Spaces:
Paused
Paused
File size: 1,510 Bytes
9f6ffb8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 | """
Uploads rag_sft_dataset.jsonl to Adaption Labs via the official Python SDK.
"""
import os
import sys
from pathlib import Path
# Add project root to sys.path
sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
import config
from adaption import Adaption
DATASET_FILE = Path("rag_sft_dataset.jsonl")
if not DATASET_FILE.exists():
DATASET_FILE = Path(config.DATA_DIR) / "processed" / "rag_sft_dataset.jsonl"
def main():
api_key = config.ADAPTION_API_KEY or os.getenv("ADAPTION_API_KEY", "")
if not api_key:
print("Error: ADAPTION_API_KEY is missing from .env")
return
print(f"Connecting to Adaption Labs with API Key: {api_key[:10]}...{api_key[-4:]}")
client = Adaption(api_key=api_key)
if not DATASET_FILE.exists():
print(f"Error: Dataset file not found at {DATASET_FILE}")
return
file_size_mb = DATASET_FILE.stat().st_size / (1024 * 1024)
print(f"Uploading '{DATASET_FILE.name}' ({file_size_mb:.2f} MB) to Adaption Labs...")
try:
response = client.datasets.upload_file(
path=str(DATASET_FILE),
name="indic_multilingual_voice_rag",
)
print("\n Upload Successful!")
print(f"Dataset Response: {response}")
print("\nYou can now see and train this dataset in your Adaption Labs dashboard at:")
print("🔗 https://adaptionlabs.ai/app/datasets")
except Exception as e:
print(f"\nUpload error: {e}")
if __name__ == "__main__":
main()
|