mock.call(inputs={"topic": "AI"}), mock.call(inputs={"topic": "AI"})]
)
def test_crew_train_error():
task = Task(
@@ -1809,7 +1840,7 @@ def test_crew_train_error():
)
with pytest.raises(TypeError) as e:
crew.train() # type: ignore purposefully throwing err
crew.train()
assert "train() missing 1 required positional argument: 'n_iterations'" in str(
e
)
@@ -2505,9 +2536,8 @@ 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(kickoff_mock, copy_mock, crew_evaluator):
def test_crew_testing_function(mock_kickoff, crew_evaluator):
task = Task(
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.",
@@ -2518,15 +2548,11 @@ def test_crew_testing_function(kickoff_mock, copy_mock, crew_evaluator):
agents=[researcher],
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(
assert len(mock_kickoff.mock_calls) == n_iterations
mock_kickoff.assert_has_calls(
[mock.call(inputs={"topic": "AI"}), mock.call(inputs={"topic": "AI"})]
)

2
uv.lock generated
View File

@@ -627,7 +627,7 @@ wheels = [
[[package]]
name = "crewai"
version = "0.75.1"
version = "0.74.2"
source = { editable = "." }
dependencies = [
{ name = "appdirs" },