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""" | |
Configuration for database to HuggingFace pipeline. | |
Update these settings to match your setup. | |
""" | |
import os | |
# Database Configuration | |
# Note: Database connection is handled by future_bench.database.get_session() | |
# The script uses the same database connection as the main FutureBench app | |
# HuggingFace Configuration | |
HF_CONFIG = { | |
"token": os.getenv("HF_TOKEN"), # Set this in your environment | |
"data_repo": "futurebench/data", | |
"results_repo": "futurebench/results", | |
"requests_repo": "futurebench/requests", # Optional: for model submissions | |
} | |
# Data Processing Settings | |
PROCESSING_CONFIG = { | |
"days_history": 180, # How many days of data to include | |
"min_predictions": 5, # Minimum predictions per model to include | |
"event_types": ["news", "polymarket", "sports"], # Which event types to include | |
"exclude_models": ["test", "debug"], # Models to exclude from public dataset | |
} | |
# Note: Schema mapping not needed since we use SQLAlchemy ORM models | |
# The script uses the same models as convert_to_csv.py: | |
# - EventBase (events table) | |
# - Prediction (predictions table) | |