diff --git a/ai_research/labs/basic_openai_api.md b/ai_research/labs/basic_openai_api.md new file mode 100644 index 0000000..6ea3aa5 --- /dev/null +++ b/ai_research/labs/basic_openai_api.md @@ -0,0 +1,67 @@ +# Using the OpenAI API with Python + +### Step 1: Setting Up the Environment + +1. **Install Python**: Make sure you have Python 3.x installed. You can download it from the [official website](https://www.python.org/). +2. **Set Up a Virtual Environment** (optional but recommended): + ```bash + python3 -m venv openai-lab-env + source openai-lab-env/bin/activate # On Windows, use `openai-lab-env\Scripts\activate` + ``` +3. **Install Necessary Packages**: + ```bash + pip3 install openai requests + ``` + +### Step 2: Configuring API Credentials + +4. **Register on OpenAI**: + - Go to the [OpenAI website](https://www.openai.com/) and register to obtain API credentials. + +5. **Configure API Credentials**: + - Store your API credentials securely, possibly using environment variables. In your terminal, you can set it up using the following command (replace `your_api_key_here` with your actual API key): + ```bash + export OPENAI_API_KEY=your_api_key_here + ``` + +### Step 3: Making API Calls + +6. **Create a Python Script**: + - Create a new Python script (let’s name it `openai_lab.py`) and open it in a text editor. + +7. **Import Necessary Libraries**: + ```python + import openai + openai.api_key = 'your_api_key_here' # Alternatively, use the environment variable to store the API key + ``` + +8. **Make a Simple API Call**: + ```python + # Generate the AI response using the GPT-3.5 model (16k) + # https://beta.openai.com/docs/api-reference/create-completion + response = openai.ChatCompletion.create( + model="gpt-3.5-turbo-16k", + messages=prompt, + max_tokens=15000 + ) + + # print the AI response + print(response.choices[0].message.content) + ``` + +### Step 4: Experimenting with the API + +9. **Experiment with Different Parameters**: + - Modify the `max_tokens`, `temperature`, and `top_p` parameters and observe how the responses change. + +10. **Handle API Responses**: + - Learn how to handle API responses and extract the required information. + +### Step 5: Building a Simple Application + +11. **Develop a Simple Application**: + - Create a more complex script that could function as a Q&A system or a content generation tool. You can use [the "Article Generator" example](https://github.com/The-Art-of-Hacking/h4cker/blob/master/ai_research/ML_Fundamentals/ai_generated/article_generator.py) we discussed during class for reference. + +12. **Testing Your Application**: + - Run various tests to ensure the functionality and robustness of your application. +