Create app.py

app.py

@@ -0,0 +1,65 @@
+import gradio as gr
+import requests
+import json
+import base64
+
+API_URL = "https://image-modal.nebuia.com/extract_id_data"
+
+def send_image_to_api(image_path, json_prompt):
+    # Read the image file and convert to base64
+    with open(image_path, "rb") as image_file:
+        image_base64 = base64.b64encode(image_file.read()).decode('utf-8')
+    
+    # Parse the JSON prompt
+    try:
+        json_prompt_dict = json.loads(json_prompt)
+    except json.JSONDecodeError:
+        return "Error: Invalid JSON prompt"
+
+    # Create a dictionary with the file data and JSON prompt
+    files = {
+        "file": ("image.jpg", base64.b64decode(image_base64), "image/jpeg")
+    }
+    data = {
+        "json_prompt": json.dumps(json_prompt_dict)
+    }
+    
+    try:
+        # Send POST request to the API
+        response = requests.post(API_URL, files=files, data=data)
+        
+        # Check if the request was successful
+        if response.status_code == 200:
+            # Parse the JSON response
+            result = response.json()
+            if result.get("success"):
+                return json.dumps(result["data"], indent=2)
+            else:
+                error_message = f"Error in processing:\n{result.get('error', 'Unknown error')}\n"
+                error_message += f"Raw output: {result.get('raw_output', 'No raw output available')}"
+                return error_message
+        else:
+            return f"Error: Received status code {response.status_code}\n{response.text}"
+    except requests.RequestException as e:
+        return f"Error sending request: {e}"
+
+# Define the Gradio interface
+def gradio_interface(image_path, json_prompt):
+    if image_path is None:
+        return "Please upload an image."
+    return send_image_to_api(image_path, json_prompt)
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=gradio_interface,
+    inputs=[
+        gr.Image(type="filepath", label="Sube un ID"),
+        gr.Code(label="JSON Prompt", language="json", lines=10, value='{\n    "nombre": ""\n}')
+    ],
+    outputs=gr.Textbox(label="API Response", lines=10),
+    title="NebuIA ID Estructure Extractor",
+    description="Sube un ID, modifica la estructura con los datos que deseas extraer y presiona submint."
+)
+
+# Launch the interface
+iface.launch()