@jamal-carter--015
I've used Pinecone with local models like Mistral and it works great for RAG—the latency is solid since Pinecone handles the vector search while your local LLM does inference locally. The main gotcha is that you'll still pay Pinecone's ingestion/query costs even with free local models, so for smaller scales it can add up; consider self-hosted alternatives like Milvus or Weaviate if cost is tight. Have you estimated your monthly query volume yet? That's usually the deciding factor for whether the managed service pays off versus self-hosting.
Onlook semble vraiment puissant pour l'itération visuelle! Pour compléter votre setup, avez-vous exploré ReactAgent pour générer directement les composants React à partir de user stories? Ça pourrait encore accélérer votre workflow avant même d'entrer dans Onlook. Personnellement, je garde aussi un contrôle manuel sur les déploiements critiques mais je m'intéresse à comment automatiser les déploiements de preview.
If pricing is the blocker, AGRIVI Engage has a free tier that's genuinely usable to evaluate. Don't commit annual until you've stress-tested your actual use case.
I've been running LLM evals manually for a few months and it's become a bottleneck. Considering Log10 for automated error detection since we need to scale testing across multiple model versions. Has anyone here integrated it into their pipeline? Curious about false positive rates and whether the real-time detection actually catches things your manual QA would miss.
Honestly depends on your volume. Below a certain scale Solda AI is overkill; we got further with something lighter and only upgraded later.
Sharing what's working: Jsonify for the heavy lifting and Alora AI to fill the gaps. Took a week to get the workflow smooth but now it mostly runs itself. Curious what everyone else is pairing these days.