yumao
5742dc47ed
daily 自建 Cursor bridge；DAILY_LLM_PROVIDER 控制后端；config/feeds.yaml 与 sensitive_words 可配置。 Co-authored-by: Cursor <cursoragent@cursor.com>
122 lines
3.4 KiB
Python
122 lines
3.4 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 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 env, env_int
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from daily.cursor_client import cursor_chat
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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 _has_openai_configured() -> bool:
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return bool(env("DAILY_LLM_API_KEY") or env("OPENAI_API_KEY"))
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def _has_cursor_configured() -> bool:
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return bool(env("CURSOR_API_KEY"))
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def llm_provider() -> str:
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raw = (env("DAILY_LLM_PROVIDER") or "auto").strip().lower()
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if raw in {"openai", "cursor"}:
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return raw
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return "auto"
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def resolve_llm_backend() -> str:
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"""返回 openai | cursor | 空字符串。"""
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provider = llm_provider()
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has_openai = _has_openai_configured()
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has_cursor = _has_cursor_configured()
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if provider == "openai":
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if has_openai:
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return "openai"
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return "cursor" if has_cursor else ""
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if provider == "cursor":
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if has_cursor:
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return "cursor"
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return "openai" if has_openai else ""
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agent_mode = (env("DAILY_REPORT_MODE") or "").strip().lower() == "agent"
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if agent_mode and has_cursor:
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return "cursor"
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if has_openai:
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return "openai"
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if has_cursor:
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return "cursor"
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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 llm_chat(system: str, user: str) -> str:
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backend = resolve_llm_backend()
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if backend == "openai":
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return _openai_chat(system, user)
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if backend == "cursor":
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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(resolve_llm_backend())
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