core/agent: route OpenAI provider through Responses API

ResponsesChatClient adapts chat-shaped agent history/tools to POST /responses; compat and DeepSeek unchanged.
2026-07-23 05:55:16 +08:00 · 2026-07-15 20:59:47 +08:00
parent 38edc09854
commit 5dd102a016
9 changed files with 594 additions and 6 deletions
@@ -0,0 +1,157 @@
+from __future__ import annotations
+
+import msgspec
+import pytest
+
+from plyngent.agent.responses_bridge import (
+    chat_messages_to_responses_input,
+    chat_param_to_responses_kwargs,
+    response_to_assistant_message,
+    response_to_chat_completion,
+    tool_items_to_response_tools,
+)
+from plyngent.agent.responses_client import ResponsesChatClient
+from plyngent.lmproto.openai.model import Response, ResponsesCreateParam
+from plyngent.lmproto.openai_compatible.model import (
+    AssistantChatMessage,
+    AssistantFunctionTool,
+    AssistantFunctionToolCall,
+    ChatCompletionsParam,
+    SystemChatMessage,
+    ToolChatMessage,
+    ToolFunction,
+    ToolFunctionItem,
+    UserChatMessage,
+)
+
+
+def test_tool_items_to_response_tools() -> None:
+    items = [
+        ToolFunctionItem(
+            function=ToolFunction(
+                name="read_file",
+                description="Read a file",
+                parameters={"type": "object", "properties": {"path": {"type": "string"}}},
+            )
+        )
+    ]
+    tools = tool_items_to_response_tools(items)
+    assert len(tools) == 1
+    assert tools[0].name == "read_file"
+
+
+def test_chat_messages_to_input_and_instructions() -> 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"),
+    ]
+    instructions, items = chat_messages_to_responses_input(messages)
+    assert instructions == "You are helpful."
+    assert len(items) == 3  # user, function_call, function_call_output
+
+
+def test_response_to_assistant_with_tools() -> None:
+    raw = {
+        "id": "resp_1",
+        "object": "response",
+        "created_at": 1,
+        "model": "gpt-test",
+        "status": "completed",
+        "output": [
+            {
+                "id": "msg_1",
+                "type": "message",
+                "role": "assistant",
+                "status": "completed",
+                "content": [{"type": "output_text", "text": "done", "annotations": []}],
+            },
+            {
+                "type": "function_call",
+                "call_id": "call_9",
+                "name": "add",
+                "arguments": '{"a":1}',
+                "status": "completed",
+            },
+        ],
+        "usage": {"input_tokens": 10, "output_tokens": 5, "total_tokens": 15},
+    }
+    response = msgspec.convert(raw, Response)
+    from msgspec import UNSET
+
+    assistant = response_to_assistant_message(response)
+    assert assistant.content == "done"
+    assert assistant.tool_calls is not UNSET
+    assert isinstance(assistant.tool_calls, list)
+    call0 = assistant.tool_calls[0]
+    assert isinstance(call0, AssistantFunctionToolCall)
+    assert call0.id == "call_9"
+    assert call0.function.name == "add"
+    completion = response_to_chat_completion(response)
+    assert completion.choices[0].message.content == "done"
+    assert isinstance(completion.usage, dict)
+    assert completion.usage["input_tokens"] == 10
+
+
+def test_chat_param_to_responses_kwargs() -> None:
+    param = ChatCompletionsParam(
+        model="gpt-test",
+        messages=[SystemChatMessage(content="sys"), UserChatMessage(content="hi")],
+        tools=[ToolFunctionItem(function=ToolFunction(name="t", parameters={"type": "object"}))],
+        temperature=0.2,
+    )
+    kwargs = chat_param_to_responses_kwargs(param)
+    assert kwargs["model"] == "gpt-test"
+    assert kwargs["instructions"] == "sys"
+    assert kwargs["store"] is False
+    assert kwargs["temperature"] == 0.2
+    assert len(kwargs["tools"]) == 1
+
+
+@pytest.mark.asyncio
+async def test_responses_chat_client_non_stream(monkeypatch: pytest.MonkeyPatch) -> None:
+    from plyngent.lmproto.openai.client import OpenAIClient
+    from plyngent.lmproto.openai_compatible.config import OpenAIConfig
+
+    platform = OpenAIClient(OpenAIConfig(access_key_or_token="sk", base_url="https://example/v1"))
+
+    body = {
+        "id": "resp_x",
+        "object": "response",
+        "created_at": 1,
+        "model": "gpt-test",
+        "status": "completed",
+        "output": [
+            {
+                "id": "msg_1",
+                "type": "message",
+                "role": "assistant",
+                "status": "completed",
+                "content": [{"type": "output_text", "text": "hello", "annotations": []}],
+            }
+        ],
+        "usage": {"input_tokens": 3, "output_tokens": 1, "total_tokens": 4},
+    }
+
+    async def fake_responses(param: ResponsesCreateParam, *, stream: bool = False):
+        assert stream is False
+        assert param.model == "gpt-test"
+        assert param.store is False
+        return msgspec.convert(body, Response)
+
+    monkeypatch.setattr(platform, "responses", fake_responses)
+    client = ResponsesChatClient(platform)
+    result = await client.chat_completions(
+        ChatCompletionsParam(model="gpt-test", messages=[UserChatMessage(content="hi")]),
+        stream=False,
+    )
+    assert result.choices[0].message.content == "hello"