Agent/examples/find knowledge/run.py

"""
图片模态特征提取研究示例

使用 Agent 模式 + Skills，研究应该提取什么样的图片模态特征
"""

import argparse
import os
import sys
import select
import asyncio
from pathlib import Path

# Clash Verge TUN 模式兼容：禁止 httpx/urllib 自动检测系统 HTTP 代理
# os.environ.setdefault("no_proxy", "*")

# 添加项目根目录到 Python 路径
sys.path.insert(0, str(Path(__file__).parent.parent.parent))

from dotenv import load_dotenv
load_dotenv()

from agent.llm.prompts import SimplePrompt
from agent.core.runner import AgentRunner, RunConfig
from agent.trace import (
    FileSystemTraceStore,
    Trace,
    Message,
)
from agent.llm import create_openrouter_llm_call

# 导入自定义工具模块，触发 @tool 装饰器注册
sys.path.insert(0, str(Path(__file__).parent))
import tool  # noqa: E402


def check_stdin() -> str | None:
    """非阻塞检查 stdin 是否有输入"""
    ready, _, _ = select.select([sys.stdin], [], [], 0)
    if ready:
        line = sys.stdin.readline().strip().lower()
        if line in ('p', 'pause'):
            return 'pause'
        if line in ('q', 'quit'):
            return 'quit'
    return None


def _read_multiline() -> str:
    """读取多行输入，以连续两次回车（空行）结束"""
    print("\n请输入干预消息（连续输入两次回车结束）：")
    lines: list[str] = []
    blank_count = 0
    while True:
        line = input()
        if line == "":
            blank_count += 1
            if blank_count >= 2:
                break
            lines.append("")
        else:
            blank_count = 0
            lines.append(line)

    while lines and lines[-1] == "":
        lines.pop()
    return "\n".join(lines)


async def show_interactive_menu(
    runner: AgentRunner,
    trace_id: str,
    current_sequence: int,
    store: FileSystemTraceStore,
):
    """显示交互式菜单"""
    print("\n" + "=" * 60)
    print("  执行已暂停")
    print("=" * 60)
    print("请选择操作：")
    print("  1. 插入干预消息并继续")
    print("  2. 查看当前 GoalTree")
    print("  3. 继续执行")
    print("  4. 停止执行")
    print("=" * 60)

    while True:
        choice = input("请输入选项 (1-4): ").strip()

        if choice == "1":
            text = _read_multiline()
            if not text:
                print("未输入任何内容，取消操作")
                continue

            print(f"\n将插入干预消息并继续执行...")
            live_trace = await store.get_trace(trace_id)
            actual_sequence = live_trace.last_sequence if live_trace and live_trace.last_sequence else current_sequence
            return {
                "action": "continue",
                "messages": [{"role": "user", "content": text}],
                "after_sequence": actual_sequence,
            }

        elif choice == "2":
            goal_tree = await store.get_goal_tree(trace_id)
            if goal_tree and goal_tree.goals:
                print("\n当前 GoalTree:")
                print(goal_tree.to_prompt())
            else:
                print("\n当前没有 Goal")
            continue

        elif choice == "3":
            print("\n继续执行...")
            return {"action": "continue"}

        elif choice == "4":
            print("\n停止执行...")
            return {"action": "stop"}

        else:
            print("无效选项，请重新输入")


async def main():
    parser = argparse.ArgumentParser(description="图片模态特征提取研究")
    parser.add_argument(
        "--trace", type=str, default=None,
        help="已有的 Trace ID，用于恢复继续执行",
    )
    args = parser.parse_args()

    # 路径配置
    base_dir = Path(__file__).parent
    project_root = base_dir.parent.parent
    prompt_path = base_dir / "test.prompt"
    output_dir = base_dir / "output"
    output_dir.mkdir(exist_ok=True)

    # 确保 input 和 knowledge 目录存在
    input_dir = base_dir / "input"
    knowledge_dir = base_dir / "knowledge"
    input_dir.mkdir(exist_ok=True)
    knowledge_dir.mkdir(exist_ok=True)

    print("=" * 60)
    print("图片模态特征提取研究 (Agent 模式)")
    print("=" * 60)
    print()
    print("💡 交互提示：")
    print("   - 执行过程中输入 'p' 或 'pause' 暂停并进入交互模式")
    print("   - 执行过程中输入 'q' 或 'quit' 停止执行")
    print("=" * 60)
    print()

    # 加载 prompt
    print("1. 加载 prompt 配置...")
    prompt = SimplePrompt(prompt_path)

    # 构建消息
    print("2. 构建任务消息...")
    messages = prompt.build_messages()

    # 创建 Agent Runner
    print("3. 创建 Agent Runner...")
    model_name = prompt.config.get('model', 'anthropic/claude-sonnet-4.6')
    print(f"   - 模型: {model_name}")

    store = FileSystemTraceStore(base_path=".trace")
    runner = AgentRunner(
        trace_store=store,
        llm_call=create_openrouter_llm_call(model=model_name),
        skills_dir=None,
        debug=True
    )

    # 判断是新建还是恢复
    resume_trace_id = args.trace
    if resume_trace_id:
        existing_trace = await store.get_trace(resume_trace_id)
        if not existing_trace:
            print(f"\n错误: Trace 不存在: {resume_trace_id}")
            sys.exit(1)
        print(f"4. 恢复已有 Trace: {resume_trace_id[:8]}...")
        print(f"   - 状态: {existing_trace.status}")
        print(f"   - 消息数: {existing_trace.total_messages}")
    else:
        print(f"4. 启动新 Agent 模式...")

    print()

    final_response = ""
    current_trace_id = resume_trace_id
    current_sequence = 0
    should_exit = False

    try:
        model_name = prompt.config.get('model', 'anthropic/claude-sonnet-4.6')

        if resume_trace_id:
            initial_messages = None
            config = RunConfig(
                model=model_name,
                temperature=float(prompt.config.get('temperature', 0.3)),
                max_iterations=1000,
                trace_id=resume_trace_id,
                enable_thinking=prompt.config.get('enable_thinking', False),
                thinking_budget_tokens=prompt.config.get('thinking_budget_tokens', 10000),
            )
        else:
            initial_messages = messages
            config = RunConfig(
                model=model_name,
                temperature=float(prompt.config.get('temperature', 0.3)),
                max_iterations=1000,
                name="图片模态特征提取研究",
                enable_thinking=prompt.config.get('enable_thinking', False),
                thinking_budget_tokens=prompt.config.get('thinking_budget_tokens', 10000),
            )

        while not should_exit:
            if current_trace_id:
                config.trace_id = current_trace_id

            final_response = ""

            # 检查 trace 状态
            if current_trace_id and initial_messages is None:
                check_trace = await store.get_trace(current_trace_id)
                if check_trace and check_trace.status in ("completed", "failed"):
                    if check_trace.status == "completed":
                        print(f"\n[Trace] ✅ 已完成")
                        print(f"  - Total messages: {check_trace.total_messages}")
                        print(f"  - Total cost: ${check_trace.total_cost:.4f}")
                    else:
                        print(f"\n[Trace] ❌ 已失败: {check_trace.error_message}")
                    current_sequence = check_trace.head_sequence

                    menu_result = await show_interactive_menu(
                        runner, current_trace_id, current_sequence, store
                    )

                    if menu_result["action"] == "stop":
                        break
                    elif menu_result["action"] == "continue":
                        new_messages = menu_result.get("messages", [])
                        if new_messages:
                            initial_messages = new_messages
                            config.after_sequence = menu_result.get("after_sequence")
                        else:
                            initial_messages = []
                            config.after_sequence = None
                        continue
                    break

                initial_messages = []

            print(f"{'▶️ 开始执行...' if not current_trace_id else '▶️ 继续执行...'}")

            # 执行 Agent
            paused = False
            try:
                async for item in runner.run(messages=initial_messages, config=config):
                    # 检查用户中断
                    cmd = check_stdin()
                    if cmd == 'pause':
                        print("\n⏸️ 正在暂停执行...")
                        if current_trace_id:
                            await runner.stop(current_trace_id)
                        await asyncio.sleep(0.5)

                        menu_result = await show_interactive_menu(
                            runner, current_trace_id, current_sequence, store
                        )

                        if menu_result["action"] == "stop":
                            should_exit = True
                            paused = True
                            break
                        elif menu_result["action"] == "continue":
                            new_messages = menu_result.get("messages", [])
                            if new_messages:
                                initial_messages = new_messages
                                after_seq = menu_result.get("after_sequence")
                                if after_seq is not None:
                                    config.after_sequence = after_seq
                                paused = True
                                break
                            else:
                                initial_messages = []
                                config.after_sequence = None
                                paused = True
                                break

                    elif cmd == 'quit':
                        print("\n🛑 用户请求停止...")
                        if current_trace_id:
                            await runner.stop(current_trace_id)
                        should_exit = True
                        break

                    # 处理 Trace 对象
                    if isinstance(item, Trace):
                        current_trace_id = item.trace_id
                        if item.status == "running":
                            print(f"[Trace] 开始: {item.trace_id[:8]}...")
                        elif item.status == "completed":
                            print(f"\n[Trace] ✅ 完成")
                            print(f"  - Total messages: {item.total_messages}")
                            print(f"  - Total tokens: {item.total_tokens}")
                            print(f"  - Total cost: ${item.total_cost:.4f}")
                        elif item.status == "failed":
                            print(f"\n[Trace] ❌ 失败: {item.error_message}")
                        elif item.status == "stopped":
                            print(f"\n[Trace] ⏸️ 已停止")

                    # 处理 Message 对象
                    elif isinstance(item, Message):
                        current_sequence = item.sequence

                        if item.role == "assistant":
                            content = item.content
                            if isinstance(content, dict):
                                text = content.get("text", "")
                                tool_calls = content.get("tool_calls")

                                if text and not tool_calls:
                                    final_response = text
                                    print(f"\n[Response] Agent 回复：")
                                    print(text)
                                elif text:
                                    preview = text[:150] + "..." if len(text) > 150 else text
                                    print(f"[Assistant] {preview}")

                                if tool_calls:
                                    for tc in tool_calls:
                                        tool_name = tc.get("function", {}).get("name", "unknown")
                                        print(f"[Tool Call] 🛠️  {tool_name}")

                        elif item.role == "tool":
                            content = item.content
                            if isinstance(content, dict):
                                tool_name = content.get("tool_name", "unknown")
                                print(f"[Tool Result] ✅ {tool_name}")
                            if item.description:
                                desc = item.description[:80] if len(item.description) > 80 else item.description
                                print(f"  {desc}...")

            except Exception as e:
                print(f"\n执行出错: {e}")
                import traceback
                traceback.print_exc()

            if paused:
                if should_exit:
                    break
                continue

            if should_exit:
                break

            # Runner 退出后显示交互菜单
            if current_trace_id:
                menu_result = await show_interactive_menu(
                    runner, current_trace_id, current_sequence, store
                )

                if menu_result["action"] == "stop":
                    break
                elif menu_result["action"] == "continue":
                    new_messages = menu_result.get("messages", [])
                    if new_messages:
                        initial_messages = new_messages
                        config.after_sequence = menu_result.get("after_sequence")
                    else:
                        initial_messages = []
                        config.after_sequence = None
                    continue
            break

    except KeyboardInterrupt:
        print("\n\n用户中断 (Ctrl+C)")
        if current_trace_id:
            await runner.stop(current_trace_id)

    # 输出结果
    if final_response:
        print()
        print("=" * 60)
        print("Agent 响应:")
        print("=" * 60)
        print(final_response)
        print("=" * 60)
        print()

        # 保存结果
        output_file = output_dir / "result.txt"
        with open(output_file, 'w', encoding='utf-8') as f:
            f.write(final_response)

        print(f"✓ 结果已保存到: {output_file}")
        print()

    # 可视化提示
    if current_trace_id:
        print("=" * 60)
        print("可视化 Step Tree:")
        print("=" * 60)
        print("1. 启动 API Server:")
        print("   python3 api_server.py")
        print()
        print("2. 浏览器访问:")
        print("   http://localhost:8000/api/traces")
        print()
        print(f"3. Trace ID: {current_trace_id}")
        print("=" * 60)


if __name__ == "__main__":
    asyncio.run(main())