llmproxy/test_content_with_tool_calls.py

#!/usr/bin/env python3
"""
测试 chat 接口同时返回文本内容和 tool_calls
"""
import sys
import os
import json

sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))

from app.response_parser import ResponseParser
from app.models import ResponseMessage, ToolCall, ToolCallFunction

def test_content_and_tool_calls():
    """测试同时返回文本内容和 tool_calls 的各种场景"""

    parser = ResponseParser()

    print("=" * 70)
    print("测试：同时返回文本内容和 tool_calls")
    print("=" * 70)

    # 场景 1: 文本在前 + tool_calls
    print("\n场景 1: 先说话，再调用工具")
    print("-" * 70)

    text1 = """好的，我来帮你查询北京的天气情况。

<invoke>{"name": "get_weather", "arguments": {"location": "北京", "unit": "celsius"}}</invoke>"""

    result1 = parser.parse(text1)

    print(f"输入文本:\n{text1}\n")
    print(f"解析结果:")
    print(f"  - content: {result1.content}")
    print(f"  - tool_calls: {len(result1.tool_calls) if result1.tool_calls else 0} 个")
    if result1.tool_calls:
        for tc in result1.tool_calls:
            print(f"    * {tc.function.name}: {tc.function.arguments}")

    # 验证
    assert result1.content is not None, "Content should not be None"
    assert result1.tool_calls is not None, "Tool calls should not be None"
    assert len(result1.tool_calls) == 1, "Should have 1 tool call"
    assert "北京" in result1.content or "查询" in result1.content, "Content should contain original text"

    print("  ✓ 场景 1 通过")

    # 场景 2: tool_calls + 文本在后
    print("\n场景 2: 先调用工具，再说话")
    print("-" * 70)

    text2 = """<invoke>{"name": "search", "arguments": {"query": "今天天气"}}</invoke>

我已经帮你查询了，请稍等片刻。"""

    result2 = parser.parse(text2)

    print(f"输入文本:\n{text2}\n")
    print(f"解析结果:")
    print(f"  - content: {result2.content}")
    print(f"  - tool_calls: {len(result2.tool_calls) if result2.tool_calls else 0} 个")
    if result2.tool_calls:
        for tc in result2.tool_calls:
            print(f"    * {tc.function.name}: {tc.function.arguments}")

    assert result2.content is not None
    assert result2.tool_calls is not None
    assert "稍等" in result2.content or "查询" in result2.content

    print("  ✓ 场景 2 通过")

    # 场景 3: 文本 - tool_calls - 文本
    print("\n场景 3: 文本 - 工具调用 - 文本（三明治结构）")
    print("-" * 70)

    text3 = """让我先查一下北京的温度。

<invoke>{"name": "get_weather", "arguments": {"location": "北京"}}</invoke>

查到了，我再查一下上海的。

<invoke>{"name": "get_weather", "arguments": {"location": "上海"}}</invoke>

好了，两个城市都查询完毕。"""

    result3 = parser.parse(text3)

    print(f"输入文本:\n{text3}\n")
    print(f"解析结果:")
    print(f"  - content: {result3.content}")
    print(f"  - tool_calls: {len(result3.tool_calls) if result3.tool_calls else 0} 个")
    if result3.tool_calls:
        for i, tc in enumerate(result3.tool_calls, 1):
            print(f"    * {tc.function.name}: {tc.function.arguments}")

    assert result3.content is not None
    assert result3.tool_calls is not None
    assert len(result3.tool_calls) == 2
    assert "先查一下" in result3.content
    assert "查询完毕" in result3.content

    print("  ✓ 场景 3 通过")

    # 场景 4: 测试 ResponseMessage 序列化
    print("\n场景 4: 验证 ResponseMessage 可以正确序列化为 JSON")
    print("-" * 70)

    msg = ResponseMessage(
        role="assistant",
        content="好的，我来帮你查询。",
        tool_calls=[
            ToolCall(
                id="call_123",
                type="function",
                function=ToolCallFunction(
                    name="get_weather",
                    arguments=json.dumps({"location": "北京"})
                )
            )
        ]
    )

    json_str = msg.model_dump_json(indent=2)
    print("序列化的 JSON 响应:")
    print(json_str)

    parsed_back = ResponseMessage.model_validate_json(json_str)
    assert parsed_back.content == msg.content
    assert parsed_back.tool_calls is not None
    assert len(parsed_back.tool_calls) == 1

    print("  ✓ 场景 4 通过 - JSON 序列化/反序列化正常")

    print("\n" + "=" * 70)
    print("所有测试通过! ✓")
    print("=" * 70)

    print("\n总结：")
    print("✓ chat 接口支持同时返回文本内容和 tool_calls")
    print("✓ content 和 tool_calls 可以同时存在")
    print("✓ 支持文本在前、在后、或前后都有文本的场景")
    print("✓ 支持多个 tool_calls 与文本内容混合")
    print("✓ JSON 序列化/反序列化正常")

    print("\n实际应用场景示例：")
    print("""
    Assistant: "好的，我来帮你查询一下。"
    [调用 get_weather 工具]
    [收到工具结果]
    Assistant: "北京今天晴天，气温 25°C。"
    """)

if __name__ == "__main__":
    test_content_and_tool_calls()