Clade Webhooks Events

Anthropic Message Batches & Async Processing

Overview

Anthropic doesn't have traditional webhooks. Instead, use Message Batches for async bulk processing — up to 10,000 requests per batch at 50% off, with a 24-hour processing SLA.

Prerequisites

• Completed clade-install-auth
• Multiple prompts/documents to process in bulk
• Tolerance for async processing (results within 24 hours)

Instructions

Step 1: Create a Batch

import Anthropic from '@claude-ai/sdk';

const client = new Anthropic();

const batch = await client.messages.batches.create({
  requests: documents.map((doc, i) => ({
    custom_id: `doc-${i}`,
    params: {
      model: 'claude-sonnet-4-20250514',
      max_tokens: 1024,
      messages: [{ role: 'user', content: `Summarize: ${doc.text}` }],
    },
  })),
});

console.log(`Batch ${batch.id} created — ${batch.request_counts.processing} processing`);

Step 2: Poll for Completion

async function waitForBatch(batchId: string): Promise<Anthropic.Messages.MessageBatch> {
  while (true) {
    const batch = await client.messages.batches.retrieve(batchId);

    if (batch.processing_status === 'ended') {
      console.log(`Batch complete:
        Succeeded: ${batch.request_counts.succeeded}
        Errored: ${batch.request_counts.errored}
        Expired: ${batch.request_counts.expired}`);
      return batch;
    }

    console.log(`Processing... ${batch.request_counts.processing} remaining`);
    await new Promise(r => setTimeout(r, 30_000)); // Check every 30s
  }
}

Step 3: Retrieve Results

const results = await client.messages.batches.results(batch.id);

for await (const result of results) {
  if (result.result.type === 'succeeded') {
    const text = result.result.message.content[0].text;
    console.log(`${result.custom_id}: ${text.substring(0, 100)}...`);
  } else {
    console.error(`${result.custom_id}: ${result.result.type} — ${result.result.error?.message}`);
  }
}

Python Example

import anthropic
import time

client = anthropic.Anthropic()

batch = client.messages.batches.create(
    requests=[
        {
            "custom_id": f"doc-{i}",
            "params": {
                "model": "claude-sonnet-4-20250514",
                "max_tokens": 1024,
                "messages": [{"role": "user", "content": f"Summarize: {doc}"}],
            },
        }
        for i, doc in enumerate(documents)
    ]
)

# Poll
while batch.processing_status != "ended":
    time.sleep(30)
    batch = client.messages.batches.retrieve(batch.id)

# Get results
for result in client.messages.batches.results(batch.id):
    if result.result.type == "succeeded":
        print(result.custom_id, result.result.message.content[0].text[:100])

Batch Limits

Output

• Batch created with up to 10,000 requests
• Processing status tracked via polling
• Results retrieved with per-request success/error status
• Failed requests identified for retry in a new batch

Error Handling

Examples

See Step 1 (batch creation), Step 2 (polling), Step 3 (result retrieval), Python example, and Batch Limits table above.

Resources

• Message Batches API
• Batch Pricing — 50% off standard

Next Steps

See clade-ci-integration for using batches in CI pipelines.