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import re |
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import json |
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from copy import deepcopy |
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from uuid import uuid4 |
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from api.db import LLMType |
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from flask import request, Response |
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from api.db.services.dialog_service import ask |
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from agent.canvas import Canvas |
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from api.db import StatusEnum |
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from api.db.db_models import API4Conversation |
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from api.db.services.api_service import API4ConversationService |
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from api.db.services.canvas_service import UserCanvasService |
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from api.db.services.dialog_service import DialogService, ConversationService, chat |
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from api.db.services.knowledgebase_service import KnowledgebaseService |
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from api.utils import get_uuid |
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from api.utils.api_utils import get_error_data_result |
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from api.utils.api_utils import get_result, token_required |
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from api.db.services.llm_service import LLMBundle |
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@manager.route('/chats/<chat_id>/sessions', methods=['POST']) |
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@token_required |
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def create(tenant_id,chat_id): |
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req = request.json |
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req["dialog_id"] = chat_id |
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dia = DialogService.query(tenant_id=tenant_id, id=req["dialog_id"], status=StatusEnum.VALID.value) |
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if not dia: |
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return get_error_data_result(message="You do not own the assistant.") |
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conv = { |
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"id": get_uuid(), |
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"dialog_id": req["dialog_id"], |
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"name": req.get("name", "New session"), |
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"message": [{"role": "assistant", "content": "Hi! I am your assistant,can I help you?"}] |
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} |
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if not conv.get("name"): |
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return get_error_data_result(message="`name` can not be empty.") |
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ConversationService.save(**conv) |
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e, conv = ConversationService.get_by_id(conv["id"]) |
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if not e: |
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return get_error_data_result(message="Fail to create a session!") |
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conv = conv.to_dict() |
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conv['messages'] = conv.pop("message") |
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conv["chat_id"] = conv.pop("dialog_id") |
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del conv["reference"] |
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return get_result(data=conv) |
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@manager.route('/agents/<agent_id>/sessions', methods=['POST']) |
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@token_required |
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def create_agent_session(tenant_id, agent_id): |
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req = request.json |
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e, cvs = UserCanvasService.get_by_id(agent_id) |
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if not e: |
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return get_error_data_result("Agent not found.") |
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if cvs.user_id != tenant_id: |
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return get_error_data_result(message="You do not own the agent.") |
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if not isinstance(cvs.dsl, str): |
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cvs.dsl = json.dumps(cvs.dsl, ensure_ascii=False) |
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canvas = Canvas(cvs.dsl, tenant_id) |
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conv = { |
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"id": get_uuid(), |
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"dialog_id": cvs.id, |
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"user_id": req.get("usr_id","") if isinstance(req, dict) else "", |
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"message": [{"role": "assistant", "content": canvas.get_prologue()}], |
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"source": "agent", |
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"dsl":json.loads(cvs.dsl) |
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} |
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API4ConversationService.save(**conv) |
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conv["agent_id"] = conv.pop("dialog_id") |
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return get_result(data=conv) |
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@manager.route('/chats/<chat_id>/sessions/<session_id>', methods=['PUT']) |
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@token_required |
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def update(tenant_id,chat_id,session_id): |
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req = request.json |
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req["dialog_id"] = chat_id |
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conv_id = session_id |
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conv = ConversationService.query(id=conv_id,dialog_id=chat_id) |
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if not conv: |
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return get_error_data_result(message="Session does not exist") |
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if not DialogService.query(id=chat_id, tenant_id=tenant_id, status=StatusEnum.VALID.value): |
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return get_error_data_result(message="You do not own the session") |
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if "message" in req or "messages" in req: |
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return get_error_data_result(message="`message` can not be change") |
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if "reference" in req: |
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return get_error_data_result(message="`reference` can not be change") |
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if "name" in req and not req.get("name"): |
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return get_error_data_result(message="`name` can not be empty.") |
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if not ConversationService.update_by_id(conv_id, req): |
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return get_error_data_result(message="Session updates error") |
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return get_result() |
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@manager.route('/chats/<chat_id>/completions', methods=['POST']) |
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@token_required |
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def completion(tenant_id, chat_id): |
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req = request.json |
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if not req.get("session_id"): |
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conv = { |
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"id": get_uuid(), |
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"dialog_id": chat_id, |
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"name": req.get("name", "New session"), |
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"message": [{"role": "assistant", "content": "Hi! I am your assistant,can I help you?"}] |
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} |
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if not conv.get("name"): |
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return get_error_data_result(message="`name` can not be empty.") |
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ConversationService.save(**conv) |
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e, conv = ConversationService.get_by_id(conv["id"]) |
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session_id=conv.id |
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else: |
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session_id = req.get("session_id") |
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if not req.get("question"): |
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return get_error_data_result(message="Please input your question.") |
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conv = ConversationService.query(id=session_id,dialog_id=chat_id) |
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if not conv: |
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return get_error_data_result(message="Session does not exist") |
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conv = conv[0] |
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if not DialogService.query(id=chat_id, tenant_id=tenant_id, status=StatusEnum.VALID.value): |
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return get_error_data_result(message="You do not own the chat") |
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msg = [] |
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question = { |
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"content": req.get("question"), |
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"role": "user", |
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"id": str(uuid4()) |
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} |
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conv.message.append(question) |
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for m in conv.message: |
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if m["role"] == "system": continue |
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if m["role"] == "assistant" and not msg: continue |
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msg.append(m) |
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message_id = msg[-1].get("id") |
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e, dia = DialogService.get_by_id(conv.dialog_id) |
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if not conv.reference: |
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conv.reference = [] |
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conv.message.append({"role": "assistant", "content": "", "id": message_id}) |
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conv.reference.append({"chunks": [], "doc_aggs": []}) |
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|
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def fillin_conv(ans): |
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reference = ans["reference"] |
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temp_reference = deepcopy(ans["reference"]) |
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nonlocal conv, message_id |
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if not conv.reference: |
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conv.reference.append(temp_reference) |
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else: |
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conv.reference[-1] = temp_reference |
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conv.message[-1] = {"role": "assistant", "content": ans["answer"], |
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"id": message_id, "prompt": ans.get("prompt", "")} |
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if "chunks" in reference: |
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chunks = reference.get("chunks") |
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chunk_list = [] |
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for chunk in chunks: |
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new_chunk = { |
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"id": chunk["chunk_id"], |
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"content": chunk["content_with_weight"], |
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"document_id": chunk["doc_id"], |
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"document_name": chunk["docnm_kwd"], |
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"dataset_id": chunk["kb_id"], |
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"image_id": chunk.get("image_id", ""), |
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"similarity": chunk["similarity"], |
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"vector_similarity": chunk["vector_similarity"], |
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"term_similarity": chunk["term_similarity"], |
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"positions": chunk.get("positions", []), |
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} |
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chunk_list.append(new_chunk) |
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reference["chunks"] = chunk_list |
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ans["id"] = message_id |
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ans["session_id"]=session_id |
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|
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def stream(): |
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nonlocal dia, msg, req, conv |
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try: |
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for ans in chat(dia, msg, **req): |
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fillin_conv(ans) |
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yield "data:" + json.dumps({"code": 0, "data": ans}, ensure_ascii=False) + "\n\n" |
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ConversationService.update_by_id(conv.id, conv.to_dict()) |
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except Exception as e: |
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yield "data:" + json.dumps({"code": 500, "message": str(e), |
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"data": {"answer": "**ERROR**: " + str(e),"reference": []}}, |
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ensure_ascii=False) + "\n\n" |
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yield "data:" + json.dumps({"code": 0, "data": True}, ensure_ascii=False) + "\n\n" |
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|
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if req.get("stream", True): |
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resp = Response(stream(), mimetype="text/event-stream") |
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resp.headers.add_header("Cache-control", "no-cache") |
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resp.headers.add_header("Connection", "keep-alive") |
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resp.headers.add_header("X-Accel-Buffering", "no") |
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resp.headers.add_header("Content-Type", "text/event-stream; charset=utf-8") |
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|
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return resp |
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|
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else: |
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answer = None |
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for ans in chat(dia, msg, **req): |
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answer = ans |
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fillin_conv(ans) |
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ConversationService.update_by_id(conv.id, conv.to_dict()) |
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break |
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return get_result(data=answer) |
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@manager.route('/agents/<agent_id>/completions', methods=['POST']) |
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@token_required |
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def agent_completion(tenant_id, agent_id): |
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req = request.json |
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|
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e, cvs = UserCanvasService.get_by_id(agent_id) |
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if not e: |
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return get_error_data_result("Agent not found.") |
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if cvs.user_id != tenant_id: |
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return get_error_data_result(message="You do not own the agent.") |
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if not isinstance(cvs.dsl, str): |
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cvs.dsl = json.dumps(cvs.dsl, ensure_ascii=False) |
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canvas = Canvas(cvs.dsl, tenant_id) |
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|
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if not req.get("session_id"): |
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session_id = get_uuid() |
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conv = { |
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"id": session_id, |
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"dialog_id": cvs.id, |
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"user_id": req.get("user_id", ""), |
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"message": [{"role": "assistant", "content": canvas.get_prologue()}], |
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"source": "agent", |
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"dsl": json.loads(cvs.dsl) |
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} |
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API4ConversationService.save(**conv) |
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conv = API4Conversation(**conv) |
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else: |
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session_id = req.get("session_id") |
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e, conv = API4ConversationService.get_by_id(req["session_id"]) |
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if not e: |
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return get_error_data_result(message="Session not found!") |
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canvas = Canvas(json.dumps(conv.dsl), tenant_id) |
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|
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messages = conv.message |
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question = req.get("question") |
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if not question: |
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return get_error_data_result("`question` is required.") |
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question = { |
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"role": "user", |
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"content": question, |
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"id": str(uuid4()) |
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} |
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messages.append(question) |
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msg = [] |
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for m in messages: |
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if m["role"] == "system": |
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continue |
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if m["role"] == "assistant" and not msg: |
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continue |
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msg.append(m) |
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if not msg[-1].get("id"): msg[-1]["id"] = get_uuid() |
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message_id = msg[-1]["id"] |
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|
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stream = req.get("stream", True) |
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|
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def fillin_conv(ans): |
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reference = ans["reference"] |
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print(reference,flush=True) |
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temp_reference = deepcopy(ans["reference"]) |
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nonlocal conv, message_id |
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if not conv.reference: |
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conv.reference.append(temp_reference) |
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else: |
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conv.reference[-1] = temp_reference |
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conv.message[-1] = {"role": "assistant", "content": ans["answer"], "id": message_id} |
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if "chunks" in reference: |
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chunks = reference.get("chunks") |
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chunk_list = [] |
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for chunk in chunks: |
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new_chunk = { |
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"id": chunk["chunk_id"], |
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"content": chunk["content_with_weight"], |
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"document_id": chunk["doc_id"], |
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"document_name": chunk["docnm_kwd"], |
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"dataset_id": chunk["kb_id"], |
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"image_id": chunk["image_id"], |
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"similarity": chunk["similarity"], |
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"vector_similarity": chunk["vector_similarity"], |
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"term_similarity": chunk["term_similarity"], |
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"positions": chunk["positions"], |
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} |
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chunk_list.append(new_chunk) |
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reference["chunks"] = chunk_list |
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ans["id"] = message_id |
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ans["session_id"] = session_id |
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|
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def rename_field(ans): |
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reference = ans['reference'] |
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if not isinstance(reference, dict): |
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return |
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for chunk_i in reference.get('chunks', []): |
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if 'docnm_kwd' in chunk_i: |
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chunk_i['doc_name'] = chunk_i['docnm_kwd'] |
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chunk_i.pop('docnm_kwd') |
|
|
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if not conv.reference: |
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conv.reference = [] |
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conv.message.append({"role": "assistant", "content": "", "id": message_id}) |
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conv.reference.append({"chunks": [], "doc_aggs": []}) |
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|
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final_ans = {"reference": [], "content": ""} |
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|
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canvas.add_user_input(msg[-1]["content"]) |
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|
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if stream: |
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def sse(): |
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nonlocal answer, cvs |
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try: |
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for ans in canvas.run(stream=stream): |
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if ans.get("running_status"): |
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yield "data:" + json.dumps({"code": 0, "message": "", |
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"data": {"answer": ans["content"], |
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"running_status": True}}, |
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ensure_ascii=False) + "\n\n" |
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continue |
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for k in ans.keys(): |
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final_ans[k] = ans[k] |
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ans = {"answer": ans["content"], "reference": ans.get("reference", [])} |
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fillin_conv(ans) |
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rename_field(ans) |
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yield "data:" + json.dumps({"code": 0, "message": "", "data": ans}, |
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ensure_ascii=False) + "\n\n" |
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|
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canvas.messages.append({"role": "assistant", "content": final_ans["content"], "id": message_id}) |
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canvas.history.append(("assistant", final_ans["content"])) |
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if final_ans.get("reference"): |
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canvas.reference.append(final_ans["reference"]) |
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conv.dsl = json.loads(str(canvas)) |
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API4ConversationService.append_message(conv.id, conv.to_dict()) |
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except Exception as e: |
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conv.dsl = json.loads(str(canvas)) |
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API4ConversationService.append_message(conv.id, conv.to_dict()) |
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yield "data:" + json.dumps({"code": 500, "message": str(e), |
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"data": {"answer": "**ERROR**: " + str(e), "reference": []}}, |
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ensure_ascii=False) + "\n\n" |
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yield "data:" + json.dumps({"code": 0, "message": "", "data": True}, ensure_ascii=False) + "\n\n" |
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|
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resp = Response(sse(), mimetype="text/event-stream") |
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resp.headers.add_header("Cache-control", "no-cache") |
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resp.headers.add_header("Connection", "keep-alive") |
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resp.headers.add_header("X-Accel-Buffering", "no") |
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resp.headers.add_header("Content-Type", "text/event-stream; charset=utf-8") |
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return resp |
|
|
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for answer in canvas.run(stream=False): |
|
if answer.get("running_status"): continue |
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final_ans["content"] = "\n".join(answer["content"]) if "content" in answer else "" |
|
canvas.messages.append({"role": "assistant", "content": final_ans["content"], "id": message_id}) |
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if final_ans.get("reference"): |
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canvas.reference.append(final_ans["reference"]) |
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conv.dsl = json.loads(str(canvas)) |
|
|
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result = {"answer": final_ans["content"], "reference": final_ans.get("reference", [])} |
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fillin_conv(result) |
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API4ConversationService.append_message(conv.id, conv.to_dict()) |
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rename_field(result) |
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return get_result(data=result) |
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|
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@manager.route('/chats/<chat_id>/sessions', methods=['GET']) |
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@token_required |
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def list_session(chat_id,tenant_id): |
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if not DialogService.query(tenant_id=tenant_id, id=chat_id, status=StatusEnum.VALID.value): |
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return get_error_data_result(message=f"You don't own the assistant {chat_id}.") |
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id = request.args.get("id") |
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name = request.args.get("name") |
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page_number = int(request.args.get("page", 1)) |
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items_per_page = int(request.args.get("page_size", 30)) |
|
orderby = request.args.get("orderby", "create_time") |
|
if request.args.get("desc") == "False" or request.args.get("desc") == "false": |
|
desc = False |
|
else: |
|
desc = True |
|
convs = ConversationService.get_list(chat_id,page_number,items_per_page,orderby,desc,id,name) |
|
if not convs: |
|
return get_result(data=[]) |
|
for conv in convs: |
|
conv['messages'] = conv.pop("message") |
|
infos = conv["messages"] |
|
for info in infos: |
|
if "prompt" in info: |
|
info.pop("prompt") |
|
conv["chat_id"] = conv.pop("dialog_id") |
|
if conv["reference"]: |
|
messages = conv["messages"] |
|
message_num = 0 |
|
chunk_num = 0 |
|
while message_num < len(messages): |
|
if message_num != 0 and messages[message_num]["role"] != "user": |
|
chunk_list = [] |
|
if "chunks" in conv["reference"][chunk_num]: |
|
chunks = conv["reference"][chunk_num]["chunks"] |
|
for chunk in chunks: |
|
new_chunk = { |
|
"id": chunk["chunk_id"], |
|
"content": chunk["content_with_weight"], |
|
"document_id": chunk["doc_id"], |
|
"document_name": chunk["docnm_kwd"], |
|
"dataset_id": chunk["kb_id"], |
|
"image_id": chunk.get("image_id", ""), |
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"similarity": chunk["similarity"], |
|
"vector_similarity": chunk["vector_similarity"], |
|
"term_similarity": chunk["term_similarity"], |
|
"positions": chunk["positions"], |
|
} |
|
chunk_list.append(new_chunk) |
|
chunk_num += 1 |
|
messages[message_num]["reference"] = chunk_list |
|
message_num += 1 |
|
del conv["reference"] |
|
return get_result(data=convs) |
|
|
|
|
|
@manager.route('/chats/<chat_id>/sessions', methods=["DELETE"]) |
|
@token_required |
|
def delete(tenant_id,chat_id): |
|
if not DialogService.query(id=chat_id, tenant_id=tenant_id, status=StatusEnum.VALID.value): |
|
return get_error_data_result(message="You don't own the chat") |
|
req = request.json |
|
convs = ConversationService.query(dialog_id=chat_id) |
|
if not req: |
|
ids = None |
|
else: |
|
ids=req.get("ids") |
|
|
|
if not ids: |
|
conv_list = [] |
|
for conv in convs: |
|
conv_list.append(conv.id) |
|
else: |
|
conv_list=ids |
|
for id in conv_list: |
|
conv = ConversationService.query(id=id,dialog_id=chat_id) |
|
if not conv: |
|
return get_error_data_result(message="The chat doesn't own the session") |
|
ConversationService.delete_by_id(id) |
|
return get_result() |
|
|
|
@manager.route('/sessions/ask', methods=['POST']) |
|
@token_required |
|
def ask_about(tenant_id): |
|
req = request.json |
|
if not req.get("question"): |
|
return get_error_data_result("`question` is required.") |
|
if not req.get("dataset_ids"): |
|
return get_error_data_result("`dataset_ids` is required.") |
|
if not isinstance(req.get("dataset_ids"),list): |
|
return get_error_data_result("`dataset_ids` should be a list.") |
|
req["kb_ids"]=req.pop("dataset_ids") |
|
for kb_id in req["kb_ids"]: |
|
if not KnowledgebaseService.accessible(kb_id,tenant_id): |
|
return get_error_data_result(f"You don't own the dataset {kb_id}.") |
|
kbs = KnowledgebaseService.query(id=kb_id) |
|
kb = kbs[0] |
|
if kb.chunk_num == 0: |
|
return get_error_data_result(f"The dataset {kb_id} doesn't own parsed file") |
|
uid = tenant_id |
|
def stream(): |
|
nonlocal req, uid |
|
try: |
|
for ans in ask(req["question"], req["kb_ids"], uid): |
|
yield "data:" + json.dumps({"code": 0, "message": "", "data": ans}, ensure_ascii=False) + "\n\n" |
|
except Exception as e: |
|
yield "data:" + json.dumps({"code": 500, "message": str(e), |
|
"data": {"answer": "**ERROR**: " + str(e), "reference": []}}, |
|
ensure_ascii=False) + "\n\n" |
|
yield "data:" + json.dumps({"code": 0, "message": "", "data": True}, ensure_ascii=False) + "\n\n" |
|
|
|
resp = Response(stream(), mimetype="text/event-stream") |
|
resp.headers.add_header("Cache-control", "no-cache") |
|
resp.headers.add_header("Connection", "keep-alive") |
|
resp.headers.add_header("X-Accel-Buffering", "no") |
|
resp.headers.add_header("Content-Type", "text/event-stream; charset=utf-8") |
|
return resp |
|
|
|
|
|
@manager.route('/sessions/related_questions', methods=['POST']) |
|
@token_required |
|
def related_questions(tenant_id): |
|
req = request.json |
|
if not req.get("question"): |
|
return get_error_data_result("`question` is required.") |
|
question = req["question"] |
|
chat_mdl = LLMBundle(tenant_id, LLMType.CHAT) |
|
prompt = """ |
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Objective: To generate search terms related to the user's search keywords, helping users find more valuable information. |
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Instructions: |
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- Based on the keywords provided by the user, generate 5-10 related search terms. |
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- Each search term should be directly or indirectly related to the keyword, guiding the user to find more valuable information. |
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- Use common, general terms as much as possible, avoiding obscure words or technical jargon. |
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- Keep the term length between 2-4 words, concise and clear. |
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- DO NOT translate, use the language of the original keywords. |
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### Example: |
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Keywords: Chinese football |
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Related search terms: |
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1. Current status of Chinese football |
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2. Reform of Chinese football |
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3. Youth training of Chinese football |
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4. Chinese football in the Asian Cup |
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5. Chinese football in the World Cup |
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Reason: |
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- When searching, users often only use one or two keywords, making it difficult to fully express their information needs. |
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- Generating related search terms can help users dig deeper into relevant information and improve search efficiency. |
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- At the same time, related terms can also help search engines better understand user needs and return more accurate search results. |
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""" |
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ans = chat_mdl.chat(prompt, [{"role": "user", "content": f""" |
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Keywords: {question} |
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Related search terms: |
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"""}], {"temperature": 0.9}) |
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return get_result(data=[re.sub(r"^[0-9]\. ", "", a) for a in ans.split("\n") if re.match(r"^[0-9]\. ", a)]) |
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