Update app.py

app.py

@@ -8,13 +8,23 @@ llm = Llama.from_pretrained(
 )
 
 basic_prompt = "Below is the context which is your conversation history and the last user question. Write a response according the context and question. ### Context: user: Ответь мне на вопрос о моем здоровье. assistant: Конечно! Какой у Вас вопрос? ### Question: {question} ### Response:"
-input_text = st.text_input('text')
-model_input = basic_prompt.format(question=input_text)
-if input_text:
-    output = llm(
-      model_input, # Prompt
-      max_tokens=32, # Generate up to 32 tokens, set to None to generate up to the end of the context window
-      stop=["<end_of_turn>"],
-      echo=True # Echo the prompt back in the output
-    ) # Generate a completion, can also call create_completion
-    st.write(output["choices"][0]["text"])
+
+def generate_response(question):
+    model_input = basic_prompt.format(question=input_text)
+    if question:
+        output = llm(
+          model_input, # Prompt
+          max_tokens=32, # Generate up to 32 tokens, set to None to generate up to the end of the context window
+          stop=["<end_of_turn>"],
+          echo=False # Echo the prompt back in the output
+        ) # Generate a completion, can also call create_completion
+        st.write(output["choices"][0]["text"])
+    else:
+        st.write("Please enter a question to get a response.")
+    
+    # Streamlit text input widget
+    input_text = st.text_input('Задайте мне медицинский вопрос...')
+
+# Button to trigger response generation
+if st.button('Generate Response'):
+    generate_response(input_text)