rag-gateway.git

			@@ -10,7 +10,8 @@
			from Log import logger
			from app.api import get_current_user_websocket
			from app.config.config import settings
			from app.config.const import IMAGE_TO_TEXT, DOCUMENT_TO_REPORT, DOCUMENT_TO_CLEANING, DOCUMENT_IA_QUESTIONS
			from app.config.const import IMAGE_TO_TEXT, DOCUMENT_TO_REPORT, DOCUMENT_TO_CLEANING, DOCUMENT_IA_QUESTIONS, \
			DOCUMENT_TO_REPORT_TITLE, DOCUMENT_TO_TITLE
			from app.models import MenuCapacityModel
			from app.models.agent_model import AgentModel, AgentType
			from app.models.base_model import get_db
			@@ -359,7 +360,7 @@
			"upload_file_id": upload_file_id
			})
			async for rag_response in dify_service.chat(token, current_user.id, question, files,
			conversation_id):
			conversation_id, {}):
			# print(rag_response)
			try:
			if rag_response[:5] == "data:":
			@@ -437,9 +438,12 @@
			upload_files = receive_message.get('upload_files', [])
			title = receive_message.get('title', "")
			workflow_type = receive_message.get('workflow', 1)
			if not upload_files:
			await websocket.send_json({"message": "Invalid request", "type": "error"})
			continue
			sub_titles = receive_message.get('sub_titles', "")
			title_number = receive_message.get('title_number', 8)
			title_style = receive_message.get('title_style', "")
			title_query = receive_message.get('title_query', "")
			if upload_files:
			title_query = "start"
			try:
			session = SessionService(db).create_session(
			chat_id,
			@@ -466,11 +470,22 @@
			if workflow_type == 2:
			inputs["file_list"] = files
			inputs["Completion_of_main_indicators"] = title
			token = DfTokenDao(db).get_token_by_id(DOCUMENT_TO_REPORT)
			inputs["sub_titles"] = sub_titles
			token = DfTokenDao(db).get_token_by_id(DOCUMENT_TO_REPORT_TITLE)
			if not token:
			await websocket.send_json(
			{"message": "Invalid token document_to_cleaning", "type": "error"})
			elif workflow_type == 3:
			inputs["file_list"] = files
			inputs["number_of_title"] = title_number
			inputs["title_style"] = title_style
			token = DfTokenDao(db).get_token_by_id(DOCUMENT_TO_TITLE)
			if not token:
			await websocket.send_json(
			{"message": "Invalid token document_to_title", "type": "error"})

			complete_response = ""
			if workflow_type == 1 or workflow_type == 2:
			async for rag_response in dify_service.workflow(token, current_user.id, inputs):
			# print(rag_response)
			try:
			@@ -547,6 +562,86 @@
			result = {"message": f"内部错误： {e2}", "type": "close"}
			await websocket.send_json(result)
			print(f"Error process message of ragflow: {e2}")
			elif workflow_type == 3:
			image_list = []
			# print(inputs)
			complete_response = ""
			async for rag_response in dify_service.chat(token, current_user.id, title_query, [],
			conversation_id, inputs):
			print(rag_response)
			try:
			if rag_response[:5] == "data:":
			# 如果是，则截取掉前5个字符，并去除首尾空白符
			complete_response = rag_response[5:].strip()
			elif "event: ping" in rag_response:
			continue
			else:
			# 否则，保持原样
			complete_response += rag_response
			try:
			data = json.loads(complete_response)
			complete_response = ""
			if data.get("event") == "node_started" or data.get(
			"event") == "node_finished": # "event": "message_end"
			if "data" not in data or not data["data"]: # 信息过滤
			logger.error("非法数据--------------------")
			logger.error(data)
			continue
			else: # 正常输出
			answer = data.get("data", "")
			if isinstance(answer, str):
			logger.error("----------------未知数据--------------------")
			logger.error(data)
			continue
			elif isinstance(answer, dict):

			message = answer.get("title", "")

			result = {"message": message, "type": "system"}
			elif data.get("event") == "message":
			message = data.get("answer", "")
			# try:
			# msg_dict = json.loads(answer)
			# message = msg_dict.get("output", "")
			# except Exception as e:
			# print(e)
			# continue
			result = {"message": message, "type": "message",
			"download_url": ""}
			try:
			SessionService(db).update_session(chat_id,
			message={"role": "assistant",
			"content": {
			"answer": message,
			"download_url": ""}},
			conversation_id=data.get(
			"conversation_id"))
			except Exception as e:
			logger.error("保存dify的会话异常！")
			logger.error(e)
			# try:
			# await websocket.send_json(result)
			# except Exception as e:
			# logger.error(e)
			# logger.error("返回客户端消息异常!")

			elif data.get("event") == "message_end":
			result = {"message": "", "type": "close", "download_url": ""}
			else:
			continue
			try:
			await websocket.send_json(result)
			except Exception as e:
			logger.error(e)
			logger.error("dify返回客户端消息异常!")
			complete_response = ""
			except json.JSONDecodeError as e:
			print(f"Error decoding JSON: {e}")
			# print(f"Response text: {text}")
			except Exception as e2:
			result = {"message": f"内部错误： {e2}", "type": "close"}
			await websocket.send_json(result)
			print(f"Error process message of ragflow: {e2}")
			elif chat_type == "documentIa":
			# print(122112)
			token = DfTokenDao(db).get_token_by_id(DOCUMENT_IA_QUESTIONS)
			@@ -588,7 +683,7 @@
			answer_str = ""
			complete_response = ""
			async for rag_response in dify_service.chat(token, current_user.id, question, files,
			conversation_id):
			conversation_id, {}):
			# print(rag_response)
			try:
			if rag_response[:5] == "data:":

	app/api/chat.py	109 ●●●●● 补丁 \| 查看 \| 原始文档 \| blame \| 历史
	app/config/const.py	2 ●●●●● 补丁 \| 查看 \| 原始文档 \| blame \| 历史
	app/service/difyService.py	4 ●●●●● 补丁 \| 查看 \| 原始文档 \| blame \| 历史

			@@ -4,6 +4,8 @@
			DOCUMENT_TO_REPORT = "document_to_report"
			IMAGE_TO_TEXT = "image_and_text_conversion"
			DOCUMENT_IA_QUESTIONS = "document_ia_questions"
			DOCUMENT_TO_REPORT_TITLE = "document_to_report_title"
			DOCUMENT_TO_TITLE = "document_to_title"
			ENV_CONF_PATH = "app/config/env_conf"
			APP_SERVICE_PATH = "app/service/"

			@@ -127,11 +127,11 @@



			async def chat(self, token: str, user_id: int, message: str, files: [], conversation_id: str):
			async def chat(self, token: str, user_id: int, message: str, files: [], conversation_id: str, inputs: dict):

			target_url = f"{self.base_url}/v1/chat-messages"
			data = {
			"inputs": {},
			"inputs": inputs,
			"query": message,
			"response_mode": "streaming",
			"conversation_id": conversation_id,