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Merge branch 'main' into feat/cli-predeploy-validation

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This commit is contained in:
Greyson LaLonde
2026-04-11 05:52:01 +08:00
committed by GitHub
parent 9f61deb072 8de4421705
commit bbc7392a32
6 changed files with 173 additions and 45 deletions
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2
lib/crewai/pyproject.toml
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@@ -40,7 +40,7 @@ dependencies = [
"pydantic-settings~=2.10.1",
"httpx~=0.28.1",
"mcp~=1.26.0",
"uv~=0.9.13",
"uv~=0.11.6",
"aiosqlite~=0.21.0",
"pyyaml~=6.0",
"aiofiles~=24.1.0",

20
lib/crewai/src/crewai/llms/providers/anthropic/completion.py
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@@ -11,10 +11,14 @@ from crewai.events.types.llm_events import LLMCallType
from crewai.llms.base_llm import BaseLLM, JsonResponseFormat, llm_call_context
from crewai.llms.hooks.base import BaseInterceptor
from crewai.llms.hooks.transport import AsyncHTTPTransport, HTTPTransport
from crewai.llms.providers.utils.common import safe_tool_conversion
from crewai.utilities.agent_utils import is_context_length_exceeded
from crewai.utilities.exceptions.context_window_exceeding_exception import (
LLMContextLengthExceededError,
)
from crewai.utilities.pydantic_schema_utils import (
sanitize_tool_params_for_anthropic_strict,
)
from crewai.utilities.types import LLMMessage
@@ -494,10 +498,8 @@ class AnthropicCompletion(BaseLLM):
continue
try:
from crewai.llms.providers.utils.common import safe_tool_conversion
name, description, parameters = safe_tool_conversion(tool, "Anthropic")
except (ImportError, KeyError, ValueError) as e:
except (KeyError, ValueError) as e:
logging.error(f"Error converting tool to Anthropic format: {e}")
raise e
@@ -506,8 +508,15 @@ class AnthropicCompletion(BaseLLM):
"description": description,
}
func_info = tool.get("function", {})
strict_enabled = bool(func_info.get("strict"))
if parameters and isinstance(parameters, dict):
anthropic_tool["input_schema"] = parameters
anthropic_tool["input_schema"] = (
sanitize_tool_params_for_anthropic_strict(parameters)
if strict_enabled
else parameters
)
else:
anthropic_tool["input_schema"] = {
"type": "object",
@@ -515,8 +524,7 @@ class AnthropicCompletion(BaseLLM):
"required": [],
}
func_info = tool.get("function", {})
if func_info.get("strict"):
if strict_enabled:
anthropic_tool["strict"] = True
anthropic_tools.append(anthropic_tool)

21
lib/crewai/src/crewai/llms/providers/bedrock/completion.py
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@@ -12,11 +12,15 @@ from typing_extensions import Required
from crewai.events.types.llm_events import LLMCallType
from crewai.llms.base_llm import BaseLLM, llm_call_context
from crewai.llms.providers.utils.common import safe_tool_conversion
from crewai.utilities.agent_utils import is_context_length_exceeded
from crewai.utilities.exceptions.context_window_exceeding_exception import (
LLMContextLengthExceededError,
)
from crewai.utilities.pydantic_schema_utils import generate_model_description
from crewai.utilities.pydantic_schema_utils import (
generate_model_description,
sanitize_tool_params_for_bedrock_strict,
)
from crewai.utilities.types import LLMMessage
@@ -1969,8 +1973,6 @@ class BedrockCompletion(BaseLLM):
tools: list[dict[str, Any]],
) -> list[ConverseToolTypeDef]:
"""Convert CrewAI tools to Converse API format following AWS specification."""
from crewai.llms.providers.utils.common import safe_tool_conversion
converse_tools: list[ConverseToolTypeDef] = []
for tool in tools:
@@ -1982,12 +1984,19 @@ class BedrockCompletion(BaseLLM):
"description": description,
}
func_info = tool.get("function", {})
strict_enabled = bool(func_info.get("strict"))
if parameters and isinstance(parameters, dict):
input_schema: ToolInputSchema = {"json": parameters}
schema_params = (
sanitize_tool_params_for_bedrock_strict(parameters)
if strict_enabled
else parameters
)
input_schema: ToolInputSchema = {"json": schema_params}
tool_spec["inputSchema"] = input_schema
func_info = tool.get("function", {})
if func_info.get("strict"):
if strict_enabled:
tool_spec["strict"] = True
converse_tool: ConverseToolTypeDef = {"toolSpec": tool_spec}

18
lib/crewai/src/crewai/llms/providers/openai/completion.py
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@@ -32,11 +32,15 @@ from crewai.events.types.llm_events import LLMCallType
from crewai.llms.base_llm import BaseLLM, JsonResponseFormat, llm_call_context
from crewai.llms.hooks.base import BaseInterceptor
from crewai.llms.hooks.transport import AsyncHTTPTransport, HTTPTransport
from crewai.llms.providers.utils.common import safe_tool_conversion
from crewai.utilities.agent_utils import is_context_length_exceeded
from crewai.utilities.exceptions.context_window_exceeding_exception import (
LLMContextLengthExceededError,
)
from crewai.utilities.pydantic_schema_utils import generate_model_description
from crewai.utilities.pydantic_schema_utils import (
generate_model_description,
sanitize_tool_params_for_openai_strict,
)
from crewai.utilities.types import LLMMessage
@@ -782,8 +786,6 @@ class OpenAICompletion(BaseLLM):
"function": {"name": "...", "description": "...", "parameters": {...}}
}
"""
from crewai.llms.providers.utils.common import safe_tool_conversion
responses_tools = []
for tool in tools:
@@ -1568,11 +1570,6 @@ class OpenAICompletion(BaseLLM):
self, tools: list[dict[str, BaseTool]]
) -> list[dict[str, Any]]:
"""Convert CrewAI tool format to OpenAI function calling format."""
from crewai.llms.providers.utils.common import safe_tool_conversion
from crewai.utilities.pydantic_schema_utils import (
force_additional_properties_false,
)
openai_tools = []
for tool in tools:
@@ -1591,8 +1588,9 @@ class OpenAICompletion(BaseLLM):
params_dict = (
parameters if isinstance(parameters, dict) else dict(parameters)
)
params_dict = force_additional_properties_false(params_dict)
openai_tool["function"]["parameters"] = params_dict
openai_tool["function"]["parameters"] = (
sanitize_tool_params_for_openai_strict(params_dict)
)
openai_tools.append(openai_tool)
return openai_tools

115
lib/crewai/src/crewai/utilities/pydantic_schema_utils.py
View File

@@ -19,7 +19,7 @@ from collections.abc import Callable
from copy import deepcopy
import datetime
import logging
from typing import TYPE_CHECKING, Annotated, Any, Final, Literal, TypedDict, Union
from typing import TYPE_CHECKING, Annotated, Any, Final, Literal, TypedDict, Union, cast
import uuid
import jsonref # type: ignore[import-untyped]
@@ -417,6 +417,119 @@ def strip_null_from_types(schema: dict[str, Any]) -> dict[str, Any]:
return schema
_STRICT_METADATA_KEYS: Final[tuple[str, ...]] = (
"title",
"default",
"examples",
"example",
"$comment",
"readOnly",
"writeOnly",
"deprecated",
)
_CLAUDE_STRICT_UNSUPPORTED: Final[tuple[str, ...]] = (
"minimum",
"maximum",
"exclusiveMinimum",
"exclusiveMaximum",
"multipleOf",
"minLength",
"maxLength",
"pattern",
"minItems",
"maxItems",
"uniqueItems",
"minContains",
"maxContains",
"minProperties",
"maxProperties",
"patternProperties",
"propertyNames",
"dependentRequired",
"dependentSchemas",
)
def _strip_keys_recursive(d: Any, keys: tuple[str, ...]) -> Any:
"""Recursively delete a fixed set of keys from a schema."""
if isinstance(d, dict):
for key in keys:
d.pop(key, None)
for v in d.values():
_strip_keys_recursive(v, keys)
elif isinstance(d, list):
for i in d:
_strip_keys_recursive(i, keys)
return d
def lift_top_level_anyof(schema: dict[str, Any]) -> dict[str, Any]:
"""Unwrap a top-level anyOf/oneOf/allOf wrapping a single object variant.
Anthropic's strict ``input_schema`` rejects top-level union keywords. When
exactly one variant is an object schema, lift it so the root is a plain
object; otherwise leave the schema alone.
"""
for key in ("anyOf", "oneOf", "allOf"):
variants = schema.get(key)
if not isinstance(variants, list):
continue
object_variants = [
v for v in variants if isinstance(v, dict) and v.get("type") == "object"
]
if len(object_variants) == 1:
lifted = deepcopy(object_variants[0])
schema.pop(key)
schema.update(lifted)
break
return schema
def _common_strict_pipeline(params: dict[str, Any]) -> dict[str, Any]:
"""Shared strict sanitization: inline refs, close objects, require all properties."""
sanitized = resolve_refs(deepcopy(params))
sanitized.pop("$defs", None)
sanitized = convert_oneof_to_anyof(sanitized)
sanitized = ensure_type_in_schemas(sanitized)
sanitized = force_additional_properties_false(sanitized)
sanitized = ensure_all_properties_required(sanitized)
return cast(dict[str, Any], _strip_keys_recursive(sanitized, _STRICT_METADATA_KEYS))
def sanitize_tool_params_for_openai_strict(
params: dict[str, Any],
) -> dict[str, Any]:
"""Sanitize a JSON schema for OpenAI strict function calling."""
if not isinstance(params, dict):
return params
return cast(
dict[str, Any], strip_unsupported_formats(_common_strict_pipeline(params))
)
def sanitize_tool_params_for_anthropic_strict(
params: dict[str, Any],
) -> dict[str, Any]:
"""Sanitize a JSON schema for Anthropic strict tool use."""
if not isinstance(params, dict):
return params
sanitized = lift_top_level_anyof(_common_strict_pipeline(params))
sanitized = _strip_keys_recursive(sanitized, _CLAUDE_STRICT_UNSUPPORTED)
return cast(dict[str, Any], strip_unsupported_formats(sanitized))
def sanitize_tool_params_for_bedrock_strict(
params: dict[str, Any],
) -> dict[str, Any]:
"""Sanitize a JSON schema for Bedrock Converse strict tool use.
Bedrock Converse uses the same grammar compiler as the underlying Claude
model, so the constraints match Anthropic's.
"""
return sanitize_tool_params_for_anthropic_strict(params)
def generate_model_description(
model: type[BaseModel],
*,