CodeGeeX4/repodemo/run_local.py

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import chainlit as cl
from chainlit.input_widget import Slider
from llm.local.codegeex4 import CodegeexChatModel
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from prompts.base_prompt import (
judge_task_prompt,
get_cur_base_user_prompt,
web_judge_task_prompt,
)
from utils.bingsearch import bing_search_prompt
from utils.tools import unzip_file, get_project_files_with_content
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local_model_path = "<your_local_model_path>"
llm = CodegeexChatModel(local_model_path)
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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
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@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。",
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starters=[
cl.Starter(
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label="请你用python写一个快速排序。",
message="请你用python写一个快速排序。",
),
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cl.Starter(
label="请你介绍一下自己。",
message="请你介绍一下自己。",
),
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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。",
),
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],
),
cl.ChatProfile(
name="联网问答",
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markdown_description="联网能力demo支持联网回答用户问题。",
),
cl.ChatProfile(
name="上传本地项目",
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markdown_description="项目级能力demo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。",
),
]
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@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"]
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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")
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extract_dir = "repodata"
if chat_profile == "chat聊天":
pass
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elif chat_profile == "上传本地项目":
files = None
while files == None:
files = await cl.AskFileMessage(
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content="请上传项目zip压缩文件!",
accept={"application/zip": [".zip"]},
max_size_mb=50,
).send()
text_file = files[0]
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extracted_path = unzip_file(text_file.path, extract_dir)
files_list = get_project_files_with_content(extracted_path)
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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()
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@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)
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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()
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if "" 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)
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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:
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index_prompt += index_tmp.format(path=index["path"], code=index["content"])
print(judge_context)
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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")
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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):
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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})
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await msg.update()