Create app.py

app.py

@@ -0,0 +1,30 @@
+import streamlit as st
+from transformers import T5ForConditionalGeneration, T5Tokenizer
+
+# Load the model and tokenizer from Hugging Face
+model_name = "google/flan-t5-large"
+model = T5ForConditionalGeneration.from_pretrained(model_name)
+tokenizer = T5Tokenizer.from_pretrained(model_name)
+
+# Streamlit app title
+st.title("AIBUDDY Chatbot")
+
+# User input
+input_text = st.text_area("Enter your query:", "Translate English to French: 'Hello, how are you?'")
+
+if st.button("Generate"):
+    # Tokenize input
+    input_ids = tokenizer(input_text, return_tensors="pt").input_ids
+
+    # Generate output
+    with st.spinner("Generating response..."):
+        output = model.generate(input_ids, max_length=100, num_return_sequences=1)
+
+    # Decode the output
+    response = tokenizer.decode(output[0], skip_special_tokens=True)
+    
+    # Display the response
+    st.subheader("Response:")
+    st.write(response)
+
+# Run the app using the command: streamlit run your_script_name.py