Full Stack AI Agent Template

Abstract

1. Introduction

Production-ready FastAPI + Next.js project generator with AI agents, RAG, and 20+ enterprise integrations.

5 AI Agent Frameworks (PydanticAI, PydanticDeep, LangChain, LangGraph, DeepAgents) RAG Pipeline (Milvus, Qdrant, pgvector, ChromaDB) FastAPI + Next.js 15 (WebSocket streaming, real-time chat UI) Conversation Sharing (direct sharing, public links, admin browser) Enterprise-Ready (JWT, OAuth, admin panel, Celery, Docker, K8s)

2. Objective

Full-stack AI app generator — FastAPI + Next.js with AI Agents, RAG, streaming, auth, and 20+ integrations out of the box.

This project demonstrates how Python, Docker, FastAPI can be applied to a real-world Full Stack Web Development problem.

3. Key Features / Modules

• Document parsing - PDF (PyMuPDF with tables, headers/footers, OCR), DOCX, TXT, MD + 130+ formats via LlamaParse
• Image description - Extract images from documents, describe via LLM vision API (opt-in)
• Chunking - RecursiveCharacterTextSplitter with configurable size/overlap
• Reranking - Cohere API or local CrossEncoder for improved search quality
• Agent integration - All 5 AI frameworks get a search_knowledge_base tool automatically

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Python 3.8 or later
• pip / virtualenv for dependencies
• VS Code, PyCharm or Jupyter Notebook
• Node.js (LTS) and npm / yarn / pnpm
• VS Code or any code editor
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/vstorm-co/full-stack-ai-agent-template.git
cd full-stack-ai-agent-template

# pip
pip install fastapi-fullstack

# uv (recommended)
uv tool install fastapi-fullstack

# pipx
pipx install fastapi-fullstack

# Automatic instrumentation in app/main.py
import logfire

logfire.configure()
logfire.instrument_fastapi(app)
logfire.instrument_asyncpg()
logfire.instrument_redis()
logfire.instrument_httpx()

# Manual spans for custom logic
with logfire.span("process_order", order_id=order.id):
    await validate_order(order)
    await charge_payment(order)
    await send_confirmation(order)

# Without this template, you'd need to manually:
# 1. Set up FastAPI project structure
# 2. Configure SQLAlchemy + Alembic migrations
# 3. Implement JWT auth with refresh tokens
# 4. Build WebSocket streaming for AI responses
# 5. Integrate PydanticAI/LangChain with tool calling
# 6. Set up RAG pipeline (parsing, chunking, embedding, vector store)
# 7. Configure Celery + Redis for background tasks
# 8. Build Next.js frontend with auth and chat UI
# 9. Write Docker Compose for all services
# 10. Add observability, rate limiting, admin panel...

# With this template:
pip install fastapi-fullstack
fastapi-fullstack
# Done. All of the above, configured and working.

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Add role-based access control
• Deploy on a VPS or cPanel hosting with a custom domain
• Add automated tests and a CI pipeline

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. Explain the frontend, backend and database layers of this application.
2. How is user authentication and authorisation implemented?
3. Describe the main database tables / collections and their relationships.
4. Which REST APIs or routes are exposed and what do they return?
5. How would you deploy this application to production?

9. Source Code & License

This project is developed by vstorm-co and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.