worker.py

from groq import Groq
import speech_recognition as sr
import requests
import os
import base64
import io
from dotenv import load_dotenv



load_dotenv()

client = Groq(
    api_key= os.getenv('GROQ_API_KEY')
)

def speech_to_text(audio_binary, voice):
    # Create a recognizer object
    recognizer = sr.Recognizer()

    # Use the WAV file with the speech recognition library
    with sr.AudioFile(io.BytesIO(audio_binary)) as source:
        # Record the audio data from the file
        audio_data = recognizer.record(source)

        try:
            # Recognize the speech using Google Web Speech API
            text = recognizer.recognize_google(audio_data, language = voice )
            return text
        except sr.UnknownValueError:
            print("UnknownValueError: Speech recognition could not understand audio")
            return None
        except sr.RequestError as e:
            print(f"RequestError: Could not request results from Google Web Speech API; {e}")
            return None
        except Exception as e:
            print(f"An error occurred: {e}")
            return None

def text_to_speech(text, voice=""):
    return None


def process_message(conversation_history):
    # Set the prompt for OpenAI Api
    system_prompt = "Act like a personal assistant. You can respond to questions, translate sentences, summarize news, and give recommendations."
    
    messages = [{"role": "system", "content": system_prompt}] + conversation_history

    # Call the OpenAI Api to process our prompt
    completion = client.chat.completions.create(
        model="openai/gpt-oss-20b", 
        messages=messages,
        temperature=0.55,
        max_completion_tokens=4096,
        top_p=1,
        reasoning_effort="low",
        stream=False,
        stop=None,
        tools=[{"type":"browser_search"},{"type":"code_interpreter"}],
        tool_choice="auto"
)

    # Parse the response to get the response message for our prompt
    response_text = completion.choices[0].message.content
    print(response_text)
    return response_text