CodeGeeX4/repodemo/run_local.py

import chainlit as cl
from chainlit.input_widget import Slider
from llm.api.codegeex4 import codegeex4
from prompts.base_prompt import judge_task_prompt,get_cur_base_user_prompt,web_judge_task_prompt
from utils.tools import unzip_file,get_project_files_with_content
from utils.bingsearch import bing_search_prompt
from llm.local.codegeex4 import CodegeexChatModel
local_model_path = '<your_local_model_path>'
llm = CodegeexChatModel(local_model_path)

class StreamProcessor:
    def __init__(self):
        self.previous_str = ""

    def get_new_part(self, new_str):
        new_part = new_str[len(self.previous_str):]
        self.previous_str = new_str
        return new_part

@cl.set_chat_profiles
async def chat_profile():
    return [
        cl.ChatProfile(
            name="chat聊天",
            markdown_description="聊天demo：支持多轮对话。",
            starters = [
                cl.Starter(
                label="请你用python写一个快速排序。",
                message="请你用python写一个快速排序。",
               
                ),

            cl.Starter(
                label="请你介绍一下自己。",
                message="请你介绍一下自己。",
               
                ),
            cl.Starter(
                label="用 Python 编写一个脚本来自动发送每日电子邮件报告，并指导我如何进行设置。",
                message="用 Python 编写一个脚本来自动发送每日电子邮件报告，并指导我如何进行设置。",
                
                ),
            cl.Starter(
                label="我是一个python初学者，请你告诉我怎么才能学好python。",
                message="我是一个python初学者，请你告诉我怎么才能学好python。",
                
                )
            ]
      
        ),
        cl.ChatProfile(
            name="联网问答",
            markdown_description="联网能力dome：支持联网回答用户问题。",
            
        ),
        cl.ChatProfile(
            name="上传本地项目",
            markdown_description="项目级能力dome：支持上传本地zip压缩包项目，可以进行项目问答和对项目进行修改。",
            
        )
    ]

    
@cl.on_chat_start
async def start():
    settings = await cl.ChatSettings(
        [
            Slider(
                id="temperature",
                label="CodeGeeX4 - Temperature",
                initial=0.2,
                min=0,
                max=1,
                step=0.1,
            ),
            Slider(
                id="top_p",
                label="CodeGeeX4 - top_p",
                initial=0.95,
                min=0,
                max=1,
                step=0.1,
            ),
        ]
    ).send()
    temperature = settings["temperature"]
    top_p = settings["top_p"]
    cl.user_session.set('temperature',temperature)
    cl.user_session.set('top_p',top_p)
    cl.user_session.set(
        "message_history",
        []
    )
    chat_profile = cl.user_session.get("chat_profile")
    extract_dir = 'repodata'
    if chat_profile == "chat聊天":
        pass
    elif chat_profile =="上传本地项目":
        files = None
        while files == None:
            files = await cl.AskFileMessage(
                content="请上传项目zip压缩文件!", accept={"application/zip": [".zip"]},max_size_mb=50
            ).send()

        text_file = files[0]
        extracted_path = unzip_file(text_file.path,extract_dir)
        files_list = get_project_files_with_content(extracted_path)
        cl.user_session.set("project_index",files_list)
        if len(files_list)>0:
            await cl.Message(
                content=f"已成功上传，您可以开始对项目进行提问！",
            ).send()
    
    

@cl.on_message
async def main(message: cl.Message):
    chat_profile = cl.user_session.get("chat_profile")
    message_history = cl.user_session.get("message_history")
    message_history.append({"role": "user", "content": message.content})
    if chat_profile == "chat聊天":
        prompt_content = get_cur_base_user_prompt(message_history=message_history)
        
    elif chat_profile=="联网问答":
        judge_context = llm.chat(web_judge_task_prompt.format(user_input=message.content),temperature=0.2)
        print(judge_context)
        message_history.pop()

        if '是' in judge_context:
            prompt_tmp = bing_search_prompt(message.content)
            message_history.append({"role": "user", "content": prompt_tmp})
        else:
            message_history.append({"role": "user", "content": message.content})
        prompt_content = get_cur_base_user_prompt(message_history=message_history)

    elif chat_profile =="上传本地项目" :
        judge_context = llm.chat(judge_task_prompt.format(user_input=message.content),temperature=0.2)
        
      
        project_index = cl.user_session.get("project_index")
        index_prompt = ""
        index_tmp = """###PATH:{path}\n{code}\n"""
        for index in project_index:
            index_prompt+=index_tmp.format(path=index['path'],code=index['content'])
        print(judge_context)
        prompt_content = get_cur_base_user_prompt(message_history=message_history,index_prompt=index_prompt,judge_context=judge_context) if '正常' not in judge_context else get_cur_base_user_prompt(message_history=message_history)
    
    

    msg = cl.Message(content="")
    await msg.send()
    temperature = cl.user_session.get("temperature")
    top_p = cl.user_session.get('top_p')
    
    if len(prompt_content)/4<120000:
        stream =  llm.stream_chat(prompt_content,temperature=temperature,top_p = top_p)
        stream_processor = StreamProcessor()
        for part in stream:
            if isinstance(part, str):
                text = stream_processor.get_new_part(part)
            elif isinstance(part, dict):
                text = stream_processor.get_new_part(part['name']+part['content'])
            if token := (text or " "):
                await msg.stream_token(token)
    else:
        await msg.stream_token("项目太大了，请换小一点的项目。")

    message_history.append({"role": "assistant", "content": msg.content})
    await msg.update()