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Merge branch 'main' into gl/feat/a2a-agent-cards

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This commit is contained in:
Greyson LaLonde
2026-01-14 05:18:10 -05:00
parent 422b35cdb7 9edbf89b68
commit f806cf5bfb
45 changed files with 3413 additions and 83 deletions
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2
lib/crewai-tools/pyproject.toml
View File

@@ -12,7 +12,7 @@ dependencies = [
"pytube~=15.0.0",
"requests~=2.32.5",
"docker~=7.1.0",
"crewai==1.7.2",
"crewai==1.8.0",
"lancedb~=0.5.4",
"tiktoken~=0.8.0",
"beautifulsoup4~=4.13.4",

2
lib/crewai-tools/src/crewai_tools/__init__.py
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@@ -291,4 +291,4 @@ __all__ = [
"ZapierActionTools",
]
__version__ = "1.7.2"
__version__ = "1.8.0"

2
lib/crewai/pyproject.toml
View File

@@ -49,7 +49,7 @@ Repository = "https://github.com/crewAIInc/crewAI"
[project.optional-dependencies]
tools = [
"crewai-tools==1.7.2",
"crewai-tools==1.8.0",
]
embeddings = [
"tiktoken~=0.8.0"

2
lib/crewai/src/crewai/__init__.py
View File

@@ -40,7 +40,7 @@ def _suppress_pydantic_deprecation_warnings() -> None:
_suppress_pydantic_deprecation_warnings()
__version__ = "1.7.2"
__version__ = "1.8.0"
_telemetry_submitted = False

11
lib/crewai/src/crewai/a2a/config.py
View File

@@ -6,7 +6,7 @@ This module is separate from experimental.a2a to avoid circular imports.
from __future__ import annotations
from importlib.metadata import version
from typing import Any, ClassVar
from typing import Any, ClassVar, Literal
from a2a.types import (
AgentCapabilities,
@@ -54,6 +54,7 @@ class A2AConfig(BaseModel):
fail_fast: If True, raise error when agent unreachable; if False, skip and continue.
trust_remote_completion_status: If True, return A2A agent's result directly when completed.
updates: Update mechanism config.
transport_protocol: A2A transport protocol (grpc, jsonrpc, http+json).
"""
model_config: ClassVar[ConfigDict] = ConfigDict(extra="forbid")
@@ -83,6 +84,10 @@ class A2AConfig(BaseModel):
default_factory=_get_default_update_config,
description="Update mechanism config",
)
transport_protocol: Literal["JSONRPC", "GRPC", "HTTP+JSON"] = Field(
default="JSONRPC",
description="Specified mode of A2A transport protocol",
)
class A2AClientConfig(BaseModel):
@@ -146,6 +151,10 @@ class A2AClientConfig(BaseModel):
default_factory=list,
description="Extension URIs the client supports",
)
transport_protocol: Literal["JSONRPC", "GRPC", "HTTP+JSON"] = Field(
default="JSONRPC",
description="Specified mode of A2A transport protocol",
)
class A2AServerConfig(BaseModel):

47
lib/crewai/src/crewai/a2a/utils/delegation.py
View File

@@ -5,7 +5,7 @@ from __future__ import annotations
import asyncio
from collections.abc import AsyncIterator, MutableMapping
from contextlib import asynccontextmanager
from typing import TYPE_CHECKING, Any
from typing import TYPE_CHECKING, Any, Literal
import uuid
from a2a.client import Client, ClientConfig, ClientFactory
@@ -16,7 +16,6 @@ from a2a.types import (
PushNotificationConfig as A2APushNotificationConfig,
Role,
TextPart,
TransportProtocol,
)
import httpx
from pydantic import BaseModel
@@ -72,6 +71,7 @@ def get_handler(config: UpdateConfig | None) -> HandlerType:
def execute_a2a_delegation(
endpoint: str,
transport_protocol: Literal["JSONRPC", "GRPC", "HTTP+JSON"],
auth: AuthScheme | None,
timeout: int,
task_description: str,
@@ -95,6 +95,23 @@ def execute_a2a_delegation(
use aexecute_a2a_delegation directly.
Args:
endpoint: A2A agent endpoint URL (AgentCard URL)
transport_protocol: Optional A2A transport protocol (grpc, jsonrpc, http+json)
auth: Optional AuthScheme for authentication (Bearer, OAuth2, API Key, HTTP Basic/Digest)
timeout: Request timeout in seconds
task_description: The task to delegate
context: Optional context information
context_id: Context ID for correlating messages/tasks
task_id: Specific task identifier
reference_task_ids: List of related task IDs
metadata: Additional metadata (external_id, request_id, etc.)
extensions: Protocol extensions for custom fields
conversation_history: Previous Message objects from conversation
agent_id: Agent identifier for logging
agent_role: Role of the CrewAI agent delegating the task
agent_branch: Optional agent tree branch for logging
response_model: Optional Pydantic model for structured outputs
turn_number: Optional turn number for multi-turn conversations
endpoint: A2A agent endpoint URL.
auth: Optional AuthScheme for authentication.
timeout: Request timeout in seconds.
@@ -136,6 +153,7 @@ def execute_a2a_delegation(
agent_role=agent_role,
agent_branch=agent_branch,
response_model=response_model,
transport_protocol=transport_protocol,
turn_number=turn_number,
updates=updates,
)
@@ -146,6 +164,7 @@ def execute_a2a_delegation(
async def aexecute_a2a_delegation(
endpoint: str,
transport_protocol: Literal["JSONRPC", "GRPC", "HTTP+JSON"],
auth: AuthScheme | None,
timeout: int,
task_description: str,
@@ -169,6 +188,23 @@ async def aexecute_a2a_delegation(
in an async context (e.g., with Crew.akickoff() or agent.aexecute_task()).
Args:
endpoint: A2A agent endpoint URL
transport_protocol: Optional A2A transport protocol (grpc, jsonrpc, http+json)
auth: Optional AuthScheme for authentication
timeout: Request timeout in seconds
task_description: Task to delegate
context: Optional context
context_id: Context ID for correlation
task_id: Specific task identifier
reference_task_ids: Related task IDs
metadata: Additional metadata
extensions: Protocol extensions
conversation_history: Previous Message objects
turn_number: Current turn number
agent_branch: Agent tree branch for logging
agent_id: Agent identifier for logging
agent_role: Agent role for logging
response_model: Optional Pydantic model for structured outputs
endpoint: A2A agent endpoint URL.
auth: Optional AuthScheme for authentication.
timeout: Request timeout in seconds.
@@ -227,6 +263,7 @@ async def aexecute_a2a_delegation(
agent_role=agent_role,
response_model=response_model,
updates=updates,
transport_protocol=transport_protocol,
)
crewai_event_bus.emit(
@@ -244,6 +281,7 @@ async def aexecute_a2a_delegation(
async def _aexecute_a2a_delegation_impl(
endpoint: str,
transport_protocol: Literal["JSONRPC", "GRPC", "HTTP+JSON"],
auth: AuthScheme | None,
timeout: int,
task_description: str,
@@ -337,7 +375,6 @@ async def _aexecute_a2a_delegation_impl(
extensions=extensions,
)
transport_protocol = TransportProtocol("JSONRPC")
new_messages: list[Message] = [*conversation_history, message]
crewai_event_bus.emit(
None,
@@ -409,7 +446,7 @@ async def _aexecute_a2a_delegation_impl(
@asynccontextmanager
async def _create_a2a_client(
agent_card: AgentCard,
transport_protocol: TransportProtocol,
transport_protocol: Literal["JSONRPC", "GRPC", "HTTP+JSON"],
timeout: int,
headers: MutableMapping[str, str],
streaming: bool,
@@ -452,7 +489,7 @@ async def _create_a2a_client(
config = ClientConfig(
httpx_client=httpx_client,
supported_transports=[str(transport_protocol.value)],
supported_transports=[transport_protocol],
streaming=streaming and not use_polling,
polling=use_polling,
accepted_output_modes=["application/json"],

2
lib/crewai/src/crewai/a2a/wrapper.py
View File

@@ -770,6 +770,7 @@ def _delegate_to_a2a(
response_model=agent_config.response_model,
turn_number=turn_num + 1,
updates=agent_config.updates,
transport_protocol=agent_config.transport_protocol,
)
conversation_history = a2a_result.get("history", [])
@@ -1084,6 +1085,7 @@ async def _adelegate_to_a2a(
agent_branch=agent_branch,
response_model=agent_config.response_model,
turn_number=turn_num + 1,
transport_protocol=agent_config.transport_protocol,
updates=agent_config.updates,
)

2
lib/crewai/src/crewai/cli/templates/crew/pyproject.toml
View File

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
authors = [{ name = "Your Name", email = "you@example.com" }]
requires-python = ">=3.10,<3.14"
dependencies = [
"crewai[tools]==1.7.2"
"crewai[tools]==1.8.0"
]
[project.scripts]

2
lib/crewai/src/crewai/cli/templates/flow/pyproject.toml
View File

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
authors = [{ name = "Your Name", email = "you@example.com" }]
requires-python = ">=3.10,<3.14"
dependencies = [
"crewai[tools]==1.7.2"
"crewai[tools]==1.8.0"
]
[project.scripts]

6
lib/crewai/src/crewai/events/event_listener.py
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@@ -209,10 +209,9 @@ class EventListener(BaseEventListener):
@crewai_event_bus.on(TaskCompletedEvent)
def on_task_completed(source: Any, event: TaskCompletedEvent) -> None:
# Handle telemetry
span = self.execution_spans.get(source)
span = self.execution_spans.pop(source, None)
if span:
self._telemetry.task_ended(span, source, source.agent.crew)
self.execution_spans[source] = None
# Pass task name if it exists
task_name = get_task_name(source)
@@ -222,11 +221,10 @@ class EventListener(BaseEventListener):
@crewai_event_bus.on(TaskFailedEvent)
def on_task_failed(source: Any, event: TaskFailedEvent) -> None:
span = self.execution_spans.get(source)
span = self.execution_spans.pop(source, None)
if span:
if source.agent and source.agent.crew:
self._telemetry.task_ended(span, source, source.agent.crew)
self.execution_spans[source] = None
# Pass task name if it exists
task_name = get_task_name(source)

72
lib/crewai/src/crewai/flow/flow.py
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@@ -1203,7 +1203,13 @@ class Flow(Generic[T], metaclass=FlowMeta):
result = self.kickoff(inputs=inputs)
result_holder.append(result)
except Exception as e:
signal_error(state, e)
# HumanFeedbackPending is expected control flow, not an error
from crewai.flow.async_feedback.types import HumanFeedbackPending
if isinstance(e, HumanFeedbackPending):
result_holder.append(e)
else:
signal_error(state, e)
finally:
self.stream = True
signal_end(state)
@@ -1258,7 +1264,13 @@ class Flow(Generic[T], metaclass=FlowMeta):
result = await self.kickoff_async(inputs=inputs)
result_holder.append(result)
except Exception as e:
signal_error(state, e, is_async=True)
# HumanFeedbackPending is expected control flow, not an error
from crewai.flow.async_feedback.types import HumanFeedbackPending
if isinstance(e, HumanFeedbackPending):
result_holder.append(e)
else:
signal_error(state, e, is_async=True)
finally:
self.stream = True
signal_end(state, is_async=True)
@@ -1590,29 +1602,45 @@ class Flow(Generic[T], metaclass=FlowMeta):
return result
except Exception as e:
if not self.suppress_flow_events:
# Check if this is a HumanFeedbackPending exception (paused, not failed)
from crewai.flow.async_feedback.types import HumanFeedbackPending
# Check if this is a HumanFeedbackPending exception (paused, not failed)
from crewai.flow.async_feedback.types import HumanFeedbackPending
if isinstance(e, HumanFeedbackPending):
# Auto-save pending feedback (create default persistence if needed)
if self._persistence is None:
from crewai.flow.persistence import SQLiteFlowPersistence
if isinstance(e, HumanFeedbackPending):
# Auto-save pending feedback (create default persistence if needed)
if self._persistence is None:
from crewai.flow.persistence import SQLiteFlowPersistence
self._persistence = SQLiteFlowPersistence()
self._persistence = SQLiteFlowPersistence()
# Regular failure
future = crewai_event_bus.emit(
self,
MethodExecutionFailedEvent(
type="method_execution_failed",
method_name=method_name,
flow_name=self.name or self.__class__.__name__,
error=e,
),
)
if future:
self._event_futures.append(future)
# Emit paused event (not failed)
if not self.suppress_flow_events:
future = crewai_event_bus.emit(
self,
MethodExecutionPausedEvent(
type="method_execution_paused",
method_name=method_name,
flow_name=self.name or self.__class__.__name__,
state=self._copy_and_serialize_state(),
flow_id=e.context.flow_id,
message=e.context.message,
emit=e.context.emit,
),
)
if future:
self._event_futures.append(future)
elif not self.suppress_flow_events:
# Regular failure - emit failed event
future = crewai_event_bus.emit(
self,
MethodExecutionFailedEvent(
type="method_execution_failed",
method_name=method_name,
flow_name=self.name or self.__class__.__name__,
error=e,
),
)
if future:
self._event_futures.append(future)
raise e
def _copy_and_serialize_state(self) -> dict[str, Any]:

5
lib/crewai/src/crewai/flow/flow_trackable.py
View File

@@ -1,4 +1,5 @@
import inspect
from typing import Any
from pydantic import BaseModel, Field, InstanceOf, model_validator
from typing_extensions import Self
@@ -14,14 +15,14 @@ class FlowTrackable(BaseModel):
inspecting the call stack.
"""
parent_flow: InstanceOf[Flow] | None = Field(
parent_flow: InstanceOf[Flow[Any]] | None = Field(
default=None,
description="The parent flow of the instance, if it was created inside a flow.",
)
@model_validator(mode="after")
def _set_parent_flow(self) -> Self:
max_depth = 5
max_depth = 8
frame = inspect.currentframe()
try:

26
lib/crewai/src/crewai/llms/providers/azure/completion.py
View File

@@ -443,7 +443,7 @@ class AzureCompletion(BaseLLM):
params["presence_penalty"] = self.presence_penalty
if self.max_tokens is not None:
params["max_tokens"] = self.max_tokens
if self.stop:
if self.stop and self.supports_stop_words():
params["stop"] = self.stop
# Handle tools/functions for Azure OpenAI models
@@ -931,8 +931,28 @@ class AzureCompletion(BaseLLM):
return self.is_openai_model
def supports_stop_words(self) -> bool:
"""Check if the model supports stop words."""
return True # Most Azure models support stop sequences
"""Check if the model supports stop words.
Models using the Responses API (GPT-5 family, o-series reasoning models,
computer-use-preview) do not support stop sequences.
See: https://learn.microsoft.com/en-us/azure/ai-foundry/foundry-models/concepts/models-sold-directly-by-azure
"""
model_lower = self.model.lower() if self.model else ""
if "gpt-5" in model_lower:
return False
o_series_models = ["o1", "o3", "o4", "o1-mini", "o3-mini", "o4-mini"]
responses_api_models = ["computer-use-preview"]
unsupported_stop_models = o_series_models + responses_api_models
for unsupported in unsupported_stop_models:
if unsupported in model_lower:
return False
return True
def get_context_window_size(self) -> int:
"""Get the context window size for the model."""

88
lib/crewai/tests/llms/azure/test_azure.py
View File

@@ -515,6 +515,94 @@ def test_azure_supports_stop_words():
assert llm.supports_stop_words() == True
def test_azure_gpt5_models_do_not_support_stop_words():
"""
Test that GPT-5 family models do not support stop words.
GPT-5 models use the Responses API which doesn't support stop sequences.
See: https://learn.microsoft.com/en-us/azure/ai-foundry/foundry-models/concepts/models-sold-directly-by-azure
"""
# GPT-5 base models
gpt5_models = [
"azure/gpt-5",
"azure/gpt-5-mini",
"azure/gpt-5-nano",
"azure/gpt-5-chat",
# GPT-5.1 series
"azure/gpt-5.1",
"azure/gpt-5.1-chat",
"azure/gpt-5.1-codex",
"azure/gpt-5.1-codex-mini",
# GPT-5.2 series
"azure/gpt-5.2",
"azure/gpt-5.2-chat",
]
for model_name in gpt5_models:
llm = LLM(model=model_name)
assert llm.supports_stop_words() == False, f"Expected {model_name} to NOT support stop words"
def test_azure_o_series_models_do_not_support_stop_words():
"""
Test that o-series reasoning models do not support stop words.
"""
o_series_models = [
"azure/o1",
"azure/o1-mini",
"azure/o3",
"azure/o3-mini",
"azure/o4",
"azure/o4-mini",
]
for model_name in o_series_models:
llm = LLM(model=model_name)
assert llm.supports_stop_words() == False, f"Expected {model_name} to NOT support stop words"
def test_azure_responses_api_models_do_not_support_stop_words():
"""
Test that models using the Responses API do not support stop words.
"""
responses_api_models = [
"azure/computer-use-preview",
]
for model_name in responses_api_models:
llm = LLM(model=model_name)
assert llm.supports_stop_words() == False, f"Expected {model_name} to NOT support stop words"
def test_azure_stop_words_not_included_for_unsupported_models():
"""
Test that stop words are not included in completion params for models that don't support them.
"""
with patch.dict(os.environ, {
"AZURE_API_KEY": "test-key",
"AZURE_ENDPOINT": "https://models.inference.ai.azure.com"
}):
# Test GPT-5 model - stop should NOT be included even if set
llm_gpt5 = LLM(
model="azure/gpt-5-nano",
stop=["STOP", "END"]
)
params = llm_gpt5._prepare_completion_params(
messages=[{"role": "user", "content": "test"}]
)
assert "stop" not in params, "stop should not be included for GPT-5 models"
# Test regular model - stop SHOULD be included
llm_gpt4 = LLM(
model="azure/gpt-4",
stop=["STOP", "END"]
)
params = llm_gpt4._prepare_completion_params(
messages=[{"role": "user", "content": "test"}]
)
assert "stop" in params, "stop should be included for GPT-4 models"
assert params["stop"] == ["STOP", "END"]
def test_azure_context_window_size():
"""
Test that Azure models return correct context window sizes

65
lib/crewai/tests/test_crew.py
View File

@@ -4500,6 +4500,71 @@ def test_crew_copy_with_memory():
pytest.fail(f"Copying crew raised an unexpected exception: {e}")
def test_sets_parent_flow_when_using_crewbase_pattern_inside_flow():
@CrewBase
class TestCrew:
agents_config = None
tasks_config = None
agents: list[BaseAgent]
tasks: list[Task]
@agent
def researcher(self) -> Agent:
return Agent(
role="Researcher",
goal="Research things",
backstory="Expert researcher",
)
@agent
def writer_agent(self) -> Agent:
return Agent(
role="Writer",
goal="Write things",
backstory="Expert writer",
)
@task
def research_task(self) -> Task:
return Task(
description="Test task for researcher",
expected_output="output",
agent=self.researcher(),
)
@task
def write_task(self) -> Task:
return Task(
description="Test task for writer",
expected_output="output",
agent=self.writer_agent(),
)
@crew
def crew(self) -> Crew:
return Crew(
agents=self.agents,
tasks=self.tasks,
process=Process.sequential,
)
captured_crew = None
class MyFlow(Flow):
@start()
def start_method(self):
nonlocal captured_crew
captured_crew = TestCrew().crew()
return captured_crew
flow = MyFlow()
flow.kickoff()
assert captured_crew is not None
assert captured_crew.parent_flow is flow
def test_sets_parent_flow_when_outside_flow(researcher, writer):
crew = Crew(
agents=[researcher, writer],

2
lib/devtools/src/crewai_devtools/__init__.py
View File

@@ -1,3 +1,3 @@
"""CrewAI development tools."""
__version__ = "1.7.2"
__version__ = "1.8.0"