120 lines
3.7 KiB
Python
120 lines
3.7 KiB
Python
"""LLM 调用共享工具（OpenAI 兼容 API / Cursor SDK）。"""
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from __future__ import annotations
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import json
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import logging
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import os
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import re
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from typing import Any
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import certifi
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import httpx
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from daily.config import ROOT, env, env_int
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logger = logging.getLogger(__name__)
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_JSON_BLOCK = re.compile(r"```(?:json)?\s*([\s\S]*?)```", re.IGNORECASE)
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def extract_json_object(text: str) -> dict[str, Any]:
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text = text.strip()
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if not text:
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return {}
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try:
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data = json.loads(text)
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return data if isinstance(data, dict) else {}
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except json.JSONDecodeError:
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pass
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match = _JSON_BLOCK.search(text)
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if match:
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try:
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data = json.loads(match.group(1).strip())
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return data if isinstance(data, dict) else {}
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except json.JSONDecodeError:
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pass
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start, end = text.find("{"), text.rfind("}")
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if start >= 0 and end > start:
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try:
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data = json.loads(text[start : end + 1])
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return data if isinstance(data, dict) else {}
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except json.JSONDecodeError:
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pass
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return {}
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def _openai_chat(system: str, user: str) -> str:
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api_key = (env("DAILY_LLM_API_KEY") or env("OPENAI_API_KEY") or "").strip()
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if not api_key:
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return ""
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base = (env("DAILY_LLM_API_BASE") or env("OPENAI_API_BASE") or "https://api.openai.com/v1").rstrip("/")
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model = env("DAILY_LLM_MODEL") or env("OPENAI_MODEL") or "gpt-4o-mini"
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timeout = env_int("DAILY_LLM_TIMEOUT", 120)
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payload = {
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"model": model,
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"temperature": 0.2,
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"messages": [
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{"role": "system", "content": system},
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{"role": "user", "content": user},
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],
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}
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with httpx.Client(timeout=timeout, verify=certifi.where()) as client:
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resp = client.post(
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f"{base}/chat/completions",
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headers={"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"},
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json=payload,
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)
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resp.raise_for_status()
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data = resp.json()
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return str(data["choices"][0]["message"]["content"] or "").strip()
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def _cursor_chat(system: str, user: str) -> str:
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api_key = (env("CURSOR_API_KEY") or "").strip()
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if not api_key:
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return ""
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from cursor_sdk import Agent, AgentOptions, CursorAgentError, LocalAgentOptions
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from daily.config import ensure_bot_on_path
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ensure_bot_on_path()
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try:
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from bridge_manager import warm_cursor_bridge
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except ImportError:
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warm_cursor_bridge = lambda: None # noqa: E731
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cwd = env("DAILY_CURSOR_CWD") or str(ROOT)
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# bridge_manager 读 bot env_config 的 CURSOR_CWD，早报侧须先对齐工作目录
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os.environ["CURSOR_CWD"] = cwd
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warm_cursor_bridge()
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model = env("CURSOR_MODEL") or "composer-2.5"
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prompt = f"{system}\n\n{user}"
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try:
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result = Agent.prompt(
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prompt,
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AgentOptions(
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api_key=api_key,
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model=model,
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local=LocalAgentOptions(cwd=cwd),
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),
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)
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except CursorAgentError as exc:
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raise RuntimeError(f"LLM 调用失败：{exc.message}") from exc
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if result.status == "error":
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raise RuntimeError(f"LLM 调用失败：{result.result or '未知错误'}")
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return (result.result or "").strip()
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def llm_chat(system: str, user: str) -> str:
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"""优先 OpenAI 兼容 API，否则 Cursor SDK。"""
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if env("DAILY_LLM_API_KEY") or env("OPENAI_API_KEY"):
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return _openai_chat(system, user)
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if env("CURSOR_API_KEY"):
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return _cursor_chat(system, user)
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return ""
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def has_llm_configured() -> bool:
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return bool(env("DAILY_LLM_API_KEY") or env("OPENAI_API_KEY") or env("CURSOR_API_KEY"))
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