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

2026-07-03 06:08:15 +00:00 · 2026-04-11 05:52:01 +08:00
parent 9f61deb072 8de4421705
commit bbc7392a32
6 changed files with 173 additions and 45 deletions
--- a/lib/crewai/pyproject.toml
+++ b/lib/crewai/pyproject.toml
@@ -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",
--- a/lib/crewai/src/crewai/llms/providers/anthropic/completion.py
+++ b/lib/crewai/src/crewai/llms/providers/anthropic/completion.py
@@ -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)
--- a/lib/crewai/src/crewai/llms/providers/bedrock/completion.py
+++ b/lib/crewai/src/crewai/llms/providers/bedrock/completion.py
@@ -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}
--- a/lib/crewai/src/crewai/llms/providers/openai/completion.py
+++ b/lib/crewai/src/crewai/llms/providers/openai/completion.py
@@ -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
--- a/lib/crewai/src/crewai/utilities/pydantic_schema_utils.py
+++ b/lib/crewai/src/crewai/utilities/pydantic_schema_utils.py
@@ -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],
    *,
--- a/uv.lock
+++ b/uv.lock
@@ -1374,7 +1374,7 @@ requires-dist = [
    { name = "tokenizers", specifier = ">=0.21,<1" },
    { name = "tomli", specifier = "~=2.0.2" },
    { name = "tomli-w", specifier = "~=1.1.0" },
-    { name = "uv", specifier = "~=0.9.13" },
+    { name = "uv", specifier = "~=0.11.6" },
    { name = "voyageai", marker = "extra == 'voyageai'", specifier = "~=0.3.5" },
 ]
 provides-extras = ["a2a", "anthropic", "aws", "azure-ai-inference", "bedrock", "docling", "embeddings", "file-processing", "google-genai", "litellm", "mem0", "openpyxl", "pandas", "qdrant", "qdrant-edge", "tools", "voyageai", "watson"]
@@ -8976,28 +8976,28 @@ wheels = [

 [[package]]
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+version = "0.11.6"
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