Upload app.py

app.py

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+import gradio as gr
+import assemblyai as aai
+from together import Together
+import base64
+from io import BytesIO
+from PIL import Image
+import os
+import yaml
+
+
+# Function to load API credentials
+def load_credentials():
+    assemblyai_key = os.getenv("ASSEMBLYAI_API_KEY")
+    together_key = os.getenv("TOGETHER_API_KEY")
+    
+    if not assemblyai_key or not together_key:
+        try:
+            with open('API.yml', 'r') as file:
+                api_creds = yaml.safe_load(file)
+                assemblyai_key = assemblyai_key or api_creds['assemblyai']
+                together_key = together_key or api_creds['Together_api']
+        except Exception as e:
+            print(f"Failed to load API credentials: {str(e)}")
+            return None, None
+    
+    return assemblyai_key, together_key
+
+# Initialize API clients
+ASSEMBLYAI_API_KEY, TOGETHER_API_KEY = load_credentials()
+
+if ASSEMBLYAI_API_KEY and TOGETHER_API_KEY:
+    aai.settings.api_key = ASSEMBLYAI_API_KEY
+    together_client = Together(api_key=TOGETHER_API_KEY)
+else:
+    raise ValueError("API credentials not found. Please check your configuration.")
+
+def transcribe_audio(audio_path):
+    """Transcribe audio using AssemblyAI."""
+    try:
+        transcriber = aai.Transcriber()
+        transcript = transcriber.transcribe(audio_path)
+        return transcript.text
+    except Exception as e:
+        return f"Error in transcription: {str(e)}"
+
+def generate_image(prompt):
+    """Generate image using Together AI."""
+    try:
+        response = together_client.images.generate(
+            prompt=prompt,
+            model="black-forest-labs/FLUX.1-schnell-Free",
+            width=1024,
+            height=768,
+            steps=4,
+            n=1,
+            response_format="b64_json"
+        )
+        # Convert base64 to PIL Image
+        img_data = base64.b64decode(response.data[0].b64_json)
+        img = Image.open(BytesIO(img_data))
+        return img
+    except Exception as e:
+        return f"Error in image generation: {str(e)}"
+
+def process_audio(audio, progress=gr.Progress()):
+    """Process audio file and generate image"""
+    if audio is None:
+        return None, "Please provide an audio input."
+    
+    progress(0.3, desc="Transcribing audio...")
+    transcribed_text = transcribe_audio(audio)
+    
+    if isinstance(transcribed_text, str) and not transcribed_text.startswith("Error"):
+        progress(0.6, desc="Generating image...")
+        generated_image = generate_image(transcribed_text)
+        
+        if isinstance(generated_image, Image.Image):
+            progress(1.0, desc="Complete!")
+            return generated_image, transcribed_text
+        else:
+            return None, f"Image generation failed: {generated_image}"
+    else:
+        return None, f"Transcription failed: {transcribed_text}"
+
+# Custom CSS for better styling
+custom_css = """
+#app-title {
+    text-align: center;
+    margin-bottom: 10px;
+}
+#app-subtitle {
+    text-align: center;
+    margin-bottom: 30px;
+}
+#main-container {
+    max-width: 1200px;
+    margin: auto;
+}
+"""
+
+# Create Gradio interface
+def create_interface():
+    with gr.Blocks(css=custom_css, theme=gr.themes.Soft(
+        primary_hue="indigo",
+        secondary_hue="blue",
+        neutral_hue="slate"
+    )) as app:
+        gr.HTML(
+            """
+            <div id="app-title">
+                <h1> Voice Generated Visions </h1>
+            </div>
+            <div id="app-subtitle">
+                <h3>✨ Transform Your Words into Stunning Visual Art ✨</h3>
+            </div>
+            """
+        )
+
+        with gr.Row():
+            with gr.Column():
+                audio_input = gr.Audio(
+                    label="Record or Upload Audio",
+                    sources=["microphone", "upload"],
+                    type="filepath"
+                )
+                submit_btn = gr.Button("🚀 Generate Vision", variant="primary")
+
+            with gr.Column():
+                output_image = gr.Image(label="Generated Image 🖼️")
+                output_text = gr.Textbox(
+                    label="Transcribed Text 📝",
+                    placeholder="Your speech will appear here...",
+                    lines=3
+                )
+
+        # Add usage instructions
+        with gr.Accordion("ℹ️ How to Use"):
+            gr.Markdown("""
+            1. **Record or Upload** 🎤
+               - Click the microphone icon to record your voice
+               - Or upload an audio file from your device
+            
+            2. **Generate** 🎨
+               - Click 'Generate Vision' to process your audio
+               - Wait for the magic to happen!
+            
+            3. **Results** ✨
+               - View your transcribed text
+               - See your words transformed into art
+            """)
+
+        submit_btn.click(
+            fn=process_audio,
+            inputs=[audio_input],
+            outputs=[output_image, output_text]
+        )
+
+    return app
+
+# Launch the app
+if __name__ == "__main__":
+    demo = create_interface()
+    demo.launch(share=True)