Build a Python Chatbot with the OpenAI API

This project walks through how to build a simple chatbot using the OpenAI API (or the Together API) in pure Python. Each file demonstrates one logical step in building up the final chatbot, from a single message to a full multi-turn conversation with memory and token management.

Who This Is For

This project is great for:

• Anyone new to LLMs who wants to learn how to use an API instead of a chat interface
• Beginners learning how to structure Python scripts
• Developers looking to understand how chat history and token limits work

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Project Files

File	Description
part1_basic_chat.py	Minimal working example: send one message and get a reply.
part2_functional_chat.py	Wraps the interaction in a function and uses variables for model and config.
part3_chat_loop.py	Adds a chat loop with memory (multi-turn conversations).
part4_final.py	Full chatbot with token budgeting using tiktoken to prevent runaway costs.
oop_chatbot.py	Full chatbot refactored to use OOP.

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Requirements

You'll need to install a couple of packages:

pip install openai tiktoken

If you're using the Together API:

pip install together

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API Key Setup

Set your API key in your environment variables. You can use either OpenAI or Together:

# For OpenAI
export OPENAI_API_KEY="your-api-key"

# OR for Together
export TOGETHER_API_KEY="your-api-key"

Never hardcode your API key in your script. Use environment variables to keep them secure.

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What You'll Learn

• How to connect to an LLM using the OpenAI or Together API
• How to format a messages list for conversation
• How to manage chat history to support memory
• What temperature and max tokens control
• How to estimate and manage token usage with tiktoken

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Model Notes

This project uses:

• "gpt-4.1-nano-2025-04-14" — A cheap, fast OpenAI-compatible model
• "meta-llama/Llama-3.3-70B-Instruct-Turbo-Free" — A free model on Together (slower but costs $0)

You can swap either one in the MODEL variable.