Update app.py

app.py

@@ -1,15 +1,41 @@
 import streamlit as st
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+
+st.title("Generating Response with HuggingFace Models")
+st.markdown("## Model: `facebook/blenderbot-400M-distill`")
+
+import os
+if "model" not in os.environ:
+    with st.spinner("Getting this ready for you.."):
+        model_name = "facebook/blenderbot-400M-distill"
+        model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+        tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+        os.environ["MODEL"] = "1"#model
+        os.environ["TOKENIZER"] = "1"#tokenizer
 
-st.title("custom chatbot with HF model")
 
 
 def get_response(input_text):
 
-    response = f"this is response for {input_text}"
+    # Tokenize the input text and history
+    inputs = tokenizer.encode_plus(input_text, return_tensors="pt")
+
+    # Generate the response from the model
+    outputs = model.generate(**inputs)
+
+    # Decode the response
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True).strip()
 
     return response
 
-user_input = st.text_input("Enter your query here..")
+user_input = st.text_area("Enter your query here...")
+
 if st.button("Get Response") and user_input:
-    answer = get_response(user_input)
-    st.write(answer)
+    with st.spinner("Generating Response..."):
+        answer = get_response(user_input)
+    if answer is not None:
+        st.success('Great! Response generated successfully')
+        st.write(answer)