Complete Guide to Build and Deploy an AI Agent with Docker Containers and Python

If you've ever thought about learning Docker for development and production, this is the course for you. 

🔗 References and Links
- Course Code: https://github.com/codingforentrepreneurs/build-deploy-ai-agent-python-docker
- Python Gmail Inbox Code: https://github.com/codingforentrepreneurs/gmail-inbox-reader-python
- Docker Desktop: https://www.docker.com/products/docker-desktop/
- Docker Hub: https://hub.docker.com/
- Docker Model Runner: https://docs.docker.com/ai/model-runner/
- Railway: https://kirr.co/wxfp4a
- DigitalOcean Promo: https://do.co/cfe-youtube
- FastAPI: https://fastapi.tiangolo.com/
- SQLModel: sqlmodel.tiangolo.com/
- LangGraph: https://www.langchain.com/langgraph
- FastAPI Analytics Code: https://github.com/codingforentrepreneurs/analytics-api
- FastAPI Analytics Course: https://www.youtube.com/watch?v=tiBeLLv5GJo&feature=youtu.be (in-depth SQLModel and Time Series)
- Google Gmail App Password: https://myaccount.google.com/apppasswords

👉 Topics Covered:

✅ Docker Fundamentals
✅ Create a custom Dockerfile
✅ Pushing to Docker Hub
✅ Using Docker Compose
✅ Running Static HTML with Docker
✅ How to use Public Open Source Docker Containers (postgres, redis, etc)
✅ Build Custom Docker Images
✅ Unlock Docker Compose Watch Mode for effective Development
✅ Benefits of the dockerignore file
✅ Mount and persist data with volumes in containers
✅ Hello World with Docker and FastAPI
✅ Unlock Deployment options
✅ Deploy to Railway with your Dockerfile (same as digitalocean)
✅ Deploy to DigitalOcean with your Dockerfile (same as railway)
✅ Integrate Postgres to FastAPI through Docker
✅ Inject runtime environment variables with env files
✅ Run open-source models directly with Docker Model Runner via Docker Desktop
✅ Learn how to nest API routes with FastAPI
✅ Integrate LangChain with FastAPI
✅ Use and manually run tools with LangChain-based AI Models
✅ Use LangGraph to use and run tools automatically
✅ Build a multi-agent system with LangGraph Supervisor
✅ Send emails through Gmail and Python's standard library
✅ Read email inbox with Gmail and Python
✅ Test production-level API calls from Docker, FastAPI, OpenAI, and LangGraph

Chapters:
00:00:00 Welcome
00:02:47 Demo & Software Overview
00:06:23 Docker at a Glance
00:10:13 Install Docker
00:14:45 Docker Run
00:21:57 Build your First Docker Container
00:27:26 Publish on Docker Hub
00:33:05 Accessing Python Web Servers in Docker
00:37:08 Your First Docker Compose Service
00:45:26 Build Custom Image with Docker Compose
00:47:49 Configure Dockerfile to Render HTML
00:54:35 Copy Local Files to Docker Container
01:00:38 Moving the Dockerfile and Build Context
01:04:19 Volumes for Containers during Development
01:08:51 Hello World with Docker and FastAPI
01:23:31 Docker Compose Watch Mode
01:28:15 Docker Ignore File and Volumes
01:35:19 Injecting Passwords and Secrets at Runtime
01:46:16 Basics of Pushing Code to GitHub
01:56:10 The Process of Deploying with Containers
01:59:12 Deploy Docker & FastAPI to Railway
02:11:42 Deploy Docker & FastAPI to DigitalOcean App Platform
02:21:22 Compose with Postgres & Docker-Managed Volumes
02:30:29 Integrate Postgres with FastAPI and SQLModel
02:38:51 Your First Database Model
02:43:25 Nested API Route in FastAPI
02:46:31 Create Chat Message Route
02:54:03 Create & List Data with Curl
02:59:52 Deploy with Timestamp Field
03:11:59 Docker Model Runner
03:18:31 LangChain with Docker Model Runner
03:26:02 Structured Output with LangChain
03:29:59 LangChain with FastAPI and SQLModel
03:37:43 Deploy LangChain with DigitalOcean and OpenAI
03:42:07 Sending Email with Python and FastAPI
03:51:14 View Emails in Gmail Inbox with Python
03:58:29 Tools for Ai Agents with LangChain
04:05:31 Executing Tool Calls with LangChain
04:17:24 LangGraph Agent and Tool Calling
04:23:51 LangGraph Research Agent
04:26:52 Connecting Multiple Agents with LangGraph Supervisor
04:34:22 Runnable Config with LangChain Tools
04:39:15 LangGraph Supervisor as FastAPI Endpoint
04:44:26 Deploy LangGraph Supervisor
04:47:46 Thank you & Next Steps

YouTube

A comprehensive guide covering Docker fundamentals and building AI agents with Python. Starts with Docker basics including container creation, image building, and Docker Compose usage. Progresses through setting up FastAPI web applications, integrating databases, and ultimately implementing AI agents using Langchain and Langraph. Covers both local development with Docker containers and deployment strategies using services like Railway and Digital Ocean. Demonstrates how to use both managed LLM services and open-source AI models available through DockerHub.