app.py

from gradio import Interface, Text, Markdown, Dropdown

def compare(prompt, model1="biogpt", model2="gemma_2b_en"):
  """
  Fetches outputs from BioGPT and Gemma for a given prompt and model selection.

  Args:
      prompt: User-defined prompt for text generation.
      model1: Name of the first model (default: biogpt).
      model2: Name of the second model (default: gemma_2b_en).

  Returns:
      A list containing BioGPT and Gemma outputs as strings.
  """
  # Replace these with actual BioGPT and Gemma inference code
  biogpt_output = f"BioGPT Output for '{prompt}'"  # Placeholder output
  gemma_output = f"Gemma Output for '{prompt}'"  # Placeholder output
  return [biogpt_output, gemma_output]

# Interface definition
interface = Interface(
  fn=compare,
  inputs=[
    Text(label="Enter Prompt:", placeholder="Write your prompt here..."),
    # Dropdown for model selection (modify options as needed)
    Dropdown(choices=["biogpt", "gpt2", "bart"], value="biogpt", label="Model 1"),
    Dropdown(choices=["gemma_2b_en", "gemma_1b_en"], value="gemma_2b_en", label="Model 2"),
  ],
  outputs=Text(label="Outputs"),
  description=Markdown("""
  This Gradio app allows you to compare text generation outputs from two different large language models (LLMs) on the same prompt. 

  * Enter a prompt in the text box.
  * Select the desired models from the dropdown menus. BioGPT and Gemma are currently supported.
  * Click "Run" to generate outputs from both models.

  **Note:** This is a demonstration, actual model inference needs to be implemented.
  """),
)


# Launch the Gradio app
interface.launch(share=True)  # Set share=True to host on Hugging Face Hub