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
# 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
# Install the Graphlit client
dotnet add package Graphlit.Client
# Run the CLI tool
cd graphlit-samples/dotnet/GraphlitIngest
dotnet run
Upload PDFs, audio, video and chat with them using RAG
cd nextjs/chat
npm install && npm run devFeatures:
- Multi-format support (PDF, DOCX, audio, video)
- Real-time streaming responses
- Conversation history
- Source citations
Extract clean Markdown from any website
cd nextjs/web-extraction
npm install && npm run devFeatures:
- Automatic web scraping
- Clean Markdown output
- Bulk processing via sitemap
- Structured data extraction
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
| Use Case | Best Sample | Key Features |
|---|---|---|
| Customer Support Bot | Next.js Chat | Document Q&A, Citations, Multi-tenant |
| Content Intelligence | Web Extraction | Scraping, Structured extraction, Bulk processing |
| Meeting Analysis | Audio Transcription Notebook | Transcription, Summarization, Entity extraction |
| Knowledge Base Search | Streamlit Apps | Semantic search, Filters, RAG |
| Document Processing | .NET CLI | Bulk ingestion, Enterprise scale, Automation |
New to Graphlit? Follow this path:
-
Start with Python Notebooks – No setup, run in Google Colab
- Begin with basic ingestion and search
- Progress to RAG and conversations
- Browse Notebooks →
-
Build a Streamlit App – Interactive UI examples
- Upload files and chat
- Web crawling demos
- Browse Streamlit Apps →
-
Deploy a Next.js Application – Production-ready examples
- Deploy to Vercel in minutes
- Customize for your use case
- Browse Next.js Apps →
-
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!
- Fork this repository
- Create your sample in the appropriate directory
- Include a README with setup instructions
- 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.
| DIY Approach | 🚀 Graphlit |
|---|---|
| Stitch together vector DB, storage, embeddings | Complete integrated platform |
| Manage your own infrastructure | Fully managed, serverless |
| Limited file format support | True multimodal from day one |
| Build your own ingestion pipelines | Automated ETL for any format |
| Handle scaling yourself | Scales automatically |
| Weeks of setup | Running in 5 minutes |
- 💬 Discord: Join our community
- 📧 Email: [email protected]
- 📖 Docs: docs.graphlit.dev
- 🐛 Issues: GitHub Issues
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