# adopt-a-pup

**Repository Path**: weir_admin/adopt-a-pup

## Basic Information

- **Project Name**: adopt-a-pup
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2026-01-20
- **Last Updated**: 2026-01-20

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# adopt-a-puppy

This project uses Quarkus, the Supersonic Subatomic Java Framework.

If you want to learn more about Quarkus, please visit its website: <https://quarkus.io/>.

## Running the application in dev mode

You can run your application in dev mode that enables live coding using:

```shell script
./mvnw quarkus:dev
```

> **_NOTE:_**  Quarkus now ships with a Dev UI, which is available in dev mode only at <http://localhost:8080/q/dev/>.

## Packaging and running the application

The application can be packaged using:

```shell script
./mvnw package
```

It produces the `quarkus-run.jar` file in the `target/quarkus-app/` directory.
Be aware that it’s not an _über-jar_ as the dependencies are copied into the `target/quarkus-app/lib/` directory.

The application is now runnable using `java -jar target/quarkus-app/quarkus-run.jar`.

If you want to build an _über-jar_, execute the following command:

```shell script
./mvnw package -Dquarkus.package.jar.type=uber-jar
```

The application, packaged as an _über-jar_, is now runnable using `java -jar target/*-runner.jar`.

## Creating a native executable

You can create a native executable using:

```shell script
./mvnw package -Dnative
```

Or, if you don't have GraalVM installed, you can run the native executable build in a container using:

```shell script
./mvnw package -Dnative -Dquarkus.native.container-build=true
```

You can then execute your native executable with: `./target/adopt-a-puppy-1.0.0-SNAPSHOT-runner`

If you want to learn more about building native executables, please consult <https://quarkus.io/guides/maven-tooling>.

## Related Guides

- REST ([guide](https://quarkus.io/guides/rest)): A Jakarta REST implementation utilizing build time processing and Vert.x. This extension is not compatible with the quarkus-resteasy extension, or any of the extensions that depend on it.
- LangChain4j Core ([guide](https://docs.quarkiverse.io/quarkus-langchain4j/dev/index.html)): Provides the basic integration with LangChain4j
- REST Jackson ([guide](https://quarkus.io/guides/rest#json-serialisation)): Jackson serialization support for Quarkus REST. This extension is not compatible with the quarkus-resteasy extension, or any of the extensions that depend on it
- LangChain4j Easy RAG ([guide](https://docs.quarkiverse.io/quarkus-langchain4j/dev/index.html)): Provides the Easy RAG functionality with LangChain4j
- LangChain4j pgvector embedding store ([guide](https://docs.quarkiverse.io/quarkus-langchain4j/dev/index.html)): Provides the pgvector Embedding store for Quarkus LangChain4j
- Hibernate ORM with Panache ([guide](https://quarkus.io/guides/hibernate-orm-panache)): Simplify your persistence code for Hibernate ORM via the active record or the repository pattern
- Quinoa ([guide](https://quarkiverse.github.io/quarkiverse-docs/quarkus-quinoa/dev/index.html)): Develop, build, and serve your npm-compatible web applications such as React, Angular, Vue, Lit, Svelte, Astro, SolidJS, and others alongside Quarkus.
- LangChain4j Ollama ([guide](https://docs.quarkiverse.io/quarkus-langchain4j/dev/index.html)): Provides the basic integration of Ollama with LangChain4j
- JDBC Driver - PostgreSQL ([guide](https://quarkus.io/guides/datasource)): Connect to the PostgreSQL database via JDBC

## Provided Code

### Hibernate ORM

Create your first JPA entity

[Related guide section...](https://quarkus.io/guides/hibernate-orm)

[Related Hibernate with Panache section...](https://quarkus.io/guides/hibernate-orm-panache)


### LangChain4j Easy RAG

This code is a very basic sample service to start developing with Quarkus LangChain4j using Easy RAG.

You have to add an extension that provides an embedding model. For that, you can choose from the plethora of extensions like quarkus-langchain4j-openai, quarkus-langchain4j-ollama, or import an in-process embedding model - these have the advantage of not having to send data over the wire.

In `./easy-rag-catalog/` you can find a set of example documents that will be used to create the RAG index which the bot (`src/main/java/org/acme/Bot.java`) will ingest.

On first run, the bot will create the RAG index and store it in `easy-rag-catalog.json` file and reuse it on subsequent runs.
This can be disabled by setting the `quarkus.langchain4j.easy-rag.reuse-embeddings.enabled` property to `false`.

Add it to a Rest endpoint:
```java
    @Inject
    Bot bot;
    
    @POST
    @Produces(MediaType.TEXT_PLAIN)
    public String chat(String q) {
        return bot.chat(q);
    }
```

In a more complete example, you would have a web interface and use websockets that would provide more interactive experience, see [ChatBot Easy RAG Sample](https://github.com/quarkiverse/quarkus-langchain4j/tree/main/samples/chatbot-easy-rag) for such an example.
### Quinoa

Quinoa codestart added a tiny Vite app in src/main/webui. The page is configured to be visible on <a href="/quinoa">/quinoa</a>.

[Related guide section...](https://quarkiverse.github.io/quarkiverse-docs/quarkus-quinoa/dev/index.html)


### REST

Easily start your REST Web Services

[Related guide section...](https://quarkus.io/guides/getting-started-reactive#reactive-jax-rs-resources)


### Message only chatbot adoption
```
Can you help me fill this form. I own a house with a fenced yard. 
It's located chaussée de Charleroi 63 at Gembloux. 
We're are 3 in the house including my 4 years old. 
I've own a dog before. 
My permit number is 1234567890 and it expires the 2nd of may 2026.
The puppy will be alone on average 8hours per day.
We consider to have a high activity level.
```


### TODO's
- send the user message back (when using voice/files)
- integrate mcp
- integrate audio response
- avatar answering