fix: cannot automatically get embedding dim when create embedding provider

astrbot/core/config/default.py

@@ -1463,6 +1463,7 @@ class ChatProviderTemplate(TypedDict):
                         "type": "openai_embedding",
                         "provider": "openai",
                         "provider_type": "embedding",
+                        "hint": "provider_group.provider.openai_embedding.hint",
                         "enable": True,
                         "embedding_api_key": "",
                         "embedding_api_base": "",
@@ -1476,6 +1477,7 @@ class ChatProviderTemplate(TypedDict):
                         "type": "gemini_embedding",
                         "provider": "google",
                         "provider_type": "embedding",
+                        "hint": "provider_group.provider.gemini_embedding.hint",
                         "enable": True,
                         "embedding_api_key": "",
                         "embedding_api_base": "",
@@ -2192,9 +2194,9 @@ class ChatProviderTemplate(TypedDict):
                         "type": "string",
                     },
                     "proxy": {
-                        "description": "代理地址",
+                        "description": "provider_group.provider.proxy.description",
                         "type": "string",
-                        "hint": "HTTP/HTTPS 代理地址，格式如 http://127.0.0.1:7890。仅对该提供商的 API 请求生效，不影响 Docker 内网通信。",
+                        "hint": "provider_group.provider.proxy.hint",
                     },
                     "model": {
                         "description": "模型 ID",

astrbot/core/provider/provider.py

@@ -305,6 +305,10 @@ def get_dim(self) -> int:
         """获取向量的维度"""
         ...
 
+    async def detect_dim(self) -> int:
+        """探测模型原生向量维度（默认实现）"""
+        return len(await self.get_embedding("astrbot"))
+
     async def test(self) -> None:
         await self.get_embedding("astrbot")
 

astrbot/core/provider/sources/gemini_embedding_source.py

@@ -78,6 +78,19 @@ async def get_embeddings(self, text: list[str]) -> list[list[float]]:
         except APIError as e:
             raise Exception(f"Gemini Embedding API批量请求失败: {e.message}")
 
+    async def detect_dim(self) -> int:
+        """探测模型原生向量维度（不传 output_dimensionality）"""
+        try:
+            result = await self.client.models.embed_content(
+                model=self.model,
+                contents="echo",
+            )
+            assert result.embeddings is not None
+            assert result.embeddings[0].values is not None
+            return len(result.embeddings[0].values)
+        except APIError as e:
+            raise Exception(f"Gemini Embedding 维度探测失败: {e.message}")
+
     def get_dim(self) -> int:
         """获取向量的维度"""
         return int(self.provider_config.get("embedding_dimensions", 768))

astrbot/core/provider/sources/openai_embedding_source.py

@@ -23,12 +23,16 @@ def __init__(self, provider_config: dict, provider_settings: dict) -> None:
         if proxy:
             logger.info(f"[OpenAI Embedding] 使用代理: {proxy}")
             http_client = httpx.AsyncClient(proxy=proxy)
+        api_base = provider_config.get("embedding_api_base", "").strip()
+        if not api_base:
+            api_base = "https://api.openai.com/v1"
+        else:
+            api_base = api_base.removesuffix("/")
+            if not api_base.endswith("/v1"):
+                api_base = f"{api_base}/v1"
         self.client = AsyncOpenAI(
             api_key=provider_config.get("embedding_api_key"),
-            base_url=provider_config.get(
-                "embedding_api_base",
-                "https://api.openai.com/v1",
-            ),
+            base_url=api_base,
             timeout=int(provider_config.get("timeout", 20)),
             http_client=http_client,
         )
@@ -52,6 +56,64 @@ async def get_embeddings(self, text: list[str]) -> list[list[float]]:
         )
         return [item.embedding for item in embeddings.data]
 
+    async def detect_dim(self) -> int:
+        """探测模型可用的最大向量维度"""
+
+        async def _request_dim(dimensions: int | None) -> int:
+            kwargs = {
+                "input": "echo",
+                "model": self.model,
+            }
+            if dimensions is not None:
+                kwargs["dimensions"] = dimensions
+            embedding = await self.client.embeddings.create(**kwargs)
+            return len(embedding.data[0].embedding)
+
+        # 1) 默认调用，获取当前默认维度
+        base_dim = await _request_dim(None)
+
+        # 2) 先判断 dimensions 参数是否可调
+        probe_dim = base_dim + 1
+        try:
+            probe_result = await _request_dim(probe_dim)
+            if probe_result != probe_dim:
+                return base_dim
+        except Exception:
+            return base_dim
+
+        # 3) 可调时探测上界：指数扩张 + 二分
+        max_cap = 32768
+        low = probe_dim
+        high = max(base_dim * 2, probe_dim + 1)
+        if high > max_cap:
+            high = max_cap
+
+        while high < max_cap:
+            try:
+                result_dim = await _request_dim(high)
+                if result_dim != high:
+                    break
+                low = high
+                high = min(high * 2, max_cap)
+            except Exception:
+                break
+
+        left = low + 1
+        right = high - 1
+        while left <= right:
+            mid = (left + right) // 2
+            try:
+                result_dim = await _request_dim(mid)
+                if result_dim == mid:
+                    low = mid
+                    left = mid + 1
+                else:
+                    right = mid - 1
+            except Exception:
+                right = mid - 1
+
+        return low
+
     def get_dim(self) -> int:
         """获取向量的维度"""
         return int(self.provider_config.get("embedding_dimensions", 1024))

astrbot/dashboard/routes/config.py

@@ -754,6 +754,16 @@ async def get_embedding_dim(self):
             if not provider_type:
                 return Response().error("provider_config 缺少 type 字段").__dict__
 
+            # 首次添加某类提供商时，provider_cls_map 可能尚未注册该适配器
+            if provider_type not in provider_cls_map:
+                try:
+                    self.core_lifecycle.provider_manager.dynamic_import_provider(
+                        provider_type,
+                    )
+                except ImportError as e:
+                    logger.error(traceback.format_exc())
+                    return Response().error(f"动态导入提供商适配器失败: {e!s}").__dict__
+
             # 获取对应的 provider 类
             if provider_type not in provider_cls_map:
                 return (
@@ -779,9 +789,8 @@ async def get_embedding_dim(self):
             if inspect.iscoroutinefunction(init_fn):
                 await init_fn()
 
-            # 获取嵌入向量维度
-            vec = await inst.get_embedding("echo")
-            dim = len(vec)
+            # 探测嵌入向量维度（优先使用 provider 的原生探测逻辑）
+            dim = await inst.detect_dim()
 
             logger.info(
                 f"检测到 {provider_config.get('id', 'unknown')} 的嵌入向量维度为 {dim}",

dashboard/src/components/shared/AstrBotConfig.vue

@@ -48,6 +48,40 @@ const filteredIterable = computed(() => {
   return rest
 })
 
+const providerHint = computed(() => {
+  const hint = props.iterable?.hint
+  if (typeof hint !== 'string' || !hint) return ''
+
+  if (
+    hint === 'provider_group.provider.openai_embedding.hint'
+    || hint === 'provider_group.provider.gemini_embedding.hint'
+  ) {
+    return ''
+  }
+
+  return hint
+})
+
+const getItemHint = (itemKey, itemMeta) => {
+  if (itemMeta?.hint) return itemMeta.hint
+
+  if (itemKey !== 'embedding_api_base') return ''
+
+  const providerType = props.iterable?.type
+  if (providerType === 'openai_embedding') {
+    return getRaw('provider_group.provider.openai_embedding.hint')
+      ? 'provider_group.provider.openai_embedding.hint'
+      : ''
+  }
+  if (providerType === 'gemini_embedding') {
+    return getRaw('provider_group.provider.gemini_embedding.hint')
+      ? 'provider_group.provider.gemini_embedding.hint'
+      : ''
+  }
+
+  return ''
+}
+
 const dialog = ref(false)
 const currentEditingKey = ref('')
 const currentEditingLanguage = ref('json')
@@ -153,14 +187,14 @@ function hasVisibleItemsAfter(items, currentIndex) {
     <div v-if="metadata[metadataKey]?.type === 'object' || metadata[metadataKey]?.config_template" class="object-config">
       <!-- Provider-level hint -->
       <v-alert
-        v-if="iterable.hint && !isEditing"
+        v-if="providerHint"
         type="info"
         variant="tonal"
         class="mb-4"
         border="start"
         density="compact"
       >
-        {{ iterable.hint }}
+        {{ translateIfKey(providerHint) }}
       </v-alert>
 
       <div v-for="(val, key, index) in filteredIterable" :key="key" class="config-item">
@@ -218,9 +252,9 @@ function hasVisibleItemsAfter(items, currentIndex) {
                 </v-list-item-title>
 
                 <v-list-item-subtitle class="property-hint">
-                  <span v-if="metadata[metadataKey].items[key]?.obvious_hint && metadata[metadataKey].items[key]?.hint"
+                  <span v-if="metadata[metadataKey].items[key]?.obvious_hint && getItemHint(key, metadata[metadataKey].items[key])"
                         class="important-hint">‼️</span>
-                  {{ translateIfKey(metadata[metadataKey].items[key]?.hint) }}
+                  {{ translateIfKey(getItemHint(key, metadata[metadataKey].items[key])) }}
                 </v-list-item-subtitle>
               </v-list-item>
             </v-col>

dashboard/src/i18n/locales/en-US/features/config-metadata.json

@@ -1086,6 +1086,12 @@
       "embedding_api_base": {
         "description": "API Base URL"
       },
+      "openai_embedding": {
+        "hint": "OpenAI Embedding automatically appends /v1 at request time."
+      },
+      "gemini_embedding": {
+        "hint": "Gemini Embedding does not require manually adding /v1beta."
+      },
       "volcengine_cluster": {
         "description": "Volcengine cluster",
         "hint": "For voice cloning models, choose volcano_icl or volcano_icl_concurr; default is volcano_tts."
@@ -1313,6 +1319,10 @@
       "api_base": {
         "description": "API Base URL"
       },
+      "proxy": {
+        "description": "Proxy address",
+        "hint": "HTTP/HTTPS proxy URL, e.g. http://127.0.0.1:7890. Applies only to this provider's API requests and does not affect Docker internal networking."
+      },
       "model": {
         "description": "Model ID",
         "hint": "Model name, e.g., gpt-4o-mini, deepseek-chat."

dashboard/src/i18n/locales/zh-CN/features/config-metadata.json

@@ -1089,6 +1089,12 @@
       "embedding_api_base": {
         "description": "API Base URL"
       },
+      "openai_embedding": {
+        "hint": "OpenAI Embedding 会在请求时自动补上 /v1。"
+      },
+      "gemini_embedding": {
+        "hint": "Gemini Embedding 无需手动添加 /v1beta。"
+      },
       "volcengine_cluster": {
         "description": "火山引擎集群",
         "hint": "若使用语音复刻大模型，可选volcano_icl或volcano_icl_concurr，默认使用volcano_tts"
@@ -1316,6 +1322,10 @@
       "api_base": {
         "description": "API Base URL"
       },
+      "proxy": {
+        "description": "代理地址",
+        "hint": "HTTP/HTTPS 代理地址，格式如 http://127.0.0.1:7890。仅对该提供商的 API 请求生效，不影响 Docker 内网通信。"
+      },
       "model": {
         "description": "模型 ID",
         "hint": "模型名称，如 gpt-4o-mini, deepseek-chat。"

dashboard/src/views/Settings.vue

@@ -336,7 +336,7 @@ const loadApiKeys = async () => {
 const tryExecCommandCopy = (text) => {
     let textArea = null;
     try {
-        if (typeof document === 'undefined') return false;
+        if (typeof document === 'undefined' || !document.body) return false;
         textArea = document.createElement('textarea');
         textArea.value = text;
         textArea.setAttribute('readonly', '');
@@ -353,7 +353,9 @@ const tryExecCommandCopy = (text) => {
         return false;
     } finally {
         try {
-            textArea?.remove?.();
+            if (textArea?.parentNode) {
+                textArea.parentNode.removeChild(textArea);
+            }
         } catch (_) {
             // ignore cleanup errors
         }