ai-dev-marketplace

Periodic task scheduling patterns with Celery Beat (crontab, interval, solar). Use when configuring periodic tasks, setting up task schedules, implementing recurring jobs, configuring django-celery-beat, or creating dynamic schedules.

Message broker setup patterns (Redis, RabbitMQ, SQS) for Celery including connection strings, SSL configuration, high availability, and production best practices. Use when configuring message brokers, setting up Redis/RabbitMQ/SQS, troubleshooting broker connections, implementing HA/failover, securing broker communications with SSL, or when user mentions broker setup, connection issues, sentinel, quorum queues, or AWS SQS integration.

Django, Flask, FastAPI integration patterns for Celery. Use when integrating Celery with Django, Flask, or FastAPI, setting up framework-specific configurations, handling application contexts, managing database transactions with tasks, configuring async workers, or when user mentions Django Celery, Flask Celery, FastAPI background tasks, framework integration, or web framework task queues.

Flower monitoring setup and configuration for Celery including real-time monitoring, authentication, custom dashboards, and Prometheus metrics integration. Use when setting up Celery monitoring, configuring Flower web UI, implementing authentication, creating custom dashboards, integrating with Prometheus, or when user mentions Flower, Celery monitoring, task monitoring, worker monitoring, or real-time metrics.

Result backend configuration patterns for Celery including Redis, Database, and RPC backends with serialization, expiration policies, and performance optimization. Use when configuring result storage, troubleshooting result persistence, implementing custom serializers, migrating between backends, optimizing result expiration, or when user mentions result backends, task results, Redis backend, PostgreSQL results, result serialization, or backend migration.

Task routing and queue management patterns for Celery including priority queues, topic exchanges, worker-specific routing, and advanced queue configurations. Use when configuring task routing, managing queues, setting up priority queues, implementing worker routing, configuring topic exchanges, or when user mentions task routing, queue management, Celery routing, worker assignments, or message broker routing.

Production-ready Celery task templates with error handling, retries, rate limiting, time limits, and custom task classes. Use when creating Celery tasks, implementing retry logic, adding rate limiting, setting time limits, building custom task classes, validating task inputs with Pydantic, handling database operations, making API calls, or when user mentions task patterns, retry mechanisms, task templates, error handling, task best practices.

Celery canvas patterns for workflow composition including chains, groups, chords, signatures, error handling, and nested workflows. Use when building complex task workflows, parallel execution patterns, task synchronization, callback handling, or when user mentions canvas primitives, workflow composition, task chains, parallel processing, or chord patterns.

Cost estimation scripts and tools for calculating GPU hours, training costs, and inference pricing across Modal, Lambda Labs, and RunPod platforms. Use when estimating ML training costs, comparing platform pricing, calculating GPU hours, budgeting for ML projects, or when user mentions cost estimation, pricing comparison, GPU budgeting, training cost analysis, or inference cost optimization.

Provides three production-ready ML training examples (sentiment classification, text generation, RedAI trade classifier) with complete training scripts, deployment configs, and datasets. Use when user needs example projects, reference implementations, starter templates, or wants to see working code for sentiment analysis, text generation, or financial trade classification.

Google Cloud Platform configuration templates for BigQuery ML and Vertex AI training with authentication setup, GPU/TPU configs, and cost estimation tools. Use when setting up GCP ML training, configuring BigQuery ML models, deploying Vertex AI training jobs, estimating GCP costs, configuring cloud authentication, selecting GPUs/TPUs for training, or when user mentions BigQuery ML, Vertex AI, GCP training, cloud ML setup, TPU training, or Google Cloud costs.

Training monitoring dashboard setup with TensorBoard and Weights & Biases (WandB) including real-time metrics tracking, experiment comparison, hyperparameter visualization, and integration patterns. Use when setting up training monitoring, tracking experiments, visualizing metrics, comparing model runs, or when user mentions TensorBoard, WandB, training metrics, experiment tracking, or monitoring dashboard.

Templates and patterns for common ML training scenarios including text classification, text generation, fine-tuning, and PEFT/LoRA. Provides ready-to-use training configurations, dataset preparation scripts, and complete training pipelines. Use when building ML training pipelines, fine-tuning models, implementing classification or generation tasks, setting up PEFT/LoRA training, or when user mentions model training, fine-tuning, classification, generation, or parameter-efficient tuning.

Data validation and pipeline testing utilities for ML training projects. Validates datasets, model checkpoints, training pipelines, and dependencies. Use when validating training data, checking model outputs, testing ML pipelines, verifying dependencies, debugging training failures, or ensuring data quality before training.

Agentic Platform Contract tables for AI agent applications - runs, events, artifacts, and tool calls tracking. Use when building AI agent backends that need structured run/event storage.

Configure Supabase authentication providers (OAuth, JWT, email). Use when setting up authentication, configuring OAuth providers (Google/GitHub/Discord), implementing auth flows, configuring JWT settings, or when user mentions Supabase auth, social login, authentication setup, or auth configuration.

End-to-end testing scenarios for Supabase - complete workflow tests from project creation to AI features, validation scripts, and comprehensive test suites. Use when testing Supabase integrations, validating AI workflows, running E2E tests, verifying production readiness, or when user mentions Supabase testing, E2E tests, integration testing, pgvector testing, auth testing, or test automation.

Configure pgvector extension for vector search in Supabase - includes embedding storage, HNSW/IVFFlat indexes, hybrid search setup, and AI-optimized query patterns. Use when setting up vector search, building RAG systems, configuring semantic search, creating embedding storage, or when user mentions pgvector, vector database, embeddings, semantic search, or hybrid search.

Row Level Security policy templates for Supabase - multi-tenant patterns, user isolation, role-based access, and secure-by-default configurations. Use when securing Supabase tables, implementing RLS policies, building multi-tenant AI apps, protecting user data, creating chat/RAG systems, or when user mentions row level security, RLS, Supabase security, tenant isolation, or data access policies.

RLS policy testing patterns for Supabase - automated test cases for Row Level Security enforcement, user isolation verification, multi-tenant security, and comprehensive security audit scripts. Use when testing RLS policies, validating user isolation, auditing Supabase security, verifying tenant isolation, testing row level security, running security tests, or when user mentions RLS testing, security validation, policy testing, or data leak prevention.

Production-ready database schema patterns for AI applications including chat/conversation schemas, RAG document storage with pgvector, multi-tenant organization models, user management, and AI usage tracking. Use when building AI applications, creating database schemas, setting up chat systems, implementing RAG, designing multi-tenant databases, or when user mentions supabase schemas, chat database, RAG storage, pgvector, embeddings, conversation history, or AI application database.

Database schema validation tools - SQL syntax checking, constraint validation, naming convention enforcement, and schema integrity verification. Use when validating database schemas, checking migrations, enforcing naming conventions, verifying constraints, or when user mentions schema validation, migration checks, database best practices, or PostgreSQL validation.

API authentication patterns, SDK installation scripts, environment variable management, and connection testing for ElevenLabs. Use when setting up ElevenLabs authentication, installing ElevenLabs SDK, configuring API keys, testing ElevenLabs connection, or when user mentions ElevenLabs authentication, xi-api-key, ELEVENLABS_API_KEY, or ElevenLabs setup.

Production deployment patterns for ElevenLabs API including rate limiting, error handling, monitoring, and testing. Use when deploying to production, implementing rate limiting, setting up monitoring, handling errors, testing concurrency, or when user mentions production deployment, rate limits, error handling, monitoring, ElevenLabs production.

ElevenLabs Speech-to-Text transcription workflows with Scribe v1 supporting 99 languages, speaker diarization, and Vercel AI SDK integration. Use when implementing audio transcription, building STT features, integrating speech-to-text, setting up Vercel AI SDK with ElevenLabs, or when user mentions transcription, STT, Scribe v1, audio-to-text, speaker diarization, or multi-language transcription.

Async SQLAlchemy 2.0+ database patterns for FastAPI including session management, connection pooling, Alembic migrations, relationship loading strategies, and query optimization. Use when implementing database models, configuring async sessions, setting up migrations, optimizing queries, managing relationships, or when user mentions SQLAlchemy, async database, ORM, Alembic, database performance, or connection pooling.

REST API design and implementation patterns for FastAPI endpoints including CRUD operations, pagination, filtering, error handling, and request/response models. Use when building FastAPI endpoints, creating REST APIs, implementing CRUD operations, adding pagination, designing API routes, handling API errors, or when user mentions FastAPI patterns, REST API design, endpoint structure, API best practices, or HTTP endpoints.

Implement and validate FastAPI authentication strategies including JWT tokens, OAuth2 password flows, OAuth2 scopes for permissions, and Supabase integration. Use when implementing authentication, securing endpoints, handling user login/signup, managing permissions, integrating OAuth providers, or when user mentions JWT, OAuth2, Supabase auth, protected routes, access control, role-based permissions, or authentication errors.

Configure multi-platform deployment for FastAPI applications including Docker containerization, Railway, DigitalOcean App Platform, and AWS deployment. Use when deploying FastAPI apps, setting up production environments, containerizing applications, configuring cloud platforms, implementing health checks, managing environment variables, setting up reverse proxies, or when user mentions Docker, Railway, DigitalOcean, AWS, deployment configuration, production setup, or container orchestration.

Production-ready FastAPI project scaffolding templates including directory structure, configuration files, settings management, dependency injection, MCP server integration, and development/production setup patterns. Use when creating FastAPI projects, setting up project structure, configuring FastAPI applications, implementing settings management, adding MCP integration, or when user mentions FastAPI setup, project scaffold, app configuration, environment management, or backend structure.

Memory layer integration patterns for FastAPI with Mem0 including client setup, memory service patterns, user tracking, conversation persistence, and background task integration. Use when implementing AI memory, adding Mem0 to FastAPI, building chat with memory, or when user mentions Mem0, conversation history, user context, or memory layer.

AI-powered content and image generation using content-image-generation MCP with Google Imagen 3/4, Veo 2/3, Claude Sonnet, and Gemini 2.0. Use when generating marketing content, creating hero images, building blog posts, generating product descriptions, creating videos, optimizing AI prompts, estimating generation costs, or when user mentions Imagen, Veo, AI content, AI images, content generation, image generation, video generation, marketing copy, or Google AI.

Astro best practices, routing patterns, component architecture, and static site generation techniques. Use when building Astro websites, setting up routing, designing component architecture, configuring static site generation, optimizing build performance, implementing content strategies, or when user mentions Astro patterns, routing, component design, SSG, static sites, or Astro best practices.

React, MDX, and Tailwind CSS integration patterns for Astro websites. Use when adding React components, configuring MDX content, setting up Tailwind styling, integrating component libraries, building interactive UI elements, or when user mentions React integration, MDX setup, Tailwind configuration, component patterns, or UI frameworks.

Astro content collections setup, type-safe schemas, query patterns, and frontmatter validation. Use when building Astro sites, setting up content collections, creating collection schemas, querying content, validating frontmatter, or when user mentions Astro collections, content management, MDX content, type-safe content, or collection queries.

Supabase CMS integration patterns, schema design, RLS policies, and content management for Astro websites. Use when building CMS systems, setting up Supabase backends, creating content schemas, implementing RLS security, or when user mentions Supabase CMS, headless CMS, content management, database schemas, or Row Level Security.

DigitalOcean Managed Database provisioning and connection patterns

DigitalOcean networking patterns - VPCs, firewalls, load balancers, DNS

AI agent workflow patterns including ReAct agents, multi-agent systems, loop control, tool orchestration, and autonomous agent architectures. Use when building AI agents, implementing workflows, creating autonomous systems, or when user mentions agents, workflows, ReAct, multi-step reasoning, loop control, agent orchestration, or autonomous AI.

Generative UI implementation patterns for AI SDK RSC including server-side streaming components, dynamic UI generation, and client-server coordination. Use when implementing generative UI, building AI SDK RSC, creating streaming components, or when user mentions generative UI, React Server Components, dynamic UI, AI-generated interfaces, or server-side streaming.

Validate and debug Vercel AI SDK provider configurations including API keys, environment setup, model compatibility, and rate limiting. Use when encountering provider errors, authentication failures, API key issues, missing environment variables, model compatibility problems, rate limiting errors, or when user mentions provider setup, configuration debugging, or SDK connection issues.

RAG (Retrieval Augmented Generation) implementation patterns including document chunking, embedding generation, vector database integration, semantic search, and RAG pipelines. Use when building RAG systems, implementing semantic search, creating knowledge bases, or when user mentions RAG, embeddings, vector database, retrieval, document chunking, or knowledge retrieval.

Testing patterns for Vercel AI SDK including mock providers, streaming tests, tool calling tests, snapshot testing, and test coverage strategies. Use when implementing tests, creating test suites, mocking AI providers, or when user mentions testing, mocks, test coverage, AI testing, streaming tests, or tool testing.

Agent-to-Agent (A2A) executor implementation patterns for task handling, execution management, and agent coordination. Use when building A2A executors, implementing task handlers, creating agent execution flows, or when user mentions A2A protocol, task execution, agent executors, task handlers, or agent coordination.

Integration patterns for combining Agent-to-Agent (A2A) Protocol with Model Context Protocol (MCP) for hybrid agent communication. Use when building systems that need both agent-to-agent communication and agent-to-tool integration, implementing composite architectures, or when user mentions A2A+MCP integration, hybrid protocols, or multi-agent tool access.

SDK installation and setup patterns for Agent-to-Agent Protocol across Python, TypeScript, Java, C#, and Go. Use when implementing A2A protocol, setting up SDKs, configuring authentication, or when user mentions SDK installation, language-specific setup, or A2A integration.

A2A agent card JSON templates with schema validation and examples for different agent types. Use when creating agent cards, implementing A2A protocol discovery, setting up agent metadata, configuring authentication schemes, defining agent capabilities, or when user mentions agent card, agent discovery, A2A metadata, service endpoint configuration, or agent authentication setup.

Vercel deployment configuration and optimization for Next.js applications including vercel.json setup, environment variables, build optimization, edge functions, and deployment troubleshooting. Use when deploying to Vercel, configuring deployment settings, optimizing build performance, setting up environment variables, configuring edge functions, or when user mentions Vercel deployment, production setup, build errors, or deployment optimization.

2025 SEO best practices for Next.js including Core Web Vitals (INP replaces FID), E-E-A-T signals, Schema markup, AI content guidelines, and technical SEO. Use when optimizing pages for search engines, implementing metadata, adding structured data, or improving page speed.

Setup Tailwind CSS and shadcn/ui component library for Next.js projects. Use when configuring Tailwind CSS, installing shadcn/ui, setting up design tokens, configuring dark mode, initializing component library, or when user mentions Tailwind setup, shadcn/ui installation, component system, design system, or theming.

Expo and React Native patterns for mobile development with EAS Build, SDK integration, and native module configuration. Use when building Expo apps, configuring native features, or setting up app signing for store deployment.

Mobile authentication patterns with Clerk, Supabase, and custom auth including biometrics, secure storage, and social login. Use when implementing authentication, managing tokens, or setting up biometric unlock.

React Navigation patterns for mobile apps including stack, tab, drawer navigators, deep linking, and typed navigation with TypeScript. Use when building navigation structure, handling deep links, or implementing authentication flows.

Responsive design patterns for mobile apps including adaptive layouts, safe areas, screen size handling, and platform-specific styling. Use when building responsive UI or handling different screen sizes.

Deep reasoning with Claude's extended thinking feature for complex multi-step problems. Use when implementing think-aloud reasoning, complex analysis, or debugging difficult issues.

Validates Claude Agent SDK configuration files, environment setup, dependencies, and project structure

Stripe integration templates with reusable code for Checkout, Payment Intents, and Subscriptions. Use when implementing Stripe payments, building checkout flows, handling subscriptions, or integrating payment processing.

Production-ready Supabase database schemas for customers, subscriptions, payments, invoices, and webhook events with comprehensive Row Level Security policies. Use when setting up payment infrastructure, creating subscription tables, implementing secure payment data storage, or configuring RLS policies for multi-tenant payment systems.

Webhook validation patterns with signature verification, event logging, and testing tools. Use when implementing webhooks, validating webhook signatures, securing payment webhooks, testing webhook endpoints, preventing replay attacks, or when user mentions webhook security, Stripe webhooks, signature verification, webhook testing, or event validation.

Document chunking implementations and benchmarking tools for RAG pipelines including fixed-size, semantic, recursive, and sentence-based strategies. Use when implementing document processing, optimizing chunk sizes, comparing chunking approaches, benchmarking retrieval performance, or when user mentions chunking, text splitting, document segmentation, RAG optimization, or chunk evaluation.

Multi-format document parsing tools for PDF, DOCX, HTML, and Markdown with support for LlamaParse, Unstructured.io, PyPDF2, PDFPlumber, and python-docx. Use when parsing documents, extracting text from PDFs, processing Word documents, converting HTML to text, extracting tables from documents, building RAG pipelines, chunking documents, or when user mentions document parsing, PDF extraction, DOCX processing, table extraction, OCR, LlamaParse, Unstructured.io, or document ingestion.

Google File Search API patterns for managed RAG with Gemini. Covers both TypeScript (@google/genai) and Python (google-genai) SDKs. Use when building File Search integrations, implementing RAG with Google AI, or when user mentions Google File Search, Gemini RAG, document indexing, or semantic search.

Model routing configuration templates and strategies for cost optimization, speed optimization, quality optimization, and intelligent fallback chains. Use when building AI applications with OpenRouter, implementing model routing strategies, optimizing API costs, setting up fallback chains, implementing quality-based routing, or when user mentions model routing, cost optimization, fallback strategies, model selection, intelligent routing, or dynamic model switching.

Configuration validation and testing utilities for OpenRouter API. Use when validating API keys, testing model availability, checking routing configuration, troubleshooting connection issues, analyzing usage costs, or when user mentions OpenRouter validation, config testing, API troubleshooting, model availability, or cost analysis.

OpenRouter framework integration templates for Vercel AI SDK, LangChain, and OpenAI SDK. Use when integrating OpenRouter with frameworks, setting up AI providers, building chat applications, implementing streaming responses, or when user mentions Vercel AI SDK, LangChain, OpenAI SDK, framework integration, or provider setup.

Agent-to-Agent (A2A) protocol implementation patterns for Google ADK - exposing agents via A2A, consuming external agents, multi-agent communication, and protocol configuration. Use when building multi-agent systems, implementing A2A protocol, exposing agents as services, consuming remote agents, configuring agent cards, or when user mentions A2A, agent-to-agent, multi-agent collaboration, remote agents, or agent orchestration.

Comprehensive observability setup patterns for Google ADK agents including logging configuration, Cloud Trace integration, BigQuery Agent Analytics, and third-party observability tools (AgentOps, Phoenix, Weave). Use when implementing monitoring, debugging agent behavior, analyzing agent performance, setting up tracing, or when user mentions observability, logging, tracing, BigQuery analytics, AgentOps, Phoenix, Arize, or Weave.

Configure ADK bidi-streaming for real-time multimodal interactions. Use when building live voice/video agents, implementing real-time streaming, configuring LiveRequestQueue, setting up audio/video processing, or when user mentions bidi-streaming, real-time agents, streaming tools, multimodal streaming, or Gemini Live API.

Best practices for memory architecture design including user vs agent vs session memory patterns, vector vs graph memory tradeoffs, retention strategies, and performance optimization. Use when designing memory systems, architecting AI memory layers, choosing memory types, planning retention strategies, or when user mentions memory architecture, user memory, agent memory, session memory, memory patterns, vector storage, graph memory, or Mem0 architecture.

Performance optimization patterns for Mem0 memory operations including query optimization, caching strategies, embedding efficiency, database tuning, batch operations, and cost reduction for both Platform and OSS deployments. Use when optimizing memory performance, reducing costs, improving query speed, implementing caching, tuning database performance, analyzing bottlenecks, or when user mentions memory optimization, performance tuning, cost reduction, slow queries, caching, or Mem0 optimization.

Complete Supabase setup for Mem0 OSS including PostgreSQL schema with pgvector for embeddings, memory_relationships tables for graph memory, RLS policies for user/tenant isolation, performance indexes, connection pooling, and backup/migration strategies. Use when setting up Mem0 with Supabase, configuring OSS memory backend, implementing memory persistence, migrating from Platform to OSS, or when user mentions Mem0 Supabase, memory database, pgvector for Mem0, memory isolation, or Mem0 backup.

DeepEval pytest-style LLM testing patterns with built-in metrics, custom evaluators, and CI integration. Use when creating LLM tests, evaluating RAG quality, or measuring faithfulness/relevance.

Supabase-backed evaluation tracking with runs, cases, and scores tables. Use when storing eval results, building dashboards, or tracking regression over time.

promptfoo configuration patterns for prompt regression testing, multi-provider comparison, and assertion-based validation. Use when setting up prompt testing, comparing LLM providers, or creating eval pipelines.

Email delivery patterns including single, batch, scheduled emails and attachment handling. Use when building transactional email systems, batch communication workflows, scheduled delivery, or implementing file/URL attachments with reply-to and CC/BCC functionality.

React Email component patterns for building responsive email templates using JSX, component composition, and preview servers. Use when creating reusable email components, building responsive templates, setting up email preview environments, or integrating React Email with Resend for dynamic email content.

Webhook event handling patterns for email tracking (sent, delivered, bounced, opened, clicked). Use when implementing email event webhooks, signature verification, processing delivery events, logging email analytics, or building real-time email status tracking.

LangGraph checkpointing patterns for state persistence with memory, SQLite, and Postgres backends. Use when implementing state recovery or human-in-the-loop workflows.

LangGraph workflow patterns including basic graphs, conditional routing, parallel execution, and subgraphs. Use when designing graph structure or workflow flow.

BullMQ queue configuration patterns including connection pooling, job options, rate limiting, and TypeScript types. Use when setting up queues or configuring job behavior.

BullMQ worker implementation patterns including job processors, concurrency, error handling, and graceful shutdown. Use when creating workers or handling job processing.