17 · API 与自动化监测

import requests
import json
import time
from datetime import datetime
 
# DeepSeek API 配置
API_KEY = "your-api-key"
API_URL = "https://api.deepseek.com/v1/chat/completions"
 
# 监测查询词列表
queries = [
    "项目管理工具推荐",
    "小团队协作软件哪个好",
    "免费看板工具推荐",
    # ... 你的查询词库
]
 
# 你的品牌和竞品名称
brands = ["你的品牌名", "竞品A", "竞品B"]
 
def search_deepseek(query):
    """调用 DeepSeek API 联网搜索"""
    response = requests.post(
        API_URL,
        headers={
            "Authorization": f"Bearer {API_KEY}",
            "Content-Type": "application/json"
        },
        json={
            "model": "deepseek-chat",
            "messages": [
                {"role": "user", "content": query}
            ],
            "search": True  # 启用联网搜索
        }
    )
    return response.json()
 
def analyze_mentions(response_text, brands):
    """分析回答中的品牌提及"""
    results = {}
    for brand in brands:
        count = response_text.count(brand)
        results[brand] = {
            "mentioned": count > 0,
            "count": count,
            "sentiment": "neutral"  # 需要更复杂的 NLP 分析
        }
    return results
 
# 执行监测
for query in queries:
    result = search_deepseek(query)
    answer = result["choices"][0]["message"]["content"]
    mentions = analyze_mentions(answer, brands)
    # 记录到数据库或 Google Sheet
    print(f"[{datetime.now()}] {query}: {mentions}")
    time.sleep(2)  # 避免触发频率限制