Update app.py

app.py

@@ -3,10 +3,14 @@ import tempfile
 import os
 import yt_dlp
 from moviepy.editor import VideoFileClip
-import openai
+
+from openai import OpenAI
+client = OpenAI()
+
+
 
 # Set your OpenAI API key (make sure it's set in Hugging Face Spaces secrets)
-openai.api_key = os.getenv("OPENAI_API_KEY")
+#openai.api_key = os.getenv("OPENAI_API_KEY")
 
 # ---------------------------
 # Helper Functions
@@ -43,16 +47,31 @@ def extract_audio(video_path: str) -> str:
         st.error(f"Error extracting audio: {e}")
         return None
 
+# audio_file = open("/path/to/file/speech.mp3", "rb")
+# transcription = client.audio.transcriptions.create(
+#   model="whisper-1", 
+#   file=audio_file, 
+#   response_format="text"
+# )
+
+# print(transcription.text)
+
 def transcribe_audio(audio_path: str) -> str:
     """Transcribe the audio to text using OpenAI's Whisper API."""
     try:
         with open(audio_path, "rb") as audio_file:
-            transcript = openai.Audio.transcribe("whisper-1", audio_file)
-        return transcript['text']
+            transcript = client.audio.transcriptions.create(
+                      model="whisper-1", 
+                      file=audio_file, 
+                      response_format="text"
+                    )
+        return transcript.text
     except Exception as e:
         st.error(f"Error transcribing audio: {e}")
         return ""
 
+
+
 def generate_summary(transcript_text: str) -> str:
     """Generate a concise summary of the transcript using OpenAI."""
     prompt = f"Summarize the following document in a concise manner, highlighting the key points that a student should know:\n\n{transcript_text}"
@@ -60,7 +79,7 @@ def generate_summary(transcript_text: str) -> str:
         {"role": "system", "content": "You are an educational assistant."},
         {"role": "user", "content": prompt}
     ]
-    completion = openai.ChatCompletion.create(model="gpt-4o-mini", messages=messages)
+    completion = client.chat.completions.create(model="gpt-4o-mini", messages=messages)
     return completion.choices[0].message.content.strip()
 
 def get_chat_response(transcript_text: str, conversation_history: list, user_query: str) -> str:
@@ -68,7 +87,7 @@ def get_chat_response(transcript_text: str, conversation_history: list, user_que
     messages = conversation_history + [
         {"role": "user", "content": f"Based on the following document:\n\n{transcript_text}\n\nQuestion: {user_query}"}
     ]
-    completion = openai.ChatCompletion.create(model="gpt-4o-mini", messages=messages)
+    completion = client.chat.completions.create(model="gpt-4o-mini", messages=messages)
     return completion.choices[0].message.content.strip()
 
 # ---------------------------