chore: import upstream snapshot with attribution

tests/processing/test_process_response.py

@@ -0,0 +1,157 @@
+from typing_extensions import TypedDict
+from pydantic import BaseModel
+from instructor.processing.response import handle_response_model
+from instructor.v2.core.response import _redact_kwargs
+from instructor.v2.providers.bedrock.handlers import (
+    _prepare_bedrock_converse_kwargs_internal,
+)
+
+
+def test_typed_dict_conversion() -> None:
+    class User(TypedDict):
+        name: str
+        age: int
+
+    _, user_tool_definition = handle_response_model(User)
+
+    class User(BaseModel):
+        name: str
+        age: int
+
+    _, pydantic_user_tool_definition = handle_response_model(User)
+    assert user_tool_definition == pydantic_user_tool_definition
+
+
+def test_redact_kwargs_hides_nested_sensitive_fields() -> None:
+    kwargs = {
+        "api_key": "top-level",
+        "headers": {
+            "Authorization": "Bearer secret",
+            "x-api-key": "nested secret",
+            "safe": "visible",
+        },
+        "messages": [{"token": "inner secret", "content": "hello"}],
+    }
+
+    assert _redact_kwargs(kwargs) == {
+        "api_key": "[redacted]",
+        "headers": {
+            "Authorization": "[redacted]",
+            "x-api-key": "[redacted]",
+            "safe": "visible",
+        },
+        "messages": [{"token": "[redacted]", "content": "hello"}],
+    }
+
+
+def test_openai_to_bedrock_conversion() -> None:
+    """OpenAI-style input should be fully converted to Bedrock format."""
+    call_kwargs = {
+        "model": "anthropic.claude-3-haiku-20240307-v1:0",
+        "messages": [
+            {"role": "system", "content": "You are a helpful assistant."},
+            {"role": "user", "content": "Extract: Jason is 22 years old"},
+            {"role": "assistant", "content": "Sure! Jason is 22."},
+        ],
+    }
+    result = _prepare_bedrock_converse_kwargs_internal(call_kwargs)
+    assert "model" not in result
+    assert result["modelId"] == "anthropic.claude-3-haiku-20240307-v1:0"
+    assert result["system"] == [{"text": "You are a helpful assistant."}]
+    assert len(result["messages"]) == 2
+    assert result["messages"][0]["role"] == "user"
+    assert result["messages"][0]["content"] == [
+        {"text": "Extract: Jason is 22 years old"}
+    ]
+    assert result["messages"][1]["role"] == "assistant"
+    assert result["messages"][1]["content"] == [{"text": "Sure! Jason is 22."}]
+
+
+def test_bedrock_native_preserved() -> None:
+    """Bedrock-native input should be preserved as-is."""
+    call_kwargs = {
+        "modelId": "anthropic.claude-3-haiku-20240307-v1:0",
+        "system": [{"text": "You are a helpful assistant."}],
+        "messages": [
+            {"role": "user", "content": [{"text": "Extract: Jason is 22 years old"}]},
+            {"role": "assistant", "content": [{"text": "Sure! Jason is 22."}]},
+        ],
+    }
+    result = _prepare_bedrock_converse_kwargs_internal(call_kwargs)
+    assert result["system"] == [{"text": "You are a helpful assistant."}]
+    assert len(result["messages"]) == 2
+    assert result["messages"][0]["content"] == [
+        {"text": "Extract: Jason is 22 years old"}
+    ]
+    assert result["messages"][1]["content"] == [{"text": "Sure! Jason is 22."}]
+
+
+def test_mixed_openai_and_bedrock() -> None:
+    """Mixed input: OpenAI-style is converted, Bedrock-native is preserved."""
+    call_kwargs = {
+        "modelId": "anthropic.claude-3-haiku-20240307-v1:0",
+        "system": [{"text": "You are a helpful assistant."}],
+        "messages": [
+            {
+                "role": "user",
+                "content": "Extract: Jason is 22 years old",
+            },  # OpenAI style
+            {
+                "role": "assistant",
+                "content": [{"text": "Sure! Jason is 22."}],
+            },  # Bedrock style
+        ],
+    }
+    result = _prepare_bedrock_converse_kwargs_internal(call_kwargs)
+    assert result["modelId"] == "anthropic.claude-3-haiku-20240307-v1:0"
+    assert result["system"] == [{"text": "You are a helpful assistant."}]
+    assert len(result["messages"]) == 2
+    # OpenAI-style user message converted
+    assert result["modelId"] == "anthropic.claude-3-haiku-20240307-v1:0"
+    assert result["messages"][0]["content"] == [
+        {"text": "Extract: Jason is 22 years old"}
+    ]
+    # Bedrock-style assistant message preserved
+    assert result["messages"][1]["content"] == [{"text": "Sure! Jason is 22."}]
+
+
+def test_bedrock_round_trip() -> None:
+    """Bedrock input should be unchanged after round-trip through the function."""
+    call_kwargs = {
+        "modelId": "anthropic.claude-3-haiku-20240307-v1:0",
+        "system": [{"text": "Bedrock system."}],
+        "messages": [
+            {"role": "user", "content": [{"text": "Bedrock user message."}]},
+        ],
+    }
+    import copy
+
+    original = copy.deepcopy(call_kwargs)
+    result = _prepare_bedrock_converse_kwargs_internal(call_kwargs)
+    assert result == original
+
+
+def test_empty_and_missing_content() -> None:
+    """Empty messages and missing content should be handled gracefully."""
+    # Empty messages
+    call_kwargs = {"messages": []}
+    result = _prepare_bedrock_converse_kwargs_internal(call_kwargs)
+    assert result["messages"] == []
+    # Message with no content
+    call_kwargs = {"messages": [{"role": "user"}]}
+    result = _prepare_bedrock_converse_kwargs_internal(call_kwargs)
+    assert result["messages"][0]["role"] == "user"
+    # Should not add a content key if not present
+    assert "content" not in result["messages"][0]
+
+
+def test_bedrock_invalid_content_format() -> None:
+    """Invalid content types should raise ValueError."""
+    call_kwargs = {
+        "messages": [{"role": "user", "content": 12345}]  # Invalid content type
+    }
+    try:
+        _prepare_bedrock_converse_kwargs_internal(call_kwargs)
+        raise AssertionError("Should have raised ValueError")
+    except ValueError as e:
+        assert "Unsupported message content type for Bedrock" in str(e)