Anthropic Messages - CometAPI Documentation

POST

messages

import os
import anthropic

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

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    system="You are a helpful assistant.",
    messages=[
        {"role": "user", "content": "Hello, world"}
    ],
)

print(message.content[0].text)

{
  "id": "<string>",
  "content": [
    {
      "text": "<string>",
      "thinking": "<string>",
      "signature": "<string>",
      "id": "<string>",
      "name": "<string>",
      "input": {}
    }
  ],
  "model": "<string>",
  "stop_sequence": "<string>",
  "usage": {
    "input_tokens": 123,
    "output_tokens": 123,
    "cache_creation_input_tokens": 123,
    "cache_read_input_tokens": 123,
    "cache_creation": {
      "ephemeral_5m_input_tokens": 123,
      "ephemeral_1h_input_tokens": 123
    }
  }
}

CometAPI mendukung Anthropic Messages API secara native, memberi Anda akses langsung ke model Claude dengan semua fitur khusus Anthropic. Gunakan endpoint ini untuk kemampuan eksklusif Claude seperti extended thinking, prompt caching, dan kontrol effort.

Baik header x-api-key maupun Authorization: Bearer didukung untuk autentikasi. SDK resmi Anthropic menggunakan x-api-key secara default.

Quick start

Untuk menggunakan SDK resmi Anthropic dengan CometAPI, atur base URL:

import os
import anthropic

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

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello!"}],
)
print(message.content[0].text)

Enable extended thinking

Aktifkan penalaran langkah demi langkah Claude dengan parameter thinking. Respons menyertakan blok konten thinking yang menampilkan penalaran internal Claude sebelum jawaban akhir.

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=16000,
    thinking={
        "type": "enabled",
        "budget_tokens": 10000,
    },
    messages=[
        {"role": "user", "content": "Prove that there are infinitely many primes."}
    ],
)

for block in message.content:
    if block.type == "thinking":
        print(f"Thinking: {block.thinking[:200]}...")
    elif block.type == "text":
        print(f"Answer: {block.text}")

Thinking memerlukan minimum budget_tokens sebesar 1.024. Token Thinking dihitung terhadap batas max_tokens Anda — atur max_tokens cukup tinggi untuk menampung Thinking dan respons.

Cache prompts

Untuk mengurangi latensi dan biaya pada permintaan berikutnya, cache prompt sistem yang besar atau prefiks percakapan. Tambahkan cache_control ke blok konten yang harus di-cache:

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    system=[
        {
            "type": "text",
            "text": "You are an expert code reviewer. [Long detailed instructions...]",
            "cache_control": {"type": "ephemeral"},
        }
    ],
    messages=[{"role": "user", "content": "Review this code..."}],
)

Penggunaan cache dilaporkan di field usage pada respons:

cache_creation_input_tokens — token yang ditulis ke cache (ditagih dengan tarif lebih tinggi)
cache_read_input_tokens — token yang dibaca dari cache (ditagih dengan tarif yang lebih rendah)

Prompt caching memerlukan minimum 1.024 token pada blok konten yang di-cache. Konten yang lebih pendek dari ini tidak akan di-cache.

Stream respons

Untuk melakukan stream respons menggunakan Server-Sent Events (SSE), setel stream: true. Event datang dalam urutan berikut:

message_start — berisi metadata message dan usage awal
content_block_start — menandai awal setiap content block
content_block_delta — potongan teks bertahap (text_delta)
content_block_stop — menandai akhir setiap content block
message_delta — stop_reason final dan usage lengkap
message_stop — menandakan akhir stream

with client.messages.stream(
    model="claude-sonnet-4-6",
    max_tokens=256,
    messages=[{"role": "user", "content": "Hello"}],
) as stream:
    for text in stream.text_stream:
        print(text, end="")

Kontrol effort

Untuk mengontrol seberapa besar effort yang dikerahkan Claude dalam menghasilkan respons, gunakan output_config.effort:

message = client.messages.create(
    model="claude-opus-4-6",
    max_tokens=4096,
    messages=[
        {"role": "user", "content": "Ringkas ini secara singkat."}
    ],
    output_config={"effort": "low"},  # "low", "medium", or "high"
)

Gunakan server tools

Claude mendukung server-side tools yang berjalan di infrastruktur Anthropic:

Web Fetch
Web Search

Ambil dan analisis konten dari URL:

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Analyze the content at https://arxiv.org/abs/1512.03385"}
    ],
    tools=[
        {"type": "web_fetch_20250910", "name": "web_fetch", "max_uses": 5}
    ],
)

Cari web untuk informasi real-time:

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "What are the latest developments in AI?"}
    ],
    tools=[
        {"type": "web_search_20250305", "name": "web_search", "max_uses": 5}
    ],
)

Contoh respons

Respons tipikal dari endpoint Anthropic milik CometAPI:

{
  "id": "msg_bdrk_01UjHdmSztrL7QYYm7CKBDFB",
  "type": "message",
  "role": "assistant",
  "content": [
    {
      "type": "text",
      "text": "Hello!"
    }
  ],
  "model": "claude-sonnet-4-6",
  "stop_reason": "end_turn",
  "stop_sequence": null,
  "usage": {
    "input_tokens": 19,
    "cache_creation_input_tokens": 0,
    "cache_read_input_tokens": 0,
    "cache_creation": {
      "ephemeral_5m_input_tokens": 0,
      "ephemeral_1h_input_tokens": 0
    },
    "output_tokens": 4
  }
}

Bandingkan dengan endpoint OpenAI-compatible

Fitur	Anthropic Messages (`/v1/messages`)	OpenAI-Compatible (`/v1/chat/completions`)
Extended thinking	Parameter `thinking` dengan `budget_tokens`	Tidak tersedia
Prompt caching	`cache_control` pada content blocks	Tidak tersedia
Kontrol effort	`output_config.effort`	Tidak tersedia
Web fetch/search	Server tools (`web_fetch`, `web_search`)	Tidak tersedia
Header autentikasi	`x-api-key` atau `Bearer`	Hanya `Bearer`
Format respons	Format Anthropic (`content` blocks)	Format OpenAI (`choices`, `message`)
Models	Hanya Claude	Multi-provider (GPT, Claude, Gemini, dll.)

Otorisasi

x-api-key

string

header

wajib

Your CometAPI key passed via the x-api-key header. Authorization: Bearer $COMETAPI_KEY is also supported.

Header

anthropic-version

string

default:2023-06-01

The Anthropic API version to use. Defaults to 2023-06-01.

Contoh:

"2023-06-01"

anthropic-beta

string

Comma-separated list of beta features to enable. Examples: max-tokens-3-5-sonnet-2024-07-15, pdfs-2024-09-25, output-128k-2025-02-19.

Body

application/json

model

string

wajib

The Claude model to use. See the Models page for current Claude model IDs.

Contoh:

"claude-sonnet-4-6"

messages

object[]

wajib

The conversation messages. Must alternate between user and assistant roles. Each message's content can be a string or an array of content blocks (text, image, document, tool_use, tool_result). There is a limit of 100,000 messages per request.

Show child attributes

max_tokens

integer

wajib

The maximum number of tokens to generate. The model may stop before reaching this limit. When using thinking, the thinking tokens count towards this limit.

Rentang yang diperlukan: x >= 1

Contoh:

1024

system

System prompt providing context and instructions to Claude. Can be a plain string or an array of content blocks (useful for prompt caching).

temperature

number

default:1

Controls randomness in the response. Range: 0.0–1.0. Use lower values for analytical tasks and higher values for creative tasks. Defaults to 1.0.

Rentang yang diperlukan: 0 <= x <= 1

top_p

number

Nucleus sampling threshold. Only tokens with cumulative probability up to this value are considered. Range: 0.0–1.0. Use either temperature or top_p, not both.

Rentang yang diperlukan: 0 <= x <= 1

top_k

integer

Only sample from the top K most probable tokens. Recommended for advanced use cases only.

Rentang yang diperlukan: x >= 0

stream

boolean

default:false

If true, stream the response incrementally using Server-Sent Events (SSE). Events include message_start, content_block_start, content_block_delta, content_block_stop, message_delta, and message_stop.

stop_sequences

string[]

Custom strings that cause the model to stop generating when encountered. The stop sequence is not included in the response.

thinking

object

Enable extended thinking — Claude's step-by-step reasoning process. When enabled, the response includes thinking content blocks before the answer. Requires a minimum budget_tokens of 1,024.

Show child attributes

tools

object[]

Tools the model may use. Supports client-defined functions, web search (web_search_20250305), web fetch (web_fetch_20250910), code execution (code_execution_20250522), and more.

Show child attributes

tool_choice

object

Controls how the model uses tools.

Show child attributes

metadata

object

Request metadata for tracking and analytics.

Show child attributes

output_config

object

Configuration for output behavior.

Show child attributes

service_tier

enum<string>

The service tier to use. auto tries priority capacity first, standard_only uses only standard capacity.

Opsi yang tersedia:

auto,

standard_only

Respons

200 - application/json

Successful response. When stream is true, the response is a stream of SSE events.

string

Unique identifier for this message (e.g., msg_01XFDUDYJgAACzvnptvVoYEL).

type

enum<string>

Always message.

Opsi yang tersedia:

message

role

enum<string>

Always assistant.

Opsi yang tersedia:

assistant

content

object[]

The response content blocks. May include text, thinking, tool_use, and other block types.

Show child attributes

model

string

The specific model version that generated this response (e.g., claude-sonnet-4-6).

stop_reason

enum<string>

Why the model stopped generating.

Opsi yang tersedia:

end_turn,

max_tokens,

stop_sequence,

tool_use,

pause_turn

stop_sequence

string | null

The stop sequence that caused the model to stop, if applicable.

usage

object

Token usage statistics.

Show child attributes

Responses

Sebelumnya

Gemini Generating Content

Selanjutnya

import os
import anthropic

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

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    system="You are a helpful assistant.",
    messages=[
        {"role": "user", "content": "Hello, world"}
    ],
)

print(message.content[0].text)

{
  "id": "<string>",
  "content": [
    {
      "text": "<string>",
      "thinking": "<string>",
      "signature": "<string>",
      "id": "<string>",
      "name": "<string>",
      "input": {}
    }
  ],
  "model": "<string>",
  "stop_sequence": "<string>",
  "usage": {
    "input_tokens": 123,
    "output_tokens": 123,
    "cache_creation_input_tokens": 123,
    "cache_read_input_tokens": 123,
    "cache_creation": {
      "ephemeral_5m_input_tokens": 123,
      "ephemeral_1h_input_tokens": 123
    }
  }
}

​Quick start

​Enable extended thinking

​Cache prompts

​Stream respons

​Kontrol effort

​Gunakan server tools

​Contoh respons

​Bandingkan dengan endpoint OpenAI-compatible

Otorisasi

Header

Body

Respons

Quick start

Enable extended thinking

Cache prompts

Stream respons

Kontrol effort

Gunakan server tools

Contoh respons

Bandingkan dengan endpoint OpenAI-compatible