Update app.py

app.py

@@ -289,15 +289,102 @@
 # 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="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)
+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):
@@ -310,9 +397,6 @@ def generate_audio_digest(topic):
     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.",
@@ -331,12 +415,9 @@ def generate_story(genre, choice):
     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"
@@ -377,3 +458,4 @@ if __name__ == "__main__":
     app.launch()
 
 
+