Spaces:
Sleeping
Sleeping
| import json | |
| from fastapi import FastAPI, HTTPException | |
| from pydantic import BaseModel | |
| import openai | |
| from typing import List, Dict, Any | |
| import os | |
| app = FastAPI() | |
| # Pydantic models for request body | |
| class StudyInput(BaseModel): | |
| overall_study_pattern: str | |
| memorization_study_pattern: str | |
| problem_solving_study_pattern: str | |
| visualization_study_pattern: str | |
| obstacle_study_pattern: str | |
| new_topic_approach: str | |
| old_topic_approach: str | |
| topic_ratio: str | |
| hours_of_study: str | |
| hours_of_study_weekends: str | |
| revision_days: str | |
| test_days: str | |
| physicsStartIndex: int | |
| chemistryStartIndex: int | |
| mathematicsStartIndex: int | |
| completed_phy_chapters: List[str] | |
| completed_chem_chapters: List[str] | |
| completed_maths_chapters: List[str] | |
| currentDate: str | |
| # Function to remove completed chapters | |
| def remove_completed_chapters(subject_data, completed_chapters): | |
| subject_data["chapters"] = [chapter for chapter in subject_data["chapters"] | |
| if chapter["chapter"] not in completed_chapters] | |
| return subject_data | |
| # Function to get data at index | |
| def get_data_at_index(json_data, index): | |
| if 0 <= index < len(json_data['chapters']): | |
| return json_data['chapters'][index] | |
| else: | |
| return {} | |
| async def generate_roadmap(study_input: StudyInput): | |
| # Load JSON data for each subject | |
| # Note: You'll need to adjust the file paths or include these JSON files in your Docker image | |
| with open('Physics.json', 'r', encoding='utf-8') as file: | |
| phy = json.load(file) | |
| with open('Chemistry.json', 'r', encoding='utf-8') as file: | |
| chem = json.load(file) | |
| with open('Maths.json', 'r', encoding='utf-8') as file: | |
| maths = json.load(file) | |
| # Remove completed chapters | |
| phy = remove_completed_chapters(phy, study_input.completed_phy_chapters) | |
| chem = remove_completed_chapters(chem, study_input.completed_chem_chapters) | |
| maths = remove_completed_chapters(maths, study_input.completed_maths_chapters) | |
| # Get data at specified indices | |
| phy = get_data_at_index(phy, study_input.physicsStartIndex) | |
| chem = get_data_at_index(chem, study_input.chemistryStartIndex) | |
| maths = get_data_at_index(maths, study_input.mathematicsStartIndex) | |
| # Prepare user persona | |
| user_persona = f""" | |
| You are required to generate a highly personalized roadmap for a student studying Physics, Chemistry, and Mathematics for the JEE Main exam. | |
| The roadmap should be tailored based on the following student-specific details: | |
| 1. *Study Preferences:* | |
| - Study Pattern: {study_input.overall_study_pattern} | |
| - Memorization Approach: {study_input.memorization_study_pattern} | |
| - Problem-Solving Approach: {study_input.problem_solving_study_pattern} | |
| - Visualization Approach: {study_input.visualization_study_pattern} | |
| 2. *Handling Challenges:* | |
| - If unable to understand a topic: {study_input.obstacle_study_pattern} | |
| - Approach to New Topics: {study_input.new_topic_approach} | |
| - Approach to Previously Encountered Topics: {study_input.old_topic_approach} | |
| 3. *Study Hours:* | |
| - Weekdays: {study_input.hours_of_study} hours/day | |
| - Weekends: {study_input.hours_of_study_weekends} hours/day | |
| - Time Allocation Ratio (Physics:Chemistry:Mathematics): {study_input.topic_ratio} | |
| - By weekdays I mean day 1, day 2 , day 3 , day 4 , day 5 | |
| - By weekends I mean day 6 , day 7 | |
| 4. *Revision and Test Strategy:* | |
| - The days of the week when you do revision : {study_input.revision_days} | |
| - The days of the week when you give tests : {study_input.test_days} | |
| """ | |
| output_structure = """{ | |
| "schedule": [ | |
| { | |
| "dayNumber": int, | |
| "date":YYYY-MM-DD | |
| "subjects": [ | |
| { | |
| "name": "string", | |
| "tasks": [ | |
| { | |
| "ChapterName": "string", | |
| "type": "string", | |
| "topic": "string", | |
| "time": "string" | |
| } | |
| ] | |
| } | |
| ] | |
| } | |
| ] | |
| } | |
| """ | |
| # Prepare system prompt | |
| sys_prompt = f""" | |
| You are required to generate a highly personalized roadmap for a student studying Physics, Chemistry, and Mathematics for the JEE Main exam. | |
| The roadmap should be tailored based on the following student-specific details: | |
| The roadmap must be provided in the following format: | |
| {output_structure} | |
| Do not include anything other than the roadmap, and ensure the focus remains strictly on the subjects {phy}, {chem}, and {maths} and associated chapters. | |
| MAKE SURE THAT YOU MAKE THE ROADMAP FOR ALL THE THREE CHAPTERS EACH OF PHYSICS , CHEMISTRY AND MATHS TO COMPLETE THOSE CHAPTERS WITH 4 ASPECTS i.e "CONCEPT UNDERSTANDING","QUESTION PRACTICE","REVISION","TEST". ALSO INCLUDE TIME FOR EACH TASK THAT YOU GENERATE | |
| MAKE SURE THAT WE FIRST COMPLETE 1) CONCEPT UNDERSTANDING , 2) QUESTION PRACTICE FOR EVERY SUBTOPIC AND THEN REVISION AND TEST FOR WHOLE CHAPTER TOGETHER. | |
| MAKE SURE THAT WE INCULDE EACH SUBTOPIC OF EACH CHAPTER FROM {phy},{chem} and {maths} IS FINISHED | |
| YOU ARE NOT CONSTRAINED TO CREATE A ROADMAP FOR ONLY 'X' NUMBER OF DAYS , YOU CAN EXTEND TILL THE TOPICS ARE FINISHED BUT ONLY STICK TO THE TIMEFRAME ALLOTED FOR EACH SUBJECT AND DO NOT GO ABOVE OR BELOW THAT TIME FRAME. | |
| Make sure you make the roadmap for 7-10 days only. | |
| Make Sure that you start the roadmap date from the date the roadmap is generated (Current Date : {study_input.currentDate}) | |
| Make Sure you newer leave any field empty | |
| Make Sure that you take care of the year in the date entry for example you are generating a roadmap from 30-12-2024 for 8 days then you must chnage the year after 31-12-2024 to 2025. | |
| """ | |
| # Make OpenAI API call | |
| openai.api_key = os.getenv("KEY") # Replace with your actual API key or use environment variables | |
| try: | |
| response = openai.ChatCompletion.create( | |
| model="gpt-4o-mini", | |
| messages=[ | |
| { | |
| "role": "system", | |
| "content": sys_prompt + "MAKE SURE YOU VERY VERY STRUCTLY FOLLOW THE JSON STRUCTURE BECAUSE I WILL PARSE YOUR OUTPUT TO JSON" | |
| }, | |
| { | |
| "role": "user", | |
| "content": user_persona | |
| } | |
| ] | |
| ) | |
| answer = response['choices'][0]['message']['content'].strip() | |
| # Second OpenAI API call | |
| response = openai.ChatCompletion.create( | |
| model="gpt-4o-mini", | |
| messages=[ | |
| { | |
| "role": "system", | |
| "content": f''' | |
| you created a very good roadmap {answer} but you make sure that you dont forget any subtopics from Physics : {phy}, Chemistry : {chem} and Maths : {maths}. ensure that the style is same as the previous roadmap. | |
| MAKE SURE YOU VERY VERY STRUCTLY FOLLOW THE JSON STRUCTURE BECAUSE I WILL PARSE YOUR OUTPUT TO JSON. | |
| DO not include json at the top of the answer | |
| ''' | |
| }, | |
| { | |
| "role": "user", | |
| "content": "Generate the roadmap, and follow the output format very very very strictly" | |
| } | |
| ] | |
| ) | |
| final_answer = response['choices'][0]['message']['content'].strip() | |
| parsed_json = json.loads(final_answer) | |
| return parsed_json | |
| except Exception as e: | |
| raise HTTPException(status_code=500, detail=str(e)) | |
| if __name__ == "__main__": | |
| import uvicorn | |
| uvicorn.run(app, host="0.0.0.0", port=8000) | |