Create app.py

app.py

@@ -0,0 +1,54 @@
+import gradio as gr
+import requests
+import base64
+from PIL import Image
+from io import BytesIO
+
+def call_api(negative_prompt, positive_prompt, api_key):
+    # API URL
+    url = "https://model-5qe9kjp3.api.baseten.co/development/predict"
+    
+    # Headers including the provided API Key
+    headers = {"Authorization": f"Api-Key {api_key}"}
+    
+    # JSON payload with the prompts
+    payload = {
+        'workflow_values': {
+            'negative_prompt': negative_prompt,
+            'positive_prompt': positive_prompt
+        }
+    }
+    
+    # POST request to the API
+    response = requests.post(url, headers=headers, json=payload)
+    
+    # Check if the request was successful
+    if response.status_code == 200:
+        data = response.json()['result'][0]['data']
+        format = response.json()['result'][0]['format']
+        
+        # Decode the base64 string to bytes
+        image_data = base64.b64decode(data)
+        
+        # Convert bytes data to an image
+        image = Image.open(BytesIO(image_data))
+        
+        return image
+    else:
+        return "Failed to fetch the image. Please check the API key and inputs."
+
+# Define Gradio interface
+interface = gr.Interface(
+    fn=call_api,
+    inputs=[
+        gr.Textbox(label="Negative Prompt", placeholder="Enter negative prompt here..."),
+        gr.Textbox(label="Positive Prompt", placeholder="Enter positive prompt here..."),
+        gr.Textbox(label="API Key", placeholder="Enter your API key here..."),
+    ],
+    outputs="image",
+    title="Image Generation API Interface",
+    description="Enter the negative and positive prompts to generate an image."
+)
+
+# Launch the interface
+interface.launch()