126 lines
4.3 KiB
Python
126 lines
4.3 KiB
Python
from __future__ import annotations
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import argparse
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from pathlib import Path
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from agent import CoreAgent
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from core_agent.config import apply_compat_env_aliases, build_core_agent_config, load_core_agent_env, require_model_config
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from providers.openai_compatible import OpenAICompatibleProvider
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from providers.rule_based import RuleBasedMeetingProvider
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from tools.default_tools import build_default_registry
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class TerminalRenderer:
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def __init__(self, assistant_name: str) -> None:
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self.assistant_name = assistant_name
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def render_event(self, event) -> None:
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if event.type == "round_start":
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print(f"\n[step {event.iteration}/{event.max_iterations}]", end="")
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elif event.type == "tool_call":
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print(f"\n[tool] {event.tool_name} {event.tool_args}")
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elif event.type == "tool_result":
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print(f"[tool-result] {_compact(event.tool_result)}")
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elif event.type == "final":
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print(f"\n{self.assistant_name}> {event.final_response}")
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def build_parser() -> argparse.ArgumentParser:
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parser = argparse.ArgumentParser(description="Meeting knowledge agent CLI.")
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parser.add_argument("--data-dir", default="data", help="台账和结构化数据保存目录。")
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parser.add_argument("--once", default="", help="只执行一条消息，适合测试。")
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parser.add_argument("--offline", action="store_true", help="只用于本地演示：强制使用离线规则 provider，不调用大模型。")
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parser.add_argument("--list-models", action="store_true", help="列出当前 OpenAI-compatible 服务暴露的模型名。")
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return parser
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def main() -> None:
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args = build_parser().parse_args()
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workspace = Path.cwd()
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load_core_agent_env(workspace)
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apply_compat_env_aliases()
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config = build_core_agent_config()
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if args.list_models:
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_list_models(config)
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return
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try:
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provider = _build_provider(config, force_offline=args.offline)
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except RuntimeError as exc:
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print(f"配置错误：{exc}")
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return
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registry = build_default_registry(workspace / args.data_dir)
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agent = CoreAgent(
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provider=provider,
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workspace=workspace,
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skill_dirs=[workspace / "skills"],
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tool_registry=registry,
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max_iterations=config.max_iterations,
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)
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session = agent.new_session(session_id="cli_default")
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renderer = TerminalRenderer(config.agent_name)
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if args.once:
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for event in session.stream_ask(args.once):
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renderer.render_event(event)
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return
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print("Meeting Knowledge Interactive Agent")
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print(r"示例：导入 D:\github_project\my_code\meeting_agent\examples\huiyi.txt 到知识库 合川分公司")
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print("示例：专线护航还有哪些待办？知识库 合川分公司")
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print("输入 exit / quit 退出。")
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while True:
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try:
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user_message = input("\n你> ").strip()
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except (EOFError, KeyboardInterrupt):
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print()
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break
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if user_message.lower() in {"exit", "quit", "q"}:
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break
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if not user_message:
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continue
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for event in session.stream_ask(user_message):
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renderer.render_event(event)
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def _build_provider(config, *, force_offline: bool):
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if force_offline:
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return RuleBasedMeetingProvider()
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require_model_config(config)
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return OpenAICompatibleProvider(
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model=config.model,
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api_key=config.api_key,
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base_url=config.base_url,
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timeout=config.timeout,
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temperature=config.temperature,
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)
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def _list_models(config) -> None:
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from openai import OpenAI
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if not config.api_key or not config.base_url:
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print("配置错误：列出模型需要 OPENAI_API_KEY 和 OPENAI_BASE_URL。")
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return
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try:
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client = OpenAI(api_key=config.api_key, base_url=config.base_url, timeout=config.timeout)
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models = client.models.list()
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except Exception as exc:
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print(f"获取模型列表失败：{exc}")
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return
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print(f"OPENAI_BASE_URL={config.base_url}")
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print("可用模型：")
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for model in models.data:
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print(f"- {model.id}")
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def _compact(text: str, limit: int = 240) -> str:
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text = " ".join(text.split())
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return text if len(text) <= limit else text[:limit] + "..."
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if __name__ == "__main__":
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main()
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