Artículo: AMZ-B0FHHW2BBG

Scalable AI Agent Engineering: Extend Context Windows and Implement Reliable Memory Systems with Semantic Kernel and Modern Vector Stores (Agentic AI Systems & Workflows)

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Peso con empaque
0.20 kg
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No
Condición
Nuevo
Producto de
Amazon

Sobre este producto
  • Initialize and customize Semantic Kernel in Python and .NET for seamless agent development
  • Construct layered memory (short-term buffers, vector indexes, long-term archives) that balances speed with depth
  • Integrate modern vector stores—FAISS, Pinecone, Qdrant, Redis—for blazing-fast semantic search and retrieval
  • Implement RAG pipelines that ground your agents’ answers in real data, slashing hallucinations
  • Automate context management with sliding-window buffers, summarization cascades, and auto-compression routines
  • Orchestrate multi-agent workflows that share memory, coordinate tasks, and handle complex pipelines from document ingestion to invoice generation
  • Deploy and scale on Kubernetes with autoscaling, telemetry, structured logging, and robust monitoring
  • Benchmark cost vs. performance across embeddings and LLM models to optimize every dollar you spend

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