Kurtis

Kurtis is an experimental fine-tuning, evaluation and inference tool for Kurtis E1.

Kurtis is a mental-health AI assistant designed with empathy at its core.

Unlike other AI models that aim for peak efficiency, Kurtis prioritizes understanding, emotional nuance, and meaningful conversations.

It won’t solve complex math problems or write code, nor will it generate images or videos.

Instead, Kurtis focuses on being a thoughtful companion, offering support, perspective, and human-like dialogue.

It doesn’t strive to break records or chase artificial intelligence supremacy—its goal is to create a space for genuine interaction.

Whether you need someone to talk to, reflect on ideas with, or engage in insightful discussion, Kurtis is there to listen and respond in an understanding way.

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Kurtis final model allows users to ask questions related to mental health topics. However, please note the following disclaimer:

Disclaimer

• Kurtis E1 is not a substitute for professional mental health therapy or advice.
• The responses generated by this model may be biased or inaccurate.
• For any serious or urgent mental health concerns, please consult with a licensed professional.
• Kurtis E1 is intended as a supportive tool for casual conversations, not for diagnosing or treating any mental health conditions.

Getting Started

Prerequisites

• uv A tool for Python dependency management.
• Python 3.10 or higher.
• Docker (optional, if you plan to use Docker).

Usage

You can interact with Kurtis by either training the model or starting a chat session.

Train the Model

To train the model using the provided configuration:

uv run -m kurtis --train --config-module kurtis.config.default

Start a Chat Session

To start a conversation with the Kurtis model:

uv run -m kurtis --chat --config-module kurtis.config.default

Command-Line Options

You can view all available command-line options using the --help flag:

uv run -m kurtis --help

The output will display:

(kurtis) ➜  kurtis git:(main) ✗ uv run -m kurtis --help

Usage: python -m kurtis [OPTIONS]

  Main command for managing the Kurtis model: - Preprocess data - Train - Chat
  interactively - Evaluate - Generate DPO data - Push datasets or model to
  Hugging Face

Options:
  --preprocessing           Pre-process the QA datasets.
  --train                   Train the model using QA datasets.
  --train-dpo               Train the model using DPO.
  --chat                    Interact with the trained model.
  --eval-model              Evaluate the model.
  --generate-dpo            Generate and clean DPO dataset.
  --push-model              Push model to Hugging Face.
  -o, --output-dir TEXT     Directory to save or load the model and
                            checkpoints.
  -c, --config-module TEXT  Kurtis python config module.
  --debug                   Enable debug mode for verbose output.
  --help                    Show this message and exit.

Makefile

A Makefile is included to help automate common development and testing tasks.

make preprocessing  - Preprocess the data using a pre-trained LLM.
make train          - Train the model.
make chat           - Start a prompt session with the model.
make install        - Install project dependencies using uv.
make eval_model     - Evaluate model.
make docker_build   - Build the Docker image for the project.
make docker_push    - Push the Docker image to the registry.
make docker_run     - Run the Docker container with output mounted.
make docker_train   - Run the training script inside the Docker container.
make docker_chat    - Start a prompt session inside the Docker container.

Evaluation Results

Work in progress.

License

This project is licensed under the MIT License - see the LICENSE file for details.