Update app.py

app.py

@@ -14,31 +14,31 @@ def image_to_base64(img_path):
 img_base64 = image_to_base64("SBC6.jpg")
 img_html = f'<img src="data:image/jpg;base64,{img_base64}" alt="SBC6" width="300" style="display: block; margin: auto;"/>'
 
-
 def predict(question_choice, audio):
     # Transcribe the audio using Whisper
     with open(audio, "rb") as audio_file:
         transcript = openai.Audio.transcribe("whisper-1", audio_file)
+    message = transcript["text"]  # This is the transcribed message from the audio input
     
-    message = transcript["text"]
-
     # Generate the system message based on the chosen question
     current_question_index = data6.questions.index(question_choice)
+    strategy, explanation = data6.strategy_text[current_question_index]
 
     # Construct the conversation with the system and user's message
     conversation = [
-        {
-            "role": "system",
-            "content": f"You are an expert English Language Teacher in a Singapore Primary school, directly guiding a Primary 6 student in Singapore. The student is answering the question: '{data6.questions[current_question_index]}'. Based on their response, provide direct feedback to help them improve their spoken skills. Emphasize areas of strength, suggest areas of improvement, and guide them on how to better answer using the {data6.strategy_text[current_question_index][0]} strategy. The feedback should be in second person, addressing the student directly."
-        },
-        {"role": "user", "content": message}
-    ]
+    {
+        "role": "system",
+        "content": f"You are an expert English Language Teacher in a Singapore Primary school, directly guiding a Primary 6 student in Singapore. The student is answering the question: '{data6.questions[current_question_index]}'. Point out areas they did well and where they can improve. Then, provide a suggested answer using the {data6.strategy_text[current_question_index][0]} strategy. Encourage the use of sophisticated vocabulary and expressions. For the second and third questions, the picture is not relevant, so the student should not refer to it in their response. {explanation} The feedback should be in second person, addressing the student directly."
+    },
+    {"role": "user", "content": message}
+]
+
 
     response = openai.ChatCompletion.create(
         model='gpt-3.5-turbo',
         messages=conversation,
-        temperature=0.7,
-        max_tokens=300,  # Limiting the response to 400 tokens
+        temperature=0.4,
+        max_tokens=400,  # Limiting the response to 500 tokens
         stream=True
     )
 
@@ -48,9 +48,11 @@ def predict(question_choice, audio):
             partial_message = partial_message + chunk['choices'][0]['delta']['content']
             yield partial_message
 
+
 def get_image_html():
     return "![](SBC6.jpg)"  # Markdown syntax to embed the image
 
+
 # Gradio Interface
 iface = gr.Interface(
     fn=predict,
@@ -59,7 +61,8 @@ iface = gr.Interface(
         gr.inputs.Audio(source="microphone", type="filepath")  # Audio input
     ],
     outputs=gr.inputs.Textbox(),  # Using inputs.Textbox as an output to make it editable
-    description=img_html
+    description=img_html,
+    css="custom.css"  # Link to the custom CSS file
 )
 iface.queue().launch()