changed app.py

app.py

@@ -1,6 +1,7 @@
 import nltk
-from fastapi import FastAPI, Form
-from fastapi.responses import PlainTextResponse
+from fastapi import FastAPI
+from fastapi.responses import JSONResponse
+from pydantic import BaseModel
 import joblib
 
 # Download necessary NLTK resources
@@ -12,11 +13,16 @@ model = joblib.load('disaster_classification_model.joblib')
 
 app = FastAPI()
 
-@app.post("/predict", response_class=PlainTextResponse)
-async def predict(text: str = Form(...)):
+class TextRequest(BaseModel):
+    text: str
+
+@app.post("/predict")
+async def predict(request: TextRequest):
+    text = request.text
     # The preprocessing is now handled by the loaded pipeline
     prediction = model.predict([text])[0]
-    return "disaster" if prediction == 1 else "not"
+    result = "disaster" if prediction == 1 else "not"
+    return JSONResponse(content={"output": result})
 
 @app.get("/")
 async def root():
@@ -24,4 +30,4 @@ async def root():
 
 if __name__ == "__main__":
     import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=7860)
+    uvicorn.run(app, host="0.0.0.0", port=7860)