mirror of
https://github.com/The-Art-of-Hacking/h4cker.git
synced 2024-12-11 16:54:26 -05:00
2.5 KiB
2.5 KiB
Using the OpenAI API with Python
Step 1: Setting Up the Environment
- Install Python: Make sure you have Python 3.x installed. You can download it from the official website.
- Set Up a Virtual Environment (optional but recommended):
python3 -m venv openai-lab-env source openai-lab-env/bin/activate # On Windows, use `openai-lab-env\Scripts\activate`
- Install Necessary Packages:
pip3 install openai requests
Step 2: Configuring API Credentials
-
Register on OpenAI:
- Go to the OpenAI website and register to obtain API credentials.
-
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):export OPENAI_API_KEY=your_api_key_here
- Store your API credentials securely, possibly using environment variables. In your terminal, you can set it up using the following command (replace
Step 3: Making API Calls
-
Create a Python Script:
- Create a new Python script (let’s name it
openai_lab.py
) and open it in a text editor.
- Create a new Python script (let’s name it
-
Import Necessary Libraries:
import openai openai.api_key = 'your_api_key_here' # Alternatively, use the environment variable to store the API key
-
Make a Simple API Call:
# 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
-
Experiment with Different Parameters:
- Modify the
max_tokens
,temperature
, andtop_p
parameters and observe how the responses change.
- Modify the
-
Handle API Responses:
- Learn how to handle API responses and extract the required information.
Step 5: Building a Simple Application
-
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 we discussed during class for reference.
-
Testing Your Application:
- Run various tests to ensure the functionality and robustness of your application.