Added deepgram nova whisperAI application API

app.py

@@ -85,21 +85,11 @@ async def process_audio():
         return jsonify({"error": str(e)}), 500
 
 
-import subprocess
-import os
-import json
-from deepgram.clients import DeepgramClient
-from deepgram.options import PrerecordedOptions
-
-# Replace with your actual Deepgram API key
-DEEPGRAM_API_KEY = "your_deepgram_api_key"
-
-async def transcribe_audio(video_file_path, wav_file_path):
+async def transcribe_audio(wav_file_path):
     """
     Transcribe audio from a video file using Whisper AI (async function).
     
     Args:
-        video_file_path (str): Path to the input video file.
         wav_file_path (str): Path to save the converted WAV file.
 
     Returns:
@@ -110,13 +100,13 @@ async def transcribe_audio(video_file_path, wav_file_path):
         # Initialize Deepgram client
         deepgram = DeepgramClient(DEEPGRAM_API_KEY)
 
-        # Convert video to audio in WAV format using FFmpeg
-        print("Converting video to audio (WAV format)...")
-        ffmpeg_command = [
-            "ffmpeg", "-i", video_file_path, "-q:a", "0", "-map", "a", wav_file_path
-        ]
-        subprocess.run(ffmpeg_command, check=True)
-        print(f"Conversion successful! WAV file saved at: {wav_file_path}")
+        # # Convert video to audio in WAV format using FFmpeg
+        # print("Converting video to audio (WAV format)...")
+        # ffmpeg_command = [
+        #     "ffmpeg", "-i", video_file_path, "-q:a", "0", "-map", "a", wav_file_path
+        # ]
+        # subprocess.run(ffmpeg_command, check=True)
+        # print(f"Conversion successful! WAV file saved at: {wav_file_path}")
 
         # Open the converted WAV file
         with open(wav_file_path, 'rb') as buffer_data:
@@ -153,14 +143,14 @@ async def transcribe_audio(video_file_path, wav_file_path):
                     return {"status": "error", "message": f"Error extracting transcript: {e}"}
 
                 # Path to the text file
-                output_text_file = "deepGramNovaTranscript.txt"
+                # output_text_file = "deepGramNovaTranscript.txt"
 
                 # Write the transcript to the text file
-                with open(output_text_file, "w", encoding="utf-8") as file:
-                    file.write(transcript)
+                # with open(output_text_file, "w", encoding="utf-8") as file:
+                #     file.write(transcript)
 
                 print(f"Transcript saved to: {output_text_file}")
-                return {"status": "success", "transcript": transcript, "file_path": output_text_file}
+                return transcript
             else:
                 return {"status": "error", "message": "Invalid response from Deepgram."}