added the app.py file

app.py

@@ -1,49 +1,8 @@
-import os
+import gradio as gr
 
-import uvicorn
-from fastapi import FastAPI
-from fastapi.responses import Response
-from starlette.responses import RedirectResponse
-from textSummarizer.pipeline.prediction import PredictionPipeline
 
-text:str = "What is Text Summarization?"
+def greet(name):
+    return "Hello " + name + "!!"
 
-app = FastAPI()
-
-@app.get("/", tags=["authentication"])
-async def index():
-    """
-    The main page.
-    """
-    return "The API is UP and running."
-
-
-@app.get("/train")
-async def training():
-    """
-    The training page.
-    """
-    try:
-        os.system("python main.py")
-        return Response("Training successful !!")
-
-    except Exception as e:
-        return Response(f"Error Occurred! {e}")
-
-
-@app.post("/predict")
-async def predict_route(text):
-    """
-    The prediction api call.
-    """
-    try:
-
-        obj = PredictionPipeline()
-        text = obj.predict(text)
-        return text
-    except Exception as e:
-        raise e
-
-
-if __name__=="__main__":
-    uvicorn.run(app, host="0.0.0.0", port=8080)
+demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+demo.launch()

app_fast_api.py

@@ -0,0 +1,49 @@
+import os
+
+import uvicorn
+from fastapi import FastAPI
+from fastapi.responses import Response
+from starlette.responses import RedirectResponse
+from textSummarizer.pipeline.prediction import PredictionPipeline
+
+text:str = "What is Text Summarization?"
+
+app = FastAPI()
+
+@app.get("/", tags=["authentication"])
+async def index():
+    """
+    The main page.
+    """
+    return "The API is UP and running."
+
+
+@app.get("/train")
+async def training():
+    """
+    The training page.
+    """
+    try:
+        os.system("python main.py")
+        return Response("Training successful !!")
+
+    except Exception as e:
+        return Response(f"Error Occurred! {e}")
+
+
+@app.post("/predict")
+async def predict_route(text):
+    """
+    The prediction api call.
+    """
+    try:
+
+        obj = PredictionPipeline()
+        text = obj.predict(text)
+        return text
+    except Exception as e:
+        raise e
+
+
+if __name__=="__main__":
+    uvicorn.run(app, host="0.0.0.0", port=8080)