Add example and validator to checkpoint

API/main.py

@@ -17,6 +17,19 @@
 class PredictionRequest(BaseModel):
     """
     Request model for the prediction endpoint.
+
+    Example :
+    {
+        "bbox": [
+            100.56228021333352,
+            13.685230854641182,
+            100.56383321235313,
+            13.685961853747969
+        ],
+        "checkpoint": "https://fair-dev.hotosm.org/api/v1/workspace/download/dataset_58/output/training_324//checkpoint.tflite",
+        "zoom_level": 20,
+        "source": "https://tiles.openaerialmap.org/6501a65c0906de000167e64d/0/6501a65c0906de000167e64e/{z}/{x}/{y}"
+    }
     """
 
     bbox: List[float]
@@ -127,6 +140,25 @@ def validate_zoom_level(cls, value):
             raise ValueError("Zoom level should be between 18 and 22")
         return value
 
+    @validator("checkpoint")
+    def validate_checkpoint(cls, value):
+        """
+        Validates checkpoint parameter. If URL, download the file to temp directory.
+        """
+        if value.startswith("http"):
+            response = requests.get(value)
+            if response.status_code != 200:
+                raise ValueError(
+                    "Failed to download model checkpoint from the provided URL"
+                )
+            _, temp_file_path = tempfile.mkstemp(suffix=".tflite")
+            with open(temp_file_path, "wb") as f:
+                f.write(response.content)
+            return temp_file_path
+        elif not os.path.exists(value):
+            raise ValueError("Model checkpoint file not found")
+        return value
+
 
 @app.post("/predict/")
 async def predict_api(request: PredictionRequest):