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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161 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.
Expert guidance for Neo4j Cypher queries and MCP server tools, focusing on schema introspection, graph operations, and efficient database development workflows.
Retrieve current weather conditions, forecasts, and temperature data for global locations to assist with daily planning and travel.
Automatically apply safe quality fixes including formatting (Black, isort), linting (Ruff auto-fixes), and resolving formatter conflicts to maintain Python code quality.
Operate Railway infrastructure: manage projects, services, databases, object storage, deployments, environments, variables, logs, and performance metrics.
Supermemory is a long-term memory infrastructure for AI agents, enabling persistent context, user profiles, and semantic RAG across multi-modal knowledge bases.
A prototype skill for automating YouTube live chat moderation using pattern-based detection for spam, toxic content, and rate limiting, optimized for testing agent reliability before deployment.
Anthropic Claude integration patterns: streaming, RAG with pgvector, tool use, model selection (Haiku/Sonnet/Opus), prompt caching, and cost management for AI-powered engineering.
Automate release note generation from git commits. Categorizes changes, transforms technical jargon into user-friendly summaries, and supports CHANGELOG.md, PR bodies, and Slack announcements.
AI language tutor for personalized learning through conversation, grammar lessons, vocabulary drills, and flashcards. Supports 100+ languages including Spanish, French, Japanese, and Mandarin.
A perspective engineering engine that researches, extracts mental models, and generates runnable persona skills based on deep expression DNA analysis.
Orchestrate complex workflows by coordinating multiple specialized AI agents for multi-perspective code analysis, feature implementation, and system-wide reviews.