Create app.py

app.py

@@ -1,25 +1,13 @@
 from fastapi import FastAPI
-from transformers import pipeline
+
+from routers import distilbert
  
 # Create a new FastAPI app instance
 app = FastAPI()
- 
-# Initialize the text classification pipeline
-# This function will be able to classify text
-# given an input.
-model_path = "SebaK13/DistilBERT-finetuned-customer-queries-balanced"
-pipe = pipeline("text-classification", model=model_path)
 
+app.include_router(distilbert)
 
 @app.get("/")
 def greet_json():
     return {"detail": "AI Challenge FastAPI"}
- 
-# Define a function to handle the GET request at `/predict`
-# The predict() function is defined as a FastAPI route that takes a 
-# string parameter called query. The function returns label based on the # input using the pipeline() object, and returns a JSON response 
-# containing the predicted label under the key "label"
-@app.get("/predict")
-def predict(query: str):
-    output = pipe(query)
-    return {"label": output[0]["generated_text"]}
+