Update app.py

app.py

@@ -4,11 +4,14 @@ from typing import List, Tuple, Optional
 import google.generativeai as genai
 import gradio as gr
 
+# Get the Google API key from environment variables
 GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY")
 
+# Define the title and subtitle for the Gradio interface
 TITLE = """<h1 align="center">🏋️ AI Personal Trainer Playground 💪</h1>"""
 SUBTITLE = """<h3 align="center">Upload your workout video and let the AI analyze your form 🖇️</h3>"""
 
+# Define the prompt for the AI model
 Prompt = """
 You are the world's best fitness expert. Your goal is to analyze in detail how people perform their exercises and sports movements. Watch the provided video carefully and give them constructive feedback in at least 10 sentences. Focus on the following aspects:
 
@@ -19,14 +22,17 @@ Overall Performance: Give an overall assessment of the workout, highlighting str
 Remember to be encouraging and supportive in your feedback. Your goal is to help them improve and stay motivated. Thank you!
 """
 
+# Function to preprocess stop sequences
 def preprocess_stop_sequences(stop_sequences: str) -> Optional[List[str]]:
     if not stop_sequences:
         return None
     return [sequence.strip() for sequence in stop_sequences.split(",")]
 
+# Function to handle user input
 def user(text_prompt: str, chatbot: List[Tuple[str, str]]):
     return "", chatbot + [[text_prompt, None]]
 
+# Function to handle bot response
 def bot(
     google_key: str,
     model_name: str,
@@ -39,15 +45,18 @@ def bot(
     text_prompt_component: str,
     chatbot: List[Tuple[str, str]]
 ):
+    # Use the provided Google API key or the one from environment variables
     google_key = google_key if google_key else GOOGLE_API_KEY
     if not google_key:
         raise ValueError(
             "GOOGLE_API_KEY is not set. "
             "Please follow the instructions in the README to set it up.")
 
+    # Combine the user input with the predefined prompt
     user_input = chatbot[-1][0]
     combined_prompt = Prompt + "\n" + user_input
 
+    # Configure the generative AI model
     genai.configure(api_key=google_key)
     generation_config = genai.types.GenerationConfig(
         temperature=temperature,
@@ -56,9 +65,11 @@ def bot(
         top_k=top_k,
         top_p=top_p)
 
+    # Handle video prompt if provided
     if video_prompt is not None:
         model = genai.GenerativeModel(model_name)
 
+        # Upload the video file
         video_file = genai.upload_file(path=video_prompt)
         while video_file.state.name == "PROCESSING":
             print('.', end='')
@@ -68,6 +79,7 @@ def bot(
         if video_file.state.name == "FAILED":
             raise ValueError(video_file.state.name)
 
+        # Generate content based on the video and prompt
         response = model.generate_content(
             contents=[video_file, combined_prompt],
             stream=True,
@@ -82,7 +94,7 @@ def bot(
             generation_config=generation_config)
         response.resolve()
 
-    # streaming effect
+    # Streaming effect for chatbot response
     chatbot[-1][1] = ""
     for chunk in response:
         for i in range(0, len(chunk.text), 10):
@@ -91,6 +103,7 @@ def bot(
             time.sleep(0.01)
             yield chatbot
 
+# Define Gradio components
 google_key_component = gr.Textbox(
     label="GOOGLE API KEY",
     value="",
@@ -172,6 +185,7 @@ top_p_component = gr.Slider(
         "the next token (using temperature). "
     ))
 
+# Define user and bot inputs
 user_inputs = [text_prompt_component, chatbot_component]
 
 bot_inputs = [
@@ -187,6 +201,7 @@ bot_inputs = [
     chatbot_component
 ]
 
+# Create the Gradio interface
 with gr.Blocks() as demo:
     gr.HTML(TITLE)
     gr.HTML(SUBTITLE)
@@ -206,6 +221,7 @@ with gr.Blocks() as demo:
                 top_k_component.render()
                 top_p_component.render()
 
+    # Define the interaction between user input and bot response
     run_button_component.click(
         fn=user,
         inputs=user_inputs,
@@ -224,6 +240,7 @@ with gr.Blocks() as demo:
         fn=bot, inputs=bot_inputs, outputs=[chatbot_component]
     )
 
+    # Define example inputs for the Gradio interface
     gr.Examples(
         fn=bot,
         inputs=bot_inputs,
@@ -281,4 +298,5 @@ with gr.Blocks() as demo:
         #cache_examples="lazy",
     )
 
+# Launch the Gradio interface
 demo.queue(max_size=99).launch(debug=False, show_error=True)