import gradio as gr
import huggingface_hub as hfh
from requests.exceptions import HTTPError

# =====================================================================================================================
# DATA
# =====================================================================================================================
# Dict with the tasks considered in this spaces, {pretty name: space tag}
TASK_TYPES = {
    "✍️ Text Generation": "txtgen",
    "🤏 Summarization": "summ",
    "🫂 Translation": "trans",
    "💬 Conversational / Chatbot": "chat",
    "🤷 Text Question Answering": "txtqa",
    "🕵️ (Table/Document/Visual) Question Answering": "otherqa",
    "🎤 Automatic Speech Recognition": "asr",
    "🌇 Image to Text": "img2txt",
}

# Dict matching all task types with their possible hub tags, {space tag: (possible hub tags)}
HUB_TAGS = {
    "txtgen": ("text-generation", "text2text-generation"),
    "summ": ("summarization", "text-generation", "text2text-generation"),
    "trans": ("translation", "text-generation", "text2text-generation"),
    "chat": ("conversational", "text-generation", "text2text-generation"),
    "txtqa": ("text-generation", "text2text-generation"),
    "otherqa": ("table-question-answering", "document-question-answering", "visual-question-answering"),
    "asr": ("automatic-speech-recognition"),
    "img2txt": ("image-to-text"),
}
assert len(TASK_TYPES) == len(TASK_TYPES)
assert all(tag in HUB_TAGS for tag in TASK_TYPES.values())

# Dict with the problems considered in this spaces, {problem: space tag}
PROBLEMS = {
    "I would like a ChatGPT-like model": "chatgpt",
    "I want to improve the overall quality of the output": "quality",
    "Speed! Make it faster 🚀": "faster",
    "I would like to reduce model hallucinations": "hallucinations",
    "I want to control the length of the output": "length",
    "The model is returning nothing / random words 🤔": "random",
    "Other": "other",
}

# =====================================================================================================================


# =====================================================================================================================
# SUGGESTIONS LOGIC
# =====================================================================================================================
def is_valid_task_for_model(model_name, task_type):
    if model_name == "":
        return True
    try:
        model_tags = hfh.HfApi().model_info(model_name).tags
    except HTTPError:
        return True  # Assume everything is okay

    possible_tags = HUB_TAGS[TASK_TYPES[task_type]]
    return any(tag in model_tags for tag in possible_tags)


def get_suggestions(task_type, model_name, problem_type):
    if task_type == "" or problem_type == "":
        return "👈 Please select a task type and a problem type."
    return ""
# =====================================================================================================================


# =====================================================================================================================
# GRADIO
# =====================================================================================================================
demo = gr.Blocks()
with demo:
    gr.Markdown(
        """
        # 🚀💬 Improving Text Generation 💬🚀

        This is a ever-evolving guide on how to improve your text generation results. It is community-led and
        curated by Hugging Face 🤗

        How to use it:
        1. Answer the questions using the dropdown menus
        2. Click on "Get Suggestions" button
        3. Explore the suggestions 🤗
        """
    )

    with gr.Row():
        with gr.Column():
            task_type = gr.Dropdown(
                label="What is the task you're trying to accomplish?",
                choices=list(TASK_TYPES.keys()),
                interactive=True,
            )
            model_name = gr.Textbox(
                label="Which model are you using? (leave blank if you haven't decided)",
                placeholder="e.g. google/flan-t5-xl",
                interactive=True,
            )
            problem_type = gr.Dropdown(
                label="What would you like to improve?",
                choices=list(PROBLEMS.keys()),
                interactive=True,
            )
            button = gr.Button(value="Get Suggestions!")
        with gr.Column(scale=2):
            suggestions = gr.Markdown(value="")

    button.click(get_suggestions, inputs=[task_type, model_name, problem_type], outputs=suggestions)


# =====================================================================================================================

if __name__ == "__main__":
    demo.launch()