YouTube Tutorial: Watch the detailed walkthrough of this code and its functionalities.
This script demonstrates the creation and interaction with a custom OpenAI Retrieval Assistant, specifically designed for "Bean There Café." It showcases how to upload a file, create an assistant, start a thread, send messages, run the assistant, retrieve results, check messages, and modify the assistant.
Before you begin, ensure you have the following installed:
- Python 3.8 or later.
openai
Python package.python-dotenv
package for environment variable management.
- Clone this repository.
- Install the required Python packages:
pip install openai python-dotenv
- Create a
.env
file in your project's root directory. - Add your OpenAI API key to the
.env
file:OPENAI_API_KEY=your_api_key_here
The script is divided into several steps, each performing a distinct function:
- Upload File: Uploads a PDF file to be used by the assistant.
- Create Assistant: Creates a new assistant with specific instructions and tools.
- Create Thread: Starts a new thread for communication.
- Create Message: Sends a query to the thread.
- Run the Assistant: Processes the query using the assistant.
- Retrieve the Run: Fetches the result of the assistant's processing.
- Check the Messages: Retrieves and prints all messages in a thread.
- Modify the Assistant: Updates the assistant with additional capabilities.
To run the script, execute:
python main.py
You can customize the assistant by changing the file upload, the instructions, the query, and the tools as per your requirements.
- What are the items on the menu?
- Could 'Bean There Café' benefit from adopting RFID technology for inventory management, and how would this align with its operational and financial plans?
- What's the total monthly revenue supposed to be and the startup cost?
- How long will it take us to be profitable at our current monthly revenue if it stays consistent and how long will it take to make back the startup costs?
- OpenAI API Documentation: Provides more in-depth details and advanced features.
Your feedback is valuable! If you have suggestions or modifications, feel free to create an issue or a pull request. For specific queries related to the tutorial, drop a comment on the YouTube video.