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Anthropic offers two ways to build with Claude, each suited to different use cases:
| Messages API | Claude Managed Agents | |
|---|---|---|
| What it is | Direct model prompting access | Pre-built, configurable agent harness that runs in managed infrastructure |
| Best for | Custom agent loops and fine-grained control | Long-running tasks and asynchronous work |
| Learn more | Messages API docs | Claude Managed Agents docs |
Panduan ini mencakup pola umum untuk bekerja dengan Messages API, termasuk permintaan dasar, percakapan multi-giliran, teknik prefill, dan kemampuan visi. Untuk spesifikasi API lengkap, lihat referensi Messages API.
This feature is eligible for Zero Data Retention (ZDR). When your organization has a ZDR arrangement, data sent through this feature is not stored after the API response is returned.
message = anthropic.Anthropic().messages.create(
model="claude-opus-4-7",
max_tokens=1024,
messages=[{"role": "user", "content": "Hello, Claude"}],
)
print(message){
"id": "msg_01XFDUDYJgAACzvnptvVoYEL",
"type": "message",
"role": "assistant",
"content": [
{
"type": "text",
"text": "Hello!"
}
],
"model": "claude-opus-4-7",
"stop_reason": "end_turn",
"stop_sequence": null,
"usage": {
"input_tokens": 12,
"output_tokens": 6
}
}Messages API bersifat stateless, yang berarti Anda selalu mengirimkan riwayat percakapan lengkap ke API. Anda dapat menggunakan pola ini untuk membangun percakapan dari waktu ke waktu. Giliran percakapan sebelumnya tidak perlu benar-benar berasal dari Claude. Anda dapat menggunakan pesan assistant sintetis.
{
"id": "msg_018gCsTGsXkYJVqYPxTgDHBU",
"type": "message",
"role": "assistant",
"content": [
{
"type": "text",
"text": "Sure, I'd be happy to provide..."
}
],
"stop_reason": "end_turn",
"stop_sequence": null,
"usage": {
"input_tokens": 30,
"output_tokens": 309
}
}Anda dapat mengisi sebelumnya bagian dari respons Claude di posisi terakhir daftar pesan input. Ini dapat digunakan untuk membentuk respons Claude. Contoh di bawah menggunakan "max_tokens": 1 untuk mendapatkan jawaban pilihan ganda tunggal dari Claude.
{
"id": "msg_01Q8Faay6S7QPTvEUUQARt7h",
"type": "message",
"role": "assistant",
"content": [
{
"type": "text",
"text": "C"
}
],
"model": "claude-sonnet-4-5",
"stop_reason": "max_tokens",
"stop_sequence": null,
"usage": {
"input_tokens": 42,
"output_tokens": 1
}
}Prefilling tidak didukung pada Claude Mythos Preview, Claude Opus 4.7, Claude Opus 4.6, dan Claude Sonnet 4.6. Permintaan menggunakan prefill dengan model ini mengembalikan kesalahan 400. Gunakan structured outputs atau instruksi system prompt sebagai gantinya. Lihat panduan migrasi untuk pola migrasi.
Claude dapat membaca teks dan gambar dalam permintaan. Gambar dapat disediakan menggunakan jenis sumber base64, url, atau file. Jenis sumber file mereferensikan gambar yang diunggah melalui Files API. Jenis media yang didukung adalah image/jpeg, image/png, image/gif, dan image/webp. Lihat panduan visi untuk detail lebih lanjut.
{
"id": "msg_01EcyWo6m4hyW8KHs2y2pei5",
"type": "message",
"role": "assistant",
"content": [
{
"type": "text",
"text": "This image shows an ant, specifically a close-up view of an ant. The ant is shown in detail, with its distinct head, antennae, and legs clearly visible. The image is focused on capturing the intricate details and features of the ant, likely taken with a macro lens to get an extreme close-up perspective."
}
],
"model": "claude-opus-4-7",
"stop_reason": "end_turn",
"stop_sequence": null,
"usage": {
"input_tokens": 1551,
"output_tokens": 71
}
}Lihat panduan penggunaan alat untuk contoh cara menggunakan alat dengan Messages API. Lihat panduan penggunaan komputer untuk contoh cara mengontrol lingkungan desktop komputer dengan Messages API. Untuk output JSON yang dijamin, lihat Structured Outputs.
message = anthropic.Anthropic().messages.create(
model="claude-opus-4-7",
max_tokens=1024,
messages=[
{"role": "user", "content": "Hello, Claude"},
{"role": "assistant", "content": "Hello!"},
{"role": "user", "content": "Can you describe LLMs to me?"},
],
)
print(message)message = anthropic.Anthropic().messages.create(
model="claude-sonnet-4-5",
max_tokens=1,
messages=[
{
"role": "user",
"content": "What is latin for Ant? (A) Apoidea, (B) Rhopalocera, (C) Formicidae",
},
{"role": "assistant", "content": "The answer is ("},
],
)
print(message)import base64
import httpx
# Option 1: Base64-encoded image
image_url = "https://upload.wikimedia.org/wikipedia/commons/a/a7/Camponotus_flavomarginatus_ant.jpg"
image_media_type = "image/jpeg"
image_data = base64.standard_b64encode(httpx.get(image_url).content).decode("utf-8")
message = anthropic.Anthropic().messages.create(
model="claude-opus-4-7",
max_tokens=1024,
messages=[
{
"role": "user",
"content": [
{
"type": "image",
"source": {
"type": "base64",
"media_type": image_media_type,
"data": image_data,
},
},
{"type": "text", "text": "What is in the above image?"},
],
}
],
)
print(message)
# Option 2: URL-referenced image
message_from_url = anthropic.Anthropic().messages.create(
model="claude-opus-4-7",
max_tokens=1024,
messages=[
{
"role": "user",
"content": [
{
"type": "image",
"source": {
"type": "url",
"url": "https://upload.wikimedia.org/wikipedia/commons/a/a7/Camponotus_flavomarginatus_ant.jpg",
},
},
{"type": "text", "text": "What is in the above image?"},
],
}
],
)
print(message_from_url)