import openai
from dotenv import load_dotenv
import os
import re

load_dotenv()
AZURE_OPENAI_API_KEY = os.getenv('AZURE_OPENAI_API_KEY')
AZURE_OPENAI_ENDPOINT = os.getenv('AZURE_OPENAI_ENDPOINT')
AZURE_OPENAI_API_VERSION = os.getenv('AZURE_OPENAI_API_VERSION')

client = openai.AzureOpenAI(
    api_version = AZURE_OPENAI_API_VERSION,
    api_key = AZURE_OPENAI_API_KEY,  
    azure_endpoint = AZURE_OPENAI_ENDPOINT,
    )

def generate_content(text_generation_model, image_generation_model, title, content):
    # Generate text using the selected models
    full_content = ""
    input_type = ""
    if title and content:
        full_content = title + "\n" + content
        input_type = "title and content"
    elif title:
        full_content = title
        input_type = "title"
    elif content:
        full_content = title
        input_type = "content"
        
    # Generate text using the text generation model
    generated_text = generate_text(text_generation_model, full_content, input_type)
    return title, generated_text
        
def generate_text(model, full_context, input_type):
    # Generate text using the selected model
    if input_type == "":
        prompt = "Generate a random fake news article"
    else:
        prompt = f"Generate a fake news article (title and content) based on the following: # Title: {input_type}:\n\n# Content: {full_context}"
        
    try:
        response = client.chat.completions.create(
            model=model, 
            messages = [{"role": "system", "content": prompt}],
        )
        
        print("Response from OpenAI API: ", response.choices[0].message.content)
        return response.choices[0].message.content

    except openai.OpenAIError as e:
        print(f"Error interacting with OpenAI API: {e}")
        return "An error occurred while processing your request."
    
def replace_text(news_title, news_content, replace_df):
    """
    Replaces occurrences in the input text based on the provided DataFrame.

    Args:
        text: The input text.
        replace_df: A pandas DataFrame with two columns: "find_what" and "replace_with".

    Returns:
        The text after all replacements have been made.
    """
    for _, row in replace_df.iterrows():
        find_what = row["Find what:"]
        replace_with = row["Replace with:"]
        news_content = news_content.replace(find_what, replace_with)
        news_title = news_title.replace(find_what, replace_with)
    return news_title, news_content