diff --git a/CONTRIBUTING_CN.md b/CONTRIBUTING_CN.md
index 52606c7896..d7199bd928 100644
--- a/CONTRIBUTING_CN.md
+++ b/CONTRIBUTING_CN.md
@@ -26,7 +26,7 @@
   | [@jyong](https://github.com/JohnJyong)                       | RAG 流水线设计                                  |
   | [@GarfieldDai](https://github.com/GarfieldDai)               | 构建 workflow 编排                     |
   | [@iamjoel](https://github.com/iamjoel) & [@zxhlyh](https://github.com/zxhlyh) | 让我们的前端更易用                  |
-  | [@guchenhe](https://github.com/guchenhe) & [@crazywoola](https://github.com/crazywoola) | 开发人员体验, 综合事项联系人 |
+  | [@guchenhe](https://github.com/guchenhe) & [@crazywoola](https://github.com/crazywoola) | 开发人员体验，综合事项联系人 |
   | [@takatost](https://github.com/takatost)                     | 产品整体方向和架构           |
 
   事项优先级：
@@ -47,7 +47,7 @@
   | ------------------------------------------------------------ | --------------- |
   | 核心功能的 Bugs（例如无法登录、应用无法工作、安全漏洞） | 紧急        |
   | 非紧急 bugs, 性能提升                        | 中等优先级 |
-  | 小幅修复(错别字, 能正常工作但存在误导的 UI)                | 低优先级    |
+  | 小幅修复 (错别字，能正常工作但存在误导的 UI)                | 低优先级    |
 
 ## 安装
 
diff --git a/README_CN.md b/README_CN.md
index 6c57b9f59c..a05ef17365 100644
--- a/README_CN.md
+++ b/README_CN.md
@@ -79,7 +79,7 @@ Dify 是一个开源的 LLM 应用开发平台。其直观的界面结合了 AI
   广泛的 RAG 功能，涵盖从文档摄入到检索的所有内容，支持从 PDF、PPT 和其他常见文档格式中提取文本的开箱即用的支持。
 
 **5. Agent 智能体**: 
-  您可以基于 LLM 函数调用或 ReAct 定义 Agent，并为 Agent 添加预构建或自定义工具。Dify 为 AI Agent 提供了50多种内置工具，如谷歌搜索、DALL·E、Stable Diffusion 和 WolframAlpha 等。
+  您可以基于 LLM 函数调用或 ReAct 定义 Agent，并为 Agent 添加预构建或自定义工具。Dify 为 AI Agent 提供了 50 多种内置工具，如谷歌搜索、DALL·E、Stable Diffusion 和 WolframAlpha 等。
 
 **6. LLMOps**: 
   随时间监视和分析应用程序日志和性能。您可以根据生产数据和标注持续改进提示、数据集和模型。
@@ -112,7 +112,7 @@ Dify 是一个开源的 LLM 应用开发平台。其直观的界面结合了 AI
     <td align="center">仅限 OpenAI</td>
   </tr>
   <tr>
-    <td align="center">RAG引擎</td>
+    <td align="center">RAG 引擎</td>
     <td align="center">✅</td>
     <td align="center">✅</td>
     <td align="center">✅</td>
@@ -234,7 +234,7 @@ docker compose up -d
 对于那些想要贡献代码的人，请参阅我们的[贡献指南](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md)。
 同时，请考虑通过社交媒体、活动和会议来支持 Dify 的分享。
 
-> 我们正在寻找贡献者来帮助将Dify翻译成除了中文和英文之外的其他语言。如果您有兴趣帮助，请参阅我们的[i18n README](https://github.com/langgenius/dify/blob/main/web/i18n/README.md)获取更多信息，并在我们的[Discord社区服务器](https://discord.gg/8Tpq4AcN9c)的`global-users`频道中留言。
+> 我们正在寻找贡献者来帮助将 Dify 翻译成除了中文和英文之外的其他语言。如果您有兴趣帮助，请参阅我们的[i18n README](https://github.com/langgenius/dify/blob/main/web/i18n/README.md)获取更多信息，并在我们的[Discord 社区服务器](https://discord.gg/8Tpq4AcN9c)的`global-users`频道中留言。
 
 **Contributors**
 
diff --git a/api/core/app/apps/base_app_runner.py b/api/core/app/apps/base_app_runner.py
index 07a248d77a..8c6b29731e 100644
--- a/api/core/app/apps/base_app_runner.py
+++ b/api/core/app/apps/base_app_runner.py
@@ -17,7 +17,11 @@ from core.external_data_tool.external_data_fetch import ExternalDataFetch
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_manager import ModelInstance
 from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
-from core.model_runtime.entities.message_entities import AssistantPromptMessage, PromptMessage
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    ImagePromptMessageContent,
+    PromptMessage,
+)
 from core.model_runtime.entities.model_entities import ModelPropertyKey
 from core.model_runtime.errors.invoke import InvokeBadRequestError
 from core.moderation.input_moderation import InputModeration
@@ -141,6 +145,7 @@ class AppRunner:
         query: Optional[str] = None,
         context: Optional[str] = None,
         memory: Optional[TokenBufferMemory] = None,
+        image_detail_config: Optional[ImagePromptMessageContent.DETAIL] = None,
     ) -> tuple[list[PromptMessage], Optional[list[str]]]:
         """
         Organize prompt messages
@@ -167,6 +172,7 @@ class AppRunner:
                 context=context,
                 memory=memory,
                 model_config=model_config,
+                image_detail_config=image_detail_config,
             )
         else:
             memory_config = MemoryConfig(window=MemoryConfig.WindowConfig(enabled=False))
@@ -201,6 +207,7 @@ class AppRunner:
                 memory_config=memory_config,
                 memory=memory,
                 model_config=model_config,
+                image_detail_config=image_detail_config,
             )
             stop = model_config.stop
 
diff --git a/api/core/app/apps/chat/app_runner.py b/api/core/app/apps/chat/app_runner.py
index c42a56ef20..8641f188f7 100644
--- a/api/core/app/apps/chat/app_runner.py
+++ b/api/core/app/apps/chat/app_runner.py
@@ -11,6 +11,7 @@ from core.app.entities.queue_entities import QueueAnnotationReplyEvent
 from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_manager import ModelInstance
+from core.model_runtime.entities.message_entities import ImagePromptMessageContent
 from core.moderation.base import ModerationError
 from core.rag.retrieval.dataset_retrieval import DatasetRetrieval
 from extensions.ext_database import db
@@ -50,6 +51,16 @@ class ChatAppRunner(AppRunner):
         query = application_generate_entity.query
         files = application_generate_entity.files
 
+        image_detail_config = (
+            application_generate_entity.file_upload_config.image_config.detail
+            if (
+                application_generate_entity.file_upload_config
+                and application_generate_entity.file_upload_config.image_config
+            )
+            else None
+        )
+        image_detail_config = image_detail_config or ImagePromptMessageContent.DETAIL.LOW
+
         # Pre-calculate the number of tokens of the prompt messages,
         # and return the rest number of tokens by model context token size limit and max token size limit.
         # If the rest number of tokens is not enough, raise exception.
@@ -85,6 +96,7 @@ class ChatAppRunner(AppRunner):
             files=files,
             query=query,
             memory=memory,
+            image_detail_config=image_detail_config,
         )
 
         # moderation
@@ -183,6 +195,7 @@ class ChatAppRunner(AppRunner):
             query=query,
             context=context,
             memory=memory,
+            image_detail_config=image_detail_config,
         )
 
         # check hosting moderation
diff --git a/api/core/app/apps/completion/app_runner.py b/api/core/app/apps/completion/app_runner.py
index 1f5727715e..4f16247318 100644
--- a/api/core/app/apps/completion/app_runner.py
+++ b/api/core/app/apps/completion/app_runner.py
@@ -9,6 +9,7 @@ from core.app.entities.app_invoke_entities import (
 )
 from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
 from core.model_manager import ModelInstance
+from core.model_runtime.entities.message_entities import ImagePromptMessageContent
 from core.moderation.base import ModerationError
 from core.rag.retrieval.dataset_retrieval import DatasetRetrieval
 from extensions.ext_database import db
@@ -43,6 +44,16 @@ class CompletionAppRunner(AppRunner):
         query = application_generate_entity.query
         files = application_generate_entity.files
 
+        image_detail_config = (
+            application_generate_entity.file_upload_config.image_config.detail
+            if (
+                application_generate_entity.file_upload_config
+                and application_generate_entity.file_upload_config.image_config
+            )
+            else None
+        )
+        image_detail_config = image_detail_config or ImagePromptMessageContent.DETAIL.LOW
+
         # Pre-calculate the number of tokens of the prompt messages,
         # and return the rest number of tokens by model context token size limit and max token size limit.
         # If the rest number of tokens is not enough, raise exception.
@@ -66,6 +77,7 @@ class CompletionAppRunner(AppRunner):
             inputs=inputs,
             files=files,
             query=query,
+            image_detail_config=image_detail_config,
         )
 
         # moderation
@@ -141,6 +153,7 @@ class CompletionAppRunner(AppRunner):
             files=files,
             query=query,
             context=context,
+            image_detail_config=image_detail_config,
         )
 
         # check hosting moderation
diff --git a/api/core/prompt/advanced_prompt_transform.py b/api/core/prompt/advanced_prompt_transform.py
index 87c7a79fb0..c7427f797e 100644
--- a/api/core/prompt/advanced_prompt_transform.py
+++ b/api/core/prompt/advanced_prompt_transform.py
@@ -46,6 +46,7 @@ class AdvancedPromptTransform(PromptTransform):
         memory_config: Optional[MemoryConfig],
         memory: Optional[TokenBufferMemory],
         model_config: ModelConfigWithCredentialsEntity,
+        image_detail_config: Optional[ImagePromptMessageContent.DETAIL] = None,
     ) -> list[PromptMessage]:
         prompt_messages = []
 
@@ -59,6 +60,7 @@ class AdvancedPromptTransform(PromptTransform):
                 memory_config=memory_config,
                 memory=memory,
                 model_config=model_config,
+                image_detail_config=image_detail_config,
             )
         elif isinstance(prompt_template, list) and all(isinstance(item, ChatModelMessage) for item in prompt_template):
             prompt_messages = self._get_chat_model_prompt_messages(
@@ -70,6 +72,7 @@ class AdvancedPromptTransform(PromptTransform):
                 memory_config=memory_config,
                 memory=memory,
                 model_config=model_config,
+                image_detail_config=image_detail_config,
             )
 
         return prompt_messages
@@ -84,6 +87,7 @@ class AdvancedPromptTransform(PromptTransform):
         memory_config: Optional[MemoryConfig],
         memory: Optional[TokenBufferMemory],
         model_config: ModelConfigWithCredentialsEntity,
+        image_detail_config: Optional[ImagePromptMessageContent.DETAIL] = None,
     ) -> list[PromptMessage]:
         """
         Get completion model prompt messages.
@@ -124,7 +128,9 @@ class AdvancedPromptTransform(PromptTransform):
             prompt_message_contents: list[PromptMessageContent] = []
             prompt_message_contents.append(TextPromptMessageContent(data=prompt))
             for file in files:
-                prompt_message_contents.append(file_manager.to_prompt_message_content(file))
+                prompt_message_contents.append(
+                    file_manager.to_prompt_message_content(file, image_detail_config=image_detail_config)
+                )
 
             prompt_messages.append(UserPromptMessage(content=prompt_message_contents))
         else:
@@ -142,6 +148,7 @@ class AdvancedPromptTransform(PromptTransform):
         memory_config: Optional[MemoryConfig],
         memory: Optional[TokenBufferMemory],
         model_config: ModelConfigWithCredentialsEntity,
+        image_detail_config: Optional[ImagePromptMessageContent.DETAIL] = None,
     ) -> list[PromptMessage]:
         """
         Get chat model prompt messages.
@@ -197,7 +204,9 @@ class AdvancedPromptTransform(PromptTransform):
                 prompt_message_contents: list[PromptMessageContent] = []
                 prompt_message_contents.append(TextPromptMessageContent(data=query))
                 for file in files:
-                    prompt_message_contents.append(file_manager.to_prompt_message_content(file))
+                    prompt_message_contents.append(
+                        file_manager.to_prompt_message_content(file, image_detail_config=image_detail_config)
+                    )
                 prompt_messages.append(UserPromptMessage(content=prompt_message_contents))
             else:
                 prompt_messages.append(UserPromptMessage(content=query))
@@ -209,19 +218,25 @@ class AdvancedPromptTransform(PromptTransform):
                     # get last user message content and add files
                     prompt_message_contents = [TextPromptMessageContent(data=cast(str, last_message.content))]
                     for file in files:
-                        prompt_message_contents.append(file_manager.to_prompt_message_content(file))
+                        prompt_message_contents.append(
+                            file_manager.to_prompt_message_content(file, image_detail_config=image_detail_config)
+                        )
 
                     last_message.content = prompt_message_contents
                 else:
                     prompt_message_contents = [TextPromptMessageContent(data="")]  # not for query
                     for file in files:
-                        prompt_message_contents.append(file_manager.to_prompt_message_content(file))
+                        prompt_message_contents.append(
+                            file_manager.to_prompt_message_content(file, image_detail_config=image_detail_config)
+                        )
 
                     prompt_messages.append(UserPromptMessage(content=prompt_message_contents))
             else:
                 prompt_message_contents = [TextPromptMessageContent(data=query)]
                 for file in files:
-                    prompt_message_contents.append(file_manager.to_prompt_message_content(file))
+                    prompt_message_contents.append(
+                        file_manager.to_prompt_message_content(file, image_detail_config=image_detail_config)
+                    )
 
                 prompt_messages.append(UserPromptMessage(content=prompt_message_contents))
         elif query:
diff --git a/api/core/prompt/simple_prompt_transform.py b/api/core/prompt/simple_prompt_transform.py
index e75877de9b..421b14e0df 100644
--- a/api/core/prompt/simple_prompt_transform.py
+++ b/api/core/prompt/simple_prompt_transform.py
@@ -9,6 +9,7 @@ from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEnti
 from core.file import file_manager
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_runtime.entities.message_entities import (
+    ImagePromptMessageContent,
     PromptMessage,
     PromptMessageContent,
     SystemPromptMessage,
@@ -60,6 +61,7 @@ class SimplePromptTransform(PromptTransform):
         context: Optional[str],
         memory: Optional[TokenBufferMemory],
         model_config: ModelConfigWithCredentialsEntity,
+        image_detail_config: Optional[ImagePromptMessageContent.DETAIL] = None,
     ) -> tuple[list[PromptMessage], Optional[list[str]]]:
         inputs = {key: str(value) for key, value in inputs.items()}
 
@@ -74,6 +76,7 @@ class SimplePromptTransform(PromptTransform):
                 context=context,
                 memory=memory,
                 model_config=model_config,
+                image_detail_config=image_detail_config,
             )
         else:
             prompt_messages, stops = self._get_completion_model_prompt_messages(
@@ -85,6 +88,7 @@ class SimplePromptTransform(PromptTransform):
                 context=context,
                 memory=memory,
                 model_config=model_config,
+                image_detail_config=image_detail_config,
             )
 
         return prompt_messages, stops
@@ -175,6 +179,7 @@ class SimplePromptTransform(PromptTransform):
         files: Sequence["File"],
         memory: Optional[TokenBufferMemory],
         model_config: ModelConfigWithCredentialsEntity,
+        image_detail_config: Optional[ImagePromptMessageContent.DETAIL] = None,
     ) -> tuple[list[PromptMessage], Optional[list[str]]]:
         prompt_messages: list[PromptMessage] = []
 
@@ -204,9 +209,9 @@ class SimplePromptTransform(PromptTransform):
             )
 
         if query:
-            prompt_messages.append(self.get_last_user_message(query, files))
+            prompt_messages.append(self.get_last_user_message(query, files, image_detail_config))
         else:
-            prompt_messages.append(self.get_last_user_message(prompt, files))
+            prompt_messages.append(self.get_last_user_message(prompt, files, image_detail_config))
 
         return prompt_messages, None
 
@@ -220,6 +225,7 @@ class SimplePromptTransform(PromptTransform):
         files: Sequence["File"],
         memory: Optional[TokenBufferMemory],
         model_config: ModelConfigWithCredentialsEntity,
+        image_detail_config: Optional[ImagePromptMessageContent.DETAIL] = None,
     ) -> tuple[list[PromptMessage], Optional[list[str]]]:
         # get prompt
         prompt, prompt_rules = self.get_prompt_str_and_rules(
@@ -262,14 +268,21 @@ class SimplePromptTransform(PromptTransform):
         if stops is not None and len(stops) == 0:
             stops = None
 
-        return [self.get_last_user_message(prompt, files)], stops
+        return [self.get_last_user_message(prompt, files, image_detail_config)], stops
 
-    def get_last_user_message(self, prompt: str, files: Sequence["File"]) -> UserPromptMessage:
+    def get_last_user_message(
+        self,
+        prompt: str,
+        files: Sequence["File"],
+        image_detail_config: Optional[ImagePromptMessageContent.DETAIL] = None,
+    ) -> UserPromptMessage:
         if files:
             prompt_message_contents: list[PromptMessageContent] = []
             prompt_message_contents.append(TextPromptMessageContent(data=prompt))
             for file in files:
-                prompt_message_contents.append(file_manager.to_prompt_message_content(file))
+                prompt_message_contents.append(
+                    file_manager.to_prompt_message_content(file, image_detail_config=image_detail_config)
+                )
 
             prompt_message = UserPromptMessage(content=prompt_message_contents)
         else:
diff --git a/api/core/provider_manager.py b/api/core/provider_manager.py
index 7d8ff18983..099acfd7f4 100644
--- a/api/core/provider_manager.py
+++ b/api/core/provider_manager.py
@@ -149,6 +149,11 @@ class ProviderManager:
             provider_name = provider_entity.provider
             provider_records = provider_name_to_provider_records_dict.get(provider_entity.provider, [])
             provider_model_records = provider_name_to_provider_model_records_dict.get(provider_entity.provider, [])
+            provider_id_entity = ModelProviderID(provider_name)
+            if provider_id_entity.is_langgenius():
+                provider_model_records.extend(
+                    provider_name_to_provider_model_records_dict.get(provider_id_entity.provider_name, [])
+                )
 
             # Convert to custom configuration
             custom_configuration = self._to_custom_configuration(
@@ -190,6 +195,20 @@ class ProviderManager:
                 provider_name
             )
 
+            provider_id_entity = ModelProviderID(provider_name)
+
+            if provider_id_entity.is_langgenius():
+                if provider_model_settings is not None:
+                    provider_model_settings.extend(
+                        provider_name_to_provider_model_settings_dict.get(provider_id_entity.provider_name, [])
+                    )
+                if provider_load_balancing_configs is not None:
+                    provider_load_balancing_configs.extend(
+                        provider_name_to_provider_load_balancing_model_configs_dict.get(
+                            provider_id_entity.provider_name, []
+                        )
+                    )
+
             # Convert to model settings
             model_settings = self._to_model_settings(
                 provider_entity=provider_entity,
@@ -207,7 +226,7 @@ class ProviderManager:
                 model_settings=model_settings,
             )
 
-            provider_configurations[str(ModelProviderID(provider_name))] = provider_configuration
+            provider_configurations[str(provider_id_entity)] = provider_configuration
 
         # Return the encapsulated object
         return provider_configurations
diff --git a/api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_sql.py b/api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_sql.py
index 284896cce7..ec9c9d94cc 100644
--- a/api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_sql.py
+++ b/api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_sql.py
@@ -194,6 +194,8 @@ class AnalyticdbVectorBySql:
 
     def search_by_vector(self, query_vector: list[float], **kwargs: Any) -> list[Document]:
         top_k = kwargs.get("top_k", 4)
+        if not isinstance(top_k, int) or top_k <= 0:
+            raise ValueError("top_k must be a positive integer")
         document_ids_filter = kwargs.get("document_ids_filter")
         where_clause = "WHERE 1=1"
         if document_ids_filter:
@@ -225,6 +227,8 @@ class AnalyticdbVectorBySql:
 
     def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:
         top_k = kwargs.get("top_k", 4)
+        if not isinstance(top_k, int) or top_k <= 0:
+            raise ValueError("top_k must be a positive integer")
         document_ids_filter = kwargs.get("document_ids_filter")
         where_clause = ""
         if document_ids_filter:
diff --git a/api/core/rag/datasource/vdb/myscale/myscale_vector.py b/api/core/rag/datasource/vdb/myscale/myscale_vector.py
index 0a44c28bb6..dbb1a7fe19 100644
--- a/api/core/rag/datasource/vdb/myscale/myscale_vector.py
+++ b/api/core/rag/datasource/vdb/myscale/myscale_vector.py
@@ -125,6 +125,8 @@ class MyScaleVector(BaseVector):
 
     def _search(self, dist: str, order: SortOrder, **kwargs: Any) -> list[Document]:
         top_k = kwargs.get("top_k", 4)
+        if not isinstance(top_k, int) or top_k <= 0:
+            raise ValueError("top_k must be a positive integer")
         score_threshold = float(kwargs.get("score_threshold") or 0.0)
         where_str = (
             f"WHERE dist < {1 - score_threshold}"
diff --git a/api/core/rag/datasource/vdb/opengauss/opengauss.py b/api/core/rag/datasource/vdb/opengauss/opengauss.py
index 7b51eb4bd8..2e5b7a31e4 100644
--- a/api/core/rag/datasource/vdb/opengauss/opengauss.py
+++ b/api/core/rag/datasource/vdb/opengauss/opengauss.py
@@ -155,7 +155,8 @@ class OpenGauss(BaseVector):
         :return: List of Documents that are nearest to the query vector.
         """
         top_k = kwargs.get("top_k", 4)
-
+        if not isinstance(top_k, int) or top_k <= 0:
+            raise ValueError("top_k must be a positive integer")
         with self._get_cursor() as cur:
             cur.execute(
                 f"SELECT meta, text, embedding <=> %s AS distance FROM {self.table_name}"
@@ -174,7 +175,8 @@ class OpenGauss(BaseVector):
 
     def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:
         top_k = kwargs.get("top_k", 5)
-
+        if not isinstance(top_k, int) or top_k <= 0:
+            raise ValueError("top_k must be a positive integer")
         with self._get_cursor() as cur:
             cur.execute(
                 f"""SELECT meta, text, ts_rank(to_tsvector(coalesce(text, '')), plainto_tsquery(%s)) AS score
diff --git a/api/core/rag/datasource/vdb/pgvector/pgvector.py b/api/core/rag/datasource/vdb/pgvector/pgvector.py
index d6e028e401..783ad93b0c 100644
--- a/api/core/rag/datasource/vdb/pgvector/pgvector.py
+++ b/api/core/rag/datasource/vdb/pgvector/pgvector.py
@@ -171,6 +171,8 @@ class PGVector(BaseVector):
         :return: List of Documents that are nearest to the query vector.
         """
         top_k = kwargs.get("top_k", 4)
+        if not isinstance(top_k, int) or top_k <= 0:
+            raise ValueError("top_k must be a positive integer")
         document_ids_filter = kwargs.get("document_ids_filter")
         where_clause = ""
         if document_ids_filter:
@@ -196,7 +198,8 @@ class PGVector(BaseVector):
 
     def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:
         top_k = kwargs.get("top_k", 5)
-
+        if not isinstance(top_k, int) or top_k <= 0:
+            raise ValueError("top_k must be a positive integer")
         with self._get_cursor() as cur:
             document_ids_filter = kwargs.get("document_ids_filter")
             where_clause = ""
diff --git a/api/core/workflow/nodes/parameter_extractor/parameter_extractor_node.py b/api/core/workflow/nodes/parameter_extractor/parameter_extractor_node.py
index e147caacf3..7b1b8cf483 100644
--- a/api/core/workflow/nodes/parameter_extractor/parameter_extractor_node.py
+++ b/api/core/workflow/nodes/parameter_extractor/parameter_extractor_node.py
@@ -7,6 +7,7 @@ from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEnti
 from core.file import File
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_manager import ModelInstance
+from core.model_runtime.entities import ImagePromptMessageContent
 from core.model_runtime.entities.llm_entities import LLMResult, LLMUsage
 from core.model_runtime.entities.message_entities import (
     AssistantPromptMessage,
@@ -129,6 +130,7 @@ class ParameterExtractorNode(LLMNode):
                 model_config=model_config,
                 memory=memory,
                 files=files,
+                vision_detail=node_data.vision.configs.detail,
             )
         else:
             # use prompt engineering
@@ -139,6 +141,7 @@ class ParameterExtractorNode(LLMNode):
                 model_config=model_config,
                 memory=memory,
                 files=files,
+                vision_detail=node_data.vision.configs.detail,
             )
 
             prompt_message_tools = []
@@ -267,6 +270,7 @@ class ParameterExtractorNode(LLMNode):
         model_config: ModelConfigWithCredentialsEntity,
         memory: Optional[TokenBufferMemory],
         files: Sequence[File],
+        vision_detail: Optional[ImagePromptMessageContent.DETAIL] = None,
     ) -> tuple[list[PromptMessage], list[PromptMessageTool]]:
         """
         Generate function call prompt.
@@ -289,6 +293,7 @@ class ParameterExtractorNode(LLMNode):
             memory_config=node_data.memory,
             memory=None,
             model_config=model_config,
+            image_detail_config=vision_detail,
         )
 
         # find last user message
@@ -347,6 +352,7 @@ class ParameterExtractorNode(LLMNode):
         model_config: ModelConfigWithCredentialsEntity,
         memory: Optional[TokenBufferMemory],
         files: Sequence[File],
+        vision_detail: Optional[ImagePromptMessageContent.DETAIL] = None,
     ) -> list[PromptMessage]:
         """
         Generate prompt engineering prompt.
@@ -361,6 +367,7 @@ class ParameterExtractorNode(LLMNode):
                 model_config=model_config,
                 memory=memory,
                 files=files,
+                vision_detail=vision_detail,
             )
         elif model_mode == ModelMode.CHAT:
             return self._generate_prompt_engineering_chat_prompt(
@@ -370,6 +377,7 @@ class ParameterExtractorNode(LLMNode):
                 model_config=model_config,
                 memory=memory,
                 files=files,
+                vision_detail=vision_detail,
             )
         else:
             raise InvalidModelModeError(f"Invalid model mode: {model_mode}")
@@ -382,6 +390,7 @@ class ParameterExtractorNode(LLMNode):
         model_config: ModelConfigWithCredentialsEntity,
         memory: Optional[TokenBufferMemory],
         files: Sequence[File],
+        vision_detail: Optional[ImagePromptMessageContent.DETAIL] = None,
     ) -> list[PromptMessage]:
         """
         Generate completion prompt.
@@ -402,6 +411,7 @@ class ParameterExtractorNode(LLMNode):
             memory_config=node_data.memory,
             memory=memory,
             model_config=model_config,
+            image_detail_config=vision_detail,
         )
 
         return prompt_messages
@@ -414,6 +424,7 @@ class ParameterExtractorNode(LLMNode):
         model_config: ModelConfigWithCredentialsEntity,
         memory: Optional[TokenBufferMemory],
         files: Sequence[File],
+        vision_detail: Optional[ImagePromptMessageContent.DETAIL] = None,
     ) -> list[PromptMessage]:
         """
         Generate chat prompt.
@@ -441,6 +452,7 @@ class ParameterExtractorNode(LLMNode):
             memory_config=node_data.memory,
             memory=None,
             model_config=model_config,
+            image_detail_config=vision_detail,
         )
 
         # find last user message