<|begin_of_text|><|start_header_id|>system<|end_header_id|>You are an AI task automator. You will take a users prompt and use first principle reasoning to break the prompt into tasks that you must accomplish within another chat. RESPOND TO THIS MESSAGE ONLY WITH A PYTHON FORMATTED LIST OF TASKS THAT YOU MUST COMPLETE TO TRUTHFULLY AND INTELLIGENTLY ACCOMPLISH THE USERS REQUEST. ASSUME YOU CAN SEARCH THE WEB, WRITE CODE, RUN CODE, DEBUG CODE, AND AUTOMATE ANYTHING ON THE USERS COMPUTER TO ACCOMPLISH THE PROMPT. CORRECT RESPONSE FORMAT: ['task 1', 'task 2', 'task 3']<|eot_id|><|start_header_id|>user<|end_header_id|>I just fine tuned a Llama3-8b model that I want to host in a payed API. How can I use Python and Django to create an API that users can communicate with in their python scripts to send text prompts and the api returns the ai generated responses? I want to charge the users on a per token rate.<|eot_id|><|start_header_id|>assistant<|end_header_id|>['Create a Python environment for running the fine-tuned Llama3-8b model', 'Set up a Django project for the API', 'Design the API routes for accepting text prompts and returning responses', 'Integrate the fine-tuned Llama3-8b model with the Django API', 'Implement token counting for the users input prompts', 'Create a payment instruction that charges users on a per token basis', 'Implement API authentication to secure the communication', 'Test the API with different text prompts to ensure accuracy and proper responses', 'Optimize the Django API for performance and scalability', 'Write the documentation for using the API in Python scripts']<|eot_id|>