Api for writing task 2 v1.

app.py

@@ -1,41 +1,66 @@
-import openai
-from flask import Flask
+from flask import Flask, request
+from flask_jwt_extended import JWTManager, jwt_required
+from functools import reduce
+from helper.token_counter import count_tokens
+from helper.process_response import make_openai_call
 import os
+
 from dotenv import load_dotenv
 
+load_dotenv()
+
 app = Flask(__name__)
 
-load_dotenv()
-openai.api_key = os.getenv("OPENAI_API_KEY")
+app.config['JWT_SECRET_KEY'] = os.getenv("JWT_SECRET_KEY")
+jwt = JWTManager(app)
+
+@app.route('/writing_task2', methods=['POST'])
+@jwt_required()
+def grade_writing_task():
+    data = request.get_json()  # Assuming the request data is in JSON format
+    question = data.get('question')
+    answer = data.get('answer')
+    messages = [
+        {
+            "role": "system",
+            "content": "You are a IELTS examiner.",
+        },
+        {
+            "role": "system",
+            "content": f"The question you have to grade is of type Writing Task 2 and is the following: {question}",
+        },
+        {
+            "role": "user",
+            "content": "It is mandatory for you to provide your response with the overall grade and breakdown grades, "
+                       "in the following json format: {'comment': 'comment about answer quality', 'overall': 7.0, 'task_response': {'Task Achievement': 8.0, "
+                       "'Coherence and Cohesion': 6.5, 'Lexical Resource': 7.5, 'Grammatical Range and Accuracy': "
+                       "6.0}}",
+        },
+        {
+            "role": "user",
+            "content": "Example output: { 'comment': 'Overall, the response is good but there are some areas that need "
+                       "improvement.\n\nIn terms of Task Achievement, the writer has addressed all parts of the question "
+                       "and has provided a clear opinion on the topic. However, some of the points made are not fully "
+                       "developed or supported with examples.\n\nIn terms of Coherence and Cohesion, there is a clear "
+                       "structure to the response with an introduction, body paragraphs and conclusion. However, there "
+                       "are some issues with cohesion as some sentences do not flow smoothly from one to another.\n\nIn "
+                       "terms of Lexical Resource, there is a good range of vocabulary used throughout the response and "
+                       "some less common words have been used effectively.\n\nIn terms of Grammatical Range and Accuracy, "
+                       "there are some errors in grammar and sentence structure which affect clarity in places.\n\nOverall, "
+                       "this response would score a band 6.5.', 'overall': 6.5, 'task_response': "
+                       "{ 'Coherence and Cohesion': 6.5, 'Grammatical Range and Accuracy': 6.0, 'Lexical Resource': 7.0, "
+                       "'Task Achievement': 7.0}}",
+        },
+        {
+            "role": "user",
+            "content": f"Evaluate this answer according to ielts grading system: {answer}",
+        },
+    ]
+    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(messages, token_count)
+    return response
 
-@app.route('/')
-def generate_summarizer(
-    max_tokens,
-    temperature,
-    top_p,
-    frequency_penalty,
-    prompt,
-    person_type,
-):
-    res = openai.ChatCompletion.create(
-        model="gpt-3.5-turbo",
-        max_tokens=100,
-        temperature=0.7,
-        top_p=0.5,
-        frequency_penalty=0.5,
-        messages=
-       [
-         {
-          "role": "system",
-          "content": "You are a helpful assistant for text summarization.",
-         },
-         {
-          "role": "user",
-          "content": f"Summarize this for a {person_type}: {prompt}",
-         },
-        ],
-    )
-    return res["choices"][0]["message"]["content"]
 
 if __name__ == '__main__':
     app.run()