CSPON/nlp_tools/jupyter/react_data_analysis.py

"""A data analysis example implemented by assistant"""
import os
from pprint import pprint
from typing import Optional

from qwen_agent.agents import ReActChat
from qwen_agent.gui import WebUI

ROOT_RESOURCE = os.path.join(os.path.dirname(__file__), 'resource')


def init_agent_service():
    llm_cfg = {
        'model': 'qwen2-instruct',
        'model_server': 'http://lq.lianqiai.cn:20335/v1',
        'api_key': "",
        # 'model': 'qwen-max',
        # 'model_server': 'dashscope',
        # 'api_key': os.getenv('DASHSCOPE_API_KEY'),
    }
    tools = ['code_interpreter']
    bot = ReActChat(llm=llm_cfg,
                    name='code interpreter',
                    description='This agent can run code to solve the problem',
                    function_list=tools)
    return bot


def test(query: str = 'pd.head the file first and then help me draw a line chart to show the changes in stock prices',
         file: Optional[str] = os.path.join(ROOT_RESOURCE, 'stock_prices.csv')):
    # Define the agent
    bot = init_agent_service()

    # Chat
    messages = []

    if not file:
        messages.append({'role': 'user', 'content': query})
    else:
        messages.append({'role': 'user', 'content': [{'text': query}, {'file': file}]})

    for response in bot.run(messages):
        pprint(response, indent=2)


def app_tui():
    # Define the agent
    bot = init_agent_service()

    # Chat
    messages = []
    while True:
        # Query example: pd.head the file first and then help me draw a line chart to show the changes in stock prices
        query = input('user question: ')
        # File example: resource/stock_prices.csv
        file = input('file url (press enter if no file): ').strip()
        if not query:
            print('user question cannot be empty！')
            continue
        if not file:
            messages.append({'role': 'user', 'content': query})
        else:
            messages.append({'role': 'user', 'content': [{'text': query}, {'file': file}]})

        response = []
        for response in bot.run(messages):
            print('bot response:', response)
        messages.extend(response)


def app_gui():
    bot = init_agent_service()
    chatbot_config = {
        'prompt.suggestions': [{
            'text': 'pd.head the file first and then help me draw a line chart to show the changes in stock prices',
            'files': [os.path.join(ROOT_RESOURCE, 'stock_prices.csv')]
        }, 'Draw a line graph y=x^2']
    }
    WebUI(bot, chatbot_config=chatbot_config).run()


if __name__ == '__main__':
    # test()
    # app_tui()
    app_gui()