v0.2.5- release

Author: calvin

admin/app/config/config_private.py

@@ -14,7 +14,7 @@
 app.config['LOG_LEVEL'] = "INFO"
 app.config['LOG_MAX_BYTES'] = 10*1024*1024
 app.config['LOG_BACKUP_COUNT'] = 10
-app.config['SECRET_KEY'] = '146c827-a8ac-4a28-8fd5-c13e5df11529'
+app.config['SECRET_KEY'] = '1e5df11529'
 app.config['download_cool_time'] = 7200
 app.config['download_max_count'] = 100
 

admin/app/config/static/user_template.xlsx

@@ -56,7 +56,7 @@ def search_all_apps(params):
     if not check_has_role(admin_user.user_id, "next_console_admin"):
         # 非平台管理员
         target_apps = target_apps.filter(
-            UserInfo.user_company_id == admin_user.user_company_id
+            UserInfo.user_company_id == admin_user.user_company_id,
         )
     target_apps = target_apps.order_by(
         AppMetaInfo.create_time.desc()
@@ -152,7 +152,11 @@ def delete_app(data):
     """
     app_code = data.get("app_code")
     user_id = int(data.get("user_id"))
-    app_info = AppMetaInfo.query.filter_by(app_code=app_code).first()
+    app_info = AppMetaInfo.query.filter(
+        AppMetaInfo.app_code == app_code,
+        AppMetaInfo.environment == '开发',
+        AppMetaInfo.app_status != '已删除'
+    ).first()
     if not app_info:
         return next_console_response(error_status=True, error_message="应用不存在！", error_code=1002)
     if app_info.app_type != '个人应用':

admin/app/config/static/user_template_twadmin.xlsx

@@ -1316,11 +1316,10 @@ def transform_to_message(task_record, global_params):
                 result = message_item
             # 保存消息
             answer_msg.msg_content = json.dumps(message_item)
-            answer_msg.msg_format = "workflow"
+            answer_msg.msg_format = "customize"
             db.session.add(answer_msg)
             db.session.commit()
             global_params["message_queue"].put(result)
-
         else:
             continue
 

admin/app/services/app_center/app_manage_service.py

@@ -35,7 +35,7 @@ def parallel_llm_node_execute(params, task_record, global_params):
     for item in params[parallel_attr]:
         new_sub_params = {k: params[k] for k in params if k not in params[parallel_attr]}
         new_sub_params[parallel_attr] = [item]
-        workflow_node_llm_params = load_llm_prams(new_sub_params, task_record, global_params)
+        workflow_node_llm_params = load_llm_prams(new_sub_params, task_record, global_params, imgUrl='base64')
         future = global_params["executor"].submit(single_llm_sub_node_execute,
                                                   llm_client, workflow_node_llm_params,
                                                   task_record.to_dict(), global_params)
@@ -119,7 +119,7 @@ def single_llm_sub_node_execute(llm_client, workflow_node_llm_params, task_recor
             except GeneratorExit:
                 pass
             except Exception as e3:
-                app.logger.error(f"调用基模型异常：{str(e3)}")
+                app.logger.error(f"调用基模型异常：{str(e3)}, {workflow_node_llm_params}")
                 msg_content += "\n\n **对不起，模型服务正忙，请稍等片刻后重试，或者可以试试切换其他模型~**"
                 if task_record.get("workflow_node_enable_message") and global_params["stream"]:
                     if task_record.get("workflow_node_message_schema_type") == "messageFlow":

admin/app/services/app_center/app_run_service.py

@@ -49,7 +49,11 @@ def file_reader_node_execute(task_params, task_record, global_params):
             if transform_engine == "PyMuPDF":
                 for k in config:
                     task_params[k] = config[k]
-                output_resources.append(pymupdf_reader(resource, task_params))
+                res = pymupdf_reader(resource, task_params)
+                if isinstance(res, list):
+                    output_resources.extend(res)
+                else:
+                    output_resources.append(res)
         elif src_format in ("docx", "doc") and resource.resource_format in ("docx", "doc"):
             if transform_engine == "python-docx":
                 pass
@@ -66,10 +70,9 @@ def file_reader_node_execute(task_params, task_record, global_params):
                 output_resources.append(html2text_reader(resource, config))
         elif src_format == "未知":
             output_resources.append(text_reader(resource, config))
-    if mode == 'list':
+    if mode == 'list' or (src_format == 'pdf'
+                          and transform_engine == 'PyMuPDF' and tgt_format in ('jpg', 'png', 'webp')):
         node_results = {"output_resources": [resource for resource in output_resources]}
-    elif src_format == 'pdf' and transform_engine == 'PyMuPDF' and tgt_format in ('jpg', 'png', 'webp'):
-        node_results = {"output_resources": [resource for resource in output_resources[0]]}
     else:
         node_results = {"output_resource": output_resources[0] if output_resources else {}}
     task_record.task_result = json.dumps(node_results)

admin/app/services/app_center/expermental_features.py

@@ -1,6 +1,6 @@
 import json
 from pathlib import Path
-
+import base64
 from openai import OpenAI
 from app.models.next_console.next_console_model import NextConsoleMessage
 from app.services.next_console.llm import NextConsoleLLMClient, LLMInstance
@@ -43,6 +43,8 @@ def llm_node_execute(params, task_record, global_params):
     msg_reasoning_content = ""
     msg_token_used = 0
     answer_msg = None
+    task_status = '执行中'
+    task_trace_log = ''
     if workflow_node_llm_params.get("stream", False):
         all_message_format = [msg_schema.get("schema_type") for msg_schema in task_record.workflow_node_message_schema]
         output_flag = task_record.workflow_node_enable_message and global_params["stream"] and 'messageFlow' in all_message_format
@@ -101,30 +103,33 @@ def llm_node_execute(params, task_record, global_params):
             pass
         except Exception as e3:
             app.logger.error(f"调用基模型异常：{str(e3)}")
+            task_status = "异常"
+            task_trace_log = str(e3)
             msg_content += "\n\n **对不起，模型服务正忙，请稍等片刻后重试，或者可以试试切换其他模型~**"
-            if task_record.workflow_node_enable_message and global_params["stream"]:
-                if task_record.workflow_node_message_schema_type == "messageFlow":
-                    except_result = {
-                        "id": "",
-                        "session_id": task_record.session_id,
-                        "qa_id": task_record.qa_id,
-                        "msg_parent_id": task_record.msg_id,
-                        "created": 0,
-                        "model": '',
-                        "object": "chat.completion",
-                        "choices": [
-                            {
-                                "finish_reason": "error",
-                                "index": 0,
-                                "delta": {
-                                    "content": msg_content,
-                                    "role": "assistant"
-                                },
+            if task_record.workflow_node_enable_message and global_params["stream"] and output_flag:
+                except_result = {
+                    "id": "",
+                    "session_id": task_record.session_id,
+                    "qa_id": task_record.qa_id,
+                    "msg_parent_id": task_record.msg_id,
+                    'msg_id': answer_msg.msg_id,
+                    "created": 0,
+                    "model": '',
+                    "object": "chat.completion",
+                    "choices": [
+                        {
+                            "finish_reason": "error",
+                            "index": 0,
+                            "delta": {
+                                "reasoning_content": "",
+                                "content": msg_content,
+                                "role": "assistant"
+                            },
 
-                            }
-                        ]
-                    }
-                    global_params["message_queue"].put(except_result)
+                        }
+                    ]
+                }
+                global_params["message_queue"].put(except_result)
         finally:
             # 更新llm节点记录
             # 如果有RAG引用，则添加到消息中
@@ -155,7 +160,10 @@ def llm_node_execute(params, task_record, global_params):
                 "reasoning_content": msg_reasoning_content,
             })
             task_record.end_time = datetime.now()
-            task_record.task_status = "已完成"
+            if task_status == '执行中':
+                task_status = "已完成"
+            task_record.task_status = task_status
+            task_record.task_trace_log = task_trace_log
             task_record.task_token_used = msg_token_used
             db.session.add(task_record)
             db.session.commit()
@@ -178,24 +186,24 @@ def llm_node_execute(params, task_record, global_params):
             task_record.task_token_used = msg_token_used
         except Exception as e:
             task_record.task_status = "异常"
+            task_record.task_trace_log = str(e)
             app.logger.error(f"workflow_chat error: {e}")
             msg_content = '对不起，模型服务正忙，请稍等片刻后重试，或者可以试试切换其他模型~'
-            task_record.task_trace_log = str(e)
+
         if task_record.workflow_node_rag_ref_show:
             reference_md = add_reference_md(task_record, global_params)
             msg_content += reference_md
         task_record.task_result = json.dumps({
                 "content": msg_content,
                 "reasoning_content": msg_reasoning_content,
             })
-        task_record.task_status = "已完成"
         task_record.end_time = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
         db.session.add(task_record)
         db.session.commit()
         return True
 
 
-def load_llm_prams(task_params, task_record, global_params):
+def load_llm_prams(task_params, task_record, global_params, imgUrl='url'):
     """
     载入大模型的所有参数
     """
@@ -244,10 +252,20 @@ def load_llm_prams(task_params, task_record, global_params):
             ).all()
             for resource in target_attachments:
                 if resource.resource_type in ("image", "media") and resource.resource_download_url:
+                    url = app.config.get("domain") + "/next_console/knowledge_center/resource_images?resource_id={}".format(resource.id)
+                    if imgUrl == 'base64':
+                        # 如果是base64编码的图片
+                        try:
+                            with open(resource.resource_path, "rb") as image_file:
+                                encoded_string = base64.b64encode(image_file.read()).decode('utf-8')
+                            url = "data:image/png;base64,{}".format(encoded_string)
+                        except Exception as e:
+                            app.logger.error(f"读取图片文件失败：{e}")
+                            continue
                     image_list.append({
                         "type": "image_url",
                         "image_url": {
-                            "url": app.config.get("domain") + "/next_console/knowledge_center/resource_images?resource_id={}".format(resource.id),
+                            "url": url,
                             "detail": "auto"
                         }
                     })

admin/app/services/app_center/file_reader.py

@@ -79,7 +79,7 @@ def load_task_result(task_record):
                 validate(exec_result, task_record.workflow_node_rpjs)
         except Exception as e:
             print(e)
-            task_record.task_trace_log = str(e)
+            task_record.task_trace_log = f"{exec_result}, 验证失败: {str(e)}"
             db.session.add(task_record)
             db.session.commit()
             return
@@ -225,15 +225,15 @@ def load_properties(properties, global_params, isStart=False):
             if properties.get(k).get("value"):
                 data[k] = properties.get(k).get("value")
                 continue
-            elif ref:
+            elif ref != '' and ref is not None:
                 # 固定值
                 if isinstance(ref, (str, int)):
                     if required and ref == '':
                         raise ValueError(f"Required field '{k}' is missing in global parameters.")
                     if properties.get(k).get("type") == "boolean":
-                        if ref == 'false':
+                        if ref == 'false' or ref is False:
                             ref = False
-                        elif ref == 'true':
+                        elif ref == 'true' or ref is True:
                             ref = True
                         else:
                             ref = None

admin/app/services/app_center/llm_node_service.py

@@ -1385,7 +1385,7 @@ def init_file_reader_node(new_node):
                             "showSubArea": False,
                             "type": "string",
                             "typeName": "string",
-                            "description": "文件名称",
+                            "description": "文件格式",
                             "value": ""
                         },
                         "size": {