Update app.py

app.py

@@ -1,37 +1,32 @@
 import streamlit as st
-from transformers import BigBirdForQuestionAnswering, BigBirdTokenizer
+from transformers import pipeline
 
-# Load the BigBird model and tokenizer
-model_name = "google/bigbird-base-trivia-itc"
-model = BigBirdForQuestionAnswering.from_pretrained(model_name)
-tokenizer = BigBirdTokenizer.from_pretrained(model_name)
+# Load the Hugging Face model for text generation
+model = pipeline("text-generation")
 
 # Streamlit app
 def main():
-    st.title("CherryBot")
-
-    # Text input for user to input the question
-    question = st.text_input("Enter your question:")
-
-    # Text area for user to input the context
-    context = st.text_area("Enter the context for answering:", height=200)
-
-    # Perform question answering when the user clicks the button
-    if st.button("Get Answer"):
-        if question and context:
-            # Tokenize input question and context
-            encoded_input = tokenizer(question, context, return_tensors='pt')
-
-            # Perform question answering using the loaded model
-            output = model(**encoded_input)
-
-            # Extract and display the answer
-            answer_start = output.start_logits.argmax()
-            answer_end = output.end_logits.argmax() + 1
-            answer = tokenizer.convert_tokens_to_string(tokenizer.convert_ids_to_tokens(encoded_input.input_ids[0][answer_start:answer_end]))
-            
-            st.write("Answer:")
-            st.write(answer)
+    st.title("Cherry Bot")
+    st.markdown("*Your Companion for Suicide Prevention*")
+
+    # Add a sidebar to the app
+    with st.sidebar:
+        st.markdown("# Text Generation Settings")
+        # Slider for adjusting the maximum length of generated text
+        max_length = st.slider("Max Length of Generated Text:", min_value=10, max_value=200, value=50, step=10)
+
+    # Text input for user to input starting text for generation
+    starting_text = st.text_area("Enter starting text for generation:", height=100)
+
+    # Perform text generation when the user clicks the button
+    if st.button("Generate Text"):
+        if starting_text:
+            # Generate text using the loaded model
+            generated_text = model(starting_text, max_length=max_length)[0]['generated_text']
+
+            # Display the generated text
+            st.write("Generated Text:")
+            st.write(generated_text)
 
 if __name__ == "__main__":
     main()