Initial commit: stock analysis backend and prototype UI.

Co-authored-by: Cursor <cursoragent@cursor.com>

backend/llm.py

@@ -0,0 +1,42 @@
+"""大模型客户端（OpenAI 兼容接口）。
+
+未配置 LLM_API_KEY 时 enabled() 返回 False，调用方应走规则降级。
+"""
+from __future__ import annotations
+
+import requests
+
+import config
+
+
+def enabled() -> bool:
+    return bool(config.LLM_API_KEY)
+
+
+def chat(messages, temperature: float = 0.5, max_tokens: int = 900) -> str:
+    """调用 chat/completions。失败抛异常，由上层捕获降级。"""
+    if not enabled():
+        raise RuntimeError("LLM 未配置")
+    url = config.LLM_BASE_URL.rstrip("/") + "/chat/completions"
+    headers = {"Authorization": f"Bearer {config.LLM_API_KEY}", "Content-Type": "application/json"}
+    payload = {"model": config.LLM_MODEL, "messages": messages,
+               "temperature": temperature, "max_tokens": max_tokens, "stream": False}
+    r = requests.post(url, json=payload, headers=headers, timeout=config.LLM_TIMEOUT)
+    r.raise_for_status()
+    data = r.json()
+    return data["choices"][0]["message"]["content"].strip()
+
+
+SYSTEM_PROMPT = (
+    "你是一名专业的A股市场分析师，擅长复盘、个股诊断与题材分析。"
+    "你的结论必须严格基于用户提供的结构化数据，不臆造未提供的数字。"
+    "语言简洁专业，使用中文。涉及操作建议时必须同时给出风险提示，"
+    "并说明这不构成投资建议。"
+)
+
+
+def ask(user_content: str, temperature: float = 0.5, max_tokens: int = 900) -> str:
+    return chat([
+        {"role": "system", "content": SYSTEM_PROMPT},
+        {"role": "user", "content": user_content},
+    ], temperature=temperature, max_tokens=max_tokens)