update

app/ui/streamlit_app.py

@@ -1,7 +1,6 @@
 """Streamlit UI scaffold for the investment assistant."""
 from __future__ import annotations
 
-import json
 import sys
 from dataclasses import asdict
 from datetime import date, timedelta
@@ -219,10 +218,10 @@ def render_settings() -> None:
 
     if model_options:
         options_with_custom = model_options + [custom_model_label]
-        if primary.model in model_options:
+        if primary.provider == selected_provider and primary.model in model_options:
             model_index = options_with_custom.index(primary.model)
         else:
-            model_index = len(options_with_custom) - 1
+            model_index = 0
         selected_model_option = st.selectbox(
             "LLM 模型",
             options_with_custom,
@@ -232,17 +231,17 @@ def render_settings() -> None:
         if selected_model_option == custom_model_label:
             custom_model_value = st.text_input(
                 "自定义模型名称",
-                value=primary.model if primary.model not in model_options else "",
+                value="" if primary.provider != selected_provider or primary.model in model_options else primary.model,
             )
+            chosen_model = custom_model_value.strip() or default_model_hint
         else:
-            custom_model_value = selected_model_option
+            chosen_model = selected_model_option
     else:
-        custom_model_value = st.text_input(
+        chosen_model = st.text_input(
             "LLM 模型",
             value=primary.model or default_model_hint,
             help="未预设该 Provider 的模型列表，请手动填写",
-        )
+        ).strip() or default_model_hint
-        selected_model_option = custom_model_label
     default_base_hint = DEFAULT_LLM_BASE_URLS.get(selected_provider, "")
     provider_default_temp = float(provider_info.get("temperature", 0.2))
     provider_default_timeout = int(provider_info.get("timeout", 30.0))
@@ -257,11 +256,16 @@ def render_settings() -> None:
         timeout_value = provider_default_timeout
 
     llm_base = st.text_input(
-        "LLM Base URL (可选)",
+        "LLM Base URL",
         value=base_value,
         help=f"默认推荐：{default_base_hint or '按供应商要求填写'}",
     )
-    llm_api_key = st.text_input("LLM API Key (OpenAI 类需要)", value=primary.api_key or "", type="password")
+    llm_api_key = st.text_input(
+        "LLM API Key",
+        value=primary.api_key or "",
+        type="password",
+        help="点击右侧小图标可查看当前 Key，该值会写入 config.json（已被 gitignore 排除）",
+    )
     llm_temperature = st.slider(
         "LLM 温度",
         min_value=0.0,
@@ -292,68 +296,104 @@ def render_settings() -> None:
         format="%d",
     )
 
-    ensemble_display = []
+    existing_api_keys = {ep.provider: ep.api_key or None for ep in llm_cfg.ensemble}
-    for endpoint in llm_cfg.ensemble:
+
-        data = asdict(endpoint)
+    ensemble_rows = [
-        if data.get("api_key"):
+        {
-            data["api_key"] = ""
+            "provider": ep.provider,
-        ensemble_display.append(data)
+            "model": ep.model,
-    ensemble_text = st.text_area(
+            "base_url": ep.base_url or "",
-        "LLM 集群配置 (JSON 数组)",
+            "api_key": ep.api_key or "",
-        value=json.dumps(ensemble_display or [], ensure_ascii=False, indent=2),
+            "temperature": float(ep.temperature),
-        height=220,
+            "timeout": float(ep.timeout),
+        }
+        for ep in llm_cfg.ensemble
+    ]
+    if not ensemble_rows:
+        ensemble_rows = [
+            {
+                "provider": "",
+                "model": "",
+                "base_url": "",
+                "api_key": "",
+                "temperature": provider_default_temp,
+                "timeout": provider_default_timeout,
+            }
+        ]
+
+    ensemble_rows = st.data_editor(
+        ensemble_rows,
+        num_rows="dynamic",
+        key="llm_ensemble_editor",
+        column_config={
+            "provider": st.column_config.SelectboxColumn(
+                "Provider",
+                options=sorted(DEFAULT_LLM_MODEL_OPTIONS.keys()),
+                help="选择 LLM 供应商"
+            ),
+            "model": st.column_config.TextColumn("模型", help="留空时使用该 Provider 的默认模型"),
+            "base_url": st.column_config.TextColumn("Base URL", help="留空时使用默认地址"),
+            "api_key": st.column_config.TextColumn("API Key", help="留空表示使用环境变量或不配置"),
+            "temperature": st.column_config.NumberColumn("温度", min_value=0.0, max_value=2.0, step=0.05),
+            "timeout": st.column_config.NumberColumn("超时(秒)", min_value=5.0, max_value=120.0, step=5.0),
+        },
+        hide_index=True,
+        use_container_width=True,
     )
+    if hasattr(ensemble_rows, "to_dict"):
+        ensemble_rows = ensemble_rows.to_dict("records")
 
     if st.button("保存 LLM 设置"):
-        original_provider = primary.provider
-        original_model = primary.model
         primary.provider = selected_provider
-        if model_options:
+        primary.model = chosen_model
-            if selected_model_option == custom_model_label:
+        primary.base_url = llm_base.strip() or DEFAULT_LLM_BASE_URLS.get(selected_provider)
-                model_input = custom_model_value.strip()
-                primary.model = model_input or DEFAULT_LLM_MODELS.get(
-                    selected_provider, DEFAULT_LLM_MODELS["ollama"]
-                )
-            else:
-                primary.model = selected_model_option
-        else:
-            primary.model = custom_model_value.strip() or DEFAULT_LLM_MODELS.get(
-                selected_provider, DEFAULT_LLM_MODELS["ollama"]
-            )
-        primary.base_url = llm_base.strip() or None
         primary.temperature = llm_temperature
         primary.timeout = llm_timeout
         api_key_value = llm_api_key.strip()
-        primary.api_key = api_key_value or None
+        if api_key_value:
+            primary.api_key = api_key_value
 
-        try:
+        new_ensemble: List[LLMEndpoint] = []
-            parsed = json.loads(ensemble_text or "[]")
+        for row in ensemble_rows:
-            if not isinstance(parsed, list):
+            provider = (row.get("provider") or "").strip().lower()
-                raise ValueError("ensemble 配置必须是数组")
+            if not provider:
-        except Exception as exc:  # noqa: BLE001
+                continue
-            LOGGER.exception("解析 LLM 集群配置失败", extra=LOG_EXTRA)
+            provider_defaults = DEFAULT_LLM_MODEL_OPTIONS.get(provider, {})
-            st.error(f"LLM 集群配置解析失败：{exc}")
+            default_model = DEFAULT_LLM_MODELS.get(provider, DEFAULT_LLM_MODELS["ollama"])
-        else:
+            default_base = DEFAULT_LLM_BASE_URLS.get(provider)
-            new_ensemble: List[LLMEndpoint] = []
+            temp_default = float(provider_defaults.get("temperature", 0.2))
-            invalid = False
+            timeout_default = float(provider_defaults.get("timeout", 30.0))
-            for item in parsed:
+
-                if not isinstance(item, dict):
+            model_val = (row.get("model") or "").strip() or default_model
-                    st.error("LLM 集群配置中的每个元素都必须是对象")
+            base_val = (row.get("base_url") or "").strip() or default_base
-                    invalid = True
+            api_raw = (row.get("api_key") or "").strip()
-                    break
+            api_value = None
-                fields = {key: item.get(key) for key in ("provider", "model", "base_url", "api_key", "temperature", "timeout")}
+            if api_raw and api_raw != "***":
-                endpoint = LLMEndpoint(**{k: v for k, v in fields.items() if v not in (None, "")})
+                api_value = api_raw
-                if not endpoint.provider:
+            else:
-                    endpoint.provider = "ollama"
+                existing = existing_api_keys.get(provider)
-                new_ensemble.append(endpoint)
+                if existing:
-            if not invalid:
+                    api_value = existing
-                llm_cfg.ensemble = new_ensemble
+
-                llm_cfg.strategy = selected_strategy
+            temp_val = row.get("temperature")
-                llm_cfg.majority_threshold = int(majority_threshold)
+            timeout_val = row.get("timeout")
-                save_config()
+            endpoint = LLMEndpoint(
-                LOGGER.info("LLM 配置已更新：%s", llm_config_snapshot(), extra=LOG_EXTRA)
+                provider=provider,
-                st.success("LLM 设置已保存，仅在当前会话生效。")
+                model=model_val,
-                st.json(llm_config_snapshot())
+                base_url=base_val,
+                api_key=api_value,
+                temperature=float(temp_val) if temp_val is not None else temp_default,
+                timeout=float(timeout_val) if timeout_val is not None else timeout_default,
+            )
+            new_ensemble.append(endpoint)
+
+        llm_cfg.ensemble = new_ensemble
+        llm_cfg.strategy = selected_strategy
+        llm_cfg.majority_threshold = int(majority_threshold)
+        save_config()
+        LOGGER.info("LLM 配置已更新：%s", llm_config_snapshot(), extra=LOG_EXTRA)
+        st.success("LLM 设置已保存，仅在当前会话生效。")
+        st.json(llm_config_snapshot())
 
 
 def render_tests() -> None: