Create app.py

app.py

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+import streamlit as st
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+
+# Load model and tokenizer
+model_name = "kalyani2599/emotional_support_bot"
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+def chatbot_response(input_text):
+    inputs = tokenizer(input_text, return_tensors="pt")
+    outputs = model.generate(**inputs, max_length=100)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
+
+# Streamlit UI
+st.title("Emotional Support Chatbot")
+st.write("Chat with the emotional support bot below:")
+
+user_input = st.text_input("Your Message")
+if user_input:
+    response = chatbot_response(user_input)
+    st.text_area("Chatbot Response", response, height=150)