चैट हिस्टरी

RAG & GenAI Copilot

Build and debug production RAG

Production RAG & GenAI Copilot helps you design, debug, evaluate, secure, and operate retrieval-augmented generation systems. It can trace failures across ingestion, parsing, chunking, indexing, retrieval, reranking, context construction, generation, citations, authorization, and evaluation; design practical RAG architectures; build retrieval and groundedness evals; review prompt-injection and data-leakage risks; and improve observability, latency, and cost. It favors measurable evidence, reversible fixes, source-level authorization, and simple architectures over prompt-only fixes or unnecessary complexity.

स्किल

Production RAG & GenAI Copilot

जानकारी

क्षमताएं: Design production RAG architectures for quality, freshness, security, latency, and cost, Debug retrieval and grounded-generation failures from traces, logs, prompts, and evals, Diagnose parsing, chunking, indexing, metadata, filtering, reranking, and context issues, Evaluate retrieval quality, groundedness, citation correctness, abstention, and regressions, Review prompt injection, RAG poisoning, cross-tenant leakage, and authorization risks, Plan low-blast-radius incident containment, verification, rollback, and permanent fixes, Improve hybrid retrieval, query rewriting, reranking, context packing, and source precedence, Design observability for retrieval traces, model calls, citations, latency, tokens, and cost, Compare retrievers, rerankers, models, vector stores, and architecture trade-offs, Use current official documentation for model, vector-store, SDK, security, and platform changes
डेवलपर: Krishna Sathvik
श्रेणी: Developer Tools
वर्ज़न: 0.1.0

चैट हिस्टरी

जानकारी

क्षमताएं

Design production RAG architectures for quality, freshness, security, latency, and cost, Debug retrieval and grounded-generation failures from traces, logs, prompts, and evals, Diagnose parsing, chunking, indexing, metadata, filtering, reranking, and context issues, Evaluate retrieval quality, groundedness, citation correctness, abstention, and regressions, Review prompt injection, RAG poisoning, cross-tenant leakage, and authorization risks, Plan low-blast-radius incident containment, verification, rollback, and permanent fixes, Improve hybrid retrieval, query rewriting, reranking, context packing, and source precedence, Design observability for retrieval traces, model calls, citations, latency, tokens, and cost, Compare retrievers, rerankers, models, vector stores, and architecture trade-offs, Use current official documentation for model, vector-store, SDK, security, and platform changes

डेवलपर

Krishna Sathvik

श्रेणी

Developer Tools

वर्ज़न

0.1.0