Added app.py

app.py

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+import banana_dev as banana
+import base64
+from io import BytesIO
+from PIL import Image
+import gradio as gr
+
+api_key = "1a3e1402-a0ce-4e5f-beb2-0437bc244f7b"
+model_key = "72127aef-ae0b-4a69-bee5-ed7ffda1ea04"
+
+model_inputs = {
+  "endpoint": "txt2img",
+  "params": {
+    "prompt": "",
+    "negative_prompt": "",
+    "steps": 25,
+    "sampler_name": "Euler a",
+    "cfg_scale": 7.5,
+    "seed": 42,
+    "batch_size": 1,
+    "n_iter": 1,
+    "width": 768,
+    "height": 768,
+    "tiling": False
+  }
+}
+
+def stable_diffusion_txt2img(prompt, api_key, model_key, model_inputs):
+  # Update the model_inputs with the provided prompt
+  model_inputs["params"]["prompt"] = prompt
+
+  # Run the model
+  out = banana.run(api_key, model_key, model_inputs)
+
+  # Process the output
+  image_byte_string = out["modelOutputs"][0]["images"]
+  image_encoded = image_byte_string[0].encode("utf-8")
+  image_bytes = BytesIO(base64.b64decode(image_encoded))
+  image = Image.open(image_bytes)
+  return image
+
+# Gradio Interface
+def generator(prompt):
+  generated_image = stable_diffusion_txt2img(prompt, api_key, model_key, model_inputs)
+  return generated_image
+
+iface = gr.Interface(fn=generator, inputs="text", outputs="image")
+iface.launch()

requirements.txt

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+banana_dev==4.0.2
+gradio==3.27.0
+Pillow==9.5.0
+Pillow==9.5.0