By adding an optional dependency on the
spring-boot-configuration-processor, a
`META-INF/spring-configuration-metadata.json` file will be created for
all `@ConfigurationProperties`-annoted types to support autocompletion
within IDEs. Since nested beans are used, the bound fields for those
beans need to be annotated with `@NestedConfigurationProperty`. (purely
for this tool, this does not affect runtime behavior in any way)
Add the Spring Boot Configuration Processor dependency to the Spring
Boot starter to generate metadata
about the LangChain4J custom properties.
Fixes gh-250
Qwen series models are provided by Alibaba Cloud. They are much better
in Asia languages then other LLMs.
DashScope is a model service platform. Qwen models are its primary
supported models. But it also supports other series like LLaMA2, Dolly,
ChatGLM, BiLLa(based on LLaMA)...These may be integrated sometime in the
future.
- all-minilm-l6-v2
- all-minilm-l6-v2-q
- e5-small-v2
- e5-small-v2-q
The idea is to give users an option to embed documents/texts in the same
Java process without any external dependencies.
ONNX Runtime is used to run models inside JVM.
Each model resides in it's own maven module (inside the jar).
Have a parent pom that contains most/all common things for the
sub-projects.
Note that it is separate from the root aggregator pom: not mixing the
aggregator and the parents makes things slightly easier.
If this change makes it harder to do releases, there might be a
possibility to generate the effective poms for each subproject, but on
the other hand releasing everything should not be too problematic.
The title says it all. Relying on [this maven
plugin](https://github.com/chonton/license-maven-plugin) for it.
Note that this adds a separate build step because we need a more recent
JDK to run the needed plugin.
deep-learning-dynamo