Update app.py

app.py

@@ -1,40 +1,31 @@
-def process_audio(audio_path, image_option, creative_text_option):
-    if audio_path is None:
-        return "Please upload an audio file.", None, None, None
+import whisper
+import gradio as gr
+from groq import Groq
+from deep_translator import GoogleTranslator
+from diffusers import StableDiffusionPipeline
+import os
+import torch
+import openai
+from huggingface_hub import InferenceApi
+from PIL import Image
+import requests
+import io
+import time
 
-    # Step 1: Transcribe audio
-    try:
-        with open(audio_path, "rb") as file:
-            transcription = client.audio.transcriptions.create(
-                file=(os.path.basename(audio_path), file.read()),
-                model="whisper-large-v3",
-                language="kn",
-                response_format="verbose_json",
-            )
-        kannada_text = transcription.text
-    except Exception as e:
-        return f"An error occurred during transcription: {str(e)}", None, None, None
+# Set up Groq API key
+api_key = os.getenv("gkannada_key")
+client = Groq(api_key=api_key)
 
-    # Step 2: Translate Kannada to English
-    try:
-        translator = GoogleTranslator(source='kn', target='en')
-        translation = translator.translate(kannada_text)
-    except Exception as e:
-        return kannada_text, f"An error occurred during translation: {str(e)}", None, None
+# Hugging Face API details for image generation
+key = os.getenv("h_key")
+API_URL = "https://api-inference.huggingface.co/models/Artples/LAI-ImageGeneration-vSDXL-2"
+headers = {"Authorization": f"Bearer {key}"}
 
-    # Step 3: Generate creative text (if selected)
-    creative_text = None
-    if creative_text_option == "Generate Creative Text":
-        try:
-            creative_text = generate_creative_text(translation)
-        except Exception as e:
-            creative_text = f"An error occurred during creative text generation: {str(e)}"
+# Function for querying image generation with retries
+def query_image_generation(payload, max_retries=5):
+    for attempt in range(max_retries):
+        response = requests.post(API_URL, headers=headers, json=payload)
 
-    # Step 4: Generate image (if selected)
-    image = None
-    if image_option == "Generate Image":
-        image = generate_image(translation)
-        if image is None:
-            return kannada_text, translation, creative_text, "An error occurred during image generation."
-
-    return kannada_text, translation, creative_text, image      
+        if response.status_code == 503:
+            print(f"Model is still loading, retrying... Attempt {attempt + 1}/{max_retries}")
+            estimated_time = min(response.json().get("estimated_time", 60), 6