Appwrite Full-Stack MVP Stack
For builders who want backend primitives without stitching together five services. Auth, database, storage, and functions come from Appwrite while the frontend stays in a normal Next.js app.
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Production Python backend for AI-powered applications — designed for the async I/O, complex dependencies, and long-running inference jobs that come with serving language models at real traffic.
Workflow stack
The order matters. Start at the top, read down the sequence, and open any step when you want the note behind it.
Persistent storage
Stores conversation history, user profiles, and AI output logs — the pgvector extension adds similarity search for RAG pipelines without a separate vector database.
Open tool profileTask queue
Celery broker for long-running inference jobs like document parsing and batch generation — keeps the API response time fast by pushing heavy work to background workers.
Open tool profileContainer packaging
Pin exact Python and package versions in a container — AI dependencies are notoriously fragile and reproducible builds prevent the worked-in-dev-failed-in-prod incidents.
Open tool profileDeployment
Deploy containers close to users globally with persistent volumes for model weights — simpler than EKS for AI workloads that don't need full Kubernetes orchestration.
Open tool profileError monitoring
Full Python async tracebacks for FastAPI — captures coroutine failures, LLM timeout errors, and Celery task exceptions with the full request context attached.
Open tool profileTools in this stack
Open any tool profile if you want pricing, fit, or comparison details.
Python API framework built around type hints, automatic docs, and high-performance async request handling.
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I run five side projects on one DigitalOcean Droplet for $24 a month. This stack handles 80k monthly visitors combined and has taught me more about infrastructure than years of managed platforms ever did.
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