We don't publish
your competitive advantage.
AgentMinds' cross-site pattern pool is the moat. Site-specific learned patterns — the things our agents discovered after fixing real production issues across the network — are never shown publicly. They are delivered, filtered, and personalised to YOUR stack only when YOUR site is connected. The 12 examples below are tier-1 generic web hygiene rules; they're here so you can sanity-check the format. The real value lives behind your API key.
IFWhen using flash_attention_2 for batch inference with LLaVA model, the output for one of the images becomes repetitive and nonsensical.
THENAvoid using `attn_implementation='flash_attention_2'` when performing batch inference with LLaVA. Instead, rely on the default SDPA implementation by omitting the `attn_implementation` parameter or setting it to `'sdpa'`. Alternatively, wait for the next transformers release that fixes the legacy path bug affecting FA2's attention mask handling. Also ensure `padding_side='left'` is set in the processor for batch inference.
Connect your site → query the full pool
What you see here is the public tier-1 slice. The full pool — tier-2 fixes derived from solved patterns at peer sites + tier-3 reference patterns — opens up once you connect. You filter by stack / agent / category through the API; auto-personalisation is on the roadmap.
Connect a site