Update app.py

app.py

@@ -1,23 +1,20 @@
-# app.py
-
-# Install necessary libraries (Run this separately in your environment if needed)
-# !pip install pandas sentence-transformers transformers datasets faiss-cpu gradio fastapi uvicorn
+# Install necessary libraries
+#!pip install pandas sentence-transformers transformers datasets faiss-cpu gradio
 
 # Import libraries
 import pandas as pd
-from sentence_transformers import SentenceTransformer
+from sentence_transformers import SentenceTransformer, util
+import torch
 import faiss
 from datasets import load_dataset
-from fastapi import FastAPI
 import gradio as gr
 
-# Initialize FastAPI app
-app = FastAPI()
-
 # Load the Dataset from Hugging Face and FAQ CSV
 support_data = load_dataset("rjac/e-commerce-customer-support-qa")
 
-# Load FAQ data from uploaded file (change as needed for local path)
+# Upload and load the FAQ data
+from google.colab import files
+uploaded = files.upload()
 faq_data = pd.read_csv("Ecommerce_FAQs.csv")
 
 # Preprocess and Clean Data
@@ -66,24 +63,14 @@ def chatbot_interface(user_input):
     response = retrieve_answer(user_input)
     return f"Bot: {response}"
 
-# Define a route to serve the Gradio interface
-@app.get("/")
-def home():
-    return {"message": "Welcome to the E-commerce Support Chatbot!"}
-
-# Launch Gradio Interface in a separate thread
-def launch_gradio():
-    iface = gr.Interface(
-        fn=chatbot_interface,
-        inputs=gr.Textbox(lines=2, placeholder="Type your question here..."),
-        outputs="text",
-        title="E-commerce Support Chatbot",
-        description="Ask questions about order tracking, returns, account help, and more!"
-    )
-    iface.launch(share=True)
-
-if __name__ == "__main__":
-    import threading
-    threading.Thread(target=launch_gradio).start()
-    import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=8000)
+# Set up Gradio Chat Interface
+iface = gr.Interface(
+    fn=chatbot_interface,
+    inputs=gr.Textbox(lines=2, placeholder="Type your question here..."),
+    outputs="text",
+    title="E-commerce Support Chatbot",
+    description="Ask questions about order tracking, returns, account help, and more!"
+)
+
+# Launch the Interface
+iface.launch(share=True)