Merge branch 'main' into fix/chore-fix

api/core/workflow/nodes/base/node.py

@@ -69,7 +69,7 @@ class BaseNode(Generic[GenericNodeData]):
         try:
             result = self._run()
         except Exception as e:
-            logger.error(f"Node {self.node_id} failed to run: {e}")
+            logger.exception(f"Node {self.node_id} failed to run: {e}")
             result = NodeRunResult(
                 status=WorkflowNodeExecutionStatus.FAILED,
                 error=str(e),

api/core/workflow/nodes/http_request/executor.py

@@ -97,15 +97,6 @@ class Executor:
         headers = self.variable_pool.convert_template(self.node_data.headers).text
         self.headers = _plain_text_to_dict(headers)
 
-        body = self.node_data.body
-        if body is None:
-            return
-        if "content-type" not in (k.lower() for k in self.headers) and body.type in BODY_TYPE_TO_CONTENT_TYPE:
-            self.headers["Content-Type"] = BODY_TYPE_TO_CONTENT_TYPE[body.type]
-        if body.type == "form-data":
-            self.boundary = f"----WebKitFormBoundary{_generate_random_string(16)}"
-            self.headers["Content-Type"] = f"multipart/form-data; boundary={self.boundary}"
-
     def _init_body(self):
         body = self.node_data.body
         if body is not None:
@@ -154,9 +145,8 @@ class Executor:
                         for k, v in files.items()
                         if v.related_id is not None
                     }
-
                     self.data = form_data
-                    self.files = files
+                    self.files = files or None
 
     def _assembling_headers(self) -> dict[str, Any]:
         authorization = deepcopy(self.auth)
@@ -217,6 +207,7 @@ class Executor:
             "timeout": (self.timeout.connect, self.timeout.read, self.timeout.write),
             "follow_redirects": True,
         }
+        # request_args = {k: v for k, v in request_args.items() if v is not None}
 
         response = getattr(ssrf_proxy, self.method)(**request_args)
         return response
@@ -244,6 +235,13 @@ class Executor:
         raw += f"Host: {url_parts.netloc}\r\n"
 
         headers = self._assembling_headers()
+        body = self.node_data.body
+        boundary = f"----WebKitFormBoundary{_generate_random_string(16)}"
+        if body:
+            if "content-type" not in (k.lower() for k in self.headers) and body.type in BODY_TYPE_TO_CONTENT_TYPE:
+                headers["Content-Type"] = BODY_TYPE_TO_CONTENT_TYPE[body.type]
+            if body.type == "form-data":
+                headers["Content-Type"] = f"multipart/form-data; boundary={boundary}"
         for k, v in headers.items():
             if self.auth.type == "api-key":
                 authorization_header = "Authorization"
@@ -256,7 +254,6 @@ class Executor:
 
         body = ""
         if self.files:
-            boundary = self.boundary
             for k, v in self.files.items():
                 body += f"--{boundary}\r\n"
                 body += f'Content-Disposition: form-data; name="{k}"\r\n\r\n'
@@ -271,7 +268,6 @@ class Executor:
             elif self.data and self.node_data.body.type == "x-www-form-urlencoded":
                 body = urlencode(self.data)
             elif self.data and self.node_data.body.type == "form-data":
-                boundary = self.boundary
                 for key, value in self.data.items():
                     body += f"--{boundary}\r\n"
                     body += f'Content-Disposition: form-data; name="{key}"\r\n\r\n'

api/core/workflow/nodes/llm/node.py

@@ -14,6 +14,7 @@ from core.model_runtime.entities import (
     PromptMessage,
     PromptMessageContentType,
     TextPromptMessageContent,
+    VideoPromptMessageContent,
 )
 from core.model_runtime.entities.llm_entities import LLMResult, LLMUsage
 from core.model_runtime.entities.model_entities import ModelType
@@ -560,7 +561,9 @@ class LLMNode(BaseNode[LLMNodeData]):
                         # cuz vision detail is related to the configuration from FileUpload feature.
                         content_item.detail = vision_detail
                         prompt_message_content.append(content_item)
-                    elif isinstance(content_item, TextPromptMessageContent | AudioPromptMessageContent):
+                    elif isinstance(
+                        content_item, TextPromptMessageContent | AudioPromptMessageContent | VideoPromptMessageContent
+                    ):
                         prompt_message_content.append(content_item)
 
                 if len(prompt_message_content) > 1:

api/core/workflow/nodes/question_classifier/question_classifier_node.py

@@ -127,7 +127,7 @@ class QuestionClassifierNode(LLMNode):
                     category_id = category_id_result
 
         except OutputParserError:
-            logging.error(f"Failed to parse result text: {result_text}")
+            logging.exception(f"Failed to parse result text: {result_text}")
         try:
             process_data = {
                 "model_mode": model_config.mode,