mirror of
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110 lines
3.3 KiB
Python
110 lines
3.3 KiB
Python
import asyncio
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import json
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import logging
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import os
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from pathlib import Path
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from typing import Any, Dict, List, Optional, Tuple
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import pandas as pd
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from dbgpt.agent import AgentContext, AgentMemory, LLMConfig, UserProxyAgent
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from dbgpt.agent.expand.data_scientist_agent import DataScientistAgent
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from dbgpt.agent.expand.web_assistant_agent import WebSearchAgent
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from dbgpt.agent.resource import RDBMSConnectorResource
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from dbgpt.model.proxy import TongyiLLMClient
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from dbgpt_ext.datasource.rdbms.conn_sqlite import SQLiteConnector
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api_base = "https://dashscope.aliyuncs.com/compatible-mode/v1"
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api_key = "sk-xxx"
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model = "qwen3-32b"
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def read_excel_headers_and_data(
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file_path: str,
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) -> Tuple[List[str], List[Dict[str, Any]]]:
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"""
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读取Excel文件，返回表头信息和结构化数据
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参数:
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file_path: Excel文件路径（.xlsx格式）
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返回:
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Tuple[表头列表, 数据列表]
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- 表头列表: 从Excel第一行读取的列名
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- 数据列表: 每个元素是一个字典，键为表头，值为对应单元格数据（空单元格转为None）
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"""
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if not Path(file_path).exists():
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raise FileNotFoundError(f"文件不存在: {file_path}")
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if Path(file_path).suffix.lower() != ".xlsx":
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raise ValueError(f"不支持的文件格式: {Path(file_path).suffix}，仅支持.xlsx")
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try:
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df = pd.read_excel(
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file_path, sheet_name=0, engine="openpyxl", keep_default_na=False
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)
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except Exception as e:
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raise RuntimeError(f"读取Excel失败: {str(e)}")
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headers = list(df.columns)
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if not headers:
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raise ValueError("Excel文件没有表头信息（第一行为空）")
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data = []
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for _, row in df.iterrows():
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row_data = {}
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for header in headers:
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value = row[header]
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row_data[header] = value if value != "" else None
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data.append(row_data)
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return headers, data
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def data2md(headers, table_data):
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md_lines = []
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md_lines.append("| " + " | ".join(headers) + " |")
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md_lines.append("| " + " | ".join(["---"] * len(headers)) + " |")
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for row in table_data:
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values = []
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for h in headers:
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val = row.get(h, "")
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if hasattr(val, "strftime"):
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values.append(val.strftime("%Y-%m-%d"))
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else:
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values.append(str(val))
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md_lines.append("| " + " | ".join(values) + " |")
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markdown_table = "\n".join(md_lines)
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return markdown_table
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async def main():
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llm_client = TongyiLLMClient(api_base=api_base, api_key=api_key, model=model)
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context: AgentContext = AgentContext(
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conv_id="test123", language="zh", temperature=0.5, max_new_tokens=2048
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)
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agent_memory = AgentMemory()
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agent_memory.gpts_memory.init(conv_id="test123")
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user_proxy = await UserProxyAgent().bind(agent_memory).bind(context).build()
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sql_boy = (
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await WebSearchAgent()
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.bind(context)
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.bind(LLMConfig(llm_client=llm_client))
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.bind(agent_memory)
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.build()
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)
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await user_proxy.initiate_chat(
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recipient=sql_boy, reviewer=user_proxy, message=f"今年的中秋节是多久？"
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)
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print(await agent_memory.gpts_memory.app_link_chat_message("test123"))
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if __name__ == "__main__":
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asyncio.run(main())
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