fixed streamlit components

app.py

@@ -10,8 +10,8 @@ from huggingface_hub import login
 #load_dotenv()
 
 #HF_TOKEN  = os.environ.get("HF_API_TOKEN")
-HF_TOKEN = st.secrets["HF_API_TOKEN"]
-login(token=HF_TOKEN)
+#HF_TOKEN = st.secrets["HF_API_TOKEN"]
+#login(token=HF_TOKEN)
 
 # Setup logging
 logging.basicConfig(stream=sys.stdout, level=logging.INFO)
@@ -30,18 +30,18 @@ model = AutoModelForCausalLM.from_pretrained(model_id)
 # Create text generation pipeline
 pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
 
-# Continuously prompt the user for questions
-while True:
-    # User input and chat interaction
-    prompt = st.text_input("Please ask your question here (or type 'exit' to quit):")
-    if prompt.lower() == 'exit':
-        break
-
-    # Display user message in chat message container
-    st.markdown("<b style='color:Red;'>User:</b> {}".format(prompt), unsafe_allow_html=True)
-    
-    # Generate response
-    result = pipe(prompt, max_length=50, truncation=True)
-    
-    # Display bot response in chat message container
-    st.markdown("<b style='color:Green;'>Bot:</b> {}".format(result[0]['generated_text']), unsafe_allow_html=True)
+
+prompt = st.text_input("Please ask your question here:")
+
+# Button to submit question
+if st.button("Submit"):
+    if prompt.strip():
+        # Display user message in chat message container
+        st.markdown("<b style='color:Red;'>User:</b> {}".format(prompt), unsafe_allow_html=True)
+        
+        # Generate response
+        result = pipe(prompt)#, max_length=100, num_return_sequences=1)
+        
+        # Display bot response in chat message container
+        st.markdown("<b style='color:Green;'>Bot:</b> {}".format(result[0]['generated_text']), unsafe_allow_html=True)
+