GPT has become the most widely used artificial intelligence tool because it packages GPT technology in a robust and intuitive chatbot. Many people rely on GPT to have interesting discussions, respond to questions, offer original ideas, and support coding and writing. However, GPT has some restrictions, such as not allowing users to save their data for later use and having a knowledge data expiration date of September 2021. This article will teach you how to Develop Custom GPT from scratch.
Step 1: Get the App and Script and Set Them Up
A computer running Windows 10 or Windows 11 is required to follow these steps. Installing the most recent versions of Python3, Git, Microsoft C++, and the GPT-retrieval script from GitHub is necessary to supply GPT with user-specific data. Ensure that every piece of software on your computer is the most recent version to prevent any glitches. Python3 requires that you select Add python.exe to PATH before clicking Install Now. This is crucial because it lets you install Python in any folder.
It would be best to get the Microsoft Visual Studio Build Tools before installing Microsoft C++. After the installation, select Desktop Development with C++ from the list of available options and click Install.
You can now download the Python script to easily query custom local data once you have the most recent versions of Python3, Git, and Microsoft C++ installed.
Step 2: Set Up the Local Environment
Launch a terminal inside the GPT-retrieval-main folder you downloaded to configure the environment. Launch Terminal and navigate to the GPT-retrieval-main folder to accomplish this.
This command uses the Python package manager to set up and maintain a Python development environment.
When the virtual setting is ready, you can provide an OpenAI API key to use their services. First, it would be best to generate an API key on OpenAI’s API keys page by choosing Create new secret key, giving the key a name, and then clicking the Create secret key button.
You will receive several characters. Your OpenAI service key is this. Click the relevant copy button to create a copy of the API key. Please remember that this API key is not public. If you want people to help you use it, only tell them about it.
After copying the constants:
- Please return to the GPT-retrieval-main folder and open them in Notepad.
- Where it says “now,” enter your API key.
- Remember to keep the file safe!
Now that you have your virtual machine up and running and your OpenAI API key installed, you can begin developing. GPT is now accepting user-provided data.
Step 3: Adding Custom Data
To incorporate user-supplied information, copy all text files to the data folder inside gpt-retrieval-main. PDF, TXT, and DOC files are all acceptable for the textual data.
Step 4: Querying GPT Through Terminal
The Python script enables you to query information from the internet and the custom data we’ve added to the data folder. This means the standard GPT backend and all local data stored in the data folder will be available.
Type “python gpt.py” into a command prompt and pass in your question or query as the script’s argument.
Please use quotation marks around your questions.
Indeed, that was successful! This indicates that Develop Custom GPT could decipher the earlier-provided Personal Sched.txt. Let’s test to see if you could give GPT information that predated its knowledge cutoff date.
Conclusion
Providing GPT with your data is a potent way to boost the model’s accuracy. This approach allows you to train the model on any text data you like using the same methods as traditional GPT, albeit with some restrictions. However, this will soon change as you have access to the most recent GPT-4 model, and it becomes simpler to integrate your data with the LLM.
