Anthropic AI recently launched a new Message Batches API, which is a useful solution for developers handling large datasets. It allows the submission of up to 10,000 queries at once, offering efficient, asynchronous processing. The API is designed for tasks where speed isn’t crucial, but handling bulk operations effectively matters. It’s especially helpful for non-urgent queries, with results processed within 24 hours and a 50% cost reduction compared to traditional API calls.
What is the Message Batches API?
The Anthropic’s Message Batches API is a service that allows developers to process large amounts of data asynchronously. This means tasks are queued and processed in bulk.
- Submit up to 10,000 queries per batch.
- Processed within 24 hours.
- Costs 50% less than standard API calls.
The API makes it suitable for large-scale operations where real-time responses aren’t necessary. Once a Message Batch is created, it begins processing immediately. Developers can use it to process multiple Messages API requests at once.
Main Features and Benefits
Here’s a breakdown of the key features that make the Anthropic Message Batches API stand out:
- High throughput: Send and process large numbers of requests without hitting rate limits.
- Cost-effective: Get 50% off API costs for bulk operations.
- Scalability: Handle large-scale data tasks, from content moderation to data analysis, without worrying about infrastructure limitations.
- Batch processing: Submit up to 10,000 requests per batch, with results typically ready within 24 hours.
Batch Limitations
While the Anthropic’s Message Batches API offers impressive scalability, it comes with some limitations:
- Maximum batch size: 10,000 requests or 32 MB.
- Processing time: Up to 24 hours.
- Batches expire after 29 days.
- Rate limits apply to API requests, not the number of requests in a batch.
Supported Models
The Message Batches API currently works with several Claude models:
- Claude 3.5 Sonnet
- Claude 3 Haiku
- Claude 3 Opus
According to Anthropic, Amazon Bedrock customers can already access batch inference, and Google Cloud’s Vertex AI support is coming. Developers can batch requests for vision, system messages, multi-turn conversations, and more. Each request within a batch is handled independently, allowing flexibility in combining different types of operations.
How Does the Message Batches API Work?
When using the Anthropic’s API, developers can send large batches of requests to be processed asynchronously. This is ideal for tasks like analyzing massive data sets or conducting content moderation.
- A batch has been created with the requests you provided.
- Each request is processed independently, but results are available only after completing all tasks.
- The process is suited for tasks that don’t need immediate results.
Here’s the Python code showing how to interact with Anthropic’s Message Batches API and send batch requests to one of their AI models, Claude 3.5.
import anthropic
client = anthropic.Anthropic()
client.beta.messages.batches.create(
requests=[
{
"custom_id": "my-first-request",
"params": {
"model": "claude-3-5-sonnet-20240620",
"max_tokens": 1024,
"messages": [
{"role": "user", "content": "Hello, world"}
]
}
},
{
"custom_id": "my-second-request",
"params": {
"model": "claude-3-5-sonnet-20240620",
"max_tokens": 1024,
"messages": [
{"role": "user", "content": "Hi again, friend"}
]
}
},
]
)For cURL and JavaScript, you can check out Anthropic’s API reference here.
Conclusion
Anthropic’s Message Batches API is a game-changer for developers handling large-scale data operations. It provides an efficient, cost-effective way to process bulk requests. It takes the stress out of managing big data tasks. You can analyze large datasets or moderate content. This Anthropic’s API simplifies bulk operations, giving you the flexibility and scale you need.
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