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Academic Content Generator

React + FastAPI + RAG + OpenAI

A web application that lets educators and students generate custom academic content using structured inputs (grade level, content type, text length, topic/standard/objective) and optional uploaded files. The system uses RAG (Retrieval-Augmented Generation) to ground outputs in trusted documents with OpenAI-powered generation.

RAG-Powered

Grounds content in trusted curriculum documents with citations

Multi-Format

Generate lessons, quizzes, stories, and assessments

Standards-Aligned

Match grade levels, objectives, and curriculum standards

Feature Overview

Core features for educational content generation

Must-Have

  • Grade level selection (K-12 + higher-ed)
  • Content type templates (story, procedural, persuasive, textbook)
  • Text length control (paragraph, page, custom word count)
  • Topic + standards + objective inputs
  • File upload for context (PDF/DOCX/TXT)
  • Generated content with citations
  • History + templates library

Nice-to-Have (Later)

  • Reading level adjustments
  • Vocabulary list constraints
  • IEP/ELL accommodations
  • Assessment item generation
  • Teacher notes generation
  • Batch generation API
  • Real-time collaborative editing

🎯Primary Users

Teachers & Instructional DesignersStudents (restricted mode)District Admins

System Architecture

Logical architecture with key components

Frontend (React)

Form-driven UI with grade, type, length, standards, and objective inputs

File upload component
Results viewer with citations
History & templates management

Backend (FastAPI)

REST APIs for generation, uploads, templates, and history management

RAG orchestration service
OpenAI integration module
Safety & moderation layer

Storage Layer

Structured data storage and vector search capabilities

PostgreSQL (users, projects, generations)
S3/Azure Blob (file storage)
pgvector/Qdrant (embeddings)

Observability

Monitoring, logging, and tracing infrastructure

Structured logs with request IDs
Token usage & cost metrics
OpenTelemetry tracing

RAG Pipeline Design

Retrieval-Augmented Generation for context-grounded outputs

Ingestion Flow

1

File Upload

Upload PDF/DOCX/TXT files and store in object storage

2

Text Extraction

Extract text and chunk into 300-800 tokens with 50-100 token overlap

3

Embedding Generation

Create embeddings using OpenAI and store in vector DB

4

Indexing Complete

Mark document indexed with metadata for retrieval

Retrieval Flow

Query Building

Topic + Objective
Standards + Grade Level
Content Type Context

Vector Search

Top K retrieval (10-20 chunks) with optional rerank

Semantic SearchBM25 HybridLLM Rerank

Context Pack with Citations

Retrieved chunks with source labels provided to generator for accurate, grounded content

API Design

RESTful FastAPI endpoints for all operations

POST
/api/generate

Generate academic content with grade, type, length, objective, and standards

Returns:output_md, citations[], tokens, cost, generation_id
POST
/api/uploads

Upload files for RAG context (multipart form data)

Returns:upload_id, status
GET
/api/uploads/{id}/status

Check ingestion status of uploaded files

Returns:upload_id, status, progress
GET
/api/generations

List generations history with filters

Returns:generations[], total, page
POST
/api/generations/{id}/regenerate

Regenerate with delta instructions (make shorter, change tone)

Returns:output_md, citations[], tokens, cost
GET
/api/templates

List saved templates and exemplars

Returns:templates[], total
POST
/api/feedback

Submit feedback for quality improvement

Returns:feedback_id, status

🔒Security Features

JWT AuthenticationRBAC (Admin/Teacher/Student)Rate LimitingAudit Logging

Key Benefits

Transform educational content creation with AI-powered generation

Rapid Content Creation

Generate lesson plans, quizzes, and study materials in minutes instead of hours

5-20s generation time3 content variantsStreaming results

Safe & Compliant

Age-appropriate content with safety filters and PII protection

Content moderationFERPA/COPPA compliantAudit trails

Standards-Aligned

Ensure content matches curriculum standards and learning objectives

K-12 standards libraryGrade-appropriateCitation-backed

Multi-User Support

Designed for teachers, students, and district administrators

Role-based accessOrg isolationUsage analytics

Implementation Timeline

8-week roadmap from MVP to production

Week 1-2
MVP Generation
Week 3-4
RAG Integration
Week 5
Templates & UI
Week 6-8
Production Ready

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