backend-rag-implementation
Build RAG systems to ground LLMs in proprietary data. Includes vector database integration, embedding strategies, hybrid search, and advanced retrieval patterns for FastAPI backends.
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446 skills found
Build RAG systems to ground LLMs in proprietary data. Includes vector database integration, embedding strategies, hybrid search, and advanced retrieval patterns for FastAPI backends.
Automate frontend API integration using Apidog and MCP servers. Generate TypeScript types, TanStack Query hooks, and axios-based clients from OpenAPI specifications for consistent, type-safe API consumption.
Symbol-level code understanding and navigation agent toolkit using LSP for precise code analysis, reference tracking, and surgical refactoring across 30+ programming languages.
Meta Marketing CLI for Graph API automation, managing ad campaigns, insights reporting, and Instagram publishing with fail-closed security.
Manages Cloudflare zones via API. Use for purging cache, querying DNS records, and monitoring analytics via GraphQL.
Semantic code analysis guide for Serena MCP. Automatically prioritizes Serena tools for symbols, references, and code memory to optimize context and efficiency.
Deploy isolated development containers with web-accessible VSCode, VNC, and automated app routing via Traefik or Cloudflare Tunnels.
An all-in-one Chinese daily utility toolkit: weather, currency exchange, news, and package tracking. Zero configuration, no API keys required.
Expert guidance for configuring FeatBit observability via OpenTelemetry. Use for setting up metrics, logs, traces, and connecting OTEL backends like Seq, Jaeger, or Prometheus for FeatBit backend monitoring.
An MCP server enabling agents to edit, manage, and compile Arduino IDE 2.0 sketches, including source code manipulation and automated build capabilities via arduino-cli.
Manage client relationships, track follow-ups, and automate personalized email drafts using Obsidian-based client profiles.
A framework to transform experimental ML prototypes into robust, production-ready Python packages using src layout, hybrid architecture, and strict configuration management.