- What is tacman/ai-batch-bundle used for?
- It is a Symfony bundle for asynchronous AI batch processing using symfony/ai. It lets you queue prompts, submit batches to an AI provider, track job status, and retrieve results without blocking requests. Typical uses include bulk generation, classification, and other high-volume AI workflows.
- How do I install tacman/ai-batch-bundle in a Laravel application?
- Start with composer require tacman/ai-batch-bundle in a non-production Laravel app. The provided overview does not confirm a Laravel service-provider registration path or manual console command registration, so validate command discovery with the batch list command before configuring credentials. Confirm configuration requirements and storage behavior in the repository docs.
- Does tacman/ai-batch-bundle support Laravel, or is it only a Symfony bundle?
- The package is described as a Symfony bundle, while the technical evaluation suggests it can fit Laravel teams through console commands, schedulers, and deployment scripts. Laravel and PHP version support are not confirmed in the provided materials. Verify compatibility against your application's Laravel version, PHP version, queue driver, and deployment model before adopting it.
- Which AI providers does tacman/ai-batch-bundle support?
- The overview only states that it uses symfony/ai and submits batches to your AI provider; it does not list supported providers or APIs. Confirm provider compatibility and credential handling in the package documentation before designing workflows. Treat provider quotas and batch size limits as external constraints you must monitor.
- How do I create and monitor an AI batch job from the CLI?
- The 0.3 release exposes batch create, list, status, wait, and download commands. Run create with a small non-sensitive payload, capture the batch ID, then use status and list for visibility. Use download only after completion, and avoid wait in long-running workers until its timeout and polling behavior are understood.
- Does ai:batch:wait block my Laravel queue workers?
- The evaluation flags ai:batch:wait as a key unknown: it may poll with backoff or hold a process for a long period. Do not wire it into long-running production workers until timeout, polling frequency, and exit behavior are documented. Prefer scheduled status checks for production monitoring.
- Are batch IDs and downloaded results persisted locally?
- The release notes do not confirm whether batch IDs, metadata, or downloaded files are persisted locally or where. Check configuration and storage behavior, including filesystem disks and retention, before relying on the commands for recovery. Plan cleanup for downloaded artifacts and sensitive payloads.
- What Laravel and PHP versions are supported by tacman/ai-batch-bundle?
- Supported Laravel and PHP versions are not confirmed in the provided materials. Confirm them in composer.json and the package docs, then test against your queue driver, filesystem disks, and deployment model. Treat version compatibility as a gating check before production rollout.
- How should I test batch commands safely before production?
- Install in a non-production environment, validate credentials and configuration, then run read-only commands such as batch list and batch status. Exercise create, wait, and download with a small non-sensitive payload, and verify exit codes and output format for automation. Add logging around command invocation and avoid printing sensitive payloads to the console.
- What are the main production risks or alternatives to tacman/ai-batch-bundle?
- Likely risks include expired credentials, provider rate limits, partial batch failure, malformed batch IDs, download interruptions, disk exhaustion, and ambiguous exit codes. Maintenance ownership should cover command behavior, credentials, batch retention, download storage, and cleanup. Alternatives include direct provider SDK batch APIs or Laravel queue jobs that wrap provider calls with your own monitoring.