refactor: React 前端重构，新旧平台合并为莞易学

src/study_tool/settings_store.py

@@ -0,0 +1,90 @@
+"""系统设置（大模型 + 学习方式）读写。"""
+from study_tool import store
+from study_tool.webapp import app
+
+from study_tool.config import *
+from study_tool.models import *
+from study_tool.runtime import log
+
+# ------------------------------------------------------------------ settings
+
+SETTINGS_NAME = "llm"
+DEFAULT_LLM = {
+    "base_url": "https://api.openai.com/v1",
+    "api_key": "",
+    "model": "gpt-4o-mini",
+    "temperature": 0.2,
+    "timeout": 120,
+    "prompt": "",
+}
+# 学习方式：fast = 只调 study/log 接口，不开浏览器；normal = 真播视频（可多路并发）
+DEFAULT_STUDY = {
+    "mode": "fast",
+    "parallel": 2,
+}
+DEFAULT_ANSWER_PROMPT = (
+    "你是考试答题助手。根据题干和选项判断正确答案。\n"
+    "单选题返回一个选项字母；多选题返回多个字母，用 # 连接（如 A#C）；判断题只返回 A 或 B（A=正确，B=错误）。\n"
+    "只输出 JSON：{\"answers\":{\"题号\":\"答案\"}}，不要输出解释或多余文字。"
+)
+TYPE_LABEL = {"01": "单选", "02": "多选", "03": "判断", "04": "问答"}
+
+
+def load_settings():
+    data = store.get_setting(SETTINGS_NAME) or {}
+    llm = dict(DEFAULT_LLM)
+    study = dict(DEFAULT_STUDY)
+    if isinstance(data, dict):
+        raw = data.get("llm")
+        if isinstance(raw, dict):
+            llm.update({k: v for k, v in raw.items() if k in DEFAULT_LLM and v is not None})
+        st = data.get("study")
+        if isinstance(st, dict):
+            study.update({k: v for k, v in st.items() if v is not None})
+    study["mode"] = study.get("mode") if study.get("mode") in ("fast", "normal") else "fast"
+    try:
+        study["parallel"] = max(1, min(int(study.get("parallel") or 2), 5))
+    except (TypeError, ValueError):
+        study["parallel"] = 2
+    return {"llm": llm, "study": study}
+
+
+def save_settings(data):
+    store.set_setting(SETTINGS_NAME, {"llm": data.get("llm") or {},
+                                      "study": data.get("study") or {}})
+
+
+@app.get("/api/settings")
+def api_get_settings():
+    cfg = load_settings()
+    llm = cfg["llm"]
+    key = llm.get("api_key") or ""
+    out = dict(llm)
+    out["api_key"] = ""
+    out["has_key"] = bool(key)
+    out["key_hint"] = (key[:4] + "…" + key[-4:]) if len(key) > 10 else ("已设置" if key else "")
+    return {"ok": True, "llm": out, "study": cfg["study"]}
+
+
+@app.post("/api/settings")
+def api_set_settings(b: LlmCfgIn):
+    cur = load_settings()
+    llm = cur["llm"]
+    if b.base_url.strip():
+        llm["base_url"] = b.base_url.strip()
+    if b.api_key.strip():          # 留空 = 保留原 key，前端不回显明文
+        llm["api_key"] = b.api_key.strip()
+    if b.model.strip():
+        llm["model"] = b.model.strip()
+    llm["temperature"] = max(0.0, min(2.0, float(b.temperature or 0)))
+    llm["timeout"] = max(10, min(600, int(b.timeout or 120)))
+    llm["prompt"] = b.prompt or ""
+    if b.study_mode in ("fast", "normal"):      # 空串 = 不改
+        cur["study"]["mode"] = b.study_mode
+    if b.study_parallel:                        # 0 = 不改
+        cur["study"]["parallel"] = max(1, min(int(b.study_parallel), 5))
+    save_settings(cur)
+    log("system", "设置已更新：模型 %s（%s），学习方式 %s/%s 路" % (
+        cur["llm"]["model"], cur["llm"]["base_url"],
+        cur["study"]["mode"], cur["study"]["parallel"]))
+    return {"ok": True, "study": cur["study"]}