https://github.com/thatrobotdev/pattern-pigeon
🐦 Pattern Pigeon is a conversational assistant built with Dialogflow CX to teach the Strategy, Composite, and Observer design patterns.
https://github.com/thatrobotdev/pattern-pigeon
Last synced: 2 months ago
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🐦 Pattern Pigeon is a conversational assistant built with Dialogflow CX to teach the Strategy, Composite, and Observer design patterns.
- Host: GitHub
- URL: https://github.com/thatrobotdev/pattern-pigeon
- Owner: thatrobotdev
- License: apache-2.0
- Created: 2025-04-14T21:29:11.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2025-04-14T21:53:49.000Z (12 months ago)
- Last Synced: 2025-04-14T22:35:01.981Z (12 months ago)
- Size: 7.81 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 🐦 Pattern Pigeon
%20🐦%20Pattern%20Pigeon.png)
> Coo coo! I'm Pattern Pigeon–your feathered friend here to help you understand software architecture patterns like Strategy, Composite, and Observer. I might ruffle in a few pigeon facts too. What are you curious about today?
Pattern Pigeon is a [deterministic](https://cloud.google.com/dialogflow/cx/docs/generative-deterministic#deterministic)[^1] conversational assistant built with Google Cloud's [Dialogflow CX](https://dialogflow.cloud.google.com/cx/projects) to teach the [Strategy](https://en.wikipedia.org/wiki/Strategy_pattern), [Composite](https://en.wikipedia.org/wiki/Composite_pattern), and [Observer](https://en.wikipedia.org/wiki/Observer_pattern) design patterns.
[^1]: All responses are generated by the agent, without generative input from a large language model (LLM). However, Flows use language models for understanding end-user intention, which may not be completely deterministic.
## 🕊️ Try the Demo
Curious how Pattern Pigeon flaps its wings?
👉 [**Check out the live demo**](https://www.jameskerrane.com/projects/pattern-pigeon/)
## Contributing
Follow the instructions from [Google Cloud](https://cloud.google.com/dialogflow/cx/docs/concept/github) to set up GitHub integration:
1. If you're contributing: [fork this repository](https://github.com/thatrobotdev/Pattern-Pigeon/fork).
2. Create a [fine-grained personal access token](https://cloud.google.com/dialogflow/cx/docs/concept/github#access_token) from [GitHub](https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/creating-a-personal-access-token). (Read-only is fine if you're not contributing.)
3. [Create a secret](https://cloud.google.com/dialogflow/cx/docs/concept/github) for the token in the Dialogflow CX console.
4. [Configure Git export/restore integration](https://cloud.google.com/dialogflow/cx/docs/concept/github#dialogflow_config) for your Dialogflow CX agent.
5. Pull the agent from GitHub!
6. If contributing, push your changes and **rebase or amend any unintended edits.**
⚠️ Note: Dialogflow CX **overwrites the entire branch** on push from the console, so make sure to:
- Commit only intended changes.
- Compare changes made in the dashboard vs. those you want to keep.
- Optionally, make edits in a local text editor and manage them manually.
## License
> The pigeon photo used was taken by Muhammad Mahdi Karim/. The image above is licensed under the [Free Art License](https://artlibre.org/licence/lal/en/). ([Learn more](.github/README/Pigeon%20<3%20Apache/LICENSE)). This project is not endorsed or connected to the Apache Software Foundation.
This project is licensed under the [Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0.html), [which you can read here](LICENSE).