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Author SHA1 Message Date
Joao Moura
aee571b775 feat: add support for agents to invoke Flows as tools
Agents can now declare flows=[MyFlow] and invoke them as regular tools.
Each Flow class is wrapped as a FlowTool(BaseTool) — the agent decides
WHEN to use it (via tool selection), the Flow handles HOW (deterministic
execution).

- Add flows field to Agent
- Add FlowTool and create_flow_tools in tools/flow_tool.py
- Export from crewai.__init__
- 14 tests

No dependency changes. No memory changes. Just the flow-tool feature.
2026-04-27 05:10:38 -07:00
Greyson LaLonde
cb46a1c4ba docs: update changelog and version for v1.14.3
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2026-04-25 00:13:43 +08:00
Greyson LaLonde
d9046b98dd feat: bump versions to 1.14.3 2026-04-25 00:04:46 +08:00
Tiago Freire
b0e2fda105 fix(flow): add execution_id separate from state.id
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* fix(flow): add execution_id separate from state.id (COR-48)

  When a consumer passes `id` in `kickoff(inputs=...)`, that value
  overwrites the flow's state.id — which was also being used as the
  execution tracking identity for telemetry, tracing, and external
  correlation. Two kickoffs sharing the same consumer id ended up
  with the same tracking id, breaking any downstream system that
  joins on it.

  Introduces `Flow.execution_id`: a stable per-run identifier stored
  as a `PrivateAttr` on the `Flow` model, exposed via property +
  setter. It defaults to a fresh `uuid4` per instance, is never
  touched by `inputs["id"]`, and can be assigned by outer systems
  that already have an execution identity (e.g. a task id).

  Switches the `current_flow_id` / `current_flow_request_id`
  ContextVars to seed from `execution_id` so OTel spans emitted by
  `FlowTrackable` children correlate on the stable tracking key.

  `state.id` keeps its existing override semantics for
  persistence/restore — consumers resuming a persisted flow via
  `inputs["id"]` work exactly as before.

  Adds tests covering default uniqueness per instance, immunity to
  consumer `inputs["id"]`, context-var propagation, absence from
  serialized state, and parity for dict-state flows.

Co-authored-by: Greyson LaLonde <greyson.r.lalonde@gmail.com>
2026-04-24 04:48:14 +08:00
Greyson LaLonde
69d777ca50 fix(flow): replay recorded method events on checkpoint resume 2026-04-24 03:41:55 +08:00
Greyson LaLonde
77b2835a1d fix(flow): serialize initial_state class refs as JSON schema
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2026-04-23 21:55:50 +08:00
Lorenze Jay
c77f1632dd fix: preserve metadata-only agent skills
Co-authored-by: Greyson LaLonde <greyson.r.lalonde@gmail.com>
2026-04-23 19:58:12 +08:00
Greyson LaLonde
69461076df refactor: dedupe checkpoint helpers and tighten state type hints 2026-04-23 19:29:04 +08:00
Greyson LaLonde
55937d7523 feat: emit lifecycle events for checkpoint operations
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2026-04-23 18:47:50 +08:00
34 changed files with 3495 additions and 106 deletions

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@@ -4,6 +4,54 @@ description: "تحديثات المنتج والتحسينات وإصلاحات
icon: "clock"
mode: "wide"
---
<Update label="25 أبريل 2026">
## v1.14.3
[عرض الإصدار على GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.3)
## ما الذي تغير
### الميزات
- إضافة أحداث دورة الحياة لعمليات نقطة التحقق
- إضافة دعم لـ e2b
- الرجوع إلى DefaultAzureCredential عند عدم توفير مفتاح API في تكامل Azure
- إضافة دعم Bedrock V4
- إضافة أدوات Daytona sandbox لوظائف محسّنة
- إضافة دعم نقطة التحقق والتفرع للوكلاء المستقلين
### إصلاحات الأخطاء
- إصلاح execution_id ليكون منفصلًا عن state.id
- حل مشكلة إعادة تشغيل أحداث الطريقة المسجلة عند استئناف نقطة التحقق
- إصلاح تسلسل مراجع class initial_state كـ JSON schema
- الحفاظ على مهارات الوكلاء التي تحتوي على بيانات وصفية فقط
- تمرير أسماء @CrewBase الضمنية إلى أحداث الطاقم
- دمج بيانات التنفيذ عند تهيئة دفعة مكررة
- إصلاح تسلسل حقول مراجع class Task لنقاط التحقق
- التعامل مع نتيجة BaseModel في حلقة إعادة المحاولة guardrail
- الحفاظ على thought_signature في استدعاءات أدوات Gemini للبث
- إصدار task_started عند استئناف التفرع وإعادة تصميم واجهة المستخدم النصية لنقطة التحقق
- استخدام تواريخ مستقبلية في اختبارات تقليم نقطة التحقق لمنع الفشل المعتمد على الوقت
- إصلاح ترتيب التشغيل الجاف والتعامل مع الفرع القديم الذي تم التحقق منه في إصدار أدوات التطوير
- ترقية lxml إلى >=6.1.0 لرقعة الأمان
- رفع python-dotenv إلى >=1.2.2 لرقعة الأمان
### الوثائق
- تحديث سجل التغييرات والإصدار لـ v1.14.3
- إضافة صفحة "بناء باستخدام الذكاء الاصطناعي" وتحديث التنقل لجميع اللغات
- إزالة الأسئلة الشائعة حول التسعير من صفحة البناء باستخدام الذكاء الاصطناعي عبر جميع المواقع
### الأداء
- تحسين MCP SDK وأنواع الأحداث لتقليل بدء التشغيل البارد بنسبة ~29%
### إعادة الهيكلة
- إعادة هيكلة مساعدي نقطة التحقق للقضاء على التكرار وتشديد تلميحات نوع الحالة
## المساهمون
@MatthiasHowellYopp, @akaKuruma, @alex-clawd, @github-actions[bot], @github-advanced-security[bot], @greysonlalonde, @iris-clawd, @lorenzejay, @mattatcha, @renatonitta
</Update>
<Update label="23 أبريل 2026">
## v1.14.3a3

File diff suppressed because it is too large Load Diff

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@@ -4,6 +4,54 @@ description: "Product updates, improvements, and bug fixes for CrewAI"
icon: "clock"
mode: "wide"
---
<Update label="Apr 25, 2026">
## v1.14.3
[View release on GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.3)
## What's Changed
### Features
- Add lifecycle events for checkpoint operations
- Add support for e2b
- Fall back to DefaultAzureCredential when no API key is provided in Azure integration
- Add Bedrock V4 support
- Add Daytona sandbox tools for enhanced functionality
- Add checkpoint and fork support to standalone agents
### Bug Fixes
- Fix execution_id to be separate from state.id
- Resolve replay of recorded method events on checkpoint resume
- Fix serialization of initial_state class references as JSON schema
- Preserve metadata-only agent skills
- Propagate implicit @CrewBase names to crew events
- Merge execution metadata on duplicate batch initialization
- Fix serialization of Task class-reference fields for checkpointing
- Handle BaseModel result in guardrail retry loop
- Preserve thought_signature in Gemini streaming tool calls
- Emit task_started on fork resume and redesign checkpoint TUI
- Use future dates in checkpoint prune tests to prevent time-dependent failures
- Fix dry-run order and handle checked-out stale branch in devtools release
- Upgrade lxml to >=6.1.0 for security patch
- Bump python-dotenv to >=1.2.2 for security patch
### Documentation
- Update changelog and version for v1.14.3
- Add 'Build with AI' page and update navigation for all languages
- Remove pricing FAQ from build-with-ai page across all locales
### Performance
- Optimize MCP SDK and event types to reduce cold start by ~29%
### Refactoring
- Refactor checkpoint helpers to eliminate duplication and tighten state type hints
## Contributors
@MatthiasHowellYopp, @akaKuruma, @alex-clawd, @github-actions[bot], @github-advanced-security[bot], @greysonlalonde, @iris-clawd, @lorenzejay, @mattatcha, @renatonitta
</Update>
<Update label="Apr 23, 2026">
## v1.14.3a3

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@@ -4,6 +4,54 @@ description: "CrewAI의 제품 업데이트, 개선 사항 및 버그 수정"
icon: "clock"
mode: "wide"
---
<Update label="2026년 4월 25일">
## v1.14.3
[GitHub 릴리스 보기](https://github.com/crewAIInc/crewAI/releases/tag/1.14.3)
## 변경 사항
### 기능
- 체크포인트 작업을 위한 생명주기 이벤트 추가
- e2b 지원 추가
- Azure 통합에서 API 키가 제공되지 않을 경우 DefaultAzureCredential로 대체
- Bedrock V4 지원 추가
- 향상된 기능을 위한 Daytona 샌드박스 도구 추가
- 독립형 에이전트에 체크포인트 및 포크 지원 추가
### 버그 수정
- execution_id를 state.id와 분리되도록 수정
- 체크포인트 재개 시 기록된 메서드 이벤트 재생 문제 해결
- initial_state 클래스 참조의 JSON 스키마 직렬화 수정
- 메타데이터 전용 에이전트 기술 보존
- 암묵적인 @CrewBase 이름을 크루 이벤트로 전파
- 중복 배치 초기화 시 실행 메타데이터 병합
- 체크포인트를 위한 Task 클래스 참조 필드의 직렬화 수정
- 가드레일 재시도 루프에서 BaseModel 결과 처리
- Gemini 스트리밍 도구 호출에서 thought_signature 보존
- 포크 재개 시 task_started 방출 및 체크포인트 TUI 재설계
- 체크포인트 가지치기 테스트에서 미래 날짜 사용하여 시간 의존적 실패 방지
- 드라이 런 주문 수정 및 devtools 릴리스에서 체크아웃된 오래된 브랜치 처리
- 보안 패치를 위해 lxml을 >=6.1.0으로 업그레이드
- 보안 패치를 위해 python-dotenv를 >=1.2.2로 업그레이드
### 문서
- v1.14.3에 대한 변경 로그 및 버전 업데이트
- 'AI로 빌드하기' 페이지 추가 및 모든 언어에 대한 내비게이션 업데이트
- 모든 로케일에서 build-with-ai 페이지의 가격 FAQ 제거
### 성능
- MCP SDK 및 이벤트 유형 최적화하여 콜드 스타트를 약 29% 감소
### 리팩토링
- 중복 제거 및 상태 유형 힌트를 강화하기 위해 체크포인트 헬퍼 리팩토링
## 기여자
@MatthiasHowellYopp, @akaKuruma, @alex-clawd, @github-actions[bot], @github-advanced-security[bot], @greysonlalonde, @iris-clawd, @lorenzejay, @mattatcha, @renatonitta
</Update>
<Update label="2026년 4월 23일">
## v1.14.3a3

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@@ -4,6 +4,54 @@ description: "Atualizações de produto, melhorias e correções do CrewAI"
icon: "clock"
mode: "wide"
---
<Update label="25 abr 2026">
## v1.14.3
[Ver release no GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.3)
## O que Mudou
### Recursos
- Adicionar eventos de ciclo de vida para operações de checkpoint
- Adicionar suporte para e2b
- Reverter para DefaultAzureCredential quando nenhuma chave de API for fornecida na integração com o Azure
- Adicionar suporte ao Bedrock V4
- Adicionar ferramentas de sandbox Daytona para funcionalidade aprimorada
- Adicionar suporte a checkpoint e fork para agentes autônomos
### Correções de Bugs
- Corrigir execution_id para ser separado de state.id
- Resolver a reprodução de eventos de método gravados na retomada do checkpoint
- Corrigir a serialização de referências de classe initial_state como esquema JSON
- Preservar habilidades de agente somente de metadados
- Propagar nomes implícitos @CrewBase para eventos da equipe
- Mesclar metadados de execução na inicialização de lote duplicado
- Corrigir a serialização de campos de referência de classe Task para checkpointing
- Lidar com o resultado BaseModel no loop de retry do guardrail
- Preservar thought_signature em chamadas de ferramentas de streaming Gemini
- Emitir task_started na retomada do fork e redesenhar TUI de checkpoint
- Usar datas futuras em testes de poda de checkpoint para evitar falhas dependentes do tempo
- Corrigir a ordem de dry-run e lidar com branch obsoleta verificada na liberação do devtools
- Atualizar lxml para >=6.1.0 para patch de segurança
- Aumentar python-dotenv para >=1.2.2 para patch de segurança
### Documentação
- Atualizar changelog e versão para v1.14.3
- Adicionar página 'Construir com IA' e atualizar navegação para todos os idiomas
- Remover FAQ de preços da página construir-com-ia em todos os locais
### Desempenho
- Otimizar MCP SDK e tipos de eventos para reduzir o tempo de inicialização a frio em ~29%
### Refatoração
- Refatorar auxiliares de checkpoint para eliminar duplicação e apertar dicas de tipo de estado
## Contribuidores
@MatthiasHowellYopp, @akaKuruma, @alex-clawd, @github-actions[bot], @github-advanced-security[bot], @greysonlalonde, @iris-clawd, @lorenzejay, @mattatcha, @renatonitta
</Update>
<Update label="23 abr 2026">
## v1.14.3a3

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@@ -152,4 +152,4 @@ __all__ = [
"wrap_file_source",
]
__version__ = "1.14.3a3"
__version__ = "1.14.3"

View File

@@ -10,7 +10,7 @@ requires-python = ">=3.10, <3.14"
dependencies = [
"pytube~=15.0.0",
"requests>=2.33.0,<3",
"crewai==1.14.3a3",
"crewai==1.14.3",
"tiktoken~=0.8.0",
"beautifulsoup4~=4.13.4",
"python-docx~=1.2.0",

View File

@@ -321,4 +321,4 @@ __all__ = [
"ZapierActionTools",
]
__version__ = "1.14.3a3"
__version__ = "1.14.3"

View File

@@ -55,7 +55,7 @@ Repository = "https://github.com/crewAIInc/crewAI"
[project.optional-dependencies]
tools = [
"crewai-tools==1.14.3a3",
"crewai-tools==1.14.3",
]
embeddings = [
"tiktoken~=0.8.0"

View File

@@ -48,7 +48,7 @@ def _suppress_pydantic_deprecation_warnings() -> None:
_suppress_pydantic_deprecation_warnings()
__version__ = "1.14.3a3"
__version__ = "1.14.3"
_LAZY_IMPORTS: dict[str, tuple[str, str]] = {
"Memory": ("crewai.memory.unified_memory", "Memory"),
@@ -94,10 +94,16 @@ try:
}
from crewai.tools.base_tool import BaseTool as _BaseTool
from crewai.tools.flow_tool import (
FlowTool as _FlowTool,
create_flow_tools as _create_flow_tools,
)
from crewai.tools.structured_tool import CrewStructuredTool as _CrewStructuredTool
_base_namespace["BaseTool"] = _BaseTool
_base_namespace["CrewStructuredTool"] = _CrewStructuredTool
_base_namespace["FlowTool"] = _FlowTool
_base_namespace["create_flow_tools"] = _create_flow_tools # type: ignore[assignment]
try:
from crewai.a2a.config import (

View File

@@ -85,6 +85,7 @@ from crewai.skills.loader import activate_skill, discover_skills
from crewai.skills.models import INSTRUCTIONS, Skill as SkillModel
from crewai.state.checkpoint_config import CheckpointConfig, apply_checkpoint
from crewai.tools.agent_tools.agent_tools import AgentTools
from crewai.tools.flow_tool import create_flow_tools
from crewai.types.callback import SerializableCallable
from crewai.utilities.agent_utils import (
get_tool_names,
@@ -305,6 +306,10 @@ class Agent(BaseAgent):
Can be a single A2AConfig/A2AClientConfig/A2AServerConfig, or a list of any number of A2AConfig/A2AClientConfig with a single A2AServerConfig.
""",
)
flows: list[Any] | None = Field(
default=None,
description="Flow classes that the agent can invoke as tools. Each entry is a Flow subclass (not an instance).",
)
agent_executor: CrewAgentExecutor | AgentExecutor | None = Field(
default=None, description="An instance of the CrewAgentExecutor class."
)
@@ -347,6 +352,7 @@ class Agent(BaseAgent):
)
self.set_skills()
self._set_flow_tools()
if self.reasoning and self.planning_config is None:
warnings.warn(
@@ -394,15 +400,17 @@ class Agent(BaseAgent):
self,
resolved_crew_skills: list[SkillModel] | None = None,
) -> None:
"""Resolve skill paths and activate skills to INSTRUCTIONS level.
"""Resolve skill paths while preserving explicit disclosure levels.
Path entries trigger discovery and activation. Pre-loaded Skill objects
below INSTRUCTIONS level are activated. Crew-level skills are merged in
with event emission so observability is consistent regardless of origin.
Path entries trigger discovery and activation because directory-based
skills opt into eager loading. Pre-loaded Skill objects keep their
current disclosure level so callers can attach METADATA-only skills and
progressively activate them later. Crew-level skills are merged in with
event emission so observability is consistent regardless of origin.
Args:
resolved_crew_skills: Pre-resolved crew skills (already discovered
and activated). When provided, avoids redundant discovery per agent.
resolved_crew_skills: Pre-resolved crew skills. When provided,
avoids redundant discovery per agent.
"""
from crewai.crew import Crew
@@ -443,8 +451,7 @@ class Agent(BaseAgent):
elif isinstance(item, SkillModel):
if item.name not in seen:
seen.add(item.name)
activated = activate_skill(item, source=self)
if activated is item and item.disclosure_level >= INSTRUCTIONS:
if item.disclosure_level >= INSTRUCTIONS:
crewai_event_bus.emit(
self,
event=SkillActivatedEvent(
@@ -454,10 +461,20 @@ class Agent(BaseAgent):
disclosure_level=item.disclosure_level,
),
)
resolved.append(activated)
resolved.append(item)
self.skills = resolved if resolved else None
def _set_flow_tools(self) -> None:
"""Convert Flow classes in ``self.flows`` to tools and merge them."""
if not self.flows:
return
flow_tools = create_flow_tools(self.flows)
if flow_tools:
if self.tools is None:
self.tools = []
self.tools.extend(flow_tools)
def _is_any_available_memory(self) -> bool:
"""Check if unified memory is available (agent or crew)."""
if getattr(self, "memory", None):

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]==1.14.3a3"
"crewai[tools]==1.14.3"
]
[project.scripts]

View File

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
authors = [{ name = "Your Name", email = "you@example.com" }]
requires-python = ">=3.10,<3.14"
dependencies = [
"crewai[tools]==1.14.3a3"
"crewai[tools]==1.14.3"
]
[project.scripts]

View File

@@ -5,7 +5,7 @@ description = "Power up your crews with {{folder_name}}"
readme = "README.md"
requires-python = ">=3.10,<3.14"
dependencies = [
"crewai[tools]==1.14.3a3"
"crewai[tools]==1.14.3"
]
[tool.crewai]

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@@ -21,6 +21,7 @@ from crewai.events.depends import Depends
from crewai.events.event_bus import crewai_event_bus
from crewai.events.handler_graph import CircularDependencyError
if TYPE_CHECKING:
from crewai.events.types.agent_events import (
AgentEvaluationCompletedEvent,
@@ -33,6 +34,20 @@ if TYPE_CHECKING:
LiteAgentExecutionErrorEvent,
LiteAgentExecutionStartedEvent,
)
from crewai.events.types.checkpoint_events import (
CheckpointBaseEvent,
CheckpointCompletedEvent,
CheckpointFailedEvent,
CheckpointForkBaseEvent,
CheckpointForkCompletedEvent,
CheckpointForkStartedEvent,
CheckpointPrunedEvent,
CheckpointRestoreBaseEvent,
CheckpointRestoreCompletedEvent,
CheckpointRestoreFailedEvent,
CheckpointRestoreStartedEvent,
CheckpointStartedEvent,
)
from crewai.events.types.crew_events import (
CrewKickoffCompletedEvent,
CrewKickoffFailedEvent,
@@ -141,6 +156,19 @@ _LAZY_EVENT_MAPPING: dict[str, str] = {
"LiteAgentExecutionCompletedEvent": "crewai.events.types.agent_events",
"LiteAgentExecutionErrorEvent": "crewai.events.types.agent_events",
"LiteAgentExecutionStartedEvent": "crewai.events.types.agent_events",
# checkpoint_events
"CheckpointBaseEvent": "crewai.events.types.checkpoint_events",
"CheckpointCompletedEvent": "crewai.events.types.checkpoint_events",
"CheckpointFailedEvent": "crewai.events.types.checkpoint_events",
"CheckpointForkBaseEvent": "crewai.events.types.checkpoint_events",
"CheckpointForkCompletedEvent": "crewai.events.types.checkpoint_events",
"CheckpointForkStartedEvent": "crewai.events.types.checkpoint_events",
"CheckpointPrunedEvent": "crewai.events.types.checkpoint_events",
"CheckpointRestoreBaseEvent": "crewai.events.types.checkpoint_events",
"CheckpointRestoreCompletedEvent": "crewai.events.types.checkpoint_events",
"CheckpointRestoreFailedEvent": "crewai.events.types.checkpoint_events",
"CheckpointRestoreStartedEvent": "crewai.events.types.checkpoint_events",
"CheckpointStartedEvent": "crewai.events.types.checkpoint_events",
# crew_events
"CrewKickoffCompletedEvent": "crewai.events.types.crew_events",
"CrewKickoffFailedEvent": "crewai.events.types.crew_events",
@@ -265,6 +293,18 @@ __all__ = [
"AgentReasoningFailedEvent",
"AgentReasoningStartedEvent",
"BaseEventListener",
"CheckpointBaseEvent",
"CheckpointCompletedEvent",
"CheckpointFailedEvent",
"CheckpointForkBaseEvent",
"CheckpointForkCompletedEvent",
"CheckpointForkStartedEvent",
"CheckpointPrunedEvent",
"CheckpointRestoreBaseEvent",
"CheckpointRestoreCompletedEvent",
"CheckpointRestoreFailedEvent",
"CheckpointRestoreStartedEvent",
"CheckpointStartedEvent",
"CircularDependencyError",
"CrewKickoffCompletedEvent",
"CrewKickoffFailedEvent",

View File

@@ -64,6 +64,22 @@ P = ParamSpec("P")
R = TypeVar("R")
_replaying: contextvars.ContextVar[bool] = contextvars.ContextVar(
"crewai_event_replaying", default=False
)
def is_replaying() -> bool:
"""Return True if the current context is dispatching a replayed event.
Listeners with side effects (checkpoint writes, external API calls that
should not be repeated) should early-return when this is true. Listeners
whose purpose is reconstructing timeline state (trace batch, console
formatter) should ignore the flag and process replayed events normally.
"""
return _replaying.get()
class CrewAIEventsBus:
"""Singleton event bus for handling events in CrewAI.
@@ -261,6 +277,11 @@ class CrewAIEventsBus:
self._runtime_state = state
self._registered_entity_ids = {id(e) for e in state.root}
@property
def runtime_state(self) -> RuntimeState | None:
"""The RuntimeState currently attached to the bus, if any."""
return self._runtime_state
def register_entity(self, entity: Any) -> None:
"""Add an entity to the RuntimeState, creating it if needed.
@@ -568,6 +589,87 @@ class CrewAIEventsBus:
return None
async def _acall_handlers_replaying(
self,
source: Any,
event: BaseEvent,
handlers: AsyncHandlerSet,
) -> None:
"""Call async handlers with the replaying flag set on the loop thread."""
token = _replaying.set(True)
try:
await self._acall_handlers(source, event, handlers)
finally:
_replaying.reset(token)
async def _emit_with_dependencies_replaying(
self, source: Any, event: BaseEvent
) -> None:
"""Dependency-aware dispatch with the replaying flag set."""
token = _replaying.set(True)
try:
await self._emit_with_dependencies(source, event)
finally:
_replaying.reset(token)
def replay(self, source: Any, event: BaseEvent) -> Future[None] | None:
"""Dispatch a previously-recorded event without mutating its fields.
Unlike :meth:`emit`, this does not run ``_prepare_event`` (so stored
event ids and ``emission_sequence`` are preserved) and does not
re-record the event. Listeners can call :func:`is_replaying` to
opt out of side-effectful processing.
Args:
source: The emitting object.
event: The previously-recorded event to dispatch.
Returns:
Future that completes when handlers finish, or None if no handlers.
"""
event_type = type(event)
with self._rwlock.r_locked():
if self._shutting_down:
return None
has_dependencies = event_type in self._handler_dependencies
sync_handlers = self._sync_handlers.get(event_type, frozenset())
async_handlers = self._async_handlers.get(event_type, frozenset())
if not sync_handlers and not async_handlers:
return None
self._ensure_executor_initialized()
self._has_pending_events = True
token = _replaying.set(True)
try:
if has_dependencies:
return self._track_future(
asyncio.run_coroutine_threadsafe(
self._emit_with_dependencies_replaying(source, event),
self._loop,
)
)
if sync_handlers:
ctx = contextvars.copy_context()
sync_future = self._sync_executor.submit(
ctx.run, self._call_handlers, source, event, sync_handlers
)
self._track_future(sync_future)
if not async_handlers:
return sync_future
return self._track_future(
asyncio.run_coroutine_threadsafe(
self._acall_handlers_replaying(source, event, async_handlers),
self._loop,
)
)
finally:
_replaying.reset(token)
def flush(self, timeout: float | None = 30.0) -> bool:
"""Block until all pending event handlers complete.

View File

@@ -30,6 +30,17 @@ from crewai.events.types.agent_events import (
AgentExecutionStartedEvent,
LiteAgentExecutionCompletedEvent,
)
from crewai.events.types.checkpoint_events import (
CheckpointCompletedEvent,
CheckpointFailedEvent,
CheckpointForkCompletedEvent,
CheckpointForkStartedEvent,
CheckpointPrunedEvent,
CheckpointRestoreCompletedEvent,
CheckpointRestoreFailedEvent,
CheckpointRestoreStartedEvent,
CheckpointStartedEvent,
)
from crewai.events.types.crew_events import (
CrewKickoffCompletedEvent,
CrewKickoffFailedEvent,
@@ -183,4 +194,13 @@ EventTypes = (
| MCPToolExecutionCompletedEvent
| MCPToolExecutionFailedEvent
| MCPConfigFetchFailedEvent
| CheckpointStartedEvent
| CheckpointCompletedEvent
| CheckpointFailedEvent
| CheckpointForkStartedEvent
| CheckpointForkCompletedEvent
| CheckpointRestoreStartedEvent
| CheckpointRestoreCompletedEvent
| CheckpointRestoreFailedEvent
| CheckpointPrunedEvent
)

View File

@@ -0,0 +1,97 @@
"""Event family for automatic state checkpointing and forking."""
from typing import Literal
from crewai.events.base_events import BaseEvent
class CheckpointBaseEvent(BaseEvent):
"""Base event for checkpoint lifecycle operations."""
type: str
location: str
provider: str
trigger: str | None = None
branch: str | None = None
parent_id: str | None = None
class CheckpointStartedEvent(CheckpointBaseEvent):
"""Event emitted immediately before a checkpoint is written."""
type: Literal["checkpoint_started"] = "checkpoint_started"
class CheckpointCompletedEvent(CheckpointBaseEvent):
"""Event emitted when a checkpoint has been written successfully."""
type: Literal["checkpoint_completed"] = "checkpoint_completed"
checkpoint_id: str
duration_ms: float
class CheckpointFailedEvent(CheckpointBaseEvent):
"""Event emitted when a checkpoint write fails."""
type: Literal["checkpoint_failed"] = "checkpoint_failed"
error: str
class CheckpointPrunedEvent(CheckpointBaseEvent):
"""Event emitted after pruning old checkpoints from a branch."""
type: Literal["checkpoint_pruned"] = "checkpoint_pruned"
removed_count: int
max_checkpoints: int
class CheckpointForkBaseEvent(BaseEvent):
"""Base event for fork lifecycle operations on a RuntimeState."""
type: str
branch: str
parent_branch: str | None = None
parent_checkpoint_id: str | None = None
class CheckpointForkStartedEvent(CheckpointForkBaseEvent):
"""Event emitted immediately before a fork relabels the branch."""
type: Literal["checkpoint_fork_started"] = "checkpoint_fork_started"
class CheckpointForkCompletedEvent(CheckpointForkBaseEvent):
"""Event emitted after a fork has established the new branch."""
type: Literal["checkpoint_fork_completed"] = "checkpoint_fork_completed"
class CheckpointRestoreBaseEvent(BaseEvent):
"""Base event for checkpoint restore lifecycle operations."""
type: str
location: str
provider: str | None = None
class CheckpointRestoreStartedEvent(CheckpointRestoreBaseEvent):
"""Event emitted immediately before a checkpoint restore begins."""
type: Literal["checkpoint_restore_started"] = "checkpoint_restore_started"
class CheckpointRestoreCompletedEvent(CheckpointRestoreBaseEvent):
"""Event emitted when a checkpoint has been restored successfully."""
type: Literal["checkpoint_restore_completed"] = "checkpoint_restore_completed"
checkpoint_id: str
branch: str | None = None
parent_id: str | None = None
duration_ms: float
class CheckpointRestoreFailedEvent(CheckpointRestoreBaseEvent):
"""Event emitted when a checkpoint restore fails."""
type: Literal["checkpoint_restore_failed"] = "checkpoint_restore_failed"
error: str

View File

@@ -45,6 +45,7 @@ from pydantic import (
BeforeValidator,
ConfigDict,
Field,
PlainSerializer,
PrivateAttr,
SerializeAsAny,
ValidationError,
@@ -58,6 +59,7 @@ from crewai.events.event_bus import crewai_event_bus
from crewai.events.event_context import (
get_current_parent_id,
reset_last_event_id,
restore_event_scope,
triggered_by_scope,
)
from crewai.events.listeners.tracing.trace_listener import (
@@ -157,6 +159,37 @@ def _resolve_persistence(value: Any) -> Any:
return value
_INITIAL_STATE_CLASS_MARKER = "__crewai_pydantic_class_schema__"
def _serialize_initial_state(value: Any) -> Any:
"""Make ``initial_state`` safe for JSON checkpoint serialization.
``BaseModel`` class refs are emitted as their JSON schema under a sentinel
marker key so deserialization can round-trip them back to a class.
``BaseModel`` instances are dumped to JSON (round-trip as plain dicts,
which ``_create_initial_state`` accepts). Bare ``type`` values that are
not ``BaseModel`` subclasses (e.g. ``dict``) are dropped since they
can't be represented in JSON.
"""
if isinstance(value, type):
if issubclass(value, BaseModel):
return {_INITIAL_STATE_CLASS_MARKER: value.model_json_schema()}
return None
if isinstance(value, BaseModel):
return value.model_dump(mode="json")
return value
def _deserialize_initial_state(value: Any) -> Any:
"""Rehydrate a class ref serialized by :func:`_serialize_initial_state`."""
if isinstance(value, dict) and _INITIAL_STATE_CLASS_MARKER in value:
from crewai.utilities.pydantic_schema_utils import create_model_from_schema
return create_model_from_schema(value[_INITIAL_STATE_CLASS_MARKER])
return value
class FlowState(BaseModel):
"""Base model for all flow states, ensuring each state has a unique ID."""
@@ -908,7 +941,11 @@ class Flow(BaseModel, Generic[T], metaclass=FlowMeta):
entity_type: Literal["flow"] = "flow"
initial_state: Any = Field(default=None)
initial_state: Annotated[ # type: ignore[type-arg]
type[BaseModel] | type[dict] | dict[str, Any] | BaseModel | None,
BeforeValidator(_deserialize_initial_state),
PlainSerializer(_serialize_initial_state, return_type=Any, when_used="json"),
] = Field(default=None)
name: str | None = Field(default=None)
tracing: bool | None = Field(default=None)
stream: bool = Field(default=False)
@@ -980,13 +1017,18 @@ class Flow(BaseModel, Generic[T], metaclass=FlowMeta):
A Flow instance on the new branch. Call kickoff() to run.
"""
flow = cls.from_checkpoint(config)
state = crewai_event_bus._runtime_state
state = crewai_event_bus.runtime_state
if state is None:
raise RuntimeError(
"Cannot fork: no runtime state on the event bus. "
"Ensure from_checkpoint() succeeded before calling fork()."
)
state.fork(branch)
new_id = str(uuid4())
if isinstance(flow._state, dict):
flow._state["id"] = new_id
else:
object.__setattr__(flow._state, "id", new_id)
return flow
checkpoint_completed_methods: set[str] | None = Field(default=None)
@@ -1008,6 +1050,8 @@ class Flow(BaseModel, Generic[T], metaclass=FlowMeta):
}
if self.checkpoint_state is not None:
self._restore_state(self.checkpoint_state)
restore_event_scope(())
reset_last_event_id()
_methods: dict[FlowMethodName, FlowMethod[Any, Any]] = PrivateAttr(
default_factory=dict
@@ -1030,6 +1074,7 @@ class Flow(BaseModel, Generic[T], metaclass=FlowMeta):
_human_feedback_method_outputs: dict[str, Any] = PrivateAttr(default_factory=dict)
_input_history: list[InputHistoryEntry] = PrivateAttr(default_factory=list)
_state: Any = PrivateAttr(default=None)
_execution_id: str = PrivateAttr(default_factory=lambda: str(uuid4()))
def __class_getitem__(cls: type[Flow[T]], item: type[T]) -> type[Flow[T]]: # type: ignore[override]
class _FlowGeneric(cls): # type: ignore[valid-type,misc]
@@ -1820,6 +1865,27 @@ class Flow(BaseModel, Generic[T], metaclass=FlowMeta):
except (AttributeError, TypeError):
return "" # Safely handle any unexpected attribute access issues
@property
def execution_id(self) -> str:
"""Stable identifier for this flow execution.
Separate from ``flow_id`` / ``state.id``, which consumers may
override via ``kickoff(inputs={"id": ...})`` to resume a persisted
flow. ``execution_id`` is never affected by ``inputs`` and stays
stable for the lifetime of a single run, so it is the correct key
for telemetry, tracing, and any external correlation that must
uniquely identify a single execution even when callers pass an
``id`` in ``inputs``.
Defaults to a fresh ``uuid4`` per ``Flow`` instance; assign to
override when an outer system already has an execution identity.
"""
return self._execution_id
@execution_id.setter
def execution_id(self, value: str) -> None:
self._execution_id = value
def _initialize_state(self, inputs: dict[str, Any]) -> None:
"""Initialize or update flow state with new inputs.
@@ -2133,9 +2199,9 @@ class Flow(BaseModel, Generic[T], metaclass=FlowMeta):
flow_id_token = None
request_id_token = None
if current_flow_id.get() is None:
flow_id_token = current_flow_id.set(self.flow_id)
flow_id_token = current_flow_id.set(self.execution_id)
if current_flow_request_id.get() is None:
request_id_token = current_flow_request_id.set(self.flow_id)
request_id_token = current_flow_request_id.set(self.execution_id)
try:
# Reset flow state for fresh execution unless restoring from persistence
@@ -2214,6 +2280,9 @@ class Flow(BaseModel, Generic[T], metaclass=FlowMeta):
if inputs is not None and "id" not in inputs:
self._initialize_state(inputs)
if self._is_execution_resuming:
await self._replay_recorded_events()
try:
# Determine which start methods to execute at kickoff
# Conditional start methods (with __trigger_methods__) are only triggered by their conditions
@@ -2361,6 +2430,44 @@ class Flow(BaseModel, Generic[T], metaclass=FlowMeta):
"""
return await self.kickoff_async(inputs, input_files, from_checkpoint)
async def _replay_recorded_events(self) -> None:
"""Dispatch recorded ``MethodExecution*`` events from the event record."""
state = crewai_event_bus.runtime_state
if state is None:
return
record = state.event_record
if len(record) == 0:
return
replayable = (
MethodExecutionStartedEvent,
MethodExecutionFinishedEvent,
MethodExecutionFailedEvent,
)
flow_name = self.name or self.__class__.__name__
nodes = sorted(
(
n
for n in record.all_nodes()
if isinstance(n.event, replayable)
and n.event.flow_name == flow_name
and n.event.method_name in self._completed_methods
),
key=lambda n: n.event.emission_sequence or 0,
)
for node in nodes:
future = crewai_event_bus.replay(self, node.event)
if future is not None:
try:
await asyncio.wrap_future(future)
except Exception:
logger.warning(
"Replayed event handler failed: %s",
node.event.type,
exc_info=True,
)
async def _execute_start_method(self, start_method_name: FlowMethodName) -> None:
"""Executes a flow's start method and its triggered listeners.

View File

@@ -10,12 +10,22 @@ from __future__ import annotations
import json
import logging
import threading
import time
from typing import Any
from crewai.agents.agent_builder.base_agent import BaseAgent
from crewai.crew import Crew
from crewai.events.base_events import BaseEvent
from crewai.events.event_bus import CrewAIEventsBus, crewai_event_bus
from crewai.events.event_bus import CrewAIEventsBus, crewai_event_bus, is_replaying
from crewai.events.types.checkpoint_events import (
CheckpointBaseEvent,
CheckpointCompletedEvent,
CheckpointFailedEvent,
CheckpointForkBaseEvent,
CheckpointPrunedEvent,
CheckpointRestoreBaseEvent,
CheckpointStartedEvent,
)
from crewai.flow.flow import Flow
from crewai.state.checkpoint_config import CheckpointConfig
from crewai.state.runtime import RuntimeState, _prepare_entities
@@ -53,12 +63,26 @@ def _resolve(value: CheckpointConfig | bool | None) -> CheckpointConfig | None |
if isinstance(value, CheckpointConfig):
_ensure_handlers_registered()
return value
if value is True:
if value:
_ensure_handlers_registered()
return CheckpointConfig()
if value is False:
return _SENTINEL
return None # None = inherit
return None
def _resolve_from_agent(agent: BaseAgent) -> CheckpointConfig | None:
"""Resolve a checkpoint config starting from an agent, walking to its crew."""
result = _resolve(agent.checkpoint)
if isinstance(result, CheckpointConfig):
return result
if result is _SENTINEL:
return None
crew = agent.crew
if isinstance(crew, Crew):
crew_result = _resolve(crew.checkpoint)
return crew_result if isinstance(crew_result, CheckpointConfig) else None
return None
def _find_checkpoint(source: Any) -> CheckpointConfig | None:
@@ -77,28 +101,11 @@ def _find_checkpoint(source: Any) -> CheckpointConfig | None:
result = _resolve(source.checkpoint)
return result if isinstance(result, CheckpointConfig) else None
if isinstance(source, BaseAgent):
result = _resolve(source.checkpoint)
if isinstance(result, CheckpointConfig):
return result
if result is _SENTINEL:
return None
crew = source.crew
if isinstance(crew, Crew):
result = _resolve(crew.checkpoint)
return result if isinstance(result, CheckpointConfig) else None
return None
return _resolve_from_agent(source)
if isinstance(source, Task):
agent = source.agent
if isinstance(agent, BaseAgent):
result = _resolve(agent.checkpoint)
if isinstance(result, CheckpointConfig):
return result
if result is _SENTINEL:
return None
crew = agent.crew
if isinstance(crew, Crew):
result = _resolve(crew.checkpoint)
return result if isinstance(result, CheckpointConfig) else None
return _resolve_from_agent(agent)
return None
return None
@@ -107,27 +114,106 @@ def _do_checkpoint(
state: RuntimeState, cfg: CheckpointConfig, event: BaseEvent | None = None
) -> None:
"""Write a checkpoint and prune old ones if configured."""
_prepare_entities(state.root)
payload = state.model_dump(mode="json")
if event is not None:
payload["trigger"] = event.type
data = json.dumps(payload)
location = cfg.provider.checkpoint(
data,
cfg.location,
parent_id=state._parent_id,
branch=state._branch,
)
state._chain_lineage(cfg.provider, location)
provider_name: str = type(cfg.provider).__name__
trigger: str | None = event.type if event is not None else None
context: dict[str, Any] = {
"task_id": event.task_id if event is not None else None,
"task_name": event.task_name if event is not None else None,
"agent_id": event.agent_id if event is not None else None,
"agent_role": event.agent_role if event is not None else None,
}
checkpoint_id: str = cfg.provider.extract_id(location)
parent_id_snapshot: str | None = state._parent_id
branch_snapshot: str = state._branch
crewai_event_bus.emit(
cfg,
CheckpointStartedEvent(
location=cfg.location,
provider=provider_name,
trigger=trigger,
branch=branch_snapshot,
parent_id=parent_id_snapshot,
**context,
),
)
start: float = time.perf_counter()
try:
_prepare_entities(state.root)
payload = state.model_dump(mode="json")
if event is not None:
payload["trigger"] = event.type
data = json.dumps(payload)
location = cfg.provider.checkpoint(
data,
cfg.location,
parent_id=parent_id_snapshot,
branch=branch_snapshot,
)
state._chain_lineage(cfg.provider, location)
checkpoint_id: str = cfg.provider.extract_id(location)
except Exception as exc:
crewai_event_bus.emit(
cfg,
CheckpointFailedEvent(
location=cfg.location,
provider=provider_name,
trigger=trigger,
branch=branch_snapshot,
parent_id=parent_id_snapshot,
error=str(exc),
**context,
),
)
raise
duration_ms: float = (time.perf_counter() - start) * 1000.0
msg: str = (
f"Checkpoint saved. Resume with: crewai checkpoint resume {checkpoint_id}"
)
logger.info(msg)
crewai_event_bus.emit(
cfg,
CheckpointCompletedEvent(
location=location,
provider=provider_name,
trigger=trigger,
branch=branch_snapshot,
parent_id=parent_id_snapshot,
checkpoint_id=checkpoint_id,
duration_ms=duration_ms,
**context,
),
)
if cfg.max_checkpoints is not None:
cfg.provider.prune(cfg.location, cfg.max_checkpoints, branch=state._branch)
try:
removed_count: int = cfg.provider.prune(
cfg.location, cfg.max_checkpoints, branch=branch_snapshot
)
except Exception:
logger.warning(
"Checkpoint prune failed for %s (branch=%s)",
cfg.location,
branch_snapshot,
exc_info=True,
)
return
crewai_event_bus.emit(
cfg,
CheckpointPrunedEvent(
location=cfg.location,
provider=provider_name,
trigger=trigger,
branch=branch_snapshot,
parent_id=parent_id_snapshot,
removed_count=removed_count,
max_checkpoints=cfg.max_checkpoints,
**context,
),
)
def _should_checkpoint(source: Any, event: BaseEvent) -> CheckpointConfig | None:
@@ -142,6 +228,13 @@ def _should_checkpoint(source: Any, event: BaseEvent) -> CheckpointConfig | None
def _on_any_event(source: Any, event: BaseEvent, state: Any) -> None:
"""Sync handler registered on every event class."""
if is_replaying():
return
if isinstance(
event,
(CheckpointBaseEvent, CheckpointForkBaseEvent, CheckpointRestoreBaseEvent),
):
return
cfg = _should_checkpoint(source, event)
if cfg is None:
return
@@ -161,7 +254,8 @@ def _register_all_handlers(event_bus: CrewAIEventsBus) -> None:
seen: set[type] = set()
def _collect(cls: type[BaseEvent]) -> None:
for sub in cls.__subclasses__():
subclasses: list[type[BaseEvent]] = cls.__subclasses__()
for sub in subclasses:
if sub not in seen:
seen.add(sub)
type_field = sub.model_fields.get("type")

View File

@@ -39,7 +39,8 @@ def _build_event_type_map() -> None:
"""Populate _event_type_map from all BaseEvent subclasses."""
def _collect(cls: type[BaseEvent]) -> None:
for sub in cls.__subclasses__():
subclasses: list[type[BaseEvent]] = cls.__subclasses__()
for sub in subclasses:
type_field = sub.model_fields.get("type")
if type_field and type_field.default:
_event_type_map[type_field.default] = sub
@@ -196,6 +197,21 @@ class EventRecord(BaseModel):
node for node in self.nodes.values() if not node.neighbors("parent")
]
def all_nodes(self) -> list[EventNode]:
"""Return a snapshot of every node under the read lock.
Returns:
A list copy of the current nodes, safe to iterate without holding
the lock.
"""
with self._lock.r_locked():
return list(self.nodes.values())
def clear(self) -> None:
"""Remove all nodes from the record under the write lock."""
with self._lock.w_locked():
self.nodes.clear()
def __len__(self) -> int:
with self._lock.r_locked():
return len(self.nodes)

View File

@@ -61,13 +61,16 @@ class BaseProvider(BaseModel, ABC):
...
@abstractmethod
def prune(self, location: str, max_keep: int, *, branch: str = "main") -> None:
def prune(self, location: str, max_keep: int, *, branch: str = "main") -> int:
"""Remove old checkpoints, keeping at most *max_keep* per branch.
Args:
location: The storage destination passed to ``checkpoint``.
max_keep: Maximum number of checkpoints to retain.
branch: Only prune checkpoints on this branch.
Returns:
The number of checkpoints removed.
"""
...

View File

@@ -95,17 +95,20 @@ class JsonProvider(BaseProvider):
await f.write(data)
return str(file_path)
def prune(self, location: str, max_keep: int, *, branch: str = "main") -> None:
def prune(self, location: str, max_keep: int, *, branch: str = "main") -> int:
"""Remove oldest checkpoint files beyond *max_keep* on a branch."""
_safe_branch(location, branch)
branch_dir = os.path.join(location, branch)
pattern = os.path.join(branch_dir, "*.json")
files = sorted(glob.glob(pattern), key=os.path.getmtime)
removed = 0
for path in files if max_keep == 0 else files[:-max_keep]:
try:
os.remove(path)
removed += 1
except OSError: # noqa: PERF203
logger.debug("Failed to remove %s", path, exc_info=True)
return removed
def extract_id(self, location: str) -> str:
"""Extract the checkpoint ID from a file path.

View File

@@ -111,11 +111,13 @@ class SqliteProvider(BaseProvider):
await db.commit()
return f"{location}#{checkpoint_id}"
def prune(self, location: str, max_keep: int, *, branch: str = "main") -> None:
def prune(self, location: str, max_keep: int, *, branch: str = "main") -> int:
"""Remove oldest checkpoint rows beyond *max_keep* on a branch."""
with sqlite3.connect(location) as conn:
conn.execute(_PRUNE, (branch, branch, max_keep))
cursor = conn.execute(_PRUNE, (branch, branch, max_keep))
removed: int = cursor.rowcount
conn.commit()
return max(removed, 0)
def extract_id(self, location: str) -> str:
"""Extract the checkpoint ID from a ``db_path#id`` string."""

View File

@@ -10,6 +10,7 @@ via ``RuntimeState.model_rebuild()``.
from __future__ import annotations
import logging
import time
from typing import TYPE_CHECKING, Any
import uuid
@@ -23,6 +24,17 @@ from pydantic import (
)
from crewai.context import capture_execution_context
from crewai.events.event_bus import crewai_event_bus
from crewai.events.types.checkpoint_events import (
CheckpointCompletedEvent,
CheckpointFailedEvent,
CheckpointForkCompletedEvent,
CheckpointForkStartedEvent,
CheckpointRestoreCompletedEvent,
CheckpointRestoreFailedEvent,
CheckpointRestoreStartedEvent,
CheckpointStartedEvent,
)
from crewai.state.checkpoint_config import CheckpointConfig
from crewai.state.event_record import EventRecord
from crewai.state.provider.core import BaseProvider
@@ -89,7 +101,7 @@ def _migrate(data: dict[str, Any]) -> dict[str, Any]:
"""
raw = data.get("crewai_version")
current = Version(get_crewai_version())
stored = Version(raw) if raw else Version("0.0.0")
stored = Version(raw) if isinstance(raw, str) and raw else Version("0.0.0")
if raw is None:
logger.warning("Checkpoint has no crewai_version — treating as 0.0.0")
@@ -159,6 +171,63 @@ class RuntimeState(RootModel): # type: ignore[type-arg]
self._checkpoint_id = provider.extract_id(location)
self._parent_id = self._checkpoint_id
def _begin_checkpoint(self, location: str) -> tuple[str, str | None, str, float]:
"""Emit the start event and return the invariant context for a checkpoint."""
provider_name: str = type(self._provider).__name__
parent_id_snapshot: str | None = self._parent_id
branch_snapshot: str = self._branch
crewai_event_bus.emit(
self,
CheckpointStartedEvent(
location=location,
provider=provider_name,
branch=branch_snapshot,
parent_id=parent_id_snapshot,
),
)
return provider_name, parent_id_snapshot, branch_snapshot, time.perf_counter()
def _emit_checkpoint_failed(
self,
location: str,
provider_name: str,
branch_snapshot: str,
parent_id_snapshot: str | None,
exc: Exception,
) -> None:
"""Emit the failure event for a checkpoint write."""
crewai_event_bus.emit(
self,
CheckpointFailedEvent(
location=location,
provider=provider_name,
branch=branch_snapshot,
parent_id=parent_id_snapshot,
error=str(exc),
),
)
def _emit_checkpoint_completed(
self,
result: str,
provider_name: str,
branch_snapshot: str,
parent_id_snapshot: str | None,
start: float,
) -> None:
"""Emit the completion event for a successful checkpoint write."""
crewai_event_bus.emit(
self,
CheckpointCompletedEvent(
location=result,
provider=provider_name,
branch=branch_snapshot,
parent_id=parent_id_snapshot,
checkpoint_id=self._provider.extract_id(result),
duration_ms=(time.perf_counter() - start) * 1000.0,
),
)
def checkpoint(self, location: str) -> str:
"""Write a checkpoint.
@@ -169,14 +238,27 @@ class RuntimeState(RootModel): # type: ignore[type-arg]
Returns:
A location identifier for the saved checkpoint.
"""
_prepare_entities(self.root)
result = self._provider.checkpoint(
self.model_dump_json(),
location,
parent_id=self._parent_id,
branch=self._branch,
provider_name, parent_id_snapshot, branch_snapshot, start = (
self._begin_checkpoint(location)
)
try:
_prepare_entities(self.root)
result = self._provider.checkpoint(
self.model_dump_json(),
location,
parent_id=parent_id_snapshot,
branch=branch_snapshot,
)
self._chain_lineage(self._provider, result)
except Exception as exc:
self._emit_checkpoint_failed(
location, provider_name, branch_snapshot, parent_id_snapshot, exc
)
raise
self._emit_checkpoint_completed(
result, provider_name, branch_snapshot, parent_id_snapshot, start
)
self._chain_lineage(self._provider, result)
return result
async def acheckpoint(self, location: str) -> str:
@@ -189,14 +271,27 @@ class RuntimeState(RootModel): # type: ignore[type-arg]
Returns:
A location identifier for the saved checkpoint.
"""
_prepare_entities(self.root)
result = await self._provider.acheckpoint(
self.model_dump_json(),
location,
parent_id=self._parent_id,
branch=self._branch,
provider_name, parent_id_snapshot, branch_snapshot, start = (
self._begin_checkpoint(location)
)
try:
_prepare_entities(self.root)
result = await self._provider.acheckpoint(
self.model_dump_json(),
location,
parent_id=parent_id_snapshot,
branch=branch_snapshot,
)
self._chain_lineage(self._provider, result)
except Exception as exc:
self._emit_checkpoint_failed(
location, provider_name, branch_snapshot, parent_id_snapshot, exc
)
raise
self._emit_checkpoint_completed(
result, provider_name, branch_snapshot, parent_id_snapshot, start
)
self._chain_lineage(self._provider, result)
return result
def fork(self, branch: str | None = None) -> None:
@@ -211,11 +306,32 @@ class RuntimeState(RootModel): # type: ignore[type-arg]
times without collisions.
"""
if branch:
self._branch = branch
new_branch = branch
elif self._checkpoint_id:
self._branch = f"fork/{self._checkpoint_id}_{uuid.uuid4().hex[:6]}"
new_branch = f"fork/{self._checkpoint_id}_{uuid.uuid4().hex[:6]}"
else:
self._branch = f"fork/{uuid.uuid4().hex[:8]}"
new_branch = f"fork/{uuid.uuid4().hex[:8]}"
parent_branch: str | None = self._branch
parent_checkpoint_id: str | None = self._checkpoint_id
crewai_event_bus.emit(
self,
CheckpointForkStartedEvent(
branch=new_branch,
parent_branch=parent_branch,
parent_checkpoint_id=parent_checkpoint_id,
),
)
self._branch = new_branch
crewai_event_bus.emit(
self,
CheckpointForkCompletedEvent(
branch=new_branch,
parent_branch=parent_branch,
parent_checkpoint_id=parent_checkpoint_id,
),
)
@classmethod
def from_checkpoint(cls, config: CheckpointConfig, **kwargs: Any) -> RuntimeState:
@@ -233,13 +349,41 @@ class RuntimeState(RootModel): # type: ignore[type-arg]
if config.restore_from is None:
raise ValueError("CheckpointConfig.restore_from must be set")
location = str(config.restore_from)
provider = detect_provider(location)
raw = provider.from_checkpoint(location)
state = cls.model_validate_json(raw, **kwargs)
state._provider = provider
checkpoint_id = provider.extract_id(location)
state._checkpoint_id = checkpoint_id
state._parent_id = checkpoint_id
crewai_event_bus.emit(config, CheckpointRestoreStartedEvent(location=location))
start: float = time.perf_counter()
provider_name: str | None = None
try:
provider = detect_provider(location)
provider_name = type(provider).__name__
raw = provider.from_checkpoint(location)
state = cls.model_validate_json(raw, **kwargs)
state._provider = provider
checkpoint_id = provider.extract_id(location)
state._checkpoint_id = checkpoint_id
state._parent_id = checkpoint_id
except Exception as exc:
crewai_event_bus.emit(
config,
CheckpointRestoreFailedEvent(
location=location,
provider=provider_name,
error=str(exc),
),
)
raise
crewai_event_bus.emit(
config,
CheckpointRestoreCompletedEvent(
location=location,
provider=provider_name,
checkpoint_id=checkpoint_id,
branch=state._branch,
parent_id=state._parent_id,
duration_ms=(time.perf_counter() - start) * 1000.0,
),
)
return state
@classmethod
@@ -260,13 +404,41 @@ class RuntimeState(RootModel): # type: ignore[type-arg]
if config.restore_from is None:
raise ValueError("CheckpointConfig.restore_from must be set")
location = str(config.restore_from)
provider = detect_provider(location)
raw = await provider.afrom_checkpoint(location)
state = cls.model_validate_json(raw, **kwargs)
state._provider = provider
checkpoint_id = provider.extract_id(location)
state._checkpoint_id = checkpoint_id
state._parent_id = checkpoint_id
crewai_event_bus.emit(config, CheckpointRestoreStartedEvent(location=location))
start: float = time.perf_counter()
provider_name: str | None = None
try:
provider = detect_provider(location)
provider_name = type(provider).__name__
raw = await provider.afrom_checkpoint(location)
state = cls.model_validate_json(raw, **kwargs)
state._provider = provider
checkpoint_id = provider.extract_id(location)
state._checkpoint_id = checkpoint_id
state._parent_id = checkpoint_id
except Exception as exc:
crewai_event_bus.emit(
config,
CheckpointRestoreFailedEvent(
location=location,
provider=provider_name,
error=str(exc),
),
)
raise
crewai_event_bus.emit(
config,
CheckpointRestoreCompletedEvent(
location=location,
provider=provider_name,
checkpoint_id=checkpoint_id,
branch=state._branch,
parent_id=state._parent_id,
duration_ms=(time.perf_counter() - start) * 1000.0,
),
)
return state

View File

@@ -0,0 +1,82 @@
"""Wrap Flow classes as callable tools so agents can invoke them."""
from __future__ import annotations
import json
from typing import Any
from pydantic import BaseModel, Field
from crewai.tools.base_tool import BaseTool
from crewai.utilities.string_utils import sanitize_tool_name
class FlowToolInputSchema(BaseModel):
"""Default input schema for a FlowTool."""
inputs: str = Field(
default="{}",
description=(
"JSON string of key-value pairs to pass as inputs to the flow. "
"Use '{}' if the flow requires no inputs."
),
)
class FlowTool(BaseTool):
"""Wraps a Flow class as a BaseTool so an agent can invoke it.
The tool instantiates the Flow, calls ``kickoff(inputs=...)`` and returns
the result as a string.
"""
name: str = ""
description: str = ""
flow_class: Any = Field(
default=None,
description="The Flow class (not instance) to wrap.",
exclude=True,
)
args_schema: Any = FlowToolInputSchema
def _run(self, inputs: str = "{}") -> str:
"""Instantiate the Flow, run kickoff, and return the result."""
try:
parsed_inputs = json.loads(inputs) if isinstance(inputs, str) else inputs
except (json.JSONDecodeError, TypeError):
parsed_inputs = {}
if not isinstance(parsed_inputs, dict):
parsed_inputs = {}
flow_instance = self.flow_class()
result = flow_instance.kickoff(inputs=parsed_inputs if parsed_inputs else None)
return str(result)
def create_flow_tools(flows: list[type] | None) -> list[BaseTool]:
"""Convert a list of Flow classes into BaseTool wrappers.
Args:
flows: Flow classes (not instances) to wrap as tools.
Returns:
A list of FlowTool instances ready for agent use.
"""
if not flows:
return []
tools: list[BaseTool] = []
for flow_cls in flows:
name = sanitize_tool_name(flow_cls.__name__)
docstring = (flow_cls.__doc__ or "").strip()
description = docstring if docstring else f"Run the {flow_cls.__name__} flow."
tools.append(
FlowTool(
name=name,
description=description,
flow_class=flow_cls,
)
)
return tools

View File

@@ -0,0 +1,165 @@
"""Tests for event bus replay dispatch and is_replaying flag."""
from __future__ import annotations
from typing import Any
from unittest.mock import patch
from crewai.events.event_bus import _replaying, crewai_event_bus, is_replaying
from crewai.events.types.flow_events import (
MethodExecutionFinishedEvent,
MethodExecutionStartedEvent,
)
def _make_started(method: str, event_id: str, sequence: int) -> MethodExecutionStartedEvent:
"""Build a MethodExecutionStartedEvent with explicit ids/sequence."""
ev = MethodExecutionStartedEvent(
method_name=method,
flow_name="F",
params={},
state={},
)
ev.event_id = event_id
ev.emission_sequence = sequence
return ev
class TestReplayPreservesFields:
"""replay() must not overwrite event_id, parent_event_id, or emission_sequence."""
def test_preserves_ids_and_sequence(self) -> None:
captured: list[MethodExecutionStartedEvent] = []
with crewai_event_bus.scoped_handlers():
@crewai_event_bus.on(MethodExecutionStartedEvent)
def _capture(_: Any, event: MethodExecutionStartedEvent) -> None:
captured.append(event)
ev = _make_started("outline", "orig-id-1", 42)
ev.parent_event_id = "parent-abc"
future = crewai_event_bus.replay(object(), ev)
if future is not None:
future.result(timeout=5.0)
assert len(captured) == 1
assert captured[0].event_id == "orig-id-1"
assert captured[0].parent_event_id == "parent-abc"
assert captured[0].emission_sequence == 42
class TestIsReplayingFlag:
"""is_replaying() must be True inside handlers dispatched via replay()."""
def test_flag_true_during_replay(self) -> None:
seen: list[bool] = []
with crewai_event_bus.scoped_handlers():
@crewai_event_bus.on(MethodExecutionStartedEvent)
def _capture(_: Any, __: MethodExecutionStartedEvent) -> None:
seen.append(is_replaying())
ev = _make_started("m", "id-1", 1)
future = crewai_event_bus.replay(object(), ev)
if future is not None:
future.result(timeout=5.0)
assert seen == [True]
assert is_replaying() is False
def test_flag_false_during_emit(self) -> None:
seen: list[bool] = []
with crewai_event_bus.scoped_handlers():
@crewai_event_bus.on(MethodExecutionStartedEvent)
def _capture(_: Any, __: MethodExecutionStartedEvent) -> None:
seen.append(is_replaying())
ev = _make_started("m", "id-1", 1)
future = crewai_event_bus.emit(object(), ev)
if future is not None:
future.result(timeout=5.0)
assert seen == [False]
class TestCheckpointListenerOptsOut:
"""CheckpointListener must early-return during replay."""
def test_checkpoint_not_written_on_replay(self) -> None:
from crewai.state.checkpoint_config import CheckpointConfig
from crewai.state.checkpoint_listener import _on_any_event
class FlowLike:
entity_type = "flow"
checkpoint = CheckpointConfig(trigger_all=True)
ev = _make_started("m", "id-1", 1)
with patch("crewai.state.checkpoint_listener._do_checkpoint") as do_cp:
token = _replaying.set(True)
try:
_on_any_event(FlowLike(), ev, state=None)
finally:
_replaying.reset(token)
assert do_cp.call_count == 0
class TestFlowResumeReplaysEvents:
"""End-to-end: a resumed flow emits MethodExecution* events for completed methods."""
def test_resume_dispatches_completed_method_events(self, tmp_path) -> None:
from crewai.flow.flow import Flow, listen, start
from crewai.flow.persistence.sqlite import SQLiteFlowPersistence
db_path = tmp_path / "flows.db"
persistence = SQLiteFlowPersistence(str(db_path))
class ThreeStepFlow(Flow[dict]):
@start()
def step_a(self) -> str:
return "a"
@listen(step_a)
def step_b(self) -> str:
return "b"
@listen(step_b)
def step_c(self) -> str:
return "c"
if crewai_event_bus.runtime_state is not None:
crewai_event_bus.runtime_state.event_record.clear()
flow1 = ThreeStepFlow(persistence=persistence)
flow1.kickoff()
flow_id = flow1.state["id"]
captured_started: list[str] = []
captured_finished: list[str] = []
flow2 = ThreeStepFlow(persistence=persistence)
flow2._completed_methods = {"step_a", "step_b"}
with crewai_event_bus.scoped_handlers():
@crewai_event_bus.on(MethodExecutionStartedEvent)
def _cs(_: Any, event: MethodExecutionStartedEvent) -> None:
captured_started.append(event.method_name)
@crewai_event_bus.on(MethodExecutionFinishedEvent)
def _cf(_: Any, event: MethodExecutionFinishedEvent) -> None:
captured_finished.append(event.method_name)
flow2.kickoff(inputs={"id": flow_id})
assert captured_started.count("step_a") == 1
assert captured_started.count("step_b") == 1
assert captured_started.count("step_c") == 1
assert captured_finished.count("step_a") == 1
assert captured_finished.count("step_b") == 1
assert captured_finished.count("step_c") == 1

View File

@@ -4,6 +4,8 @@ from pathlib import Path
import pytest
from crewai import Agent
from crewai.agent.utils import append_skill_context
from crewai.skills.loader import activate_skill, discover_skills, format_skill_context
from crewai.skills.models import INSTRUCTIONS, METADATA
@@ -76,3 +78,23 @@ class TestSkillDiscoveryAndActivation:
all_skills.extend(discover_skills(search_path))
names = {s.name for s in all_skills}
assert names == {"skill-a", "skill-b"}
def test_agent_preserves_metadata_for_discovered_skills(self, tmp_path: Path) -> None:
_create_skill_dir(tmp_path, "travel", body="Use this skill for travel planning.")
discovered = discover_skills(tmp_path)
agent = Agent(
role="Travel Advisor",
goal="Provide personalized travel suggestions.",
backstory="An experienced travel consultant.",
skills=discovered,
)
assert agent.skills is not None
assert agent.skills[0].disclosure_level == METADATA
assert agent.skills[0].instructions is None
prompt = append_skill_context(agent, "Plan a 10-day Japan itinerary.")
assert "## Skill: travel" in prompt
assert "Skill travel" in prompt
assert "Use this skill for travel planning." not in prompt

View File

@@ -11,11 +11,12 @@ from typing import Any
from unittest.mock import MagicMock, patch
import pytest
from pydantic import BaseModel
from crewai.agent.core import Agent
from crewai.agents.agent_builder.base_agent import BaseAgent
from crewai.crew import Crew
from crewai.flow.flow import Flow, start
from crewai.flow.flow import _INITIAL_STATE_CLASS_MARKER, Flow, start
from crewai.state.checkpoint_config import CheckpointConfig
from crewai.state.checkpoint_listener import (
_find_checkpoint,
@@ -310,6 +311,65 @@ class TestRuntimeStateLineage:
assert state._branch != first
class TestFlowInitialStateSerialization:
"""Regression tests for checkpoint serialization of ``Flow.initial_state``."""
def test_class_ref_serializes_as_schema(self) -> None:
class MyState(BaseModel):
id: str = "x"
foo: str = "bar"
flow = Flow(initial_state=MyState)
state = RuntimeState(root=[flow])
dumped = json.loads(state.model_dump_json())
entity = dumped["entities"][0]
wrapped = entity["initial_state"]
assert isinstance(wrapped, dict)
assert _INITIAL_STATE_CLASS_MARKER in wrapped
assert wrapped[_INITIAL_STATE_CLASS_MARKER].get("title") == "MyState"
def test_class_ref_round_trips_to_basemodel_subclass(self) -> None:
class MyState(BaseModel):
id: str = "x"
foo: str = "bar"
flow = Flow(initial_state=MyState)
raw = RuntimeState(root=[flow]).model_dump_json()
restored = RuntimeState.model_validate_json(
raw, context={"from_checkpoint": True}
)
rehydrated = restored.root[0].initial_state
assert isinstance(rehydrated, type)
assert issubclass(rehydrated, BaseModel)
assert set(rehydrated.model_fields.keys()) == {"id", "foo"}
def test_instance_serializes_as_values(self) -> None:
class MyState(BaseModel):
id: str = "x"
foo: str = "bar"
flow = Flow(initial_state=MyState(foo="baz"))
state = RuntimeState(root=[flow])
dumped = json.loads(state.model_dump_json())
entity = dumped["entities"][0]
assert entity["initial_state"] == {"id": "x", "foo": "baz"}
def test_dict_passthrough(self) -> None:
flow = Flow(initial_state={"id": "x", "foo": "bar"})
state = RuntimeState(root=[flow])
dumped = json.loads(state.model_dump_json())
entity = dumped["entities"][0]
assert entity["initial_state"] == {"id": "x", "foo": "bar"}
def test_dict_round_trips_as_dict(self) -> None:
flow = Flow(initial_state={"id": "x", "foo": "bar"})
raw = RuntimeState(root=[flow]).model_dump_json()
restored = RuntimeState.model_validate_json(
raw, context={"from_checkpoint": True}
)
assert restored.root[0].initial_state == {"id": "x", "foo": "bar"}
# ---------- JsonProvider forking ----------

View File

@@ -4519,8 +4519,8 @@ def test_sets_flow_context_when_using_crewbase_pattern_inside_flow():
flow.kickoff()
assert captured_crew is not None
assert captured_crew._flow_id == flow.flow_id # type: ignore[attr-defined]
assert captured_crew._request_id == flow.flow_id # type: ignore[attr-defined]
assert captured_crew._flow_id == flow.execution_id # type: ignore[attr-defined]
assert captured_crew._request_id == flow.execution_id # type: ignore[attr-defined]
def test_sets_flow_context_when_outside_flow(researcher, writer):
@@ -4554,8 +4554,8 @@ def test_sets_flow_context_when_inside_flow(researcher, writer):
flow = MyFlow()
result = flow.kickoff()
assert result._flow_id == flow.flow_id # type: ignore[attr-defined]
assert result._request_id == flow.flow_id # type: ignore[attr-defined]
assert result._flow_id == flow.execution_id # type: ignore[attr-defined]
assert result._request_id == flow.execution_id # type: ignore[attr-defined]
def test_reset_knowledge_with_no_crew_knowledge(researcher, writer):

View File

@@ -0,0 +1,185 @@
"""Tests for Flow-as-tool functionality."""
from __future__ import annotations
from unittest.mock import MagicMock
from crewai.flow.flow import Flow, start
from crewai.tools.flow_tool import FlowTool, create_flow_tools
# ---------------------------------------------------------------------------
# Test Flow classes
# ---------------------------------------------------------------------------
class SimpleFlow(Flow):
"""A simple flow that greets the user."""
@start()
def greet(self) -> str:
return "Hello from SimpleFlow!"
class MathFlow(Flow):
"""Performs basic math operations."""
@start()
def compute(self) -> str:
return "42"
class NoDocFlow(Flow):
@start()
def run_it(self) -> str:
return "no doc"
# ---------------------------------------------------------------------------
# FlowTool unit tests
# ---------------------------------------------------------------------------
class TestFlowTool:
def test_wrap_simple_flow(self) -> None:
tool = FlowTool(
name="simple_flow",
description="A simple flow that greets the user.",
flow_class=SimpleFlow,
)
assert tool.name == "simple_flow"
assert "greets the user" in tool.description
def test_run_invokes_kickoff(self) -> None:
mock_flow = MagicMock()
mock_flow.return_value = mock_flow # __init__ returns self
mock_flow.kickoff.return_value = "mocked result"
tool = FlowTool(
name="test_flow",
description="test",
flow_class=mock_flow,
)
result = tool._run(inputs="{}")
assert result == "mocked result"
mock_flow.kickoff.assert_called_once()
def test_run_with_json_inputs(self) -> None:
mock_flow = MagicMock()
mock_flow.return_value = mock_flow
mock_flow.kickoff.return_value = "result with inputs"
tool = FlowTool(
name="test_flow",
description="test",
flow_class=mock_flow,
)
result = tool._run(inputs='{"key": "value"}')
assert result == "result with inputs"
mock_flow.kickoff.assert_called_once_with(inputs={"key": "value"})
def test_run_with_invalid_json_defaults_to_empty(self) -> None:
mock_flow = MagicMock()
mock_flow.return_value = mock_flow
mock_flow.kickoff.return_value = "ok"
tool = FlowTool(
name="test_flow",
description="test",
flow_class=mock_flow,
)
result = tool._run(inputs="not valid json")
assert result == "ok"
mock_flow.kickoff.assert_called_once_with(inputs=None)
def test_run_returns_string(self) -> None:
mock_flow = MagicMock()
mock_flow.return_value = mock_flow
mock_flow.kickoff.return_value = 42
tool = FlowTool(
name="test_flow",
description="test",
flow_class=mock_flow,
)
result = tool._run()
assert result == "42"
assert isinstance(result, str)
# ---------------------------------------------------------------------------
# create_flow_tools tests
# ---------------------------------------------------------------------------
class TestCreateFlowTools:
def test_creates_tools_from_flow_classes(self) -> None:
tools = create_flow_tools([SimpleFlow, MathFlow])
assert len(tools) == 2
names = {t.name for t in tools}
assert "simple_flow" in names
assert "math_flow" in names
def test_description_from_docstring(self) -> None:
tools = create_flow_tools([SimpleFlow])
assert len(tools) == 1
assert "greets the user" in tools[0].description
def test_description_fallback_when_no_docstring(self) -> None:
tools = create_flow_tools([NoDocFlow])
assert len(tools) == 1
assert "NoDocFlow" in tools[0].description
def test_empty_list_returns_empty(self) -> None:
assert create_flow_tools([]) == []
def test_none_returns_empty(self) -> None:
assert create_flow_tools(None) == []
def test_tools_are_base_tool_instances(self) -> None:
from crewai.tools.base_tool import BaseTool
tools = create_flow_tools([SimpleFlow])
for tool in tools:
assert isinstance(tool, BaseTool)
# ---------------------------------------------------------------------------
# Agent integration tests
# ---------------------------------------------------------------------------
class TestAgentFlowIntegration:
def test_agent_with_flows_has_flow_tools(self) -> None:
from crewai.agent.core import Agent
agent = Agent(
role="Test Agent",
goal="Test flows",
backstory="I test things",
flows=[SimpleFlow, MathFlow],
)
tool_names = {t.name for t in (agent.tools or [])}
assert "simple_flow" in tool_names
assert "math_flow" in tool_names
def test_agent_without_flows_no_extra_tools(self) -> None:
from crewai.agent.core import Agent
agent = Agent(
role="Test Agent",
goal="Test",
backstory="I test things",
)
# Should not have any flow tools
flow_tool_names = {
t.name for t in (agent.tools or []) if isinstance(t, FlowTool)
}
assert len(flow_tool_names) == 0
def test_flow_tool_executes_real_flow(self) -> None:
"""Test that a FlowTool actually runs the Flow's kickoff."""
tools = create_flow_tools([SimpleFlow])
tool = tools[0]
result = tool.run(inputs="{}")
assert "Hello from SimpleFlow" in result

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@@ -0,0 +1,127 @@
"""Regression tests for ``Flow.execution_id``.
``execution_id`` is the stable tracking identifier for a single flow run.
It must stay independent of ``state.id`` so that consumers passing an
``id`` in ``inputs`` (used for persistence restore) cannot destabilize
the identity used by telemetry, tracing, and external correlation.
"""
from __future__ import annotations
from typing import Any
import pytest
from crewai.flow.flow import Flow, FlowState, start
from crewai.flow.flow_context import current_flow_id, current_flow_request_id
class _CaptureState(FlowState):
captured_flow_id: str = ""
captured_state_id: str = ""
captured_current_flow_id: str = ""
captured_execution_id: str = ""
class _IdentityCaptureFlow(Flow[_CaptureState]):
initial_state = _CaptureState
@start()
def capture(self) -> None:
self.state.captured_flow_id = self.flow_id
self.state.captured_state_id = self.state.id
self.state.captured_current_flow_id = current_flow_id.get() or ""
self.state.captured_execution_id = self.execution_id
def test_execution_id_defaults_to_fresh_uuid_per_instance() -> None:
a = _IdentityCaptureFlow()
b = _IdentityCaptureFlow()
assert a.execution_id
assert b.execution_id
assert a.execution_id != b.execution_id
def test_execution_id_survives_consumer_id_in_inputs() -> None:
flow = _IdentityCaptureFlow()
original_execution_id = flow.execution_id
flow.kickoff(inputs={"id": "consumer-supplied-id"})
assert flow.state.id == "consumer-supplied-id"
assert flow.flow_id == "consumer-supplied-id"
assert flow.execution_id == original_execution_id
assert flow.execution_id != "consumer-supplied-id"
def test_two_runs_with_same_consumer_id_have_distinct_execution_ids() -> None:
flow_a = _IdentityCaptureFlow()
flow_b = _IdentityCaptureFlow()
colliding_id = "shared-consumer-id"
flow_a.kickoff(inputs={"id": colliding_id})
flow_b.kickoff(inputs={"id": colliding_id})
assert flow_a.state.id == colliding_id
assert flow_b.state.id == colliding_id
assert flow_a.execution_id != flow_b.execution_id
def test_execution_id_is_writable() -> None:
flow = _IdentityCaptureFlow()
flow.execution_id = "external-task-id"
assert flow.execution_id == "external-task-id"
flow.kickoff(inputs={"id": "consumer-supplied-id"})
assert flow.execution_id == "external-task-id"
assert flow.state.id == "consumer-supplied-id"
def test_current_flow_id_context_var_matches_execution_id() -> None:
flow = _IdentityCaptureFlow()
flow.execution_id = "external-task-id"
flow.kickoff(inputs={"id": "consumer-supplied-id"})
assert flow.state.captured_current_flow_id == "external-task-id"
assert flow.state.captured_flow_id == "consumer-supplied-id"
assert flow.state.captured_execution_id == "external-task-id"
def test_execution_id_not_included_in_serialized_state() -> None:
flow = _IdentityCaptureFlow()
flow.execution_id = "external-task-id"
flow.kickoff()
dumped = flow.state.model_dump()
assert "execution_id" not in dumped
assert "_execution_id" not in dumped
assert dumped["id"] == flow.state.id
def test_dict_state_flow_also_exposes_stable_execution_id() -> None:
class DictFlow(Flow[dict[str, Any]]):
initial_state = dict # type: ignore[assignment]
@start()
def noop(self) -> None:
pass
flow = DictFlow()
original = flow.execution_id
flow.kickoff(inputs={"id": "consumer-supplied-id"})
assert flow.state["id"] == "consumer-supplied-id"
assert flow.execution_id == original
@pytest.fixture(autouse=True)
def _reset_flow_context_vars():
yield
for var in (current_flow_id, current_flow_request_id):
try:
var.set(None)
except LookupError:
# ContextVar was never set in this context; nothing to reset.
pass

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@@ -1,3 +1,3 @@
"""CrewAI development tools."""
__version__ = "1.14.3a3"
__version__ = "1.14.3"

2
uv.lock generated
View File

@@ -13,7 +13,7 @@ resolution-markers = [
]
[options]
exclude-newer = "2026-04-22T16:00:00Z"
exclude-newer = "2026-04-23T07:00:00Z"
[manifest]
members = [