Claude API 聯網搜尋實現指南

bash_20250124, custom, memory_20250818, text_editor_*(20250124/0429/0728),
tool_search_tool_bm25(_20251119), tool_search_tool_regex(_20251119)

curl https://api.apiyi.com/v1/messages \
  -H "content-type: application/json" \
  -H "x-api-key: 你的APIYI_KEY(ClaudeOfficial分組)" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "claude-sonnet-4-6",
    "max_tokens": 2048,
    "tools": [{"type": "web_search_20260209", "name": "web_search"}],
    "messages": [{"role": "user", "content": "Anthropic 最近釋出了什麼新模型？請搜尋並給出來源"}]
  }'

"usage": {
  "server_tool_use": { "web_search_requests": 2 }
}

import requests

API_KEY = "你的APIYI_KEY"  # 預設分組即可
URL = "https://api.apiyi.com/v1/messages"
HEADERS = {
    "content-type": "application/json",
    "x-api-key": API_KEY,
    "anthropic-version": "2023-06-01",
}

SEARCH_TOOL = {
    "name": "web_search",
    "description": ("Search the web for current information. Call this whenever "
                    "the user asks about recent events or anything after your "
                    "knowledge cutoff. You may call it multiple times."),
    "input_schema": {
        "type": "object",
        "properties": {"query": {"type": "string", "description": "搜尋關鍵詞"}},
        "required": ["query"],
    },
}

def do_search(query: str) -> str:
    """接您選用的搜尋 API（Tavily/Brave/Serper 等），返回結果文本。"""
    # 以 Tavily 為例：
    # r = requests.post("https://api.tavily.com/search",
    #                   json={"api_key": TAVILY_KEY, "query": query, "max_results": 5})
    # return "\n".join(f"- {x['title']}\n  {x['url']}\n  {x['content'][:200]}"
    #                  for x in r.json()["results"])
    ...

messages = [{"role": "user", "content": "Anthropic 最近釋出了什麼新模型？請搜尋後回答並附來源"}]

for _ in range(5):  # 工具迴圈，最多 5 輪
    resp = requests.post(URL, headers=HEADERS, json={
        "model": "claude-sonnet-4-6",
        "max_tokens": 2048,
        "tools": [SEARCH_TOOL],
        "messages": messages,
    }, timeout=180).json()

    if resp.get("stop_reason") != "tool_use":
        print(next(b["text"] for b in resp["content"] if b["type"] == "text"))
        break

    messages.append({"role": "assistant", "content": resp["content"]})
    results = [{"type": "tool_result", "tool_use_id": b["id"],
                "content": do_search(b["input"]["query"])}
               for b in resp["content"] if b["type"] == "tool_use"]
    messages.append({"role": "user", "content": results})