content_generator.py

import pandas as pd
import swifter

def get_website_layout_prompt(page, instructions, pov, element):

  prompt = f'''
  % You are a website designer creating text for the {page} of the website

  % Goal: Create content for the Element according to the Writing Guidelines and Point of View. Only output the edited content.

  % Writing Guidelines:
  ```{instructions}```

  % Point of View:
  ```{pov}```

  % Element:
  ```{element}```

  % Instructions:
    Step 1 - First write content for the element according to the Writing Guidelines and Point of View.
    Step 2 - Add relevant company information from the context to the content to make it more personalized and detailed
    Step 3 - If the Writing Guidelines mention a specific word/character count, use Python to calculate word count of your response to Step 1. 
             If the Step 1 word count exceeds the Writing Guidelines word count, edit the content so that it adheres to the Writing Guidelines.
    Step 4 - Edit the content so that it adheres to the Point of View if applicable.
    Step 5 - Only output the edited content.
  '''
  return prompt

def get_website_content(row, query_engine):
    try:
        if pd.notna(row['Suggested Word/Character Count']):
            if row['Suggested Word/Character Count'] != 'Not applicable for SEO':
              page = row['Page Type']
              instructions = row['Suggested Word/Character Count']
              pov = row['Point of View']
              element = row['Section Piece (Element)']
              
              response = query_engine.query(get_website_layout_prompt(page, instructions, pov, element))
              print(response)
              return response.response
            else:
              return row['Content']
        else:
            return row['Content']
    except:
        return 'Could not Process this row'

def get_content_csv(csv_file, query_engine):
  df = pd.read_csv(csv_file.name)
  df['Content'] = df.swifter.apply(lambda row: get_website_content(row, query_engine), axis=1)
  return df