File: working-with-messages.md | Updated: 11/15/2025
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Using the Messages API
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This guide covers common patterns for working with the Messages API, including basic requests, multi-turn conversations, prefill techniques, and vision capabilities. For complete API specifications, see the Messages API reference .
Shell
Python
TypeScript
Copy
#!/bin/sh
curl https://api.anthropic.com/v1/messages \
--header "x-api-key: $ANTHROPIC_API_KEY" \
--header "anthropic-version: 2023-06-01" \
--header "content-type: application/json" \
--data \
'{
"model": "claude-sonnet-4-5",
"max_tokens": 1024,
"messages": [\
{"role": "user", "content": "Hello, Claude"}\
]
}'
JSON
Copy
{
"id": "msg_01XFDUDYJgAACzvnptvVoYEL",
"type": "message",
"role": "assistant",
"content": [\
{\
"type": "text",\
"text": "Hello!"\
}\
],
"model": "claude-sonnet-4-5",
"stop_reason": "end_turn",
"stop_sequence": null,
"usage": {
"input_tokens": 12,
"output_tokens": 6
}
}
The Messages API is stateless, which means that you always send the full conversational history to the API. You can use this pattern to build up a conversation over time. Earlier conversational turns don’t necessarily need to actually originate from Claude — you can use synthetic assistant messages.
Shell
Python
TypeScript
Copy
#!/bin/sh
curl https://api.anthropic.com/v1/messages \
--header "x-api-key: $ANTHROPIC_API_KEY" \
--header "anthropic-version: 2023-06-01" \
--header "content-type: application/json" \
--data \
'{
"model": "claude-sonnet-4-5",
"max_tokens": 1024,
"messages": [\
{"role": "user", "content": "Hello, Claude"},\
{"role": "assistant", "content": "Hello!"},\
{"role": "user", "content": "Can you describe LLMs to me?"}\
\
]
}'
JSON
Copy
{
"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
}
}
You can pre-fill part of Claude’s response in the last position of the input messages list. This can be used to shape Claude’s response. The example below uses "max_tokens": 1 to get a single multiple choice answer from Claude.
Shell
Python
TypeScript
Copy
#!/bin/sh
curl https://api.anthropic.com/v1/messages \
--header "x-api-key: $ANTHROPIC_API_KEY" \
--header "anthropic-version: 2023-06-01" \
--header "content-type: application/json" \
--data \
'{
"model": "claude-sonnet-4-5",
"max_tokens": 1,
"messages": [\
{"role": "user", "content": "What is latin for Ant? (A) Apoidea, (B) Rhopalocera, (C) Formicidae"},\
{"role": "assistant", "content": "The answer is ("}\
]
}'
JSON
Copy
{
"id": "msg_01Q8Faay6S7QPTvEUUQARt7h",
"type": "message",
"role": "assistant",
"content": [\
{\
"type": "text",\
"text": "C"\
}\
],
"model": "claude-sonnet-4-5",
"stop_reason": "max_tokens",
"stop_sequence": null,
"usage": {
"input_tokens": 42,
"output_tokens": 1
}
}
For more information on prefill techniques, see our prefill guide .
Claude can read both text and images in requests. We support both base64 and url source types for images, and the image/jpeg, image/png, image/gif, and image/webp media types. See our vision guide
for more details.
Shell
Python
TypeScript
Copy
#!/bin/sh
# Option 1: Base64-encoded image
IMAGE_URL="https://upload.wikimedia.org/wikipedia/commons/a/a7/Camponotus_flavomarginatus_ant.jpg"
IMAGE_MEDIA_TYPE="image/jpeg"
IMAGE_BASE64=$(curl "$IMAGE_URL" | base64)
curl https://api.anthropic.com/v1/messages \
--header "x-api-key: $ANTHROPIC_API_KEY" \
--header "anthropic-version: 2023-06-01" \
--header "content-type: application/json" \
--data \
'{
"model": "claude-sonnet-4-5",
"max_tokens": 1024,
"messages": [\
{"role": "user", "content": [\
{"type": "image", "source": {\
"type": "base64",\
"media_type": "'$IMAGE_MEDIA_TYPE'",\
"data": "'$IMAGE_BASE64'"\
}},\
{"type": "text", "text": "What is in the above image?"}\
]}\
]
}'
# Option 2: URL-referenced image
curl https://api.anthropic.com/v1/messages \
--header "x-api-key: $ANTHROPIC_API_KEY" \
--header "anthropic-version: 2023-06-01" \
--header "content-type: application/json" \
--data \
'{
"model": "claude-sonnet-4-5",
"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?"}\
]}\
]
}'
JSON
Copy
{
"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-sonnet-4-5",
"stop_reason": "end_turn",
"stop_sequence": null,
"usage": {
"input_tokens": 1551,
"output_tokens": 71
}
}
See our guide for examples for how to use tools with the Messages API. See our computer use guide for examples of how to control desktop computer environments with the Messages API.
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