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198 lines
7.7 KiB
Python
198 lines
7.7 KiB
Python
"""实验 5-11:对话式界面定制 Agent。
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职责:接收一条自然语言 UI 定制需求(如"把发送按钮改成蓝色"),读取前端源码,
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调用 OpenAI 让模型定位并改写相应源文件(颜色 / 字体 / 文案 / 布局 / 组件)。
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设计要点
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--------
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- 只暴露少量"可定制文件"给模型(frontend/src 下的 App.jsx 与 theme.css),
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降低模型改错文件的概率,也让改动可控、可验证。
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- 通过 function calling 的 `apply_edits` 工具,让模型返回"要整体改写的文件全文"。
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相比零散的 search/replace,整文件改写对小文件更稳定、更少破坏语法。
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- 修改前先把原文件内容快照下来,改后可计算 diff、读回断言,并跑构建验证。
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环境变量:
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OPENAI_API_KEY (必填,本实验读取此项)
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OPENAI_BASE_URL (可选,切换到兼容 OpenAI 协议的服务端点)
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MODEL (可选,默认 gpt-5.6-luna)
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OPENROUTER_API_KEY(可选,无直连 key 时自动改走 OpenRouter 兜底)
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"""
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import os
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import json
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from pathlib import Path
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from openai import OpenAI
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try:
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from dotenv import load_dotenv
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load_dotenv()
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except Exception: # dotenv 是可选依赖
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pass
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# 可被 Agent 定制的前端源文件(相对 frontend/ 的路径)。
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EDITABLE_FILES = [
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"src/App.jsx",
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"src/theme.css",
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]
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OPENROUTER_BASE_URL = "https://openrouter.ai/api/v1"
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def map_model_to_openrouter(model: str) -> str:
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"""把直连模型名映射为 OpenRouter 上的 id(非可映射 id 统一兜底到当前廉价旗舰)。"""
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if not model or "/" in model:
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return model or "openai/gpt-5.6-luna"
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m = model.lower()
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if m.startswith(("gpt-", "o1", "o3", "o4")):
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return "openai/" + model
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if m.startswith("claude"):
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if "haiku" in m:
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return "anthropic/claude-haiku-4.5"
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if "sonnet" in m:
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return "anthropic/claude-sonnet-4.6"
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return "anthropic/claude-opus-4.8"
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if m.startswith("gemini"):
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return "google/" + model
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return "openai/gpt-5.6-luna"
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def build_client_and_model():
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model = os.getenv("MODEL", "gpt-5.6-luna")
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api_key = os.getenv("OPENAI_API_KEY")
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base_url = os.getenv("OPENAI_BASE_URL")
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orkey = os.getenv("OPENROUTER_API_KEY")
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# 通用 OpenRouter 兜底:无直连 key,或默认 gpt-5.x(直连需组织实名认证)时改走 OpenRouter。
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prefer_or = bool(orkey) and (model or "").lower().startswith("gpt-5")
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if prefer_or or (not api_key and orkey):
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api_key, base_url, model = orkey, OPENROUTER_BASE_URL, map_model_to_openrouter(model)
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if not api_key:
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raise SystemExit("未找到 OPENAI_API_KEY(或 OPENROUTER_API_KEY 兜底),请先在环境变量或 .env 中设置。")
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# timeout / max_retries:让偶发的网络/SSL 抖动自动重试,不至于整轮崩溃
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client_kwargs = {"api_key": api_key, "timeout": 60.0, "max_retries": 3}
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if base_url:
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client_kwargs["base_url"] = base_url
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client = OpenAI(**client_kwargs)
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return client, model
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APPLY_EDITS_TOOL = {
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"type": "function",
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"function": {
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"name": "apply_edits",
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"description": (
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"根据用户的界面定制需求,改写一个或多个前端源文件。"
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"只返回真正需要改动的文件;每个文件返回改写后的完整内容。"
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),
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"parameters": {
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"type": "object",
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"properties": {
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"summary": {
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"type": "string",
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"description": "用一句话说明本次改了什么(中文)。",
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},
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"files": {
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"type": "array",
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"description": "需要改写的文件列表。",
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"items": {
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"type": "object",
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"properties": {
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"path": {
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"type": "string",
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"description": "相对 frontend/ 的文件路径,"
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"必须是可编辑文件之一。",
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},
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"content": {
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"type": "string",
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"description": "改写后的文件完整内容。",
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},
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},
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"required": ["path", "content"],
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},
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},
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},
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"required": ["summary", "files"],
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},
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},
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}
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SYSTEM_PROMPT = """你是一个前端界面定制 Agent,负责把用户的自然语言 UI 需求落到 React(Vite) 源码上。
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规则:
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1. 只能修改用户提供的"可编辑文件",不要新增或删除文件。
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2. 优先做最小改动:改颜色/字体/间距等样式,改 theme.css;改文案/组件结构,改 App.jsx。
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3. 颜色请使用明确的 CSS 颜色值(如十六进制 #2563eb)。如果用户给了具体色值,就用它。
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4. 保持代码可编译:JSX/CSS 语法必须正确,不要破坏原有功能。
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5. 必须调用 apply_edits 工具返回结果,files 里给出改写后的完整文件内容。
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"""
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def read_editable_sources(frontend_dir: Path) -> dict:
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"""读取所有可编辑文件当前内容,返回 {相对路径: 内容}。"""
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sources = {}
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for rel in EDITABLE_FILES:
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p = frontend_dir / rel
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sources[rel] = p.read_text(encoding="utf-8")
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return sources
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def customize(client, model, frontend_dir: Path, requirement: str) -> dict:
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"""让模型针对一条自然语言需求改写源码,返回 apply_edits 的参数 dict。
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仅调用模型并解析工具参数,不落盘(写文件、验证在 demo.py 里做,便于展示 diff)。
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"""
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sources = read_editable_sources(frontend_dir)
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file_blocks = "\n\n".join(
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f"===== 文件: {rel} =====\n{content}" for rel, content in sources.items()
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)
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user_prompt = (
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f"可编辑文件当前内容如下:\n\n{file_blocks}\n\n"
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f"用户的定制需求:{requirement}\n\n"
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f"请调用 apply_edits 返回需要改写的文件全文。"
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)
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resp = client.chat.completions.create(
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model=model,
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messages=[
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{"role": "system", "content": SYSTEM_PROMPT},
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{"role": "user", "content": user_prompt},
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],
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tools=[APPLY_EDITS_TOOL],
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tool_choice={"type": "function", "function": {"name": "apply_edits"}},
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temperature=(1 if any(k in (model or "").lower()
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for k in ("gpt-5", "o1", "o3", "o4", "thinking", "reasoner", "kimi-k3"))
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else 0),
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)
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msg = resp.choices[0].message
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if not msg.tool_calls:
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raise RuntimeError("模型没有返回 apply_edits 工具调用。")
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raw_args = msg.tool_calls[0].function.arguments or "{}"
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try:
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args = json.loads(raw_args)
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except json.JSONDecodeError:
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# Tolerate bad apply_edits JSON; degrade to empty edits.
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args = {}
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# 安全校验:只允许改写白名单内的文件。
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# 要求每个文件项带有字符串 content:否则下游写盘循环会对
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# {"path": ...}(缺少 content)抛出 KeyError 而中断整个 demo。
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# 形状不合法的项直接丢弃(与非 dict 过滤一致);白名单校验仍会对
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# 带 content 但路径非法的项抛错。
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files = [
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f
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for f in (args.get("files") or [])
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if isinstance(f, dict) and isinstance(f.get("content"), str)
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]
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for f in files:
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path = f.get("path")
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if path not in EDITABLE_FILES:
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raise RuntimeError(f"模型试图修改非白名单文件:{path}")
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args["files"] = files
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return args
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