main.py

from fastapi import FastAPI, Request
import openai
from pydantic import BaseModel
import os

# Define a Pydantic model for the input
class RoadmapLogs(BaseModel):
    roadmap_logs: str

# Initialize the FastAPI app
app = FastAPI()

# Define OpenAI API key (replace this with your method to fetch the key, such as an environment variable)
openai.api_key = os.getenv('RaghavOPENAIKey')

# Define the prompt and system role
role = """You are an expert assistant who analyzes student performance on their study roadmap and provides insights based on their behavior. 
If the student has rushed through tasks, make them feel guilty. If they have done a good job, appreciate them but still remind them about deep learning and mastery. 
MAKE SURE YOU VERY STRICTLY FOLLOW THE OUTPUT STRUCTURE THAT IS 'AI Insight Heading:AI Insight Description'"""

@app.post("/generate_insight")
async def generate_insight(request: RoadmapLogs):
    prompt = f""" I am giving you some logs for a roadmap feature {request.roadmap_logs}. Your task is to analyze them and answer my queries.
                  'Checked' means the task is completed.
                  Make sure to include the topic details that they have left out.
                  Always start with a rhetorical question in the case of negative feedback and a compliment in case of positive feedback. 
                  Make sure to instill a sense of guilt in them while also acting as a benevolent guide.
                  Make sure the insight reflects their approach, score and behavior accordingly.
                  If you dont recieve any logs then motivate the user.
                  If you dont revive any logs and just roadmap structure that means the user has not done any tasks it doesnt mean that he/she has completed all of them it means they have not done even a single task.
                  MAKE SURE YOU DONT GIVE ANY THING ELSE IN THE OUTPUT APART FROM THE STRUCTURE.
                  MAKE SURE YOU THAT YOU GIVE ME ONLY TWO THINGS 1) AI Insight Heading and 2) The AI Insight description.
                  MAKE SURE YOU FOLLOW THE FOLLOWING OUTPUT STRCUTURE:
                  The heading should be a very short 2,3 line summary of the description
                  output_structure:
                  '"AI Insight Heading":"AI Insight Description"'
              """
    # Call OpenAI API
    response = openai.ChatCompletion.create(
        model="gpt-4o-mini",
        messages=[
            {"role": "system", "content": role},
            {"role": "user", "content": prompt}
        ]
    )

    # Extract and return the insight
    answer = response['choices'][0]['message']['content'].strip()
    return {"AI_Insight": answer}