Create app.py

app.py

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+# prompt: add the theme  featrue in above  Audio Transcription, Translation, and Sentiment Analysis app and also need selectbox for sentiment and generated image
+import whisper
+import os
+import gradio as gr
+from groq import Groq
+from deep_translator import GoogleTranslator
+import pickle
+from diffusers import StableDiffusionPipeline
+import matplotlib.pyplot as plt
+import torch
+
+
+# Replace with your actual API key
+api_key ="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"
+client = Groq(api_key=api_key)
+
+
+model_id1 = "dreamlike-art/dreamlike-diffusion-1.0"
+model_id2 = "stabilityai/stable-diffusion-xl-base-1.0"
+
+pipe = StableDiffusionPipeline.from_pretrained(model_id1, torch_dtype=torch.float16, use_safetensors=True)
+pipe = pipe.to("cpu")
+
+prompt = """dreamlikeart, a grungy woman with rainbow hair, travelling between dimensions, dynamic pose, happy, soft eyes and narrow chin,
+extreme bokeh, dainty figure, long hair straight down, torn kawaii shirt and baggy jeans
+"""
+image = pipe(prompt).images[0]
+
+# Function to transcribe, translate, and analyze sentiment
+def process_audio(audio_path, image_option):
+    if audio_path is None:
+        return "Please upload an audio file.", None, None, None
+
+    # 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="ta",
+                response_format="verbose_json",
+            )
+        tamil_text = transcription.text
+    except Exception as e:
+        return f"An error occurred during transcription: {str(e)}", None, None, None
+
+    # Step 2: Translate Tamil to English
+    try:
+        translator = GoogleTranslator(source='ta', target='en')
+        translation = translator.translate(tamil_text)
+    except Exception as e:
+        return tamil_text, f"An error occurred during translation: {str(e)}", None, None
+
+
+
+    # Step 3: Generate image (if selected)
+    image = None
+    if image_option == "Generate Image":
+        try:
+            model_id1 = "dreamlike-art/dreamlike-diffusion-1.0"
+            pipe = StableDiffusionPipeline.from_pretrained(model_id1, torch_dtype=torch.float16, use_safetensors=True)
+            pipe = pipe.to("cpu")
+            image = pipe(translation).images[0]
+        except Exception as e:
+            return tamil_text, translation, f"An error occurred during image generation: {str(e)}"
+
+    return tamil_text, translation, image
+
+# Create Gradio interface
+with gr.Blocks(theme=gr.themes.Base()) as iface:
+    gr.Markdown("# Audio Transcription, Translation, and image Generate")
+    with gr.Row():
+        with gr.Column():
+            audio_input = gr.Audio(type="filepath", label="Upload Audio File")
+            image_option = gr.Dropdown(["Generate Image", "Skip Image"], label="Image Generation", value="Generate Image")
+            submit_button = gr.Button("Process Audio")
+        with gr.Column():
+            tamil_text_output = gr.Textbox(label="Tamil Transcription")
+            translation_output = gr.Textbox(label="English Translation")
+            image_output = gr.Image(label="Generated Image")
+
+    submit_button.click(
+        fn=process_audio,
+        inputs=[audio_input, image_option],
+        outputs=[tamil_text_output, translation_output, image_output]
+    )
+
+# Launch the interface
+iface.launch()