open-notebook/open_notebook/plugins/podcasts.py
2024-11-08 18:29:51 -03:00

392 lines
9.9 KiB
Python

from typing import ClassVar, List, Optional
from loguru import logger
from podcastfy.client import generate_podcast
from pydantic import Field, field_validator
from open_notebook.config import DATA_FOLDER
from open_notebook.domain.notebook import ObjectModel
class PodcastEpisode(ObjectModel):
table_name: ClassVar[str] = "podcast_episode"
name: str
template: str
instructions: str
text: str
audio_file: str
class PodcastConfig(ObjectModel):
table_name: ClassVar[str] = "podcast_config"
name: str
podcast_name: str
podcast_tagline: str
output_language: str = Field(default="English")
person1_role: str
person2_role: str
conversation_style: List[str]
engagement_technique: List[str]
dialogue_structure: List[str]
transcript_model: Optional[str] = None
transcript_model_provider: Optional[str] = None
user_instructions: Optional[str] = None
ending_message: Optional[str] = None
wordcount: int = Field(ge=400, le=10000)
creativity: float = Field(ge=0, le=1)
provider: str = Field(default="openai")
voice1: Optional[str] = None
voice2: Optional[str] = None
model: str
def generate_episode(self, episode_name, text, instructions=None):
self.user_instructions = (
instructions if instructions else self.user_instructions
)
conversation_config = {
"word_count": self.wordcount,
"conversation_style": self.conversation_style,
"roles_person1": self.person1_role,
"roles_person2": self.person2_role,
"dialogue_structure": self.dialogue_structure,
"podcast_name": self.podcast_name,
"podcast_tagline": self.podcast_tagline,
"output_language": self.output_language,
"user_instructions": self.user_instructions,
"engagement_techniques": self.engagement_technique,
"creativity": self.creativity,
"text_to_speech": {
"output_directories": {
"transcripts": f"{DATA_FOLDER}/podcasts/transcripts",
"audio": f"{DATA_FOLDER}/podcasts/audio",
},
"temp_audio_dir": f"{DATA_FOLDER}/podcasts/audio/tmp",
"ending_message": "Thank you for listening to this episode. Don't forget to subscribe to our podcast for more interesting conversations.",
"default_tts_model": self.provider,
self.provider: {
"default_voices": {
"question": self.voice1,
"answer": self.voice2,
},
"model": self.model,
},
"audio_format": "mp3",
},
}
logger.debug(
f"Generating episode {episode_name} with config {conversation_config}"
)
api_key_label = None
llm_model_name = None
if self.transcript_model_provider:
if self.transcript_model_provider == "openai":
api_key_label = "OPENAI_API_KEY"
llm_model_name = self.transcript_model
elif self.transcript_model_provider == "anthropic":
api_key_label = "ANTHROPIC_API_KEY"
llm_model_name = self.transcript_model
elif self.transcript_model_provider == "gemini":
api_key_label = "GEMINI_API_KEY"
llm_model_name = self.transcript_model
audio_file = generate_podcast(
conversation_config=conversation_config,
text=text,
tts_model=self.provider,
llm_model_name=llm_model_name,
api_key_label=api_key_label,
)
episode = PodcastEpisode(
name=episode_name,
template=self.name,
instructions=instructions,
text=str(text),
audio_file=audio_file,
)
episode.save()
@field_validator(
"name", "podcast_name", "podcast_tagline", "output_language", "model"
)
@classmethod
def validate_required_strings(cls, value: str, field) -> str:
if value is None or value.strip() == "":
raise ValueError(f"{field.field_name} cannot be None or empty string")
return value.strip()
@field_validator("wordcount")
def validate_wordcount(cls, value):
if not 400 <= value <= 6000:
raise ValueError("Wordcount must be between 400 and 10000")
return value
@field_validator("creativity")
def validate_creativity(cls, value):
if not 0 <= value <= 1:
raise ValueError("Creativity must be between 0 and 1")
return value
conversation_styles = [
"Analytical",
"Argumentative",
"Informative",
"Humorous",
"Casual",
"Formal",
"Inspirational",
"Debate-style",
"Interview-style",
"Storytelling",
"Reflective",
"Narrative",
"Satirical",
"Educational",
"Conversational",
"Critical",
"Empathetic",
"Philosophical",
"Speculative",
"Motivational",
"Fun",
"Technical",
"Light-hearted",
"Serious",
"Investigative",
"Debunking",
"Collaborative",
"Didactic",
"Thought-provoking",
"Controversial",
"Skeptical",
"Optimistic",
"Pessimistic",
"Objective",
"Subjective",
"Sarcastic",
"Emotional",
"Exploratory",
"Friendly",
"Fast-paced",
"Slow-paced",
"Introspective",
"Open-ended",
"Affirmative",
"Dissenting",
]
# Dialogue Structures
dialogue_structures = [
"Topic Introduction",
"Opening Monologue",
"Guest Introduction",
"Icebreakers",
"Historical Context",
"Defining Terms",
"Problem Statement",
"Overview of the Issue",
"Deep Dive into Subtopics",
"Pro Arguments",
"Con Arguments",
"Cross-examination",
"Rebuttal",
"Expert Interviews",
"Panel Discussion",
"Case Studies",
"Myth Busting",
"Debunking Misconceptions",
"Audience Questions",
"Q&A Session",
"Listener Feedback",
"Rapid-fire Questions",
"Summary of Key Points",
"Recap",
"Key Takeaways",
"Actionable Tips",
"Call to Action",
"Future Outlook",
"Teaser for Next Episode",
"Closing Remarks",
"Thank You and Credits",
"Outtakes or Bloopers",
"Sponsor Messages",
"Social Media Shout-outs",
"Resource Recommendations",
"Feedback Request",
"Lightning Round",
"Behind-the-Scenes Insights",
"Ethical Considerations",
"Fact-checking Segment",
"Trending Topics",
"Closing Inspirational Quote",
"Final Reflections",
"Debrief",
"Farewell Messages",
"Next Episode Preview",
"Live Reactions",
"Call-in Segment",
"Acknowledgements",
"Transition Segments",
"Break Segments",
]
# Podcast Participant Roles
participant_roles = [
"Main Summarizer",
"Questioner/Clarifier",
"Optimist",
"Skeptic",
"Specialist",
"Thesis Presenter",
"Counterargument Provider",
"Professor",
"Student",
"Moderator",
"Host",
"Co-host",
"Expert Guest",
"Novice",
"Devil's Advocate",
"Analyst",
"Storyteller",
"Fact-checker",
"Comedian",
"Interviewer",
"Interviewee",
"Historian",
"Visionary",
"Strategist",
"Critic",
"Enthusiast",
"Mediator",
"Commentator",
"Researcher",
"Reporter",
"Advocate",
"Influencer",
"Observer",
"Listener",
"Facilitator",
"Innovator",
"Debater",
"Educator",
"Motivator",
"Narrator",
"Explorer",
"Opponent",
"Proponent",
"Philosopher",
"Engineer",
"Doctor",
"Psychologist",
"Economist",
"Politician",
"Scientist",
"Entrepreneur",
"Artist",
"Author",
"Journalist",
"Activist",
"Challenger",
"Supporter",
"Mentor",
"Mentee",
"Panelist",
"Audience Representative",
"Case Study Presenter",
"Data Analyst",
"Ethicist",
"Cultural Critic",
"Technologist",
"Environmentalist",
"Legal Expert",
"Healthcare Professional",
"Financial Advisor",
"Policy Maker",
"Sociologist",
"Anthropologist",
"Myth Buster",
"Trend Analyst",
"Futurist",
"Negotiator",
"Community Leader",
"Voice of Reason",
"Conflict Resolver",
"Emotional Support",
"Pragmatist",
"Idealist",
"Realist",
"Satirist",
"Story Analyst",
"Language Expert",
"Historical Witness",
"Survivor",
"Inspirational Figure",
"Cultural Ambassador",
"Digital Nomad",
"Remote Correspondent",
"Field Reporter",
"Data Scientist",
"Gamer",
"Musician",
"Filmmaker",
]
# Engagement Techniques
engagement_techniques = [
"Rhetorical Questions",
"Anecdotes",
"Analogies",
"Humor",
"Metaphors",
"Storytelling",
"Quizzes",
"Polls",
"Contests/Giveaways",
"Guest Appearances",
"Sound Effects",
"Music Interludes",
"Shout-outs",
"Interactive Challenges",
"Personal Testimonials",
"Quotes",
"Jokes",
"Surprise Elements",
"Emotional Appeals",
"Provocative Statements",
"Irony",
"Sarcasm",
"Alliteration",
"Repetition",
"Foreshadowing",
"Cliffhangers",
"Audience Participation",
"Sensory Descriptions",
"Visual Aids (if applicable)",
"Callbacks to Earlier Points",
"Pop Culture References",
"Hyperbole",
"Parables",
"Thought Experiments",
"Puzzles and Riddles",
"Role-playing",
"Mock Scenarios",
"Debates",
"Sound Bites",
"Catchphrases",
"Voice Modulation",
"Interactive Games",
"Live Demos",
"Behind-the-Scenes Insights",
"Vivid Imagery",
"Statistics and Facts",
"Open-ended Questions",
"Challenges to Assumptions",
"Evoking Curiosity",
"Memes (if visual components are included)",
"Surveys",
"Testimonials",
"Provocations",
]