app.py

import os
from flask import Flask, request, render_template, jsonify
from groq import Groq
import json

# Set up the Groq client
os.environ["GROQ_API_KEY"] = "your_groq_api_key_here"  # Replace with your actual API key
client = Groq(api_key=os.environ["GROQ_API_KEY"])

app = Flask(__name__)

# Route to render the upload form
@app.route('/')
def index():
    return render_template('index.html')

# Route to handle the audio upload and transcription
@app.route('/transcribe', methods=['POST'])
def transcribe_audio():
    audio_data = request.files['audio_data']
    selected_language = request.form['language']

    try:
        # Transcribe the audio based on the selected language
        transcription = client.audio.transcriptions.create(
            file=(audio_data.filename, audio_data.read()),
            model="whisper-large-v3",  # You can change this model if needed
            response_format="text",
            language=selected_language,
        )

        return jsonify({'transcription': transcription['text']})  # Fix to extract text
    except Exception as e:
        return str(e), 500

# Route to check grammar and vocabulary of the transcription
@app.route('/check_grammar', methods=['POST'])
def check_grammar():
    transcription = request.form['transcription']
    selected_language = request.form['language']

    if not transcription:
        return "No transcription available."

    try:
        # Grammar check with scoring and concise feedback
        grammar_prompt = f"""
        Check the grammar of the following text in {selected_language}:
        \"\"\"
        {transcription}
        \"\"\"
        Provide a score from 1 to 10 and a concise feedback (1-1.5 lines) without including the score in the feedback.
        Return the result in JSON format with keys 'score' and 'feedback'.
        """
        grammar_check_response = client.chat.completions.create(
            model="gemma-7b-it",  # Change the model if needed
            messages=[{"role": "user", "content": grammar_prompt}]
        )
        grammar_response_content = grammar_check_response.choices[0].message.content.strip()
        grammar_result = json.loads(grammar_response_content)
        grammar_score = grammar_result.get('score', '')
        grammar_feedback = grammar_result.get('feedback', '')

        # Vocabulary check with scoring and concise feedback
        vocabulary_prompt = f"""
        Check the vocabulary accuracy of the following text in {selected_language}:
        \"\"\"
        {transcription}
        \"\"\"
        Provide a score from 1 to 10 and a concise feedback (1-1.5 lines) without including the score in the feedback.
        Return the result in JSON format with keys 'score' and 'feedback'.
        """
        vocabulary_check_response = client.chat.completions.create(
            model="llama3-8b-8192",  # Change the model if needed
            messages=[{"role": "user", "content": vocabulary_prompt}]
        )
        vocabulary_response_content = vocabulary_check_response.choices[0].message.content.strip()
        vocabulary_result = json.loads(vocabulary_response_content)
        vocabulary_score = vocabulary_result.get('score', '')
        vocabulary_feedback = vocabulary_result.get('feedback', '')

        return jsonify({
            'grammar_feedback': grammar_feedback,
            'grammar_score': grammar_score,
            'vocabulary_feedback': vocabulary_feedback,
            'vocabulary_score': vocabulary_score
        })
    except Exception as e:
        return str(e), 500

if __name__ == "__main__":
    app.run(debug=True)