Atlas Notes

Headlines · 2

1. 3h
   How Agents Resume Work With Context, Memory, and Checkpoints

   A tutorial distinguishes chat history, context, long-term memory, checkpoints, and execution records by the information each preserves. Using a synthetic Atlas Notes document-comparison scenario, it explains how an agent can continue research, carry saved preferences into later requests, and distinguish an unknown tool result from an action that never occurred. Open ETF Agent v0.26.0 examples demonstrate memory changes, compaction and rereading, and cross-process recovery.

   掘金 · 人工智能 · 🔥 5
2. 3h
   Tutorial: Tracing Model Inputs Through Prompts, RAG, and Memory

   This tutorial explains how prompts, context, retrieval-augmented generation, and long-term memory contribute different elements to a model’s input. Using synthetic Atlas Notes documents and Open ETF Agent v0.26.0, it shows how to diagnose an incorrect answer by checking whether the task was specified clearly, the required source text reached the request, retrieval selected suitable material, and recalled memory remained applicable. The Open ETF Agent example uses preset actions to simulate model selection, so it does not establish how a real model performs.

   掘金 · 人工智能 · 🔥 5

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