Update tools.py

tools.py

@@ -32,41 +32,37 @@ def days_until(date_str: str) -> str :
 datetime_tools = [current_date, day_of_week, days_until]
 
 @tool
-def transcribe_audio(audio_input: str) -> str:
-    """
-    Transcribes an audio file from a local file or a URL
+def transcribe_audio(audio_file: str, file_extension: str) -> str:
+    """ Transcribes an audio file to text
 
     Args:
-        audio_input (str): A local file path or a direct URL to the audio file (.mp3, .m4a, etc.)
+        audio_file (str): local file path to the audio file (.mp3, .m4a, etc.)
+        file_extension (str): file extension of the audio, e.g. mp3
     
     Returns:
         str: The transcribed text from the audio.
     """
+    
     try:
-        # Detects if audio_input is a URL
-        is_url = audio_input.startswith("http://") or audio_input.startswith("https://")
-
-        if is_url:
-            parsed = urlparse(audio_input)  # breaks down the URL into components (scheme, netloc, path, params, etc.)
-            extension = os.path.splitext(parsed.path)[1] or ".mp3"  # get the actual file extension from the URL path or define it to .mp3 if no extension is found
-            
-            # Download to temporary file
-            with tempfile.NamedTemporaryFile(suffix=extension, delete=False) as tmp_file:  # creates a temporary file
-                response = requests.get(audio_input)  # downloads the content
-                response.raise_for_status()  # checks if the http request was successful
-                tmp_file.write(response.content)  # saves the file to disk
-                file_path = tmp_file.name
-        else:
-            file_path = audio_input
-
-        # Transcribing audio using OpenAI Whisper
+        response = requests.get(audio_file)  # download the audio_file
+        response.raise_for_status()  # check if the http request was successful
+        
+        # clean file extension and save to disk
+        file_extension = file_extension.replace('.','')
+        filename = f'tmp.{file_extension}'
+        with open(filename, 'wb') as file:  # opens a new file for writing with a name like, e.g. tmp.mp3
+            file.write(response.content)    # write(w) the binary(b) contents (audio file) to disk
+        
+        # transcribe audio with OpenAI Whisper
         client = OpenAI()
-        with open(file_path, "rb") as audio_file: # opens the audio file from disk in binary mode (rb); the "with" block ensures the file is automatically closed afterward
+        
+        # read(r) the audio file from disk in binary(b) mode "rb"; the "with" block ensures the file is automatically closed afterward
+        with open(filename, "rb") as audio_content:
             transcription = client.audio.transcriptions.create(
                 model="whisper-1",
-                file=audio_file
-            )
+                file=audio_content
+        )
         return transcription.text
 
     except Exception as e:
-        return f"Transcription failed: {e}"
+        return f"transcribe_audio failed: {e}"