Atmosphere89/PromptAligner

1# ===========================2# app.py — PromptAligner main interface3# ===========================4 5import gradio as gr6from evaluator import compute_harmony_index7from feedback_module import calc_cds8from rewriter import refine_prompt9 10 11def generate_image(prompt):12    """13    Placeholder for image generation call.14    You can later connect this to Stable Diffusion, SDXL, or any other model.15    """16    return f"Generated image based on prompt: {prompt}"17 18 19def main_interface(prompt, feedback=None):20    """21    Main loop connecting the evaluator, feedback analyzer, and rewriter.22    """23    # Placeholder values for Harmony Index calculation24    v_c, v_a, v_s = 0.8, 0.7, 0.925    harmony = compute_harmony_index(v_c, v_a, v_s)26    result_text = f"Harmony Index: {harmony:.3f}"27 28    # Optional feedback scoring29    if feedback:30        caption = "Placeholder image description"31        cds = calc_cds(prompt, feedback, caption)32        result_text += f" | Consistency Deviation Score: {cds:.3f}"33 34    # Prompt refinement step35    improved_prompt = refine_prompt(prompt)36    return result_text, improved_prompt37 38 39# Create a simple Gradio UI40iface = gr.Interface(41    fn=main_interface,42    inputs=[43        gr.Textbox(label="Prompt", placeholder="Describe the image you want to generate"),44        gr.Textbox(label="Feedback (optional)", placeholder="Enter feedback or improvement request")45    ],46    outputs=[47        gr.Textbox(label="Evaluation"),48        gr.Textbox(label="Refined Prompt")49    ],50    title="PromptAligner Prototype",51    description="Adaptive prompt refinement with feedback-based evaluation"52)53 54if __name__ == "__main__":55    # Hugging Faceで公開用に share=True を指定56    iface.launch(share=True)