From 3f35db3000e6abe47759b545c5415f6f63ad2517 Mon Sep 17 00:00:00 2001
From: Nati-Man <nasnake7@gmail.com>
Date: Wed, 1 Oct 2025 09:58:23 +0300
Subject: [PATCH] feat : add event recommendation system

---
 src/main.py             | 36 +++++++++++++++++++++++++++++++++++-
 tests/test_recommend.py | 18 ++++++++++++++++++
 2 files changed, 53 insertions(+), 1 deletion(-)
 create mode 100644 tests/test_recommend.py

diff --git a/src/main.py b/src/main.py
index 837fc7e..bf8dfd0 100644
--- a/src/main.py
+++ b/src/main.py
@@ -1,4 +1,4 @@
-from fastapi import FastAPI
+from fastapi import FastAPI, HTTPException
 from fastapi.responses import JSONResponse
 from pydantic import BaseModel, Field
 from typing import List
@@ -7,6 +7,7 @@
 from sklearn.model_selection import train_test_split
 from sklearn.preprocessing import StandardScaler
 from sklearn.pipeline import Pipeline
+from typing import Dict, List
 
 app = FastAPI(
     title="Veritix Microservice",
@@ -17,6 +18,12 @@
 # Global model pipeline; created at startup
 model_pipeline: Pipeline | None = None
 
+mock_user_events: Dict[str, list[str]] = {
+    "user1": ["concert_A", "concert_B"],
+    "user2": ["concert_B", "concert_C"],
+    "user3": ["concert_A", "concert_C", "concert_D"],
+    "user4": ["concert_D", "concert_E"],
+}
 
 class PredictRequest(BaseModel):
     """Request body for /predict-scalper endpoint.
@@ -31,6 +38,12 @@ class PredictRequest(BaseModel):
 class PredictResponse(BaseModel):
     probability: float
 
+class RecommendRequest(BaseModel):  
+    user_id: str  
+
+
+class RecommendResponse(BaseModel):  
+    recommendations: List[str]
 
 def generate_synthetic_event_data(num_samples: int = 2000, random_seed: int = 42) -> tuple[np.ndarray, np.ndarray]:
     """Generate synthetic data for scalper detection.
@@ -115,3 +128,24 @@ def predict_scalper(payload: PredictRequest):
 #     import uvicorn
 #     # Note: host="0.0.0.0" is crucial for Docker development
 #     uvicorn.run(app, host="0.0.0.0", port=8000)
+
+@app.post("/recommend-events", response_model=RecommendResponse)  
+def recommend_events(payload: RecommendRequest):  
+    user_id = payload.user_id  
+    if user_id not in mock_user_events:  
+        raise HTTPException(  
+            status_code=404,  
+            detail={"message": "User not found"}  
+        )  
+    user_events = set(mock_user_events[user_id])  
+    scores = {}  
+    for other_user, events in mock_user_events.items():  
+        if other_user == user_id:  
+            continue  
+        overlap = len(user_events.intersection(events))  
+        for e in events:  
+            if e not in user_events:  
+                scores[e] = scores.get(e, 0) + overlap  
+
+    recommended = sorted(scores, key=scores.get, reverse=True)[:3]  
+    return RecommendResponse(recommendations=recommended)  
\ No newline at end of file
diff --git a/tests/test_recommend.py b/tests/test_recommend.py
new file mode 100644
index 0000000..3125967
--- /dev/null
+++ b/tests/test_recommend.py
@@ -0,0 +1,18 @@
+from fastapi.testclient import TestClient  
+from src.main import app  
+
+client = TestClient(app)  
+
+def test_recommend_events_valid_user():  
+    response = client.post("/recommend-events", json={"user_id": "user1"})  
+    assert response.status_code == 200  
+    data = response.json()  
+    assert "recommendations" in data  
+    assert isinstance(data["recommendations"], list)  
+    assert len(data["recommendations"]) <= 3  
+
+def test_recommend_events_user_not_found():  
+    response = client.post("/recommend-events", json={"user_id": "unknown"})  
+    assert response.status_code == 404  
+    data = response.json()  
+    assert data["detail"] == "User not found"  
\ No newline at end of file