update analytics for api usage

Author: 0xGingi

api-docs.md

@@ -1263,6 +1263,65 @@ curl -X GET "http://localhost:3432/api/db/model-performance?recalculate=true" \
 
 ---
 
+### Analytics
+
+#### GET `/api/analytics`
+Get model analytics for the user (stats + insights).
+
+**Authentication**: Session or API Key
+
+**Query Parameters**:
+- `recalculate`: Set to `"false"` to use cached stats. Defaults to `"true"`.
+
+**Response**:
+```json
+{
+  "success": true,
+  "stats": [
+    {
+      "id": "string",
+      "modelId": "string",
+      "provider": "string",
+      "totalMessages": "number",
+      "avgRating": "number | null",
+      "thumbsUpCount": "number",
+      "thumbsDownCount": "number",
+      "regenerateCount": "number",
+      "avgResponseTime": "number | null",
+      "avgTokens": "number | null",
+      "totalCost": "number",
+      "errorCount": "number",
+      "accurateCount": "number",
+      "helpfulCount": "number",
+      "creativeCount": "number",
+      "fastCount": "number",
+      "costEffectiveCount": "number"
+    }
+  ],
+  "insights": {
+    "totalMessages": "number",
+    "totalCost": "number",
+    "avgRating": "number | null",
+    "mostUsedModel": "ModelPerformanceStat | null",
+    "bestRatedModel": "ModelPerformanceStat | null",
+    "mostCostEffective": "ModelPerformanceStat | null",
+    "fastestModel": "ModelPerformanceStat | null"
+  }
+}
+```
+
+**CURL Example**:
+```bash
+curl -X GET "http://localhost:3432/api/analytics" \
+  -b "session_cookie=your_session"
+
+# Use cached stats
+curl -X GET "http://localhost:3432/api/analytics?recalculate=false" \
+  -b "session_cookie=your_session"
+```
+
+---
+
 ### User Settings
 
 #### GET `/api/db/user-settings`

src/routes/account/analytics/+page.server.ts

@@ -1,10 +1,7 @@
 import { redirect } from '@sveltejs/kit';
 import type { PageServerLoad } from './$types';
 import { auth } from '$lib/auth';
-import {
-	getModelPerformanceStatsByUser,
-	calculateAllModelPerformanceStats,
-} from '$lib/db/queries/model-performance';
+import { getModelAnalytics } from '$lib/analytics/model-analytics';
 
 export const load: PageServerLoad = async ({ request }) => {
 	const session = await auth.api.getSession({ headers: request.headers });
@@ -18,91 +15,13 @@ export const load: PageServerLoad = async ({ request }) => {
 	try {
 		console.log(`[analytics] Loading analytics for user ${userId}`);
 
-		// Always recalculate stats to ensure they're up-to-date
-		const stats = await calculateAllModelPerformanceStats(userId);
+		const { stats, insights } = await getModelAnalytics(userId, { recalculate: true });
 		console.log(`[analytics] Calculated stats for ${stats.length} models`);
-
-		// Calculate additional insights
-		const totalMessages = stats.reduce((sum, s) => sum + s.totalMessages, 0);
-		const totalCost = stats.reduce((sum, s) => {
-			const cost = s.totalCost;
-			if (cost === null || cost === undefined || isNaN(cost)) {
-				return sum;
-			}
-			return sum + cost;
-		}, 0);
-		const avgRating =
-			stats.filter((s) => s.avgRating !== null).length > 0
-				? stats.reduce((sum, s) => sum + (s.avgRating ?? 0), 0) /
-					stats.filter((s) => s.avgRating !== null).length
-				: null;
-
-		// Find most used model
-		const mostUsedModel =
-			stats.length > 0
-				? stats.reduce(
-						(prev, current) => (current.totalMessages > prev.totalMessages ? current : prev),
-						stats[0]!
-					)
-				: null;
-
-		// Find best rated model (with at least 5 messages)
-		const qualifiedModels = stats.filter((s) => s.totalMessages >= 5 && s.avgRating !== null);
-		const bestRatedModel =
-			qualifiedModels.length > 0
-				? qualifiedModels.reduce((prev, current) =>
-						(current.avgRating ?? 0) > (prev.avgRating ?? 0) ? current : prev
-					)
-				: null;
-
-		// Find most cost-effective model (lowest cost per message with at least 5 messages)
-		const modelsWithCost = stats.filter((s) => s.totalMessages >= 5 && s.totalCost > 0);
-		const mostCostEffective =
-			modelsWithCost.length > 0
-				? modelsWithCost.reduce((prev, current) => {
-						const prevCostPerMsg = prev.totalCost / prev.totalMessages;
-						const currentCostPerMsg = current.totalCost / current.totalMessages;
-						return currentCostPerMsg < prevCostPerMsg ? current : prev;
-					})
-				: null;
-
-		// Find fastest model by tokens/sec (requires avgTokens and avgResponseTime with at least 5 messages)
-		const modelsWithSpeed = stats.filter(
-			(s) =>
-				s.totalMessages >= 5 &&
-				s.avgTokens !== null &&
-				s.avgTokens !== undefined &&
-				s.avgResponseTime !== null &&
-				s.avgResponseTime !== undefined &&
-				s.avgResponseTime > 0
-		);
-
-		const fastestModel =
-			modelsWithSpeed.length > 0
-				? modelsWithSpeed.reduce((prev, current) => {
-						const prevSpeed = (prev.avgTokens ?? 0) / ((prev.avgResponseTime ?? 0) / 1000 || 1); // tokens per second
-						const currentSpeed =
-							(current.avgTokens ?? 0) / ((current.avgResponseTime ?? 0) / 1000 || 1);
-						return currentSpeed > prevSpeed ? current : prev;
-					})
-				: null;
-
 		console.log(
-			`[analytics] Generated insights: ${totalMessages} messages, $${totalCost.toFixed(2)} cost`
+			`[analytics] Generated insights: ${insights.totalMessages} messages, $${insights.totalCost.toFixed(2)} cost`
 		);
 
-		return {
-			stats,
-			insights: {
-				totalMessages,
-				totalCost,
-				avgRating,
-				mostUsedModel,
-				bestRatedModel,
-				mostCostEffective,
-				fastestModel,
-			},
-		};
+		return { stats, insights };
 	} catch (err) {
 		console.error(`[analytics] Error loading analytics for user ${userId}:`, err);
 		// Return empty data on error rather than crashing
@@ -115,6 +34,7 @@ export const load: PageServerLoad = async ({ request }) => {
 				mostUsedModel: null,
 				bestRatedModel: null,
 				mostCostEffective: null,
+				fastestModel: null,
 			},
 		};
 	}