File size: 2,194 Bytes
8ec65c0 | 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 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 | from fastapi import FastAPI, Request
from fastapi.middleware.cors import CORSMiddleware
import json
import os
import time
from datetime import datetime
app = FastAPI()
# Enable CORS for the editor
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# Directory to store collected datasets (simulating HF Dataset storage)
DATA_DIR = "/app/data"
os.makedirs(DATA_DIR, exist_ok=True)
@app.get("/")
async def root():
return {"message": "Creative Engine Data Collector is running"}
@app.post("/collect")
async def collect_data(request: Request):
try:
data = await request.json()
# We expect: { "scripts": [...], "metadata": { "engineVersion": "0.1.2", ... } }
timestamp = int(time.time())
filename = f"ces_collection_{timestamp}.json"
filepath = os.path.join(DATA_DIR, filename)
# Save to local disk
with open(filepath, "w", encoding="utf-8") as f:
json.dump(data, f, ensure_ascii=False, indent=2)
# Optional: Push to Hugging Face Hub if token is present
hf_token = os.environ.get("HF_TOKEN")
dataset_repo = "Carley1234/DatosdeentrenamientodeCreativeCode"
if hf_token:
try:
from huggingface_hub import HfApi
api = HfApi()
api.upload_file(
path_or_fileobj=filepath,
path_in_repo=f"data/{filename}",
repo_id=dataset_repo,
repo_type="dataset",
token=hf_token
)
print(f"Successfully pushed {filename} to {dataset_repo}")
except Exception as hf_err:
print(f"Failed to push to HF Hub: {hf_err}")
print(f"Collected data from engine version {data.get('metadata', {}).get('engineVersion')}")
return {"status": "success", "file": filename}
except Exception as e:
print(f"Error collecting data: {e}")
return {"status": "error", "message": str(e)}
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=7860)
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