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import gradio as gr
import random
from datetime import datetime
import tempfile
import os
import edge_tts
import asyncio
import warnings
from gradio_client import Client
import pytz
import re
import json
warnings.filterwarnings('ignore')
# Initialize client outside of interface definition
arxiv_client = None
def init_client():
global arxiv_client
if arxiv_client is None:
arxiv_client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
return arxiv_client
def generate_story(prompt, model_choice):
"""Generate story using specified model"""
try:
client = init_client()
if client is None:
return "Error: Story generation service is not available."
result = client.predict(
prompt=prompt,
llm_model_picked=model_choice,
stream_outputs=True,
api_name="/ask_llm"
)
return result
except Exception as e:
return f"Error generating story: {str(e)}"
async def generate_speech(text, voice="en-US-AriaNeural"):
"""Generate speech from text"""
try:
communicate = edge_tts.Communicate(text, voice)
with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp_file:
tmp_path = tmp_file.name
await communicate.save(tmp_path)
return tmp_path
except Exception as e:
print(f"Error in text2speech: {str(e)}")
return None
def process_story_and_audio(prompt, model_choice):
"""Process story and generate audio"""
try:
# Generate story
story = generate_story(prompt, model_choice)
if isinstance(story, str) and story.startswith("Error"):
return story, None
# Generate audio
audio_path = asyncio.run(generate_speech(story))
return story, audio_path
except Exception as e:
return f"Error: {str(e)}", None
# Create the Gradio interface
with gr.Blocks(title="AI Story Generator") as demo:
gr.Markdown("""
# 🎭 AI Story Generator & Narrator
Generate creative stories and listen to them!
""")
with gr.Row():
with gr.Column():
prompt_input = gr.Textbox(
label="Story Concept",
placeholder="Enter your story idea...",
lines=3
)
model_choice = gr.Dropdown(
label="Model",
choices=[
"mistralai/Mixtral-8x7B-Instruct-v0.1",
"mistralai/Mistral-7B-Instruct-v0.2"
],
value="mistralai/Mixtral-8x7B-Instruct-v0.1"
)
generate_btn = gr.Button("Generate Story")
with gr.Row():
story_output = gr.Textbox(
label="Generated Story",
lines=10,
interactive=False
)
with gr.Row():
audio_output = gr.Audio(
label="Story Narration",
type="filepath"
)
generate_btn.click(
fn=process_story_and_audio,
inputs=[prompt_input, model_choice],
outputs=[story_output, audio_output]
)
# Launch the app using the current pattern
if __name__ == "__main__":
demo.launch() |