[Serve] Java Serve improvement

reps/2023-08-18-serve-java-dag-api.md

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+## Summary
+### General Motivation
+Compared to the latest Serve API in Python, Ray Serve Java lacks a major version update. Currently, the main form of the Serve API is the DAG API, which involves networking deployments through binding and deploying the graph. For example:
+```python
+import ray
+from ray import serve
+from ray.serve.handle import RayServeHandle, DeploymentHandle
+
+
+@serve.deployment
+def preprocess(inp: int) -> int:
+    return inp + 1
+
+
+@serve.deployment
+class Model:
+    def __init__(self, preprocess_handle: RayServeHandle, increment: int):
+        self.preprocess_handle: DeploymentHandle = preprocess_handle.options(use_new_handle_api=True)
+        self.increment = increment
+
+    async def predict(self, inp: int) -> int:
+        preprocessed = await self.preprocess_handle.remote(inp)
+        return preprocessed + self.increment
+
+app = Model.bind(preprocess.bind(), increment=2)
+handle = serve.run(app)
+assert ray.get(handle.predict.remote(1)) == 4
+
+```
+Looking back at Java, we hope that Java can keep up with the features of the Serve API, allowing Java developers to deploy Java projects as Serve deployments and compose multiple deployments to accomplish complex online computations.
+### Should this change be within `ray` or outside?
+Main `ray` project. A part of java/serve.
+## Stewardship
+
+### Required Reviewers
+@sihanwang41 @edoakes
+
+### Shepherd of the Proposal (should be a senior committer)
+@sihanwang41 @edoakes
+
+## Design and Architecture
+
+### Update Java User API to be Consistent with Python
+A standard Java deployment demo is shown below:
+```java
+import io.ray.serve.api.Serve;
+import io.ray.serve.deployment.Application;
+import io.ray.serve.handle.DeploymentHandle;
+
+public class DeploymentDemo {
+  private String msg;
+
+  public DeploymentDemo(String msg) {
+    this.msg = msg;
+  }
+
+  public String call() {
+    return msg;
+  }
+
+  public static void main(String[] args) {
+    Application deployment =
+        Serve.deployment().setDeploymentDef(DeploymentDemo.class.getName()).bind();
+    DeploymentHandle handle = Serve.run(deployment).get();
+    System.out.println(handle.remote().result());
+  }
+}
+
+```
+In this demo, a deployment is defined through the `bind` method, and it is deployed using the `Serve.run` API.
+Furthermore, a deployment can bind other deployments, and users can use the deployment input parameters in a similar way to the `DeploymentHandle`. For example:
+```java
+import io.ray.serve.api.Serve;
+import io.ray.serve.deployment.Application;
+import io.ray.serve.handle.DeploymentHandle;
+import io.ray.serve.handle.DeploymentResponse;
+
+public class Driver {
+  private DeploymentHandle modelAHandle;
+  private DeploymentHandle modelBHandle;
+
+  public Driver(DeploymentHandle modelAHandle, DeploymentHandle modelBHandle) {
+    this.modelAHandle = modelAHandle;
+    this.modelBHandle = modelBHandle;
+  }
+
+  public String call(String request) {
+    DeploymentResponse responseA = modelAHandle.remote(request);
+    DeploymentResponse responseB = modelBHandle.remote(request);
+    return (String) responseA.result() + responseB.result();
+  }
+
+  public static class ModelA {
+    public String call(String msg) {
+      return msg;
+    }
+  }
+
+  public static class ModelB {
+    public String call(String msg) {
+      return msg;
+    }
+  }
+
+  public static void main(String[] args) {
+    Application modelA = Serve.deployment().setDeploymentDef(ModelA.class.getName()).bind();
+    Application modelB = Serve.deployment().setDeploymentDef(ModelB.class.getName()).bind();
+
+    Application driver =
+        Serve.deployment().setDeploymentDef(Driver.class.getName()).bind(modelA, modelB);
+    Serve.run(driver);
+  }
+}
+
+```
+In this example, the modelA and modelB are defined as two Deployments, and the driver is instantiated with the corresponding `DeploymentHandle` of these two Deployments. When `call` is executed, both models are invoked. Additionally, it is evident that `DeploymentHandle.remote` returns `DeploymentResponse` instead of `ObjectRef`. The result can be accessed through `DeploymentResponse.result`.
+
+### Deploying Deployments of the Other Languages through Python API
+In another REP ([Add Cpp Deployment in Ray Serve](https://github.com/ray-project/enhancements/pull/34)), it is mentioned how to deploy C++ deployments through Python. Deploying Java deployments through Python is similar. Since Java and C++ do not have the decorator mechanism like Python, a straightforward way is to directly use the `serve.deployment` API (with the addition of a new `language` parameter):
+
+```python
+deployment = serve.deployment('io.ray.serve.ExampleDeployment', name='my_deployment', language=JAVA)
+
+```
+### Deploying through the Config File
+Based on the mentioned API, we can deploy a Java code file that orchestrates an application using the `serve run` command. For example, consider the following Text.java file:
+```java
+import io.ray.serve.api.Serve;
+import io.ray.serve.deployment.Application;
+import io.ray.serve.handle.DeploymentHandle;
+
+public class Text {
+
+  public static class Hello {
+    public String call() {
+      return "Hello";
+    }
+  }
+
+  public static class World {
+    public String call() {
+      return " world!";
+    }
+  }
+
+  public static class Ingress {
+    private DeploymentHandle helloHandle;
+    private DeploymentHandle worldHandle;
+
+    public Ingress(DeploymentHandle helloHandle, DeploymentHandle worldHandle) {
+      this.helloHandle = helloHandle;
+      this.worldHandle = worldHandle;
+    }
+
+    public String call() {
+      return (String) helloHandle.remote().result() + worldHandle.remote().result();
+    }
+  }
+
+  public static Application app() {
+    Application hello = Serve.deployment().setDeploymentDef(Hello.class.getName()).bind();
+    Application world = Serve.deployment().setDeploymentDef(World.class.getName()).bind();
+
+    Application app =
+        Serve.deployment().setDeploymentDef(Ingress.class.getName()).bind(hello, world);
+    return app;
+  }
+}
+
+```
+This code orchestrates an application within a static method named `app`. The CLI command for its deployment is as follows:
+```shell
+$ serve run java:io.ray.serve.repdemo.Text:app
+```
+
+> It should be noted that `java` is mentioned here to represent the programming language used for orchestrating the application. Currently, there is no clear plan on how to expand this parameter in the serve run command. One direct approach that comes to mind is to concatenate it before the `import_path`.
+
+Additionally, similar to the Python `app_builder`, a Java application also supports custom parameters. For example:
+```java
+import io.ray.serve.api.Serve;
+import io.ray.serve.deployment.Application;
+import java.util.Map;
+
+public class Hello {
+
+  public static class HelloWorld {
+    private String message;
+
+    public HelloWorld(String message) {
+      this.message = message;
+    }
+
+    public String call() {
+      return message;
+    }
+  }
+
+  public static Application appBuilder(Map<String, String> args) {
+    return Serve.deployment()
+        .setDeploymentDef(HelloWorld.class.getName())
+        .bind(args.get("message"));
+  }
+}
+
+```
+
+The `appBuilder` method takes a `Map` as input parameter, from which users can retrieve the required `message` parameter. The syntax for deployment is as follows:
+
+
+```shell
+$ serve run java:io.ray.serve.repdemo.Hello:appBuilder message="Hello from CLI"
+```
+
+Furthermore, it is worth mentioning that `appBuilder` also supports user-defined input parameter of custom types, as long as the type includes the specified attributes. For example:
+
+```java
+import io.ray.serve.api.Serve;
+import io.ray.serve.deployment.Application;
+import java.util.Map;
+
+public class Hello {
+
+  public static class HelloWorldArgs {
+    private String message;
+
+    public String getMessage() {
+      return message;
+    }
+
+    public void setMessage(String message) {
+      this.message = message;
+    }
+  }
+
+  public static class HelloWorld {
+    private String message;
+
+    public HelloWorld(String message) {
+      this.message = message;
+    }
+
+    public String call() {
+      return message;
+    }
+  }
+
+  public static Application typedAppBuilder(HelloWorldArgs args) {
+    return Serve.deployment().setDeploymentDef(HelloWorld.class.getName()).bind(args.getMessage());
+  }
+}
+
+```
+
+```shell
+$ serve run java:io.ray.serve.repdemo.Hello:typedAppBuilder message="Hello from CLI"
+```
+
+For the aforementioned `Text.java` file, we can generate the corresponding Serve config file using the `serve build` command:
+
+```shell
+$ serve build io.ray.serve.repdemo.Text:app -o serve_config.yaml
+```
+
+The generated config file looks like this:
+```yaml
+proxy_location: EveryNode
+
+http_options:
+  host: 0.0.0.0
+  port: 8000
+
+grpc_options:
+  port: 9000
+  grpc_servicer_functions: []
+
+applications:
+- name: app
+  route_prefix: /
+  import_path: io.ray.serve.repdemo.Text:app
+  language: java
+  runtime_env: {}
+  deployments:
+  - name: Hello
+  - name: World
+  - name: Ingress
+
+```
+
+The `serve run` command allows direct specification of this config file for deploying the application:
+
+```shell
+$ serve run serve_config.yaml
+```
+
+### Serve Handle C++ Core
+
+In the design of C++ Deployment, it also includes the C++ implementation of Serve Handle. After the implementation, it can be reused as the core of Serve Handle by other languages (Python and Java) to avoid maintaining duplicate logic in the three languages. For the complete design, we will continue to supplement it in the "[Cpp Deployment Design](https://github.com/ray-project/enhancements/pull/34)" or another new document.
+
+## Compatibility, Deprecation, and Migration Plan
+In Java, the old API will be marked with the @Deprecated annotation, for example:
+```java
+public class Deployment {
+  @Deprecated
+  public void deploy(boolean blocking) {
+    Serve.getGlobalClient()
+        .deploy(
+            name,
+            deploymentDef,
+            initArgs,
+            rayActorOptions,
+            config,
+            version,
+            prevVersion,
+            routePrefix,
+            url,
+            blocking);
+  }
+}
+```
+This is also done to maintain consistency with the Python API, and to allow for easy removal of the deprecated API in the future.
+## Test Plan and Acceptance Criteria
+Related test cases will be provided under ray/java/serve, and they will cover the three scenarios mentioned above.
+## (Optional) Follow-on Work
+- Optimize the code by removing unused components and improving cross-language parameter handling.
+- Support the usage of streaming.