Add the ability to rate insights to curate training data

src/ai/handlers.rs

@@ -25,6 +25,18 @@ pub struct GetPhotoInsightQuery {
     pub path: String,
 }
 
+#[derive(Debug, Deserialize)]
+pub struct RateInsightRequest {
+    pub file_path: String,
+    pub approved: bool,
+}
+
+#[derive(Debug, Deserialize)]
+pub struct ExportTrainingDataQuery {
+    #[serde(default)]
+    pub approved_only: Option<bool>,
+}
+
 #[derive(Debug, Serialize)]
 pub struct PhotoInsightResponse {
     pub id: i32,
@@ -37,6 +49,8 @@ pub struct PhotoInsightResponse {
     pub prompt_eval_count: Option<i32>,
     #[serde(skip_serializing_if = "Option::is_none")]
     pub eval_count: Option<i32>,
+    #[serde(skip_serializing_if = "Option::is_none")]
+    pub approved: Option<bool>,
 }
 
 #[derive(Debug, Serialize)]
@@ -139,6 +153,7 @@ pub async fn get_insight_handler(
                 model_version: insight.model_version,
                 prompt_eval_count: None,
                 eval_count: None,
+                approved: insight.approved,
             };
             HttpResponse::Ok().json(response)
         }
@@ -205,6 +220,7 @@ pub async fn get_all_insights_handler(
                     model_version: insight.model_version,
                     prompt_eval_count: None,
                     eval_count: None,
+                    approved: insight.approved,
                 })
                 .collect();
 
@@ -287,6 +303,7 @@ pub async fn generate_agentic_insight_handler(
                         model_version: insight.model_version,
                         prompt_eval_count,
                         eval_count,
+                        approved: insight.approved,
                     };
                     HttpResponse::Ok().json(response)
                 }
@@ -377,3 +394,86 @@ pub async fn get_available_models_handler(
 
     HttpResponse::Ok().json(response)
 }
+
+/// POST /insights/rate - Rate an insight (thumbs up/down for training data)
+#[post("/insights/rate")]
+pub async fn rate_insight_handler(
+    _claims: Claims,
+    request: web::Json<RateInsightRequest>,
+    insight_dao: web::Data<std::sync::Mutex<Box<dyn InsightDao>>>,
+) -> impl Responder {
+    let normalized_path = normalize_path(&request.file_path);
+    log::info!(
+        "Rating insight for {}: approved={}",
+        normalized_path,
+        request.approved
+    );
+
+    let otel_context = opentelemetry::Context::new();
+    let mut dao = insight_dao.lock().expect("Unable to lock InsightDao");
+
+    match dao.rate_insight(&otel_context, &normalized_path, request.approved) {
+        Ok(()) => HttpResponse::Ok().json(serde_json::json!({
+            "success": true,
+            "message": "Insight rated successfully"
+        })),
+        Err(e) => {
+            log::error!("Failed to rate insight: {:?}", e);
+            HttpResponse::InternalServerError().json(serde_json::json!({
+                "error": format!("Failed to rate insight: {:?}", e)
+            }))
+        }
+    }
+}
+
+/// GET /insights/training-data - Export approved training data as JSONL
+#[get("/insights/training-data")]
+pub async fn export_training_data_handler(
+    _claims: Claims,
+    query: web::Query<ExportTrainingDataQuery>,
+    insight_dao: web::Data<std::sync::Mutex<Box<dyn InsightDao>>>,
+) -> impl Responder {
+    let approved_only = query.approved_only.unwrap_or(true);
+    log::info!("Exporting training data (approved_only={})", approved_only);
+
+    let otel_context = opentelemetry::Context::new();
+    let mut dao = insight_dao.lock().expect("Unable to lock InsightDao");
+
+    let insights = if approved_only {
+        dao.get_approved_insights(&otel_context)
+    } else {
+        dao.get_all_insights(&otel_context)
+    };
+
+    match insights {
+        Ok(insights) => {
+            let mut jsonl = String::new();
+            for insight in &insights {
+                if let Some(ref messages) = insight.training_messages {
+                    let entry = serde_json::json!({
+                        "file_path": insight.file_path,
+                        "model_version": insight.model_version,
+                        "generated_at": insight.generated_at,
+                        "title": insight.title,
+                        "summary": insight.summary,
+                        "messages": serde_json::from_str::<serde_json::Value>(messages)
+                            .unwrap_or(serde_json::Value::Null),
+                    });
+                    jsonl.push_str(&entry.to_string());
+                    jsonl.push('\n');
+                }
+            }
+
+            HttpResponse::Ok()
+                .content_type("application/jsonl")
+                .insert_header(("Content-Disposition", "attachment; filename=\"training_data.jsonl\""))
+                .body(jsonl)
+        }
+        Err(e) => {
+            log::error!("Failed to export training data: {:?}", e);
+            HttpResponse::InternalServerError().json(serde_json::json!({
+                "error": format!("Failed to export training data: {:?}", e)
+            }))
+        }
+    }
+}

src/ai/insight_generator.rs

@@ -1,6 +1,6 @@
 use anyhow::Result;
 use base64::Engine as _;
-use chrono::{DateTime, NaiveDate, Utc};
+use chrono::{DateTime, Local, NaiveDate, Utc};
 use image::ImageFormat;
 use opentelemetry::KeyValue;
 use opentelemetry::trace::{Span, Status, TraceContextExt, Tracer};
@@ -1165,6 +1165,7 @@ impl InsightGenerator {
             generated_at: Utc::now().timestamp(),
             model_version: ollama_client.primary_model.clone(),
             is_current: true,
+            training_messages: None,
         };
 
         let mut dao = self.insight_dao.lock().expect("Unable to lock InsightDao");
@@ -1367,6 +1368,7 @@ Return ONLY the summary, nothing else."#,
             "recall_facts_for_photo" => self.tool_recall_facts_for_photo(arguments, cx).await,
             "store_entity" => self.tool_store_entity(arguments, ollama, cx).await,
             "store_fact" => self.tool_store_fact(arguments, file_path, cx).await,
+            "get_current_datetime" => Self::tool_get_current_datetime(),
             unknown => format!("Unknown tool: {}", unknown),
         };
         if result.starts_with("Error") || result.starts_with("No ") {
@@ -2023,6 +2025,16 @@ Return ONLY the summary, nothing else."#,
         )
     }
 
+    /// Tool: get_current_datetime — returns the current local date and time
+    fn tool_get_current_datetime() -> String {
+        let now = Local::now();
+        format!(
+            "Current date/time: {} ({})",
+            now.format("%Y-%m-%d %H:%M:%S %Z"),
+            now.format("%A")
+        )
+    }
+
     // ── Agentic insight generation ──────────────────────────────────────
 
     /// Build the list of tool definitions for the agentic loop
@@ -2237,6 +2249,15 @@ Return ONLY the summary, nothing else."#,
             }),
         ));
 
+        tools.push(Tool::function(
+            "get_current_datetime",
+            "Get the current date and time. Useful for understanding how long ago the photo was taken.",
+            serde_json::json!({
+                "type": "object",
+                "properties": {}
+            }),
+        ));
+
         if has_vision {
             tools.push(Tool::function(
                 "describe_photo",
@@ -2630,10 +2651,13 @@ Return ONLY the summary, nothing else."#,
                 "Based on the context gathered, please write the final photo insight: a title and a detailed personal summary. Write in first person as Cameron.",
             ));
             let (final_response, prompt_tokens, eval_tokens) =
-                ollama_client.chat_with_tools(messages, vec![]).await?;
+                ollama_client
+                    .chat_with_tools(messages.clone(), vec![])
+                    .await?;
             last_prompt_eval_count = prompt_tokens;
             last_eval_count = eval_tokens;
-            final_content = final_response.content;
+            final_content = final_response.content.clone();
+            messages.push(final_response);
         }
 
         loop_cx
@@ -2653,7 +2677,16 @@ Return ONLY the summary, nothing else."#,
             &final_content[..final_content.len().min(200)]
         );
 
-        // 14. Store insight (returns the persisted row including its new id)
+        // 14. Serialize the full message history for training data
+        let training_messages = match serde_json::to_string(&messages) {
+            Ok(json) => Some(json),
+            Err(e) => {
+                log::warn!("Failed to serialize training messages: {}", e);
+                None
+            }
+        };
+
+        // 15. Store insight (returns the persisted row including its new id)
         let insight = InsertPhotoInsight {
             file_path: file_path.to_string(),
             title,
@@ -2661,6 +2694,7 @@ Return ONLY the summary, nothing else."#,
             generated_at: Utc::now().timestamp(),
             model_version: ollama_client.primary_model.clone(),
             is_current: true,
+            training_messages,
         };
 
         let stored = {
@@ -2682,7 +2716,7 @@ Return ONLY the summary, nothing else."#,
 
         let stored_insight = stored?;
 
-        // 15. Backfill source_insight_id on all facts recorded for this photo during the loop
+        // 16. Backfill source_insight_id on all facts recorded for this photo during the loop
         {
             let mut kdao = self
                 .knowledge_dao

src/ai/mod.rs

@@ -8,8 +8,9 @@ pub mod sms_client;
 #[allow(unused_imports)]
 pub use daily_summary_job::{generate_daily_summaries, strip_summary_boilerplate};
 pub use handlers::{
-    delete_insight_handler, generate_agentic_insight_handler, generate_insight_handler,
+    delete_insight_handler, export_training_data_handler, generate_agentic_insight_handler,
-    get_all_insights_handler, get_available_models_handler, get_insight_handler,
+    generate_insight_handler, get_all_insights_handler, get_available_models_handler,
+    get_insight_handler, rate_insight_handler,
 };
 pub use insight_generator::InsightGenerator;
 pub use ollama::{ModelCapabilities, OllamaClient};

src/database/insights_dao.rs

@@ -37,6 +37,18 @@ pub trait InsightDao: Sync + Send {
         &mut self,
         context: &opentelemetry::Context,
     ) -> Result<Vec<PhotoInsight>, DbError>;
+
+    fn rate_insight(
+        &mut self,
+        context: &opentelemetry::Context,
+        file_path: &str,
+        approved: bool,
+    ) -> Result<(), DbError>;
+
+    fn get_approved_insights(
+        &mut self,
+        context: &opentelemetry::Context,
+    ) -> Result<Vec<PhotoInsight>, DbError>;
 }
 
 pub struct SqliteInsightDao {
@@ -169,4 +181,47 @@ impl InsightDao for SqliteInsightDao {
         })
         .map_err(|_| DbError::new(DbErrorKind::QueryError))
     }
+
+    fn rate_insight(
+        &mut self,
+        context: &opentelemetry::Context,
+        path: &str,
+        is_approved: bool,
+    ) -> Result<(), DbError> {
+        trace_db_call(context, "update", "rate_insight", |_span| {
+            use schema::photo_insights::dsl::*;
+
+            let mut connection = self.connection.lock().expect("Unable to get InsightDao");
+
+            diesel::update(
+                photo_insights
+                    .filter(file_path.eq(path))
+                    .filter(is_current.eq(true)),
+            )
+            .set(approved.eq(Some(is_approved)))
+            .execute(connection.deref_mut())
+            .map(|_| ())
+            .map_err(|_| anyhow::anyhow!("Update error"))
+        })
+        .map_err(|_| DbError::new(DbErrorKind::UpdateError))
+    }
+
+    fn get_approved_insights(
+        &mut self,
+        context: &opentelemetry::Context,
+    ) -> Result<Vec<PhotoInsight>, DbError> {
+        trace_db_call(context, "query", "get_approved_insights", |_span| {
+            use schema::photo_insights::dsl::*;
+
+            let mut connection = self.connection.lock().expect("Unable to get InsightDao");
+
+            photo_insights
+                .filter(approved.eq(true))
+                .filter(training_messages.is_not_null())
+                .order(generated_at.desc())
+                .load::<PhotoInsight>(connection.deref_mut())
+                .map_err(|_| anyhow::anyhow!("Query error"))
+        })
+        .map_err(|_| DbError::new(DbErrorKind::QueryError))
+    }
 }

src/database/models.rs

@@ -86,6 +86,7 @@ pub struct InsertPhotoInsight {
     pub generated_at: i64,
     pub model_version: String,
     pub is_current: bool,
+    pub training_messages: Option<String>,
 }
 
 #[derive(Serialize, Queryable, Clone, Debug)]
@@ -97,6 +98,8 @@ pub struct PhotoInsight {
     pub generated_at: i64,
     pub model_version: String,
     pub is_current: bool,
+    pub training_messages: Option<String>,
+    pub approved: Option<bool>,
 }
 
 // --- Knowledge memory models ---

src/database/schema.rs

@@ -151,6 +151,8 @@ diesel::table! {
         generated_at -> BigInt,
         model_version -> Text,
         is_current -> Bool,
+        training_messages -> Nullable<Text>,
+        approved -> Nullable<Bool>,
     }
 }
 

src/main.rs

@@ -1185,6 +1185,8 @@ fn main() -> std::io::Result<()> {
                 .service(ai::delete_insight_handler)
                 .service(ai::get_all_insights_handler)
                 .service(ai::get_available_models_handler)
+                .service(ai::rate_insight_handler)
+                .service(ai::export_training_data_handler)
                 .add_feature(add_tag_services::<_, SqliteTagDao>)
                 .add_feature(knowledge::add_knowledge_services::<_, SqliteKnowledgeDao>)
                 .app_data(app_data.clone())