Update app.py

app.py

@@ -1,10 +1,9 @@
 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
+os.environ["GROQ_API_KEY"] = "your_groq_api_key_here"
 client = Groq(api_key=os.environ["GROQ_API_KEY"])
 
 app = Flask(__name__)
@@ -24,69 +23,80 @@ def transcribe_audio():
         # 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
+            model="whisper-large-v3",
+            prompt="Transcribe the audio accurately based on the selected language.",
             response_format="text",
             language=selected_language,
         )
 
-        return jsonify({'transcription': transcription['text']})  # Fix to extract text
+        return jsonify({'transcription': transcription})
     except Exception as e:
-        return str(e), 500
+        return jsonify({'error': 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']
+    transcription = request.form.get('transcription')
+    selected_language = request.form.get('language')
 
-    if not transcription:
-        return "No transcription available."
+    if not transcription or not selected_language:
+        return jsonify({'error': 'Missing transcription or language selection'}), 400
 
     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
+        grammar_prompt = (
+            f"Briefly check the grammar of the following text in {selected_language}: {transcription}. "
+            "Identify any word that does not belong to the selected language and flag it. Based on the number of incorrect words, also check the grammar deeply and carefully. "
+            "Provide a score from 1 to 10 based on the grammar accuracy, reducing points for incorrect words and make sure to output the score on a new line after two line breaks like 'SCORE='."
+        )
+
         grammar_check_response = client.chat.completions.create(
-            model="gemma-7b-it",  # Change the model if needed
+            model="llama3-groq-70b-8192-tool-use-preview",
             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'.
-        """
+        grammar_feedback = grammar_check_response.choices[0].message.content.strip()
+
+        # Vocabulary check
+        vocabulary_prompt = (
+            f"Check the vocabulary accuracy of the following text in {selected_language}: {transcription}. "
+            "Identify any word that does not belong to the selected language and flag it. Based on the number of incorrect words, also check the grammar deeply and carefully. "
+            "Provide a score from 1 to 10 based on the vocabulary accuracy reducing points for incorrect words and make sure to output the score on a new line after two line breaks like 'SCORE='."
+        )
+
         vocabulary_check_response = client.chat.completions.create(
-            model="llama3-8b-8192",  # Change the model if needed
+            model="llama-3.1-70b-versatile",
             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', '')
+        vocabulary_feedback = vocabulary_check_response.choices[0].message.content.strip()
+
+        # Return feedback and scores
+        grammar_score = calculate_score(grammar_feedback)
+        vocabulary_score = calculate_score(vocabulary_feedback)
 
         return jsonify({
             'grammar_feedback': grammar_feedback,
-            'grammar_score': grammar_score,
             'vocabulary_feedback': vocabulary_feedback,
+            'grammar_score': grammar_score,
             'vocabulary_score': vocabulary_score
         })
     except Exception as e:
-        return str(e), 500
+        return jsonify({'error': str(e)}), 500
+
+def calculate_score(feedback):
+    """ 
+    Calculate score based on feedback content. 
+    This function searches for the keyword 'SCORE=' or similar variations 
+    (SCORE:, score:, etc.) and extracts the score value.
+    """
+    import re
+    match = re.search(r'(SCORE=|score=|SCORE:|score:|SCORE = )\s*(\d+)', feedback)
+    
+    if match:
+        # Extract and return the score as an integer
+        return int(match.group(2))
+    
+    # Return a default score of 0 if no score is found in the feedback
+    return 0
 
 if __name__ == "__main__":
     app.run(debug=True)