python script auto outline maker with products

import os
import openai
import time
import csv
from pprint import pprint

# Set your OpenAI API key
OPENAI_API_TOKEN = "xd"
api_key = os.environ["OPENAI_API_KEY"] = OPENAI_API_TOKEN

# Initialize the OpenAI client
client = openai.OpenAI()

# Function to upload a file to OpenAI
def upload_file(file_path, purpose):
    with open(file_path, "rb") as file:
        response = client.files.create(file=file, purpose=purpose)
    return response.id  # Access the 'id' attribute directly




# Upload your files
internal_links_file_id = upload_file('internallinks.txt', 'assistants')
products_file_id = upload_file('products.txt', 'assistants')
content_plan_file_id = upload_file('2men_it_blog_content_plan_expanded (1).csv', 'assistants')

# Create an Assistant
assistant = client.beta.assistants.create(
    name="Content Creation Assistant",
    model="gpt-4-1106-preview",
    instructions="you never invent any internal links, you only use products.txt and internalinks.txt You generate blog post outlines based on {blog_post_idea}. You use {products_file_id} (which is products.txt) to add suggested RELEVANT (NOT JUST THE FIRST) 10 product images and product URLs and {internal_links_file_id} (which is internallinks.txt) to add 10 suggested collectoin internal links to the outline.",
    tools=[{"type": "retrieval"}],
    file_ids=[internal_links_file_id, products_file_id, content_plan_file_id]
)

# Function to append the outline to the existing CSV file
def append_to_csv(row, outline):
    row['Blog Outline'] = outline  # Add the generated outline to the row
    with open('2men_it_blog_content_plan_expanded (1).csv', 'a', newline='', encoding='utf-8') as f:
        writer = csv.DictWriter(f, fieldnames=row.keys())
        writer.writerow(row)

def process_content_plan():
    input_file = '2men_it_blog_content_plan_expanded (1).csv'
    output_file = 'processed_content_plan.csv'
    processed_rows = []

    with open(input_file, newline='', encoding='utf-8') as csvfile:
        reader = csv.DictReader(csvfile)
        for row in reader:
            if row.get('Processed', 'No') == 'Yes':  # Skip already processed rows
                continue

            blog_post_idea = row['Blog Post Ideas']  # Extract the blog post idea

            # Create a Thread
            thread = client.beta.threads.create()

            # Add a Message to a Thread
            message_content = f"Generate an outline for a blog post about '{blog_post_idea}'. Please include a diverse range of product suggestions from different categories in our product sitemap. You never invent any internal links, you only use products.txt and internalinks.txt. A maximum of 10 products and 10 internal links should be used."
            message = client.beta.threads.messages.create(thread_id=thread.id, role="user", content=message_content)

            # Run the Assistant
            run = client.beta.threads.runs.create(thread_id=thread.id, assistant_id=assistant.id)

            # Wait for the run to complete and retrieve the outline
            outline = None
            while True:
                run_status = client.beta.threads.runs.retrieve(thread_id=thread.id, run_id=run.id)
                if run_status.status == 'completed':
                    # Retrieve messages from the thread to see the assistant's response
                    messages = client.beta.threads.messages.list(thread_id=thread.id)
                    for message in messages.data:
                        if message.role == "assistant":
                            outline = message.content
                            break
                    break
                time.sleep(10)

            if outline:
                row['Blog Outline'] = outline  # Add the generated outline to the row
                pprint(outline)

            # Mark the row as processed and store it
            row['Processed'] = 'Yes'
            processed_rows.append(row)

    # Write the processed rows to the output file
    with open(output_file, 'w', newline='', encoding='utf-8') as f:
        writer = csv.DictWriter(f, fieldnames=processed_rows[0].keys())
        writer.writeheader()
        writer.writerows(processed_rows)

process_content_plan()