feat: add Document Split Node functionality and localization

apps/application/flow/step_node/document_split_node/i_document_split_node.py

@@ -22,7 +22,7 @@ class DocumentSplitNodeSerializer(serializers.Serializer):
         required=False, label=_("paragraph title relate problem"), default=False
     )
     paragraph_title_relate_problem_reference = serializers.ListField(
-        required=False, label=_("paragraph title relate problem reference"), child=serializers.CharField()
+        required=False, label=_("paragraph title relate problem reference"), child=serializers.CharField(), default=[]
     )
     document_name_relate_problem_type = serializers.ChoiceField(
         choices=['custom', 'referencing'], required=False, label=_("document name relate problem type"),
@@ -32,7 +32,7 @@ class DocumentSplitNodeSerializer(serializers.Serializer):
         required=False, label=_("document name relate problem"), default=False
     )
     document_name_relate_problem_reference = serializers.ListField(
-        required=False, label=_("document name relate problem reference"), child=serializers.CharField()
+        required=False, label=_("document name relate problem reference"), child=serializers.CharField(), default=[]
     )
     limit = serializers.IntegerField(required=False, label=_("limit"), default=4096)
     patterns = serializers.ListField(
@@ -55,9 +55,9 @@ class IDocumentSplitNode(INode):
     def _run(self):
         res = self.workflow_manage.get_reference_field(self.node_params_serializer.data.get('file_list')[0],
                                                        self.node_params_serializer.data.get('file_list')[1:])
-        return self.execute(file_list=res, **self.flow_params_serializer.data)
+        return self.execute(files=res, **self.node_params_serializer.data, **self.flow_params_serializer.data)
 
-    def execute(self, file_list, knowledge_id, split_strategy, paragraph_title_relate_problem_type,
+    def execute(self, files, knowledge_id, split_strategy, paragraph_title_relate_problem_type,
                 paragraph_title_relate_problem, paragraph_title_relate_problem_reference,
                 document_name_relate_problem_type, document_name_relate_problem,
                 document_name_relate_problem_reference, limit, patterns, with_filter, **kwargs) -> NodeResult:

apps/application/flow/step_node/document_split_node/impl/base_document_split_node.py

@@ -1,59 +1,85 @@
 # coding=utf-8
+import io
+import mimetypes
+
+from django.core.files.uploadedfile import InMemoryUploadedFile
 from django.db.models import QuerySet
 
 from application.flow.i_step_node import NodeResult
 from application.flow.step_node.document_split_node.i_document_split_node import IDocumentSplitNode
-from knowledge.models import File
+from knowledge.models import File, FileSourceType
 from knowledge.serializers.document import split_handles, FileBufferHandle
 
 
+def bytes_to_uploaded_file(file_bytes, file_name="file.txt"):
+    content_type, _ = mimetypes.guess_type(file_name)
+    if content_type is None:
+        # 如果未能识别，设置为默认的二进制文件类型
+        content_type = "application/octet-stream"
+    # 创建一个内存中的字节流对象
+    file_stream = io.BytesIO(file_bytes)
+
+    # 获取文件大小
+    file_size = len(file_bytes)
+
+    # 创建 InMemoryUploadedFile 对象
+    uploaded_file = InMemoryUploadedFile(
+        file=file_stream,
+        field_name=None,
+        name=file_name,
+        content_type=content_type,
+        size=file_size,
+        charset=None,
+    )
+    return uploaded_file
+
+
 class BaseDocumentSplitNode(IDocumentSplitNode):
     def save_context(self, details, workflow_manage):
         self.context['content'] = details.get('content')
-        print(details)
 
-    def execute(self, file_list, knowledge_id, split_strategy, paragraph_title_relate_problem_type,
+    def execute(self, files, knowledge_id, split_strategy, paragraph_title_relate_problem_type,
                 paragraph_title_relate_problem, paragraph_title_relate_problem_reference,
                 document_name_relate_problem_type, document_name_relate_problem,
                 document_name_relate_problem_reference, limit, patterns, with_filter, **kwargs) -> NodeResult:
         get_buffer = FileBufferHandle().get_buffer
+        self.context['file_list'] = files
+        self.context['knowledge_id'] = knowledge_id
 
         paragraph_list = []
-        for doc in file_list:
+        for doc in files:
             file = QuerySet(File).filter(id=doc['file_id']).first()
-            file_id = file.id
+            file_mem = bytes_to_uploaded_file(file.get_bytes(), file_name=file.file_name)
+
             for split_handle in split_handles:
-                if split_handle.support(file, get_buffer):
-                    result = split_handle.handle(file, patterns, with_filter, limit, get_buffer, self.save_image)
+                if split_handle.support(file_mem, get_buffer):
+                    result = split_handle.handle(file_mem, patterns, with_filter, limit, get_buffer, self.save_image)
                     if isinstance(result, list):
                         for item in result:
-                            item['source_file_id'] = file_id
+                            item['source_file_id'] = file.id
                         paragraph_list = result
                     else:
-                        result['source_file_id'] = file_id
+                        result['source_file_id'] = file.id
                         paragraph_list = [result]
 
-        self.context['file_list'] = file_list
         self.context['paragraph_list'] = paragraph_list
 
-        print(paragraph_list)
 
         return NodeResult({'paragraph_list': paragraph_list}, {})
 
     def save_image(self, image_list):
-        # if image_list is not None and len(image_list) > 0:
-        #     exist_image_list = [str(i.get('id')) for i in
-        #                         QuerySet(File).filter(id__in=[i.id for i in image_list]).values('id')]
-        #     save_image_list = [image for image in image_list if not exist_image_list.__contains__(str(image.id))]
-        #     save_image_list = list({img.id: img for img in save_image_list}.values())
-        #     # save image
-        #     for file in save_image_list:
-        #         file_bytes = file.meta.pop('content')
-        #         file.meta['knowledge_id'] = self.data.get('knowledge_id')
-        #         file.source_type = FileSourceType.KNOWLEDGE
-        #         file.source_id = self.data.get('knowledge_id')
-        #         file.save(file_bytes)
-        pass
+        if image_list is not None and len(image_list) > 0:
+            exist_image_list = [str(i.get('id')) for i in
+                                QuerySet(File).filter(id__in=[i.id for i in image_list]).values('id')]
+            save_image_list = [image for image in image_list if not exist_image_list.__contains__(str(image.id))]
+            save_image_list = list({img.id: img for img in save_image_list}.values())
+            # save image
+            for file in save_image_list:
+                file_bytes = file.meta.pop('content')
+                file.meta['knowledge_id'] = self.context.get('knowledge_id')
+                file.source_type = FileSourceType.KNOWLEDGE
+                file.source_id = self.context.get('knowledge_id')
+                file.save(file_bytes)
 
     def get_details(self, index: int, **kwargs):
         return {