podcast-generation

name podcast-generation description Use this skill when the user requests to generate, create, or produce podcasts from text content. Converts written content into a two-host conversational podcast audio format with natural dialogue. Podcast Generation Skill Overview This skill generates high-quality podcast audio from text content. The workflow includes creating a structured JSON script (conversational dialogue) and executing audio generation through text-to-speech synthesis. Core Capabilities Convert any text content (articles, reports, documentation) into podcast scripts Generate natural two-host conversational dialogue (male and female hosts) Synthesize speech audio using text-to-speech Mix audio chunks into a final podcast MP3 file Support both English and Chinese content Workflow Step 1: Understand Requirements When a user requests podcast generation, identify: Source content: The text/article/report to convert into a podcast Language: English or Chinese (based on content) Output location: Where to save the generated podcast You don't need to check the folder under /mnt/user-data Step 2: Create Structured Script JSON Generate a structured JSON script file in /mnt/user-data/workspace/ with naming pattern: {descriptive-name}-script.json The JSON structure: { "locale" : "en" , "lines" : [ { "speaker" : "male" , "paragraph" : "dialogue text" } , { "speaker" : "female" , "paragraph" : "dialogue text" } ] } Step 3: Execute Generation Call the Python script: python /mnt/skills/public/podcast-generation/scripts/generate.py \ --script-file /mnt/user-data/workspace/script-file.json \ --output-file /mnt/user-data/outputs/generated-podcast.mp3 \ --transcript-file /mnt/user-data/outputs/generated-podcast-transcript.md Parameters: --script-file : Absolute path to JSON script file (required) --output-file : Absolute path to output MP3 file (required) --transcript-file : Absolute path to output transcript markdown file (optional, but recommended) [!IMPORTANT] Execute the script in one complete call. Do NOT split the workflow into separate steps. The script handles all TTS API calls and audio generation internally. Do NOT read the Python file, just call it with the parameters. Always include --transcript-file to generate a readable transcript for the user. The TTS provider and its concurrency are selected automatically from environment variables — you do not choose or tune them. Script JSON Format The script JSON file must follow this structure: { "title" : "The History of Artificial Intelligence" , "locale" : "en" , "lines" : [ { "speaker" : "male" , "paragraph" : "Hello Deer! Welcome back to another episode." } , { "speaker" : "female" , "paragraph" : "Hey everyone! Today we have an exciting topic to discuss." } , { "speaker" : "male" , "paragraph" : "That's right! We're going to talk about..." } ] } Fields: title : Title of the podcast episode (optional, used as heading in transcript) locale : Language code - "en" for English or "zh" for Chinese lines : Array of dialogue lines speaker : Either "male" or "female" paragraph : The dialogue text for this speaker Script Writing Guidelines When creating the script JSON, follow these guidelines: Format Requirements Only two hosts: male and female, alternating naturally Target runtime: approximately 10 minutes of dialogue (around 40-60 lines) Start with the male host saying a greeting that includes "Hello Deer" Tone & Style Natural, conversational dialogue - like two friends chatting Use casual expressions and conversational transitions Avoid overly formal language or academic tone Include reactions, follow-up questions, and natural interjections Content Guidelines Frequent back-and-forth between hosts Keep sentences short and easy to follow when spoken Plain text only - no markdown formatting in the output Translate technical concepts into accessible language No mathematical formulas, code, or complex notation Make content engaging and accessible for audio-only listeners Exclude meta information like dates, author names, or document structure Podcast Generation Example User request: "Generate a podcast about the history of artificial intelligence" Step 1: Create script file /mnt/user-data/workspace/ai-history-script.json : { "title" : "The History of Artificial Intelligence" , "locale" : "en" , "lines" : [ { "speaker" : "male" , "paragraph" : "Hello Deer! Welcome back to another fascinating episode. Today we're diving into something that's literally shaping our future - the history of artificial intelligence." } , { "speaker" : "female" , "paragraph" : "Oh, I love this topic! You know, AI feels so modern, but it actually has roots going back over seventy years." } , { "speaker" : "male" , "paragraph" : "Exactly! It all started back in the 1950s. The term artificial intelligence was actually coined by John McCarthy in 1956 at a famous conference at Dartmouth." } , { "speaker" : "female" , "paragraph" : "Wait, so they were already thinking about machines that could think back then? That's incredible!" } , { "speaker" : "male" , "paragraph" : "Right? The early pioneers were so optimistic. They thought we'd have human-level AI within a generation." } , { "speaker" : "female" , "paragraph" : "But things didn't quite work out that way, did they?" } , { "speaker" : "male" , "paragraph" : "No, not at all. The 1970s brought what's called the first AI winter..." } ] } Step 2: Execute generation: python /mnt/skills/public/podcast-generation/scripts/generate.py \ --script-file /mnt/user-data/workspace/ai-history-script.json \ --output-file /mnt/user-data/outputs/ai-history-podcast.mp3 \ --transcript-file /mnt/user-data/outputs/ai-history-transcript.md This will generate: ai-history-podcast.mp3 : The audio podcast file ai-history-transcript.md : A readable markdown transcript of the podcast Specific Templates Read the following template file only when matching the user request. Tech Explainer - For converting technical documentation and tutorials Output Format The generated podcast follows the "Hello Deer" format: Two hosts: one male, one female Natural conversational dialogue Starts with "Hello Deer" greeting Target duration: approximately 10 minutes Alternating speakers for engaging flow Output Handling After generation: Podcasts and transcripts are saved in /mnt/user-data/outputs/ Share both the podcast MP3 and transcript MD with user using present_files tool Provide brief description of the generation result (topic, duration, hosts) Offer to regenerate if adjustments needed Requirements The following environment variables must be set: For Volcengine: VOLCENGINE_TTS_APPID and VOLCENGINE_TTS_ACCESS_TOKEN For MiniMax: MINIMAX_API_KEY VOLCENGINE_TTS_CLUSTER : Volcengine TTS cluster (optional, defaults to "volcano_tts") VOLCENGINE_TTS_VOICE_TYPE_MALE : Volcengine male voice type (optional, defaults to zh_male_yangguangqingnian_moon_bigtts ) VOLCENGINE_TTS_VOICE_TYPE_FEMALE : Volcengine female voice type (optional, defaults to zh_female_sajiaonvyou_moon_bigtts ) Voice type overrides are trimmed; unset or blank values use the listed defaults. Notes Always execute the full pipeline in one call - no need to test individual steps or worry about timeouts The script JSON should match the content language (en or zh) Technical content should be simplified for audio accessibility in the script Complex notations (formulas, code) should be translated to plain language in the script Long content may result in longer podcasts Providers (Volcengine / MiniMax) Auto-selected by environment variables: VOLCENGINE_TTS_APPID + VOLCENGINE_TTS_ACCESS_TOKEN set → Volcengine TTS (default). Only MINIMAX_API_KEY set → MiniMax TTS ( /v1/t2a_v2 ). Force with PODCAST_GENERATION_PROVIDER=volcengine|minimax . MiniMax overrides: MINIMAX_API_HOST (default https://api.minimaxi.com ), MINIMAX_TTS_MODEL (default speech-2.6-hd ), MINIMAX_TTS_VOICE_MALE (default male-qn-qingse ), MINIMAX_TTS_VOICE_FEMALE (default female-tianmei ). Concurrency is owned by each provider internally — MiniMax runs single-threaded to reduce rate-limit failures, Volcengine uses 4 workers. There is no caller-facing concurrency knob; transient rate limits are handled by automatic retry with backoff.