from youtube_transcript_api import YouTubeTranscriptApi
from pydantic import BaseModel, Field
from typing import List, Generator, Iterable
import instructor
import openai

client = instructor.patch(openai.OpenAI())


def extract_video_id(url: str) -> str | None:
    import re

    match = re.search(r"v=([a-zA-Z0-9_-]+)", url)
    if match:
        return match.group(1)


class TranscriptSegment(BaseModel):
    source_id: int
    start: float
    text: str


def get_transcript_with_timing(
    video_id: str,
) -> Generator[TranscriptSegment, None, None]:
    """
    Fetches the transcript of a YouTube video along with the start and end times for each text segment,
    and returns them as a list of Pydantic models.

    Parameters:
    - video_id (str): The YouTube video ID for which the transcript is to be fetched.

    Returns:
    - A generator that yields TranscriptSegment models, each containing 'index', 'start', and 'text' keys.
    """
    transcript = YouTubeTranscriptApi.get_transcript(video_id)
    for ii, segment in enumerate(transcript):
        yield TranscriptSegment(
            source_id=ii, start=segment["start"], text=segment["text"]
        )


class YoutubeClip(BaseModel):
    title: str = Field(
        description="Specific and informative title for the individual clip."
    )
    description: str = Field(
        description="A detailed description of the clip, including any notable quotes or phrases. should be a summary of sorts."
    )
    start: float
    end: float
    source_ids: List[int] = Field(exclude=True)


class YoutubeClips(BaseModel):
    clips: List[YoutubeClip]


def yield_clips(segments: Iterable[TranscriptSegment]) -> Iterable[YoutubeClips]:
    """
    Extracts a list of YouTube clips from a list of transcript segments.

    Parameters:
    - segments (Iterable[TranscriptSegment]): A list of TranscriptSegment models, each containing 'index', 'start', and 'text' keys.

    Returns:
    - A generator that yields YoutubeClipw models, each containing 'title', 'description', 'start', 'end', and 'source_ids' keys.
    """

    return client.chat.completions.create(
        model="gpt-4-turbo-preview",
        stream=True,
        messages=[
            {
                "role": "system",
                "content": "You are given a sequence of YouTube transcripts and your job is to return notable clips that can be recut as smaller videos. give very specific titles and descriptions. Make sure the length of clips is proportional to the length of the video. Note that this is a transcript and so there might be spelling errors. Note that and correct any spellings. Use the context to make sure you're spelling things correctly. ",
            },
            {
                "role": "user",
                "content": f"Let's use the following transcript segments.\n{segments}",
            },
        ],
        response_model=instructor.Partial[YoutubeClips],
        validation_context={"segments": segments},
    )  # type: ignore


# Example usage
if __name__ == "__main__":
    from rich.table import Table
    from rich.console import Console
    from rich.prompt import Prompt

    console = Console()
    url = Prompt.ask("Enter a YouTube URL")

    with console.status("[bold green]Processing YouTube URL...") as status:
        video_id = extract_video_id(url)

        if video_id is None:
            raise ValueError("Invalid YouTube video URL")

        transcript = list(get_transcript_with_timing(video_id))
        status.update("[bold green]Generating clips...")

        for clip in yield_clips(transcript):
            console.clear()

            table = Table(title="YouTube Clips", padding=(0, 1))

            table.add_column("Title", style="cyan")
            table.add_column("Description", style="magenta")
            table.add_column("Start", justify="right", style="green")
            table.add_column("End", justify="right", style="green")
            for youtube_clip in clip.clips or []:
                table.add_row(
                    youtube_clip.title,
                    youtube_clip.description,
                    str(youtube_clip.start),
                    str(youtube_clip.end),
                )
            console.print(table)
