| | |
| | | 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, \ |
| | | DOCUMENT_TO_REPORT_TITLE, DOCUMENT_TO_TITLE, DOCUMENT_TO_PAPER |
| | | DOCUMENT_TO_REPORT_TITLE, DOCUMENT_TO_TITLE, DOCUMENT_TO_PAPER, DOCUMENT_IA_QUESTIONS_DS |
| | | from app.models import MenuCapacityModel |
| | | from app.models.agent_model import AgentModel, AgentType |
| | | from app.models.base_model import get_db |
| | |
| | | # token = get_dify_token(db, current_user.id) |
| | | try: |
| | | async def forward_to_dify(): |
| | | if chat_type == "imageTalk": |
| | | if agent.type == "imageTalk": |
| | | token = DfTokenDao(db).get_token_by_id(IMAGE_TO_TEXT) |
| | | if not token: |
| | | await websocket.send_json({"message": "Invalid token", "type": "error"}) |
| | |
| | | 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 == "reportWorkflow": |
| | | elif agent.type == "reportWorkflow": |
| | | |
| | | while True: |
| | | receive_message = await websocket.receive_json() |
| | | print(f"Received from client {chat_id}: {receive_message}") |
| | | upload_files = receive_message.get('upload_files', []) |
| | | upload_filenames = receive_message.get('upload_filenames', []) |
| | | title = receive_message.get('title', "") |
| | | sub_titles = receive_message.get('sub_titles', "") |
| | | workflow_type = receive_message.get('workflow', 1) |
| | |
| | | AgentType.DIFY, |
| | | current_user.id, |
| | | {"role": "user", "content": title if title else title_query, "type": workflow_type, |
| | | "is_clean": is_clean}, |
| | | "is_clean": is_clean, "upload_filenames":upload_filenames}, |
| | | workflow_type |
| | | ) |
| | | conversation_id = session.conversation_id |
| | |
| | | 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": |
| | | token = DfTokenDao(db).get_token_by_id(DOCUMENT_IA_QUESTIONS) |
| | | elif chat_type == "documentIa" or chat_type == "documentIaDs": |
| | | token_dict = { |
| | | "documentIa": DOCUMENT_IA_QUESTIONS, |
| | | "documentIaDs": DOCUMENT_IA_QUESTIONS_DS, |
| | | } |
| | | token = DfTokenDao(db).get_token_by_id(token_dict[chat_type]) |
| | | # print(token) |
| | | if not token: |
| | | await websocket.send_json({"message": "Invalid token", "type": "error"}) |
| | |
| | | receive_message = await websocket.receive_json() |
| | | print(f"Received from client {chat_id}: {receive_message}") |
| | | upload_file_id = receive_message.get('upload_file_id', []) |
| | | upload_filenames = receive_message.get('upload_filenames', []) |
| | | question = receive_message.get('message', "") |
| | | if not question and not image_url: |
| | | await websocket.send_json({"message": "Invalid request", "type": "error"}) |
| | |
| | | agent_id, |
| | | AgentType.DIFY, |
| | | current_user.id, |
| | | {"role": "user", "content": question} |
| | | {"role": "user", "content": question, "upload_filenames": upload_filenames} |
| | | ) |
| | | conversation_id = session.conversation_id |
| | | except Exception as e: |
| | |
| | | logger.error(data) |
| | | continue |
| | | elif isinstance(answer, dict): |
| | | if answer.get("status") == "failed": |
| | | message = answer.get("error", "") |
| | | else: |
| | | message = answer.get("title", "") |
| | | |
| | | message = answer.get("title", "") |
| | | |
| | | result = {"message": message, "type": "system"} |
| | | continue |
| | | result = {"message": message, "type": "system"} |
| | | # continue |
| | | elif data.get("event") == "message": # "event": "message_end" |
| | | # 正常输出 |
| | | answer = data.get("answer", "") |