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>

migrations/2026-04-24-000000_add_fewshot_source_to_insights/down.sql

@@ -0,0 +1,24 @@
+-- SQLite can't DROP COLUMN cleanly on older versions; rebuild the table.
+CREATE TABLE photo_insights_backup AS
+    SELECT id, library_id, rel_path, title, summary, generated_at, model_version,
+           is_current, training_messages, approved, backend
+    FROM photo_insights;
+DROP TABLE photo_insights;
+CREATE TABLE photo_insights (
+    id INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT,
+    library_id INTEGER NOT NULL REFERENCES libraries(id),
+    rel_path TEXT NOT NULL,
+    title TEXT NOT NULL,
+    summary TEXT NOT NULL,
+    generated_at BIGINT NOT NULL,
+    model_version TEXT NOT NULL,
+    is_current BOOLEAN NOT NULL DEFAULT TRUE,
+    training_messages TEXT,
+    approved BOOLEAN,
+    backend TEXT NOT NULL DEFAULT 'local'
+);
+INSERT INTO photo_insights
+    SELECT id, library_id, rel_path, title, summary, generated_at, model_version,
+           is_current, training_messages, approved, backend
+    FROM photo_insights_backup;
+DROP TABLE photo_insights_backup;

migrations/2026-04-24-000000_add_fewshot_source_to_insights/up.sql

@@ -0,0 +1 @@
+ALTER TABLE photo_insights ADD COLUMN fewshot_source_ids TEXT;

src/ai/handlers.rs

@@ -4,6 +4,7 @@ use opentelemetry::trace::{Span, Status, Tracer};
 use serde::{Deserialize, Serialize};
 
 use crate::ai::insight_chat::{ChatStreamEvent, ChatTurnRequest};
+use crate::ai::ollama::ChatMessage;
 use crate::ai::{InsightGenerator, ModelCapabilities, OllamaClient};
 use crate::data::Claims;
 use crate::database::{ExifDao, InsightDao};
@@ -12,6 +13,13 @@ use crate::otel::{extract_context_from_request, global_tracer};
 use crate::state::AppState;
 use crate::utils::normalize_path;
 
+/// Hardcoded few-shot exemplars for the agentic endpoint. Populate with the
+/// ids of approved insights whose `training_messages` should be compressed
+/// into trajectory form and injected into the system prompt. Empty = no
+/// change in behavior. Request-level `fewshot_insight_ids` overrides this
+/// when non-empty.
+const DEFAULT_FEWSHOT_INSIGHT_IDS: &[i32] = &[2918, 2908];
+
 #[derive(Debug, Deserialize)]
 pub struct GeneratePhotoInsightRequest {
     pub file_path: String,
@@ -33,6 +41,12 @@ pub struct GeneratePhotoInsightRequest {
     /// OpenRouter chat). Only respected by the agentic endpoint.
     #[serde(default)]
     pub backend: Option<String>,
+    /// Insight ids whose stored `training_messages` should be compressed
+    /// into few-shot trajectories and injected into the system prompt.
+    /// Silently truncated to the first 2. When absent/empty, the handler
+    /// falls back to `DEFAULT_FEWSHOT_INSIGHT_IDS`.
+    #[serde(default)]
+    pub fewshot_insight_ids: Option<Vec<i32>>,
 }
 
 #[derive(Debug, Deserialize)]
@@ -326,6 +340,41 @@ pub async fn generate_agentic_insight_handler(
         span.set_attribute(KeyValue::new("backend", b.clone()));
     }
 
+    // Resolve few-shot ids: request-provided ids take precedence when
+    // non-empty; otherwise fall back to the hardcoded defaults.
+    let fewshot_ids: Vec<i32> = match request.fewshot_insight_ids.as_deref() {
+        Some(ids) if !ids.is_empty() => ids.iter().take(2).copied().collect(),
+        _ => DEFAULT_FEWSHOT_INSIGHT_IDS
+            .iter()
+            .take(2)
+            .copied()
+            .collect(),
+    };
+    span.set_attribute(KeyValue::new("fewshot_count", fewshot_ids.len() as i64));
+
+    let fewshot_examples: Vec<Vec<ChatMessage>> = {
+        let otel_context = opentelemetry::Context::new();
+        let mut dao = insight_dao.lock().expect("Unable to lock InsightDao");
+        fewshot_ids
+            .iter()
+            .filter_map(|id| {
+                let insight = dao.get_insight_by_id(&otel_context, *id).ok().flatten()?;
+                let json = insight.training_messages?;
+                match serde_json::from_str::<Vec<ChatMessage>>(&json) {
+                    Ok(msgs) => Some(msgs),
+                    Err(e) => {
+                        log::warn!(
+                            "Few-shot insight {} has malformed training_messages: {}",
+                            id,
+                            e
+                        );
+                        None
+                    }
+                }
+            })
+            .collect()
+    };
+
     let result = insight_generator
         .generate_agentic_insight_for_photo(
             &normalized_path,
@@ -338,6 +387,8 @@ pub async fn generate_agentic_insight_handler(
             request.min_p,
             max_iterations,
             request.backend.clone(),
+            fewshot_examples,
+            fewshot_ids,
         )
         .await;
 

src/ai/insight_chat.rs

@@ -502,6 +502,11 @@ impl InsightChatService {
                 .await?;
             let title = title_raw.trim().trim_matches('"').to_string();
 
+            // Amended rows intentionally do not inherit the parent's
+            // `fewshot_source_ids`. The parent's few-shot influence is still
+            // present in this row's content; if you want strict lineage
+            // tracking for training-set filtering, fetch the parent here and
+            // copy its value forward.
             let new_row = InsertPhotoInsight {
                 library_id: req.library_id,
                 file_path: normalized.clone(),
@@ -512,6 +517,7 @@ impl InsightChatService {
                 is_current: true,
                 training_messages: Some(json),
                 backend: effective_backend.clone(),
+                fewshot_source_ids: None,
             };
             let cx = opentelemetry::Context::new();
             let mut dao = self.insight_dao.lock().expect("Unable to lock InsightDao");
@@ -608,7 +614,7 @@ impl InsightChatService {
     ) -> BoxStream<'static, ChatStreamEvent> {
         let svc = self;
         let s = async_stream::stream! {
-            match svc.chat_turn_stream_inner(req, |ev| Ok(ev)).await {
+            match svc.chat_turn_stream_inner(req, Ok).await {
                 Ok(mut rx) => {
                     while let Some(ev) = rx.recv().await {
                         yield ev;
@@ -955,6 +961,11 @@ impl InsightChatService {
                 .await?;
             let title = title_raw.trim().trim_matches('"').to_string();
 
+            // Amended rows intentionally do not inherit the parent's
+            // `fewshot_source_ids`. The parent's few-shot influence is still
+            // present in this row's content; if you want strict lineage
+            // tracking for training-set filtering, fetch the parent here and
+            // copy its value forward.
             let new_row = InsertPhotoInsight {
                 library_id: req.library_id,
                 file_path: normalized.clone(),
@@ -965,6 +976,7 @@ impl InsightChatService {
                 is_current: true,
                 training_messages: Some(json),
                 backend: effective_backend.clone(),
+                fewshot_source_ids: None,
             };
             let cx = opentelemetry::Context::new();
             let mut dao = self.insight_dao.lock().expect("Unable to lock InsightDao");

src/ai/insight_generator.rs

@@ -1227,6 +1227,7 @@ impl InsightGenerator {
             is_current: true,
             training_messages: None,
             backend: "local".to_string(),
+            fewshot_source_ids: None,
         };
 
         let mut dao = self.insight_dao.lock().expect("Unable to lock InsightDao");
@@ -2634,6 +2635,159 @@ Return ONLY the summary, nothing else."#,
     /// text, and runs the loop through OpenRouter (chat only — embeddings
     /// and describe calls stay local in either mode).
     #[allow(clippy::too_many_arguments)]
+    /// Render a set of prior-conversation transcripts into a compact
+    /// trajectory block for inclusion in the system prompt. Tool results
+    /// are summarised to one line each so the prompt stays small.
+    fn render_fewshot_examples(examples: &[Vec<ChatMessage>]) -> String {
+        if examples.is_empty() {
+            return String::new();
+        }
+
+        let mut out = String::from("## Examples of strong context-gathering\n\n");
+        out.push_str(
+            "The following are compressed trajectories from prior high-quality insights. \
+             They show the *pattern* of tool use, not answers to copy.\n\n",
+        );
+
+        for (i, msgs) in examples.iter().enumerate() {
+            out.push_str(&format!("### Example {}\n\n", i + 1));
+            out.push_str(&Self::render_single_trajectory(msgs));
+            out.push('\n');
+        }
+
+        out.push_str("---\n\n");
+        out
+    }
+
+    fn render_single_trajectory(msgs: &[ChatMessage]) -> String {
+        let mut out = String::new();
+
+        if let Some(first_user) = msgs.iter().find(|m| m.role == "user") {
+            let trimmed = first_user
+                .content
+                .lines()
+                .filter(|l| !l.trim().is_empty())
+                .take(8)
+                .collect::<Vec<_>>()
+                .join("\n");
+            out.push_str(&format!("Input:\n{}\n\n", trimmed));
+        }
+
+        out.push_str("Trajectory:\n");
+        let mut step = 1;
+        let mut final_content: Option<String> = None;
+
+        for (i, m) in msgs.iter().enumerate() {
+            if m.role != "assistant" {
+                continue;
+            }
+            if let Some(ref calls) = m.tool_calls {
+                for call in calls {
+                    let args_brief = Self::brief_json_args(&call.function.arguments);
+                    let result_summary = msgs
+                        .get(i + 1)
+                        .filter(|r| r.role == "tool")
+                        .map(|r| Self::summarize_tool_result(&call.function.name, &r.content))
+                        .unwrap_or_else(|| "(no result)".to_string());
+                    out.push_str(&format!(
+                        "{}. {}({}) -> {}\n",
+                        step, call.function.name, args_brief, result_summary
+                    ));
+                    step += 1;
+                }
+            } else if !m.content.is_empty() {
+                final_content = Some(m.content.clone());
+            }
+        }
+
+        if let Some(content) = final_content {
+            let short: String = content.chars().take(240).collect();
+            out.push_str(&format!("\nFinal insight: {}...\n", short));
+        }
+
+        out
+    }
+
+    fn brief_json_args(v: &serde_json::Value) -> String {
+        let Some(obj) = v.as_object() else {
+            return v.to_string();
+        };
+        obj.iter()
+            .map(|(k, v)| {
+                let rendered = match v {
+                    serde_json::Value::String(s) if s.len() > 40 => {
+                        format!("\"{}...\"", &s[..40])
+                    }
+                    _ => v.to_string(),
+                };
+                format!("{}={}", k, rendered)
+            })
+            .collect::<Vec<_>>()
+            .join(", ")
+    }
+
+    /// Collapse a raw tool-result string (the text the model saw) into a
+    /// short phrase suitable for a few-shot trajectory. Detects the
+    /// "Found N ...", "No ...", and "Error ..." idioms used by the tool
+    /// implementations in this file. Unknown shapes fall back to a char
+    /// count, which is deliberately visible so drift shows up in output.
+    fn summarize_tool_result(tool_name: &str, raw: &str) -> String {
+        if raw.starts_with("Error ") {
+            return "error".to_string();
+        }
+        if raw.starts_with("No ") || raw.starts_with("Could not ") {
+            return "empty (pivoted)".to_string();
+        }
+
+        if let Some(rest) = raw.strip_prefix("Found ")
+            && let Some(n_str) = rest.split_whitespace().next()
+            && let Ok(n) = n_str.parse::<usize>()
+        {
+            let kind = match tool_name {
+                "search_messages" | "get_sms_messages" => "messages",
+                "get_calendar_events" => "events",
+                "get_location_history" => "location records",
+                _ => "results",
+            };
+            return format!("{} {}", n, kind);
+        }
+
+        match tool_name {
+            "search_rag" => {
+                let n = raw.split("\n\n").filter(|s| !s.trim().is_empty()).count();
+                format!("{} rag hits", n)
+            }
+            "get_file_tags" => {
+                let n = raw.split(',').filter(|s| !s.trim().is_empty()).count();
+                format!("{} tags", n)
+            }
+            "describe_photo" => {
+                let short: String = raw.chars().take(80).collect();
+                format!("described: \"{}...\"", short)
+            }
+            "reverse_geocode" => {
+                let short: String = raw.chars().take(60).collect();
+                format!("place: {}", short)
+            }
+            "recall_entities" | "recall_facts_for_photo" => {
+                let n = raw.lines().skip(1).filter(|l| !l.trim().is_empty()).count();
+                let kind = if tool_name == "recall_entities" {
+                    "entities"
+                } else {
+                    "facts"
+                };
+                format!("{} {}", n, kind)
+            }
+            "store_entity" | "store_fact" => raw
+                .split_whitespace()
+                .find_map(|tok| tok.strip_prefix("ID:"))
+                .map(|id| format!("stored id={}", id.trim_end_matches(',')))
+                .unwrap_or_else(|| "stored".to_string()),
+            "get_current_datetime" => "time noted".to_string(),
+            _ => format!("{} chars", raw.len()),
+        }
+    }
+
     pub async fn generate_agentic_insight_for_photo(
         &self,
         file_path: &str,
@@ -2646,6 +2800,8 @@ Return ONLY the summary, nothing else."#,
         min_p: Option<f32>,
         max_iterations: usize,
         backend: Option<String>,
+        fewshot_examples: Vec<Vec<ChatMessage>>,
+        fewshot_source_ids: Vec<i32>,
     ) -> Result<(Option<i32>, Option<i32>)> {
         let tracer = global_tracer();
         let current_cx = opentelemetry::Context::current();
@@ -2990,8 +3146,10 @@ Return ONLY the summary, nothing else."#,
             ),
             None => String::new(),
         };
+        let fewshot_block = Self::render_fewshot_examples(&fewshot_examples);
         let base_system = format!(
             "You are a personal photo memory assistant helping to reconstruct a memory from a photo.{owner_id_note}\n\n\
+            {fewshot_block}\
             IMPORTANT INSTRUCTIONS:\n\
             1. You MUST call multiple tools to gather context BEFORE writing any final insight. Do not produce a final answer after only one or two tool calls.\n\
             2. When calling get_sms_messages and search_rag, always make at least one call WITHOUT a contact filter to capture what else was happening in {owner_name}'s life around this date — other conversations, events, and activities provide important wider context even when a specific contact is known.\n\
@@ -3002,6 +3160,7 @@ Return ONLY the summary, nothing else."#,
             7. If a tool returns no results, that is useful information — continue calling the remaining tools anyway.\n\
             8. You have a hard budget of {max_iterations} tool-calling iterations before the loop ends. Plan your context gathering so you can write a complete final insight within that budget.",
             owner_id_note = owner_id_note,
+            fewshot_block = fewshot_block,
             owner_name = owner_name,
             max_iterations = max_iterations
         );
@@ -3153,12 +3312,10 @@ Return ONLY the summary, nothing else."#,
                 "Agentic loop exhausted after {} iterations, requesting final answer",
                 iterations_used
             );
-            messages.push(ChatMessage::user(
-                &format!(
-                    "Based on the context gathered, please write the final photo insight: a title and a detailed personal summary. Write in first person as {}.",
-                    user_display_name()
-                ),
-            ));
+            messages.push(ChatMessage::user(format!(
+                "Based on the context gathered, please write the final photo insight: a title and a detailed personal summary. Write in first person as {}.",
+                user_display_name()
+            )));
             let (final_response, prompt_tokens, eval_tokens) = chat_backend
                 .chat_with_tools(messages.clone(), vec![])
                 .await?;
@@ -3204,6 +3361,11 @@ Return ONLY the summary, nothing else."#,
 
         // 15. Store insight (returns the persisted row including its new id)
         let model_version = chat_backend.primary_model().to_string();
+        let fewshot_source_ids_json = if fewshot_source_ids.is_empty() {
+            None
+        } else {
+            Some(serde_json::to_string(&fewshot_source_ids).unwrap_or_else(|_| "[]".to_string()))
+        };
         let insight = InsertPhotoInsight {
             library_id: crate::libraries::PRIMARY_LIBRARY_ID,
             file_path: file_path.to_string(),
@@ -3214,6 +3376,7 @@ Return ONLY the summary, nothing else."#,
             is_current: true,
             training_messages,
             backend: backend_label.clone(),
+            fewshot_source_ids: fewshot_source_ids_json,
         };
 
         let stored = {
@@ -3333,6 +3496,7 @@ Return ONLY the summary, nothing else."#,
 #[cfg(test)]
 mod tests {
     use super::*;
+    use crate::ai::ollama::{ToolCall, ToolCallFunction};
 
     #[test]
     fn combine_contexts_includes_tags_section_when_tags_present() {
@@ -3374,4 +3538,219 @@ mod tests {
         let result = InsightGenerator::combine_contexts(None, None, None, None, None);
         assert_eq!(result, "No additional context available");
     }
+
+    // These tests assert the shape of the strings returned by the tool
+    // implementations above. If a tool's output format changes, update the
+    // tool AND the corresponding arm of `summarize_tool_result` — these
+    // tests exist to make that coupling loud.
+
+    #[test]
+    fn summarize_errors_uniformly() {
+        assert_eq!(
+            InsightGenerator::summarize_tool_result("search_rag", "Error searching RAG: boom"),
+            "error"
+        );
+        assert_eq!(
+            InsightGenerator::summarize_tool_result(
+                "get_sms_messages",
+                "Error fetching SMS messages: timeout"
+            ),
+            "error"
+        );
+    }
+
+    #[test]
+    fn summarize_empty_results_uniformly() {
+        assert_eq!(
+            InsightGenerator::summarize_tool_result("search_rag", "No relevant messages found."),
+            "empty (pivoted)"
+        );
+        assert_eq!(
+            InsightGenerator::summarize_tool_result("get_sms_messages", "No messages found."),
+            "empty (pivoted)"
+        );
+        assert_eq!(
+            InsightGenerator::summarize_tool_result(
+                "reverse_geocode",
+                "Could not resolve coordinates to a place name."
+            ),
+            "empty (pivoted)"
+        );
+        assert_eq!(
+            InsightGenerator::summarize_tool_result(
+                "recall_facts_for_photo",
+                "No knowledge facts found for this photo."
+            ),
+            "empty (pivoted)"
+        );
+    }
+
+    #[test]
+    fn summarize_found_count_per_tool() {
+        assert_eq!(
+            InsightGenerator::summarize_tool_result(
+                "get_sms_messages",
+                "Found 7 messages:\n[2023-08-15 10:00] Sarah: hi"
+            ),
+            "7 messages"
+        );
+        assert_eq!(
+            InsightGenerator::summarize_tool_result(
+                "search_messages",
+                "Found 3 messages (mode: hybrid):\n\n[2023-08-15] Sarah — hi"
+            ),
+            "3 messages"
+        );
+        assert_eq!(
+            InsightGenerator::summarize_tool_result(
+                "get_calendar_events",
+                "Found 2 calendar events:\n[2023-08-15 10:00] Wedding"
+            ),
+            "2 events"
+        );
+        assert_eq!(
+            InsightGenerator::summarize_tool_result(
+                "get_location_history",
+                "Found 5 location records:\n[2023-08-15 10:00] 39.0, -120.0"
+            ),
+            "5 location records"
+        );
+    }
+
+    #[test]
+    fn summarize_search_rag_counts_hits() {
+        let raw = "[2023-08-15] Sarah: venue confirmed\n\n[2023-08-14] Mom: travel plans\n\n[2023-08-13] Dad: weather";
+        assert_eq!(
+            InsightGenerator::summarize_tool_result("search_rag", raw),
+            "3 rag hits"
+        );
+    }
+
+    #[test]
+    fn summarize_get_file_tags() {
+        assert_eq!(
+            InsightGenerator::summarize_tool_result("get_file_tags", "wedding, tahoe, 2023"),
+            "3 tags"
+        );
+    }
+
+    #[test]
+    fn summarize_describe_photo_truncates() {
+        let raw = "A wedding ceremony at Lake Tahoe with about 40 guests seated in rows facing a lakeside arch decorated with white flowers.";
+        let out = InsightGenerator::summarize_tool_result("describe_photo", raw);
+        assert!(out.starts_with("described: \""));
+        assert!(out.contains("A wedding ceremony at Lake Tahoe"));
+        assert!(out.ends_with("...\""));
+    }
+
+    #[test]
+    fn summarize_reverse_geocode_returns_place() {
+        let out =
+            InsightGenerator::summarize_tool_result("reverse_geocode", "South Lake Tahoe, CA, USA");
+        assert_eq!(out, "place: South Lake Tahoe, CA, USA");
+    }
+
+    #[test]
+    fn summarize_recall_entities_counts_lines() {
+        let raw = "Known entities:\n- Sarah (person)\n- Tahoe (place)\n- Wedding 2023 (event)";
+        assert_eq!(
+            InsightGenerator::summarize_tool_result("recall_entities", raw),
+            "3 entities"
+        );
+    }
+
+    #[test]
+    fn summarize_recall_facts_counts_lines() {
+        let raw = "Knowledge for this photo:\n- Sarah: college friend\n- Tahoe: vacation spot";
+        assert_eq!(
+            InsightGenerator::summarize_tool_result("recall_facts_for_photo", raw),
+            "2 facts"
+        );
+    }
+
+    #[test]
+    fn summarize_store_entity_extracts_id() {
+        assert_eq!(
+            InsightGenerator::summarize_tool_result(
+                "store_entity",
+                "Entity stored: ID:42 | person | Sarah | confidence:0.80"
+            ),
+            "stored id=42"
+        );
+    }
+
+    #[test]
+    fn summarize_store_fact_extracts_id() {
+        assert_eq!(
+            InsightGenerator::summarize_tool_result(
+                "store_fact",
+                "Stored new fact: ID:17 | confidence:0.60"
+            ),
+            "stored id=17"
+        );
+        assert_eq!(
+            InsightGenerator::summarize_tool_result(
+                "store_fact",
+                "Corroborated existing fact: ID:17 | confidence:0.85"
+            ),
+            "stored id=17"
+        );
+    }
+
+    #[test]
+    fn summarize_current_datetime() {
+        assert_eq!(
+            InsightGenerator::summarize_tool_result(
+                "get_current_datetime",
+                "Current date/time: 2024-01-15 12:00:00 PST (Monday)"
+            ),
+            "time noted"
+        );
+    }
+
+    #[test]
+    fn summarize_unknown_tool_falls_back_to_char_count() {
+        let out = InsightGenerator::summarize_tool_result("never_heard_of_it", "some output");
+        assert_eq!(out, "11 chars");
+    }
+
+    #[test]
+    fn render_fewshot_empty_returns_empty_string() {
+        assert!(InsightGenerator::render_fewshot_examples(&[]).is_empty());
+    }
+
+    #[test]
+    fn render_single_trajectory_walks_tool_calls_in_order() {
+        let arguments = serde_json::json!({ "query": "wedding", "date": "2023-08-15" });
+        let msgs = vec![
+            ChatMessage::system("ignored"),
+            ChatMessage::user("Photo file path: /photos/img.jpg\nDate taken: August 15, 2023"),
+            ChatMessage {
+                role: "assistant".to_string(),
+                content: String::new(),
+                tool_calls: Some(vec![ToolCall {
+                    function: ToolCallFunction {
+                        name: "search_rag".to_string(),
+                        arguments,
+                    },
+                    id: None,
+                }]),
+                images: None,
+            },
+            ChatMessage::tool_result("No relevant messages found."),
+            ChatMessage {
+                role: "assistant".to_string(),
+                content: "Final title\n\nFinal body.".to_string(),
+                tool_calls: None,
+                images: None,
+            },
+        ];
+        let out = InsightGenerator::render_single_trajectory(&msgs);
+        assert!(out.contains("Input:"));
+        assert!(out.contains("/photos/img.jpg"));
+        assert!(out.contains("1. search_rag("));
+        assert!(out.contains("query=\"wedding\""));
+        assert!(out.contains("-> empty (pivoted)"));
+        assert!(out.contains("Final insight: Final title"));
+    }
 }

src/ai/ollama.rs

@@ -4,6 +4,7 @@ use chrono::NaiveDate;
 use reqwest::Client;
 use serde::{Deserialize, Serialize};
 use std::collections::HashMap;
+use std::sync::atomic::{AtomicBool, Ordering};
 use std::sync::{Arc, Mutex};
 use std::time::{Duration, Instant};
 
@@ -19,6 +20,19 @@ pub use crate::ai::llm_client::{ToolCall, ToolCallFunction, ToolFunction};
 // Cache duration: 15 minutes
 const CACHE_DURATION_SECS: u64 = 15 * 60;
 
+/// Default total request timeout for generation calls, in seconds.
+/// Overridable via `OLLAMA_REQUEST_TIMEOUT_SECONDS` env var for slow
+/// CPU-offloaded models where inference can take several minutes.
+const DEFAULT_REQUEST_TIMEOUT_SECS: u64 = 120;
+
+fn configured_request_timeout_secs() -> u64 {
+    std::env::var("OLLAMA_REQUEST_TIMEOUT_SECONDS")
+        .ok()
+        .and_then(|v| v.parse::<u64>().ok())
+        .filter(|&s| s > 0)
+        .unwrap_or(DEFAULT_REQUEST_TIMEOUT_SECS)
+}
+
 /// Embedding model used across the app. Callers that persist a
 /// `model_version` alongside an embedding should read this constant so the
 /// stored label always matches what `generate_embeddings` actually ran.
@@ -65,6 +79,12 @@ pub struct OllamaClient {
     top_p: Option<f32>,
     top_k: Option<i32>,
     min_p: Option<f32>,
+    /// Sticky preference shared across clones: when the fallback server
+    /// succeeded most recently, try it first on the next call. Avoids
+    /// re-probing the primary with a model it doesn't have loaded across
+    /// every iteration of the agent loop. `Arc<AtomicBool>` so cloning
+    /// `OllamaClient` shares the flag rather than resetting it.
+    prefer_fallback: Arc<AtomicBool>,
 }
 
 impl OllamaClient {
@@ -77,7 +97,7 @@ impl OllamaClient {
         Self {
             client: Client::builder()
                 .connect_timeout(Duration::from_secs(5)) // Quick connection timeout
-                .timeout(Duration::from_secs(120)) // Total request timeout for generation
+                .timeout(Duration::from_secs(configured_request_timeout_secs()))
                 .build()
                 .unwrap_or_else(|_| Client::new()),
             primary_url,
@@ -89,9 +109,44 @@ impl OllamaClient {
             top_p: None,
             top_k: None,
             min_p: None,
+            prefer_fallback: Arc::new(AtomicBool::new(false)),
         }
     }
 
+    /// Return the server attempt order as `(label, url, model)` tuples.
+    /// Respects the sticky `prefer_fallback` flag so the most recently
+    /// successful server is tried first.
+    fn attempt_order(&self) -> Vec<(&'static str, String, String)> {
+        let primary = (
+            "primary",
+            self.primary_url.clone(),
+            self.primary_model.clone(),
+        );
+        let fallback = self.fallback_url.as_ref().map(|url| {
+            let model = self
+                .fallback_model
+                .clone()
+                .unwrap_or_else(|| self.primary_model.clone());
+            ("fallback", url.clone(), model)
+        });
+
+        let prefer_fallback = fallback.is_some() && self.prefer_fallback.load(Ordering::Relaxed);
+
+        let mut order = Vec::with_capacity(2);
+        if prefer_fallback {
+            if let Some(fb) = fallback.clone() {
+                order.push(fb);
+            }
+            order.push(primary);
+        } else {
+            order.push(primary);
+            if let Some(fb) = fallback {
+                order.push(fb);
+            }
+        }
+        order
+    }
+
     pub fn set_num_ctx(&mut self, num_ctx: Option<i32>) {
         self.num_ctx = num_ctx;
     }
@@ -587,68 +642,57 @@ Analyze the image and use specific details from both the visual content and the
 
     /// Send a chat request with tool definitions to /api/chat.
     /// Returns the assistant's response message (may contain tool_calls or final content).
-    /// Uses primary/fallback URL routing same as other generation methods.
+    /// Tries servers in preference order — most recently successful first —
+    /// so a fallback-only model doesn't re-404 against the primary on every
+    /// iteration of the agent loop.
     pub async fn chat_with_tools(
         &self,
         messages: Vec<ChatMessage>,
         tools: Vec<Tool>,
     ) -> Result<(ChatMessage, Option<i32>, Option<i32>)> {
-        // Try primary server first
-        log::info!(
-            "Attempting chat_with_tools with primary server: {} (model: {})",
-            self.primary_url,
-            self.primary_model
-        );
-        let primary_result = self
-            .try_chat_with_tools(&self.primary_url, messages.clone(), tools.clone())
-            .await;
-
-        match primary_result {
-            Ok(result) => {
-                log::info!("Successfully got chat_with_tools response from primary server");
-                Ok(result)
-            }
-            Err(e) => {
-                log::warn!("Primary server chat_with_tools failed: {}", e);
-
-                // Try fallback server if available
-                if let Some(fallback_url) = &self.fallback_url {
-                    let fallback_model =
-                        self.fallback_model.as_ref().unwrap_or(&self.primary_model);
+        let order = self.attempt_order();
+        let mut errors: Vec<String> = Vec::new();
 
+        for (label, url, model) in &order {
+            log::info!(
+                "Attempting chat_with_tools with {} server: {} (model: {})",
+                label,
+                url,
+                model
+            );
+            match self
+                .try_chat_with_tools(url, messages.clone(), tools.clone())
+                .await
+            {
+                Ok(result) => {
                     log::info!(
-                        "Attempting chat_with_tools with fallback server: {} (model: {})",
-                        fallback_url,
-                        fallback_model
+                        "Successfully got chat_with_tools response from {} server",
+                        label
                     );
-                    match self
-                        .try_chat_with_tools(fallback_url, messages, tools)
-                        .await
-                    {
-                        Ok(result) => {
-                            log::info!(
-                                "Successfully got chat_with_tools response from fallback server"
-                            );
-                            Ok(result)
-                        }
-                        Err(fallback_e) => {
-                            log::error!(
-                                "Fallback server chat_with_tools also failed: {}",
-                                fallback_e
-                            );
-                            Err(anyhow::anyhow!(
-                                "Both primary and fallback servers failed. Primary: {}, Fallback: {}",
-                                e,
-                                fallback_e
-                            ))
-                        }
-                    }
-                } else {
-                    log::error!("No fallback server configured");
-                    Err(e)
+                    self.prefer_fallback
+                        .store(*label == "fallback", Ordering::Relaxed);
+                    return Ok(result);
+                }
+                Err(e) => {
+                    log::warn!("{} server chat_with_tools failed: {}", label, e);
+                    errors.push(format!("{}: {}", label, e));
                 }
             }
         }
+
+        if order.len() <= 1 {
+            log::error!("No fallback server configured; chat_with_tools exhausted");
+        } else {
+            log::error!(
+                "All {} servers failed for chat_with_tools ({})",
+                order.len(),
+                errors.join(" / ")
+            );
+        }
+        Err(anyhow::anyhow!(
+            "chat_with_tools failed on all servers: {}",
+            errors.join(" / ")
+        ))
     }
 
     /// Streaming variant of `chat_with_tools`. Tries primary, then falls
@@ -662,26 +706,30 @@ Analyze the image and use specific details from both the visual content and the
         messages: Vec<ChatMessage>,
         tools: Vec<Tool>,
     ) -> Result<BoxStream<'static, Result<LlmStreamEvent>>> {
-        // Attempt primary. If it can't be opened at all, try fallback.
-        match self
-            .try_chat_with_tools_stream(&self.primary_url, messages.clone(), tools.clone())
-            .await
-        {
-            Ok(s) => Ok(s),
-            Err(e) => {
-                if let Some(fallback_url) = self.fallback_url.clone() {
-                    log::warn!(
-                        "Streaming chat primary failed ({}); trying fallback {}",
-                        e,
-                        fallback_url
-                    );
-                    self.try_chat_with_tools_stream(&fallback_url, messages, tools)
-                        .await
-                } else {
-                    Err(e)
+        // Same preference logic as `chat_with_tools`. Only the initial
+        // connection is retried across servers — once the stream begins,
+        // mid-stream errors propagate to the caller.
+        let order = self.attempt_order();
+        let mut last_err: Option<anyhow::Error> = None;
+
+        for (label, url, _model) in &order {
+            match self
+                .try_chat_with_tools_stream(url, messages.clone(), tools.clone())
+                .await
+            {
+                Ok(s) => {
+                    self.prefer_fallback
+                        .store(*label == "fallback", Ordering::Relaxed);
+                    return Ok(s);
+                }
+                Err(e) => {
+                    log::warn!("Streaming chat on {} server failed: {}", label, e);
+                    last_err = Some(e);
                 }
             }
         }
+
+        Err(last_err.unwrap_or_else(|| anyhow::anyhow!("No Ollama server configured")))
     }
 
     async fn try_chat_with_tools_stream(
@@ -859,8 +907,12 @@ Analyze the image and use specific details from both the visual content and the
         if !response.status().is_success() {
             let status = response.status();
             let body = response.text().await.unwrap_or_default();
-            log::error!(
-                "chat_with_tools request body that caused {}: {}",
+            // warn, not error — the outer `chat_with_tools` may recover via
+            // the fallback server. When both fail, the outer layer emits the
+            // actual error log.
+            log::warn!(
+                "chat_with_tools request to {} got {}: {}",
+                base_url,
                 status,
                 request_json
             );

src/ai/openrouter.rs

@@ -452,8 +452,7 @@ impl LlmClient for OpenRouterClient {
                 // SSE frames are delimited by a blank line. Walk the buffer
                 // for "\n\n" markers; anything before them is a complete
                 // frame (possibly multi-line).
-                loop {
-                    let Some(sep) = find_double_newline(&buf) else { break };
+                while let Some(sep) = find_double_newline(&buf) {
                     let frame = buf.drain(..sep + 2).collect::<Vec<_>>();
                     let frame_str = match std::str::from_utf8(&frame) {
                         Ok(s) => s,

src/bin/populate_knowledge.rs

@@ -251,6 +251,8 @@ async fn main() -> anyhow::Result<()> {
                 args.min_p,
                 args.max_iterations,
                 None,
+                Vec::new(),
+                Vec::new(),
             )
             .await
         {

src/database/daily_summary_dao.rs

@@ -268,7 +268,7 @@ impl DailySummaryDao for SqliteDailySummaryDao {
                 .into_iter()
                 .take(limit)
                 .map(|(similarity, summary)| {
-                    log::info!(
+                    log::debug!(
                         "Summary match: similarity={:.3}, date={}, contact={}, summary=\"{}\"",
                         similarity,
                         summary.date,
@@ -388,7 +388,7 @@ impl DailySummaryDao for SqliteDailySummaryDao {
                 .into_iter()
                 .take(limit)
                 .map(|(combined, similarity, days, summary)| {
-                    log::info!(
+                    log::debug!(
                         "Summary match: combined={:.3} (sim={:.3}, days={}), date={}, contact={}, summary=\"{}\"",
                         combined,
                         similarity,

src/database/insights_dao.rs

@@ -38,6 +38,16 @@ pub trait InsightDao: Sync + Send {
         file_path: &str,
     ) -> Result<Vec<PhotoInsight>, DbError>;
 
+    /// Fetch a single insight by primary key, regardless of `is_current`.
+    /// Used by the few-shot injection flow where the caller picks specific
+    /// historical insights (which may have been superseded) as training
+    /// exemplars for a fresh generation.
+    fn get_insight_by_id(
+        &mut self,
+        context: &opentelemetry::Context,
+        insight_id: i32,
+    ) -> Result<Option<PhotoInsight>, DbError>;
+
     fn delete_insight(
         &mut self,
         context: &opentelemetry::Context,
@@ -198,6 +208,25 @@ impl InsightDao for SqliteInsightDao {
         .map_err(|_| DbError::new(DbErrorKind::QueryError))
     }
 
+    fn get_insight_by_id(
+        &mut self,
+        context: &opentelemetry::Context,
+        insight_id: i32,
+    ) -> Result<Option<PhotoInsight>, DbError> {
+        trace_db_call(context, "query", "get_insight_by_id", |_span| {
+            use schema::photo_insights::dsl::*;
+
+            let mut connection = self.connection.lock().expect("Unable to get InsightDao");
+
+            photo_insights
+                .find(insight_id)
+                .first::<PhotoInsight>(connection.deref_mut())
+                .optional()
+                .map_err(|_| anyhow::anyhow!("Query error"))
+        })
+        .map_err(|_| DbError::new(DbErrorKind::QueryError))
+    }
+
     fn delete_insight(
         &mut self,
         context: &opentelemetry::Context,

src/database/models.rs

@@ -102,6 +102,12 @@ pub struct InsertPhotoInsight {
     pub training_messages: Option<String>,
     /// `"local"` (Ollama with images) | `"hybrid"` (local vision + OpenRouter chat).
     pub backend: String,
+    /// JSON array of insight ids whose `training_messages` were compressed
+    /// and injected into the system prompt as few-shot exemplars when this
+    /// row was generated. `None` means no few-shot was used (pristine
+    /// generation). Used downstream to filter out contaminated rows when
+    /// assembling an unbiased training / evaluation set.
+    pub fewshot_source_ids: Option<String>,
 }
 
 #[derive(Serialize, Queryable, Clone, Debug)]
@@ -119,6 +125,7 @@ pub struct PhotoInsight {
     pub approved: Option<bool>,
     /// `"local"` (Ollama with images) | `"hybrid"` (local vision + OpenRouter chat).
     pub backend: String,
+    pub fewshot_source_ids: Option<String>,
 }
 
 // --- Libraries ---

src/database/schema.rs

@@ -143,6 +143,7 @@ diesel::table! {
         training_messages -> Nullable<Text>,
         approved -> Nullable<Bool>,
         backend -> Text,
+        fewshot_source_ids -> Nullable<Text>,
     }
 }