import requests
# Azure OpenAI 客户端
def get_openai_answer(prompt):
    
    api_key = "your api key"
    endpoint = "your deployment endpoint, like: https://<your azure ai name>.openai.azure.com/openai/deployments/<LLM Name>/chat/completions?api-version=2025-01-01-preview"
if not api_key or not endpoint:
        raise ValueError("请配置 Azure OpenAI 信息")
        
    headers = {
        "Content-Type": "application/json",
        "api-key": api_key
    }
    systemprompt  = f"""" 您是一个有趣的聊天智能体，能愉快的和人类聊天"""
    data = {
        "messages": [
            {"role": "system", "content": systemprompt},
            {"role": "user", "content": prompt}
        ],
        "max_tokens": 5000,
        "temperature": 0.7
    }
    response = requests.post(endpoint, headers=headers, json=data)
    response.raise_for_status()
    result = response.json()
    return result["choices"][0]["message"]["content"]
# 示例用法
if __name__ == "__main__":
    prompt = "请介绍一下Azure OpenAI的主要功能。"
    print(get_openai_answer(prompt))

# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
from botbuilder.core import ActivityHandler, MessageFactory, TurnContext
from botbuilder.schema import ChannelAccount
from bots.call_openai import get_openai_answer
class EchoBot(ActivityHandler):
    async def on_members_added_activity(self, members_added: [ChannelAccount], turn_context: TurnContext):
        for member in members_added:
            if member.id != turn_context.activity.recipient.id:
                await turn_context.send_activity("Hello and welcome, this is python code.")
    async def on_message_activity(self, turn_context: TurnContext):
        #call LLM API to get response 
        llmresponse = get_openai_answer(turn_context.activity.text)
        return await turn_context.send_activity(
            MessageFactory.text(f"{llmresponse}")
        )