Production-ready examples showing you how to build AI applications with semantic memory.

Learn by doing with these real-world implementations of the Graphlit Platform – from simple document Q&A to advanced RAG pipelines.

Stop reading tutorials. Start building.

These aren't toy examples – they're production-ready applications you can deploy and customize. Each sample demonstrates a specific use case, from document intelligence to media analysis to multi-tenant AI agents.

All samples use the same simple API that handles:

• ✅ Content ingestion and extraction
• ✅ Semantic search and retrieval
• ✅ RAG-powered conversations
• ✅ Multi-modal processing (PDFs, audio, video, images)
• ✅ Real-time streaming responses

Build AI assistants that understand your documents

• Next.js Chat – Upload PDFs, audio, video and chat with them
• Streamlit Document Q&A – Simple UI for document-based conversations
• Python Notebook: RAG Basics – Learn RAG fundamentals interactively

Perfect for: Customer support bots, internal knowledge assistants, document analysis

Convert any content into clean, structured data

• Next.js File Extraction – Extract Markdown from PDFs, DOCX, PPTX
• Next.js Web Extraction – Scrape and extract structured data from websites
• Python Notebook: Entity Extraction – Extract entities, relationships, and insights

Perfect for: Content pipelines, data migration, document processing

Ingest and analyze web content at scale

• Web Crawling Notebook – Crawl websites and extract knowledge
• RSS Feed Monitor – Track and analyze content feeds
• Sitemap Scraping – Bulk ingest entire websites

Perfect for: Competitive intelligence, content aggregation, research tools

Transcribe and analyze audio and video

• Audio Transcription Notebook – Transcribe podcasts, meetings, calls
• Video Processing – Extract insights from video content
• Multi-speaker Diarization – Identify and separate speakers

Perfect for: Meeting analysis, podcast search, video content platforms

Build secure, scalable applications

• .NET CLI Tool – Bulk content ingestion for enterprises
• Multi-tenant Notebook – Isolate data per organization
• RBAC Examples – Role-based access control

Perfect for: SaaS applications, enterprise deployments, B2B platforms

# Get your free Graphlit account (1GB free, no credit card)
https://portal.graphlit.dev/

# You'll need these credentials:
# - Organization ID
# - Environment ID
# - JWT Secret

# Install the Graphlit client
pip install graphlit-client

# Run any Google Colab notebook - no setup needed!
# https://github.com/graphlit/graphlit-samples/tree/main/python/Notebook%20Examples

📓 Browse Python Notebooks →

# Install the Graphlit client
npm install graphlit-client

# Clone and run any Next.js sample
git clone https://github.com/graphlit/graphlit-samples.git
cd graphlit-samples/nextjs/chat
npm install
npm run dev

🚀 Deploy to Vercel in one click – Each Next.js sample includes a deploy button

📱 Browse Next.js Apps →

# Install the Graphlit client
dotnet add package Graphlit.Client

# Run the CLI tool
cd graphlit-samples/dotnet/GraphlitIngest
dotnet run

💻 Browse .NET Examples →

Upload PDFs, audio, video and chat with them using RAG

cd nextjs/chat
npm install && npm run dev

Features:

• Multi-format support (PDF, DOCX, audio, video)
• Real-time streaming responses
• Conversation history
• Source citations

View Sample →

Extract clean Markdown from any website

cd nextjs/web-extraction
npm install && npm run dev

Features:

• Automatic web scraping
• Clean Markdown output
• Bulk processing via sitemap
• Structured data extraction

View Sample →

Transcribe and analyze audio with speaker diarization

# Run in Google Colab
# No setup required!

Features:

• Multi-speaker detection
• Automatic summarization
• Entity extraction
• Search and retrieval

Open in Colab →

New to Graphlit? Follow this path:

1. Start with Python Notebooks – No setup, run in Google Colab

   • Begin with basic ingestion and search
   • Progress to RAG and conversations
   • Browse Notebooks →

2. Build a Streamlit App – Interactive UI examples

   • Upload files and chat
   • Web crawling demos
   • Browse Streamlit Apps →

3. Deploy a Next.js Application – Production-ready examples

   • Deploy to Vercel in minutes
   • Customize for your use case
   • Browse Next.js Apps →

4. Scale with .NET – Enterprise integration

   • Bulk ingestion pipelines
   • Command-line tools
   • Browse .NET Examples →

• 📘 Platform Documentation – Complete API reference
• 🎥 Video Tutorials – Step-by-step guides
• 💬 Discord Community – Get help from the community

• Python SDK – pip install graphlit-client
• TypeScript/JavaScript SDK – npm install graphlit-client
• C# / .NET SDK – dotnet add package Graphlit.Client

• 🌐 Graphlit Website – Platform overview and pricing
• 🚀 Sign Up Free – Get started in 5 minutes
• 📊 Pricing – Free tier + usage-based plans

Have a sample application you'd like to share? We welcome contributions!

1. Fork this repository
2. Create your sample in the appropriate directory
3. Include a README with setup instructions
4. Submit a pull request

See our contribution guidelines for more details.

Graphlit is free to get started:

• ✅ 1GB storage
• ✅ 1,000 content items
• ✅ 3 feeds
• ✅ 100 conversations
• ✅ Full API access
• ✅ All content types supported

Paid plans start at $49/month with usage-based credits for additional content.

View Pricing Details →

• 💬 Discord: Join our community
• 📧 Email: support@graphlit.com
• 📖 Docs: docs.graphlit.dev
• 🐛 Issues: GitHub Issues