Add final touches for cloud deployment

app.py

@@ -2,16 +2,14 @@
 import streamlit as st
 from utils import get_ideal_prompt, print_outputs
 
-"""
-hide_st_style = 
+hide_st_style = """
             <style>
             #MainMenu {visibility: hidden;}
             footer {visibility: hidden;}
             header {visibility: hidden;}
             </style>
-
-st.markdown(hide_st_style, unsafe_allow_html=True)
 """
+st.markdown(hide_st_style, unsafe_allow_html=True)
 
 st.title('Act as GPT')
 
@@ -34,11 +32,15 @@
 if user_input != "":
     openai.api_key = OPENAI_API_KEY
 
-    # predicting the input
-    modified_input = get_ideal_prompt(user_input, 150)
-    input_area = st.text_area("modified_input", value=modified_input, key="text_area", height=200)
+    # Generate the ideal prompt based on user input
+    predict_prompt = get_ideal_prompt(user_input, max_tokens)
+    # Text area for modified input prompt
+    prompt = st.text_area("modified_input", value=predict_prompt, key="text_area", height=200)
+    # Columns for buttons and output display
     but_col1, _, _, _ = st.columns([1, 1, 1, 1])
     write_col1, write_col2, write_col3 = st.columns([1, 1, 1])
 
     if but_col1.button("Run"):
-        print_outputs(input_area, user_input, model, write_col1, write_col2, write_col3)
+        print_outputs(prompt, user_input, model, write_col1, write_col2, write_col3)
+
+

utils.py

@@ -1,11 +1,6 @@
 import streamlit as st
 import openai
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, AutoConfig
-import nltk
-
-nltk.download('punkt')
-nltk.download('wordnet')
-nltk.download('stopwords')
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
 
 @st.cache_resource()
@@ -22,13 +17,6 @@ def get_completion(
         prompt,
         system_prompt="You will act as an advanced language model. You will be given an input prompt from a user, your task is just to paraphrase the prompt, don't do anything else.",
         model="gpt-3.5-turbo"):
-    """
-    This function servers as a portal into Gpt API
-    :param system_prompt:
-    :param prompt:
-    :param model:
-    :return:
-    """
     if not prompt:
         return prompt  # Return an empty string if the prompt is invalid
     # you will be provided with a prompt to act as someone or something, try to give the most ideal output for an unexpierienced user and epxlain everything from scratch
@@ -46,13 +34,31 @@ def get_completion(
 
 
 def get_ideal_prompt(user_prompt, max_new_tokens=150):
+    """
+    Generate the ideal prompt based on the user input and maximum number of new tokens.
+    Args:
+        user_prompt (str): The user input.
+        max_new_tokens (int): Maximum number of new tokens to predict the output prompt.
+
+    Returns:
+        str: The generated ideal prompt.
+    """
     batch = tokenizer(user_prompt, return_tensors="pt")
-    generated_ids = model.generate(batch["input_ids"], max_new_tokens)
+    generated_ids = model.generate(batch["input_ids"], max_length=max_new_tokens)
     output = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
     return output[0]
 
 
 def print_outputs(input_text, system_prompt="", model='gpt-3.5-turbo', *args):
+    """
+     Print the outputs using the GPT API through the specified model and an internal function.
+
+    Args:
+        input_text (str): The input text.
+        system_prompt (str): The system prompt.
+        model (str): The GPT model to use.
+        *args: Additional arguments for writing the output.
+    """
     for arg in args:
         output = get_completion(input_text, system_prompt, model)
         arg.write(output)