updated questions generator

test.py

@@ -1,3 +1,78 @@
 import os
-API_KEY = "erp_" + os.urandom(16).hex() 
-print(API_KEY)
+import json
+import asyncio
+from openai import AsyncOpenAI
+from pydantic import BaseModel, Field
+from typing import List, Dict, Optional
+from src.prompts.sops import *
+from src.models.questions_response import *
+from src.services.sop_document_parser import DocumentParser
+from src.prompts.questions import *
+from dotenv import load_dotenv
+
+load_dotenv()
+
+class QuestionsGenerator:
+    def __init__(self):
+        self.api_key = os.getenv("OPENAI_API_KEY")
+        self.client = AsyncOpenAI(api_key=self.api_key)
+        self.model = "gpt-4o-mini"
+
+    async def generate_single_frequency_questions(self, docs, assessment_type, frequency_number, total_duration):
+        prompt = get_questions_prompt_v3()
+        frequency_label = f"{assessment_type} number : {frequency_number}"
+
+        response = await self.client.chat.completions.create(
+            model=self.model,
+            messages=[
+                {"role": "system", "content": prompt},
+                {"role": "user", "content": f"The SOPs are provided below."},
+                {"role": "user", "content": json.dumps(docs)},
+                {"role": "user", "content": f"Assessment Type: {assessment_type}"},
+                {"role": "user", "content": f"Current Frequency Number to generate: {frequency_label}"},
+                {"role": "user", "content": f"Duration: {total_duration}"}
+            ],
+            temperature=0.1,
+            response_format={ "type": "json_object" },
+            max_tokens=10000
+        )
+
+        questions_json = json.loads(response.choices[0].message.content)
+        return questions_json
+
+    async def generate_questions(self, input_data: Dict) -> AssessmentQuestions:
+        try:
+            sops = input_data['sops']
+            assessment_type = input_data['assessment_type']
+            total_duration = input_data['duration']
+
+            chunk_size = 1000
+            docs_text = [sops[i:i + chunk_size] for i in range(0, len(sops), chunk_size)]
+            docs = [{"type": "text", "text": text} for text in docs_text]
+
+            tasks = []
+            for frequency_number in range(1, total_duration + 1):
+                task = self.generate_single_frequency_questions(docs, assessment_type, frequency_number, total_duration)
+                tasks.append(task)
+
+            all_questions = await asyncio.gather(*tasks)
+
+            return AssessmentQuestions(questions=Questions(questions=all_questions))
+
+        except Exception as e:
+            print(f"An error occurred: {e}")
+            return None
+
+# Usage
+async def main():
+    generator = QuestionsGenerator()
+    input_data = {
+        "sops": "Your SOP text here",
+        "assessment_type": "weekly",
+        "duration": 4
+    }
+    result = await generator.generate_questions(input_data)
+    print(result)
+
+if __name__ == "__main__":
+    asyncio.run(main())