| # 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. | |