fix(app):

1. Import issue handling；
2. embedding model checkout;
3. omni model removes thinking

api/app/core/models/base.py

@@ -79,8 +79,10 @@ class RedBearModelFactory:
                 model_kwargs: Dict[str, Any] = config.extra_params.get("model_kwargs", {})
                 if is_streaming:
                     model_kwargs["enable_thinking"] = config.deep_thinking
-                    if config.deep_thinking and config.thinking_budget_tokens:
-                        model_kwargs["thinking_budget"] = config.thinking_budget_tokens
+                    if config.deep_thinking:
+                        model_kwargs["incremental_output"] = True
+                        if config.thinking_budget_tokens:
+                            model_kwargs["thinking_budget"] = config.thinking_budget_tokens
                 else:
                     model_kwargs["enable_thinking"] = False
                 params["model_kwargs"] = model_kwargs
@@ -140,8 +142,10 @@ class RedBearModelFactory:
                 model_kwargs: Dict[str, Any] = config.extra_params.get("model_kwargs", {})
                 if is_streaming:
                     model_kwargs["enable_thinking"] = config.deep_thinking
-                    if config.deep_thinking and config.thinking_budget_tokens:
-                        model_kwargs["thinking_budget"] = config.thinking_budget_tokens
+                    if config.deep_thinking:
+                        model_kwargs["incremental_output"] = True
+                        if config.thinking_budget_tokens:
+                            model_kwargs["thinking_budget"] = config.thinking_budget_tokens
                 else:
                     model_kwargs["enable_thinking"] = False
                 params["model_kwargs"] = model_kwargs

api/app/core/models/embedding.py

@@ -1,5 +1,5 @@
 
-from typing import Any, Dict, List, Optional, Union
+from typing import Any, Dict, List, Union
 from langchain_core.embeddings import Embeddings
 
 from app.core.models.base import RedBearModelConfig, get_provider_embedding_class, RedBearModelFactory
@@ -22,7 +22,8 @@ class RedBearEmbeddings(Embeddings):
             self._model = self._create_model(config)
             self._client = None
 
-    def _create_model(self, config: RedBearModelConfig) -> Embeddings:
+    @staticmethod
+    def _create_model(config: RedBearModelConfig) -> Embeddings:
         """根据配置创建 LangChain 模型"""
         embedding_class = get_provider_embedding_class(config.provider)
         provider = config.provider.lower()
@@ -36,6 +37,8 @@ class RedBearEmbeddings(Embeddings):
                 "api_key": config.api_key,
                 "timeout": httpx.Timeout(timeout=config.timeout, connect=60.0),
                 "max_retries": config.max_retries,
+                "check_embedding_ctx_length": False,
+                "encoding_format": "float"
             }
         elif provider == ModelProvider.DASHSCOPE:
             params = {

api/app/core/models/scripts/dashscope_models.yaml

@@ -803,7 +803,6 @@ models:
   - vision
   - video
   - audio
-  - thinking
   is_omni: true
   tags:
   - 大语言模型