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docs(web): document AI explanations of backup errors

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Manuel Escalante
2026-11-01 14:36:54 +01:00
parent 5dc98e9daf
commit 9ed09cc28e
2 changed files with 4 additions and 4 deletions
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web/messages/en/docs/monitor/ai-assistant.json
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},
"header": {
"title": "AI Assistant",
"description": "Optional AI rewriting turns eligible notification templates into plain-language messages, with per-channel detail levels, thirteen UI languages, custom prompts, a public community library and context enrichment. Backup reports <code>backup_complete</code> and <code>backup_fail</code> bypass AI entirely.",
"description": "Optional AI rewriting turns eligible notification templates into plain-language messages, with per-channel detail levels, thirteen UI languages, custom prompts, a public community library and context enrichment. Backup reports backup_complete and backup_fail are never rewritten; with AI Suggestions on, the AI only appends an explanation when a backup reports errors.",
"section": "ProxMenux Monitor"
},
"intro": {
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"intro1": "Every commercial provider charges per <em>token</em>, so it's worth understanding what a token is before picking a plan. A token is roughly four characters of English text or about three quarters of a word. The phrase <em>\"Backup completed on storage local-bak\"</em> is around eight tokens. A short journal excerpt of ten lines can be 200-400 tokens depending on the technical density.",
"intro2": "Two things are billed on every call:",
"items": [
"<strong>Input tokens</strong> cover the system prompt and user message: severity, title, rendered body and enriched context. Their number depends on the actual prompt and event content. Each rewritten channel can incur its own input-token usage; backup-complete and backup-fail reports bypass AI.",
"<strong>Input tokens</strong> cover the system prompt and user message: severity, title, rendered body and enriched context. Their number depends on the actual prompt and event content. Each rewritten channel can incur its own input-token usage; backup-complete and backup-fail reports only use tokens when the AI explains backup errors.",
"<strong>Output tokens</strong> — what the model writes back. The Monitor caps this with <code>max_tokens</code> (see the table below). The cap is a <em>limit</em>, not a charge: if the model produces 250 tokens with a cap of 1500, you pay for 250."
],
"capsIntro": "These are the actual caps the dispatcher applies, taken straight from <code>AI_DETAIL_TOKENS</code> in <code>notification_templates.py</code>:",
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},
"templates": {
"heading": "A note on templates",
"body1": "The AI receives a rendered template rather than raw event data. Types such as <code>vm_start</code>, <code>auth_fail</code> and <code>health_degraded</code> have templates in <code>notification_templates.py</code>. The AI rewrites eligible template output; <code>backup_complete</code> and <code>backup_fail</code> retain their deterministic reports and bypass AI.",
"body1": "The AI receives a rendered template rather than raw event data. Types such as <code>vm_start</code>, <code>auth_fail</code> and <code>health_degraded</code> have templates in <code>notification_templates.py</code>. The AI rewrites eligible template output; <code>backup_complete</code> and <code>backup_fail</code> retain their deterministic reports; with AI Suggestions on, the AI only appends an explanation when the backup reports errors.",
"body2": "Two practical implications: the AI never sees a hostname or VMID it has to invent — those fields are placed by the template before the rewrite. And if AI is disabled, the templated body is what gets dispatched directly. The <link>Notifications</link> page documents the dispatch pipeline in full and is the right cross-reference for everything that happens to an event before it reaches this layer."
},
"privacy": {
web/messages/en/docs/monitor/notifications.json
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},
"aiRewrite": {
"heading": "Optional AI rewrite",
"body1": "Eligible events can be rewritten by an LLM before delivery. Backup results (backup_complete and backup_fail) bypass this rewrite. AI is off by default and runs in the dispatch thread when enabled. If the call fails or times out, the original template text is used.",
"body1": "Eligible events can be rewritten by an LLM before delivery. Backup results (backup_complete and backup_fail) are not rewritten; with AI Suggestions on, the AI only appends an explanation when a backup reports errors. AI is off by default and runs in the dispatch thread when enabled. If the call fails or times out, the original template text is used.",
"body2": "Six providers are supported (OpenAI, Anthropic, Google Gemini, Groq, OpenRouter and local Ollama), with per-channel detail level (<code>brief</code>, <code>standard</code>, <code>detailed</code>), output language, prompt mode (<code>default</code> or <code>custom</code>) and an optional custom prompt. Full configuration walk-through, captures and prompt examples live in the dedicated <link>AI Assistant</link> page.",
"privacyTitle": "Privacy note",
"privacyBody": "AI requests can include the title, severity, rendered body, system/custom prompt and collected context, including hostnames, IPs, usernames, errors and journal lines. They go to the selected endpoint. Ollama keeps processing local only with both a local server and a local model; a remote server or cloud model sends data outside the host. Disable rewriting or use a controlled local endpoint and model when event content must stay on the network."