Create app.py

app.py

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+import streamlit as st
+import requests
+
+# Set the model ID of your fine-tuned model on Hugging Face
+MODEL_ID = "Mishal23/fine-tuned-dialoGPT-crm-chatbot"  # Your model ID
+
+# Retrieve your Hugging Face token from secrets
+HUGGING_FACE_TOKEN = st.secrets["HUGGING_FACE_TOKEN"]
+
+# Function to generate a response from the chatbot using the Hugging Face API
+def generate_response(prompt):
+    headers = {"Authorization": f"Bearer {HUGGING_FACE_TOKEN}"}
+    payload = {"inputs": prompt}
+    
+    try:
+        # Make the API call to the Hugging Face model
+        response = requests.post(f"https://api-inference.huggingface.co/models/{MODEL_ID}", headers=headers, json=payload)
+        response.raise_for_status()  # Raise an error for bad responses
+        return response.json()[0]['generated_text']
+    except requests.exceptions.HTTPError as http_err:
+        st.error(f"HTTP error occurred: {http_err}")
+        return "Sorry, there was an error with the server."
+    except requests.exceptions.RequestException as req_err:
+        st.error(f"Request error occurred: {req_err}")
+        return "Sorry, there was an issue with your request."
+    except Exception as e:
+        st.error(f"Error generating response: {e}")
+        return "Sorry, I couldn't generate a response."
+
+# Streamlit UI setup
+st.title("Chatbot Powered by Hugging Face")
+st.subheader("Talk to the Chatbot")
+
+# User input
+user_input = st.text_input("You: ", "")
+
+# Button to submit the input
+if st.button("Send"):
+    if user_input:
+        with st.spinner("Generating response..."):
+            bot_response = generate_response(user_input)
+            st.text_area("Chatbot:", value=bot_response, height=200)
+    else:
+        st.warning("Please enter a message before sending.")