Two-Track Program for Dialogue Status Maintenance
Dialog continuity maintenance requirements for Grok-2:
Option A: Technology Enhanced
- modifications
tokenizer.tok.jsonincrease<|dialog|>and other special markings - adoptionvLLMThe persistent caching technique that sets the
--enable-continuous-batching - Reserve 10-20% of video memory per dialog round for K/V caching
Option B: Architecture Improved
- Realization of externalLangChainMemory module for storing historical conversations through vector databases
- Designing a two-stage retrieval mechanism: semantic search followed by temporal ordering
- Add dialog state tracking (DST) middleware to handle coreference
Comparison of results: Technical solution A has lower latency (<100ms) but consumes video memory, solution B supports longer history (100+ rounds) but introduces 50-80ms additional latency. In practice, it is recommended to adopt a hybrid strategy according to the needs of the scenario.
This answer comes from the articleGrok-2: xAI's Open Source Hybrid Expert Large Language ModelThe
May not be reproduced without permission:AI productivity tools " How to avoid context loss in Grok-2 in multiple rounds of dialog?
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