Upload transcribe.py

tools/transcribe.py

@@ -0,0 +1,47 @@
+# tools/transcribe.py
+from langchain_core.tools import tool
+from groq import Groq
+import os
+from dotenv import load_dotenv
+
+load_dotenv()
+
+@tool
+def transcribe_audio(filename: str) -> str:
+    """
+    Transcribe speech from an audio file into text.
+    Use this immediately after downloading an .mp3 or .wav file to know what is said inside it.
+
+    Args:
+        filename (str): The filename of the audio (e.g., 'audio.mp3') located in LLMFiles/.
+
+    Returns:
+        str: The transcribed text.
+    """
+    try:
+        api_key = os.getenv("GROQ_API_KEY")
+        if not api_key:
+            return "Error: GROQ_API_KEY not found."
+
+        # Initialize Groq Client
+        client = Groq(api_key=api_key)
+        
+        # Construct full path (assuming download_file saves to LLMFiles)
+        file_path = os.path.join("LLMFiles", filename)
+        
+        if not os.path.exists(file_path):
+            return f"Error: File {file_path} does not exist. Did you download it first?"
+
+        # Open file and send to Groq Whisper
+        with open(file_path, "rb") as file:
+            transcription = client.audio.transcriptions.create(
+                file=(filename, file.read()),
+                model="distil-whisper-large-v3-en", # Fast and accurate English model
+                response_format="json",
+                temperature=0.0
+            )
+            
+        return transcription.text
+
+    except Exception as e:
+        return f"Error transcribing audio: {str(e)}"