메시지 생성

import os
import anthropic

client = anthropic.Anthropic(
    base_url="https://api.cometapi.com",
    api_key=os.environ["COMETAPI_KEY"],
)

with client.messages.stream(
    model="claude-opus-5",
    max_tokens=4096,
    messages=[
        {
            "role": "user",
            "content": "A shop sells notebooks for $7 each. Buying three earns a $4 discount. A customer pays $20 for three notebooks. Calculate the total and the change, and explain your steps.",
        },
    ],
    thinking={
        "type": "adaptive",
    },
    output_config={
        "effort": "xhigh",
    },
) as stream:
    message = stream.get_final_message()

for block in message.content:
    if block.type == "text":
        print(block.text)

import os
from pathlib import Path
import anthropic

client = anthropic.Anthropic(
    base_url="https://api.cometapi.com",
    api_key=os.environ["COMETAPI_KEY"],
)

reference = Path("reference.txt").read_text(encoding="utf-8")

with client.messages.stream(
    model="claude-sonnet-5",
    max_tokens=1024,
    messages=[
        {
            "role": "user",
            "content": "How long can customers return damaged books, and what must they provide?",
        },
    ],
    system=[
        {
            "type": "text",
            "text": reference,
            "cache_control": {
                "type": "ephemeral",
            },
        },
    ],
) as stream:
    message = stream.get_final_message()

for block in message.content:
    if block.type == "text":
        print(block.text)

print(message.usage.model_dump_json())

import os
import anthropic

client = anthropic.Anthropic(
    base_url="https://api.cometapi.com",
    api_key=os.environ["COMETAPI_KEY"],
)

with client.messages.stream(
    model="claude-opus-5",
    max_tokens=1024,
    messages=[
        {
            "role": "user",
            "content": "Write a two-line poem about a comet.",
        },
    ],
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

import os
import anthropic

client = anthropic.Anthropic(
    base_url="https://api.cometapi.com",
    api_key=os.environ["COMETAPI_KEY"],
)

with client.messages.stream(
    model="claude-opus-5",
    max_tokens=1000,
    messages=[
        {
            "role": "user",
            "content": "Summarize the benefit of automated tests in one sentence.",
        },
    ],
    output_config={
        "effort": "low",
    },
) as stream:
    message = stream.get_final_message()

for block in message.content:
    if block.type == "text":
        print(block.text)

import json
import os
import anthropic

client = anthropic.Anthropic(
    base_url="https://api.cometapi.com",
    api_key=os.environ["COMETAPI_KEY"],
)
tools = [{
    "name": "get_order_status",
    "description": "Look up the status of a demonstration order.",
    "input_schema": {
        "type": "object",
        "properties": {
            "order_id": {
                "type": "string",
                "description": "The order reference.",
            },
        },
        "required": ["order_id"],
    },
}]
messages = [{
    "role": "user",
    "content": "Check the status of demo-order-42 using the order tool.",
}]

with client.messages.stream(
    model="claude-opus-5",
    max_tokens=1000,
    messages=messages,
    tools=tools,
) as stream:
    message = stream.get_final_message()

tool_call = next(b for b in message.content if b.type == "tool_use")
messages.append({
    "role": "assistant",
    "content": [block.model_dump() for block in message.content],
})
messages.append({
    "role": "user",
    "content": [{
        "type": "tool_result",
        "tool_use_id": tool_call.id,
        "content": json.dumps({
            "status": "ready_for_pickup",
            "pickup_code": "COMET42",
        }),
    }],
})

with client.messages.stream(
    model="claude-opus-5",
    max_tokens=1000,
    messages=messages,
    tools=tools,
) as stream:
    follow_up = stream.get_final_message()

for block in follow_up.content:
    if block.type == "text":
        print(block.text)

{
  "id": "msg_example",
  "type": "message",
  "role": "assistant",
  "model": "claude-opus-5",
  "content": [
    {
      "type": "text",
      "text": "Here are three search queries covering different angles of the topic:\n\n1. **\"grid-scale battery storage cost trends 2024 2025\"**\n — Targets economics and recent price data for lithium-ion and other utility-scale systems.\n\n2. **\"long-duration energy storage technologies comparison flow battery vs compressed air vs thermal\"**\n — Surfaces technical comparisons of options for storage beyond the 4–8 hour range, where lithium-ion becomes less cost-effective.\n\n3. **\"green hydrogen seasonal storage feasibility round-trip efficiency\"**\n — Digs into the viability of hydrogen for multi-week or seasonal balancing, including its efficiency penalties.\n\n**A few tips for refining these:**\n- Add `site:.gov` or `site:.edu` to prioritize research and agency reports (e.g., NREL, IEA, DOE).\n- Append a region like `Europe`, `India`, or `California` if you need location-specific policy or deployment data.\n- Try `filetype:pdf` to pull up technical white papers and government studies directly.\n\nWant me to tailor these toward a specific use case — academic research, investment analysis, or policy work?"
    }
  ],
  "stop_reason": "end_turn",
  "stop_sequence": null,
  "usage": {
    "input_tokens": 23,
    "cache_creation_input_tokens": 0,
    "cache_read_input_tokens": 0,
    "cache_creation": {
      "ephemeral_5m_input_tokens": 0,
      "ephemeral_1h_input_tokens": 0
    },
    "output_tokens": 437,
    "output_tokens_details": {
      "thinking_tokens": 50
    }
  }
}