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feat(analysis): gate page leasing on a vision readiness probe

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The analysis worker leases an analyze_page job (incrementing attempts in
SQL) before calling vision, so a stopped/loading vision burns all retries
and writes a permanent failed page_analysis row. With the vision-manager
autoscaler idle-stopping the container, that would poison the queue on
every cold start.

Add an optional VisionReadiness seam (HTTP GET /health in production) wired
via the new env-only ANALYSIS_VISION_HEALTH_URL. When set, the worker parks
without leasing until the probe answers 2xx; jobs stay pending with
attempts untouched and resume the instant vision is ready. None preserves
today's behavior for always-on endpoints.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
MechaCat02
2026-06-14 14:57:48 +02:00
parent 2b7a11b480
commit b86aa80c87
6 changed files with 258 additions and 1 deletions
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11
backend/src/config.rs
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@@ -124,6 +124,13 @@ pub struct AnalysisConfig {
pub workers: usize,
/// OpenAI-compatible chat/completions URL (`ANALYSIS_VISION_URL`).
pub endpoint: String,
/// Optional vision readiness probe URL (`ANALYSIS_VISION_HEALTH_URL`),
/// e.g. `http://mangalord-vision:8000/health`. When set, the worker
/// refuses to lease a job until this answers 2xx — so an autoscaler that
/// idle-stops the vision container never lets a job burn its retries or
/// land a `failed` row. `None` (the default) disables the gate, matching
/// the prior behavior for always-on endpoints. Env-only, like `api_key`.
pub vision_health_url: Option<String>,
/// Model id to request (`ANALYSIS_MODEL`).
pub model: String,
/// Optional bearer token (`ANALYSIS_API_KEY`); local servers usually
@@ -190,6 +197,7 @@ impl Default for AnalysisConfig {
enabled: false,
workers: 1,
endpoint: "http://localhost:8000/v1/chat/completions".to_string(),
vision_health_url: None,
model: String::new(),
api_key: None,
request_timeout: Duration::from_secs(120),
@@ -221,6 +229,9 @@ impl AnalysisConfig {
enabled: env_bool("ANALYSIS_ENABLED", d.enabled),
workers: env_usize("ANALYSIS_WORKERS", d.workers).max(1),
endpoint: std::env::var("ANALYSIS_VISION_URL").unwrap_or(d.endpoint),
vision_health_url: std::env::var("ANALYSIS_VISION_HEALTH_URL")
.ok()
.filter(|s| !s.is_empty()),
model: std::env::var("ANALYSIS_MODEL").unwrap_or(d.model),
api_key: std::env::var("ANALYSIS_API_KEY")
.ok()