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HuggingFace Inference Endpoint Handler for LearningStudio Callout Detection.
This wrapper provides an EMCO-compatible API format for LearningStudio integration,
calling the AWS Lambda-based callout detection pipeline via API Gateway.
"""
from typing import Dict, Any
from inference import inference
class EndpointHandler:
"""
HuggingFace Inference Endpoint Handler.
This class provides the interface expected by HuggingFace Inference Endpoints.
It wraps the callout detection pipeline and transforms outputs to EMCO format.
"""
def __init__(self, path: str = ""):
"""
Initialize the endpoint handler.
Args:
path: Model path (unused for this wrapper, but required by HF interface)
"""
# No model to load - this is a wrapper for an external API
pass
def __call__(self, data: Dict[str, Any]) -> Dict[str, Any]:
"""
Process an inference request.
Args:
data: Request data with format:
{
"inputs": "image_url_or_base64",
"parameters": {...} # Optional parameters
}
Returns:
EMCO-compatible response:
{
"predictions": [
{
"id": 1,
"label": "callout",
"class_id": 0,
"confidence": 0.95,
"bbox": {"x1": 100, "y1": 200, "x2": 300, "y2": 400}
},
...
],
"total_detections": N,
"image": "base64_encoded_image"
}
"""
# Extract input
inputs = data.get("inputs")
if inputs is None:
return {
"error": "Missing 'inputs' field",
"predictions": [],
"total_detections": 0,
"image": ""
}
# Extract optional parameters
parameters = data.get("parameters", {})
# Call the inference function
result = inference(inputs, parameters)
return result
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