| import json |
| from langchain.document_loaders import PyPDFLoader |
| from models import ExtractionResult, EvaluationResult |
| from llm import get_llm |
|
|
| llm = get_llm() |
|
|
| def extract_answers_from_pdf(pdf_path: str) -> ExtractionResult: |
| """ |
| Loads a PDF, extracts its content, and uses the LLM to output a JSON of the answers. |
| """ |
| loader = PyPDFLoader(pdf_path) |
| pages = loader.load_and_split() |
| all_page_content = "\n".join(page.page_content for page in pages) |
| |
| |
| extraction_schema = ExtractionResult.model_json_schema() |
| system_message = ( |
| "You are a document analysis tool that extracts the options and correct answers from the provided document content. " |
| "The output must be a JSON object that strictly follows the schema: " + json.dumps(extraction_schema, indent=2) |
| ) |
| user_message = ( |
| "Please extract the correct answers and options (A, B, C, D, E) from the following document content:\n\n" |
| + all_page_content |
| ) |
| prompt = system_message + "\n\n" + user_message |
| |
| response = llm.invoke(prompt, response_format={"type": "json_object"}) |
| result = ExtractionResult.model_validate_json(response.content) |
| return result |
|
|
| def evaluate_student(answer_key: ExtractionResult, student: ExtractionResult) -> EvaluationResult: |
| """ |
| Compares the answer key with a student's answers and returns the evaluation result. |
| """ |
| evaluation_schema = EvaluationResult.model_json_schema() |
| system_message = ( |
| "You are an academic evaluation tool that compares the answer key with a student's answers. " |
| "Calculate the total marks, grade, and percentage based on the provided JSON objects. " |
| "The output must be a JSON object that strictly follows the schema: " + json.dumps(evaluation_schema, indent=2) |
| ) |
| user_message = ( |
| "Answer Key JSON:\n" + json.dumps(answer_key.model_dump(), indent=2) + "\n\n" |
| "Student Answer JSON:\n" + json.dumps(student.model_dump(), indent=2) |
| ) |
| prompt = system_message + "\n\n" + user_message |
| |
| response = llm.invoke(prompt, response_format={"type": "json_object"}) |
| evaluation_result = EvaluationResult.model_validate_json(response.content) |
| return evaluation_result |
|
|
