智能体中心不显示自研智能体

zhaoqingang

2025-04-11 afc68af3a67b2f936429feb3a68c1f09e03ce930

 app/service/v2/chat.py

@@ -1,16 +1,28 @@
import asyncio
import datetime
import io
import json
import time
import uuid

import fitz
from fastapi import HTTPException
from sqlalchemy import or_

from Log import logger
from app.config.agent_base_url import RG_CHAT_DIALOG, DF_CHAT_AGENT, DF_CHAT_PARAMETERS, RG_CHAT_SESSIONS, \
    DF_CHAT_WORKFLOW
    DF_CHAT_WORKFLOW, DF_UPLOAD_FILE, RG_ORIGINAL_URL, RG_CHAT_UPDATE_URL, DF_WORKFLOW_DRAFT, DF_WORKFLOW_PUBLISH
from app.config.config import settings
from app.config.const import *
from app.models import DialogModel, ApiTokenModel
from app.models import DialogModel, ApiTokenModel, UserTokenModel, ComplexChatSessionDao, ChatDataRequest, \
    ComplexChatDao, KnowledgeModel, UserModel, KnowledgeUserModel
from app.models.v2.session_model import ChatSessionDao, ChatData
from app.service.v2.app_driver.chat_agent import ChatAgent
from app.service.v2.app_driver.chat_data import ChatBaseApply
from app.service.v2.app_driver.chat_dialog import ChatDialog
from app.service.v2.app_driver.chat_workflow import ChatWorkflow
from docx import Document
from dashscope import get_tokenizer  # dashscope版本 >= 1.14.0


async def update_session_log(db, session_id: str, message: dict, conversation_id: str):
@@ -23,15 +35,15 @@


async def add_session_log(db, session_id: str, question: str, chat_id: str, user_id, event_type: str,
                          conversation_id: str):
                          conversation_id: str, agent_type, query: dict = None):
    try:
        session = await ChatSessionDao(db).update_or_insert_by_id(
            session_id=session_id,
            name=question[:255],
            agent_id=chat_id,
            agent_type=1,
            agent_type=agent_type,
            tenant_id=user_id,
            message={"role": "user", "content": question},
            message={"role": "user", "content": question, "query": query},
            conversation_id=conversation_id,
            event_type=event_type
        )
@@ -41,11 +53,31 @@
    return None


async def get_app_token(db, app_id):
    app_token = db.query(UserTokenModel).filter_by(id=app_id).first()
    if app_token:
        return app_token.access_token
    return ""


async def get_chat_token(db, app_id):
    app_token = db.query(ApiTokenModel).filter_by(app_id=app_id).first()
    if app_token:
        return app_token.token
    return ""

async def get_workflow_token(db):
    user_token = db.query(UserTokenModel).filter(UserTokenModel.id == workflow_server).first()
    return user_token.access_token if user_token else ""


async def add_chat_token(db, data):
    try:
        api_token = ApiTokenModel(**data)
        db.add(api_token)
        db.commit()
    except Exception as e:
        logger.error(e)


async def get_chat_info(db, chat_id: str):
@@ -61,17 +93,49 @@
        return ChatAgent(), url


async def service_chat_dialog(db, chat_id: str, question: str, session_id: str, user_id, mode: str):
async def get_user_kb(db, user_id: int, kb_ids: list) -> list:
    res = []
    user = db.query(UserModel).filter(UserModel.id == user_id).first()
    if user is None:
        return res
    query = db.query(KnowledgeModel)
    if user.permission != "admin":
        klg_list = [j.id for i in user.groups for j in i.knowledges]
        for i in db.query(KnowledgeUserModel).filter(KnowledgeUserModel.user_id == user_id,
                                                     KnowledgeUserModel.status == 1).all():
            if i.kb_id not in klg_list:
                klg_list.append(i.kb_id)
        query = query.filter(or_(KnowledgeModel.id.in_(klg_list), KnowledgeModel.tenant_id == str(user_id)))
        kb_list = query.all()
        for kb in kb_list:
            if kb.id in kb_ids:
                if kb.permission == "team":
                    res.append(kb.id)
                elif kb.tenant_id == str(user_id):
                    res.append(kb.id)
        return res
    else:
        return kb_ids


async def service_chat_dialog(db, chat_id: str, question: str, session_id: str, user_id: int, mode: str, kb_ids: list):
    conversation_id = ""
    token = await get_chat_token(db, rg_api_token)
    url = settings.fwr_base_url + RG_CHAT_DIALOG.format(chat_id)
    kb_id = await get_user_kb(db, user_id, kb_ids)
    if not kb_id:
        yield "data: " + json.dumps({"message": smart_message_error,
                                     "error": "\n**ERROR**: The agent has no knowledge base to work with!",
                                     "status": http_400},
                                    ensure_ascii=False) + "\n\n"
        return
    chat = ChatDialog()
    session = await add_session_log(db, session_id, question, chat_id, user_id, mode, session_id)
    session = await add_session_log(db, session_id, question, chat_id, user_id, mode, session_id, RG_TYPE)
    if session:
        conversation_id = session.conversation_id
    message = {"role": "assistant", "answer": "", "reference": {}}
    try:
        async for ans in chat.chat_completions(url, await chat.request_data(question, conversation_id),
        async for ans in chat.chat_completions(url, await chat.complex_request_data(question, kb_id, conversation_id),
                                               await chat.get_headers(token)):
            data = {}
            error = ""
@@ -102,31 +166,54 @@
        logger.error(e)
        try:
            yield "data: " + json.dumps({"message": smart_message_error,
                                         "error": "**ERROR**: " + str(e), "status": http_500},
                                         "error": "\n**ERROR**: " + str(e), "status": http_500},
                                        ensure_ascii=False) + "\n\n"
        except:
            ...
    finally:
        message["role"] = "assistant"
        await update_session_log(db, session_id, message, conversation_id)


async def data_process(data):
    if isinstance(data, str):
        return data.replace("dify", "smart")
    elif isinstance(data, dict):
        for k in list(data.keys()):
            if isinstance(k, str) and "dify" in k:
                new_k = k.replace("dify", "smart")
                data[new_k] = await data_process(data[k])
                del data[k]
            else:
                data[k] = await data_process(data[k])
        return data
    elif isinstance(data, list):
        for i in range(len(data)):
            data[i] = await data_process(data[i])
        return data
    else:
        return data


async def service_chat_workflow(db, chat_id: str, chat_data: ChatData, session_id: str, user_id, mode: str):
    conversation_id = ""
    answer_event = ""
    answer_agent = ""
    answer_workflow = ""
    download_url = ""
    message_id = ""
    task_id = ""
    error = ""
    files = []
    node_list = []
    token = await get_chat_token(db, chat_id)

    chat, url = await get_chat_object(mode)
    if hasattr(chat_data, "query"):
        query = chat_data.query
    else:
        query = "start new workflow"
    session = await add_session_log(db, session_id, query, chat_id, user_id, mode, conversation_id)
        query = "start new conversation"
    session = await add_session_log(db, session_id, query if query else "start new conversation", chat_id, user_id,
                                    mode, conversation_id, DF_TYPE, chat_data.to_dict())
    if session:
        conversation_id = session.conversation_id
    try:
@@ -158,16 +245,26 @@
                event = smart_message_file
            elif ans.get("event") in [workflow_started, node_started, node_finished]:
                data = ans.get("data", {})
                data["inputs"] = []
                data["outputs"] = []
                data["inputs"] = await data_process(data.get("inputs", {}))
                data["outputs"] = await data_process(data.get("outputs", {}))
                data["files"] = await data_process(data.get("files", []))
                data["process_data"] = ""
                if data.get("status") == "failed":
                    status = http_500
                    error = data.get("error", "")
                node_list.append(ans)
                event = [smart_workflow_started, smart_node_started, smart_node_finished][
                    [workflow_started, node_started, node_finished].index(ans.get("event"))]
            elif ans.get("event") == workflow_finished:
                data = ans.get("data", {})
                answer_workflow = data.get("outputs", {}).get("output", data.get("outputs", {}).get("answer"))
                download_url = data.get("outputs", {}).get("download_url")
                event = smart_workflow_finished
                if data.get("status") == "failed":
                    status = http_500
                    error = data.get("error", "")
                node_list.append(ans)

            elif ans.get("event") == message_end:
                event = smart_message_end
            else:
@@ -182,18 +279,23 @@
        logger.error(e)
        try:
            yield "data: " + json.dumps({"message": smart_message_error,
                                         "error": "**ERROR**: " + str(e), "status": http_500},
                                         "error": "\n**ERROR**: " + str(e), "status": http_500},
                                        ensure_ascii=False) + "\n\n"
        except:
            ...
    finally:
        await update_session_log(db, session_id, {"role": "assistant", "answer": answer_event or answer_agent,
        await update_session_log(db, session_id, {"role": "assistant",
                                                  "answer": answer_event or answer_agent or answer_workflow or error,
                                                  "download_url": download_url,
                                                  "node_list": node_list, "task_id": task_id, "id": message_id,
                                                  "error": error}, conversation_id)


async def service_chat_basic(db, chat_id: str, question: str, session_id: str, user_id):
    ...
async def service_chat_basic(db, chat_id: str, chat_data: ChatData, session_id: str, user_id, mode: str):
    if chat_id == basic_report_talk:
        complex_chat = await ComplexChatDao(db).get_complex_chat_by_mode(chat_data.report_mode)
        if complex_chat:
            ...


async def service_chat_parameters(db, chat_id, user_id):
@@ -201,27 +303,523 @@
    if not chat_info:
        return {}
    return chat_info.parameters
    # if chat_info.dialog_type == RG_TYPE:
    #     return {"retriever_resource":
    #         {
    #             "enabled": True
    #         }
    #     }
    # elif chat_info.dialog_type == BASIC_TYPE:
    #     ...
    # elif chat_info.dialog_type == DF_TYPE:
    #     token = await get_chat_token(db, chat_id)
    #     if not token:
    #         return {}
    #     url = settings.dify_base_url + DF_CHAT_PARAMETERS
    #     chat = ChatBaseApply()
    #     return await chat.chat_get(url, {"user": str(user_id)}, await chat.get_headers(token))


async def service_chat_sessions(db, chat_id, name):
    token = await get_chat_token(db, rg_api_token)
    # print(token)
    if not token:
        return {}
    url = settings.fwr_base_url + RG_CHAT_SESSIONS.format(chat_id)
    chat = ChatDialog()
    return await chat.chat_sessions(url, {"name": name}, await chat.get_headers(token))


async def service_chat_sessions_list(db, chat_id, current, page_size, user_id, keyword):
    total, session_list = await ChatSessionDao(db).get_session_list(
        user_id=user_id,
        agent_id=chat_id,
        keyword=keyword,
        page=current,
        page_size=page_size
    )
    return json.dumps({"total": total, "rows": [session.to_dict() for session in session_list]})


async def service_chat_session_log(db, session_id):
    session_log = await ChatSessionDao(db).get_session_by_id(session_id)
    if not session_log:
        return {}
    log_info = session_log.log_to_json()
    if session_log.event_type == complex_chat:
        total, message_list = await ComplexChatSessionDao(db).get_session_list(session_id)
        log_info["message"] = [message.log_to_json() for message in message_list[::-1]]

    return json.dumps(log_info)


async def service_chat_upload(db, chat_id, file, user_id):
    files = []
    token = await get_chat_token(db, chat_id)
    if not token:
        return files
    url = settings.dify_base_url + DF_UPLOAD_FILE
    chat = ChatBaseApply()
    for f in file:
        try:
            file_content = await f.read()
            file_upload = await chat.chat_upload(url, {"file": (f.filename, file_content)}, {"user": str(user_id)},
                                                 {'Authorization': f'Bearer {token}'})
            try:
                tokens = await read_file(file_content, f.filename, f.content_type)
                file_upload["tokens"] = tokens
            except:
                ...
            files.append(file_upload)
        except Exception as e:
            logger.error(e)
    return json.dumps(files) if files else ""


async def get_str_token(input_str):
    # 获取tokenizer对象，目前只支持通义千问系列模型
    tokenizer = get_tokenizer('qwen-turbo')
    # 将字符串切分成token并转换为token id
    tokens = tokenizer.encode(input_str)
    return len(tokens)


async def read_pdf(pdf_stream):
    text = ""
    with fitz.open(stream=pdf_stream, filetype="pdf") as pdf_document:
        for page in pdf_document:
            text += page.get_text()
    return text


async def read_word(word_stream):
    # 使用 python-docx 打开 Word 文件流
    doc = Document(io.BytesIO(word_stream))

    # 提取每个段落的文本
    text = ""
    for para in doc.paragraphs:
        text += para.text

    return text


async def read_file(file, filename, content_type):
    text = ""
    if content_type == "application/pdf" or filename.endswith('.pdf'):

        # 提取 PDF 内容
        text = await read_pdf(file)
    elif content_type == "application/vnd.openxmlformats-officedocument.wordprocessingml.document" or filename.endswith(
            '.docx'):
        text = await read_word(file)

    return await get_str_token(text)


async def service_chunk_retrieval(query, knowledge_id, top_k, similarity_threshold, api_key):
    # print(query)

    try:
        request_data = json.loads(query)
        payload = {
            "question": request_data.get("query", ""),
            "dataset_ids": request_data.get("dataset_ids", []),
            "page_size": top_k,
            "similarity_threshold": similarity_threshold if similarity_threshold else 0.2
        }
    except json.JSONDecodeError as e:
        fixed_json = query.replace("'", '"')
        try:
            request_data = json.loads(fixed_json)
            payload = {
                "question": request_data.get("query", ""),
                "dataset_ids": request_data.get("dataset_ids", []),
                "page_size": top_k,
                "similarity_threshold": similarity_threshold if similarity_threshold else 0.2
            }
        except Exception:
            payload = {
                "question": query,
                "dataset_ids": [knowledge_id],
                "page_size": top_k,
                "similarity_threshold": similarity_threshold if similarity_threshold else 0.2
            }
    # print(payload)
    url = settings.fwr_base_url + RG_ORIGINAL_URL
    chat = ChatBaseApply()
    response = await  chat.chat_post(url, payload, await chat.get_headers(api_key))
    if not response:
        raise HTTPException(status_code=500, detail="服务异常！")
    records = [
        {
            "content": chunk["content"],
            "score": chunk["similarity"],
            "title": chunk.get("document_keyword", "Unknown Document"),
            "metadata": {"document_id": chunk["document_id"],
                         "path": f"{settings.fwr_base_url}/document/{chunk['document_id']}?ext={chunk.get('document_keyword').split('.')[-1]}&prefix=document",
                         'highlight': chunk.get("highlight"), "image_id": chunk.get("image_id"),
                         "positions": chunk.get("positions"), }
        }
        for chunk in response.get("data", {}).get("chunks", [])
    ]
    # print(len(records))
    # print(records)
    return records


async def service_base_chunk_retrieval(query, knowledge_id, top_k, similarity_threshold, api_key):
    # request_data = json.loads(query)
    payload = {
        "question": query,
        "dataset_ids": [knowledge_id],
        "page_size": top_k,
        "similarity_threshold": similarity_threshold
    }
    url = settings.fwr_base_url + RG_ORIGINAL_URL
    # url = "http://192.168.20.116:11080/" + RG_ORIGINAL_URL
    chat = ChatBaseApply()
    response = await chat.chat_post(url, payload, await chat.get_headers(api_key))
    if not response:
        raise HTTPException(status_code=500, detail="服务异常！")
    records = [
        {
            "content": chunk["content"],
            "score": chunk["similarity"],
            "title": chunk.get("document_keyword", "Unknown Document"),
            "metadata": {"document_id": chunk["document_id"]}
        }
        for chunk in response.get("data", {}).get("chunks", [])
    ]
    return records


async def add_complex_log(db, message_id, chat_id, session_id, chat_mode, query, user_id, mode, agent_type,
                          message_type, conversation_id="", node_data=None, query_data=None):
    if not node_data:
        node_data = []
    if not query_data:
        query_data = {}
    # print(node_data)
    # print("--------------------------------------------------------")
    # print(query_data)
    try:
        complex_log = ComplexChatSessionDao(db)
        if not conversation_id:
            session = await complex_log.get_session_by_session_id(session_id, chat_id)
            if session:
                conversation_id = session.conversation_id
        await complex_log.create_session(message_id,
                                         chat_id=chat_id,
                                         session_id=session_id,
                                         chat_mode=chat_mode,
                                         message_type=message_type,
                                         content=query,
                                         event_type=mode,
                                         tenant_id=user_id,
                                         conversation_id=conversation_id,
                                         node_data=json.dumps(node_data),
                                         query=json.dumps(query_data),
                                         agent_type=agent_type)
        return conversation_id, True

    except Exception as e:
        logger.error(e)
        return conversation_id, False


async def add_query_files(db, message_id):
    query = {}
    complex_log = await ComplexChatSessionDao(db).get_session_by_id(message_id)
    if complex_log:
        query = json.loads(complex_log.query)
    return query.get("files", [])


async def service_complex_chat(db, chat_id, mode, user_id, chat_request: ChatDataRequest):
    answer_event = ""
    answer_agent = ""
    answer_dialog = ""
    answer_workflow = ""
    download_url = ""
    message_id = ""
    task_id = ""
    error = ""
    node_list = []
    reference = {}
    conversation_id = ""
    query_data = chat_request.to_dict()
    new_message_id = str(uuid.uuid4())
    inputs = {"is_deep": chat_request.isDeep}
    files = chat_request.files
    if chat_request.chatMode == complex_content_optimization_chat:
        inputs["type"] = chat_request.optimizeType
    elif chat_request.chatMode == complex_dialog_chat:
        if not files and chat_request.parentId:
            files = await add_query_files(db, chat_request.parentId)
    if chat_request.chatMode != complex_content_optimization_chat:
        await add_session_log(db, chat_request.sessionId, chat_request.query if chat_request.query else "未命名会话",
                              chat_id, user_id,
                              mode, "", DF_TYPE)
        conversation_id, message = await add_complex_log(db, new_message_id, chat_id, chat_request.sessionId,
                                                         chat_request.chatMode, chat_request.query, user_id, mode,
                                                         DF_TYPE, 1, query_data=query_data)
        if not message:
            yield "data: " + json.dumps({"message": smart_message_error,
                                         "error": "\n**ERROR**: 创建会话失败！", "status": http_500},
                                        ensure_ascii=False) + "\n\n"
            return

    query_data["parentId"] = new_message_id
    try:
        if chat_request.chatMode == complex_knowledge_chat or chat_request.chatMode == complex_knowledge_chat_deep:
            if not conversation_id:
                session = await service_chat_sessions(db, chat_id, chat_request.query)
                # print(session)
                if not session or session.get("code") != 0:
                    yield "data: " + json.dumps(
                        {"message": smart_message_error, "error": "\n**ERROR**: chat agent error", "status": http_500})
                    return
                conversation_id = session.get("data", {}).get("id")
            token = await get_chat_token(db, rg_api_token)
            url = settings.fwr_base_url + RG_CHAT_DIALOG.format(chat_id)
            chat = ChatDialog()
            try:
                async for ans in chat.chat_completions(url, await chat.complex_request_data(chat_request.query,
                                                                                            chat_request.knowledgeId,
                                                                                            conversation_id),
                                                       await chat.get_headers(token)):
                    data = {}
                    error = ""
                    status = http_200
                    if ans.get("code", None) == 102:
                        error = ans.get("message", "error！")
                        status = http_400
                        event = smart_message_error
                    else:
                        if isinstance(ans.get("data"), bool) and ans.get("data") is True:
                            event = smart_message_end
                        else:
                            data = ans.get("data", {})
                            # conversation_id = data.get("session_id", "")
                            if "session_id" in data:
                                del data["session_id"]
                            data["prompt"] = ""
                            if not message_id:
                                message_id = data.get("id", "")
                            answer_dialog = data.get("answer", "")
                            reference = data.get("reference", {})
                            event = smart_message_cover
                    message_str = "data: " + json.dumps(
                        {"event": event, "data": data, "error": error, "status": status, "message_id": message_id,
                         "parent_id": new_message_id,
                         "session_id": chat_request.sessionId},
                        ensure_ascii=False) + "\n\n"
                    for i in range(0, len(message_str), max_chunk_size):
                        chunk = message_str[i:i + max_chunk_size]
                        # print(chunk)
                        yield chunk  # 发送分块消息
            except Exception as e:

                logger.error(e)
                try:
                    yield "data: " + json.dumps({"message": smart_message_error,
                                                 "error": "\n**ERROR**: " + str(e), "status": http_500},
                                                ensure_ascii=False) + "\n\n"
                except:
                    ...
        else:
            token = await get_chat_token(db, chat_id)
            chat, url = await get_chat_object(mode)
            async for ans in chat.chat_completions(url,
                                                   await chat.complex_request_data(chat_request.query, conversation_id,
                                                                                   str(user_id), files=files,
                                                                                   inputs=inputs),
                                                   await chat.get_headers(token)):
                # print(ans)
                data = {}
                status = http_200
                conversation_id = ans.get("conversation_id")
                task_id = ans.get("task_id")
                if ans.get("event") == message_error:
                    error = ans.get("message", "参数异常！")
                    status = http_400
                    event = smart_message_error
                elif ans.get("event") == message_agent:
                    data = {"answer": ans.get("answer", ""), "id": ans.get("message_id", "")}
                    answer_agent += ans.get("answer", "")
                    message_id = ans.get("message_id", "")
                    event = smart_message_stream
                elif ans.get("event") == message_event:
                    data = {"answer": ans.get("answer", ""), "id": ans.get("message_id", "")}
                    answer_event += ans.get("answer", "")
                    message_id = ans.get("message_id", "")
                    event = smart_message_stream
                elif ans.get("event") == message_file:
                    data = {"url": ans.get("url", ""), "id": ans.get("id", ""),
                            "type": ans.get("type", "")}
                    files.append(data)
                    event = smart_message_file
                elif ans.get("event") in [workflow_started, node_started, node_finished]:
                    data = ans.get("data", {})
                    data["inputs"] = await data_process(data.get("inputs", {}))
                    data["outputs"] = await data_process(data.get("outputs", {}))
                    data["files"] = await data_process(data.get("files", []))
                    data["process_data"] = ""
                    if data.get("status") == "failed":
                        status = http_500
                        error = data.get("error", "")
                    node_list.append(ans)
                    event = [smart_workflow_started, smart_node_started, smart_node_finished][
                        [workflow_started, node_started, node_finished].index(ans.get("event"))]
                elif ans.get("event") == workflow_finished:
                    data = ans.get("data", {})
                    answer_workflow = data.get("outputs", {}).get("output", data.get("outputs", {}).get("answer"))
                    download_url = data.get("outputs", {}).get("download_url")
                    event = smart_workflow_finished
                    if data.get("status") == "failed":
                        status = http_500
                        error = data.get("error", "")
                    node_list.append(ans)

                elif ans.get("event") == message_end:
                    event = smart_message_end
                else:
                    continue

                yield "data: " + json.dumps(
                    {"event": event, "data": data, "error": error, "status": status, "task_id": task_id,
                     "message_id": message_id,
                     "parent_id": new_message_id,
                     "session_id": chat_request.sessionId},
                    ensure_ascii=False) + "\n\n"

    except Exception as e:
        logger.error(e)
        try:
            yield "data: " + json.dumps({"message": smart_message_error,
                                         "error": "\n**ERROR**: " + str(e), "status": http_500},
                                        ensure_ascii=False) + "\n\n"
        except:
            ...
    finally:
        # await update_session_log(db, session_id, {"role": "assistant",
        #                                           "answer": answer_event or answer_agent or answer_workflow or error,
        #                                           "download_url": download_url,
        #                                           "node_list": node_list, "task_id": task_id, "id": message_id,
        #                                           "error": error}, conversation_id)
        if message_id:
            await add_complex_log(db, message_id, chat_id, chat_request.sessionId, chat_request.chatMode,
                                  answer_event or answer_agent or answer_workflow or answer_dialog or error, user_id,
                                  mode, DF_TYPE, 2, conversation_id, node_data=node_list or reference,
                                  query_data=query_data)


async def service_complex_upload(db, chat_id, file, user_id):
    files = []
    token = await get_chat_token(db, chat_id)
    if not token:
        return files
    url = settings.dify_base_url + DF_UPLOAD_FILE
    chat = ChatBaseApply()
    for f in file:
        try:
            file_content = await f.read()
            file_upload = await chat.chat_upload(url, {"file": (f.filename, file_content)}, {"user": str(user_id)},
                                                 {'Authorization': f'Bearer {token}'})
            # try:
            #     tokens = await read_file(file_content, f.filename, f.content_type)
            #     file_upload["tokens"] = tokens
            # except:
            #     ...
            files.append(file_upload)
        except Exception as e:
            logger.error(e)
    return json.dumps(files) if files else ""


async def service_complex_model(db, chat_type, model_type, model_name, model_provider):
    if chat_type == 1 and model_type == 1:
        return await set_dialog_model(db, complex_knowledge_chat, model_name,model_provider)
    elif chat_type == 1 and model_type == 2:
        return await set_dialog_model(db, complex_knowledge_chat_deep, model_name, model_provider)
    else:
        if model_type == 1:
            chats = [complex_dialog_chat, complex_network_chat, complex_mindmap_chat, complex_content_optimization_chat]
        else:
            chats = [complex_dialog_chat, complex_network_chat]
        return await set_workflow_model(db,chats
            , # , complex_network_chat, complex_mindmap_chat, complex_content_optimization_chat
            model_type, model_name, model_provider)


async def set_dialog_model(db, chat_mode, model_name, model_provider):
    chat = await ComplexChatDao(db).get_complex_chat_by_mode(chat_mode)
    if chat:
        access_token = await get_chat_token(db, rg_api_token)
        url = settings.fwr_base_url + RG_CHAT_UPDATE_URL.format(chat.id)
        chat_base = ChatBaseApply()
        payload = {
            "name": chat.name,
            "llm": {
                "model_name": model_name
            }
        }
        response = await  chat_base.chat_put(url, payload, await chat_base.get_headers(access_token))
        # print(response)
        if not response:
            return "服务异常,修改失败！"
        await ComplexChatDao(db).update_complex_chat_by_id(chat.id, {"chat_model": model_name, "chat_model_ds": model_name, "chat_provider": model_provider, "update_date": datetime.datetime.now()})
        return ""

async def set_workflow_model(db, chat_modes, model_type, model_name, model_provider):
    chat_base = ChatBaseApply()
    token = await get_workflow_token(db)
    for chat_mode in chat_modes:
        chat = await ComplexChatDao(db).get_complex_chat_by_mode(chat_mode)
        if chat:

            get_draft_url = settings.dify_base_url + DF_WORKFLOW_DRAFT.format(chat.id)
            draft_data = await chat_base.chat_get(get_draft_url, {}, await chat_base.get_headers(token))
            if draft_data:
                graph = draft_data.get("graph")
                for node in graph.get("nodes"):
                    if node.get("data", {}).get("type") == "llm":
                        if model_type == 1 and "深度搜索" not in node.get("data", {}).get("title"):
                            node["data"]["model"]["name"] = model_name
                            node["data"]["model"]["provider"] = model_provider
                        elif model_type == 2 and "深度搜索" in node.get("data", {}).get("title"):
                            node["data"]["model"]["name"] = model_name
                            node["data"]["model"]["provider"] = model_provider

                draft_data_query = {"conversation_variables": draft_data.get("conversation_variables"),
                                    "environment_variables": draft_data.get("environment_variables"),
                                    "hash": draft_data.get("hash"),
                                    "features": draft_data.get("features"),
                                    "graph": graph}
                set_draft_data = await chat_base.chat_post(get_draft_url, draft_data_query, await chat_base.get_headers(token))
                if set_draft_data and set_draft_data.get("result") == "success":
                    publish_url = settings.dify_base_url + DF_WORKFLOW_PUBLISH.format(chat.id)
                    publish_data = await chat_base.chat_post(publish_url, {}, await chat_base.get_headers(token))
                    if publish_data and publish_data.get("result") == "success":
                        update_kwargs = {"chat_provider": model_provider, "update_date": datetime.datetime.now()}
                        if model_type == 1:
                            update_kwargs["chat_model"] = model_name
                        else:
                            update_kwargs["chat_model_ds"] = model_name
                        await ComplexChatDao(db).update_complex_chat_by_id(chat.id, update_kwargs)


async def service_get_complex_model(db):
    res = {}
    for complexs in await ComplexChatDao(db).aget_complex_chat():
        if complexs.chat_mode == complex_knowledge_chat:
            res["dialog"] = {"modelName": complexs.chat_model, "modelProvider": complexs.chat_provider}
        elif complexs.chat_mode == complex_knowledge_chat_deep:
            res["dialog_ds"] = {"modelName": complexs.chat_model_ds, "modelProvider": complexs.chat_provider}
        else:
            res["workflow"] = {"modelName": complexs.chat_model, "modelProvider": complexs.chat_provider}
            res["workflow_ds"] = {"modelName": complexs.chat_model_ds, "modelProvider": complexs.chat_provider}

    return json.dumps(res)

if __name__ == "__main__":
    q = json.dumps({"query": "设备", "dataset_ids": ["fc68db52f43111efb94a0242ac120004"]})
    top_k = 2
    similarity_threshold = 0.5
    api_key = "ragflow-Y4MGYwY2JlZjM2YjExZWY4ZWU5MDI0Mm"


    # a = service_chunk_retrieval(q, top_k, similarity_threshold, api_key)
    # print(a)
    async def a():
        b = await service_chunk_retrieval(q, top_k, similarity_threshold, api_key)
        print(b)


    asyncio.run(a())