添加自动获取模型列表，目前仅支持适配了 OpenAI格式的供应商，更多供应商支持中……

server/routers/chat_router.py

@@ -203,6 +203,13 @@ async def get_chat_models(model_provider: str):
     model = select_model(model_provider=model_provider)
     return {"models": model.get_models()}
 
+@chat.post("/models/update")
+async def update_chat_models(model_provider: str, model_names: list[str]):
+    """更新指定模型提供商的模型列表"""
+    config.model_names[model_provider]["models"] = model_names
+    config._save_models_to_file()
+    return {"models": config.model_names[model_provider]["models"]}
+
 @chat.get("/tools")
 async def get_tools():
     """获取所有工具"""

src/config/__init__.py

@@ -4,13 +4,6 @@ import yaml
 from pathlib import Path
 from src.utils.logging_config import logger
 
-with open(Path("src/static/models.yaml"), 'r', encoding='utf-8') as f:
-    _models = yaml.safe_load(f)
-
-MODEL_NAMES = _models["MODEL_NAMES"]
-EMBED_MODEL_INFO = _models["EMBED_MODEL_INFO"]
-RERANKER_LIST = _models["RERANKER_LIST"]
-
 DEFAULT_MOCK_API = 'this_is_mock_api_key_in_frontend'
 
 class SimpleConfig(dict):
@@ -46,6 +39,8 @@ class Config(SimpleConfig):
         self.filename = str(Path("saves/config/base.yaml"))
         os.makedirs(os.path.dirname(self.filename), exist_ok=True)
 
+        self._update_models_from_file()
+
         ### >>> 默认配置
         self.add_item("stream", default=True, des="是否开启流式输出")
         # 功能选项
@@ -56,13 +51,13 @@ class Config(SimpleConfig):
         # 模型配置
         ## 注意这里是模型名，而不是具体的模型路径，默认使用 HuggingFace 的路径
         ## 如果需要自定义本地模型路径，则在 src/.env 中配置 MODEL_DIR
-        self.add_item("model_provider", default="siliconflow", des="模型提供商", choices=list(MODEL_NAMES.keys()))
+        self.add_item("model_provider", default="siliconflow", des="模型提供商", choices=list(self.model_names.keys()))
-        self.add_item("model_provider_lite", default="siliconflow", des="模型提供商（用于轻量任务）", choices=list(MODEL_NAMES.keys()))
+        self.add_item("model_provider_lite", default="siliconflow", des="模型提供商（用于轻量任务）", choices=list(self.model_names.keys()))
         self.add_item("model_name", default="Qwen/Qwen2.5-7B-Instruct", des="模型名称")
         self.add_item("model_name_lite", default="Qwen/Qwen2.5-7B-Instruct", des="模型名称（用于轻量任务）")
 
-        self.add_item("embed_model", default="siliconflow/BAAI/bge-m3", des="Embedding 模型", choices=list(EMBED_MODEL_INFO.keys()))
+        self.add_item("embed_model", default="siliconflow/BAAI/bge-m3", des="Embedding 模型", choices=list(self.embed_model_names.keys()))
-        self.add_item("reranker", default="siliconflow/BAAI/bge-reranker-v2-m3", des="Re-Ranker 模型", choices=list(RERANKER_LIST.keys()))
+        self.add_item("reranker", default="siliconflow/BAAI/bge-reranker-v2-m3", des="Re-Ranker 模型", choices=list(self.reranker_names.keys()))
         self.add_item("model_local_paths", default={}, des="本地模型路径")
         self.add_item("use_rewrite_query", default="off", des="重写查询", choices=["off", "on", "hyde"])
         self.add_item("device", default="cuda", des="运行本地模型的设备", choices=["cpu", "cuda"])
@@ -89,11 +84,40 @@ class Config(SimpleConfig):
         ]
         return {k: v for k, v in self.items() if k not in blocklist}
 
-    def handle_self(self):
+    def _update_models_from_file(self):
-        self.model_names = MODEL_NAMES
+        """
-        self.embed_model_names = EMBED_MODEL_INFO
+        从 models.yaml 和 models.private.yml 中更新 MODEL_NAMES
-        self.reranker_names = RERANKER_LIST
+        """
 
+        with open(Path("src/static/models.yaml"), 'r', encoding='utf-8') as f:
+            _models = yaml.safe_load(f)
+
+        # 尝试打开一个 models.private.yml 文件，用来覆盖 models.yaml 中的配置
+        try:
+            with open(Path("src/static/models.private.yml"), 'r', encoding='utf-8') as f:
+                _models_private = yaml.safe_load(f)
+        except FileNotFoundError:
+            _models_private = {}
+
+        _models = {**_models, **_models_private}
+
+        self.model_names = _models["MODEL_NAMES"]
+        self.embed_model_names = _models["EMBED_MODEL_INFO"]
+        self.reranker_names = _models["RERANKER_LIST"]
+
+    def _save_models_to_file(self):
+        _models = {
+            "MODEL_NAMES": self.model_names,
+            "EMBED_MODEL_INFO": self.embed_model_names,
+            "RERANKER_LIST": self.reranker_names,
+        }
+        with open(Path("src/static/models.private.yml"), 'w', encoding='utf-8') as f:
+            yaml.dump(_models, f, indent=2, allow_unicode=True)
+
+    def handle_self(self):
+        """
+        处理配置
+        """
         model_provider_info = self.model_names.get(self.model_provider, {})
         self.model_dir = os.environ.get("MODEL_DIR", "")
         logger.info(f"MODEL_DIR: {self.model_dir}; 如果是在 docker 中运行，会自动挂载 MODEL_DIR 到 /models 目录，请检查 docker compose 文件")

src/core/graphbase.py

@@ -141,8 +141,7 @@ class GraphDatabase:
                 """)
 
         # 判断模型名称是否匹配
-        from src.config import EMBED_MODEL_INFO
+        cur_embed_info = config.embed_model_names[config.embed_model]
-        cur_embed_info = EMBED_MODEL_INFO[config.embed_model]
         self.embed_model_name = self.embed_model_name or cur_embed_info.get('name')
         assert self.embed_model_name == cur_embed_info.get('name') or self.embed_model_name is None, \
             f"embed_model_name={self.embed_model_name}, {cur_embed_info.get('name')=}"

src/models/embedding.py

@@ -5,7 +5,6 @@ from FlagEmbedding import FlagModel
 from zhipuai import ZhipuAI
 
 from src import config
-from src.config import EMBED_MODEL_INFO
 from src.utils import hashstr, logger, get_docker_safe_url
 
 
@@ -17,9 +16,9 @@ class BaseEmbeddingModel:
             return self.dimension
 
         if hasattr("embed_model_fullname"):
-            return EMBED_MODEL_INFO[self.embed_model_fullname].get("dimension", None)
+            return config.embed_model_names[self.embed_model_fullname].get("dimension", None)
 
-        return EMBED_MODEL_INFO[self.model].get("dimension", None)
+        return config.embed_model_names[self.model].get("dimension", None)
 
     def encode(self, message):
         return self.predict(message)
@@ -54,7 +53,7 @@ class BaseEmbeddingModel:
 
 class LocalEmbeddingModel(FlagModel, BaseEmbeddingModel):
     def __init__(self, config, **kwargs):
-        info = EMBED_MODEL_INFO[config.embed_model]
+        info = config.embed_model_names[config.embed_model]
 
         self.model = config.model_local_paths.get(info["name"], info.get("local_path"))
         self.model = self.model or info["name"]
@@ -79,8 +78,8 @@ class ZhipuEmbedding(BaseEmbeddingModel):
 
     def __init__(self, config) -> None:
         self.config = config
-        self.model = EMBED_MODEL_INFO[config.embed_model]["name"]
+        self.model = config.embed_model_names[config.embed_model]["name"]
-        self.dimension = EMBED_MODEL_INFO[config.embed_model]["dimension"]
+        self.dimension = config.embed_model_names[config.embed_model]["dimension"]
         self.client = ZhipuAI(api_key=os.getenv("ZHIPUAI_API_KEY"))
         self.embed_model_fullname = config.embed_model
 
@@ -95,7 +94,7 @@ class ZhipuEmbedding(BaseEmbeddingModel):
 
 class OllamaEmbedding(BaseEmbeddingModel):
     def __init__(self, config) -> None:
-        self.info = EMBED_MODEL_INFO[config.embed_model]
+        self.info = config.embed_model_names[config.embed_model]
         self.model = self.info["name"]
         self.url = self.info.get("url", "http://localhost:11434/api/embed")
         self.url = get_docker_safe_url(self.url)
@@ -119,7 +118,7 @@ class OllamaEmbedding(BaseEmbeddingModel):
 class OtherEmbedding(BaseEmbeddingModel):
 
     def __init__(self, config) -> None:
-        self.info = EMBED_MODEL_INFO[config.embed_model]
+        self.info = config.embed_model_names[config.embed_model]
         self.embed_model_fullname = config.embed_model
         self.dimension = self.info.get("dimension", None)
         self.model = self.info["name"]
@@ -150,7 +149,7 @@ def get_embedding_model(config):
         return None
 
     provider, model_name = config.embed_model.split('/', 1)
-    assert config.embed_model in EMBED_MODEL_INFO.keys(), f"Unsupported embed model: {config.embed_model}, only support {EMBED_MODEL_INFO.keys()}"
+    assert config.embed_model in config.embed_model_names.keys(), f"Unsupported embed model: {config.embed_model}, only support {config.embed_model_names.keys()}"
     logger.debug(f"Loading embedding model {config.embed_model}")
     if provider == "local":
         model = LocalEmbeddingModel(config)

src/models/rerank_model.py

@@ -4,13 +4,13 @@ import requests
 import numpy as np
 from FlagEmbedding import FlagReranker
 
-from src.config import RERANKER_LIST
+from src import config
 from src.utils.logging_config import logger
 
 
 class LocalReranker(FlagReranker):
     def __init__(self, config, **kwargs):
-        model_info = RERANKER_LIST[config.reranker]
+        model_info = config.reranker_names[config.reranker]
         model_name_or_path = config.model_local_paths.get(model_info["name"], model_info.get("local_path"))
         model_name_or_path = model_name_or_path or model_info["name"]
         logger.info(f"Loading Reranker model {config.reranker} from {model_name_or_path}")
@@ -25,7 +25,7 @@ def sigmoid(x):
 class SilconFlowReranker():
     def __init__(self, config, **kwargs):
         self.url = "https://api.siliconflow.cn/v1/rerank"
-        self.model = RERANKER_LIST[config.reranker]["name"]
+        self.model = config.reranker_names[config.reranker]["name"]
 
         api_key = os.getenv("SILICONFLOW_API_KEY")
         assert api_key, "SILICONFLOW_API_KEY is required"
@@ -59,12 +59,12 @@ class SilconFlowReranker():
         }
 
 def get_reranker(config):
-    assert config.reranker in RERANKER_LIST.keys(), f"Unsupported Reranker: {config.reranker}, only support {RERANKER_LIST.keys()}"
+    assert config.reranker in config.reranker_names.keys(), f"Unsupported Reranker: {config.reranker}, only support {config.reranker_names.keys()}"
     provider, model_name = config.reranker.split('/', 1)
     if provider == "local":
         return LocalReranker(config)
     elif provider == "siliconflow":
         return SilconFlowReranker(config)
     else:
-        raise ValueError(f"Unsupported Reranker: {config.reranker}, only support {RERANKER_LIST.keys()}")
+        raise ValueError(f"Unsupported Reranker: {config.reranker}, only support {config.reranker_names.keys()}")
 

src/static/models.yaml

@@ -1,3 +1,13 @@
+####################################################
+#
+#  不要直接修改这个里面的文件，可能会有被覆盖的风险，
+#  建议 复制一份 在 models.private.yml 中修改，
+#  会自动加载
+#
+#####################################################
+
+
+
 MODEL_NAMES:
   openai:
     name: OpenAI

web/src/views/SettingView.vue

@@ -169,6 +169,14 @@
                 <InfoCircleOutlined />
               </a>
             </div>
+            <a-button
+              type="text"
+              class="config-button"
+              @click.stop="openProviderConfig(item)"
+              title="配置模型提供商"
+            >
+              <SettingOutlined />
+            </a-button>
             <a-button
               type="text"
               class="expand-button"
@@ -202,6 +210,14 @@
                 <InfoCircleOutlined />
               </a>
             </div>
+            <a-button
+              type="text"
+              class="config-button"
+              @click.stop="openProviderConfig(item)"
+              title="配置模型提供商"
+            >
+              <SettingOutlined />
+            </a-button>
             <div class="missing-keys">
               需配置<span v-for="(key, idx) in modelNames[item].env" :key="idx">{{ key }}</span>
             </div>
@@ -217,6 +233,43 @@
         />
       </div>
     </div>
+    <a-modal
+      class="provider-config-modal"
+      v-model:open="providerConfig.visible"
+      :title="`配置${providerConfig.providerName}模型`"
+      @ok="saveProviderConfig"
+      @cancel="cancelProviderConfig"
+      :okText="'保存配置'"
+      :cancelText="'取消'"
+      :ok-type="'primary'"
+      :width="800"
+      :bodyStyle="{ padding: '16px 24px' }"
+    >
+      <div v-if="providerConfig.loading" class="modal-loading-container">
+        <a-spin :indicator="h(LoadingOutlined, { style: { fontSize: '32px', color: 'var(--main-color)' }})" />
+        <div class="loading-text">正在获取模型列表...</div>
+      </div>
+      <div v-else class="modal-config-content">
+        <div class="modal-config-header">
+          <h3>选择 {{ providerConfig.providerName }} 的模型</h3>
+          <p class="description">勾选您希望在系统中启用的模型，请注意，列表中可能包含非对话模型，请仔细甄别。</p>
+        </div>
+
+        <div class="modal-models-section">
+          <div class="modal-checkbox-list">
+            <a-checkbox-group v-model:value="providerConfig.selectedModels">
+              <div v-for="(model, index) in providerConfig.allModels" :key="index" class="modal-checkbox-item">
+                <a-checkbox :value="model.id">{{ model.id }}</a-checkbox>
+              </div>
+            </a-checkbox-group>
+          </div>
+          <div v-if="providerConfig.allModels.length === 0" class="modal-no-models">
+            <a-alert v-if="!modelStatus[providerConfig.provider]" type="warning" message="请在 src/.env 中配置对应的 APIKEY" />
+            <a-alert v-else type="warning" message="该提供商暂未适配获取模型列表的方法，如果需要添加模型，请在 src/static/models.private.yml 中添加。" />
+          </div>
+        </div>
+      </div>
+    </a-modal>
   </div>
 </template>
 
@@ -235,6 +288,7 @@ import {
   InfoCircleOutlined,
   DownOutlined,
   UpOutlined,
+  LoadingOutlined,
 } from '@ant-design/icons-vue';
 import HeaderComponent from '@/components/HeaderComponent.vue';
 import TableConfigComponent from '@/components/TableConfigComponent.vue';
@@ -257,6 +311,15 @@ const customModel = reactive({
   api_base: '',
   edit_type: 'add',
 })
+const providerConfig = reactive({
+  visible: false,
+  provider: '',
+  providerName: '',
+  models: [],
+  allModels: [], // 所有可用的模型
+  selectedModels: [], // 用户选择的模型
+  loading: false,
+})
 const state = reactive({
   loading: false,
   section: 'base',
@@ -427,6 +490,99 @@ const sendRestart = () => {
     }, 200)
   })
 }
+
+// 获取模型提供商的模型列表
+const fetchProviderModels = (provider) => {
+  providerConfig.loading = true;
+  fetch(`/api/chat/models?model_provider=${provider}`)
+    .then(response => response.json())
+    .then(data => {
+      console.log(`${provider} 模型列表:`, data);
+
+      // 处理各种可能的API返回格式
+      let modelsList = [];
+
+      // 情况1: { data: [...] }
+      if (data.data && Array.isArray(data.data)) {
+        modelsList = data.data;
+      }
+      // 情况2: { models: [...] } (字符串数组)
+      else if (data.models && Array.isArray(data.models)) {
+        modelsList = data.models.map(model => typeof model === 'string' ? { id: model } : model);
+      }
+      // 情况3: { models: { data: [...] } }
+      else if (data.models && data.models.data && Array.isArray(data.models.data)) {
+        modelsList = data.models.data;
+      }
+
+      console.log("处理后的模型列表:", modelsList);
+      providerConfig.allModels = modelsList;
+      providerConfig.loading = false;
+    })
+    .catch(error => {
+      console.error(`获取${provider}模型列表失败:`, error);
+      message.error({ content: `获取${modelNames.value[provider].name}模型列表失败`, duration: 2 });
+      providerConfig.loading = false;
+    });
+}
+
+const openProviderConfig = (provider) => {
+  providerConfig.provider = provider;
+  providerConfig.providerName = modelNames.value[provider].name;
+  providerConfig.allModels = [];
+  providerConfig.visible = true;
+  providerConfig.loading = true;
+
+  // 获取当前选择的模型作为初始选中值
+  const currentModels = modelNames.value[provider]?.models || [];
+  providerConfig.selectedModels = [...currentModels];
+
+  // 获取所有可用模型
+  fetchProviderModels(provider);
+}
+
+const saveProviderConfig = async () => {
+  if (!modelStatus.value[providerConfig.provider]) {
+    message.error('请在 src/.env 中配置对应的 APIKEY')
+    return
+  }
+
+  message.loading({ content: '保存配置中...', key: 'save-config', duration: 0 });
+
+  try {
+    // 发送选择的模型列表到后端
+    const response = await fetch(`/api/chat/models/update?model_provider=${providerConfig.provider}`, {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json',
+      },
+      body: JSON.stringify(providerConfig.selectedModels),
+    });
+
+    if (!response.ok) {
+      throw new Error('保存模型配置失败');
+    }
+
+    const data = await response.json();
+    console.log('更新后的模型列表:', data.models);
+
+    message.success({ content: '模型配置已保存!', key: 'save-config', duration: 2 });
+
+    // 关闭弹窗
+    providerConfig.visible = false;
+
+    // 刷新配置
+    configStore.refreshConfig();
+
+  } catch (error) {
+    console.error('保存配置失败:', error);
+    message.error({ content: '保存配置失败: ' + error.message, key: 'save-config', duration: 2 });
+  }
+}
+
+const cancelProviderConfig = () => {
+  providerConfig.visible = false;
+}
 </script>
 
 <style lang="less" scoped>
@@ -792,3 +948,58 @@ const sendRestart = () => {
 }
 </style>
 
+<style lang="less">
+
+.provider-config-modal {
+  .ant-modal-body {
+    padding: 16px 0 !important;
+    .modal-loading-container {
+      display: flex;
+      flex-direction: column;
+      justify-content: center;
+      align-items: center;
+      height: 200px;
+
+      .loading-text {
+        margin-top: 20px;
+        color: var(--gray-700);
+        font-size: 14px;
+      }
+    }
+
+    .modal-config-content {
+      max-height: 70vh;
+      overflow-y: auto;
+      // padding-right: 10px;
+
+      .modal-config-header {
+        margin-bottom: 20px;
+
+        .description {
+          font-size: 14px;
+          color: var(--gray-600);
+          margin: 0;
+        }
+      }
+
+      .modal-models-section {
+        .modal-checkbox-list {
+          max-height: 50vh;
+          overflow-y: auto;
+          .modal-checkbox-item {
+            margin-bottom: 4px;
+            padding: 4px 6px;
+            border-radius: 6px;
+            background-color: white;
+            border: 1px solid var(--gray-200);
+
+            &:hover {
+              background-color: var(--gray-50);
+            }
+          }
+        }
+      }
+    }
+  }
+}
+</style>