SemanticScuttle - klotz.me

klotz: context* + agent*

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1. A curated list of awesome platforms, tools, practices and resources that helps run LLMs locally

   - **Inference** – Platforms and engines for running models, plus user interfaces.
   - **Models** – LLMs (general, coding, multimodal, image, audio), model providers, and specific model highlights.
   - **RAG** – Retrieval-Augmented Generation tools.
   - **Safeguards** – Safety and content filtering.
   - **Agents & Tools** – Agent frameworks, Model Context Protocol, coding agents, computer/browser automation, memory management, and testing/evaluation.
   - **Research, Training & Fine-tuning** – Security, sandboxing, and model development.
   - **Hardware** – Local hardware options.
   - **Tutorials** – Guides covering models, prompt/context engineering, inference, agents, and RAG.
   - **Communities** – Places to connect and share knowledge.

   2026-08-22 Tags: github, rafska, awesome list, local llm, llm, tag, agent, tools, harness, inference, context by klotz
2. Context architecture is replacing RAG as agentic AI pushes enterprise retrieval to its limits

   **Redis Iris** is a context and memory platform designed for agentic pull architectures. It replaces static RAG with dynamic, live-synced data, semantic tool access, and session management to handle high-frequency AI agent requests at scale.
   
   * Delivers petabyte-scale retrieval with sub-millisecond latency by optimizing costs (99% flash/SSD, 1% RAM).
   * Auto-generates MCP tools via Pydantic models, enabling agents to query business data directly with row-level access controls.
   * Uses CDC pipelines for continuous synchronization with sources like Snowflake, Databricks, and Postgres.

   2026-05-19 Tags: redis, iris, petabyte, llm, agent, context, pedantic, postgres by klotz

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