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# # kukubuddy_ai_light.py
# import random
# import gradio as gr
# from transformers import pipeline
# from TTS.api import TTS
# # Small & memory-efficient models
# summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")
# story_gen = pipeline("text2text-generation", model="google/flan-t5-small")
# tts = TTS(model_name="tts_models/en/ljspeech/tacotron2-DDC", progress_bar=False, gpu=False)
# # ---------- Feature 1: Daily Audio Digest ----------
# def generate_audio_digest(topic):
# dummy_text = f"This is a sample Kuku FM podcast about {topic}. " * 10
# summary = summarizer(dummy_text, max_length=300, min_length=30, do_sample=False)[0]["summary_text"]
# audio_path = "digest.wav"
# tts.tts_to_file(text=summary, file_path=audio_path)
# return summary, audio_path
# # ---------- Feature 2: Interactive Story Generator ----------
# story_cache = {}
# # More vivid genre-specific prompts
# genre_templates = {
# "fantasy": "In a land of dragons and forgotten magic, a tale begins. ",
# "sci-fi": "In a distant galaxy, governed by AI and cosmic laws, a new story unfolds. ",
# "thriller": "It started on a stormy night, when a single knock on the door changed everything. ",
# "romance": "They locked eyes for the first time in a quiet bookstore. ",
# "horror": "The clock struck midnight, and something moved in the shadows. ",
# "myth": "Long before time was time, gods and mortals shared the same sky. ",
# "comedy": "There was once a chicken who wanted to cross a space highway... "
# }
# # Random creative twist options
# twist_prompts = [
# "But little did they know, everything was about to change.",
# "Suddenly, a mysterious voice echoed in the air.",
# "Out of nowhere, a glowing symbol appeared.",
# "But fate had other plans.",
# "And just like that, the rules of the world shifted."
# ]
# def generate_story(genre, choice):
# genre = genre.lower()
# base_prompt = genre_templates.get(genre, f"Begin a story in the genre: {genre}. ")
# # If it's a new story
# if genre not in story_cache:
# story_cache[genre] = base_prompt
# # Add user decision and twist
# if choice:
# twist = random.choice(twist_prompts)
# story_cache[genre] += f"\nThe user chose: '{choice}'. {twist} "
# # Generate new content
# generated = story_gen(story_cache[genre])[0]['generated_text']
# # Update cache for continuity
# story_cache[genre] = generated
# # Audio output
# story_audio_path = "story.wav"
# tts.tts_to_file(text=generated, file_path=story_audio_path)
# return generated, story_audio_path
# # ---------- Gradio UI ----------
# digest_ui = gr.Interface(
# fn=generate_audio_digest,
# inputs=gr.Textbox(label="Enter your topic of interest", placeholder="e.g. motivation, productivity"),
# outputs=[gr.Text(label="Summary"), gr.Audio(label="Audio Digest", type="filepath")],
# title="🎧 KukuBuddy: Daily Audio Digest"
# )
# story_ui = gr.Interface(
# fn=generate_story,
# inputs=[
# gr.Textbox(label="Genre", placeholder="e.g. sci-fi, myth, thriller"),
# gr.Textbox(label="Your last choice", placeholder="e.g. Enter the castle")
# ],
# outputs=[gr.Text(label="Next Scene"), gr.Audio(label="Narration", type="filepath")],
# title="📖 KukuBuddy: Interactive Story"
# )
# app = gr.TabbedInterface([digest_ui, story_ui], tab_names=["📌 Daily Digest", "🧠 Interactive Story"])
# if __name__ == "__main__":
# app.launch()
# import random
# import gradio as gr
# from transformers import pipeline
# from TTS.api import TTS
# # Small & memory-efficient models
# summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")
# story_gen = pipeline("text2text-generation", model="google/flan-t5-small")
# tts = TTS(model_name="tts_models/en/ljspeech/tacotron2-DDC", progress_bar=False, gpu=False)
# # ---------- Feature 1: Daily Audio Digest ----------
# def generate_audio_digest(topic):
# dummy_text = f"This is a sample Kuku FM podcast about {topic}. " * 10
# summary = summarizer(dummy_text, max_length=300, min_length=30, do_sample=False)[0]["summary_text"]
# audio_path = "digest.wav"
# tts.tts_to_file(text=summary, file_path=audio_path)
# return summary, audio_path, audio_path # return twice for play and download
# # ---------- Feature 2: Interactive Story Generator ----------
# story_cache = {}
# # More vivid genre-specific prompts
# genre_templates = {
# "fantasy": "In a land of dragons and forgotten magic, a tale begins. ",
# "sci-fi": "In a distant galaxy, governed by AI and cosmic laws, a new story unfolds. ",
# "thriller": "It started on a stormy night, when a single knock on the door changed everything. ",
# "romance": "They locked eyes for the first time in a quiet bookstore. ",
# "horror": "The clock struck midnight, and something moved in the shadows. ",
# "myth": "Long before time was time, gods and mortals shared the same sky. ",
# "comedy": "There was once a chicken who wanted to cross a space highway... "
# }
# # Random creative twist options
# twist_prompts = [
# "But little did they know, everything was about to change.",
# "Suddenly, a mysterious voice echoed in the air.",
# "Out of nowhere, a glowing symbol appeared.",
# "But fate had other plans.",
# "And just like that, the rules of the world shifted."
# ]
# def generate_story(genre, choice):
# genre = genre.lower()
# base_prompt = genre_templates.get(genre, f"Begin a story in the genre: {genre}. ")
# # If it's a new story
# if genre not in story_cache:
# story_cache[genre] = base_prompt
# # Add user decision and twist
# if choice:
# twist = random.choice(twist_prompts)
# story_cache[genre] += f"\nThe user chose: '{choice}'. {twist} "
# # Generate new content
# generated = story_gen(story_cache[genre])[0]['generated_text']
# # Update cache for continuity
# story_cache[genre] = generated
# # Audio output
# story_audio_path = "story.wav"
# tts.tts_to_file(text=generated, file_path=story_audio_path)
# return generated, story_audio_path, story_audio_path # return twice for play and download
# # ---------- Gradio UI ----------
# digest_ui = gr.Interface(
# fn=generate_audio_digest,
# inputs=gr.Textbox(label="Enter your topic of interest", placeholder="e.g. motivation, productivity"),
# outputs=[
# gr.Text(label="Summary"),
# gr.Audio(label="🔊 Audio Digest", type="filepath"),
# gr.File(label="⬇️ Download Audio File")
# ],
# title="🎧 KukuBuddy: Daily Audio Digest"
# )
# story_ui = gr.Interface(
# fn=generate_story,
# inputs=[
# gr.Textbox(label="Genre", placeholder="e.g. sci-fi, myth, thriller"),
# gr.Textbox(label="Your last choice", placeholder="e.g. Enter the castle")
# ],
# outputs=[
# gr.Text(label="📖 Next Scene"),
# gr.Audio(label="🔊 Narration", type="filepath"),
# gr.File(label="⬇️ Download Narration")
# ],
# title="📖 KukuBuddy: Interactive Story"
# )
# app = gr.TabbedInterface(
# [digest_ui, story_ui],
# tab_names=["📌 Daily Digest", "🧠 Interactive Story"]
# )
# if __name__ == "__main__":
# app.launch()
# kukubuddy_ai_light.py
# import random
# import gradio as gr
# from transformers import pipeline
# from TTS.api import TTS
# # Small & memory-efficient models
# summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")
# story_gen = pipeline("text2text-generation", model="google/flan-t5-small")
# tts = TTS(model_name="tts_models/en/ljspeech/tacotron2-DDC", progress_bar=False, gpu=False)
# # ---------- Feature 1: Daily Audio Digest ----------
# def generate_audio_digest(topic):
# dummy_text = f"This is a sample Kuku FM podcast about {topic}. " * 10
# summary = summarizer(dummy_text, max_length=300, min_length=30, do_sample=False)[0]["summary_text"]
# audio_path = "digest.wav"
# tts.tts_to_file(text=summary, file_path=audio_path)
# return summary, audio_path, audio_path
# # ---------- Feature 2: Interactive Story Generator ----------
# # Genre-specific openers
# genre_templates = {
# "fantasy": "In a land of dragons and forgotten magic, a tale begins.",
# "sci-fi": "In a distant galaxy, governed by AI and cosmic laws, a new story unfolds.",
# "thriller": "It started on a stormy night, when a single knock on the door changed everything.",
# "romance": "They locked eyes for the first time in a quiet bookstore.",
# "horror": "The clock struck midnight, and something moved in the shadows.",
# "myth": "Long before time was time, gods and mortals shared the same sky.",
# "comedy": "There was once a chicken who wanted to cross a space highway..."
# }
# # Optional creative twists for inspiration (no longer injected into prompt text)
# twist_prompts = [
# "But little did they know, everything was about to change.",
# "Suddenly, a mysterious voice echoed in the air.",
# "Out of nowhere, a glowing symbol appeared.",
# "But fate had other plans.",
# "And just like that, the rules of the world shifted."
# ]
# def generate_story(genre, choice):
# genre = genre.lower()
# base_prompt = genre_templates.get(genre, f"Begin a story in the genre: {genre}.")
# prompt = base_prompt
# if choice:
# twist = random.choice(twist_prompts)
# prompt += f" The character decided to '{choice}'. {twist}"
# generated = story_gen(prompt)[0]['generated_text']
# story_audio_path = "story.wav"
# tts.tts_to_file(text=generated, file_path=story_audio_path)
# return generated, story_audio_path, story_audio_path
# # ---------- Gradio UI ----------
# digest_ui = gr.Interface(
# fn=generate_audio_digest,
# inputs=gr.Textbox(label="Enter your topic of interest", placeholder="e.g. motivation, productivity"),
# outputs=[
# gr.Textbox(label="Summary", lines=5),
# gr.Audio(label="🔊 Audio Digest", type="filepath"),
# gr.File(label="⬇️ Download Audio File")
# ],
# title="🎧 KukuBuddy: Daily Audio Digest"
# )
# story_ui = gr.Interface(
# fn=generate_story,
# inputs=[
# gr.Textbox(label="Genre", placeholder="e.g. sci-fi, myth, thriller"),
# gr.Textbox(label="Your last choice", placeholder="e.g. Enter the castle")
# ],
# outputs=[
# gr.Textbox(label="📖 Next Scene", lines=5),
# gr.Audio(label="🔊 Narration", type="filepath"),
# gr.File(label="⬇️ Download Narration")
# ],
# title="📖 KukuBuddy: Interactive Story"
# )
# app = gr.TabbedInterface(
# [digest_ui, story_ui],
# tab_names=["📌 Daily Digest", "🧠 Interactive Story"]
# )
# if __name__ == "__main__":
# app.launch()
# import random
# import gradio as gr
# from transformers import pipeline
# from TTS.api import TTS
# # --------------- Lightweight Models ---------------
# summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")
# story_gen = pipeline("text-generation", model="datificate/gpt2-small-story", max_length=250, pad_token_id=50256)
# tts = TTS(model_name="tts_models/en/ljspeech/tacotron2-DDC", progress_bar=False, gpu=False)
# # --------------- Feature 1: Daily Audio Digest ---------------
# def generate_audio_digest(topic):
# dummy_text = f"This is a sample Kuku FM podcast about {topic}. " * 10
# summary = summarizer(dummy_text, max_length=300, min_length=30, do_sample=False)[0]["summary_text"]
# audio_path = "digest.wav"
# tts.tts_to_file(text=summary, file_path=audio_path)
# return summary, audio_path, audio_path
# # --------------- Feature 2: Interactive Story Generator ---------------
# story_cache = {}
# # Genre-specific openers
# genre_templates = {
# "fantasy": "In a land of dragons and forgotten magic, a tale begins.",
# "sci-fi": "In a distant galaxy governed by AI and cosmic laws, a new story unfolds.",
# "thriller": "It started on a stormy night, when a knock on the door changed everything.",
# "romance": "They locked eyes for the first time in a quiet bookstore.",
# "horror": "The clock struck midnight, and something moved in the shadows.",
# "myth": "Long before time began, gods and mortals shared the same sky.",
# "comedy": "There was once a chicken who wanted to cross a space highway..."
# }
# def generate_story(genre, choice):
# genre = genre.lower()
# base_prompt = genre_templates.get(genre, f"Begin a story in the genre: {genre}.")
# prompt = base_prompt
# if choice:
# prompt += f" The character decided to '{choice}'."
# # GPT-style continuation
# prompt += " What happened next was"
# generated = story_gen(prompt, do_sample=True, top_p=0.92, temperature=0.9)[0]['generated_text']
# # Extract only the new scene, not the input prompt
# next_scene = generated[len(prompt):].strip()
# story_audio_path = "story.wav"
# tts.tts_to_file(text=next_scene, file_path=story_audio_path)
# return next_scene, story_audio_path, story_audio_path
# # --------------- Gradio UI ---------------
# digest_ui = gr.Interface(
# fn=generate_audio_digest,
# inputs=gr.Textbox(label="🎯 Enter your topic of interest", placeholder="e.g. motivation, productivity", lines=2),
# outputs=[
# gr.Textbox(label="📝 Summary", lines=4),
# gr.Audio(label="🎧 Audio Digest", type="filepath"),
# gr.File(label="⬇️ Download Audio")
# ],
# title="🎧 KukuBuddy: Daily Audio Digest"
# )
# story_ui = gr.Interface(
# fn=generate_story,
# inputs=[
# gr.Textbox(label="📚 Genre", placeholder="e.g. sci-fi, myth, thriller", lines=1),
# gr.Textbox(label="🎮 Your last choice", placeholder="e.g. Enter the castle", lines=2)
# ],
# outputs=[
# gr.Textbox(label="📝 Next Scene", lines=4),
# gr.Audio(label="🎧 Narration", type="filepath"),
# gr.File(label="⬇️ Download Audio")
# ],
# title="📖 KukuBuddy: Interactive Story"
# )
# app = gr.TabbedInterface([digest_ui, story_ui], tab_names=["📌 Daily Digest", "🧠 Interactive Story"])
# if __name__ == "__main__":
# app.launch()
# import random
# import gradio as gr
# from transformers import pipeline
# from TTS.api import TTS
# # --------------- Lightweight Models ---------------
# summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")
# story_gen = pipeline("text-generation", model="mrm8488/GPT-2-finetuned-fiction", max_length=250, pad_token_id=50256)
# tts = TTS(model_name="tts_models/en/ljspeech/glow-tts", progress_bar=False, gpu=False)
# # --------------- Feature 1: Daily Audio Digest ---------------
# def generate_audio_digest(topic):
# dummy_text = f"This is a sample Kuku FM podcast about {topic}. " * 10
# summary = summarizer(dummy_text, max_length=300, min_length=30, do_sample=False)[0]["summary_text"]
# audio_path = "digest.wav"
# tts.tts_to_file(text=summary, file_path=audio_path)
# return summary, audio_path, audio_path
# # --------------- Feature 2: Interactive Story Generator ---------------
# genre_templates = {
# "fantasy": "In a land of dragons and forgotten magic, a tale begins.",
# "sci-fi": "In a distant galaxy governed by AI and cosmic laws, a new story unfolds.",
# "thriller": "It started on a stormy night, when a knock on the door changed everything.",
# "romance": "They locked eyes for the first time in a quiet bookstore.",
# "horror": "The clock struck midnight, and something moved in the shadows.",
# "myth": "Long before time began, gods and mortals shared the same sky.",
# "comedy": "There was once a chicken who wanted to cross a space highway..."
# }
# def generate_story(genre, choice):
# genre = genre.lower()
# base_prompt = genre_templates.get(genre, f"Begin a story in the genre: {genre}.")
# prompt = base_prompt
# if choice:
# prompt += f" The character decided to '{choice}'."
# prompt += " What happened next was"
# generated = story_gen(prompt, do_sample=True, top_p=0.92, temperature=0.9)[0]['generated_text']
# next_scene = generated[len(prompt):].strip()
# story_audio_path = "story.wav"
# tts.tts_to_file(text=next_scene, file_path=story_audio_path)
# return next_scene, story_audio_path, story_audio_path
# # --------------- Gradio UI ---------------
# digest_ui = gr.Interface(
# fn=generate_audio_digest,
# inputs=gr.Textbox(label="🎯 Enter your topic of interest", placeholder="e.g. motivation, productivity", lines=2),
# outputs=[
# gr.Textbox(label="📝 Summary", lines=4),
# gr.Audio(label="🎧 Audio Digest", type="filepath"),
# gr.File(label="⬇️ Download Audio")
# ],
# title="🎧 KukuBuddy: Daily Audio Digest"
# )
# story_ui = gr.Interface(
# fn=generate_story,
# inputs=[
# gr.Textbox(label="📚 Genre", placeholder="e.g. sci-fi, myth, thriller", lines=1),
# gr.Textbox(label="🎮 Your last choice", placeholder="e.g. Enter the castle", lines=2)
# ],
# outputs=[
# gr.Textbox(label="📝 Next Scene", lines=4),
# gr.Audio(label="🎧 Narration", type="filepath"),
# gr.File(label="⬇️ Download Audio")
# ],
# title="📖 KukuBuddy: Interactive Story"
# )
# app = gr.TabbedInterface([digest_ui, story_ui], tab_names=["📌 Daily Digest", "🧠 Interactive Story"])
# if __name__ == "__main__":
# app.launch()
import random
import gradio as gr
from transformers import pipeline, set_seed
from TTS.api import TTS
# --------------- Lightweight Models ---------------
summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")
story_gen = pipeline("text-generation", model="aspis/gpt2-genre-story-generation", max_length=250, pad_token_id=50256)
set_seed(42)
tts = TTS(model_name="tts_models/en/ljspeech/glow-tts", progress_bar=False, gpu=False)
# --------------- Feature 1: Daily Audio Digest ---------------
def generate_audio_digest(topic):
dummy_text = f"This is a sample Kuku FM podcast about {topic}. " * 10
summary = summarizer(dummy_text, max_length=300, min_length=30, do_sample=False)[0]["summary_text"]
audio_path = "digest.wav"
tts.tts_to_file(text=summary, file_path=audio_path)
return summary, audio_path, audio_path
# --------------- Feature 2: Interactive Story Generator ---------------
# Genre-specific openers to guide the style of the story
genre_templates = {
"fantasy": "In a land of dragons and forgotten magic, a tale begins.",
"sci-fi": "In a distant galaxy governed by AI and cosmic laws, a new story unfolds.",
"thriller": "It started on a stormy night, when a knock on the door changed everything.",
"romance": "They locked eyes for the first time in a quiet bookstore.",
"horror": "The clock struck midnight, and something moved in the shadows.",
"myth": "Long before time began, gods and mortals shared the same sky.",
"comedy": "There was once a chicken who wanted to cross a space highway..."
}
def generate_story(genre, choice):
genre = genre.lower()
base_prompt = genre_templates.get(genre, f"Begin a story in the genre: {genre}.")
# Build a more detailed prompt using the user's choice.
prompt = base_prompt
if choice:
prompt += f" The protagonist made a bold decision: '{choice}'."
# Add clear instructions to generate a coherent narrative.
prompt += " Continue the story in a creative and engaging way. Develop the characters and emotions naturally."
generated = story_gen(prompt, do_sample=True, top_p=0.9, temperature=0.85)[0]['generated_text']
# Extract only the generated continuation.
next_scene = generated[len(prompt):].strip()
story_audio_path = "story.wav"
tts.tts_to_file(text=next_scene, file_path=story_audio_path)
return next_scene, story_audio_path, story_audio_path
# --------------- Gradio UI ---------------
digest_ui = gr.Interface(
fn=generate_audio_digest,
inputs=gr.Textbox(label="🎯 Enter your topic of interest", placeholder="e.g. motivation, productivity", lines=2),
outputs=[
gr.Textbox(label="📝 Summary", lines=4),
gr.Audio(label="🎧 Audio Digest", type="filepath"),
gr.File(label="⬇️ Download Audio")
],
title="🎧 KukuBuddy: Daily Audio Digest"
)
story_ui = gr.Interface(
fn=generate_story,
inputs=[
gr.Textbox(label="📚 Genre", placeholder="e.g. sci-fi, myth, thriller, romance", lines=1),
gr.Textbox(label="🎮 Your last choice", placeholder="e.g. Enter the castle", lines=2)
],
outputs=[
gr.Textbox(label="📝 Next Scene", lines=4),
gr.Audio(label="🎧 Narration", type="filepath"),
gr.File(label="⬇️ Download Audio")
],
title="📖 KukuBuddy: Interactive Story"
)
app = gr.TabbedInterface([digest_ui, story_ui], tab_names=["📌 Daily Digest", "🧠 Interactive Story"])
if __name__ == "__main__":
app.launch()
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