diary-news/backend/app/api/admin_llm.py

"""Admin LLM 设置(仅 owner)。

- GET /admin/llm-settings  — 读当前设置(单行)
- PUT /admin/llm-settings  — 更新(可只传部分字段)
- POST /admin/llm-settings/reset  — 恢复默认提示词
- POST /admin/llm-settings/test   — 测一次连通性(发个最小 chat 请求)
- POST /admin/llm-enrich/{article_id}  — 手动触发某篇的 LLM 增强
"""
from __future__ import annotations

import logging
from typing import Any

from fastapi import APIRouter, Depends, HTTPException, status
from pydantic import BaseModel
from sqlalchemy import select

from app.core.deps import require_owner
from app.database import AsyncSessionLocal
from app.models.article import Article
from app.models.llm_setting import LlmSetting
from app.schemas.llm import LlmSettingOut, LlmSettingUpdate, get_default_prompts
from app.services.llm.client import LlmClient

logger = logging.getLogger("news.admin_llm")
router = APIRouter(prefix="/admin/llm", tags=["admin-llm"], dependencies=[Depends(require_owner)])


@router.get("/settings", response_model=LlmSettingOut)
async def get_settings():
    async with AsyncSessionLocal() as session:
        row = (await session.execute(select(LlmSetting).where(LlmSetting.id == 1))).scalar_one_or_none()
        if row is None:
            # 返回默认值(不写库)
            defaults = get_default_prompts()
            return LlmSettingOut(
                format_prompt=defaults["format_prompt"],
                classify_prompt=defaults["classify_prompt"],
                commentary_prompt=defaults["commentary_prompt"],
                image_prompt_template=defaults["image_prompt_template"],
                blocklist_tags=[],
                meituan_api_key_set=False,
            )
        return LlmSettingOut.from_row(row)


@router.put("/settings", response_model=LlmSettingOut)
async def update_settings(body: LlmSettingUpdate):
    async with AsyncSessionLocal() as session:
        row = (await session.execute(select(LlmSetting).where(LlmSetting.id == 1))).scalar_one_or_none()
        if row is None:
            row = LlmSetting(id=1, **get_default_prompts())
            session.add(row)
            await session.flush()
        # 只更新传入的字段
        update_data = body.model_dump(exclude_unset=True)
        for k, v in update_data.items():
            setattr(row, k, v)
        await session.commit()
        await session.refresh(row)
        return LlmSettingOut.from_row(row)


class ResetResponse(BaseModel):
    reset: bool
    detail: str = ""


@router.post("/settings/reset", response_model=ResetResponse)
async def reset_settings():
    """恢复默认提示词。"""
    async with AsyncSessionLocal() as session:
        row = (await session.execute(select(LlmSetting).where(LlmSetting.id == 1))).scalar_one_or_none()
        defaults = get_default_prompts()
        if row is None:
            row = LlmSetting(id=1, **defaults)
            session.add(row)
        else:
            row.format_prompt = defaults["format_prompt"]
            row.classify_prompt = defaults["classify_prompt"]
            row.commentary_prompt = defaults["commentary_prompt"]
            row.image_prompt_template = defaults["image_prompt_template"]
        await session.commit()
    return ResetResponse(reset=True, detail="已恢复默认提示词")


class TestResponse(BaseModel):
    ok: bool
    detail: str = ""
    configured: bool


@router.post("/settings/test", response_model=TestResponse)
async def test_connection():
    """最小测试:发一个 'hi' chat 请求,确认 key + 端点通。

    优先用 llm_settings 表里的 agnes_api_key / agnes_base_url_override,
    都没有再 fallback 到 .env 里的 agnes_api_key / agnes_base_url。
    """
    from app.services.llm.providers import get_angel_client

    async with AsyncSessionLocal() as session:
        row = (await session.execute(select(LlmSetting).where(LlmSetting.id == 1))).scalar_one_or_none()
        if row is None:
            return TestResponse(ok=False, configured=False, detail="LLM 设置未初始化")
    # 用工厂:DB key 优先,.env 兜底
    client = get_angel_client(row)
    if not client.is_configured():
        return TestResponse(
            ok=False, configured=False,
            detail="Angel api_key 未配置(请在设置页填 key,或在 .env 配 AGNES_API_KEY)",
        )
    try:
        reply = await client.chat(
            system="你是测试助手,只用 1 个词回答 OK 或 FAIL。",
            user="ping",
            temperature=0.0,
            max_tokens=10,
        )
        return TestResponse(ok=True, configured=True, detail=f"reply={reply[:50]!r}")
    except Exception as e:
        return TestResponse(ok=False, configured=True, detail=f"{type(e).__name__}: {e}")


@router.post("/settings/test-meituan", response_model=TestResponse)
async def test_meituan_connection():
    """最小测试:发一个 'hi' chat 请求,确认美团大模型 LongCat 端点通。"""
    from app.services.llm.providers import get_meituan_client

    async with AsyncSessionLocal() as session:
        row = (await session.execute(select(LlmSetting).where(LlmSetting.id == 1))).scalar_one_or_none()
        if row is None:
            return TestResponse(ok=False, configured=False, detail="美团 provider 未配置(api_key 空)")
    client = get_meituan_client(row)
    if client is None:
        return TestResponse(ok=False, configured=False, detail="美团 MEITUAN_API_KEY 未配置")
    try:
        reply = await client.chat(
            system="你是测试助手,只用 1 个词回答 OK 或 FAIL。",
            user="ping",
            temperature=0.0,
            max_tokens=10,
        )
        return TestResponse(ok=True, configured=True, detail=f"reply={reply[:50]!r}")
    except Exception as e:
        return TestResponse(ok=False, configured=True, detail=f"{type(e).__name__}: {e}")


class EnrichTriggerResponse(BaseModel):
    triggered: bool
    detail: str = ""
    results: dict[str, str] | None = None


@router.post("/enrich/{article_id}", response_model=EnrichTriggerResponse)
async def trigger_enrich(article_id: int):
    """手动触发某篇的 4 项 LLM 增强(同步等待,不会丢在后台)。"""
    from app.services.llm.enrichment import enrich_article

    async with AsyncSessionLocal() as session:
        row = (await session.execute(select(Article).where(Article.id == article_id))).scalar_one_or_none()
        if not row:
            raise HTTPException(status.HTTP_404_NOT_FOUND, "Article not found")
    try:
        results = await enrich_article(article_id)
        return EnrichTriggerResponse(triggered=True, detail=f"done for {article_id}", results=results)
    except Exception as e:
        logger.exception("manual enrich failed for %s", article_id)
        raise HTTPException(status.HTTP_500_INTERNAL_SERVER_ERROR, f"{type(e).__name__}: {e}")