import gradio as gr
import requests
import huggingface_hub

# Initialize the client, pointing it to one of the available models
client = huggingface_hub.InferenceClient(model="mistralai/Mixtral-8x7B-Instruct-v0.1")


PROMPT = """
Write a short, imperative description of the provided app's purpose. It MUST ALWAYS be under 80 characters and a single-sentence. You can mention some technology names that you extract from the source code.

Example descriptions: "Remove background from images.", "Generate captions for images using ViT and GPT2.", "Predict the nutritional value of food based on an image of the food."

The provided app.py file:
"""


def generate(spaces):
    output = ""
    space_ids = [
        str.removeprefix("https://huggingface.co/spaces/")
        for str in spaces.split()
        if len(str) > 0
    ]
    print(space_ids)
    for space_id in space_ids:
        # TODO(support non-app.py Spaces)
        app_py = requests.get(
            url=f"https://huggingface.co/spaces/{space_id}/resolve/main/app.py"
        ).text

        input = PROMPT + f"```py{app_py}```"

        chat_completion = client.chat_completion(
            messages=[
                {"role": "user", "content": input},
            ],
            max_tokens=500,
        )
        output += chat_completion.choices[0].message.content + "\n"
        yield output


iface = gr.Interface(
    description="""
    ## Generate description for a space using a LLM

    Uses mixtral, feel free to duplicate to tweak stuff.
    """,
    fn=generate,
    inputs=gr.Textbox(
        label="list of Spaces to generate a description for",
        value="""
https://huggingface.co/spaces/julien-c/coqui
https://huggingface.co/spaces/TTS-AGI/TTS-Arena
https://huggingface.co/spaces/playgroundai/playground-v2.5
https://huggingface.co/spaces/amirgame197/Remove-Video-Background
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
        """.strip(),
    ),
    outputs=gr.Textbox(label="descriptions", lines=4),
)
iface.launch()