feat: AI 生成增强 - 风格/长度/评分/历史/复制
- 后端 prompt 支持风格选择（6种）和字数范围 - 后端 AI 输出改为 JSON 格式，含评分和推荐理由 - GenerateRequest/Response schema 新增 style/length/score/reason 字段 - 前端新增风格选择、字数范围控件 - 前端新增随机选题按钮 - 前端新增复制内容功能 - 前端新增生成历史记录（会话级 20 条） - 结果卡片展示 AI 评分和推荐理由
This commit is contained in:
bwstudio
+85
-15
@@ -1,7 +1,8 @@
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"""智能笑话生成器 API"""
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import json
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from datetime import datetime
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from fastapi import APIRouter, Depends, HTTPException
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from fastapi import APIRouter, Depends, HTTPException, Query
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from openai import OpenAI
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from sqlalchemy.orm import Session
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@@ -21,17 +22,43 @@ GENERATION_PROMPT = """你是一位幽默大师，专门创作轻松搞笑的短
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要求：
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1. 根据场景和关键词创作一条原创笑话
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2. 笑话要有反转或意外结局
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3. 语言简洁，30-150字
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4. 直接输出笑话内容，不需要解释
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3. 语言风格：{style}
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4. 字数要求：{length_requirement}
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5. 直接输出笑话内容，不需要解释
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格式：
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标题：xxx
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内容：xxx
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"""
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请严格按照以下 JSON 格式输出，不要加任何额外说明：
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{{
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"title": "笑话标题",
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"content": "笑话正文",
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"score": 8,
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"reason": "这个笑话巧妙结合了场景和关键词，结尾有反转"
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}}
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score 是 1-10 的整数评分，reason 是用一句话说明亮点。"""
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STYLE_MAP = {
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"cold": "冷幽默 / 无厘头",
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"warm": "温馨幽默 / 暖心搞笑",
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"twist": "反转 / 神转折",
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"pun": "谐音梗 / 文字游戏",
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"sketch": "段子 / 吐槽调侃",
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"irony": "讽刺幽默 / 黑色幽默",
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}
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LENGTH_MAP = {
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"short": "30-80字，非常简短",
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"medium": "80-150字，正常长度",
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"long": "150-300字，可以描述一个小场景",
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}
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def _build_prompt(scenarios: list[str], keywords: list[str]) -> str:
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"""构建 AI prompt"""
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def _build_prompt(
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scenarios: list[str],
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keywords: list[str],
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style: str = "twist",
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length: str = "medium",
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) -> str:
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"""构建 AI prompt，支持风格和长度控制"""
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parts = []
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if scenarios:
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parts.append(f"场景：{', '.join(scenarios)}")
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@@ -39,7 +66,11 @@ def _build_prompt(scenarios: list[str], keywords: list[str]) -> str:
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parts.append(f"关键词：{', '.join(keywords)}")
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if not parts:
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parts.append("场景：日常生活的各种趣事（不指定具体场景）")
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return GENERATION_PROMPT.format(context="\n".join(parts))
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return GENERATION_PROMPT.format(
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context="\n".join(parts),
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style=STYLE_MAP.get(style, "反转 / 神转折"),
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length_requirement=LENGTH_MAP.get(length, "80-150字，正常长度"),
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)
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@router.post("", response_model=GenerateResponse)
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@@ -47,11 +78,10 @@ def generate_joke(
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req: GenerateRequest,
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db: Session = Depends(get_db),
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):
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"""调用 AI 生成笑话"""
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"""调用 AI 生成笑话，支持风格和长度控制"""
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# 获取激活的 AI 配置
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setting = db.query(AiSetting).filter(AiSetting.is_active == True).first()
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if not setting:
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# 如果没有配置，尝试返回默认配置
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setting = db.query(AiSetting).first()
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if not setting or not setting.api_key:
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@@ -60,22 +90,62 @@ def generate_joke(
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# 调用 AI
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try:
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client = OpenAI(base_url=setting.api_base, api_key=setting.api_key)
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prompt = _build_prompt(req.scenarios, req.keywords)
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prompt = _build_prompt(req.scenarios, req.keywords, req.style, req.length)
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response = client.chat.completions.create(
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model=setting.model_name,
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messages=[{"role": "user", "content": prompt}],
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temperature=setting.temperature,
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temperature=req.temperature,
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max_tokens=setting.max_tokens,
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)
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raw = response.choices[0].message.content
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return _parse_response(raw)
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return _parse_json_response(raw)
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except json.JSONDecodeError:
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raise HTTPException(status_code=500, detail="AI 返回格式异常，请重新生成")
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"生成失败: {str(e)}")
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def _parse_json_response(raw: str | None) -> GenerateResponse:
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"""解析 AI 返回的 JSON 格式"""
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if not raw or not raw.strip():
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return GenerateResponse(title="生成的笑话", content="（内容生成失败，请重新生成）", score=0)
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# 尝试从 markdown 代码块中提取 JSON
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raw = raw.strip()
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if raw.startswith("```"):
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lines = raw.split("\n")
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# 去掉第一行 ```json 和最后一行 ```
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if len(lines) >= 3:
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raw = "\n".join(lines[1:-1]).strip()
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# 移除可能的尾部分号
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if raw.endswith(","):
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raw = raw[:-1]
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try:
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data = json.loads(raw)
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except json.JSONDecodeError:
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# 如果 JSON 解析失败，尝试查找花括号内的内容
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try:
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start = raw.index("{")
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end = raw.rindex("}") + 1
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raw = raw[start:end]
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data = json.loads(raw)
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except (ValueError, json.JSONDecodeError):
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return _parse_response(raw)
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return GenerateResponse(
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title=data.get("title", "生成的笑话"),
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content=data.get("content", ""),
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score=data.get("score", 0),
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reason=data.get("reason", ""),
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created_at=datetime.now(),
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)
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def _parse_response(raw: str | None) -> GenerateResponse:
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"""解析 AI 返回内容，提取标题和内容"""
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# 防御：处理空或 None 输入
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@@ -74,12 +74,18 @@ class GenerateRequest(BaseModel):
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"""笑话生成请求"""
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keywords: list[str] = []
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scenarios: list[str] = []
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style: str = "twist"
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length: str = "medium"
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temperature: float = 0.8
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class Config:
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json_schema_extra = {
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"example": {
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"keywords": ["加班"],
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"scenarios": ["职场"]
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"scenarios": ["职场"],
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"style": "twist",
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"length": "medium",
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"temperature": 0.8,
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}
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}
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@@ -88,6 +94,8 @@ class GenerateResponse(BaseModel):
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"""笑话生成响应"""
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title: str
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content: str
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score: int = 0
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reason: str = ""
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created_at: datetime | None = None
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class Config:
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