Kimi K3 API クイックスタート：Python、ストリーミング、ビジョン、ツール呼び出し

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python3 -m pip install --upgrade 'openai>=1.0'

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import os

from openai import OpenAI

client = OpenAI(
    api_key=os.environ["MOONSHOT_API_KEY"],
    base_url="https://api.moonshot.ai/v1",
)

completion = client.chat.completions.create(
    model="kimi-k3",
    messages=[{"role": "user", "content": "用一句话介绍 Kimi K3。"}],
)

print(completion.choices[0].message.content)

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$env:MOONSHOT_API_KEY = "你的 API Key"
python .\kimi_k3_demo.py

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[Environment]::SetEnvironmentVariable("MOONSHOT_API_KEY", "你的 API Key", "User")

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export MOONSHOT_API_KEY="你的 API Key"
python3 kimi_k3_demo.py

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curl https://api.moonshot.ai/v1/chat/completions \
  --header "Authorization: Bearer $MOONSHOT_API_KEY" \
  --header "Content-Type: application/json" \
  --data '{
    "model": "kimi-k3",
    "messages": [{"role": "user", "content": "用一句话介绍 Kimi K3。"}]
  }'

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$headers = @{
    Authorization = "Bearer $env:MOONSHOT_API_KEY"
    "Content-Type" = "application/json"
}

$body = @{
    model = "kimi-k3"
    messages = @(
        @{ role = "user"; content = "用一句话介绍 Kimi K3。" }
    )
} | ConvertTo-Json -Depth 5

Invoke-RestMethod `
    -Uri "https://api.moonshot.ai/v1/chat/completions" `
    -Method Post `
    -Headers $headers `
    -Body $body

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completion = client.chat.completions.create(
    model="kimi-k3",
    reasoning_effort="max",
    messages=[
        {"role": "user", "content": "证明根号 2 是无理数。"}
    ],
)

print(completion.choices[0].message.content)

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stream = client.chat.completions.create(
    model="kimi-k3",
    messages=[{"role": "user", "content": "解释天空为什么是蓝色的。"}],
    stream=True,
)

for chunk in stream:
    delta = chunk.choices[0].delta
    reasoning = getattr(delta, "reasoning_content", None)
    if reasoning:
        print(reasoning, end="", flush=True)
    if delta.content:
        print(delta.content, end="", flush=True)

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import base64
from pathlib import Path

image_data = base64.b64encode(Path("image.png").read_bytes()).decode()

completion = client.chat.completions.create(
    model="kimi-k3",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "image_url",
                    "image_url": {
                        "url": f"data:image/png;base64,{image_data}"
                    },
                },
                {"type": "text", "text": "描述这张图片。"},
            ],
        }
    ],
)

print(completion.choices[0].message.content)

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import json

completion = client.chat.completions.create(
    model="kimi-k3",
    messages=[
        {"role": "user", "content": "小林今年 28 岁，提取姓名和年龄。"}
    ],
    response_format={
        "type": "json_schema",
        "json_schema": {
            "name": "person",
            "strict": True,
            "schema": {
                "type": "object",
                "properties": {
                    "name": {"type": "string"},
                    "age": {"type": "integer"},
                },
                "required": ["name", "age"],
                "additionalProperties": False,
            },
        },
    },
)

person = json.loads(completion.choices[0].message.content or "{}")
print(person)

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import json
from typing import Any

tools: list[dict[str, Any]] = [
    {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "查询城市天气",
            "parameters": {
                "type": "object",
                "properties": {"city": {"type": "string"}},
                "required": ["city"],
            },
        },
    }
]

messages: list[Any] = [
    {"role": "user", "content": "今天上海天气如何？"}
]

first = client.chat.completions.create(
    model="kimi-k3",
    messages=messages,
    tools=tools,
    tool_choice="required",
)

assistant_message = first.choices[0].message
messages.append(assistant_message)

for tool_call in assistant_message.tool_calls or []:
    arguments = json.loads(tool_call.function.arguments)
    result = json.dumps(
        {"city": arguments["city"], "weather": "sunny", "temperature_c": 32},
        ensure_ascii=False,
    )
    messages.append(
        {
            "role": "tool",
            "tool_call_id": tool_call.id,
            "content": result,
        }
    )

final = client.chat.completions.create(
    model="kimi-k3",
    messages=messages,
    tools=tools,
)

print(final.choices[0].message.content)

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from pathlib import Path

knowledge = Path("knowledge-base.md").read_text(encoding="utf-8")

for question in ["总结主要结论。", "列出三个实施风险。"]:
    completion = client.chat.completions.create(
        model="kimi-k3",
        messages=[
            {"role": "system", "content": knowledge},
            {"role": "user", "content": question},
        ],
    )
    print(completion.choices[0].message.content)