import os
import gradio as gr
from utils import get_model_summary, install_flash_attn#, authenticate_hf

# Install required package
install_flash_attn()

# Create the Gradio Blocks interface
with gr.Blocks(theme="sudeepshouche/minimalist") as demo:
    with gr.Row():
        with gr.Column():
            textbox = gr.Textbox(label="Model Name", placeholder="Enter the model name here OR select an example below...", lines=1)
            gr.Markdown("### Vision Models")
            vision_examples = gr.Examples(
                examples=[
                    ["google/paligemma-3b-mix-224"],
                    ["google/paligemma-3b-ft-refcoco-seg-224"],
                    ["llava-hf/llava-v1.6-mistral-7b-hf"],
                    ["xtuner/llava-phi-3-mini-hf"],
                    ["xtuner/llava-llama-3-8b-v1_1-transformers"],
                    ["vikhyatk/moondream2"],
                    ["openbmb/MiniCPM-Llama3-V-2_5"],
                    ["microsoft/Phi-3-vision-128k-instruct"],
                    ["HuggingFaceM4/idefics2-8b-chatty"],
                    ["microsoft/llava-med-v1.5-mistral-7b"]
                ],
                inputs=textbox
            )
            
            gr.Markdown("### Other Models")
            other_examples = gr.Examples(
                examples=[
                    ["NousResearch/Meta-Llama-3-8B-Instruct"],
                    ["dwb2023/llama38binstruct_summarize"],
                    ["dwb2023/llama38binstruct_summarize_v3"],
                    ["dwb2023/llama38binstruct_summarize_v4"],                    
                    ["dwb2023/mistral-7b-instruct-quantized"],
                    ["mistralai/Mistral-7B-Instruct-v0.2"],
                    ["mistralai/Mistral-7B-Instruct-v0.3"],
                    ["google/gemma-7b"],
                    ["microsoft/Phi-3-mini-4k-instruct"],
                    ["meta-llama/Meta-Llama-3-8B"]
                ],
                inputs=textbox
            )
            submit_button = gr.Button("Submit")

            gr.Markdown("""
            #### 🧠📖 Where to get started with Vision Language Models!!! 🔧🧩 
            
            - [Hugging Face overview of VLMs](https://huggingface.co/blog/vlms#overview-of-open-source-vision-language-models)
            - [Blog Post on PaliGemma Model Capabilities and Use Cases](https://huggingface.co/blog/paligemma#model-capabilities)
            
            Keep an eye on the evolution of the [Model Explorer from Google](https://ai.google.dev/edge/model-explorer#two_ways_to_use_model_explorer).  It didn't work initially for some of the VLM "fusion" model types I was initially looking at, but certainly a great tool for the right model.
            """)
            
        with gr.Column():
            output = gr.Textbox(label="Model Architecture", lines=20, placeholder="Model architecture will appear here...", show_copy_button=True)
            error_output = gr.Textbox(label="Error", lines=10, placeholder="Exceptions will appear here...", show_copy_button=True)

    def handle_click(model_name):
        model_summary, error_message = get_model_summary(model_name)
        return model_summary, error_message

    submit_button.click(fn=handle_click, inputs=textbox, outputs=[output, error_output])

# Launch the interface
demo.launch()