Added video recommendations

backend/main.py

@@ -64,4 +64,20 @@ def run_tts():
     gpt4_model = TextModel(model_name="gpt-4-1106-preview")
     response_text = gpt4_model.complete(input_text)
     # Call the tts function with the formatted string
-    tts(response_text)
+    tts(response_text)
+
+def recommend_video_link(question, context):        
+    client = OpenAI()
+    response = client.chat.completions.create(
+        model="gpt-3.5-turbo",
+        messages=[
+            {"role": "system", "content": "Based on the video titles below, recommend the most relevant video for the question. If the question can't be answered based on the titles, then return empty string. Note: Only provide the link to the video and no additional text.\n\n" + context},
+            {"role": "user", "content": f"Question: {question}\nAnswer:"}
+        ],
+        temperature=0,
+        max_tokens=100,
+        top_p=1,
+        frequency_penalty=0,
+        presence_penalty=0,    
+    )
+    return response.choices[0].message.content

frontend/app.py

@@ -18,6 +18,7 @@
 VOICE_TESTING = "backend/speech.mp3"
 LOGO = "frontend/testing_data/logo.jpeg"
 FAVICON = "frontend/testing_data/logo.png"
+VIDEO_LINK = "videos.csv"
 
 # Initialize state variables if not already present
 if "student_images_paths" not in st.session_state:
@@ -166,6 +167,8 @@
                 audio_bytes = audio_file.read()
                 st.audio(audio_bytes, format="audio/mp3", start_time=0)
 
+                df = pd.read_csv(VIDEO_LINK)
+                context = read_video_csv(df)
                 results = "🌟 Here are the recommended questions for improvement! Let's dive in and explore 🚀<ul>"
                 with open(CSV_PATH, mode="r", encoding="utf-8") as csv_file:
                     # Create a CSV reader object from the file object
@@ -177,7 +180,9 @@
                     for row in csv_reader: 
                         question_id = row["question_id"]                                               
                         question = row["question"]
-                        results += f"<li><strong>Question {question_id}:</strong> {question}</li>"
+                        video = recommend_video_link(question, context)
+
+                        results += f"<li><strong>Question {question_id}:</strong> {question}. Ref: {video} </li>"
 
                     results += "</ul>✨ Keep up the great work, and remember, every question is a step towards mastery! 📚"
 

frontend/utils.py

@@ -31,3 +31,12 @@ def display_images(file_paths, default_image_path, title):
     else:
         # Display default image if no images are found
         st.image(default_image_path, caption="Default Image", width=500)
+
+def read_video_csv(df):
+    # Prepare the context for GPT based on video names and their links
+    context = "Based on the following video titles and their links:\n"
+    for _, row in df.iterrows():
+        question = row['question']
+        video_link = row['link']
+        context += f"- {question}: {video_link}\n"
+    return context 

videos.csv

@@ -0,0 +1,5 @@
+question,link
+Solve for x: 2x + 5 = 15,https://www.youtube.com/watch?v=pOeotbDbC7I 
+Find the roots of the quadratic equation: x^2 - 5x + 6 = 0 ,https://www.youtube.com/watch?v=ri5PJ7b6594 
+"If f(x) = 3x^2 - 2x + 1, find f(2) ",https://www.youtube.com/watch?v=UzeLsa38wQI 
+Simplify the expression 2x^2 - 8 / x - 2 ,https://www.youtube.com/watch?v=M-AqHlSQwcI