mirror of
https://github.com/Haidra-Org/AI-Horde.git
synced 2026-11-06 05:17:31 +00:00
tazlin
4063734bd1
- docs/explanation/kudos_retention.md is the entry point: the problem, the three readers of old rows and their replacements, the rejected alternative, partitions by age, the per-dataset replacement and archive table, one state diagram per dataset, properties and costs, a symptom table and a code map - docs/reference/kudos_accounting.md gains the retention sections: catalog columns, states and step table, block reasons, configuration, archive objects, metrics and log lines, health fields, operator commands - docs/how-to/kudos_ledger_operations.md gains the partition conversion, enabling retention with a held-drops soak and a grace period, rehearsing removal on a restored copy, handling blocked units, recovering from late rows or a chain gap, rolling back a removed partition, user statements and archive restore - The explanation of kudos accounting links to the retention explanation instead of describing retention itself; the class index, topics page and site navigation list the new document
1.4 KiB
1.4 KiB
Explanation
Why the subsystems here are built the way they are: the problem each one solves, the alternatives that were weighed, and the properties the chosen design buys.
These pages give the shape of a design. A single choice, with its drivers and its consequences, is recorded instead in Decisions.
Documents
| Document | Summary |
|---|---|
| Kudos accounting, projection, and concurrency | Why kudos movements are recorded as typed events, how the projector materializes them, and how spends stay safe while balances lag. |
| Kudos event retention | Why the kudos event tables keep only an online window, what replaces older rows for each dataset, and what guards each irreversible drop. |
| Request feasibility and queue pressure | Practical guidance for using request progress, worker compatibility, capacity counts, queue estimates, and stall warnings in API clients. |
| Chat requests on the Horde | How chat requests use the text queue, worker capability declarations and a separate OpenAI-compatible front, with the design tradeoffs and client guarantees. |