Telegpt is a project that combines the power of Generative Pretraining Transformers (GPT) with the versatility of Telegram's API to create a responsive and interactive chatbot. It utilizes a model trained on chat data to respond to messages in a human-like manner.
You can clone the Telegpt repository and install the package using the following commands:
> cd Telegpt
> ./install.shensure you have installed the dependencies listed in the requirements.txt file.
pip install -r requirements.txtTraining Telegpt requires conversational data, and the provided prepare.py script helps to facilitate this process. This script is responsible for processing the input text files, filtering specific phrases, removing timestamps, and encoding the text using Byte-Pair Encoding (BPE). The output is a binary file containing the processed tokens, which is ready to be consumed by the training script.
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Exporting Chats: From the WhatsApp mobile application, I exported individual chats. Each chat was exported as a
.txtfile and stored in a directory nameddata/. Ensure all your chat data files are placed in a specific directory. -
Preprocessing Data: I used the
prepare.pyscript to preprocess the concatenated chat file:python prepare.py --folder data/
Replace
data/with the path to your directory if you've used a different one.
After running the script, train.bin and val.bin files will be generated in the same directory. These files contain the Byte-Pair Encoded tokens of your chat data, ready to be used for training.
Telegpt allows you to train the model on your own data. A convenient shell script named train.sh simplifies the process of job submission to an HPC cluster using Slurm workload manager. This script will prompt you to enter computational resources requirements, generate a temporary Slurm job submission script, and submit it.
After training the model, you can use it to generate responses. Integrating with the Telegram API allows the model to function as a chatbot.