core/agent: wire anthropic messages bridge and dispatch

tests/test_agent/test_messages_bridge.py

@@ -0,0 +1,200 @@
+"""Tests for Anthropic Messages chat ↔ native conversion."""
+
+from __future__ import annotations
+
+from msgspec import UNSET
+
+from plyngent.agent.messages_bridge import (
+    anthropic_response_to_assistant,
+    anthropic_response_to_chat_completion,
+    anthropic_stop_to_finish_reason,
+    anthropic_usage_to_dict,
+    chat_messages_to_anthropic,
+    chat_param_to_anthropic_param,
+    tool_items_to_anthropic_tools,
+)
+from plyngent.lmproto.anthropic.model import (
+    AnthropicAssistantMessage,
+    AnthropicMessageResponse,
+    AnthropicResponseText,
+    AnthropicResponseToolUse,
+    AnthropicToolResultContent,
+    AnthropicToolUseContent,
+    AnthropicUsage,
+    AnthropicUserMessage,
+)
+from plyngent.lmproto.openai_compatible.model import (
+    AssistantChatMessage,
+    AssistantFunctionTool,
+    AssistantFunctionToolCall,
+    ChatCompletionsParam,
+    DeveloperChatMessage,
+    SystemChatMessage,
+    ToolChatMessage,
+    ToolFunction,
+    ToolFunctionItem,
+    UserChatMessage,
+)
+
+
+def test_tool_items_to_anthropic_tools() -> None:
+    items = [
+        ToolFunctionItem(
+            function=ToolFunction(
+                name="read_file",
+                description="Read a file",
+                parameters={"type": "object", "properties": {"path": {"type": "string"}}},
+            )
+        )
+    ]
+    tools = tool_items_to_anthropic_tools(items)
+    assert len(tools) == 1
+    assert tools[0].name == "read_file"
+    assert tools[0].input_schema is not UNSET
+
+
+def test_chat_messages_system_and_tool_round() -> None:
+    messages = [
+        SystemChatMessage(content="You are helpful."),
+        UserChatMessage(content="hi"),
+        AssistantChatMessage(
+            content=None,
+            tool_calls=[
+                AssistantFunctionToolCall(
+                    id="call_1",
+                    function=AssistantFunctionTool(name="read_file", arguments='{"path":"a"}'),
+                )
+            ],
+        ),
+        ToolChatMessage(content="file body", tool_call_id="call_1"),
+    ]
+    system, items = chat_messages_to_anthropic(messages)
+    assert system == "You are helpful."
+    assert len(items) == 3
+    assert isinstance(items[0], AnthropicUserMessage)
+    assert items[0].content == "hi"
+    assert isinstance(items[1], AnthropicAssistantMessage)
+    assert isinstance(items[1].content, list)
+    assert any(isinstance(b, AnthropicToolUseContent) and b.id == "call_1" for b in items[1].content)
+    assert isinstance(items[2], AnthropicUserMessage)
+    assert isinstance(items[2].content, list)
+    assert isinstance(items[2].content[0], AnthropicToolResultContent)
+    assert items[2].content[0].tool_use_id == "call_1"
+    assert items[2].content[0].content == "file body"
+
+
+def test_developer_becomes_user_prefix() -> None:
+    system, items = chat_messages_to_anthropic(
+        [
+            SystemChatMessage(content="persona"),
+            UserChatMessage(content="go"),
+            DeveloperChatMessage(content="checkpoint"),
+        ]
+    )
+    assert system == "persona"
+    assert len(items) == 2
+    assert isinstance(items[1], AnthropicUserMessage)
+    assert items[1].content == "[developer] checkpoint"
+
+
+def test_merge_consecutive_tool_results() -> None:
+    messages = [
+        UserChatMessage(content="go"),
+        AssistantChatMessage(
+            content=None,
+            tool_calls=[
+                AssistantFunctionToolCall(
+                    id="c1",
+                    function=AssistantFunctionTool(name="a", arguments="{}"),
+                ),
+                AssistantFunctionToolCall(
+                    id="c2",
+                    function=AssistantFunctionTool(name="b", arguments="{}"),
+                ),
+            ],
+        ),
+        ToolChatMessage(content="r1", tool_call_id="c1"),
+        ToolChatMessage(content="r2", tool_call_id="c2"),
+    ]
+    _, items = chat_messages_to_anthropic(messages)
+    assert len(items) == 3  # user, assistant, one merged tool-result user
+    assert isinstance(items[2], AnthropicUserMessage)
+    assert isinstance(items[2].content, list)
+    assert len(items[2].content) == 2
+
+
+def test_anthropic_response_to_assistant_with_tools() -> None:
+    response = AnthropicMessageResponse(
+        id="msg_1",
+        model="claude-test",
+        stop_reason="tool_use",
+        content=[
+            AnthropicResponseText(text="calling"),
+            AnthropicResponseToolUse(id="tu_1", name="add", input={"a": 1, "b": 2}),
+        ],
+        usage=AnthropicUsage(input_tokens=12, output_tokens=4),
+    )
+    assistant = anthropic_response_to_assistant(response)
+    assert assistant.content == "calling"
+    assert assistant.tool_calls is not UNSET
+    assert len(assistant.tool_calls) == 1
+    call = assistant.tool_calls[0]
+    assert isinstance(call, AssistantFunctionToolCall)
+    assert call.id == "tu_1"
+    assert call.function.name == "add"
+    assert '"a":1' in call.function.arguments or '"a": 1' in call.function.arguments
+
+
+def test_anthropic_response_to_chat_completion_usage() -> None:
+    response = AnthropicMessageResponse(
+        id="msg_1",
+        model="claude-test",
+        stop_reason="end_turn",
+        content=[AnthropicResponseText(text="done")],
+        usage=AnthropicUsage(input_tokens=9, output_tokens=3),
+    )
+    chat = anthropic_response_to_chat_completion(response)
+    assert chat.choices[0].message.content == "done"
+    assert chat.choices[0].finish_reason == "stop"
+    assert chat.usage is not UNSET
+    assert chat.usage["prompt_tokens"] == 9
+    assert chat.usage["completion_tokens"] == 3
+
+
+def test_stop_reason_mapping() -> None:
+    assert anthropic_stop_to_finish_reason("end_turn", has_tool_calls=False) == "stop"
+    assert anthropic_stop_to_finish_reason("tool_use", has_tool_calls=True) == "tool_calls"
+    assert anthropic_stop_to_finish_reason("max_tokens", has_tool_calls=False) == "length"
+    assert anthropic_stop_to_finish_reason("refusal", has_tool_calls=False) == "content_filter"
+    assert anthropic_stop_to_finish_reason(None, has_tool_calls=True) == "tool_calls"
+
+
+def test_usage_to_dict() -> None:
+    assert anthropic_usage_to_dict(AnthropicUsage(input_tokens=1, output_tokens=2)) == {
+        "prompt_tokens": 1,
+        "completion_tokens": 2,
+        "total_tokens": 3,
+        "input_tokens": 1,
+        "output_tokens": 2,
+    }
+    assert anthropic_usage_to_dict(AnthropicUsage()) is None
+
+
+def test_chat_param_to_anthropic_param() -> None:
+    param = ChatCompletionsParam(
+        model="claude-test",
+        messages=[
+            SystemChatMessage(content="Be brief."),
+            UserChatMessage(content="hi"),
+        ],
+        tools=[ToolFunctionItem(function=ToolFunction(name="f", description="d", parameters={"type": "object"}))],
+        temperature=0.2,
+        max_completion_tokens=1024,
+    )
+    body = chat_param_to_anthropic_param(param)
+    assert body.model == "claude-test"
+    assert body.max_tokens == 1024
+    assert body.system == "Be brief."
+    assert body.tools is not UNSET
+    assert len(body.tools) == 1
+    assert body.temperature == 0.2