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Merge branch 'main' into docs/secrets-manager-migration

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Heitor Carvalho
2026-05-21 14:07:39 -03:00
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parent c00713ef1d 56b6594669
commit 3b0794a4bb
33 changed files with 668 additions and 80 deletions
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25
docs/ar/changelog.mdx
View File

@@ -4,6 +4,31 @@ description: "تحديثات المنتج والتحسينات وإصلاحات
icon: "clock"
mode: "wide"
---
<Update label="21 مايو 2026">
## v1.14.6a1
[عرض الإصدار على GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.6a1)
## ما الذي تغير
### الميزات
- إضافة مستودع المهارات مع التسجيل، التخزين المؤقت، واجهة سطر الأوامر، وتكامل SDK
- توليد ملاحظات إصدار مصنفة للمؤسسات
### إصلاحات الأخطاء
- تعزيز تسلسل حالة وقت التشغيل عبر حقول الكيان
- تحديث idna إلى 3.15 لمعالجة مشكلة الأمان GHSA-65pc-fj4g-8rjx
- إزالة تعبيرات JSX `{" "}` التي تعطل عرض `<Steps>`
### الوثائق
- تحديث سجل التغييرات والإصدار لـ v1.14.5
## المساهمون
@akaKuruma, @alex-clawd, @greysonlalonde
</Update>
<Update label="19 مايو 2026">
## v1.14.5

25
docs/en/changelog.mdx
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@@ -4,6 +4,31 @@ description: "Product updates, improvements, and bug fixes for CrewAI"
icon: "clock"
mode: "wide"
---
<Update label="May 21, 2026">
## v1.14.6a1
[View release on GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.6a1)
## What's Changed
### Features
- Add Skills Repository with registry, cache, CLI, and SDK integration
- Generate categorized release notes for enterprise
### Bug Fixes
- Harden RuntimeState serialization across entity fields
- Bump idna to 3.15 to address security issue GHSA-65pc-fj4g-8rjx
- Remove `{" "}` JSX expressions breaking `<Steps>` render
### Documentation
- Update changelog and version for v1.14.5
## Contributors
@akaKuruma, @alex-clawd, @greysonlalonde
</Update>
<Update label="May 19, 2026">
## v1.14.5

25
docs/ko/changelog.mdx
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@@ -4,6 +4,31 @@ description: "CrewAI의 제품 업데이트, 개선 사항 및 버그 수정"
icon: "clock"
mode: "wide"
---
<Update label="2026년 5월 21일">
## v1.14.6a1
[GitHub 릴리스 보기](https://github.com/crewAIInc/crewAI/releases/tag/1.14.6a1)
## 변경 사항
### 기능
- 레지스트리, 캐시, CLI 및 SDK 통합이 포함된 기술 저장소 추가
- 기업용으로 분류된 릴리스 노트 생성
### 버그 수정
- 엔티티 필드 전반에 걸쳐 RuntimeState 직렬화 강화
- 보안 문제 GHSA-65pc-fj4g-8rjx를 해결하기 위해 idna를 3.15로 업데이트
- `<Steps>` 렌더링을 방해하는 `{" "}` JSX 표현식 제거
### 문서
- v1.14.5에 대한 변경 로그 및 버전 업데이트
## 기여자
@akaKuruma, @alex-clawd, @greysonlalonde
</Update>
<Update label="2026년 5월 19일">
## v1.14.5

25
docs/pt-BR/changelog.mdx
View File

@@ -4,6 +4,31 @@ description: "Atualizações de produto, melhorias e correções do CrewAI"
icon: "clock"
mode: "wide"
---
<Update label="21 mai 2026">
## v1.14.6a1
[Ver release no GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.6a1)
## O que Mudou
### Recursos
- Adicionar Repositório de Habilidades com registro, cache, CLI e integração SDK
- Gerar notas de versão categorizadas para empresas
### Correções de Bugs
- Fortalecer a serialização de RuntimeState entre os campos da entidade
- Atualizar idna para 3.15 para resolver problema de segurança GHSA-65pc-fj4g-8rjx
- Remover expressões JSX `{" "}` que quebram a renderização de `<Steps>`
### Documentação
- Atualizar changelog e versão para v1.14.5
## Contribuidores
@akaKuruma, @alex-clawd, @greysonlalonde
</Update>
<Update label="19 mai 2026">
## v1.14.5

2
lib/cli/pyproject.toml
View File

@@ -8,7 +8,7 @@ authors = [
]
requires-python = ">=3.10, <3.14"
dependencies = [
"crewai-core==1.14.5",
"crewai-core==1.14.6a1",
"click~=8.1.7",
"pydantic>=2.11.9,<2.13",
"pydantic-settings~=2.10.1",

2
lib/cli/src/crewai_cli/__init__.py
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@@ -1 +1 @@
__version__ = "1.14.5"
__version__ = "1.14.6a1"

2
lib/crewai-core/src/crewai_core/__init__.py
View File

@@ -1 +1 @@
__version__ = "1.14.5"
__version__ = "1.14.6a1"

2
lib/crewai-files/src/crewai_files/__init__.py
View File

@@ -152,4 +152,4 @@ __all__ = [
"wrap_file_source",
]
__version__ = "1.14.5"
__version__ = "1.14.6a1"

2
lib/crewai-tools/pyproject.toml
View File

@@ -10,7 +10,7 @@ requires-python = ">=3.10, <3.14"
dependencies = [
"pytube~=15.0.0",
"requests>=2.33.0,<3",
"crewai==1.14.5",
"crewai==1.14.6a1",
"tiktoken>=0.8.0,<0.13",
"beautifulsoup4~=4.13.4",
"python-docx~=1.2.0",

2
lib/crewai-tools/src/crewai_tools/__init__.py
View File

@@ -330,4 +330,4 @@ __all__ = [
"ZapierActionTools",
]
__version__ = "1.14.5"
__version__ = "1.14.6a1"

2
lib/crewai-tools/src/crewai_tools/tools/mongodb_vector_search_tool/vector_search.py
View File

@@ -103,7 +103,7 @@ class MongoDBVectorSearchTool(BaseTool):
),
]
)
package_dependencies: list[str] = Field(default_factory=lambda: ["mongdb"])
package_dependencies: list[str] = Field(default_factory=lambda: ["pymongo"])
def __init__(self, **kwargs: Any) -> None:
super().__init__(**kwargs)

2
lib/crewai-tools/tool.specs.json
View File

@@ -14633,7 +14633,7 @@
},
"name": "MongoDBVectorSearchTool",
"package_dependencies": [
"mongdb"
"pymongo"
],
"run_params_schema": {
"description": "Input for MongoDBTool.",

6
lib/crewai/pyproject.toml
View File

@@ -8,8 +8,8 @@ authors = [
]
requires-python = ">=3.10, <3.14"
dependencies = [
"crewai-core==1.14.5",
"crewai-cli==1.14.5",
"crewai-core==1.14.6a1",
"crewai-cli==1.14.6a1",
# Core Dependencies
"pydantic>=2.11.9,<2.13",
"openai>=2.30.0,<3",
@@ -54,7 +54,7 @@ Repository = "https://github.com/crewAIInc/crewAI"
[project.optional-dependencies]
tools = [
"crewai-tools==1.14.5",
"crewai-tools==1.14.6a1",
]
embeddings = [
"tiktoken>=0.8.0,<0.13"

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

@@ -48,7 +48,7 @@ def _suppress_pydantic_deprecation_warnings() -> None:
_suppress_pydantic_deprecation_warnings()
__version__ = "1.14.5"
__version__ = "1.14.6a1"
_LAZY_IMPORTS: dict[str, tuple[str, str]] = {
"Memory": ("crewai.memory.unified_memory", "Memory"),

53
lib/crewai/src/crewai/agents/agent_builder/base_agent.py
View File

@@ -31,13 +31,13 @@ from crewai.agents.tools_handler import ToolsHandler
from crewai.events.base_events import set_emission_counter
from crewai.events.event_bus import crewai_event_bus
from crewai.events.event_context import restore_event_scope, set_last_event_id
from crewai.knowledge.knowledge import Knowledge
from crewai.knowledge.knowledge import Knowledge, _resolve_knowledge_sources
from crewai.knowledge.knowledge_config import KnowledgeConfig
from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
from crewai.knowledge.storage.base_knowledge_storage import BaseKnowledgeStorage
from crewai.llms.base_llm import BaseLLM
from crewai.mcp.config import MCPServerConfig
from crewai.memory.memory_scope import MemoryScope, MemorySlice
from crewai.memory.memory_scope import MemoryScope, MemorySlice, _ensure_memory_kind
from crewai.memory.unified_memory import Memory
from crewai.rag.embeddings.types import EmbedderConfig
from crewai.security.security_config import SecurityConfig
@@ -127,6 +127,13 @@ def _validate_executor_ref(value: Any) -> Any:
return value
def _serialize_executor_ref(value: Any) -> dict[str, Any] | None:
if value is None:
return None
result: dict[str, Any] = value.model_dump(mode="json")
return result
def _serialize_llm_ref(value: Any) -> dict[str, Any] | None:
if value is None:
return None
@@ -251,14 +258,13 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
max_iter: int = Field(
default=25, description="Maximum iterations for an agent to execute a task"
)
agent_executor: SerializeAsAny[BaseAgentExecutor] | None = Field(
default=None, description="An instance of the CrewAgentExecutor class."
)
@field_validator("agent_executor", mode="before")
@classmethod
def _validate_agent_executor(cls, v: Any) -> Any:
return _validate_executor_ref(v)
agent_executor: Annotated[
SerializeAsAny[BaseAgentExecutor] | None,
BeforeValidator(_validate_executor_ref),
PlainSerializer(
_serialize_executor_ref, return_type=dict | None, when_used="json"
),
] = Field(default=None, description="An instance of the CrewAgentExecutor class.")
llm: Annotated[
str | BaseLLM | None,
@@ -288,7 +294,10 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
knowledge: Knowledge | None = Field(
default=None, description="Knowledge for the agent."
)
knowledge_sources: list[BaseKnowledgeSource] | None = Field(
knowledge_sources: Annotated[
list[BaseKnowledgeSource] | None,
BeforeValidator(_resolve_knowledge_sources),
] = Field(
default=None,
description="Knowledge sources for the agent.",
)
@@ -326,7 +335,14 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
default=None,
description="List of MCP server references. Supports 'https://server.com/path' for external servers and bare slugs like 'notion' for connected MCP integrations. Use '#tool_name' suffix for specific tools.",
)
memory: bool | Memory | MemoryScope | MemorySlice | None = Field(
memory: Annotated[
bool
| Annotated[
Memory | MemoryScope | MemorySlice, Field(discriminator="memory_kind")
]
| None,
BeforeValidator(_ensure_memory_kind),
] = Field(
default=None,
description=(
"Enable agent memory. Pass True for default Memory(), "
@@ -397,8 +413,21 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
self.agent_executor._resuming = True
if self.checkpoint_kickoff_event_id is not None:
self._kickoff_event_id = self.checkpoint_kickoff_event_id
self._rebind_memory_view()
self._restore_event_scope(state)
def _rebind_memory_view(self) -> None:
"""Reattach a fresh ``Memory`` to a restored ``MemoryScope``/``MemorySlice``.
Checkpoint JSON omits the live ``Memory`` dependency, so scoped
memory views raise ``RuntimeError`` on first use after restore.
"""
if (
isinstance(self.memory, MemoryScope | MemorySlice)
and self.memory._memory is None
):
self.memory.bind(Memory())
def _restore_event_scope(self, state: RuntimeState) -> None:
"""Rebuild the event scope stack from the checkpoint's event record.

52
lib/crewai/src/crewai/crew.py
View File

@@ -93,11 +93,11 @@ from crewai.events.types.crew_events import (
CrewTrainStartedEvent,
)
from crewai.flow.flow_trackable import FlowTrackable
from crewai.knowledge.knowledge import Knowledge
from crewai.knowledge.knowledge import Knowledge, _resolve_knowledge_sources
from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
from crewai.llm import LLM
from crewai.llms.base_llm import BaseLLM
from crewai.memory.memory_scope import MemoryScope, MemorySlice
from crewai.memory.memory_scope import MemoryScope, MemorySlice, _ensure_memory_kind
from crewai.memory.unified_memory import Memory
from crewai.process import Process
from crewai.rag.embeddings.types import EmbedderConfig
@@ -223,7 +223,14 @@ class Crew(FlowTrackable, BaseModel):
] = Field(default_factory=list)
process: Process = Field(default=Process.sequential)
verbose: bool = Field(default=False)
memory: bool | Memory | MemoryScope | MemorySlice | None = Field(
memory: Annotated[
bool
| Annotated[
Memory | MemoryScope | MemorySlice, Field(discriminator="memory_kind")
]
| None,
BeforeValidator(_ensure_memory_kind),
] = Field(
default=False,
description=(
"Enable crew memory. Pass True for default Memory(), "
@@ -322,7 +329,10 @@ class Crew(FlowTrackable, BaseModel):
default_factory=list,
description="list of execution logs for tasks",
)
knowledge_sources: list[BaseKnowledgeSource] | None = Field(
knowledge_sources: Annotated[
list[BaseKnowledgeSource] | None,
BeforeValidator(_resolve_knowledge_sources),
] = Field(
default=None,
description=(
"Knowledge sources for the crew. Add knowledge sources to the "
@@ -477,8 +487,42 @@ class Crew(FlowTrackable, BaseModel):
if self.checkpoint_train is not None:
self._train = self.checkpoint_train
self._rebind_memory_views()
self._restore_event_scope()
def _rebind_memory_views(self) -> None:
"""Reattach a live ``Memory`` to restored ``MemoryScope``/``MemorySlice`` views.
Checkpoint JSON omits the live ``Memory`` dependency on scope/slice
views, so after restore they raise ``RuntimeError`` on first use.
Prefer the crew's restored ``Memory`` (from ``create_crew_memory``
or a ``Crew.memory=Memory(...)`` instance) so all views share one
backing store; fall back to a fresh ``Memory()`` only if nothing is
available.
"""
from crewai.memory.memory_scope import MemoryScope, MemorySlice
from crewai.memory.unified_memory import Memory
backing: Memory | None = None
if isinstance(self._memory, Memory):
backing = self._memory
elif isinstance(self.memory, Memory):
backing = self.memory
def _ensure(view: Any) -> None:
nonlocal backing
if not isinstance(view, MemoryScope | MemorySlice):
return
if view._memory is not None:
return
if backing is None:
backing = Memory()
view.bind(backing)
_ensure(self.memory)
for agent in self.agents:
_ensure(agent.memory)
def _restore_event_scope(self) -> None:
"""Rebuild the event scope stack from the checkpoint's event record."""
from crewai.events.base_events import set_emission_counter

61
lib/crewai/src/crewai/flow/flow.py
View File

@@ -113,7 +113,7 @@ from crewai.flow.utils import (
is_flow_method_name,
is_simple_flow_condition,
)
from crewai.memory.memory_scope import MemoryScope, MemorySlice
from crewai.memory.memory_scope import MemoryScope, MemorySlice, _ensure_memory_kind
from crewai.memory.unified_memory import Memory
from crewai.state.checkpoint_config import (
CheckpointConfig,
@@ -159,6 +159,39 @@ def _resolve_persistence(value: Any) -> Any:
return value
def _serialize_persistence(value: Any) -> dict[str, Any] | None:
if value is None:
return None
if isinstance(value, FlowPersistence):
return value.model_dump(mode="json")
raise TypeError(
f"Cannot serialize Flow.persistence of type {type(value).__name__}: "
"expected FlowPersistence or None."
)
def _validate_input_provider(value: Any) -> Any:
if value is None or isinstance(value, InputProvider):
return value
from crewai.types.callback import _dotted_path_to_instance
resolved = _dotted_path_to_instance(value)
if resolved is None or isinstance(resolved, InputProvider):
return resolved
raise ValueError(
f"Resolved input_provider {resolved!r} does not implement the "
"InputProvider protocol (missing request_input)."
)
def _serialize_input_provider(value: Any) -> str | None:
if value is None:
return None
from crewai.types.callback import _instance_to_dotted_path
return _instance_to_dotted_path(value)
_INITIAL_STATE_CLASS_MARKER = "__crewai_pydantic_class_schema__"
@@ -949,15 +982,30 @@ class Flow(BaseModel, Generic[T], metaclass=FlowMeta):
name: str | None = Field(default=None)
tracing: bool | None = Field(default=None)
stream: bool = Field(default=False)
memory: Memory | MemoryScope | MemorySlice | None = Field(default=None)
input_provider: InputProvider | None = Field(default=None)
memory: Annotated[
Annotated[
Memory | MemoryScope | MemorySlice, Field(discriminator="memory_kind")
]
| None,
BeforeValidator(_ensure_memory_kind),
] = Field(default=None)
input_provider: Annotated[
InputProvider | None,
BeforeValidator(_validate_input_provider),
PlainSerializer(
_serialize_input_provider, return_type=str | None, when_used="json"
),
] = Field(default=None)
suppress_flow_events: bool = Field(default=False)
human_feedback_history: list[HumanFeedbackResult] = Field(default_factory=list)
last_human_feedback: HumanFeedbackResult | None = Field(default=None)
persistence: Annotated[
SerializeAsAny[FlowPersistence] | Any,
SerializeAsAny[FlowPersistence] | None,
BeforeValidator(lambda v, _: _resolve_persistence(v)),
PlainSerializer(
_serialize_persistence, return_type=dict | None, when_used="json"
),
] = Field(default=None)
max_method_calls: int = Field(default=100)
@@ -1050,6 +1098,11 @@ class Flow(BaseModel, Generic[T], metaclass=FlowMeta):
}
if self.checkpoint_state is not None:
self._restore_state(self.checkpoint_state)
if (
isinstance(self.memory, MemoryScope | MemorySlice)
and self.memory._memory is None
):
self.memory.bind(Memory())
restore_event_scope(())
reset_last_event_id()

87
lib/crewai/src/crewai/knowledge/knowledge.py
View File

@@ -1,16 +1,89 @@
import os
from typing import Annotated, Any
from pydantic import BaseModel, ConfigDict, Field
from pydantic import BaseModel, BeforeValidator, ConfigDict, Field, PlainSerializer
from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
from crewai.knowledge.source.crew_docling_source import CrewDoclingSource
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.string_knowledge_source import StringKnowledgeSource
from crewai.knowledge.source.text_file_knowledge_source import (
TextFileKnowledgeSource,
)
from crewai.knowledge.storage.knowledge_storage import KnowledgeStorage
from crewai.rag.core.base_embeddings_provider import BaseEmbeddingsProvider
from crewai.rag.embeddings.types import EmbedderConfig
from crewai.rag.types import SearchResult
_KNOWN_SOURCES: dict[str, type[BaseKnowledgeSource]] = {
"string": StringKnowledgeSource,
"docling": CrewDoclingSource,
"csv": CSVKnowledgeSource,
"excel": ExcelKnowledgeSource,
"json": JSONKnowledgeSource,
"pdf": PDFKnowledgeSource,
"text_file": TextFileKnowledgeSource,
}
def _resolve_knowledge_sources(value: Any) -> Any:
"""Coerce list of dicts into typed BaseKnowledgeSource subclasses via source_type.
Pass-through for anything else (existing instances, mocks).
"""
if not isinstance(value, list):
return value
resolved: list[Any] = []
for idx, item in enumerate(value):
if isinstance(item, dict):
tag = item.get("source_type")
if not isinstance(tag, str):
resolved.append(item)
continue
cls = _KNOWN_SOURCES.get(tag)
if cls is None:
raise ValueError(
f"Unknown source_type={tag!r} at index {idx}: "
f"expected one of {sorted(_KNOWN_SOURCES)}"
)
try:
resolved.append(cls.model_validate(item))
except Exception as exc:
raise ValueError(
f"Failed to validate knowledge source at index {idx} "
f"with source_type={tag!r}: {exc}"
) from exc
else:
resolved.append(item)
return resolved
os.environ["TOKENIZERS_PARALLELISM"] = "false" # removes logging from fastembed
def _serialize_embedder_spec(value: Any) -> dict[str, Any] | None:
if value is None:
return None
if isinstance(value, BaseEmbeddingsProvider):
return value.model_dump(mode="json")
if isinstance(value, dict):
return value
if isinstance(value, type) and issubclass(value, BaseEmbeddingsProvider):
raise TypeError(
f"Cannot checkpoint embedder class {value.__module__}.{value.__qualname__}: "
"build_embedder requires an instance or ProviderSpec dict, not a class. "
"Instantiate the provider before assigning it to Knowledge.embedder."
)
raise TypeError(
f"Cannot serialize embedder of type {type(value).__name__}: "
"expected ProviderSpec dict or BaseEmbeddingsProvider instance."
)
class Knowledge(BaseModel):
"""
Knowledge is a collection of sources and setup for the vector store to save and query relevant context.
@@ -20,10 +93,18 @@ class Knowledge(BaseModel):
embedder: EmbedderConfig | None = None
"""
sources: list[BaseKnowledgeSource] = Field(default_factory=list)
sources: Annotated[
list[BaseKnowledgeSource],
BeforeValidator(_resolve_knowledge_sources),
] = Field(default_factory=list)
model_config = ConfigDict(arbitrary_types_allowed=True)
storage: KnowledgeStorage | None = Field(default=None)
embedder: EmbedderConfig | None = None
embedder: Annotated[
EmbedderConfig | None,
PlainSerializer(
_serialize_embedder_spec, return_type=dict | None, when_used="json"
),
] = None
collection_name: str | None = None
def __init__(

4
lib/crewai/src/crewai/knowledge/source/base_knowledge_source.py
View File

@@ -13,7 +13,9 @@ class BaseKnowledgeSource(BaseModel, ABC):
chunk_size: int = 4000
chunk_overlap: int = 200
chunks: list[str] = Field(default_factory=list)
chunk_embeddings: list[np.ndarray[Any, np.dtype[Any]]] = Field(default_factory=list)
chunk_embeddings: list[np.ndarray[Any, np.dtype[Any]]] = Field(
default_factory=list, exclude=True
)
model_config = ConfigDict(arbitrary_types_allowed=True)
storage: KnowledgeStorage | None = Field(default=None)

3
lib/crewai/src/crewai/knowledge/source/crew_docling_source.py
View File

@@ -2,7 +2,7 @@ from __future__ import annotations
from collections.abc import Iterator
from pathlib import Path
from typing import TYPE_CHECKING, Any
from typing import TYPE_CHECKING, Any, Literal
from urllib.parse import urlparse
@@ -45,6 +45,7 @@ class CrewDoclingSource(BaseKnowledgeSource):
_logger: Logger = Logger(verbose=True)
source_type: Literal["docling"] = "docling"
file_path: list[Path | str] | None = Field(default=None)
file_paths: list[Path | str] = Field(default_factory=list)
chunks: list[str] = Field(default_factory=list)

3
lib/crewai/src/crewai/knowledge/source/csv_knowledge_source.py
View File

@@ -1,5 +1,6 @@
import csv
from pathlib import Path
from typing import Literal
from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledgeSource
@@ -7,6 +8,8 @@ from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledge
class CSVKnowledgeSource(BaseFileKnowledgeSource):
"""A knowledge source that stores and queries CSV file content using embeddings."""
source_type: Literal["csv"] = "csv"
def load_content(self) -> dict[Path, str]:
"""Load and preprocess CSV file content."""
content_dict = {}

3
lib/crewai/src/crewai/knowledge/source/excel_knowledge_source.py
View File

@@ -1,6 +1,6 @@
from pathlib import Path
from types import ModuleType
from typing import Any
from typing import Any, Literal
from pydantic import Field, field_validator
@@ -16,6 +16,7 @@ class ExcelKnowledgeSource(BaseKnowledgeSource):
_logger: Logger = Logger(verbose=True)
source_type: Literal["excel"] = "excel"
file_path: Path | list[Path] | str | list[str] | None = Field(
default=None,
description="[Deprecated] The path to the file. Use file_paths instead.",

4
lib/crewai/src/crewai/knowledge/source/json_knowledge_source.py
View File

@@ -1,6 +1,6 @@
import json
from pathlib import Path
from typing import Any
from typing import Any, Literal
from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledgeSource
@@ -8,6 +8,8 @@ from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledge
class JSONKnowledgeSource(BaseFileKnowledgeSource):
"""A knowledge source that stores and queries JSON file content using embeddings."""
source_type: Literal["json"] = "json"
def load_content(self) -> dict[Path, str]:
"""Load and preprocess JSON file content."""
content: dict[Path, str] = {}

3
lib/crewai/src/crewai/knowledge/source/pdf_knowledge_source.py
View File

@@ -1,5 +1,6 @@
from pathlib import Path
from types import ModuleType
from typing import Literal
from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledgeSource
@@ -7,6 +8,8 @@ from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledge
class PDFKnowledgeSource(BaseFileKnowledgeSource):
"""A knowledge source that stores and queries PDF file content using embeddings."""
source_type: Literal["pdf"] = "pdf"
def load_content(self) -> dict[Path, str]:
"""Load and preprocess PDF file content."""
pdfplumber = self._import_pdfplumber()

3
lib/crewai/src/crewai/knowledge/source/string_knowledge_source.py
View File

@@ -1,4 +1,4 @@
from typing import Any
from typing import Any, Literal
from pydantic import Field
@@ -8,6 +8,7 @@ from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
class StringKnowledgeSource(BaseKnowledgeSource):
"""A knowledge source that stores and queries plain text content using embeddings."""
source_type: Literal["string"] = "string"
content: str = Field(...)
collection_name: str | None = Field(default=None)

3
lib/crewai/src/crewai/knowledge/source/text_file_knowledge_source.py
View File

@@ -1,4 +1,5 @@
from pathlib import Path
from typing import Literal
from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledgeSource
@@ -6,6 +7,8 @@ from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledge
class TextFileKnowledgeSource(BaseFileKnowledgeSource):
"""A knowledge source that stores and queries text file content using embeddings."""
source_type: Literal["text_file"] = "text_file"
def load_content(self) -> dict[Path, str]:
"""Load and preprocess text file content."""
content = {}

109
lib/crewai/src/crewai/memory/memory_scope.py
View File

@@ -6,6 +6,7 @@ from datetime import datetime
from typing import Any, Literal
from pydantic import BaseModel, ConfigDict, Field, PrivateAttr, model_validator
from typing_extensions import Self
from crewai.memory.types import (
_RECALL_OVERSAMPLE_FACTOR,
@@ -16,15 +17,35 @@ from crewai.memory.types import (
from crewai.memory.unified_memory import Memory
def _ensure_memory_kind(value: Any) -> Any:
"""Backfill ``memory_kind`` on legacy dicts that predate the discriminator.
Lets pre-1.14.6 configs/checkpoints flow into the discriminated
``Memory | MemoryScope | MemorySlice`` union without crashing. Inference:
``scopes`` key → ``slice``; ``root_path`` → ``scope``; else ``memory``.
Pass-through for non-dict values (instances, ``bool``, ``None``).
"""
if isinstance(value, dict) and "memory_kind" not in value:
if "scopes" in value:
value["memory_kind"] = "slice"
elif "root_path" in value:
value["memory_kind"] = "scope"
else:
value["memory_kind"] = "memory"
return value
class MemoryScope(BaseModel):
"""View of Memory restricted to a root path. All operations are scoped under that path."""
model_config = ConfigDict(arbitrary_types_allowed=True)
memory_kind: Literal["scope"] = "scope"
root_path: str = Field(default="/")
_memory: Memory = PrivateAttr()
_root: str = PrivateAttr()
_memory: Memory | None = PrivateAttr(default=None)
_root: str = PrivateAttr(default="")
@model_validator(mode="wrap")
@classmethod
@@ -34,21 +55,38 @@ class MemoryScope(BaseModel):
return data
if not isinstance(data, dict):
raise ValueError(f"Expected dict or MemoryScope, got {type(data).__name__}")
if "memory" not in data:
raise ValueError("MemoryScope requires a 'memory' key")
memory = data.pop("memory")
memory = data.pop("memory", None)
instance: MemoryScope = handler(data)
instance._memory = memory
if memory is not None:
instance._memory = memory
root = instance.root_path.rstrip("/") or ""
if root and not root.startswith("/"):
root = "/" + root
instance._root = root
return instance
def bind(self, memory: Memory) -> Self:
"""Rebind the runtime ``Memory`` dependency after restore.
Required after deserializing from a checkpoint, since the live
``Memory`` cannot be serialized.
"""
self._memory = memory
return self
def _require_memory(self) -> Memory:
"""Return the bound ``Memory`` or raise a clear error if missing."""
if self._memory is None:
raise RuntimeError(
"MemoryScope is not bound to a Memory; call .bind(memory) "
"after restore."
)
return self._memory
@property
def read_only(self) -> bool:
"""Whether the underlying memory is read-only."""
return self._memory.read_only
return self._require_memory().read_only
def _scope_path(self, scope: str | None) -> str:
if not scope or scope == "/":
@@ -73,7 +111,7 @@ class MemoryScope(BaseModel):
) -> MemoryRecord | None:
"""Remember content; scope is relative to this scope's root."""
path = self._scope_path(scope)
return self._memory.remember(
return self._require_memory().remember(
content,
scope=path,
categories=categories,
@@ -96,7 +134,7 @@ class MemoryScope(BaseModel):
) -> list[MemoryRecord]:
"""Remember multiple items; scope is relative to this scope's root."""
path = self._scope_path(scope)
return self._memory.remember_many(
return self._require_memory().remember_many(
contents,
scope=path,
categories=categories,
@@ -119,7 +157,7 @@ class MemoryScope(BaseModel):
) -> list[MemoryMatch]:
"""Recall within this scope (root path and below)."""
search_scope = self._scope_path(scope) if scope else (self._root or "/")
return self._memory.recall(
return self._require_memory().recall(
query,
scope=search_scope,
categories=categories,
@@ -131,7 +169,7 @@ class MemoryScope(BaseModel):
def extract_memories(self, content: str) -> list[str]:
"""Extract discrete memories from content; delegates to underlying Memory."""
return self._memory.extract_memories(content)
return self._require_memory().extract_memories(content)
def forget(
self,
@@ -143,7 +181,7 @@ class MemoryScope(BaseModel):
) -> int:
"""Forget within this scope."""
prefix = self._scope_path(scope) if scope else (self._root or "/")
return self._memory.forget(
return self._require_memory().forget(
scope=prefix,
categories=categories,
older_than=older_than,
@@ -154,27 +192,27 @@ class MemoryScope(BaseModel):
def list_scopes(self, path: str = "/") -> list[str]:
"""List child scopes under path (relative to this scope's root)."""
full = self._scope_path(path)
return self._memory.list_scopes(full)
return self._require_memory().list_scopes(full)
def info(self, path: str = "/") -> ScopeInfo:
"""Info for path under this scope."""
full = self._scope_path(path)
return self._memory.info(full)
return self._require_memory().info(full)
def tree(self, path: str = "/", max_depth: int = 3) -> str:
"""Tree under path within this scope."""
full = self._scope_path(path)
return self._memory.tree(full, max_depth=max_depth)
return self._require_memory().tree(full, max_depth=max_depth)
def list_categories(self, path: str | None = None) -> dict[str, int]:
"""Categories in this scope; path None means this scope root."""
full = self._scope_path(path) if path else (self._root or "/")
return self._memory.list_categories(full)
return self._require_memory().list_categories(full)
def reset(self, scope: str | None = None) -> None:
"""Reset within this scope."""
prefix = self._scope_path(scope) if scope else (self._root or "/")
self._memory.reset(scope=prefix)
self._require_memory().reset(scope=prefix)
def subscope(self, path: str) -> MemoryScope:
"""Return a narrower scope under this scope."""
@@ -191,11 +229,13 @@ class MemorySlice(BaseModel):
model_config = ConfigDict(arbitrary_types_allowed=True)
memory_kind: Literal["slice"] = "slice"
scopes: list[str] = Field(default_factory=list)
categories: list[str] | None = Field(default=None)
read_only: bool = Field(default=True)
_memory: Memory = PrivateAttr()
_memory: Memory | None = PrivateAttr(default=None)
@model_validator(mode="wrap")
@classmethod
@@ -205,14 +245,27 @@ class MemorySlice(BaseModel):
return data
if not isinstance(data, dict):
raise ValueError(f"Expected dict or MemorySlice, got {type(data).__name__}")
if "memory" not in data:
raise ValueError("MemorySlice requires a 'memory' key")
memory = data.pop("memory")
memory = data.pop("memory", None)
data["scopes"] = [s.rstrip("/") or "/" for s in data.get("scopes", [])]
instance: MemorySlice = handler(data)
instance._memory = memory
if memory is not None:
instance._memory = memory
return instance
def bind(self, memory: Memory) -> Self:
"""Rebind the runtime ``Memory`` dependency after restore."""
self._memory = memory
return self
def _require_memory(self) -> Memory:
"""Return the bound ``Memory`` or raise a clear error if missing."""
if self._memory is None:
raise RuntimeError(
"MemorySlice is not bound to a Memory; call .bind(memory) "
"after restore."
)
return self._memory
def remember(
self,
content: str,
@@ -226,7 +279,7 @@ class MemorySlice(BaseModel):
"""Remember into an explicit scope. No-op when read_only=True."""
if self.read_only:
return None
return self._memory.remember(
return self._require_memory().remember(
content,
scope=scope,
categories=categories,
@@ -250,7 +303,7 @@ class MemorySlice(BaseModel):
cats = categories or self.categories
all_matches: list[MemoryMatch] = []
for sc in self.scopes:
matches = self._memory.recall(
matches = self._require_memory().recall(
query,
scope=sc,
categories=cats,
@@ -272,14 +325,14 @@ class MemorySlice(BaseModel):
def extract_memories(self, content: str) -> list[str]:
"""Extract discrete memories from content; delegates to underlying Memory."""
return self._memory.extract_memories(content)
return self._require_memory().extract_memories(content)
def list_scopes(self, path: str = "/") -> list[str]:
"""List scopes across all slice roots."""
out: list[str] = []
for sc in self.scopes:
full = f"{sc.rstrip('/')}{path}" if sc != "/" else path
out.extend(self._memory.list_scopes(full))
out.extend(self._require_memory().list_scopes(full))
return sorted(set(out))
def info(self, path: str = "/") -> ScopeInfo:
@@ -291,7 +344,7 @@ class MemorySlice(BaseModel):
children: list[str] = []
for sc in self.scopes:
full = f"{sc.rstrip('/')}{path}" if sc != "/" else path
inf = self._memory.info(full)
inf = self._require_memory().info(full)
total_records += inf.record_count
all_categories.update(inf.categories)
if inf.oldest_record:
@@ -321,6 +374,6 @@ class MemorySlice(BaseModel):
counts: dict[str, int] = {}
for sc in self.scopes:
full = (f"{sc.rstrip('/')}{path}" if sc != "/" else path) if path else sc
for k, v in self._memory.list_categories(full).items():
for k, v in self._require_memory().list_categories(full).items():
counts[k] = counts.get(k, 0) + v
return counts

2
lib/crewai/src/crewai/memory/unified_memory.py
View File

@@ -63,6 +63,8 @@ class Memory(BaseModel):
model_config = ConfigDict(arbitrary_types_allowed=True)
memory_kind: Literal["memory"] = "memory"
llm: Annotated[BaseLLM | str, PlainValidator(_passthrough)] = Field(
default="gpt-4o-mini",
description="LLM for analysis (model name or BaseLLM instance).",

60
lib/crewai/src/crewai/state/runtime.py
View File

@@ -113,12 +113,68 @@ def _migrate(data: dict[str, Any]) -> dict[str, Any]:
)
# --- migrations in version order ---
# if stored < Version("X.Y.Z"):
# data.setdefault("some_field", "default")
if stored < Version("1.14.6"):
for entity in data.get("entities") or []:
_backfill_discriminators(entity)
return data
def _backfill_memory_kind(value: Any) -> None:
"""Infer ``memory_kind`` from structural fields on legacy memory dicts."""
if not isinstance(value, dict) or "memory_kind" in value:
return
if "scopes" in value:
value["memory_kind"] = "slice"
elif "root_path" in value:
value["memory_kind"] = "scope"
else:
value["memory_kind"] = "memory"
def _backfill_source_type(source: Any) -> None:
"""Infer ``source_type`` for legacy knowledge source dicts when possible.
Only StringKnowledgeSource is reliably inferrable: it stores ``content``
as a plain string. File-based sources (CSV/PDF/Excel/JSON/docling) also
have a ``content`` field but populate it with dicts/lists, so we leave
those untagged and let downstream validation surface a clear error.
"""
if not isinstance(source, dict) or "source_type" in source:
return
if isinstance(source.get("content"), str):
source["source_type"] = "string"
return
raise ValueError(
"Legacy knowledge source is missing 'source_type' and could not be "
"inferred during migration. Re-checkpoint after upgrading to 1.14.6+."
)
def _backfill_sources_on(container: Any) -> None:
"""Apply source_type backfill to ``sources`` and ``knowledge_sources`` lists."""
if not isinstance(container, dict):
return
for key in ("sources", "knowledge_sources"):
for src in container.get(key) or []:
_backfill_source_type(src)
def _backfill_discriminators(entity: Any) -> None:
"""Walk an entity dict and backfill discriminator fields added in 1.14.6."""
if not isinstance(entity, dict):
return
_backfill_memory_kind(entity.get("memory"))
_backfill_sources_on(entity)
_backfill_sources_on(entity.get("knowledge"))
for agent in entity.get("agents") or []:
if not isinstance(agent, dict):
continue
_backfill_memory_kind(agent.get("memory"))
_backfill_sources_on(agent)
_backfill_sources_on(agent.get("knowledge"))
class RuntimeState(RootModel): # type: ignore[type-arg]
root: list[Entity]
_provider: BaseProvider = PrivateAttr(default_factory=JsonProvider)

86
lib/crewai/src/crewai/types/callback.py
View File

@@ -19,6 +19,15 @@ from pydantic import BeforeValidator, WithJsonSchema
from pydantic.functional_serializers import PlainSerializer
_TRUSTED_DESERIALIZE_VALUES = frozenset({"1", "true", "yes"})
def _trusted_deserialize() -> bool:
"""Return True only if ``CREWAI_DESERIALIZE_CALLBACKS`` is an explicit yes."""
raw = os.environ.get("CREWAI_DESERIALIZE_CALLBACKS", "")
return raw.strip().lower() in _TRUSTED_DESERIALIZE_VALUES
def _is_non_roundtrippable(fn: object) -> bool:
"""Return ``True`` if *fn* cannot survive a serialize/deserialize round-trip.
@@ -76,7 +85,7 @@ def string_to_callable(value: Any) -> Callable[..., Any]:
raise ValueError(
f"Invalid callback path {value!r}: expected 'module.name' format"
)
if not os.environ.get("CREWAI_DESERIALIZE_CALLBACKS"):
if not _trusted_deserialize():
raise ValueError(
f"Refusing to resolve callback path {value!r}: "
"set CREWAI_DESERIALIZE_CALLBACKS=1 to allow. "
@@ -150,3 +159,78 @@ SerializableCallable = Annotated[
PlainSerializer(callable_to_string, return_type=str, when_used="json"),
WithJsonSchema({"type": "string"}),
]
def _instance_to_dotted_path(value: Any) -> str:
"""Serialize an instance to a dotted path naming its class."""
if inspect.isclass(value):
module = getattr(value, "__module__", "<unknown>")
qualname = getattr(
value, "__qualname__", getattr(value, "__name__", str(type(value)))
)
raise ValueError(f"Expected an instance, got class {module}.{qualname}.")
cls = type(value)
if cls.__module__ == "builtins":
raise ValueError(
f"Cannot serialize {value!r}: builtin values are not "
"checkpointable instances."
)
module = getattr(cls, "__module__", None)
qualname = getattr(cls, "__qualname__", None)
if module is None or qualname is None:
raise ValueError(
f"Cannot serialize {value!r}: class missing __module__ or __qualname__. "
"Use a module-level class for checkpointable instances."
)
if qualname.endswith("<lambda>") or "<locals>" in qualname:
raise ValueError(
f"Cannot serialize {value!r}: class defined in <locals>. "
"Use a module-level class for checkpointable instances."
)
return f"{module}.{qualname}"
def _dotted_path_to_instance(value: Any) -> Any:
"""Resolve a dotted path to a class and instantiate it with no args.
If *value* is already a non-string object it is returned as-is.
"""
if value is None:
return value
if not isinstance(value, str):
if inspect.isclass(value):
raise ValueError(
f"Expected an instance or dotted path string, got class "
f"{getattr(value, '__module__', '<unknown>')}."
f"{getattr(value, '__qualname__', getattr(value, '__name__', ''))}."
)
if type(value).__module__ == "builtins":
raise ValueError(
f"Expected an instance of a user-defined class or dotted "
f"path string, got builtin value {value!r}."
)
return value
if "." not in value:
raise ValueError(
f"Invalid provider path {value!r}: expected 'module.name' format"
)
if not _trusted_deserialize():
raise ValueError(
f"Refusing to resolve provider path {value!r}: "
"set CREWAI_DESERIALIZE_CALLBACKS=1 to allow. "
"Only enable this for trusted checkpoint data."
)
cls = _resolve_dotted_path(value)
if not inspect.isclass(cls):
raise ValueError(
f"Invalid provider path {value!r}: expected a class, got "
f"{type(cls).__name__}"
)
try:
return cls()
except TypeError as exc:
raise ValueError(
f"Cannot reinstantiate {value!r} with no arguments: {exc}. "
"Only no-arg constructors are checkpointable; rebuild the "
"instance manually and assign it after restore."
) from exc

10
lib/crewai/src/crewai/utilities/reset_memories.py
View File

@@ -25,10 +25,16 @@ def _reset_flow_memory(flow: Flow[Any]) -> None:
try:
if hasattr(mem, "reset"):
mem.reset()
elif hasattr(mem, "_memory") and hasattr(mem._memory, "reset"):
elif hasattr(mem, "_memory") and mem._memory is not None:
mem._memory.reset()
except (FileNotFoundError, OSError):
except FileNotFoundError:
# Storage directory was never created — nothing to reset.
pass
except OSError as exc:
click.echo(f"Memory reset skipped: storage I/O error ({exc}).", err=True)
except RuntimeError as exc:
# Restored MemoryScope/MemorySlice without a rebound Memory.
click.echo(f"Memory reset skipped: {exc}", err=True)
def reset_memories_command(

76
lib/crewai/tests/test_flow_ask.py
View File

@@ -7,20 +7,87 @@ durability, input history tracking, and integration with flow machinery.
from __future__ import annotations
import copy
import time
from datetime import datetime
from typing import Any
from unittest.mock import MagicMock, patch
from pydantic import BaseModel
from crewai.flow import Flow, flow_config, listen, start
from crewai.flow.async_feedback.providers import ConsoleProvider
from crewai.flow.flow import FlowState
from crewai.flow.input_provider import InputProvider, InputResponse
from crewai.flow.persistence.base import FlowPersistence
# ── Test helpers ─────────────────────────────────────────────────
class _SaveCall:
"""Lightweight stand-in for ``MagicMock.call_args`` entries."""
__slots__ = ("args", "kwargs")
def __init__(self, args: tuple[Any, ...], kwargs: dict[str, Any]) -> None:
self.args = args
self.kwargs = kwargs
class _SaveStateRecorder:
"""Callable that records each ``save_state`` invocation."""
def __init__(self, owner: RecordingPersistence) -> None:
self._owner = owner
self.call_args_list: list[_SaveCall] = []
def __call__(
self,
flow_uuid: str,
method_name: str,
state_data: dict[str, Any] | BaseModel,
) -> None:
snapshot: dict[str, Any] | BaseModel
if isinstance(state_data, BaseModel):
snapshot = state_data.model_copy(deep=True)
else:
snapshot = copy.deepcopy(state_data)
self.call_args_list.append(
_SaveCall((flow_uuid, method_name, snapshot), {})
)
self._owner._states[flow_uuid] = snapshot
class RecordingPersistence(FlowPersistence):
"""In-memory FlowPersistence that records ``save_state`` invocations."""
persistence_type: str = "RecordingPersistence"
def model_post_init(self, _: Any) -> None:
object.__setattr__(self, "_states", {})
object.__setattr__(self, "save_state", _SaveStateRecorder(self))
def init_db(self) -> None:
return None
def save_state( # type: ignore[no-redef]
self,
flow_uuid: str,
method_name: str,
state_data: dict[str, Any] | BaseModel,
) -> None:
return None
def load_state(self, flow_uuid: str) -> dict[str, Any] | None:
snapshot = self._states.get(flow_uuid)
if snapshot is None:
return None
if isinstance(snapshot, BaseModel):
return snapshot.model_copy(deep=True).model_dump()
return copy.deepcopy(snapshot)
class MockInputProvider:
"""Mock input provider that returns pre-configured responses."""
@@ -436,8 +503,7 @@ class TestAskCheckpoint:
def test_ask_checkpoints_state_before_waiting(self) -> None:
"""State is saved to persistence before waiting for input."""
mock_persistence = MagicMock()
mock_persistence.load_state.return_value = None
mock_persistence = RecordingPersistence()
class TestFlow(Flow):
input_provider = MockInputProvider(["answer"])
@@ -480,8 +546,7 @@ class TestAskCheckpoint:
server crashes while waiting for input, previously gathered data
is safe.
"""
mock_persistence = MagicMock()
mock_persistence.load_state.return_value = None
mock_persistence = RecordingPersistence()
class GatherFlow(Flow):
input_provider = MockInputProvider(["AI", "detailed"])
@@ -678,8 +743,7 @@ class TestAskIntegration:
def test_ask_with_state_persistence_recovery(self) -> None:
"""Ask checkpoints state so previously gathered values survive."""
mock_persistence = MagicMock()
mock_persistence.load_state.return_value = None
mock_persistence = RecordingPersistence()
class RecoverableFlow(Flow):
input_provider = MockInputProvider(["AI", "detailed"])

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

@@ -1,3 +1,3 @@
"""CrewAI development tools."""
__version__ = "1.14.5"
__version__ = "1.14.6a1"