feat(v2/anthropic): implement provider with mode registry integration

Author: jxnl

instructor/providers/anthropic/client.py

@@ -69,9 +69,15 @@ def from_anthropic(
     warnings.warn(
         "from_anthropic() is deprecated and will be removed in v2.0. "
         "Use instructor.v2.from_anthropic() with Mode instead:\n"
+<<<<<<< HEAD
         "  from instructor.v2.providers.anthropic import from_anthropic\n"
         "  from instructor import Mode\n"
         "  client = from_anthropic(anthropic_client, mode=Mode.TOOLS)\n"
+=======
+        "  from instructor.v2 import from_anthropic\n"
+        "  from instructor import Mode\n"
+        "  client = from_anthropic(anthropic_client, Mode.ANTHROPIC_TOOLS)\n"
+>>>>>>> 13857221 (feat(v2/anthropic): implement provider with mode registry integration)
         "Or use from_provider() which automatically routes to v2:\n"
         "  client = instructor.from_provider('anthropic/claude-3-sonnet')",
         DeprecationWarning,

instructor/v2/providers/anthropic/handlers.py

@@ -191,6 +191,7 @@ def prepare_request(
     ) -> tuple[type[BaseModel] | None, dict[str, Any]]:
         """Prepare request kwargs for TOOLS mode.
 
+<<<<<<< HEAD
         Supports:
         - Regular single tool use (single model)
         - Parallel tool calling (Iterable[Union[Model1, Model2, ...]])
@@ -200,16 +201,21 @@ def prepare_request(
         If thinking is enabled, automatically adjusts tool_choice to "auto"
         (required by API constraint).
 
+=======
+>>>>>>> 13857221 (feat(v2/anthropic): implement provider with mode registry integration)
         Args:
             response_model: Pydantic model to extract (or None)
             kwargs: Original request kwargs
 
         Returns:
             Tuple of (response_model, modified_kwargs)
         """
+<<<<<<< HEAD
         from collections.abc import Iterable
         from typing import get_origin
 
+=======
+>>>>>>> 13857221 (feat(v2/anthropic): implement provider with mode registry integration)
         new_kwargs = kwargs.copy()
 
         # Extract and combine system messages BEFORE serializing message content
@@ -235,6 +241,7 @@ def prepare_request(
             # Just return with processed messages and extracted system
             return None, new_kwargs
 
+<<<<<<< HEAD
         # Detect if this is a parallel tools request (Iterable[Union[...]])
         is_parallel = False
         if get_origin(response_model) is Iterable:
@@ -283,6 +290,15 @@ def prepare_request(
                     "type": "tool",
                     "name": response_model.__name__,
                 }
+=======
+        # Generate tool schema
+        tool_descriptions = generate_anthropic_schema(response_model)
+        new_kwargs["tools"] = [tool_descriptions]
+        new_kwargs["tool_choice"] = {
+            "type": "tool",
+            "name": response_model.__name__,
+        }
+>>>>>>> 13857221 (feat(v2/anthropic): implement provider with mode registry integration)
 
         return response_model, new_kwargs
 
@@ -358,6 +374,7 @@ def parse_response(
         response_model: type[BaseModel],
         validation_context: dict[str, Any] | None = None,
         strict: bool | None = None,
+<<<<<<< HEAD
     ) -> BaseModel | Any:
         """Parse TOOLS mode response.
 
@@ -366,26 +383,39 @@ def parse_response(
         - Parallel tool use (returns generator of model instances)
         - Extended thinking responses (filters out thinking blocks)
 
+=======
+    ) -> BaseModel:
+        """Parse TOOLS mode response.
+
+>>>>>>> 13857221 (feat(v2/anthropic): implement provider with mode registry integration)
         Args:
             response: Anthropic API response
             response_model: Pydantic model to validate against
             validation_context: Optional context for validation
             strict: Optional strict validation mode
 
         Returns:
+<<<<<<< HEAD
             Validated Pydantic model instance or generator of instances for parallel
+=======
+            Validated Pydantic model instance
+>>>>>>> 13857221 (feat(v2/anthropic): implement provider with mode registry integration)
 
         Raises:
             IncompleteOutputException: If response hit max_tokens
             ValidationError: If response doesn't match model
         """
         from anthropic.types import Message
+<<<<<<< HEAD
         from collections.abc import Iterable
         from typing import get_origin
+=======
+>>>>>>> 13857221 (feat(v2/anthropic): implement provider with mode registry integration)
 
         if isinstance(response, Message) and response.stop_reason == "max_tokens":
             raise IncompleteOutputException(last_completion=response)
 
+<<<<<<< HEAD
         # Check if this is a parallel response (Iterable[Union[...]])
         is_parallel = get_origin(response_model) is Iterable
 
@@ -463,6 +493,27 @@ def prepare_request(
         Mode.warn_anthropic_reasoning_tools_deprecation()
         # Delegate to parent handler
         return super().prepare_request(response_model, kwargs)
+=======
+        # Extract tool calls
+        tool_calls = [
+            json.dumps(c.input) for c in response.content if c.type == "tool_use"
+        ]
+
+        # Validate exactly one tool call
+        tool_calls_validator = TypeAdapter(
+            Annotated[list[Any], Field(min_length=1, max_length=1)]
+        )
+        tool_call = tool_calls_validator.validate_python(tool_calls)[0]
+
+        parsed = response_model.model_validate_json(
+            tool_call, context=validation_context, strict=strict
+        )
+
+        # Attach raw response for access via create_with_completion
+        parsed._raw_response = response  # type: ignore
+
+        return parsed
+>>>>>>> 13857221 (feat(v2/anthropic): implement provider with mode registry integration)
 
 
 @register_mode_handler(Provider.ANTHROPIC, Mode.JSON)

tests/v2/test_anthropic_integration.py

@@ -92,15 +92,20 @@ def test_query_anthropic_modes():
 
     assert Mode.TOOLS in modes
     assert Mode.JSON in modes
+<<<<<<< HEAD
     assert Mode.ANTHROPIC_REASONING_TOOLS in modes
     assert len(modes) == 3  # TOOLS, JSON, and ANTHROPIC_REASONING_TOOLS
+=======
+    assert len(modes) == 2  # Only TOOLS and JSON for now
+>>>>>>> 13857221 (feat(v2/anthropic): implement provider with mode registry integration)
 
 
 def test_query_tools_providers():
     """Test querying v2 registry for TOOLS mode providers."""
     providers = mode_registry.get_providers_for_mode(Mode.TOOLS)
 
     assert Provider.ANTHROPIC in providers
+<<<<<<< HEAD
 
 
 def test_anthropic_reasoning_tools_mode_registered():
@@ -197,3 +202,5 @@ def test_tools_mode_respects_user_tool_choice():
 
     # Should respect user's tool_choice
     assert result["tool_choice"]["type"] == "auto"
+=======
+>>>>>>> 13857221 (feat(v2/anthropic): implement provider with mode registry integration)

tests/v2/test_routing.py

@@ -40,7 +40,11 @@ def test_from_provider_anthropic_async():
 
 
 def test_old_from_anthropic_deprecation_warning():
+<<<<<<< HEAD
     """Test that old from_anthropic() emits deprecation warning with correct v2 example."""
+=======
+    """Test that old from_anthropic() emits deprecation warning."""
+>>>>>>> 13857221 (feat(v2/anthropic): implement provider with mode registry integration)
     import anthropic
     from instructor import from_anthropic
 
@@ -55,10 +59,13 @@ def test_old_from_anthropic_deprecation_warning():
         assert issubclass(w[0].category, DeprecationWarning)
         assert "deprecated" in str(w[0].message).lower()
         assert "v2" in str(w[0].message)
+<<<<<<< HEAD
         # Verify the warning shows correct v2 Mode enum (TOOLS not ANTHROPIC_TOOLS)
         assert "Mode.TOOLS" in str(w[0].message)
         # Verify it mentions the correct v2 import path
         assert "instructor.v2.providers.anthropic" in str(w[0].message)
+=======
+>>>>>>> 13857221 (feat(v2/anthropic): implement provider with mode registry integration)
 
 
 @pytest.mark.skip(reason="Requires Anthropic API key")