Artículo: AMZ-B0FHR7WTLW

Practical Context Engineering for AI Developers: Optimize token management, memory stores, and RAG pipelines with LangChain and Semantic Kernel for ... projects (AI Agents MAde Easy for Everyone)

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0.20 kg
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No
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Producto de
Amazon

Sobre este producto
  • Optimize token management so your prompts pack maximum relevance within model limits.
  • Configure and combine memory stores—from FAISS and Pinecone to Dragonfly and Redis—for instant, session-aware recall.
  • Construct both pure-play and agentic RAG pipelines, weaving together semantic and keyword retrieval, reranking, and multi-model orchestration.
  • Automate context compression and token budgeting, using on-the-fly summarization and dynamic selection to control latency and expenses.
  • Secure and scale your services, from PII detection and encryption to containerized deployment, Kubernetes auto-scaling, and telemetry-driven monitoring.
  • Extend your stack with custom retrievers, external API integrations, domain-tuned embedding models, and feedback-driven improvements.

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