feat: implement FastAPI service for Sinhala sentiment analysis with model integration and API tests

app/main.py

@@ -1,6 +1,6 @@
 from fastapi import FastAPI, HTTPException
 from pydantic import BaseModel
-from app.model import predict_sentiment
+from app.model import predict_sentiment, load_model
 import logging
 
 logging.basicConfig(level=logging.INFO)
@@ -19,6 +19,16 @@ class SentimentResponse(BaseModel):
     label: str
     score: float
 
+@app.on_event("startup")
+async def startup_event():
+    """Load the model when the app starts."""
+    try:
+        load_model()
+        logger.info("Model loaded successfully on startup")
+    except Exception as e:
+        logger.error(f"Failed to load model on startup: {e}")
+        raise
+
 @app.get("/")
 def read_root():
     return {"message": "Welcome to the Sinhala Sentiment Analysis API. Use POST /predict to analyze text."}

app/model.py

@@ -5,14 +5,18 @@ logger = logging.getLogger(__name__)
 
 # Using a robust Sinhala sentiment analysis model from Hugging Face
 MODEL_NAME = "keshan/sinhala-sentiment-analysis"
+sentiment_pipeline = None
 
-try:
-    logger.info(f"Loading model {MODEL_NAME}...")
-    sentiment_pipeline = pipeline("sentiment-analysis", model=MODEL_NAME)
-    logger.info("Model loaded successfully.")
-except Exception as e:
-    logger.error(f"Error loading model: {e}")
-    sentiment_pipeline = None
+def load_model():
+    global sentiment_pipeline
+    if sentiment_pipeline is None:
+        try:
+            logger.info(f"Loading model {MODEL_NAME}...")
+            sentiment_pipeline = pipeline("sentiment-analysis", model=MODEL_NAME)
+            logger.info("Model loaded successfully.")
+        except Exception as e:
+            logger.error(f"Error loading model: {e}")
+            raise e
 
 def predict_sentiment(text: str):
     if not sentiment_pipeline:

tests/test_api.py

@@ -1,20 +1,24 @@
 from fastapi.testclient import TestClient
 from app.main import app
+import pytest
 
-client = TestClient(app)
+@pytest.fixture(scope="module")
+def client():
+    with TestClient(app) as c:
+        yield c
 
-def test_read_root():
+def test_read_root(client):
     response = client.get("/")
     assert response.status_code == 200
     assert "Welcome" in response.json()["message"]
 
-def test_predict_sentiment_positive():
+def test_predict_sentiment_positive(client):
     # "This is a very good creation." in Sinhala
     response = client.post("/predict", json={"text": "මෙය ඉතා හොඳ නිර්මාණයක්."}) 
     assert response.status_code == 200
     assert "label" in response.json()
     assert "score" in response.json()
 
-def test_predict_sentiment_empty():
+def test_predict_sentiment_empty(client):
     response = client.post("/predict", json={"text": ""})
     assert response.status_code == 400