Kimi K2.6 上线：开源旗舰 Agent 编程登顶

from openai import OpenAI

client = OpenAI(
    api_key="sk-your-apiyi-key",
    base_url="https://api.apiyi.com/v1"
)

# 典型用法：Agent 编程 + 工具调用
resp = client.chat.completions.create(
    model="kimi-k2.6",
    messages=[
        {"role": "system", "content": "你是一名资深全栈工程师，擅长在真实代码库中完成 PR 级任务。"},
        {"role": "user", "content": "帮我把这个仓库的日志系统统一迁移到 structlog，并给出最小变更的 PR"}
    ],
    temperature=0.3,
)
print(resp.choices[0].message.content)

# 让模型严格从给定前缀继续补全（常用于结构化输出）
resp = client.chat.completions.create(
    model="kimi-k2.6",
    messages=[
        {"role": "user", "content": "请输出一个用户对象，仅返回 JSON"},
        {
            "role": "assistant",
            "content": '{"id": 1, "name": "',
        }
    ],
    extra_body={"prefix": True},   # 开启前缀续写
    temperature=0.2,
)
print(resp.choices[0].message.content)

tools = [{
    "type": "function",
    "function": {
        "name": "search_repo",
        "description": "在指定仓库里按关键词检索代码",
        "parameters": {
            "type": "object",
            "properties": {
                "repo": {"type": "string"},
                "query": {"type": "string"}
            },
            "required": ["repo", "query"]
        }
    }
}]

resp = client.chat.completions.create(
    model="kimi-k2.6",
    messages=[{"role": "user", "content": "在 apiyi/core 仓库里找一下限流中间件的实现"}],
    tools=tools,
    tool_choice="auto",
)
print(resp.choices[0].message.tool_calls)