https://github.com/fullstackwithlawrence/agentic-ai-workflow

Example agentic workflow using openai api
https://github.com/fullstackwithlawrence/agentic-ai-workflow

Last synced: 2 months ago
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Example agentic workflow using openai api

• Host: GitHub
• URL: https://github.com/fullstackwithlawrence/agentic-ai-workflow
• Owner: FullStackWithLawrence
• License: agpl-3.0
• Created: 2025-09-30T18:33:56.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2025-09-30T21:44:03.000Z (3 months ago)
• Last Synced: 2025-09-30T22:24:36.101Z (3 months ago)
• Language: Python
• Size: 46.9 KB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • Contributing: .github/CONTRIBUTING.md
  • Funding: .github/FUNDING.yml
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md

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README

          
# Agentic AI Workflow Example

[![FullStackWithLawrence](https://a11ybadges.com/badge?text=FullStackWithLawrence&badgeColor=orange&logo=youtube&logoColor=282828)](https://www.youtube.com/@FullStackWithLawrence)


[![OpenAI](https://a11ybadges.com/badge?logo=openai)](https://platform.openai.com/)

[![Docker](https://a11ybadges.com/badge?logo=docker)](https://docs.docker.com/)

[![Python](https://a11ybadges.com/badge?logo=python)](https://www.python.org/)

![Unit Tests](https://github.com/FullStackWithLawrence/agentic-ai-workflow/actions/workflows/testsPython.yml/badge.svg?branch=main)

![GHA pushMain Status](https://img.shields.io/github/actions/workflow/status/FullStackWithLawrence/agentic-ai-workflow/pushMain.yml?branch=main)

![Auto Assign](https://github.com/FullStackwithLawrence/agentic-ai-workflow/actions/workflows/auto-assign.yml/badge.svg)

[![Release Notes](https://img.shields.io/github/release/FullStackWithLawrence/agentic-ai-workflow)](https://github.com/FullStackWithLawrence/agentic-ai-workflow/releases)

[![License: AGPL v3](https://img.shields.io/badge/License-AGPL_v3-blue.svg)](https://www.gnu.org/licenses/agpl-3.0)

[![hack.d Lawrence McDaniel](https://img.shields.io/badge/hack.d-Lawrence%20McDaniel-orange.svg)](https://lawrencemcdaniel.com)

A Python command-line application that demonstrates how to use OpenAI Api function calling to drive an automated agentic workflow. Additionally, this repo demonstrates

- how to use Docker Compose to containerize your project

- how to leverage Pydantic for constructing complex JSON objects

Python code is [located here](./app/)

![Agentic AI Workflow](https://github.com/FullStackWithLawrence/agentic-ai-workflow/blob/main/doc/img/agentic-workflow.png)

## Quick Start

1. Setup the application

```console

git clone https://github.com/FullStackWithLawrence/agentic-ai-workflow.git

cd agentic-ai-workflow

make init    # create a virtual environment

```

2. Configure OpenAI API. Find and open the file `.env` in the root folder of the project. Add your OpenAI API key, save and close the file. See [OpenAI API Getting Started](./doc/OPENAI_API_GETTING_STARTED_GUIDE.md) for detailed setup instructions.

3. Run the application

```console

source activate

python -m app.agent

```

## OPTIONAL: Docker

This application can also run as a Docker container.

```console

make                # initializes a .env file for OPENAI_API_KEY and DOCKERHUB_ACCESS_TOKEN

make docker-build   # run Docker compose to containerize your application

make docker-run     # run the application as a Docker container

```

Other Docker commands

```console

make docker-push    # push your Docker container to DockerHub. A DockerHub account and DOCKERHUB_ACCESS_TOKEN is required.

make docker-prune   # prune (permanently delete) all existing data in Docker: containers, images, cache.

```

## Requirements

- [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git). _pre-installed on Linux and macOS_

- [make](https://gnuwin32.sourceforge.net/packages/make.htm). _pre-installed on Linux and macOS._

- [OpenAI platform API key](https://platform.openai.com/).

  _If you're new to OpenAI API then see [How to Get an OpenAI API Key](./doc/OPENAI_API_GETTING_STARTED_GUIDE.md)_

- [Python 3.13](https://www.python.org/downloads/): for creating virtual environment.

- [Docker](https://docs.docker.com/): the Docker run-time environment for your operating system. Can be installed as a desktop application or as a service (daemon)

- [Docker Compose](https://docs.docker.com/compose/install/): used to create your production container.

## Documentation

Documentation is available here: [Documentation](./doc/)

## Support

To get community support, go to the official [Issues Page](https://github.com/FullStackWithLawrence/agentic-ai-workflow/issues) for this project.

## Good Coding Best Practices

This project demonstrates a wide variety of good coding best practices for managing mission-critical cloud-based micro services in a team environment. Please see this [Code Management Best Practices](./doc/GOOD_CODING_PRACTICE.md) for additional details.

We want to make this project more accessible to students and learners as an instructional tool while not adding undue code review workloads to anyone with merge authority for the project. To this end we've also added several pre-commit code linting and code style enforcement tools, as well as automated procedures for version maintenance of package dependencies, pull request evaluations, and semantic releases.

## Contributing

We welcome contributions! There are a variety of ways for you to get involved, regardless of your background. In addition to Pull requests, this project would benefit from contributors focused on documentation and how-to video content creation, testing, community engagement, and stewards to help us to ensure that we comply with evolving standards for the ethical use of AI.

For developers, please see:

- the [Developer Setup Guide](./doc/CONTRIBUTING.md)

- and these [commit comment guidelines](./doc/SEMANTIC_VERSIONING.md) 😬😬😬 for managing CI rules for automated semantic releases.

You can also contact [Lawrence McDaniel](https://lawrencemcdaniel.com/contact) directly.