Initial

app.py

@@ -247,7 +247,22 @@ def transform_output_to_tables(final_output: dict):
 
 
 with gr.Blocks() as demo:
-    gr.Markdown("Callytics Demo")
+    gr.Markdown(
+        """
+    <div align=\"center\">
+
+# <span style=\"font-size:48px;\">Callytics</span>
+
+<span style=\"font-size:20px;\">__`Callytics` is an advanced call analytics solution leveraging speech recognition and large language model (LLM) technologies to analyze customer service and call center conversations. By simultaneously processing audio and text from each call, Callytics provides valuable insights, including sentiment analysis, topic identification, conflict detection, profanity detection, and conversation summaries. These cutting-edge capabilities enable businesses to optimize customer interactions, identify improvement opportunities, and enhance overall service quality.__</span>
+
+<span style=\"font-size:18px;\">**Note:** This demo uses HuggingFace's free CPU tier, which results in significantly longer processing times. For example, analyzing a 1-minute call may take approximately 7 minutes.</span>
+
+<span style=\"font-size:18px;\">- You can explore the [GitHub repository](https://github.com/bunyaminergen/Callytics) for more details.</span>  
+<span style=\"font-size:18px;\">- If you don't have your own call center recordings, feel free to test the application using provided sample audio files.</span>
+
+</div>
+        """
+    )
 
     with gr.Row():
         audio_input = gr.Audio(type="filepath", label="Upload your audio")