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Update main.py
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main.py
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# main.py
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from fastapi import FastAPI, HTTPException
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from pydantic import BaseModel
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from typing import Dict
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import os
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from groq import Groq
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app = FastAPI()
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# Pydantic model for request
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class ScoreInput(BaseModel):
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score_percentages: Dict[str, float]
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time_percentages: Dict[str, float]
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# Helper functions
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def get_final_score(score_percentages: Dict[str, float], time_percentages: Dict[str, float]) -> Dict[str, float]:
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final_score = {}
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for skill in score_percentages:
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score_avg = (score_percentages[skill] + time_percentages[skill]) / 2
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final_score[skill] = score_avg
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return final_score
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def get_strengths_and_weaknesses(final_score: Dict[str, float]):
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sorted_skills = sorted(
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[(skill, score) for skill, score in final_score.items()],
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key=lambda item: item[1],
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reverse=True
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)
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num_skills = len(sorted_skills)
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if num_skills == 0:
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return [], [], []
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split1 = num_skills // 3
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split2 = 2 * (num_skills // 3)
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strengths = sorted_skills[:split1]
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opportunities = sorted_skills[split1:split2]
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challenges = sorted_skills[split2:]
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return strengths, opportunities, challenges
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# FastAPI route
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@app.post("/analyze")
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async def analyze_scores(input_data: ScoreInput):
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final_score = get_final_score(input_data.score_percentages, input_data.time_percentages)
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strengths, opportunities, challenges = get_strengths_and_weaknesses(final_score)
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# Groq API call
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api_key = os.getenv("GROQ_API_KEY")
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if not api_key:
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raise HTTPException(status_code=500, detail="Groq API key not found")
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client = Groq(api_key=api_key)
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sys_prompt = f"""You are an advanced language model trained to analyze student responses from a questionnaire on Academic, Cognitive, and Study Profile aspects related to JEE Mains preparation. Your task is to generate a personalized SCO (Strengths, Challenges, Opportunities) analysis and an Action Plan section based on the user's inputs.
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You have been provided with the strengths {strengths}, Opportunities {opportunities} and Challenges {challenges} skills of the user
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Output Structure:
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SCO Analysis:
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Strengths:
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- List the student's strengths based on their {strengths} skills
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- Let the student now how they can use these strengths in their JEE preparation and exam to improve their score.
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- Also tell them how do they improve their score more.
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Opportunities:
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- List the student's strengths based on their {opportunities} skills
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- Suggest opportunities for improvement by leveraging the student's strengths and addressing their challenges.
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- Recommend ways to enhance their score in the {opportunities} skills.
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- Also tell them if they improve in these skills what opportunities they have in improving their scores
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Challenges:
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- List the student's strengths based on their {challenges} skills
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- Guide the student that these skills are basically the core area where they are lacking
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- Tell them that if they continue not focusing upon them they might get far away from their JEE goal.
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Action Plan:
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- Provide a detailed plan to the student to improve in the {challenges} skills.
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- Recommend targeted strategies, resources, and techniques to improve their {challenges} skills.
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- Let them know if they improve these areas how it can help boost their scores and make their preparation more effective.
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- Incorporate time management, revision, and test-taking strategies specific to JEE Mains and the identified subjects/topics/subtopics.
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uvicorn.run(app, host="0.0.0.0", port=8000)
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# main.py
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from fastapi import FastAPI, HTTPException
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from pydantic import BaseModel
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from typing import Dict
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import os
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from groq import Groq
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app = FastAPI()
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# Pydantic model for request
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class ScoreInput(BaseModel):
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score_percentages: Dict[str, float]
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time_percentages: Dict[str, float]
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# Helper functions
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def get_final_score(score_percentages: Dict[str, float], time_percentages: Dict[str, float]) -> Dict[str, float]:
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final_score = {}
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for skill in score_percentages:
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score_avg = (score_percentages[skill] + time_percentages[skill]) / 2
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final_score[skill] = score_avg
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return final_score
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def get_strengths_and_weaknesses(final_score: Dict[str, float]):
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sorted_skills = sorted(
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[(skill, score) for skill, score in final_score.items()],
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key=lambda item: item[1],
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reverse=True
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)
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num_skills = len(sorted_skills)
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if num_skills == 0:
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return [], [], []
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split1 = num_skills // 3
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split2 = 2 * (num_skills // 3)
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strengths = sorted_skills[:split1]
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opportunities = sorted_skills[split1:split2]
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challenges = sorted_skills[split2:]
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return strengths, opportunities, challenges
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# FastAPI route
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@app.post("/analyze")
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async def analyze_scores(input_data: ScoreInput):
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final_score = get_final_score(input_data.score_percentages, input_data.time_percentages)
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strengths, opportunities, challenges = get_strengths_and_weaknesses(final_score)
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# Groq API call
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api_key = os.getenv("GROQ_API_KEY")
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if not api_key:
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raise HTTPException(status_code=500, detail="Groq API key not found")
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client = Groq(api_key=api_key)
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sys_prompt = f"""You are an advanced language model trained to analyze student responses from a questionnaire on Academic, Cognitive, and Study Profile aspects related to JEE Mains preparation. Your task is to generate a personalized SCO (Strengths, Challenges, Opportunities) analysis and an Action Plan section based on the user's inputs.
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You have been provided with the strengths {strengths}, Opportunities {opportunities} and Challenges {challenges} skills of the user
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Output Structure:
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SCO Analysis:
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Strengths:
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- List the student's strengths based on their {strengths} skills
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- Let the student now how they can use these strengths in their JEE preparation and exam to improve their score.
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- Also tell them how do they improve their score more.
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Opportunities:
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- List the student's strengths based on their {opportunities} skills
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- Suggest opportunities for improvement by leveraging the student's strengths and addressing their challenges.
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- Recommend ways to enhance their score in the {opportunities} skills.
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- Also tell them if they improve in these skills what opportunities they have in improving their scores
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Challenges:
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- List the student's strengths based on their {challenges} skills
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- Guide the student that these skills are basically the core area where they are lacking
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- Tell them that if they continue not focusing upon them they might get far away from their JEE goal.
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Action Plan:
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- Provide a detailed plan to the student to improve in the {challenges} skills.
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- Recommend targeted strategies, resources, and techniques to improve their {challenges} skills.
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- Let them know if they improve these areas how it can help boost their scores and make their preparation more effective.
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- Incorporate time management, revision, and test-taking strategies specific to JEE Mains and the identified subjects/topics/subtopics.
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Things that LLM need to make sure:
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1) Your analysis and action plan should be comprehensive, consistent, and tailored to the individual student's responses while leveraging your knowledge of the JEE Mains exam context, the mapping of subjects/topics to general cognitive traits and skills, and the ability to identify overarching trends across related subjects/topics.
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2) Make sure you give very much visually appealing output , with symbols and logos.
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3) Make sure you give out output in bullet points.
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4) While entering a new line in the output use "\n" new line character.
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5) Make the output very much JEE (Joint Entrance Examination) based and give everything with context to Physics , Chemistry and Maths JEE syllabus.
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6) Use Italics, Bold and underline appropriately to improve the output more.
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"""
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try:
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chat_completion = client.chat.completions.create(
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messages=[
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{"role": "system", "content": sys_prompt},
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{"role": "user", "content": f"Generate the SOCA analysis based on the system prompt and {strengths}, {opportunities} and {challenges}. MAKE SURE WE STRICTLY FOLLOW THE STRUCTURE."},
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],
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model="llama3-70b-8192",
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)
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analysis = chat_completion.choices[0].message.content
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"Error calling Groq API: {str(e)}")
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return {"analysis": analysis}
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=8000)
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