202 lines
6.8 KiB
Python
202 lines
6.8 KiB
Python
import requests
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import logging
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import json
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from django.conf import settings
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from datetime import datetime
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logger = logging.getLogger(__name__)
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class AIService:
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"""
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通用AI服务类，提供对不同AI模型的统一调用接口
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"""
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@staticmethod
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def call_silicon_cloud_api(messages, model="deepseek-ai/DeepSeek-V3", max_tokens=512, temperature=0.7):
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"""
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调用SiliconCloud API
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Args:
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messages: 消息列表，格式为[{"role": "user", "content": "..."}, ...]
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model: 使用的模型名称，默认为DeepSeek-V3
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max_tokens: 最大生成token数
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temperature: 温度参数，控制创造性
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Returns:
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tuple: (生成内容, 错误信息)
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"""
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try:
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# 获取API密钥
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api_key = getattr(settings, 'SILICON_CLOUD_API_KEY', '')
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if not api_key:
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return None, "未配置Silicon Cloud API密钥"
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url = "https://api.siliconflow.cn/v1/chat/completions"
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payload = {
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"model": model,
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"stream": False,
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"max_tokens": max_tokens,
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"temperature": temperature,
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"top_p": 0.7,
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"top_k": 50,
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"frequency_penalty": 0.5,
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"n": 1,
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"stop": [],
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"messages": messages
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}
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headers = {
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"Authorization": f"Bearer {api_key}",
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"Content-Type": "application/json"
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}
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# 设置代理（如果配置了）
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proxies = None
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proxy_url = getattr(settings, 'PROXY_URL', None)
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if proxy_url:
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proxies = {
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"http": proxy_url,
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"https": proxy_url
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}
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# 发送请求
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logger.info(f"正在调用SiliconCloud API，模型: {model}")
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response = requests.post(url, json=payload, headers=headers, proxies=proxies)
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if response.status_code != 200:
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logger.error(f"API请求失败，状态码: {response.status_code}，响应: {response.text}")
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return None, f"API请求失败，状态码: {response.status_code}"
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result = response.json()
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# 从API响应中提取内容
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if 'choices' in result and result['choices']:
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content = result['choices'][0]['message']['content'].strip()
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return content, None
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else:
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logger.error(f"API响应格式错误: {result}")
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return None, "API响应格式错误，无法提取内容"
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except requests.exceptions.RequestException as e:
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logger.error(f"API请求异常: {str(e)}")
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return None, f"API请求异常: {str(e)}"
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except Exception as e:
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logger.error(f"调用AI服务失败: {str(e)}")
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return None, f"调用AI服务失败: {str(e)}"
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@staticmethod
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def generate_email_reply(goal_description, conversation_summary, last_message):
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"""
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生成邮件回复话术
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Args:
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goal_description: 用户目标描述
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conversation_summary: 对话摘要
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last_message: 达人最后发送的消息内容
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Returns:
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tuple: (推荐话术内容, 错误信息)
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"""
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try:
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# 验证必要参数
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if not goal_description or not last_message:
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return None, "缺少必要参数：目标描述或最后消息"
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# 准备提示信息
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prompt = f"""
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请为用户提供一条回复达人邮件的推荐话术，帮助用户实现销售目标。
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用户目标：{goal_description}
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对话摘要：{conversation_summary or '无对话摘要'}
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达人最后发送的消息：
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{last_message}
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要求：
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1. 回复应当专业礼貌，并围绕用户目标展开
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2. 提供有说服力的话术，推动促成合作
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3. 不超过200字
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4. 直接给出回复内容，不要包含任何额外解释
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"""
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messages = [
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{
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"role": "system",
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"content": "你是一名专业的邮件回复助手，你的任务是生成有效的销售话术，帮助用户实现销售目标。"
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},
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{
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"role": "user",
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"content": prompt
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}
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]
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# 调用通用API方法
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return AIService.call_silicon_cloud_api(
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messages,
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model="Pro/deepseek-ai/DeepSeek-R1",
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max_tokens=512,
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temperature=0.7
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)
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except Exception as e:
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logger.error(f"生成回复话术失败: {str(e)}")
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return None, f"生成回复话术失败: {str(e)}"
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@staticmethod
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def generate_conversation_summary(conversation_history):
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"""
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生成对话摘要
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Args:
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conversation_history: 对话历史记录列表
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Returns:
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tuple: (摘要内容, 错误信息)
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"""
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try:
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if not conversation_history:
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return None, "无对话历史，无法生成摘要"
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# 构造对话历史文本
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conversation_text = "\n\n".join([
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f"**{'用户' if msg.get('is_from_user', False) else '达人'}**: {msg.get('content', '')}"
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for msg in conversation_history
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])
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# 准备提示信息
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prompt = f"""
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请对以下用户与达人之间的对话内容进行总结:
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{conversation_text}
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要求:
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1. 总结应包含双方主要讨论的话题和关键点
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2. 特别关注产品详情、价格谈判、合作意向等商务要点
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3. 简明扼要，不超过200字
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4. 直接给出总结内容，不要包含任何额外解释
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"""
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messages = [
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{
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"role": "system",
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"content": "你是一名专业的对话总结助手，擅长提取商务沟通中的关键信息。"
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},
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{
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"role": "user",
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"content": prompt
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}
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]
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# 调用通用API方法
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return AIService.call_silicon_cloud_api(
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messages,
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model="Pro/deepseek-ai/DeepSeek-R1",
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max_tokens=512,
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temperature=0.5
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)
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except Exception as e:
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logger.error(f"生成对话摘要失败: {str(e)}")
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return None, f"生成对话摘要失败: {str(e)}" |