Add speaking task 3 grading endpoint.

app.py

@@ -3,7 +3,8 @@ from flask_jwt_extended import JWTManager, jwt_required
 from functools import reduce
 import firebase_admin
 from firebase_admin import credentials, firestore
-from helper.api_messages import QuestionType, get_grading_messages, get_question_gen_messages, get_question_tips
+from helper.api_messages import QuestionType, get_grading_messages, get_question_gen_messages, get_question_tips, \
+    get_speaking_grading_messages
 from helper.file_helper import delete_files_older_than_one_day
 from helper.firebase_helper import download_firebase_file, upload_file_firebase, upload_file_firebase_get_url, \
     save_to_db
@@ -473,6 +474,40 @@ def save_speaking_task_2_question():
     except Exception as e:
         return str(e)
 
+@app.route('/speaking_task_3', methods=['POST'])
+@jwt_required()
+def grade_speaking_task_3():
+    delete_files_older_than_one_day(AUDIO_FILES_PATH)
+    try:
+        data = request.get_json()
+        answers = data.get('answers')
+
+        for item in answers:
+            sound_file_name = AUDIO_FILES_PATH + str(uuid.uuid4())
+            download_firebase_file(FIREBASE_BUCKET, item["answer"], sound_file_name)
+            answer_text = speech_to_text(sound_file_name)
+            item["answer_text"] = answer_text
+            os.remove(sound_file_name)
+            if not has_10_words(answer_text):
+                return {
+                    "comment": "The audio recorded does not contain enough english words to be graded.",
+                    "overall": 0,
+                    "task_response": {
+                        "Fluency and Coherence": 0,
+                        "Lexical Resource": 0,
+                        "Grammatical Range and Accuracy": 0,
+                        "Pronunciation": 0
+                    }
+                }
+
+        messages = get_speaking_grading_messages(answers)
+        token_count = reduce(lambda count, item: count + count_tokens(item)['n_tokens'],
+                             map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
+        response = make_openai_call(GPT_3_5_TURBO, messages, token_count, GRADING_FIELDS, GRADING_TEMPERATURE)
+        return response
+    except Exception as e:
+        return str(e), 400
+
 @app.route('/save_speaking_task_3', methods=['POST'])
 @jwt_required()
 def save_speaking_task_3_question():