Process multiple images - DreamLayer

DreamLayer currently exposes individual executions, not a native batch submission endpoint. A conversation is a sequence of turns, not a batch. Keep each image’s request, key, execution ID, and output separate.

A queue you can resume

Create one request JSON per image using the runnable examples. For edits, upload each reference once and store its input asset ID in that file. Use the Python queue below with agent_client.py in the same directory:

from pathlib import Path
import subprocess
import time

for request in sorted(Path("requests").glob("*.json")):
    journal = Path("jobs") / request.name
    journal.parent.mkdir(exist_ok=True)
    command = (["resume", str(journal)] if journal.exists()
               else ["submit", str(request), str(journal)])
    result = subprocess.run(["python3", "agent_client.py", *command], check=False)
    if result.returncode:
        print(f"Needs attention: {journal}")
        # Stop admission: the failed client may still own an active server job.
        # Inspect canonical state before advancing the queue.
        break
    time.sleep(7)  # Also pace submissions; concurrency alone is not rate limiting.

The serial queue is deliberately conservative. If you add concurrency, use a semaphore with at most two active executions across your account and one shared request limiter. Keep work queued locally when the account is busy. Bound retry attempts and honor limits.

Recover partial failures

Item state	Action
Completed	Download that execution’s existing asset; do not regenerate it.
Running or queued	Resume that execution. Keep it counted against your concurrency budget.
Request acknowledgement lost	Replay the saved bytes with their original key.
Needs input	Resolve its question in its conversation before proceeding.
Failed or cancelled	Record the failure. A replacement requires a separate decision and new request identity.

A retryable HTTP error is not proof that a job failed. Keep uncertainty separate from terminal failure. Never rerun an entire group with fresh keys because one item failed.