feat(ai): few-shot exemplars + sticky Ollama preference
- Few-shot injection on /insights/generate/agentic: compresses prior training_messages into trajectory blocks (tool calls + result summaries) and injects into the system prompt. Hardcoded default ids with optional request override. - New fewshot_source_ids column on photo_insights (+ migration) to track which exemplars influenced a given row, for downstream training-set filtering. Chat amend rows stamp None with a lineage note. - Ollama client now remembers which server (primary/fallback) most recently succeeded and tries it first on the next call, via a shared Arc<AtomicBool>. Avoids re-404ing the primary on every agent iteration when the chosen model only lives on the fallback. - Demote noisy logs: daily_summary "Summary match" lines to debug; inner chat_with_tools non-2xx body log from error to warn (outer layer owns the terminal-error signal). - Drift-guard tests for summarize_tool_result covering the success / empty / error / unknown shape for every tool. - Tidy: three pre-existing clippy warnings cleaned up. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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@@ -102,6 +102,12 @@ pub struct InsertPhotoInsight {
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pub training_messages: Option<String>,
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/// `"local"` (Ollama with images) | `"hybrid"` (local vision + OpenRouter chat).
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pub backend: String,
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/// JSON array of insight ids whose `training_messages` were compressed
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/// and injected into the system prompt as few-shot exemplars when this
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/// row was generated. `None` means no few-shot was used (pristine
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/// generation). Used downstream to filter out contaminated rows when
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/// assembling an unbiased training / evaluation set.
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pub fewshot_source_ids: Option<String>,
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}
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#[derive(Serialize, Queryable, Clone, Debug)]
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@@ -119,6 +125,7 @@ pub struct PhotoInsight {
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pub approved: Option<bool>,
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/// `"local"` (Ollama with images) | `"hybrid"` (local vision + OpenRouter chat).
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pub backend: String,
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pub fewshot_source_ids: Option<String>,
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}
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// --- Libraries ---
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