SyllabAI: Study Smarter with Your Syllabus

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Overview

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Get Started

git clone https://github.com/Alchemyst-ai/SyllabAI.git
cd SyllabAI
npm install       # or: pnpm install
cp .env.example .env
npm run dev       # app starts at http://localhost:3000 (default)

⚡ After setup, upload a small test syllabus at /upload and visit /chat to interact.

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How It Works ?

1. Prepare your syllabus – Export or collect your syllabus in PDF, DOCX or TXT.
2. Upload – Use the Upload page to send the file to the backend extraction endpoint.
3. Extract & Index – Backend extracts text and adds it to a document store (or index) via /context/add.
4. Ask – Use the Chat UI to ask questions; the backend generates responses grounded in the indexed syllabus.

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Environment Variables

NEXT_PUBLIC_BACKEND_URL=https://your-backend.example.com
NEXT_PUBLIC_API_KEY=your_api_key_here
# Optional: configure timeouts, storage endpoints, and dev ports

⚠️ Keep keys and secrets out of version control.

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Code Structure

Root Directory
├── app/                 # Next.js app (pages & routes)
│   ├── page.tsx         # Landing
│   ├── upload/page.tsx  # Upload UI and client-side flow
│   └── chat/page.tsx    # Chat UI and message handling
├── components/          # Reusable UI components
│   ├── file-upload.tsx
│   ├── chat-message.tsx
│   └── document-viewer.tsx
├── lib/                 # Utility helpers
├── public/              # Static assets
├── styles/              # Tailwind / CSS
├── package.json         # Scripts & dependencies
└── README.md            # Project README

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Architecture & Flow

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1. Frontend

• app/upload/page.tsx — file upload, validation, and /upload call
• app/chat/page.tsx — chat UI, fetch document, send chat_history
• components/* — UI primitives (file upload, message, viewer)

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2. Backend (integration)

• POST /upload — Accepts multipart/form-data (file), returns { text }.
• POST /context/add — Accepts documents payload to index/store content.
• POST /chat/generate — Accepts a chat_history and returns a generated response object.

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3. Storage / Indexing

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4. Configuration

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Core Features

• Upload PDF / DOCX / TXT syllabus files
• Extract and index content for retrieval
• Chat UI that answers questions grounded in the syllabus
• Modular frontend that can work with different backends

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API Endpoints

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Documents

• POST /upload — Upload a file (FormData) and receive extracted text { "text": "..." }.
• POST /context/add — Add documents for indexing: { documents: [{ content, fileName, fileType, fileSize, name }], source, context_type }.

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Chat

• POST /chat/generate — Generate an assistant response from chat_history and options. The UI expects response content at result.response.kwargs.content.

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Example HTTP requests

1. Upload (curl)

curl -X POST "$NEXT_PUBLIC_BACKEND_URL/upload" \
    -H "Authorization: Bearer $NEXT_PUBLIC_API_KEY" \
    -F "file=@/path/to/syllabus.pdf"

{ "text": "This is mock extracted text from syllabus.pdf" }

2. Context add (curl)

curl -X POST "$NEXT_PUBLIC_BACKEND_URL/context/add" \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer $NEXT_PUBLIC_API_KEY" \
    -d '{ "documents": [{ "content": "<extracted text>", "fileName": "syllabus.pdf", "name": "Intro to CS" }], "source": "user-upload", "context_type": "resource" }'

{ "success": true, "documentId": "doc_12345" }

3. Chat generate (curl)

curl -X POST "$NEXT_PUBLIC_BACKEND_URL/chat/generate" \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer $NEXT_PUBLIC_API_KEY" \
    -d '{ "chat_history": [{ "type": "human", "id": "1", "lc_kwargs": { "content": "What are the grading policies?" } }] }'

{
    "result": {
        "response": {
            "kwargs": {
                "content": "The grading policy is: Assignments 40%, Midterm 30%, Final 30%."
            }
        }
    }
}

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Troubleshooting

• 400/401 errors: verify NEXT_PUBLIC_BACKEND_URL and NEXT_PUBLIC_API_KEY.
• Empty chat responses: ensure the document was added via /context/add and the backend returns embeddings or indexed content.
• Upload parsing errors: check backend logs for file parser issues (unsupported PDF structure or encoding).

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How to run & deploy

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Run locally

npm install
npm run dev       # development server
npm run build
npm run start     # production

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Testing

• Upload a short syllabus (~1–3 pages) and ask a few questions in the chat UI.
• Optionally add unit/integration tests for upload and chat API integrations.

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Security & Best Practices

• Keep API keys secret and use server-side auth where possible.
• Validate and sanitize uploads server-side to prevent malicious files.
• Rate-limit generation endpoints and monitor usage.

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Benefits

1. Fast to set up and test — a minimal frontend that integrates with any compatible backend.
2. Focused UX for syllabus-driven learning.
3. Easily extensible — swap or enhance the backend for improved retrieval and generation.