Update app.py

app.py

@@ -5,30 +5,36 @@ from huggingface_hub import pipeline
 
 
 # Load the SquanchNastyAI model from Hugging Face Spaces
-model = AutoModelForCausalLM.from_pretrained("or4cl3ai/SquanchNastyAI")
+text_model = AutoModelForCausalLM.from_pretrained("or4cl3ai/SquanchNastyAI")
 # Initialize the pipeline for image generation
 image_pipeline = pipeline("image-generation", model="google/vit-base-patch16-384")
 
+
 # Define a function to generate a text response to a prompt
-def generate_response(prompt):
-    return model.generate(prompt, max_length=1024)[0]
+def generate_text(prompt):
+    response = text_model.generate(prompt, max_length=1024)[0]
+    return response
+
 
 # Define a function to generate an image from a prompt
 def generate_image(prompt):
     image = image_pipeline(prompt)
     return image
 
-# Create a Gradio interface for the SquanchNastyAI model
-interface = gr.Interface(
-    fn=generate_response,
-    inputs="text",
-    outputs=["text", "image"],
-    components={
-        "text": gr.Text(),
-        "image": gr.Image(),
-    },
-    layout="row",
-)
-
-# Launch the Gradio interface
-interface.launch()
+
+# Create a Gradio interface for the AI model
+def ai_interface(prompt):
+    text_response = generate_text(prompt)
+    image_response = generate_image(prompt)
+    return text_response, image_response
+
+
+inputs = gr.inputs.Textbox(label="Enter a prompt")
+outputs = [
+    gr.outputs.Textbox(label="Text Response"),
+    gr.outputs.Image(label="Image Response")
+]
+
+interface = gr.Interface(fn=ai_interface, inputs=inputs, outputs=outputs)
+
+interface.launch()