rag-implementation
Build production-grade RAG systems using vector databases, semantic search, and LangGraph to ground LLMs in external knowledge.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
161 skills found
Build production-grade RAG systems using vector databases, semantic search, and LangGraph to ground LLMs in external knowledge.
Manage dlt data pipelines and Temporal workflows for the SignalRoom marketing platform. Sync sources like Everflow, Redtrack, and S3 to Postgres, check status, and debug ingestion.
End-to-end autonomous research agent: from idea generation and literature review to experiment execution, adversarial review loops, and paper writing.
A toolkit for building robust LLM integrations: API patterns, streaming, function calling, RAG pipelines, and cost-effective model routing.
Architect and optimize production-grade RAG systems. Master embedding models, vector databases, chunking strategies, and retrieval pipelines for high-accuracy LLM applications.
An end-to-end video processing pipeline that transforms raw recordings into transcripts, key insights, short clips, and polished articles.
AI-powered lead generation pipeline: intelligent lead scoring (0-100) and context-aware follow-up generation for sales, cold outreach, and CRM integration.
Build RAG systems to ground LLMs in proprietary data. Includes vector database integration, embedding strategies, hybrid search, and advanced retrieval patterns for FastAPI backends.
A suite of professional tools for auditing, evaluating, chunking, and scaffolding production-ready RAG pipelines within Claude Code.
Directly interface with RagCode MCP via SSE protocol without complex configuration files or binary dependencies.
Automated single-cell RNA-seq quality control pipeline following scverse best practices. Performs MAD-based outlier detection, cell filtering, and diagnostic visualization for .h5ad and .h5 datasets.
A framework for managing the end-to-end LLM project lifecycle, from evaluating task-model fit and pipeline architecture design to implementing structured output parsing and agent-assisted development.