Create app.py

app.py

@@ -0,0 +1,53 @@
+import os
+from huggingface_hub import InferenceClient
+import base64
+import json
+
+class LoRAInferenceWrapper:
+    def __init__(self, model_id, lora_file_path):
+        """
+        Initialize the LoRA Inference Wrapper.
+        
+        Args:
+            model_id (str): Hugging Face model ID (e.g., stabilityai/stable-diffusion-3.5-large).
+            lora_file_path (str): Path to the local LoRA file.
+        """
+        # Retrieve the API token from environment variables
+        token = os.getenv("HF_TOKEN")
+        if not token:
+            raise ValueError("HF_TOKEN is not set. Add it as a secret in the Hugging Face Space.")
+        self.client = InferenceClient(model_id, token=token)
+        self.lora_file_path = lora_file_path
+
+    def load_lora_weights(self):
+        # Load LoRA weights (same as before)
+        try:
+            with open(self.lora_file_path, "rb") as f:
+                lora_weights = f.read()
+            return base64.b64encode(lora_weights).decode('utf-8')
+        except FileNotFoundError:
+            raise Exception(f"LoRA file not found at path: {self.lora_file_path}")
+
+    def generate_with_lora(self, prompt):
+        # Generate image (same as before)
+        processed_lora = self.load_lora_weights()
+        extended_prompt = json.dumps({
+            "prompt": prompt,
+            "lora": processed_lora
+        })
+        result = self.client.text_to_image(prompt=extended_prompt)
+        return result
+
+# Example usage
+if __name__ == "__main__":
+    model_id = "stabilityai/stable-diffusion-3.5-large"
+    lora_file_path = "./lora_file.pth"
+
+    lora_client = LoRAInferenceWrapper(model_id, lora_file_path)
+
+    prompt = "A futuristic city skyline with neon lights."
+    try:
+        result = lora_client.generate_with_lora(prompt)
+        print("Generated image result:", result)
+    except Exception as e:
+        print("Error:", str(e))