Create app.py

app.py

@@ -0,0 +1,67 @@
+import gradio as gr
+import os
+from huggingface_hub import InferenceClient, login
+
+login(os.getenv("HUGGINGFACEHUB_API_TOKEN"))
+
+
+repo_id = "meta-llama/Meta-Llama-3-8B-Instruct"
+
+from huggingface_hub import InferenceClient
+
+
+
+def image_generator(text_input, style):
+
+  system_input = f"You are an expert prompt engineer with artistic flair. "
+  user_input = f"Write a concise prompt for a {style} image containing {text_input}. Only return the prompt."
+
+  messages = [
+      {"role": "system", "content": system_input},
+      {"role": "user", "content": user_input},
+  ]
+
+  client = InferenceClient( repo_id, ) 
+
+  chat_completion = client.chat_completion(
+    messages=messages,
+    max_tokens=500,
+    )
+  prompt = chat_completion.choices[0].message.content
+
+  client = InferenceClient()
+
+  image = client.text_to_image(
+      prompt=prompt,
+      model="stabilityai/stable-diffusion-xl-base-1.0",
+      guidance_scale=8,
+      seed=42,
+  )
+  return prompt, image
+
+
+
+with gr.Blocks() as demo:
+  with gr.Row():
+    with gr.Column():
+      input_text = gr.Textbox(label="Prompt")
+      style = gr.Radio(["fun", "interesting"])
+      prompt = gr.Textbox(interactive=False, visible=True, label="Refined prompt")
+      output_image = gr.Image(interactive=False, label="Result")
+
+      with gr.Row():
+        reset = gr.ClearButton([input_text])
+        submit = gr.Button("Submit")
+    with gr.Column():
+      submit.click(fn=image_generator, inputs=[input_text, style], outputs=[prompt, output_image])
+
+  examples = gr.Examples(
+      examples=[
+          ["a llama and a cookbook", "fun"],
+          ["a squirrel", "interesting"],
+      ],
+      inputs=[input_text, style]),
+
+
+if __name__ == "__main__":
+    demo.launch()