README.md

QuestCrafter-AI_Project

QuestCrafter is a lightweight generative AI project that builds a "Dungeon Master" for RPG quests. It fine-tunes a small language model on curated prompt-to-quest data, compares baseline vs fine-tuned outputs, evaluates quality with automatic metrics and a human rubric, and delivers a simple interactive demo (Streamlit or Gradio).

Setup

• Python 3.10+
• Create a virtual env and install dependencies:
  • pip install -r requirements.txt

Repository structure (W1)

• data/ raw and processed datasets
• scripts/ data and training scripts (W1 starts with download_data.py)
• models/ model checkpoints (later)
• docs/ project docs (board, roles)

Data pipeline (W1)

We use the Reddit Jokes dataset (CSV). The script cleans, filters, splits, and exports JSONL files with a consistent schema.

Download + preprocess

Example: python download_data.py --dataset redditjokes --local_csv path/to/reddit_jokes.csv

Output: data/raw/redditjokes/train.jsonl, val.jsonl, test.jsonl

JSONL schema

Each line has:

• prompt
• response
• source
• optional metadata (e.g., score, author)

Filters (defaults)

• Prompt: 5 to 300 characters (if prompt exists)
• Response: 20 to 800 characters
• Drops [deleted] / [removed]

Override with: --min_prompt_chars, --max_prompt_chars, --min_response_chars, --max_response_chars, --keep_deleted

Team docs

• GitHub board and issues: docs/github_board.md
• Roles, branches, and tasks: docs/team_roles.md

Upload dataset to Hugging Face

Use the script below to upload archive.zip to your dataset repo.

1. Install deps: pip install -r requirements.txt

2. Upload (choose one):

• With token env: set HF_TOKEN=your_token python upload_to_hf.py --repo_id GemimaOndele/questcrafter-dataset --file "C:\Users\gemim\OneDrive\Bureau\M1-cours-Data engineer\MSC 1 AI\Semestre 2\Foundations of machine learning and datascience\Project\archive.zip"

• With token argument: python upload_to_hf.py --token your_token --repo_id GemimaOndele/questcrafter-dataset --file "C:\Users\gemim\OneDrive\Bureau\M1-cours-Data engineer\MSC 1 AI\Semestre 2\Foundations of machine learning and datascience\Project\archive.zip"

If you already logged in with huggingface-cli login, the script will use that cached token.