Update app.py

app.py

@@ -53,31 +53,25 @@ def get_predictions(audio_input):
 
 ###
 
-# Define the image generation function using the Stable Diffusion API
-url = "https://stablediffusionapi.com/api/v3/text2img"
-title = "<h2><center>Text to Image Generation with Stable Diffusion API</center></h2>"
-description = "Get the API key by signing up here [Stable Diffusion API](https://stablediffusionapi.com)."
-
-def get_image(key, prompt, inference_steps, filter):
-    payload = {
-        "key": key,
-        "prompt": prompt,
-        "negative_prompt": "((out of frame)), ((extra fingers)), mutated hands, ((poorly drawn hands)), ((poorly drawn face)), (((mutation))), (((deformed))), (((tiling))), ((naked)), ((tile)), ((fleshpile)), ((ugly)), (((abstract))), blurry, ((bad anatomy)), ((bad proportions)), ((extra limbs)), cloned face, (((skinny))), glitchy, ((extra breasts)), ((double torso)), ((extra arms)), ((extra hands)), ((mangled fingers)), ((missing breasts)), (missing lips), ((ugly face)), ((fat)), ((extra legs)), anime",
-        "width": "512",
-        "height": "512",
-        "samples": "1",
-        "num_inference_steps": inference_steps,
-        "safety_checker": filter,
-        "enhance_prompt": "yes",
-        "guidance_scale": 7.5
-    }
-    headers = {}
-    response = requests.request("POST", url, headers=headers, data=payload)
-    url1 = str(json.loads(response.text)['output'][0])
-    r = requests.get(url1)
-    i = Image.open(BytesIO(r.content))
-    return i
-    
+# Define a function to generate an image using DeepAI Text to Image API
+def generate_image(api_key, text):
+    url = "https://api.deepai.org/api/text2img"
+    headers = {'api-key': api_key}
+    response = requests.post(
+        url,
+        data={
+            'text': text,
+        },
+        headers=headers
+    )
+    response_data = response.json()
+    if 'output_url' in response_data:
+        image_url = response_data['output_url']
+        image_response = requests.get(image_url)
+        image = Image.open(BytesIO(image_response.content))
+        return image
+    else:
+        return None
 ####
     
 # Create the Gradio interface
@@ -88,7 +82,7 @@ with gr.Blocks() as interface:
             with gr.Row():
                 input_audio = gr.Audio(label="Input Audio", type="filepath")
                 submit_button = gr.Button("Submit")
-            output_label = gr.Label("Prediction")  # Use a single Label instead of a list
+            output_label = [gr.Label("Prediction"), gr.Image(type='pil')]  # Use a single Label instead of a list
 
     # Set the function to be called when the button is clicked
     submit_button.click(get_predictions, inputs=input_audio, outputs=output_label)