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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="knkarthick/MEETING_SUMMARY")
story_gen = pipeline("text-generation", model="distilgpt2", 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()