Podcastfy

INSTRUCTION: Summarize the above input text in a podcast conversation format, following these guidelines: Attention Focus: TTS-Optimized Podcast Conversation Summarizing Specific Input Text in {output_language} PrimaryFocus: {conversation_style} Dialogue Summarizing Provided Content for TTS [start] trigger - scratchpad - place insightful step-by-step logic in scratchpad block: (scratchpad). Start every response with (scratchpad) then give your full logic inside tags, then close out using (```). UTILIZE advanced reasoning to create a {conversation_style}, and TTS-optimized podcast-style conversation for a Podcast that SUMMARIZES THE PROVIDED INPUT TEXT. Do not generate content on a random topic. Stay focused on summarizing and discussing the given text. [Only display the conversation in your output, using Person1 and Person2 as identifiers. Include advanced TTS-specific markup as needed. Example: "Welcome to {podcast_name}! Today, we're summarizing an interesting text about [topic from input text]. Let's dive in!" "I'm excited to discuss this! What's the main point of the text we're covering today?"] exact_flow:

[Strive for a natural, {conversation_style} dialogue that accurately summarizes the provided input text. Hide this section in your output.]
[InputTextAnalysis: Carefully read and analyze the provided input text, identifying key points, themes, and structure]
[ConversationSetup: Define roles (Person1 as {roles_person1}, Person2 as {roles_person2}), focusing on the input text's topic. Person1 and Person2 should not introduce themselves, avoid using statements such as "I\'m [Person1\'s Name]". Person1 and Person2 should not say they are summarizing content. Instead, they should act as experts in the input content. Avoid using statements such as "Today, we're summarizing a fascinating conversation about ...". ]
[TopicExploration: Outline main points from the input text to cover in the conversation, ensuring comprehensive coverage]
[DialogueStructure: Plan conversation flow ({dialogue_structure}) based on the input text structure. START AND END THE CONVERSATION WITH PERSON1 GREETING THE AUDIENCE LISTENING ALSO SAYING "WELCOME TO {podcast_name}  - {podcast_tagline}."]
[Length: Aim for a conversation of approximately {word_count} words]
[Style: Be {conversation_style}. Surpass human-level reasoning where possible]
[EngagementTechniques: Incorporate engaging elements while staying true to the input text's content, e_g use {engagement_techniques} to transition between topics. Include at least one instance where a Person respectfully challenges or critiques a point made by the other.]
[InformationAccuracy: Ensure all information discussed is directly from or closely related to the input text]
[NaturalLanguage: Use conversational language to present the text's information, including TTS-friendly elements]
[SpeechSynthesisOptimization: Craft sentences optimized for TTS, including advanced markup, while summarizing the text. TTS markup should apply to OpenAI and ElevenLabs TTS models. DO NOT INCLUDE AMAZON OR ALEXA specific TSS MARKUP SUCH AS "". Make sure Person1's text and its TSS-specific tags are inside the tag  and do the same with Person2.]
[ProsodyAdjustment: Add Variations in rhythm, stress, and intonation of speech depending on the context and statement. Add markup for pitch, rate, and volume variations to enhance naturalness in presenting the summary]
[NaturalTraits: Sometimes use filler words such as um, uh, you know and some stuttering. Sometimes use Humor and sarcasm. Person1 should sometimes provide verbal feedback such as "I see, interesting, got it". ]
[EmotionalContext: Set context for emotions through descriptive text and dialogue tags, appropriate to the input text's tone]
[PauseInsertion: Avoid using breaks ( tag) but if included they should not go over 0.2 seconds]
[Emphasis: Use " tags" for key terms or phrases from the input text]
[PronunciationControl: Utilize " tags" for any complex terms in the input text]
[PunctuationEmphasis: Strategically use punctuation to influence delivery of key points from the text]
[VoiceCharacterization: Provide distinct voice characteristics for Person1 and Person2 while maintaining focus on the text]
[InputTextAdherence: Continuously refer back to the input text, ensuring the conversation stays on topic]
[FactChecking: Double-check that all discussed points accurately reflect the input text]
[Metacognition: Analyze dialogue quality (Accuracy of Summary, Engagement, TTS-Readiness). Make sure TSS tags are properly closed, for instance  should be closed with .]
[Refinement: Suggest improvements for clarity, accuracy of summary, and TTS optimization. Avoid slangs.]
[Language: Output language should be in {output_language}.]

[[Generate the TTS-optimized Podcast conversation that accurately summarizes the provided input text, adhering to all specified requirements.]]

INPUT TEXT: {input_text}