feat: add temperature, top_p, top_k, min_p params to insight generation

Expose Ollama sampling params through the insight generation endpoints
so users can tune creativity/determinism per request. All four are
optional — omitted values fall through to the model's server-side
defaults.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

src/ai/handlers.rs

@@ -18,6 +18,14 @@ pub struct GeneratePhotoInsightRequest {
     pub system_prompt: Option<String>,
     #[serde(default)]
     pub num_ctx: Option<i32>,
+    #[serde(default)]
+    pub temperature: Option<f32>,
+    #[serde(default)]
+    pub top_p: Option<f32>,
+    #[serde(default)]
+    pub top_k: Option<i32>,
+    #[serde(default)]
+    pub min_p: Option<f32>,
 }
 
 #[derive(Debug, Deserialize)]
@@ -108,6 +116,10 @@ pub async fn generate_insight_handler(
             request.model.clone(),
             request.system_prompt.clone(),
             request.num_ctx,
+            request.temperature,
+            request.top_p,
+            request.top_k,
+            request.min_p,
         )
         .await;
 
@@ -282,6 +294,10 @@ pub async fn generate_agentic_insight_handler(
             request.model.clone(),
             request.system_prompt.clone(),
             request.num_ctx,
+            request.temperature,
+            request.top_p,
+            request.top_k,
+            request.min_p,
             max_iterations,
         )
         .await;