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4 Commits

Author SHA1 Message Date
Lucas Gomide
2fccd5f8bc wip 2026-02-09 15:54:52 -03:00
Lucas Gomide
89556605cd feat: improve JSON schema handling for MCP tools
- Convert enum constraints to Literal types
- Handle format constraints (date, date-time)
- Preserve original MCP tool names for server calls
2026-02-05 12:06:50 -03:00
Lucas Gomide
ff00055e2c feat: use original tool name instead of the normalized one 2026-02-05 12:01:15 -03:00
Lucas Gomide
507aec7a48 wip 2026-02-05 11:39:55 -03:00
56 changed files with 1406 additions and 2098 deletions

View File

@@ -33,11 +33,8 @@ def test_brave_tool_search(mock_get, brave_tool):
mock_get.return_value.json.return_value = mock_response
result = brave_tool.run(query="test")
data = json.loads(result)
assert isinstance(data, list)
assert len(data) >= 1
assert data[0]["title"] == "Test Title"
assert data[0]["url"] == "http://test.com"
assert "Test Title" in result
assert "http://test.com" in result
@patch("requests.get")

View File

@@ -14,7 +14,7 @@ dependencies = [
"instructor>=1.3.3",
# Text Processing
"pdfplumber~=0.11.4",
"regex~=2026.1.15",
"regex~=2024.9.11",
# Telemetry and Monitoring
"opentelemetry-api~=1.34.0",
"opentelemetry-sdk~=1.34.0",
@@ -36,7 +36,7 @@ dependencies = [
"json5~=0.10.0",
"portalocker~=2.7.0",
"pydantic-settings~=2.10.1",
"mcp~=1.26.0",
"mcp~=1.23.1",
"uv~=0.9.13",
"aiosqlite~=0.21.0",
]

View File

@@ -24,6 +24,7 @@ from pydantic import (
)
from typing_extensions import Self
from crewai.agent.json_schema_converter import JSONSchemaConverter
from crewai.agent.utils import (
ahandle_knowledge_retrieval,
apply_training_data,
@@ -1178,6 +1179,7 @@ class Agent(BaseAgent):
tools = []
for tool_def in tools_list:
tool_name = tool_def.get("name", "")
original_tool_name = tool_def.get("original_name", tool_name)
if not tool_name:
continue
@@ -1199,6 +1201,7 @@ class Agent(BaseAgent):
tool_name=tool_name,
tool_schema=tool_schema,
server_name=server_name,
original_tool_name=original_tool_name,
)
tools.append(native_tool)
except Exception as e:
@@ -1213,26 +1216,63 @@ class Agent(BaseAgent):
raise RuntimeError(f"Failed to get native MCP tools: {e}") from e
def _get_amp_mcp_tools(self, amp_ref: str) -> list[BaseTool]:
"""Get tools from CrewAI AMP MCP marketplace."""
# Parse: "crewai-amp:mcp-name" or "crewai-amp:mcp-name#tool_name"
"""Get tools from CrewAI AMP MCP via crewai-oauth service.
Fetches MCP server configuration with tokens injected from crewai-oauth,
then uses _get_native_mcp_tools to connect and discover tools.
"""
# Parse: "crewai-amp:mcp-slug" or "crewai-amp:mcp-slug#tool_name"
amp_part = amp_ref.replace("crewai-amp:", "")
if "#" in amp_part:
mcp_name, specific_tool = amp_part.split("#", 1)
mcp_slug, specific_tool = amp_part.split("#", 1)
else:
mcp_name, specific_tool = amp_part, None
mcp_slug, specific_tool = amp_part, None
# Call AMP API to get MCP server URLs
mcp_servers = self._fetch_amp_mcp_servers(mcp_name)
# Fetch MCP config from crewai-oauth (with tokens injected)
mcp_config_dict = self._fetch_amp_mcp_config(mcp_slug)
tools = []
for server_config in mcp_servers:
server_ref = server_config["url"]
if specific_tool:
server_ref += f"#{specific_tool}"
server_tools = self._get_external_mcp_tools(server_ref)
tools.extend(server_tools)
if not mcp_config_dict:
self._logger.log(
"warning", f"Failed to fetch MCP config for '{mcp_slug}' from crewai-oauth"
)
return []
return tools
# Convert dict to MCPServerConfig (MCPServerHTTP or MCPServerSSE)
config_type = mcp_config_dict.get("type", "http")
if config_type == "sse":
mcp_config = MCPServerSSE(
url=mcp_config_dict["url"],
headers=mcp_config_dict.get("headers"),
cache_tools_list=mcp_config_dict.get("cache_tools_list", False),
)
else:
mcp_config = MCPServerHTTP(
url=mcp_config_dict["url"],
headers=mcp_config_dict.get("headers"),
streamable=mcp_config_dict.get("streamable", True),
cache_tools_list=mcp_config_dict.get("cache_tools_list", False),
)
# Apply tool filter if specific tool requested
if specific_tool:
from crewai.mcp.filters import create_static_tool_filter
mcp_config.tool_filter = create_static_tool_filter(
allowed_tool_names=[specific_tool]
)
# Use native MCP tools to connect and discover tools
try:
tools, client = self._get_native_mcp_tools(mcp_config)
if client:
self._mcp_clients.append(client)
return tools
except Exception as e:
self._logger.log(
"warning", f"Failed to get MCP tools from '{mcp_slug}': {e}"
)
return []
@staticmethod
def _extract_server_name(server_url: str) -> str:
@@ -1389,6 +1429,9 @@ class Agent(BaseAgent):
}
return schemas
# Shared JSON Schema converter instance
_schema_converter: JSONSchemaConverter = JSONSchemaConverter()
def _json_schema_to_pydantic(
self, tool_name: str, json_schema: dict[str, Any]
) -> type:
@@ -1401,77 +1444,62 @@ class Agent(BaseAgent):
Returns:
Pydantic BaseModel class
"""
from pydantic import Field, create_model
return self._schema_converter.json_schema_to_pydantic(tool_name, json_schema)
properties = json_schema.get("properties", {})
required_fields = json_schema.get("required", [])
def _fetch_amp_mcp_config(self, mcp_slug: str) -> dict[str, Any] | None:
"""Fetch MCP server configuration from crewai-oauth service.
field_definitions: dict[str, Any] = {}
Returns MCPServerConfig dict with tokens injected, ready for use with
_get_native_mcp_tools.
for field_name, field_schema in properties.items():
field_type = self._json_type_to_python(field_schema)
field_description = field_schema.get("description", "")
is_required = field_name in required_fields
if is_required:
field_definitions[field_name] = (
field_type,
Field(..., description=field_description),
)
else:
field_definitions[field_name] = (
field_type | None,
Field(default=None, description=field_description),
)
model_name = f"{tool_name.replace('-', '_').replace(' ', '_')}Schema"
return create_model(model_name, **field_definitions) # type: ignore[no-any-return]
def _json_type_to_python(self, field_schema: dict[str, Any]) -> type:
"""Convert JSON Schema type to Python type.
Environment variables:
CREWAI_OAUTH_URL: Base URL of crewai-oauth service
CREWAI_OAUTH_API_KEY: API key for authenticating with crewai-oauth
Args:
field_schema: JSON Schema field definition
mcp_slug: The MCP server slug (e.g., "notion-mcp-abc123")
Returns:
Python type
Dict with type, url, headers, streamable, cache_tools_list, or None if failed.
"""
import os
json_type = field_schema.get("type")
import requests
if "anyOf" in field_schema:
types: list[type] = []
for option in field_schema["anyOf"]:
if "const" in option:
types.append(str)
else:
types.append(self._json_type_to_python(option))
unique_types = list(set(types))
if len(unique_types) > 1:
result: Any = unique_types[0]
for t in unique_types[1:]:
result = result | t
return result # type: ignore[no-any-return]
return unique_types[0]
try:
endpoint = f"http://localhost:8787/mcps/{mcp_slug}/config"
response = requests.get(
endpoint,
headers={"Authorization": "Bearer 6b327f9ebe62726590f8de8f624cf018ad4765fecb7373f9db475a940ad546d0"},
timeout=30,
)
type_mapping: dict[str | None, type] = {
"string": str,
"number": float,
"integer": int,
"boolean": bool,
"array": list,
"object": dict,
}
if response.status_code == 200:
return response.json()
elif response.status_code == 400:
error_data = response.json()
self._logger.log(
"warning",
f"MCP '{mcp_slug}' is not connected: {error_data.get('error_description', 'Unknown error')}",
)
return None
elif response.status_code == 404:
self._logger.log(
"warning", f"MCP server '{mcp_slug}' not found in crewai-oauth"
)
return None
else:
self._logger.log(
"warning",
f"Failed to fetch MCP config from crewai-oauth: HTTP {response.status_code}",
)
return None
return type_mapping.get(json_type, Any)
@staticmethod
def _fetch_amp_mcp_servers(mcp_name: str) -> list[dict[str, Any]]:
"""Fetch MCP server configurations from CrewAI AMP API."""
# TODO: Implement AMP API call to "integrations/mcps" endpoint
# Should return list of server configs with URLs
return []
except requests.exceptions.RequestException as e:
self._logger.log(
"warning", f"Failed to connect to crewai-oauth: {e}"
)
return None
@staticmethod
def get_multimodal_tools() -> Sequence[BaseTool]:

View File

@@ -0,0 +1,399 @@
from typing import Any, Literal, Type, Union, get_args
from pydantic import Field, create_model
from pydantic.fields import FieldInfo
import datetime
import uuid
class JSONSchemaConverter:
"""Converts JSON Schema definitions to Python/Pydantic types."""
def json_schema_to_pydantic(
self, tool_name: str, json_schema: dict[str, Any]
) -> Type[Any]:
"""Convert JSON Schema to Pydantic model for tool arguments.
Args:
tool_name: Name of the tool (used for model naming)
json_schema: JSON Schema dict with 'properties', 'required', etc.
Returns:
Pydantic BaseModel class
"""
properties = json_schema.get("properties", {})
required_fields = json_schema.get("required", [])
model_name = f"{tool_name.replace('-', '_').replace(' ', '_')}Schema"
return self._create_pydantic_model(model_name, properties, required_fields)
def _json_type_to_python(
self, field_schema: dict[str, Any], field_name: str = "Field"
) -> Type[Any]:
"""Convert JSON Schema type to Python type, handling nested structures.
Args:
field_schema: JSON Schema field definition
field_name: Name of the field (used for nested model naming)
Returns:
Python type (may be a dynamically created Pydantic model for objects/arrays)
"""
if not field_schema:
return Any
# Handle $ref if needed
if "$ref" in field_schema:
# You might want to implement reference resolution here
return Any
# Handle enum constraint - create Literal type
if "enum" in field_schema:
return self._handle_enum(field_schema)
# Handle different schema constructs in order of precedence
if "allOf" in field_schema:
return self._handle_allof(field_schema, field_name)
if "anyOf" in field_schema or "oneOf" in field_schema:
return self._handle_union_schemas(field_schema, field_name)
json_type = field_schema.get("type")
if isinstance(json_type, list):
return self._handle_type_union(json_type)
if json_type == "array":
return self._handle_array_type(field_schema, field_name)
if json_type == "object":
return self._handle_object_type(field_schema, field_name)
# Handle format for string types
if json_type == "string" and "format" in field_schema:
return self._get_formatted_type(field_schema["format"])
return self._get_simple_type(json_type)
def _get_formatted_type(self, format_type: str) -> Type[Any]:
"""Get Python type for JSON Schema format constraint.
Args:
format_type: JSON Schema format string (date, date-time, email, etc.)
Returns:
Appropriate Python type for the format
"""
format_mapping: dict[str, Type[Any]] = {
"date": datetime.date,
"date-time": datetime.datetime,
"time": datetime.time,
"email": str, # Could use EmailStr from pydantic
"uri": str,
"uuid": str, # Could use UUID
"hostname": str,
"ipv4": str,
"ipv6": str,
}
return format_mapping.get(format_type, str)
def _handle_enum(self, field_schema: dict[str, Any]) -> Type[Any]:
"""Handle enum constraint by creating a Literal type.
Args:
field_schema: Schema containing enum values
Returns:
Literal type with enum values
"""
enum_values = field_schema.get("enum", [])
if not enum_values:
return str
# Filter out None values for the Literal type
non_null_values = [v for v in enum_values if v is not None]
if not non_null_values:
return type(None)
# Create Literal type with enum values
# For strings, create Literal["value1", "value2", ...]
if all(isinstance(v, str) for v in non_null_values):
literal_type = Literal[tuple(non_null_values)] # type: ignore[valid-type]
# If null is in enum, make it optional
if None in enum_values:
return literal_type | None # type: ignore[return-value]
return literal_type # type: ignore[return-value]
# For mixed types or non-strings, fall back to the base type
json_type = field_schema.get("type", "string")
return self._get_simple_type(json_type)
def _handle_allof(
self, field_schema: dict[str, Any], field_name: str
) -> Type[Any]:
"""Handle allOf schema composition by merging all schemas.
Args:
field_schema: Schema containing allOf
field_name: Name for the generated model
Returns:
Merged Pydantic model or basic type
"""
merged_properties: dict[str, Any] = {}
merged_required: list[str] = []
found_type: str | None = None
for sub_schema in field_schema["allOf"]:
# Collect type information
if sub_schema.get("type"):
found_type = sub_schema.get("type")
# Merge properties
if sub_schema.get("properties"):
merged_properties.update(sub_schema["properties"])
# Merge required fields
if sub_schema.get("required"):
merged_required.extend(sub_schema["required"])
# Handle nested anyOf/oneOf - merge properties from all variants
for union_key in ("anyOf", "oneOf"):
if union_key in sub_schema:
for variant in sub_schema[union_key]:
if variant.get("properties"):
# Merge variant properties (will be optional)
for prop_name, prop_schema in variant["properties"].items():
if prop_name not in merged_properties:
merged_properties[prop_name] = prop_schema
# If we found properties, create a merged object model
if merged_properties:
return self._create_pydantic_model(
field_name, merged_properties, merged_required
)
# Fallback: return the found type or dict
if found_type == "object":
return dict
elif found_type == "array":
return list
return dict # Default for complex allOf
def _handle_union_schemas(
self, field_schema: dict[str, Any], field_name: str
) -> Type[Any]:
"""Handle anyOf/oneOf union schemas.
Args:
field_schema: Schema containing anyOf or oneOf
field_name: Name for nested types
Returns:
Union type combining all options
"""
key = "anyOf" if "anyOf" in field_schema else "oneOf"
types: list[Type[Any]] = []
for option in field_schema[key]:
if "const" in option:
# For const values, use string type
# Could use Literal[option["const"]] for more precision
types.append(str)
else:
types.append(self._json_type_to_python(option, field_name))
return self._build_union_type(types)
def _handle_type_union(self, json_types: list[str]) -> Type[Any]:
"""Handle union types from type arrays.
Args:
json_types: List of JSON Schema type strings
Returns:
Union of corresponding Python types
"""
type_mapping: dict[str, Type[Any]] = {
"string": str,
"number": float,
"integer": int,
"boolean": bool,
"null": type(None),
"array": list,
"object": dict,
}
types = [type_mapping.get(t, Any) for t in json_types]
return self._build_union_type(types)
def _handle_array_type(
self, field_schema: dict[str, Any], field_name: str
) -> Type[Any]:
"""Handle array type with typed items.
Args:
field_schema: Schema with type="array"
field_name: Name for item types
Returns:
list or list[ItemType]
"""
items_schema = field_schema.get("items")
if items_schema:
item_type = self._json_type_to_python(items_schema, f"{field_name}Item")
return list[item_type] # type: ignore[valid-type]
return list
def _handle_object_type(
self, field_schema: dict[str, Any], field_name: str
) -> Type[Any]:
"""Handle object type with properties.
Args:
field_schema: Schema with type="object"
field_name: Name for the generated model
Returns:
Pydantic model or dict
"""
properties = field_schema.get("properties")
if properties:
required_fields = field_schema.get("required", [])
return self._create_pydantic_model(field_name, properties, required_fields)
# Object without properties (e.g., additionalProperties only)
return dict
def _create_pydantic_model(
self,
field_name: str,
properties: dict[str, Any],
required_fields: list[str],
) -> Type[Any]:
"""Create a Pydantic model from properties.
Args:
field_name: Base name for the model
properties: Property schemas
required_fields: List of required property names
Returns:
Dynamically created Pydantic model
"""
model_name = f"Generated_{field_name}_{uuid.uuid4().hex[:8]}"
field_definitions: dict[str, Any] = {}
for prop_name, prop_schema in properties.items():
prop_type = self._json_type_to_python(prop_schema, prop_name.title())
prop_description = self._build_field_description(prop_schema)
is_required = prop_name in required_fields
if is_required:
field_definitions[prop_name] = (
prop_type,
Field(..., description=prop_description),
)
else:
field_definitions[prop_name] = (
prop_type | None,
Field(default=None, description=prop_description),
)
return create_model(model_name, **field_definitions) # type: ignore[return-value]
def _build_field_description(self, prop_schema: dict[str, Any]) -> str:
"""Build a comprehensive field description including constraints.
Args:
prop_schema: Property schema with description and constraints
Returns:
Enhanced description with format, enum, and other constraints
"""
parts: list[str] = []
# Start with the original description
description = prop_schema.get("description", "")
if description:
parts.append(description)
# Add format constraint
format_type = prop_schema.get("format")
if format_type:
parts.append(f"Format: {format_type}")
# Add enum constraint (if not already handled by Literal type)
enum_values = prop_schema.get("enum")
if enum_values:
enum_str = ", ".join(repr(v) for v in enum_values)
parts.append(f"Allowed values: [{enum_str}]")
# Add pattern constraint
pattern = prop_schema.get("pattern")
if pattern:
parts.append(f"Pattern: {pattern}")
# Add min/max constraints
minimum = prop_schema.get("minimum")
maximum = prop_schema.get("maximum")
if minimum is not None:
parts.append(f"Minimum: {minimum}")
if maximum is not None:
parts.append(f"Maximum: {maximum}")
min_length = prop_schema.get("minLength")
max_length = prop_schema.get("maxLength")
if min_length is not None:
parts.append(f"Min length: {min_length}")
if max_length is not None:
parts.append(f"Max length: {max_length}")
# Add examples if available
examples = prop_schema.get("examples")
if examples:
examples_str = ", ".join(repr(e) for e in examples[:3]) # Limit to 3
parts.append(f"Examples: {examples_str}")
return ". ".join(parts) if parts else ""
def _get_simple_type(self, json_type: str | None) -> Type[Any]:
"""Map simple JSON Schema types to Python types.
Args:
json_type: JSON Schema type string
Returns:
Corresponding Python type
"""
simple_type_mapping: dict[str | None, Type[Any]] = {
"string": str,
"number": float,
"integer": int,
"boolean": bool,
"null": type(None),
}
return simple_type_mapping.get(json_type, Any)
def _build_union_type(self, types: list[Type[Any]]) -> Type[Any]:
"""Build a union type from a list of types.
Args:
types: List of Python types to combine
Returns:
Union type or single type if only one unique type
"""
# Remove duplicates while preserving order
unique_types = list(dict.fromkeys(types))
if len(unique_types) == 1:
return unique_types[0]
# Build union using | operator
result = unique_types[0]
for t in unique_types[1:]:
result = result | t
return result # type: ignore[no-any-return]

View File

@@ -37,10 +37,9 @@ class BaseAgentAdapter(BaseAgent, ABC):
tools: Optional list of BaseTool instances to be configured
"""
@abstractmethod
def configure_structured_output(self, task: Any) -> None:
def configure_structured_output(self, structured_output: Any) -> None:
"""Configure the structured output for the specific agent implementation.
Args:
task: The task object containing output format specifications.
structured_output: The structured output to be configured
"""

View File

@@ -814,7 +814,6 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
agent_key=agent_key,
),
)
error_event_emitted = False
track_delegation_if_needed(func_name, args_dict, self.task)
@@ -897,7 +896,6 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
error=e,
),
)
error_event_emitted = True
elif max_usage_reached and original_tool:
# Return error message when max usage limit is reached
result = f"Tool '{func_name}' has reached its usage limit of {original_tool.max_usage_count} times and cannot be used anymore."
@@ -925,20 +923,20 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
color="red",
)
if not error_event_emitted:
crewai_event_bus.emit(
self,
event=ToolUsageFinishedEvent(
output=result,
tool_name=func_name,
tool_args=args_dict,
from_agent=self.agent,
from_task=self.task,
agent_key=agent_key,
started_at=started_at,
finished_at=datetime.now(),
),
)
# Emit tool usage finished event
crewai_event_bus.emit(
self,
event=ToolUsageFinishedEvent(
output=result,
tool_name=func_name,
tool_args=args_dict,
from_agent=self.agent,
from_task=self.task,
agent_key=agent_key,
started_at=started_at,
finished_at=datetime.now(),
),
)
# Append tool result message
tool_message: LLMMessage = {
@@ -1009,7 +1007,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
raise
if self.ask_for_human_input:
formatted_answer = await self._ahandle_human_feedback(formatted_answer)
formatted_answer = self._handle_human_feedback(formatted_answer)
self._create_short_term_memory(formatted_answer)
self._create_long_term_memory(formatted_answer)
@@ -1508,20 +1506,6 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
provider = get_provider()
return provider.handle_feedback(formatted_answer, self)
async def _ahandle_human_feedback(
self, formatted_answer: AgentFinish
) -> AgentFinish:
"""Process human feedback asynchronously via the configured provider.
Args:
formatted_answer: Initial agent result.
Returns:
Final answer after feedback.
"""
provider = get_provider()
return await provider.handle_feedback_async(formatted_answer, self)
def _is_training_mode(self) -> bool:
"""Check if training mode is active.

View File

@@ -1,8 +1,6 @@
import os
from typing import Any
from urllib.parse import urljoin
import httpx
import os
import requests
from crewai.cli.config import Settings
@@ -35,11 +33,7 @@ class PlusAPI:
if settings.org_uuid:
self.headers["X-Crewai-Organization-Id"] = settings.org_uuid
self.base_url = (
os.getenv("CREWAI_PLUS_URL")
or str(settings.enterprise_base_url)
or DEFAULT_CREWAI_ENTERPRISE_URL
)
self.base_url = os.getenv("CREWAI_PLUS_URL") or str(settings.enterprise_base_url) or DEFAULT_CREWAI_ENTERPRISE_URL
def _make_request(
self, method: str, endpoint: str, **kwargs: Any
@@ -55,10 +49,8 @@ class PlusAPI:
def get_tool(self, handle: str) -> requests.Response:
return self._make_request("GET", f"{self.TOOLS_RESOURCE}/{handle}")
async def get_agent(self, handle: str) -> httpx.Response:
url = urljoin(self.base_url, f"{self.AGENTS_RESOURCE}/{handle}")
async with httpx.AsyncClient() as client:
return await client.get(url, headers=self.headers)
def get_agent(self, handle: str) -> requests.Response:
return self._make_request("GET", f"{self.AGENTS_RESOURCE}/{handle}")
def publish_tool(
self,

View File

@@ -43,23 +43,3 @@ def platform_context(integration_token: str) -> Generator[None, Any, None]:
yield
finally:
_platform_integration_token.reset(token)
_current_task_id: contextvars.ContextVar[str | None] = contextvars.ContextVar(
"current_task_id", default=None
)
def set_current_task_id(task_id: str | None) -> contextvars.Token[str | None]:
"""Set the current task ID in the context. Returns a token for reset."""
return _current_task_id.set(task_id)
def reset_current_task_id(token: contextvars.Token[str | None]) -> None:
"""Reset the current task ID to its previous value."""
_current_task_id.reset(token)
def get_current_task_id() -> str | None:
"""Get the current task ID from the context."""
return _current_task_id.get()

View File

@@ -2,9 +2,7 @@
from __future__ import annotations
import asyncio
from contextvars import ContextVar, Token
import sys
from typing import TYPE_CHECKING, Protocol, runtime_checkable
@@ -48,21 +46,13 @@ class ExecutorContext(Protocol):
...
class AsyncExecutorContext(ExecutorContext, Protocol):
"""Extended context for executors that support async invocation."""
async def _ainvoke_loop(self) -> AgentFinish:
"""Invoke the agent loop asynchronously and return the result."""
...
@runtime_checkable
class HumanInputProvider(Protocol):
"""Protocol for human input handling.
Implementations handle the full feedback flow:
- Sync: prompt user, loop until satisfied
- Async: use non-blocking I/O and async invoke loop
- Async: raise exception for external handling
"""
def setup_messages(self, context: ExecutorContext) -> bool:
@@ -96,7 +86,7 @@ class HumanInputProvider(Protocol):
formatted_answer: AgentFinish,
context: ExecutorContext,
) -> AgentFinish:
"""Handle the full human feedback flow synchronously.
"""Handle the full human feedback flow.
Args:
formatted_answer: The agent's current answer.
@@ -110,25 +100,6 @@ class HumanInputProvider(Protocol):
"""
...
async def handle_feedback_async(
self,
formatted_answer: AgentFinish,
context: AsyncExecutorContext,
) -> AgentFinish:
"""Handle the full human feedback flow asynchronously.
Uses non-blocking I/O for user prompts and async invoke loop
for agent re-execution.
Args:
formatted_answer: The agent's current answer.
context: Async executor context for callbacks.
Returns:
The final answer after feedback processing.
"""
...
@staticmethod
def _get_output_string(answer: AgentFinish) -> str:
"""Extract output string from answer.
@@ -145,7 +116,7 @@ class HumanInputProvider(Protocol):
class SyncHumanInputProvider(HumanInputProvider):
"""Default human input provider with sync and async support."""
"""Default synchronous human input via terminal."""
def setup_messages(self, context: ExecutorContext) -> bool:
"""Use standard message setup.
@@ -186,33 +157,6 @@ class SyncHumanInputProvider(HumanInputProvider):
return self._handle_regular_feedback(formatted_answer, feedback, context)
async def handle_feedback_async(
self,
formatted_answer: AgentFinish,
context: AsyncExecutorContext,
) -> AgentFinish:
"""Handle feedback asynchronously without blocking the event loop.
Args:
formatted_answer: The agent's current answer.
context: Async executor context for callbacks.
Returns:
The final answer after feedback processing.
"""
feedback = await self._prompt_input_async(context.crew)
if context._is_training_mode():
return await self._handle_training_feedback_async(
formatted_answer, feedback, context
)
return await self._handle_regular_feedback_async(
formatted_answer, feedback, context
)
# ── Sync helpers ──────────────────────────────────────────────────
@staticmethod
def _handle_training_feedback(
initial_answer: AgentFinish,
@@ -265,62 +209,6 @@ class SyncHumanInputProvider(HumanInputProvider):
return answer
# ── Async helpers ─────────────────────────────────────────────────
@staticmethod
async def _handle_training_feedback_async(
initial_answer: AgentFinish,
feedback: str,
context: AsyncExecutorContext,
) -> AgentFinish:
"""Process training feedback asynchronously (single iteration).
Args:
initial_answer: The agent's initial answer.
feedback: Human feedback string.
context: Async executor context for callbacks.
Returns:
Improved answer after processing feedback.
"""
context._handle_crew_training_output(initial_answer, feedback)
context.messages.append(context._format_feedback_message(feedback))
improved_answer = await context._ainvoke_loop()
context._handle_crew_training_output(improved_answer)
context.ask_for_human_input = False
return improved_answer
async def _handle_regular_feedback_async(
self,
current_answer: AgentFinish,
initial_feedback: str,
context: AsyncExecutorContext,
) -> AgentFinish:
"""Process regular feedback with async iteration loop.
Args:
current_answer: The agent's current answer.
initial_feedback: Initial human feedback string.
context: Async executor context for callbacks.
Returns:
Final answer after all feedback iterations.
"""
feedback = initial_feedback
answer = current_answer
while context.ask_for_human_input:
if feedback.strip() == "":
context.ask_for_human_input = False
else:
context.messages.append(context._format_feedback_message(feedback))
answer = await context._ainvoke_loop()
feedback = await self._prompt_input_async(context.crew)
return answer
# ── I/O ───────────────────────────────────────────────────────────
@staticmethod
def _prompt_input(crew: Crew | None) -> str:
"""Show rich panel and prompt for input.
@@ -374,79 +262,6 @@ class SyncHumanInputProvider(HumanInputProvider):
finally:
formatter.resume_live_updates()
@staticmethod
async def _prompt_input_async(crew: Crew | None) -> str:
"""Show rich panel and prompt for input without blocking the event loop.
Args:
crew: The crew instance for context.
Returns:
User input string from terminal.
"""
from rich.panel import Panel
from rich.text import Text
from crewai.events.event_listener import event_listener
formatter = event_listener.formatter
formatter.pause_live_updates()
try:
if crew and getattr(crew, "_train", False):
prompt_text = (
"TRAINING MODE: Provide feedback to improve the agent's performance.\n\n"
"This will be used to train better versions of the agent.\n"
"Please provide detailed feedback about the result quality and reasoning process."
)
title = "🎓 Training Feedback Required"
else:
prompt_text = (
"Provide feedback on the Final Result above.\n\n"
"• If you are happy with the result, simply hit Enter without typing anything.\n"
"• Otherwise, provide specific improvement requests.\n"
"• You can provide multiple rounds of feedback until satisfied."
)
title = "💬 Human Feedback Required"
content = Text()
content.append(prompt_text, style="yellow")
prompt_panel = Panel(
content,
title=title,
border_style="yellow",
padding=(1, 2),
)
formatter.console.print(prompt_panel)
response = await _async_readline()
if response.strip() != "":
formatter.console.print("\n[cyan]Processing your feedback...[/cyan]")
return response
finally:
formatter.resume_live_updates()
async def _async_readline() -> str:
"""Read a line from stdin using the event loop's native I/O.
Falls back to asyncio.to_thread on platforms where piping stdin
is unsupported.
Returns:
The line read from stdin, with trailing newline stripped.
"""
loop = asyncio.get_running_loop()
try:
reader = asyncio.StreamReader()
protocol = asyncio.StreamReaderProtocol(reader)
await loop.connect_read_pipe(lambda: protocol, sys.stdin)
raw = await reader.readline()
return raw.decode().rstrip("\n")
except (OSError, NotImplementedError, ValueError):
return await asyncio.to_thread(input)
_provider: ContextVar[HumanInputProvider | None] = ContextVar(
"human_input_provider",

View File

@@ -751,8 +751,6 @@ class Crew(FlowTrackable, BaseModel):
for after_callback in self.after_kickoff_callbacks:
result = after_callback(result)
result = self._post_kickoff(result)
self.usage_metrics = self.calculate_usage_metrics()
return result
@@ -766,9 +764,6 @@ class Crew(FlowTrackable, BaseModel):
clear_files(self.id)
detach(token)
def _post_kickoff(self, result: CrewOutput) -> CrewOutput:
return result
def kickoff_for_each(
self,
inputs: list[dict[str, Any]],
@@ -941,8 +936,6 @@ class Crew(FlowTrackable, BaseModel):
for after_callback in self.after_kickoff_callbacks:
result = after_callback(result)
result = self._post_kickoff(result)
self.usage_metrics = self.calculate_usage_metrics()
return result
@@ -1188,9 +1181,6 @@ class Crew(FlowTrackable, BaseModel):
self.manager_agent = manager
manager.crew = self
def _get_execution_start_index(self, tasks: list[Task]) -> int | None:
return None
def _execute_tasks(
self,
tasks: list[Task],
@@ -1207,9 +1197,6 @@ class Crew(FlowTrackable, BaseModel):
Returns:
CrewOutput: Final output of the crew
"""
custom_start = self._get_execution_start_index(tasks)
if custom_start is not None:
start_index = custom_start
task_outputs: list[TaskOutput] = []
futures: list[tuple[Task, Future[TaskOutput], int]] = []
@@ -1318,10 +1305,8 @@ class Crew(FlowTrackable, BaseModel):
if files:
supported_types: list[str] = []
if agent and agent.llm and agent.llm.supports_multimodal():
provider = (
getattr(agent.llm, "provider", None)
or getattr(agent.llm, "model", None)
or "openai"
provider = getattr(agent.llm, "provider", None) or getattr(
agent.llm, "model", "openai"
)
api = getattr(agent.llm, "api", None)
supported_types = get_supported_content_types(provider, api)
@@ -1517,7 +1502,6 @@ class Crew(FlowTrackable, BaseModel):
final_string_output = final_task_output.raw
self._finish_execution(final_string_output)
self.token_usage = self.calculate_usage_metrics()
crewai_event_bus.flush()
crewai_event_bus.emit(
self,
CrewKickoffCompletedEvent(
@@ -2027,13 +2011,7 @@ class Crew(FlowTrackable, BaseModel):
@staticmethod
def _show_tracing_disabled_message() -> None:
"""Show a message when tracing is disabled."""
from crewai.events.listeners.tracing.utils import (
has_user_declined_tracing,
should_suppress_tracing_messages,
)
if should_suppress_tracing_messages():
return
from crewai.events.listeners.tracing.utils import has_user_declined_tracing
console = Console()

View File

@@ -195,7 +195,6 @@ __all__ = [
"ToolUsageFinishedEvent",
"ToolUsageStartedEvent",
"ToolValidateInputErrorEvent",
"_extension_exports",
"crewai_event_bus",
]
@@ -211,29 +210,14 @@ _AGENT_EVENT_MAPPING = {
"LiteAgentExecutionStartedEvent": "crewai.events.types.agent_events",
}
_extension_exports: dict[str, Any] = {}
def __getattr__(name: str) -> Any:
"""Lazy import for agent events and registered extensions."""
"""Lazy import for agent events to avoid circular imports."""
if name in _AGENT_EVENT_MAPPING:
import importlib
module_path = _AGENT_EVENT_MAPPING[name]
module = importlib.import_module(module_path)
return getattr(module, name)
if name in _extension_exports:
import importlib
value = _extension_exports[name]
if isinstance(value, str):
module_path, _, attr_name = value.rpartition(".")
if module_path:
module = importlib.import_module(module_path)
return getattr(module, attr_name)
return importlib.import_module(value)
return value
msg = f"module {__name__!r} has no attribute {name!r}"
raise AttributeError(msg)

View File

@@ -63,7 +63,6 @@ class BaseEvent(BaseModel):
parent_event_id: str | None = None
previous_event_id: str | None = None
triggered_by_event_id: str | None = None
started_event_id: str | None = None
emission_sequence: int | None = None
def to_json(self, exclude: set[str] | None = None) -> Serializable:

View File

@@ -227,39 +227,6 @@ class CrewAIEventsBus:
return decorator
def off(
self,
event_type: type[BaseEvent],
handler: Callable[..., Any],
) -> None:
"""Unregister an event handler for a specific event type.
Args:
event_type: The event class to stop listening for
handler: The handler function to unregister
"""
with self._rwlock.w_locked():
if event_type in self._sync_handlers:
existing_sync = self._sync_handlers[event_type]
if handler in existing_sync:
self._sync_handlers[event_type] = existing_sync - {handler}
if not self._sync_handlers[event_type]:
del self._sync_handlers[event_type]
if event_type in self._async_handlers:
existing_async = self._async_handlers[event_type]
if handler in existing_async:
self._async_handlers[event_type] = existing_async - {handler}
if not self._async_handlers[event_type]:
del self._async_handlers[event_type]
if event_type in self._handler_dependencies:
self._handler_dependencies[event_type].pop(handler, None)
if not self._handler_dependencies[event_type]:
del self._handler_dependencies[event_type]
self._execution_plan_cache.pop(event_type, None)
def _call_handlers(
self,
source: Any,
@@ -407,8 +374,7 @@ class CrewAIEventsBus:
if popped is None:
handle_empty_pop(event_type_name)
else:
popped_event_id, popped_type = popped
event.started_event_id = popped_event_id
_, popped_type = popped
expected_start = VALID_EVENT_PAIRS.get(event_type_name)
if expected_start and popped_type and popped_type != expected_start:
handle_mismatch(event_type_name, popped_type, expected_start)
@@ -570,52 +536,24 @@ class CrewAIEventsBus:
... # Do stuff...
... # Handlers are cleared after the context
"""
with self._rwlock.r_locked():
saved_sync: dict[type[BaseEvent], frozenset[SyncHandler]] = dict(
self._sync_handlers
)
saved_async: dict[type[BaseEvent], frozenset[AsyncHandler]] = dict(
self._async_handlers
)
saved_deps: dict[type[BaseEvent], dict[Handler, list[Depends[Any]]]] = {
event_type: dict(handlers)
for event_type, handlers in self._handler_dependencies.items()
}
for event_type, sync_handlers in saved_sync.items():
for sync_handler in sync_handlers:
self.off(event_type, sync_handler)
for event_type, async_handlers in saved_async.items():
for async_handler in async_handlers:
self.off(event_type, async_handler)
with self._rwlock.w_locked():
prev_sync = self._sync_handlers
prev_async = self._async_handlers
prev_deps = self._handler_dependencies
prev_cache = self._execution_plan_cache
self._sync_handlers = {}
self._async_handlers = {}
self._handler_dependencies = {}
self._execution_plan_cache = {}
try:
yield
finally:
with self._rwlock.r_locked():
current_sync = dict(self._sync_handlers)
current_async = dict(self._async_handlers)
for event_type, cur_sync in current_sync.items():
orig_sync = saved_sync.get(event_type, frozenset())
for new_handler in cur_sync - orig_sync:
self.off(event_type, new_handler)
for event_type, cur_async in current_async.items():
orig_async = saved_async.get(event_type, frozenset())
for new_async_handler in cur_async - orig_async:
self.off(event_type, new_async_handler)
for event_type, sync_handlers in saved_sync.items():
for sync_handler in sync_handlers:
deps = saved_deps.get(event_type, {}).get(sync_handler)
self._register_handler(event_type, sync_handler, deps)
for event_type, async_handlers in saved_async.items():
for async_handler in async_handlers:
deps = saved_deps.get(event_type, {}).get(async_handler)
self._register_handler(event_type, async_handler, deps)
with self._rwlock.w_locked():
self._sync_handlers = prev_sync
self._async_handlers = prev_async
self._handler_dependencies = prev_deps
self._execution_plan_cache = prev_cache
def shutdown(self, wait: bool = True) -> None:
"""Gracefully shutdown the event loop and wait for all tasks to finish.

View File

@@ -797,13 +797,7 @@ class TraceCollectionListener(BaseEventListener):
from rich.console import Console
from rich.panel import Panel
from crewai.events.listeners.tracing.utils import (
has_user_declined_tracing,
should_suppress_tracing_messages,
)
if should_suppress_tracing_messages():
return
from crewai.events.listeners.tracing.utils import has_user_declined_tracing
console = Console()

View File

@@ -1,4 +1,3 @@
from collections.abc import Callable
from contextvars import ContextVar, Token
from datetime import datetime
import getpass
@@ -27,35 +26,6 @@ logger = logging.getLogger(__name__)
_tracing_enabled: ContextVar[bool | None] = ContextVar("_tracing_enabled", default=None)
_first_time_trace_hook: ContextVar[Callable[[], bool] | None] = ContextVar(
"_first_time_trace_hook", default=None
)
_suppress_tracing_messages: ContextVar[bool] = ContextVar(
"_suppress_tracing_messages", default=False
)
def set_suppress_tracing_messages(suppress: bool) -> object:
"""Set whether to suppress tracing-related console messages.
Args:
suppress: True to suppress messages, False to show them.
Returns:
A token that can be used to restore the previous value.
"""
return _suppress_tracing_messages.set(suppress)
def should_suppress_tracing_messages() -> bool:
"""Check if tracing messages should be suppressed.
Returns:
True if messages should be suppressed, False otherwise.
"""
return _suppress_tracing_messages.get()
def should_enable_tracing(*, override: bool | None = None) -> bool:
"""Determine if tracing should be enabled.
@@ -437,13 +407,10 @@ def truncate_messages(
def should_auto_collect_first_time_traces() -> bool:
"""True if we should auto-collect traces for first-time user.
Returns:
True if first-time user AND telemetry not disabled AND tracing not explicitly enabled, False otherwise.
"""
hook = _first_time_trace_hook.get()
if hook is not None:
return hook()
if _is_test_environment():
return False
@@ -465,9 +432,6 @@ def prompt_user_for_trace_viewing(timeout_seconds: int = 20) -> bool:
if _is_test_environment():
return False
if should_suppress_tracing_messages():
return False
try:
import threading

View File

@@ -16,7 +16,7 @@ class ToolUsageEvent(BaseEvent):
tool_name: str
tool_args: dict[str, Any] | str
tool_class: str | None = None
run_attempts: int = 0
run_attempts: int | None = None
delegations: int | None = None
agent: Any | None = None
task_name: str | None = None
@@ -26,7 +26,7 @@ class ToolUsageEvent(BaseEvent):
model_config = ConfigDict(arbitrary_types_allowed=True)
def __init__(self, **data: Any) -> None:
def __init__(self, **data):
if data.get("from_task"):
task = data["from_task"]
data["task_id"] = str(task.id)
@@ -96,10 +96,10 @@ class ToolExecutionErrorEvent(BaseEvent):
type: str = "tool_execution_error"
tool_name: str
tool_args: dict[str, Any]
tool_class: Callable[..., Any]
tool_class: Callable
agent: Any | None = None
def __init__(self, **data: Any) -> None:
def __init__(self, **data):
super().__init__(**data)
# Set fingerprint data from the agent
if self.agent and hasattr(self.agent, "fingerprint") and self.agent.fingerprint:

View File

@@ -1,4 +1,3 @@
from contextvars import ContextVar
import os
import threading
from typing import Any, ClassVar, cast
@@ -11,36 +10,6 @@ from rich.text import Text
from crewai.cli.version import is_newer_version_available
_disable_version_check: ContextVar[bool] = ContextVar(
"_disable_version_check", default=False
)
_suppress_console_output: ContextVar[bool] = ContextVar(
"_suppress_console_output", default=False
)
def set_suppress_console_output(suppress: bool) -> object:
"""Set whether to suppress all console output.
Args:
suppress: True to suppress output, False to show it.
Returns:
A token that can be used to restore the previous value.
"""
return _suppress_console_output.set(suppress)
def should_suppress_console_output() -> bool:
"""Check if console output should be suppressed.
Returns:
True if output should be suppressed, False otherwise.
"""
return _suppress_console_output.get()
class ConsoleFormatter:
tool_usage_counts: ClassVar[dict[str, int]] = {}
@@ -77,15 +46,9 @@ class ConsoleFormatter:
if not self.verbose:
return
if _disable_version_check.get():
return
if os.getenv("CI", "").lower() in ("true", "1"):
return
if os.getenv("CREWAI_DISABLE_VERSION_CHECK", "").lower() in ("true", "1"):
return
try:
is_newer, current, latest = is_newer_version_available()
if is_newer and latest:
@@ -113,12 +76,8 @@ To update, run: uv sync --upgrade-package crewai"""
from crewai.events.listeners.tracing.utils import (
has_user_declined_tracing,
is_tracing_enabled_in_context,
should_suppress_tracing_messages,
)
if should_suppress_tracing_messages():
return
if not is_tracing_enabled_in_context():
if has_user_declined_tracing():
message = """Info: Tracing is disabled.
@@ -170,8 +129,6 @@ To enable tracing, do any one of these:
def print(self, *args: Any, **kwargs: Any) -> None:
"""Print to console. Simplified to only handle panel-based output."""
if should_suppress_console_output():
return
# Skip blank lines during streaming
if len(args) == 0 and self._is_streaming:
return
@@ -528,9 +485,6 @@ To enable tracing, do any one of these:
if not self.verbose:
return
if should_suppress_console_output():
return
self._is_streaming = True
self._last_stream_call_type = call_type

View File

@@ -18,7 +18,6 @@ from crewai.agents.parser import (
AgentFinish,
OutputParserError,
)
from crewai.core.providers.human_input import get_provider
from crewai.events.event_bus import crewai_event_bus
from crewai.events.listeners.tracing.utils import (
is_tracing_enabled_in_context,
@@ -32,8 +31,7 @@ from crewai.events.types.tool_usage_events import (
ToolUsageFinishedEvent,
ToolUsageStartedEvent,
)
from crewai.flow.flow import Flow, StateProxy, listen, or_, router, start
from crewai.flow.types import FlowMethodName
from crewai.flow.flow import Flow, listen, or_, router, start
from crewai.hooks.llm_hooks import (
get_after_llm_call_hooks,
get_before_llm_call_hooks,
@@ -43,12 +41,7 @@ from crewai.hooks.tool_hooks import (
get_after_tool_call_hooks,
get_before_tool_call_hooks,
)
from crewai.hooks.types import (
AfterLLMCallHookCallable,
AfterLLMCallHookType,
BeforeLLMCallHookCallable,
BeforeLLMCallHookType,
)
from crewai.hooks.types import AfterLLMCallHookType, BeforeLLMCallHookType
from crewai.utilities.agent_utils import (
convert_tools_to_openai_schema,
enforce_rpm_limit,
@@ -198,12 +191,8 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
self._instance_id = str(uuid4())[:8]
self.before_llm_call_hooks: list[
BeforeLLMCallHookType | BeforeLLMCallHookCallable
] = []
self.after_llm_call_hooks: list[
AfterLLMCallHookType | AfterLLMCallHookCallable
] = []
self.before_llm_call_hooks: list[BeforeLLMCallHookType] = []
self.after_llm_call_hooks: list[AfterLLMCallHookType] = []
self.before_llm_call_hooks.extend(get_before_llm_call_hooks())
self.after_llm_call_hooks.extend(get_after_llm_call_hooks())
@@ -218,71 +207,6 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
)
self._state = AgentReActState()
@property
def messages(self) -> list[LLMMessage]:
"""Delegate to state for ExecutorContext conformance."""
return self._state.messages
@messages.setter
def messages(self, value: list[LLMMessage]) -> None:
"""Delegate to state for ExecutorContext conformance."""
if self._flow_initialized and hasattr(self, "_state_lock"):
with self._state_lock:
self._state.messages = value
else:
self._state.messages = value
@property
def ask_for_human_input(self) -> bool:
"""Delegate to state for ExecutorContext conformance."""
return self._state.ask_for_human_input
@ask_for_human_input.setter
def ask_for_human_input(self, value: bool) -> None:
"""Delegate to state for ExecutorContext conformance."""
self._state.ask_for_human_input = value
def _invoke_loop(self) -> AgentFinish:
"""Invoke the agent loop and return the result.
Required by ExecutorContext protocol.
"""
self._state.iterations = 0
self._state.is_finished = False
self._state.current_answer = None
self.kickoff()
answer = self._state.current_answer
if not isinstance(answer, AgentFinish):
raise RuntimeError("Agent loop did not produce a final answer")
return answer
async def _ainvoke_loop(self) -> AgentFinish:
"""Invoke the agent loop asynchronously and return the result.
Required by AsyncExecutorContext protocol.
"""
self._state.iterations = 0
self._state.is_finished = False
self._state.current_answer = None
await self.akickoff()
answer = self._state.current_answer
if not isinstance(answer, AgentFinish):
raise RuntimeError("Agent loop did not produce a final answer")
return answer
def _format_feedback_message(self, feedback: str) -> LLMMessage:
"""Format feedback as a message for the LLM.
Required by ExecutorContext protocol.
"""
return format_message_for_llm(
self._i18n.slice("feedback_instructions").format(feedback=feedback)
)
def _ensure_flow_initialized(self) -> None:
"""Ensure Flow.__init__() has been called.
@@ -374,10 +298,18 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
Flow initialization is deferred to prevent event emission during agent setup.
Returns the temporary state until invoke() is called.
"""
if self._flow_initialized and hasattr(self, "_state_lock"):
return StateProxy(self._state, self._state_lock) # type: ignore[return-value]
return self._state
@property
def messages(self) -> list[LLMMessage]:
"""Compatibility property for mixin - returns state messages."""
return self._state.messages
@messages.setter
def messages(self, value: list[LLMMessage]) -> None:
"""Set state messages."""
self._state.messages = value
@property
def iterations(self) -> int:
"""Compatibility property for mixin - returns state iterations."""
@@ -484,14 +416,15 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
raise
@listen("continue_reasoning_native")
def call_llm_native_tools(self) -> None:
def call_llm_native_tools(
self,
) -> Literal["native_tool_calls", "native_finished", "context_error"]:
"""Execute LLM call with native function calling.
Always calls the LLM so it can read reflection prompts and decide
whether to provide a final answer or request more tools.
Note: This is a listener, not a router. The route_native_tool_result
router fires after this to determine the next step based on state.
Returns routing decision based on whether tool calls or final answer.
"""
try:
# Clear pending tools - LLM will decide what to do next after reading
@@ -521,7 +454,8 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
if isinstance(answer, list) and answer and self._is_tool_call_list(answer):
# Store tool calls for sequential processing
self.state.pending_tool_calls = list(answer)
return # Router will check pending_tool_calls
return "native_tool_calls"
if isinstance(answer, BaseModel):
self.state.current_answer = AgentFinish(
@@ -531,7 +465,7 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
)
self._invoke_step_callback(self.state.current_answer)
self._append_message_to_state(answer.model_dump_json())
return # Router will check current_answer
return "native_finished"
# Text response - this is the final answer
if isinstance(answer, str):
@@ -542,7 +476,8 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
)
self._invoke_step_callback(self.state.current_answer)
self._append_message_to_state(answer)
return # Router will check current_answer
return "native_finished"
# Unexpected response type, treat as final answer
self.state.current_answer = AgentFinish(
@@ -552,12 +487,13 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
)
self._invoke_step_callback(self.state.current_answer)
self._append_message_to_state(str(answer))
# Router will check current_answer
return "native_finished"
except Exception as e:
if is_context_length_exceeded(e):
self._last_context_error = e
return # Router will check _last_context_error
return "context_error"
if e.__class__.__module__.startswith("litellm"):
raise e
handle_unknown_error(self._printer, e, verbose=self.agent.verbose)
@@ -570,22 +506,6 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
return "execute_tool"
return "agent_finished"
@router(call_llm_native_tools)
def route_native_tool_result(
self,
) -> Literal["native_tool_calls", "native_finished", "context_error"]:
"""Route based on LLM response for native tool calling.
Checks state set by call_llm_native_tools to determine next step.
This router is needed because only router return values trigger
downstream listeners.
"""
if self._last_context_error is not None:
return "context_error"
if self.state.pending_tool_calls:
return "native_tool_calls"
return "native_finished"
@listen("execute_tool")
def execute_tool_action(self) -> Literal["tool_completed", "tool_result_is_final"]:
"""Execute the tool action and handle the result."""
@@ -769,7 +689,6 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
agent_key=agent_key,
),
)
error_event_emitted = False
track_delegation_if_needed(func_name, args_dict, self.task)
@@ -845,7 +764,6 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
error=e,
),
)
error_event_emitted = True
elif max_usage_reached and original_tool:
# Return error message when max usage limit is reached
result = f"Tool '{func_name}' has reached its usage limit of {original_tool.max_usage_count} times and cannot be used anymore."
@@ -874,20 +792,20 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
color="red",
)
if not error_event_emitted:
crewai_event_bus.emit(
self,
event=ToolUsageFinishedEvent(
output=result,
tool_name=func_name,
tool_args=args_dict,
from_agent=self.agent,
from_task=self.task,
agent_key=agent_key,
started_at=started_at,
finished_at=datetime.now(),
),
)
# Emit tool usage finished event
crewai_event_bus.emit(
self,
event=ToolUsageFinishedEvent(
output=result,
tool_name=func_name,
tool_args=args_dict,
from_agent=self.agent,
from_task=self.task,
agent_key=agent_key,
started_at=started_at,
finished_at=datetime.now(),
),
)
# Append tool result message
tool_message: LLMMessage = {
@@ -943,11 +861,9 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
self.state.iterations += 1
return "initialized"
@listen(or_("initialized", "tool_completed", "native_tool_completed"))
@listen("initialized")
def continue_iteration(self) -> Literal["check_iteration"]:
"""Bridge listener that connects iteration loop back to iteration check."""
if self._flow_initialized:
self._discard_or_listener(FlowMethodName("continue_iteration"))
return "check_iteration"
@router(or_(initialize_reasoning, continue_iteration))
@@ -1189,7 +1105,7 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
)
if self.state.ask_for_human_input:
formatted_answer = await self._ahandle_human_feedback(formatted_answer)
formatted_answer = self._handle_human_feedback(formatted_answer)
self._create_short_term_memory(formatted_answer)
self._create_long_term_memory(formatted_answer)
@@ -1403,22 +1319,17 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
Returns:
Final answer after feedback.
"""
provider = get_provider()
return provider.handle_feedback(formatted_answer, self)
output_str = (
str(formatted_answer.output)
if isinstance(formatted_answer.output, BaseModel)
else formatted_answer.output
)
human_feedback = self._ask_human_input(output_str)
async def _ahandle_human_feedback(
self, formatted_answer: AgentFinish
) -> AgentFinish:
"""Process human feedback asynchronously and refine answer.
if self._is_training_mode():
return self._handle_training_feedback(formatted_answer, human_feedback)
Args:
formatted_answer: Initial agent result.
Returns:
Final answer after feedback.
"""
provider = get_provider()
return await provider.handle_feedback_async(formatted_answer, self)
return self._handle_regular_feedback(formatted_answer, human_feedback)
def _is_training_mode(self) -> bool:
"""Check if training mode is active.
@@ -1428,6 +1339,101 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
"""
return bool(self.crew and self.crew._train)
def _handle_training_feedback(
self, initial_answer: AgentFinish, feedback: str
) -> AgentFinish:
"""Process training feedback and generate improved answer.
Args:
initial_answer: Initial agent output.
feedback: Training feedback.
Returns:
Improved answer.
"""
self._handle_crew_training_output(initial_answer, feedback)
self.state.messages.append(
format_message_for_llm(
self._i18n.slice("feedback_instructions").format(feedback=feedback)
)
)
# Re-run flow for improved answer
self.state.iterations = 0
self.state.is_finished = False
self.state.current_answer = None
self.kickoff()
# Get improved answer from state
improved_answer = self.state.current_answer
if not isinstance(improved_answer, AgentFinish):
raise RuntimeError(
"Training feedback iteration did not produce final answer"
)
self._handle_crew_training_output(improved_answer)
self.state.ask_for_human_input = False
return improved_answer
def _handle_regular_feedback(
self, current_answer: AgentFinish, initial_feedback: str
) -> AgentFinish:
"""Process regular feedback iteratively until user is satisfied.
Args:
current_answer: Current agent output.
initial_feedback: Initial user feedback.
Returns:
Final answer after iterations.
"""
feedback = initial_feedback
answer = current_answer
while self.state.ask_for_human_input:
if feedback.strip() == "":
self.state.ask_for_human_input = False
else:
answer = self._process_feedback_iteration(feedback)
output_str = (
str(answer.output)
if isinstance(answer.output, BaseModel)
else answer.output
)
feedback = self._ask_human_input(output_str)
return answer
def _process_feedback_iteration(self, feedback: str) -> AgentFinish:
"""Process a single feedback iteration and generate updated response.
Args:
feedback: User feedback.
Returns:
Updated agent response.
"""
self.state.messages.append(
format_message_for_llm(
self._i18n.slice("feedback_instructions").format(feedback=feedback)
)
)
# Re-run flow
self.state.iterations = 0
self.state.is_finished = False
self.state.current_answer = None
self.kickoff()
# Get answer from state
answer = self.state.current_answer
if not isinstance(answer, AgentFinish):
raise RuntimeError("Feedback iteration did not produce final answer")
return answer
@classmethod
def __get_pydantic_core_schema__(
cls, _source_type: Any, _handler: GetCoreSchemaHandler

View File

@@ -28,8 +28,6 @@ Example:
```
"""
from typing import Any
from crewai.flow.async_feedback.providers import ConsoleProvider
from crewai.flow.async_feedback.types import (
HumanFeedbackPending,
@@ -43,15 +41,4 @@ __all__ = [
"HumanFeedbackPending",
"HumanFeedbackProvider",
"PendingFeedbackContext",
"_extension_exports",
]
_extension_exports: dict[str, Any] = {}
def __getattr__(name: str) -> Any:
"""Support extensions via dynamic attribute lookup."""
if name in _extension_exports:
return _extension_exports[name]
msg = f"module {__name__!r} has no attribute {name!r}"
raise AttributeError(msg)

View File

@@ -7,14 +7,7 @@ for building event-driven workflows with conditional execution and routing.
from __future__ import annotations
import asyncio
from collections.abc import (
Callable,
ItemsView,
Iterator,
KeysView,
Sequence,
ValuesView,
)
from collections.abc import Callable, Sequence
from concurrent.futures import Future
import copy
import inspect
@@ -52,7 +45,6 @@ from crewai.events.listeners.tracing.utils import (
has_user_declined_tracing,
set_tracing_enabled,
should_enable_tracing,
should_suppress_tracing_messages,
)
from crewai.events.types.flow_events import (
FlowCreatedEvent,
@@ -416,132 +408,6 @@ def and_(*conditions: str | FlowCondition | Callable[..., Any]) -> FlowCondition
return {"type": AND_CONDITION, "conditions": processed_conditions}
class LockedListProxy(Generic[T]):
"""Thread-safe proxy for list operations.
Wraps a list and uses a lock for all mutating operations.
"""
def __init__(self, lst: list[T], lock: threading.Lock) -> None:
self._list = lst
self._lock = lock
def append(self, item: T) -> None:
with self._lock:
self._list.append(item)
def extend(self, items: list[T]) -> None:
with self._lock:
self._list.extend(items)
def insert(self, index: int, item: T) -> None:
with self._lock:
self._list.insert(index, item)
def remove(self, item: T) -> None:
with self._lock:
self._list.remove(item)
def pop(self, index: int = -1) -> T:
with self._lock:
return self._list.pop(index)
def clear(self) -> None:
with self._lock:
self._list.clear()
def __setitem__(self, index: int, value: T) -> None:
with self._lock:
self._list[index] = value
def __delitem__(self, index: int) -> None:
with self._lock:
del self._list[index]
def __getitem__(self, index: int) -> T:
return self._list[index]
def __len__(self) -> int:
return len(self._list)
def __iter__(self) -> Iterator[T]:
return iter(self._list)
def __contains__(self, item: object) -> bool:
return item in self._list
def __repr__(self) -> str:
return repr(self._list)
def __bool__(self) -> bool:
return bool(self._list)
class LockedDictProxy(Generic[T]):
"""Thread-safe proxy for dict operations.
Wraps a dict and uses a lock for all mutating operations.
"""
def __init__(self, d: dict[str, T], lock: threading.Lock) -> None:
self._dict = d
self._lock = lock
def __setitem__(self, key: str, value: T) -> None:
with self._lock:
self._dict[key] = value
def __delitem__(self, key: str) -> None:
with self._lock:
del self._dict[key]
def pop(self, key: str, *default: T) -> T:
with self._lock:
return self._dict.pop(key, *default)
def update(self, other: dict[str, T]) -> None:
with self._lock:
self._dict.update(other)
def clear(self) -> None:
with self._lock:
self._dict.clear()
def setdefault(self, key: str, default: T) -> T:
with self._lock:
return self._dict.setdefault(key, default)
def __getitem__(self, key: str) -> T:
return self._dict[key]
def __len__(self) -> int:
return len(self._dict)
def __iter__(self) -> Iterator[str]:
return iter(self._dict)
def __contains__(self, key: object) -> bool:
return key in self._dict
def keys(self) -> KeysView[str]:
return self._dict.keys()
def values(self) -> ValuesView[T]:
return self._dict.values()
def items(self) -> ItemsView[str, T]:
return self._dict.items()
def get(self, key: str, default: T | None = None) -> T | None:
return self._dict.get(key, default)
def __repr__(self) -> str:
return repr(self._dict)
def __bool__(self) -> bool:
return bool(self._dict)
class StateProxy(Generic[T]):
"""Proxy that provides thread-safe access to flow state.
@@ -556,13 +422,7 @@ class StateProxy(Generic[T]):
object.__setattr__(self, "_proxy_lock", lock)
def __getattr__(self, name: str) -> Any:
value = getattr(object.__getattribute__(self, "_proxy_state"), name)
lock = object.__getattribute__(self, "_proxy_lock")
if isinstance(value, list):
return LockedListProxy(value, lock)
if isinstance(value, dict):
return LockedDictProxy(value, lock)
return value
return getattr(object.__getattribute__(self, "_proxy_state"), name)
def __setattr__(self, name: str, value: Any) -> None:
if name in ("_proxy_state", "_proxy_lock"):
@@ -1732,6 +1592,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
reset_emission_counter()
reset_last_event_id()
# Emit FlowStartedEvent and log the start of the flow.
if not self.suppress_flow_events:
future = crewai_event_bus.emit(
self,
@@ -1742,10 +1603,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
),
)
if future:
try:
await asyncio.wrap_future(future)
except Exception:
logger.warning("FlowStartedEvent handler failed", exc_info=True)
self._event_futures.append(future)
self._log_flow_event(
f"Flow started with ID: {self.flow_id}", color="bold magenta"
)
@@ -1837,12 +1695,6 @@ class Flow(Generic[T], metaclass=FlowMeta):
final_output = self._method_outputs[-1] if self._method_outputs else None
if self._event_futures:
await asyncio.gather(
*[asyncio.wrap_future(f) for f in self._event_futures]
)
self._event_futures.clear()
if not self.suppress_flow_events:
future = crewai_event_bus.emit(
self,
@@ -1854,12 +1706,13 @@ class Flow(Generic[T], metaclass=FlowMeta):
),
)
if future:
try:
await asyncio.wrap_future(future)
except Exception:
logger.warning(
"FlowFinishedEvent handler failed", exc_info=True
)
self._event_futures.append(future)
if self._event_futures:
await asyncio.gather(
*[asyncio.wrap_future(f) for f in self._event_futures]
)
self._event_futures.clear()
if not self.suppress_flow_events:
trace_listener = TraceCollectionListener()
@@ -1934,14 +1787,40 @@ class Flow(Generic[T], metaclass=FlowMeta):
await self._execute_listeners(start_method_name, result, finished_event_id)
# Then execute listeners for the router result (e.g., "approved")
router_result_trigger = FlowMethodName(str(result))
listener_result = (
self.last_human_feedback
if self.last_human_feedback is not None
else result
)
await self._execute_listeners(
router_result_trigger, listener_result, finished_event_id
listeners_for_result = self._find_triggered_methods(
router_result_trigger, router_only=False
)
if listeners_for_result:
# Pass the HumanFeedbackResult if available
listener_result = (
self.last_human_feedback
if self.last_human_feedback is not None
else result
)
racing_group = self._get_racing_group_for_listeners(
listeners_for_result
)
if racing_group:
racing_members, _ = racing_group
other_listeners = [
name
for name in listeners_for_result
if name not in racing_members
]
await self._execute_racing_listeners(
racing_members,
other_listeners,
listener_result,
finished_event_id,
)
else:
tasks = [
self._execute_single_listener(
listener_name, listener_result, finished_event_id
)
for listener_name in listeners_for_result
]
await asyncio.gather(*tasks)
else:
await self._execute_listeners(start_method_name, result, finished_event_id)
@@ -2147,14 +2026,15 @@ class Flow(Generic[T], metaclass=FlowMeta):
router_input = router_result_to_feedback.get(
str(current_trigger), current_result
)
(
router_result,
current_triggering_event_id,
) = await self._execute_single_listener(
current_triggering_event_id = await self._execute_single_listener(
router_name, router_input, current_triggering_event_id
)
# After executing router, the router's result is the path
router_result = (
self._method_outputs[-1] if self._method_outputs else None
)
if router_result: # Only add non-None results
router_results.append(FlowMethodName(str(router_result)))
router_results.append(router_result)
# If this was a human_feedback router, map the outcome to the feedback
if self.last_human_feedback is not None:
router_result_to_feedback[str(router_result)] = (
@@ -2194,14 +2074,12 @@ class Flow(Generic[T], metaclass=FlowMeta):
racing_members,
other_listeners,
listener_result,
current_triggering_event_id,
triggering_event_id,
)
else:
tasks = [
self._execute_single_listener(
listener_name,
listener_result,
current_triggering_event_id,
listener_name, listener_result, triggering_event_id
)
for listener_name in listeners_triggered
]
@@ -2384,7 +2262,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
listener_name: FlowMethodName,
result: Any,
triggering_event_id: str | None = None,
) -> tuple[Any, str | None]:
) -> str | None:
"""Executes a single listener method with proper event handling.
This internal method manages the execution of an individual listener,
@@ -2397,9 +2275,8 @@ class Flow(Generic[T], metaclass=FlowMeta):
used for causal chain tracking.
Returns:
A tuple of (listener_result, event_id) where listener_result is the return
value of the listener method and event_id is the MethodExecutionFinishedEvent
id, or (None, None) if skipped during resumption.
The event_id of the MethodExecutionFinishedEvent emitted by this listener,
or None if events are suppressed.
Note:
- Inspects method signature to determine if it accepts the trigger result
@@ -2425,7 +2302,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
):
# This conditional start was executed, continue its chain
await self._execute_start_method(start_method_name)
return (None, None)
return None
# For cyclic flows, clear from completed to allow re-execution
self._completed_methods.discard(listener_name)
# Also clear from fired OR listeners for cyclic flows
@@ -2463,7 +2340,46 @@ class Flow(Generic[T], metaclass=FlowMeta):
listener_name, listener_result, finished_event_id
)
return (listener_result, finished_event_id)
# If this listener is also a router (e.g., has @human_feedback with emit),
# we need to trigger listeners for the router result as well
if listener_name in self._routers and listener_result is not None:
router_result_trigger = FlowMethodName(str(listener_result))
listeners_for_result = self._find_triggered_methods(
router_result_trigger, router_only=False
)
if listeners_for_result:
# Pass the HumanFeedbackResult if available
feedback_result = (
self.last_human_feedback
if self.last_human_feedback is not None
else listener_result
)
racing_group = self._get_racing_group_for_listeners(
listeners_for_result
)
if racing_group:
racing_members, _ = racing_group
other_listeners = [
name
for name in listeners_for_result
if name not in racing_members
]
await self._execute_racing_listeners(
racing_members,
other_listeners,
feedback_result,
finished_event_id,
)
else:
tasks = [
self._execute_single_listener(
name, feedback_result, finished_event_id
)
for name in listeners_for_result
]
await asyncio.gather(*tasks)
return finished_event_id
except Exception as e:
# Don't log HumanFeedbackPending as an error - it's expected control flow
@@ -2710,8 +2626,6 @@ class Flow(Generic[T], metaclass=FlowMeta):
@staticmethod
def _show_tracing_disabled_message() -> None:
"""Show a message when tracing is disabled."""
if should_suppress_tracing_messages():
return
console = Console()

View File

@@ -3,12 +3,7 @@ from __future__ import annotations
from typing import TYPE_CHECKING, Any, cast
from crewai.events.event_listener import event_listener
from crewai.hooks.types import (
AfterLLMCallHookCallable,
AfterLLMCallHookType,
BeforeLLMCallHookCallable,
BeforeLLMCallHookType,
)
from crewai.hooks.types import AfterLLMCallHookType, BeforeLLMCallHookType
from crewai.utilities.printer import Printer
@@ -154,12 +149,12 @@ class LLMCallHookContext:
event_listener.formatter.resume_live_updates()
_before_llm_call_hooks: list[BeforeLLMCallHookType | BeforeLLMCallHookCallable] = []
_after_llm_call_hooks: list[AfterLLMCallHookType | AfterLLMCallHookCallable] = []
_before_llm_call_hooks: list[BeforeLLMCallHookType] = []
_after_llm_call_hooks: list[AfterLLMCallHookType] = []
def register_before_llm_call_hook(
hook: BeforeLLMCallHookType | BeforeLLMCallHookCallable,
hook: BeforeLLMCallHookType,
) -> None:
"""Register a global before_llm_call hook.
@@ -195,7 +190,7 @@ def register_before_llm_call_hook(
def register_after_llm_call_hook(
hook: AfterLLMCallHookType | AfterLLMCallHookCallable,
hook: AfterLLMCallHookType,
) -> None:
"""Register a global after_llm_call hook.
@@ -222,9 +217,7 @@ def register_after_llm_call_hook(
_after_llm_call_hooks.append(hook)
def get_before_llm_call_hooks() -> list[
BeforeLLMCallHookType | BeforeLLMCallHookCallable
]:
def get_before_llm_call_hooks() -> list[BeforeLLMCallHookType]:
"""Get all registered global before_llm_call hooks.
Returns:
@@ -233,7 +226,7 @@ def get_before_llm_call_hooks() -> list[
return _before_llm_call_hooks.copy()
def get_after_llm_call_hooks() -> list[AfterLLMCallHookType | AfterLLMCallHookCallable]:
def get_after_llm_call_hooks() -> list[AfterLLMCallHookType]:
"""Get all registered global after_llm_call hooks.
Returns:
@@ -243,7 +236,7 @@ def get_after_llm_call_hooks() -> list[AfterLLMCallHookType | AfterLLMCallHookCa
def unregister_before_llm_call_hook(
hook: BeforeLLMCallHookType | BeforeLLMCallHookCallable,
hook: BeforeLLMCallHookType,
) -> bool:
"""Unregister a specific global before_llm_call hook.
@@ -269,7 +262,7 @@ def unregister_before_llm_call_hook(
def unregister_after_llm_call_hook(
hook: AfterLLMCallHookType | AfterLLMCallHookCallable,
hook: AfterLLMCallHookType,
) -> bool:
"""Unregister a specific global after_llm_call hook.

View File

@@ -3,12 +3,7 @@ from __future__ import annotations
from typing import TYPE_CHECKING, Any
from crewai.events.event_listener import event_listener
from crewai.hooks.types import (
AfterToolCallHookCallable,
AfterToolCallHookType,
BeforeToolCallHookCallable,
BeforeToolCallHookType,
)
from crewai.hooks.types import AfterToolCallHookType, BeforeToolCallHookType
from crewai.utilities.printer import Printer
@@ -117,12 +112,12 @@ class ToolCallHookContext:
# Global hook registries
_before_tool_call_hooks: list[BeforeToolCallHookType | BeforeToolCallHookCallable] = []
_after_tool_call_hooks: list[AfterToolCallHookType | AfterToolCallHookCallable] = []
_before_tool_call_hooks: list[BeforeToolCallHookType] = []
_after_tool_call_hooks: list[AfterToolCallHookType] = []
def register_before_tool_call_hook(
hook: BeforeToolCallHookType | BeforeToolCallHookCallable,
hook: BeforeToolCallHookType,
) -> None:
"""Register a global before_tool_call hook.
@@ -159,7 +154,7 @@ def register_before_tool_call_hook(
def register_after_tool_call_hook(
hook: AfterToolCallHookType | AfterToolCallHookCallable,
hook: AfterToolCallHookType,
) -> None:
"""Register a global after_tool_call hook.
@@ -189,9 +184,7 @@ def register_after_tool_call_hook(
_after_tool_call_hooks.append(hook)
def get_before_tool_call_hooks() -> list[
BeforeToolCallHookType | BeforeToolCallHookCallable
]:
def get_before_tool_call_hooks() -> list[BeforeToolCallHookType]:
"""Get all registered global before_tool_call hooks.
Returns:
@@ -200,9 +193,7 @@ def get_before_tool_call_hooks() -> list[
return _before_tool_call_hooks.copy()
def get_after_tool_call_hooks() -> list[
AfterToolCallHookType | AfterToolCallHookCallable
]:
def get_after_tool_call_hooks() -> list[AfterToolCallHookType]:
"""Get all registered global after_tool_call hooks.
Returns:
@@ -212,7 +203,7 @@ def get_after_tool_call_hooks() -> list[
def unregister_before_tool_call_hook(
hook: BeforeToolCallHookType | BeforeToolCallHookCallable,
hook: BeforeToolCallHookType,
) -> bool:
"""Unregister a specific global before_tool_call hook.
@@ -238,7 +229,7 @@ def unregister_before_tool_call_hook(
def unregister_after_tool_call_hook(
hook: AfterToolCallHookType | AfterToolCallHookCallable,
hook: AfterToolCallHookType,
) -> bool:
"""Unregister a specific global after_tool_call hook.

View File

@@ -1 +0,0 @@
"""Knowledge source utilities."""

View File

@@ -1,70 +0,0 @@
"""Helper utilities for knowledge sources."""
from typing import Any, ClassVar
from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
from crewai.knowledge.source.csv_knowledge_source import CSVKnowledgeSource
from crewai.knowledge.source.excel_knowledge_source import ExcelKnowledgeSource
from crewai.knowledge.source.json_knowledge_source import JSONKnowledgeSource
from crewai.knowledge.source.pdf_knowledge_source import PDFKnowledgeSource
from crewai.knowledge.source.text_file_knowledge_source import TextFileKnowledgeSource
class SourceHelper:
"""Helper class for creating and managing knowledge sources."""
SUPPORTED_FILE_TYPES: ClassVar[list[str]] = [
".csv",
".pdf",
".json",
".txt",
".xlsx",
".xls",
]
_FILE_TYPE_MAP: ClassVar[dict[str, type[BaseKnowledgeSource]]] = {
".csv": CSVKnowledgeSource,
".pdf": PDFKnowledgeSource,
".json": JSONKnowledgeSource,
".txt": TextFileKnowledgeSource,
".xlsx": ExcelKnowledgeSource,
".xls": ExcelKnowledgeSource,
}
@classmethod
def is_supported_file(cls, file_path: str) -> bool:
"""Check if a file type is supported.
Args:
file_path: Path to the file.
Returns:
True if the file type is supported.
"""
return file_path.lower().endswith(tuple(cls.SUPPORTED_FILE_TYPES))
@classmethod
def get_source(
cls, file_path: str, metadata: dict[str, Any] | None = None
) -> BaseKnowledgeSource:
"""Create appropriate KnowledgeSource based on file extension.
Args:
file_path: Path to the file.
metadata: Optional metadata to attach to the source.
Returns:
The appropriate KnowledgeSource instance.
Raises:
ValueError: If the file type is not supported.
"""
if not cls.is_supported_file(file_path):
raise ValueError(f"Unsupported file type: {file_path}")
lower_path = file_path.lower()
for ext, source_cls in cls._FILE_TYPE_MAP.items():
if lower_path.endswith(ext):
return source_cls(file_path=[file_path], metadata=metadata)
raise ValueError(f"Unsupported file type: {file_path}")

View File

@@ -420,6 +420,7 @@ class MCPClient:
return [
{
"name": sanitize_tool_name(tool.name),
"original_name": tool.name,
"description": getattr(tool, "description", ""),
"inputSchema": getattr(tool, "inputSchema", {}),
}

View File

@@ -27,8 +27,6 @@ if TYPE_CHECKING:
from crewai import Agent, Task
from crewai.agents.cache.cache_handler import CacheHandler
from crewai.crews.crew_output import CrewOutput
from crewai.hooks.llm_hooks import LLMCallHookContext
from crewai.hooks.tool_hooks import ToolCallHookContext
from crewai.project.wrappers import (
CrewInstance,
OutputJsonClass,
@@ -36,8 +34,6 @@ if TYPE_CHECKING:
)
from crewai.tasks.task_output import TaskOutput
_post_initialize_crew_hooks: list[Callable[[Any], None]] = []
class AgentConfig(TypedDict, total=False):
"""Type definition for agent configuration dictionary.
@@ -270,9 +266,6 @@ class CrewBaseMeta(type):
instance.map_all_agent_variables()
instance.map_all_task_variables()
for hook in _post_initialize_crew_hooks:
hook(instance)
original_methods = {
name: method
for name, method in cls.__dict__.items()
@@ -492,61 +485,47 @@ def _register_crew_hooks(instance: CrewInstance, cls: type) -> None:
if has_agent_filter:
agents_filter = hook_method._filter_agents
def make_filtered_before_llm(
bound_fn: Callable[[LLMCallHookContext], bool | None],
agents_list: list[str],
) -> Callable[[LLMCallHookContext], bool | None]:
def filtered(context: LLMCallHookContext) -> bool | None:
def make_filtered_before_llm(bound_fn, agents_list):
def filtered(context):
if context.agent and context.agent.role not in agents_list:
return None
return bound_fn(context)
return filtered
before_llm_hook = make_filtered_before_llm(bound_hook, agents_filter)
final_hook = make_filtered_before_llm(bound_hook, agents_filter)
else:
before_llm_hook = bound_hook
final_hook = bound_hook
register_before_llm_call_hook(before_llm_hook)
instance._registered_hook_functions.append(
("before_llm_call", before_llm_hook)
)
register_before_llm_call_hook(final_hook)
instance._registered_hook_functions.append(("before_llm_call", final_hook))
if hasattr(hook_method, "is_after_llm_call_hook"):
if has_agent_filter:
agents_filter = hook_method._filter_agents
def make_filtered_after_llm(
bound_fn: Callable[[LLMCallHookContext], str | None],
agents_list: list[str],
) -> Callable[[LLMCallHookContext], str | None]:
def filtered(context: LLMCallHookContext) -> str | None:
def make_filtered_after_llm(bound_fn, agents_list):
def filtered(context):
if context.agent and context.agent.role not in agents_list:
return None
return bound_fn(context)
return filtered
after_llm_hook = make_filtered_after_llm(bound_hook, agents_filter)
final_hook = make_filtered_after_llm(bound_hook, agents_filter)
else:
after_llm_hook = bound_hook
final_hook = bound_hook
register_after_llm_call_hook(after_llm_hook)
instance._registered_hook_functions.append(
("after_llm_call", after_llm_hook)
)
register_after_llm_call_hook(final_hook)
instance._registered_hook_functions.append(("after_llm_call", final_hook))
if hasattr(hook_method, "is_before_tool_call_hook"):
if has_tool_filter or has_agent_filter:
tools_filter = getattr(hook_method, "_filter_tools", None)
agents_filter = getattr(hook_method, "_filter_agents", None)
def make_filtered_before_tool(
bound_fn: Callable[[ToolCallHookContext], bool | None],
tools_list: list[str] | None,
agents_list: list[str] | None,
) -> Callable[[ToolCallHookContext], bool | None]:
def filtered(context: ToolCallHookContext) -> bool | None:
def make_filtered_before_tool(bound_fn, tools_list, agents_list):
def filtered(context):
if tools_list and context.tool_name not in tools_list:
return None
if (
@@ -559,28 +538,22 @@ def _register_crew_hooks(instance: CrewInstance, cls: type) -> None:
return filtered
before_tool_hook = make_filtered_before_tool(
final_hook = make_filtered_before_tool(
bound_hook, tools_filter, agents_filter
)
else:
before_tool_hook = bound_hook
final_hook = bound_hook
register_before_tool_call_hook(before_tool_hook)
instance._registered_hook_functions.append(
("before_tool_call", before_tool_hook)
)
register_before_tool_call_hook(final_hook)
instance._registered_hook_functions.append(("before_tool_call", final_hook))
if hasattr(hook_method, "is_after_tool_call_hook"):
if has_tool_filter or has_agent_filter:
tools_filter = getattr(hook_method, "_filter_tools", None)
agents_filter = getattr(hook_method, "_filter_agents", None)
def make_filtered_after_tool(
bound_fn: Callable[[ToolCallHookContext], str | None],
tools_list: list[str] | None,
agents_list: list[str] | None,
) -> Callable[[ToolCallHookContext], str | None]:
def filtered(context: ToolCallHookContext) -> str | None:
def make_filtered_after_tool(bound_fn, tools_list, agents_list):
def filtered(context):
if tools_list and context.tool_name not in tools_list:
return None
if (
@@ -593,16 +566,14 @@ def _register_crew_hooks(instance: CrewInstance, cls: type) -> None:
return filtered
after_tool_hook = make_filtered_after_tool(
final_hook = make_filtered_after_tool(
bound_hook, tools_filter, agents_filter
)
else:
after_tool_hook = bound_hook
final_hook = bound_hook
register_after_tool_call_hook(after_tool_hook)
instance._registered_hook_functions.append(
("after_tool_call", after_tool_hook)
)
register_after_tool_call_hook(final_hook)
instance._registered_hook_functions.append(("after_tool_call", final_hook))
instance._hooks_being_registered = False

View File

@@ -72,8 +72,6 @@ class CrewInstance(Protocol):
__crew_metadata__: CrewMetadata
_mcp_server_adapter: Any
_all_methods: dict[str, Callable[..., Any]]
_registered_hook_functions: list[tuple[str, Callable[..., Any]]]
_hooks_being_registered: bool
agents: list[Agent]
tasks: list[Task]
base_directory: Path

View File

@@ -31,7 +31,6 @@ from pydantic_core import PydanticCustomError
from typing_extensions import Self
from crewai.agents.agent_builder.base_agent import BaseAgent
from crewai.context import reset_current_task_id, set_current_task_id
from crewai.core.providers.content_processor import process_content
from crewai.events.event_bus import crewai_event_bus
from crewai.events.types.task_events import (
@@ -562,7 +561,6 @@ class Task(BaseModel):
tools: list[Any] | None,
) -> TaskOutput:
"""Run the core execution logic of the task asynchronously."""
task_id_token = set_current_task_id(str(self.id))
self._store_input_files()
try:
agent = agent or self.agent
@@ -650,7 +648,6 @@ class Task(BaseModel):
raise e # Re-raise the exception after emitting the event
finally:
clear_task_files(self.id)
reset_current_task_id(task_id_token)
def _execute_core(
self,
@@ -659,7 +656,6 @@ class Task(BaseModel):
tools: list[Any] | None,
) -> TaskOutput:
"""Run the core execution logic of the task."""
task_id_token = set_current_task_id(str(self.id))
self._store_input_files()
try:
agent = agent or self.agent
@@ -748,7 +744,6 @@ class Task(BaseModel):
raise e # Re-raise the exception after emitting the event
finally:
clear_task_files(self.id)
reset_current_task_id(task_id_token)
def _post_agent_execution(self, agent: BaseAgent) -> None:
pass

View File

@@ -6,7 +6,6 @@ Classes:
HallucinationGuardrail: Placeholder guardrail that validates task outputs.
"""
from collections.abc import Callable
from typing import Any
from crewai.llm import LLM
@@ -14,36 +13,32 @@ from crewai.tasks.task_output import TaskOutput
from crewai.utilities.logger import Logger
_validate_output_hook: Callable[..., tuple[bool, Any]] | None = None
class HallucinationGuardrail:
"""Placeholder for the HallucinationGuardrail feature.
Attributes:
context: Optional reference context that outputs would be checked against.
context: The reference context that outputs would be checked against.
llm: The language model that would be used for evaluation.
threshold: Optional minimum faithfulness score that would be required to pass.
tool_response: Optional tool response information that would be used in evaluation.
Examples:
>>> # Basic usage without context (uses task expected_output as context)
>>> guardrail = HallucinationGuardrail(llm=agent.llm)
>>> # With context for reference
>>> # Basic usage with default verdict logic
>>> guardrail = HallucinationGuardrail(
... llm=agent.llm,
... context="AI helps with various tasks including analysis and generation.",
... llm=agent.llm,
... )
>>> # With custom threshold for stricter validation
>>> strict_guardrail = HallucinationGuardrail(
... context="Quantum computing uses qubits in superposition.",
... llm=agent.llm,
... threshold=8.0, # Require score >= 8 to pass
... threshold=8.0, # Would require score >= 8 to pass in enterprise version
... )
>>> # With tool response for additional context
>>> guardrail_with_tools = HallucinationGuardrail(
... context="The current weather data",
... llm=agent.llm,
... tool_response="Weather API returned: Temperature 22°C, Humidity 65%",
... )
@@ -51,17 +46,16 @@ class HallucinationGuardrail:
def __init__(
self,
context: str,
llm: LLM,
context: str | None = None,
threshold: float | None = None,
tool_response: str = "",
):
"""Initialize the HallucinationGuardrail placeholder.
Args:
context: The reference context that outputs would be checked against.
llm: The language model that would be used for evaluation.
context: Optional reference context that outputs would be checked against.
If not provided, the task's expected_output will be used as context.
threshold: Optional minimum faithfulness score that would be required to pass.
tool_response: Optional tool response information that would be used in evaluation.
"""
@@ -84,17 +78,16 @@ class HallucinationGuardrail:
def __call__(self, task_output: TaskOutput) -> tuple[bool, Any]:
"""Validate a task output against hallucination criteria.
In the open source, this method always returns that the output is valid.
Args:
task_output: The output to be validated.
Returns:
A tuple containing:
- True if validation passed, False otherwise
- The raw task output if valid, or error feedback if invalid
- True
- The raw task output
"""
if callable(_validate_output_hook):
return _validate_output_hook(self, task_output)
self._logger.log(
"warning",
"Premium hallucination detection skipped (use for free at https://app.crewai.com)\n",

View File

@@ -1,10 +1,6 @@
import asyncio
from collections.abc import Coroutine
import inspect
from typing import Any
from pydantic import BaseModel, Field
from typing_extensions import TypeIs
from crewai.agent import Agent
from crewai.lite_agent_output import LiteAgentOutput
@@ -12,13 +8,6 @@ from crewai.llms.base_llm import BaseLLM
from crewai.tasks.task_output import TaskOutput
def _is_coroutine(
obj: LiteAgentOutput | Coroutine[Any, Any, LiteAgentOutput],
) -> TypeIs[Coroutine[Any, Any, LiteAgentOutput]]:
"""Check if obj is a coroutine for type narrowing."""
return inspect.iscoroutine(obj)
class LLMGuardrailResult(BaseModel):
valid: bool = Field(
description="Whether the task output complies with the guardrail"
@@ -73,10 +62,7 @@ class LLMGuardrail:
- If the Task result complies with the guardrail, saying that is valid
"""
kickoff_result = agent.kickoff(query, response_format=LLMGuardrailResult)
if _is_coroutine(kickoff_result):
return asyncio.run(kickoff_result)
return kickoff_result
return agent.kickoff(query, response_format=LLMGuardrailResult)
def __call__(self, task_output: TaskOutput) -> tuple[bool, Any]:
"""Validates the output of a task based on specified criteria.

View File

@@ -903,7 +903,7 @@ class Telemetry:
{
"id": str(task.id),
"description": task.description,
"output": task.output.raw if task.output else "",
"output": task.output.raw_output,
}
for task in crew.tasks
]
@@ -923,9 +923,6 @@ class Telemetry:
value: The attribute value.
"""
if span is None:
return
def _operation() -> None:
return span.set_attribute(key, value)

View File

@@ -27,14 +27,16 @@ class MCPNativeTool(BaseTool):
tool_name: str,
tool_schema: dict[str, Any],
server_name: str,
original_tool_name: str | None = None,
) -> None:
"""Initialize native MCP tool.
Args:
mcp_client: MCPClient instance with active session.
tool_name: Original name of the tool on the MCP server.
tool_name: Name of the tool (may be prefixed).
tool_schema: Schema information for the tool.
server_name: Name of the MCP server for prefixing.
original_tool_name: Original name of the tool on the MCP server.
"""
# Create tool name with server prefix to avoid conflicts
prefixed_name = f"{server_name}_{tool_name}"
@@ -57,7 +59,7 @@ class MCPNativeTool(BaseTool):
# Set instance attributes after super().__init__
self._mcp_client = mcp_client
self._original_tool_name = tool_name
self._original_tool_name = original_tool_name or tool_name
self._server_name = server_name
# self._logger = logging.getLogger(__name__)

View File

@@ -270,7 +270,6 @@ class ToolUsage:
result = None # type: ignore
should_retry = False
available_tool = None
error_event_emitted = False
try:
if self.tools_handler and self.tools_handler.cache:
@@ -409,7 +408,6 @@ class ToolUsage:
except Exception as e:
self.on_tool_error(tool=tool, tool_calling=calling, e=e)
error_event_emitted = True
self._run_attempts += 1
if self._run_attempts > self._max_parsing_attempts:
self._telemetry.tool_usage_error(llm=self.function_calling_llm)
@@ -437,7 +435,7 @@ class ToolUsage:
result = self._format_result(result=result)
finally:
if started_event_emitted and not error_event_emitted:
if started_event_emitted:
self.on_tool_use_finished(
tool=tool,
tool_calling=calling,
@@ -502,7 +500,6 @@ class ToolUsage:
result = None # type: ignore
should_retry = False
available_tool = None
error_event_emitted = False
try:
if self.tools_handler and self.tools_handler.cache:
@@ -641,7 +638,6 @@ class ToolUsage:
except Exception as e:
self.on_tool_error(tool=tool, tool_calling=calling, e=e)
error_event_emitted = True
self._run_attempts += 1
if self._run_attempts > self._max_parsing_attempts:
self._telemetry.tool_usage_error(llm=self.function_calling_llm)
@@ -669,7 +665,7 @@ class ToolUsage:
result = self._format_result(result=result)
finally:
if started_event_emitted and not error_event_emitted:
if started_event_emitted:
self.on_tool_use_finished(
tool=tool,
tool_calling=calling,

View File

@@ -0,0 +1,37 @@
"""Human-in-the-loop (HITL) type definitions.
This module provides type definitions for human-in-the-loop interactions
in crew executions.
"""
from typing import TypedDict
class HITLResumeInfo(TypedDict, total=False):
"""HITL resume information passed from flow to crew.
Attributes:
task_id: Unique identifier for the task.
crew_execution_id: Unique identifier for the crew execution.
task_key: Key identifying the specific task.
task_output: Output from the task before human intervention.
human_feedback: Feedback provided by the human.
previous_messages: History of messages in the conversation.
"""
task_id: str
crew_execution_id: str
task_key: str
task_output: str
human_feedback: str
previous_messages: list[dict[str, str]]
class CrewInputsWithHITL(TypedDict, total=False):
"""Crew inputs that may contain HITL resume information.
Attributes:
_hitl_resume: Optional HITL resume information for continuing execution.
"""
_hitl_resume: HITLResumeInfo

View File

@@ -42,8 +42,6 @@ if TYPE_CHECKING:
from crewai.llm import LLM
from crewai.task import Task
_create_plus_client_hook: Callable[[], Any] | None = None
class SummaryContent(TypedDict):
"""Structure for summary content entries.
@@ -93,11 +91,7 @@ def parse_tools(tools: list[BaseTool]) -> list[CrewStructuredTool]:
for tool in tools:
if isinstance(tool, CrewAITool):
structured_tool = tool.to_structured_tool()
structured_tool.current_usage_count = 0
if structured_tool._original_tool:
structured_tool._original_tool.current_usage_count = 0
tools_list.append(structured_tool)
tools_list.append(tool.to_structured_tool())
else:
raise ValueError("Tool is not a CrewStructuredTool or BaseTool")
@@ -824,15 +818,12 @@ def load_agent_from_repository(from_repository: str) -> dict[str, Any]:
if from_repository:
import importlib
if callable(_create_plus_client_hook):
client = _create_plus_client_hook()
else:
from crewai.cli.authentication.token import get_auth_token
from crewai.cli.plus_api import PlusAPI
from crewai.cli.authentication.token import get_auth_token
from crewai.cli.plus_api import PlusAPI
client = PlusAPI(api_key=get_auth_token())
client = PlusAPI(api_key=get_auth_token())
_print_current_organization()
response = asyncio.run(client.get_agent(from_repository))
response = client.get_agent(from_repository)
if response.status_code == 404:
raise AgentRepositoryError(
f"Agent {from_repository} does not exist, make sure the name is correct or the agent is available on your organization."

View File

@@ -1,7 +1,7 @@
from __future__ import annotations
from collections import defaultdict
from typing import TYPE_CHECKING, Any
from typing import TYPE_CHECKING
from pydantic import BaseModel, Field, InstanceOf
from rich.box import HEAVY_EDGE
@@ -36,13 +36,7 @@ class CrewEvaluator:
iteration: The current iteration of the evaluation.
"""
def __init__(
self,
crew: Crew,
eval_llm: InstanceOf[BaseLLM] | str | None = None,
openai_model_name: str | None = None,
llm: InstanceOf[BaseLLM] | str | None = None,
) -> None:
def __init__(self, crew: Crew, eval_llm: InstanceOf[BaseLLM]) -> None:
self.crew = crew
self.llm = eval_llm
self.tasks_scores: defaultdict[int, list[float]] = defaultdict(list)
@@ -92,9 +86,7 @@ class CrewEvaluator:
"""
self.iteration = iteration
def print_crew_evaluation_result(
self, token_usage: list[dict[str, Any]] | None = None
) -> None:
def print_crew_evaluation_result(self) -> None:
"""
Prints the evaluation result of the crew in a table.
A Crew with 2 tasks using the command crewai test -n 3
@@ -212,7 +204,7 @@ class CrewEvaluator:
CrewTestResultEvent(
quality=quality_score,
execution_duration=current_task.execution_duration,
model=getattr(self.llm, "model", str(self.llm)),
model=self.llm.model,
crew_name=self.crew.name,
crew=self.crew,
),

View File

@@ -4,8 +4,6 @@ from __future__ import annotations
from typing import TYPE_CHECKING, Final, Literal, NamedTuple
from crewai.events.utils.console_formatter import should_suppress_console_output
if TYPE_CHECKING:
from _typeshed import SupportsWrite
@@ -79,8 +77,6 @@ class Printer:
file: A file-like object (stream); defaults to the current sys.stdout.
flush: Whether to forcibly flush the stream.
"""
if should_suppress_console_output():
return
if isinstance(content, str):
content = [ColoredText(content, color)]
print(

View File

@@ -19,7 +19,6 @@ def to_serializable(
exclude: set[str] | None = None,
max_depth: int = 5,
_current_depth: int = 0,
_ancestors: set[int] | None = None,
) -> Serializable:
"""Converts a Python object into a JSON-compatible representation.
@@ -32,7 +31,6 @@ def to_serializable(
exclude: Set of keys to exclude from the result.
max_depth: Maximum recursion depth. Defaults to 5.
_current_depth: Current recursion depth (for internal use).
_ancestors: Set of ancestor object ids for cycle detection (for internal use).
Returns:
Serializable: A JSON-compatible structure.
@@ -43,29 +41,16 @@ def to_serializable(
if exclude is None:
exclude = set()
if _ancestors is None:
_ancestors = set()
if isinstance(obj, (str, int, float, bool, type(None))):
return obj
if isinstance(obj, uuid.UUID):
return str(obj)
if isinstance(obj, (date, datetime)):
return obj.isoformat()
object_id = id(obj)
if object_id in _ancestors:
return f"<circular_ref:{type(obj).__name__}>"
new_ancestors = _ancestors | {object_id}
if isinstance(obj, (list, tuple, set)):
return [
to_serializable(
item,
exclude=exclude,
max_depth=max_depth,
_current_depth=_current_depth + 1,
_ancestors=new_ancestors,
item, max_depth=max_depth, _current_depth=_current_depth + 1
)
for item in obj
]
@@ -76,7 +61,6 @@ def to_serializable(
exclude=exclude,
max_depth=max_depth,
_current_depth=_current_depth + 1,
_ancestors=new_ancestors,
)
for key, value in obj.items()
if key not in exclude
@@ -87,16 +71,12 @@ def to_serializable(
obj=obj.model_dump(exclude=exclude),
max_depth=max_depth,
_current_depth=_current_depth + 1,
_ancestors=new_ancestors,
)
except Exception:
try:
return {
_to_serializable_key(k): to_serializable(
v,
max_depth=max_depth,
_current_depth=_current_depth + 1,
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v, max_depth=max_depth, _current_depth=_current_depth + 1
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if k not in (exclude or set())

View File

@@ -51,10 +51,6 @@ class ConcreteAgentAdapter(BaseAgentAdapter):
# Dummy implementation for MCP tools
return []
def configure_structured_output(self, task: Any) -> None:
# Dummy implementation for structured output
pass
async def aexecute_task(
self,
task: Any,

View File

@@ -606,10 +606,9 @@ def test_lite_agent_with_invalid_llm():
@patch.dict("os.environ", {"CREWAI_PLATFORM_INTEGRATION_TOKEN": "test_token"})
@patch("crewai_tools.tools.crewai_platform_tools.crewai_platform_action_tool.requests.post")
@patch("crewai_tools.tools.crewai_platform_tools.crewai_platform_tool_builder.requests.get")
@pytest.mark.vcr()
def test_agent_kickoff_with_platform_tools(mock_get, mock_post):
def test_agent_kickoff_with_platform_tools(mock_get):
"""Test that Agent.kickoff() properly integrates platform tools with LiteAgent"""
mock_response = Mock()
mock_response.raise_for_status.return_value = None
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}
mock_get.return_value = mock_response
# Mock the platform tool execution
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mock_post_response.ok = True
mock_post_response.json.return_value = {
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"issue_url": "https://github.com/test/repo/issues/1"
}
mock_post.return_value = mock_post_response
agent = Agent(
role="Test Agent",
goal="Test goal",

View File

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import os
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def test_get_agent_with_org_uuid(self, mock_make_request, mock_settings_class):
mock_settings = MagicMock()
mock_settings.org_uuid = self.org_uuid
mock_settings.enterprise_base_url = os.getenv('CREWAI_PLUS_URL')
mock_settings_class.return_value = mock_settings
# re-initialize Client
self.api = PlusAPI(self.api_key)
mock_response = MagicMock()
mock_make_request.return_value = mock_response
response = self.api.get_agent("test_agent_handle")
self.assert_request_with_org_id(
mock_make_request, "GET", "/crewai_plus/api/v1/agents/test_agent_handle"
)
self.assertEqual(response, mock_response)
@patch("crewai.cli.plus_api.PlusAPI._make_request")
def test_get_tool(self, mock_make_request):
mock_response = MagicMock()
@@ -309,49 +338,3 @@ class TestPlusAPI(unittest.TestCase):
custom_api.base_url,
"https://custom-url-from-env.com",
)
@pytest.mark.asyncio
@patch("httpx.AsyncClient")
async def test_get_agent(mock_async_client_class):
api = PlusAPI("test_api_key")
mock_response = MagicMock()
mock_client_instance = AsyncMock()
mock_client_instance.get.return_value = mock_response
mock_async_client_class.return_value.__aenter__.return_value = mock_client_instance
response = await api.get_agent("test_agent_handle")
mock_client_instance.get.assert_called_once_with(
f"{api.base_url}/crewai_plus/api/v1/agents/test_agent_handle",
headers=api.headers,
)
assert response == mock_response
@pytest.mark.asyncio
@patch("httpx.AsyncClient")
@patch("crewai.cli.plus_api.Settings")
async def test_get_agent_with_org_uuid(mock_settings_class, mock_async_client_class):
org_uuid = "test-org-uuid"
mock_settings = MagicMock()
mock_settings.org_uuid = org_uuid
mock_settings.enterprise_base_url = os.getenv("CREWAI_PLUS_URL")
mock_settings_class.return_value = mock_settings
api = PlusAPI("test_api_key")
mock_response = MagicMock()
mock_client_instance = AsyncMock()
mock_client_instance.get.return_value = mock_response
mock_async_client_class.return_value.__aenter__.return_value = mock_client_instance
response = await api.get_agent("test_agent_handle")
mock_client_instance.get.assert_called_once_with(
f"{api.base_url}/crewai_plus/api/v1/agents/test_agent_handle",
headers=api.headers,
)
assert "X-Crewai-Organization-Id" in api.headers
assert api.headers["X-Crewai-Organization-Id"] == org_uuid
assert response == mock_response

View File

@@ -177,40 +177,4 @@ class TestTriggeredByScope:
raise ValueError("test error")
except ValueError:
pass
assert get_triggering_event_id() is None
def test_agent_scope_preserved_after_tool_error_event() -> None:
from crewai.events import crewai_event_bus
from crewai.events.types.tool_usage_events import (
ToolUsageErrorEvent,
ToolUsageStartedEvent,
)
push_event_scope("crew-1", "crew_kickoff_started")
push_event_scope("task-1", "task_started")
push_event_scope("agent-1", "agent_execution_started")
crewai_event_bus.emit(
None,
ToolUsageStartedEvent(
tool_name="test_tool",
tool_args={},
agent_key="test_agent",
)
)
crewai_event_bus.emit(
None,
ToolUsageErrorEvent(
tool_name="test_tool",
tool_args={},
agent_key="test_agent",
error=ValueError("test error"),
)
)
crewai_event_bus.flush()
assert get_current_parent_id() == "agent-1"
assert get_triggering_event_id() is None

View File

@@ -308,7 +308,6 @@ def test_external_memory_search_events(
"parent_event_id": None,
"previous_event_id": ANY,
"triggered_by_event_id": None,
"started_event_id": ANY,
"emission_sequence": ANY,
"query": "test value",
"limit": 3,
@@ -331,7 +330,6 @@ def test_external_memory_search_events(
"parent_event_id": ANY,
"previous_event_id": ANY,
"triggered_by_event_id": None,
"started_event_id": ANY,
"emission_sequence": ANY,
"query": "test value",
"results": [],
@@ -392,7 +390,6 @@ def test_external_memory_save_events(
"parent_event_id": None,
"previous_event_id": ANY,
"triggered_by_event_id": None,
"started_event_id": ANY,
"emission_sequence": ANY,
"value": "saving value",
"metadata": {"task": "test_task"},
@@ -414,7 +411,6 @@ def test_external_memory_save_events(
"parent_event_id": ANY,
"previous_event_id": ANY,
"triggered_by_event_id": None,
"started_event_id": ANY,
"emission_sequence": ANY,
"value": "saving value",
"metadata": {"task": "test_task"},

View File

@@ -74,7 +74,6 @@ def test_long_term_memory_save_events(long_term_memory):
"parent_event_id": None,
"previous_event_id": ANY,
"triggered_by_event_id": None,
"started_event_id": ANY,
"emission_sequence": ANY,
"value": "test_task",
"metadata": {"task": "test_task", "quality": 0.5},
@@ -95,7 +94,6 @@ def test_long_term_memory_save_events(long_term_memory):
"parent_event_id": None,
"previous_event_id": ANY,
"triggered_by_event_id": None,
"started_event_id": ANY,
"emission_sequence": ANY,
"value": "test_task",
"metadata": {
@@ -155,7 +153,6 @@ def test_long_term_memory_search_events(long_term_memory):
"parent_event_id": None,
"previous_event_id": ANY,
"triggered_by_event_id": None,
"started_event_id": ANY,
"emission_sequence": ANY,
"query": "test query",
"limit": 5,
@@ -178,7 +175,6 @@ def test_long_term_memory_search_events(long_term_memory):
"parent_event_id": ANY,
"previous_event_id": ANY,
"triggered_by_event_id": None,
"started_event_id": ANY,
"emission_sequence": ANY,
"query": "test query",
"results": None,

View File

@@ -85,7 +85,6 @@ def test_short_term_memory_search_events(short_term_memory):
"parent_event_id": None,
"previous_event_id": ANY,
"triggered_by_event_id": None,
"started_event_id": ANY,
"emission_sequence": ANY,
"query": "test value",
"limit": 3,
@@ -108,7 +107,6 @@ def test_short_term_memory_search_events(short_term_memory):
"parent_event_id": None,
"previous_event_id": ANY,
"triggered_by_event_id": None,
"started_event_id": ANY,
"emission_sequence": ANY,
"query": "test value",
"results": [],
@@ -166,7 +164,6 @@ def test_short_term_memory_save_events(short_term_memory):
"parent_event_id": None,
"previous_event_id": ANY,
"triggered_by_event_id": None,
"started_event_id": ANY,
"emission_sequence": ANY,
"value": "test value",
"metadata": {"task": "test_task"},
@@ -188,7 +185,6 @@ def test_short_term_memory_save_events(short_term_memory):
"parent_event_id": None,
"previous_event_id": ANY,
"triggered_by_event_id": None,
"started_event_id": ANY,
"emission_sequence": ANY,
"value": "test value",
"metadata": {"task": "test_task"},

View File

@@ -157,176 +157,6 @@ class TestMultiStepFlows:
assert execution_order == ["generate", "review", "finalize"]
def test_chained_router_feedback_steps(self):
"""Test that a router outcome can trigger another router method.
Regression test: @listen("outcome") combined with @human_feedback(emit=...)
creates a method that is both a listener and a router. The flow must find
and execute it when the upstream router emits the matching outcome.
"""
execution_order: list[str] = []
class ChainedRouterFlow(Flow):
@start()
@human_feedback(
message="First review:",
emit=["approved", "rejected"],
llm="gpt-4o-mini",
)
def draft(self):
execution_order.append("draft")
return "draft content"
@listen("approved")
@human_feedback(
message="Final review:",
emit=["publish", "revise"],
llm="gpt-4o-mini",
)
def final_review(self, prev: HumanFeedbackResult):
execution_order.append("final_review")
return "final content"
@listen("rejected")
def on_rejected(self, prev: HumanFeedbackResult):
execution_order.append("on_rejected")
return "rejected"
@listen("publish")
def on_publish(self, prev: HumanFeedbackResult):
execution_order.append("on_publish")
return "published"
@listen("revise")
def on_revise(self, prev: HumanFeedbackResult):
execution_order.append("on_revise")
return "revised"
flow = ChainedRouterFlow()
with (
patch.object(
flow,
"_request_human_feedback",
side_effect=["looks good", "ship it"],
),
patch.object(
flow,
"_collapse_to_outcome",
side_effect=["approved", "publish"],
),
):
result = flow.kickoff()
assert execution_order == ["draft", "final_review", "on_publish"]
assert result == "published"
assert len(flow.human_feedback_history) == 2
assert flow.human_feedback_history[0].outcome == "approved"
assert flow.human_feedback_history[1].outcome == "publish"
def test_chained_router_rejected_path(self):
"""Test that a start-router outcome routes to a non-router listener."""
execution_order: list[str] = []
class ChainedRouterFlow(Flow):
@start()
@human_feedback(
message="Review:",
emit=["approved", "rejected"],
llm="gpt-4o-mini",
)
def draft(self):
execution_order.append("draft")
return "draft"
@listen("approved")
@human_feedback(
message="Final:",
emit=["publish", "revise"],
llm="gpt-4o-mini",
)
def final_review(self, prev: HumanFeedbackResult):
execution_order.append("final_review")
return "final"
@listen("rejected")
def on_rejected(self, prev: HumanFeedbackResult):
execution_order.append("on_rejected")
return "rejected"
flow = ChainedRouterFlow()
with (
patch.object(
flow, "_request_human_feedback", return_value="bad"
),
patch.object(
flow, "_collapse_to_outcome", return_value="rejected"
),
):
result = flow.kickoff()
assert execution_order == ["draft", "on_rejected"]
assert result == "rejected"
assert len(flow.human_feedback_history) == 1
assert flow.human_feedback_history[0].outcome == "rejected"
def test_router_and_non_router_listeners_for_same_outcome(self):
"""Test that both router and non-router listeners fire for the same outcome."""
execution_order: list[str] = []
class MixedListenerFlow(Flow):
@start()
@human_feedback(
message="Review:",
emit=["approved", "rejected"],
llm="gpt-4o-mini",
)
def draft(self):
execution_order.append("draft")
return "draft"
@listen("approved")
@human_feedback(
message="Final:",
emit=["publish", "revise"],
llm="gpt-4o-mini",
)
def router_listener(self, prev: HumanFeedbackResult):
execution_order.append("router_listener")
return "final"
@listen("approved")
def plain_listener(self, prev: HumanFeedbackResult):
execution_order.append("plain_listener")
return "logged"
@listen("publish")
def on_publish(self, prev: HumanFeedbackResult):
execution_order.append("on_publish")
return "published"
flow = MixedListenerFlow()
with (
patch.object(
flow,
"_request_human_feedback",
side_effect=["approve it", "publish it"],
),
patch.object(
flow,
"_collapse_to_outcome",
side_effect=["approved", "publish"],
),
):
flow.kickoff()
assert "draft" in execution_order
assert "router_listener" in execution_order
assert "plain_listener" in execution_order
assert "on_publish" in execution_order
class TestStateManagement:
"""Tests for state management with human feedback."""

View File

@@ -10,9 +10,7 @@ from crewai import Agent, Task
from crewai.events.event_bus import crewai_event_bus
from crewai.events.types.tool_usage_events import (
ToolSelectionErrorEvent,
ToolUsageErrorEvent,
ToolUsageFinishedEvent,
ToolUsageStartedEvent,
ToolValidateInputErrorEvent,
)
from crewai.tools import BaseTool
@@ -746,78 +744,3 @@ def test_tool_usage_finished_event_with_cached_result():
assert isinstance(event.started_at, datetime.datetime)
assert isinstance(event.finished_at, datetime.datetime)
assert event.type == "tool_usage_finished"
def test_tool_error_does_not_emit_finished_event():
from crewai.tools.tool_calling import ToolCalling
class FailingTool(BaseTool):
name: str = "Failing Tool"
description: str = "A tool that always fails"
def _run(self, **kwargs) -> str:
raise ValueError("Intentional failure")
failing_tool = FailingTool().to_structured_tool()
mock_agent = MagicMock()
mock_agent.key = "test_agent_key"
mock_agent.role = "test_agent_role"
mock_agent._original_role = "test_agent_role"
mock_agent.verbose = False
mock_agent.fingerprint = None
mock_agent.i18n.tools.return_value = {"name": "Add Image"}
mock_agent.i18n.errors.return_value = "Error: {error}"
mock_agent.i18n.slice.return_value = "Available tools: {tool_names}"
mock_task = MagicMock()
mock_task.delegations = 0
mock_task.name = "Test Task"
mock_task.description = "A test task"
mock_task.id = "test-task-id"
mock_action = MagicMock()
mock_action.tool = "failing_tool"
mock_action.tool_input = "{}"
tool_usage = ToolUsage(
tools_handler=MagicMock(cache=None, last_used_tool=None),
tools=[failing_tool],
task=mock_task,
function_calling_llm=None,
agent=mock_agent,
action=mock_action,
)
started_events = []
error_events = []
finished_events = []
error_received = threading.Event()
@crewai_event_bus.on(ToolUsageStartedEvent)
def on_started(source, event):
if event.tool_name == "failing_tool":
started_events.append(event)
@crewai_event_bus.on(ToolUsageErrorEvent)
def on_error(source, event):
if event.tool_name == "failing_tool":
error_events.append(event)
error_received.set()
@crewai_event_bus.on(ToolUsageFinishedEvent)
def on_finished(source, event):
if event.tool_name == "failing_tool":
finished_events.append(event)
tool_calling = ToolCalling(tool_name="failing_tool", arguments={})
tool_usage.use(calling=tool_calling, tool_string="Action: failing_tool")
assert error_received.wait(timeout=5), "Timeout waiting for error event"
crewai_event_bus.flush()
assert len(started_events) >= 1, "Expected at least one ToolUsageStartedEvent"
assert len(error_events) >= 1, "Expected at least one ToolUsageErrorEvent"
assert len(finished_events) == 0, (
"ToolUsageFinishedEvent should NOT be emitted after ToolUsageErrorEvent"
)

156
uv.lock generated
View File

@@ -1295,7 +1295,7 @@ requires-dist = [
{ name = "json5", specifier = "~=0.10.0" },
{ name = "jsonref", specifier = "~=1.1.0" },
{ name = "litellm", marker = "extra == 'litellm'", specifier = ">=1.74.9,<3" },
{ name = "mcp", specifier = "~=1.26.0" },
{ name = "mcp", specifier = "~=1.23.1" },
{ name = "mem0ai", marker = "extra == 'mem0'", specifier = "~=0.1.94" },
{ name = "openai", specifier = ">=1.83.0,<3" },
{ name = "openpyxl", specifier = "~=3.1.5" },
@@ -1311,7 +1311,7 @@ requires-dist = [
{ name = "pyjwt", specifier = ">=2.9.0,<3" },
{ name = "python-dotenv", specifier = "~=1.1.1" },
{ name = "qdrant-client", extras = ["fastembed"], marker = "extra == 'qdrant'", specifier = "~=1.14.3" },
{ name = "regex", specifier = "~=2026.1.15" },
{ name = "regex", specifier = "~=2024.9.11" },
{ name = "tiktoken", marker = "extra == 'embeddings'", specifier = "~=0.8.0" },
{ name = "tokenizers", specifier = "~=0.20.3" },
{ name = "tomli", specifier = "~=2.0.2" },
@@ -3777,7 +3777,7 @@ wheels = [
[[package]]
name = "mcp"
version = "1.26.0"
version = "1.23.3"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "anyio" },
@@ -3795,9 +3795,9 @@ dependencies = [
{ name = "typing-inspection" },
{ name = "uvicorn", marker = "sys_platform != 'emscripten'" },
]
sdist = { url = "https://files.pythonhosted.org/packages/fc/6d/62e76bbb8144d6ed86e202b5edd8a4cb631e7c8130f3f4893c3f90262b10/mcp-1.26.0.tar.gz", hash = "sha256:db6e2ef491eecc1a0d93711a76f28dec2e05999f93afd48795da1c1137142c66", size = 608005, upload-time = "2026-01-24T19:40:32.468Z" }
sdist = { url = "https://files.pythonhosted.org/packages/a7/a4/d06a303f45997e266f2c228081abe299bbcba216cb806128e2e49095d25f/mcp-1.23.3.tar.gz", hash = "sha256:b3b0da2cc949950ce1259c7bfc1b081905a51916fcd7c8182125b85e70825201", size = 600697, upload-time = "2025-12-09T16:04:37.351Z" }
wheels = [
{ url = "https://files.pythonhosted.org/packages/fd/d9/eaa1f80170d2b7c5ba23f3b59f766f3a0bb41155fbc32a69adfa1adaaef9/mcp-1.26.0-py3-none-any.whl", hash = "sha256:904a21c33c25aa98ddbeb47273033c435e595bbacfdb177f4bd87f6dceebe1ca", size = 233615, upload-time = "2026-01-24T19:40:30.652Z" },
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[[package]]
@@ -6792,91 +6792,71 @@ wheels = [
[[package]]
name = "regex"
version = "2026.1.15"
version = "2024.9.11"
source = { registry = "https://pypi.org/simple" }
sdist = { url = "https://files.pythonhosted.org/packages/0b/86/07d5056945f9ec4590b518171c4254a5925832eb727b56d3c38a7476f316/regex-2026.1.15.tar.gz", hash = "sha256:164759aa25575cbc0651bef59a0b18353e54300d79ace8084c818ad8ac72b7d5", size = 414811, upload-time = "2026-01-14T23:18:02.775Z" }
sdist = { url = "https://files.pythonhosted.org/packages/f9/38/148df33b4dbca3bd069b963acab5e0fa1a9dbd6820f8c322d0dd6faeff96/regex-2024.9.11.tar.gz", hash = "sha256:6c188c307e8433bcb63dc1915022deb553b4203a70722fc542c363bf120a01fd", size = 399403, upload-time = "2024-09-11T19:00:09.814Z" }
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