Retrieves the transcript/subtitles for a specified YouTube video. Uses the YouTube Transcript API to fetch time-coded transcripts in the requested languages. The transcripts include timing information, text content, and duration for each segment....
Generates a concise summary of a YouTube video's content using Gemini AI. This tool first retrieves the video's transcript, then uses Google's Gemini 2.0 Flash model to create a structured summary of the key points discussed in the video. Args: video_id (str): The YouTube video ID to summarize Returns: List[Dict]: A list containing a single dictionary with: - type: "summary" - data: Dictionary containing video_id, summary text, and model used Raises: ToolError: When summarization fails (API key missing, transcript unavailable, etc.)
Answers natural language questions about a YouTube video's content. This tool leverages Google's Gemini 2.0 Flash model to provide responses to questions based solely on the video's transcript....
Searches YouTube for videos matching a specific query and returns detailed metadata. This tool performs a two-step API process: 1. First searches for videos matching the query 2....
Retrieves comments from a YouTube video using the YouTube Data API. This tool fetches top-level comments from a video's comment section, including author information, comment text, timestamps, and like counts. Args: video_id (str): The YouTube video ID to get comments from max_comments (int, optional): Maximum number of comments to retrieve....
Retrieves the current like count for a specified YouTube video. This tool accesses the YouTube Data API to fetch the most up-to-date engagement statistics for a video, specifically focusing on like count. Args: video_id (str): The YouTube video ID to get likes for Returns: List[Dict]: A list containing a single dictionary with: - type: "stats" - data: Dictionary containing video_id and likes count Raises: ToolError: When like count retrieval fails (API key missing, video unavailable, etc.)
