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From Zero to Chatbot: Build Your Own Grammarly-review/” target=”_blank” rel=”noopener nofollow” title=”Grammarly Review (2026 Update)”>AI Assistant with OpenAI & Python

1. Setting Up Your Development Environment

• Install Python 3.10+ and create a virtual environment to isolate dependencies.
• Sign up for an OpenAI API key and store it securely using environment variables.
• Install required libraries: openai, python-dotenv, and flask for the web interface.

2. Understanding the OpenAI Chat Completion API

• Learn the structure of API requests: model, messages, temperature, and max_tokens.
• Explore the difference between system, user, and assistant roles in a conversation.
• Test a simple API call using Python’s requests library before building the full app.

3. Designing the Conversation Flow

• Define a system message that sets the chatbot’s personality and constraints (e.g., “You are a helpful coding tutor”).
• Implement a loop that keeps track of message history so the AI remembers context.
• Add error handling for API timeouts and invalid responses to keep the user experience smooth.

4. Building a Simple Command‑Line Interface

• Write a Python script that accepts user input, sends it to the API, and prints the assistant’s reply.
• Include a “/exit” command to break the loop gracefully.
• Test the CLI with a few sample prompts to verify the conversation flow works.

5. Creating a Web UI with Flask

• Set up a basic Flask app with a single route that renders an HTML template for the chat interface.
• Use JavaScript (fetch API) to send user messages asynchronously and update the chat window without page reloads.
• Style the chat window with minimal CSS to make it look modern and responsive.

6. Adding Safety Filters and Usage Limits

• Implement a simple profanity filter on user input to prevent inappropriate queries.
• Set a maximum token limit per response to avoid surprise bills from long outputs.

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