Develop an AI Test Generation Bot that:

$$ Accepts multiple PDF files as input.

$$ Extracts relevant information and creates vector embeddings using Google

embeddings model and stores it in a vector database$($Pinecone$,$ Chroma etc$).$

$$ Generates objective or subjective test questions along with answers based on

user$-$specified topics, chapters, subjects, or class level through LLM$+$Semantic search

on the vector embeddings.

Specific Requirements:

PDF Processing:

$$ Implement robust PDF parsing techniques to extract text and structure accurately.

$$ Handle diverse PDF formats and layouts effectively.

Embedding Generation:

$$ Utilize any embedding model$($like Google$$s latest $001$ model$)$ understanding

capabilities to create comprehensive text embeddings.

$$ Integrate Langchain for semantic knowledge graph construction and reasoning.

$$ Incorporate Google embeddings for additional semantic context.

Test Question Generation:

$$ Develop algorithms through function calling to generate diverse and challenging test

questions aligned with specified topics and difficulty levels.

$$ Ensure questions are grammatically correct and semantically meaningful.

$$ Offer the ability to create both objective $($multiple choice, true$/$false$,$ fill$-$in$-$the$-$blank$)$

and subjective $($essay$-$style$)$ questions.

User Interface:

Design an intuitive interface for:

$$ Uploading PDF files.

$$ Specifying topics, chapters, subjects, and class levels.

$$ Generating and viewing test questions..

$$ Potentially exporting generated tests as PDF or other formats.

so please write full code for above task in node js and frontend in react and use google api more