Customization#

Gateways are customizable in Jina. You can implement them in much the same way as an Executor. With customized Gateways, Jina gives you more power by letting you implement any server, protocol and interface at the Gateway level. This means you have more freedom to:

Define and expose your own API Gateway interface to clients. You can define your JSON schema or protos etc.
Use your favorite server framework.
Choose the protocol used to serve your app.

The next sections detail the steps to implement and use a custom Gateway.

Implementing the custom Gateway#

Just like for Executors, you can implement a custom Gateway by inheriting from a base Gateway class. Jina will instantiate your implemented class, inject runtime arguments and user-defined arguments into it, run it, orchestrate it, and send it health-checks.

There are two Gateway base classes for implementing a custom Gateway:

FastAPIBaseGateway: Use this abstract class to implement a custom Gateway using FastAPI.
Gateway: Use this abstract class to implement a custom Gateway of any type.

Whether your custom Gateway is based on a FastAPI app using FastAPIBaseGateway or based on a general server using Gateway, you will need to implement your server behavior in almost the same way. In the next section we will discuss the implementation steps, and then we will discuss how to use both base Gateway classes.

Server implementation#

When implementing the server to your custom Gateway:

Create an app/server and define the endpoints you want to expose as a service.
In each of your endpoints’ implementation, convert server requests to your endpoint into Document objects.
Send Documents to Executors in the Flow using a GatewayStreamer object. This lets you use Executors as a service and receive response Documents back.
Convert response Documents to a server response and return it.
Implement the required health-checks for the Gateway. (This is not required when using FastAPIBaseGateway.)
Bind your Gateway server to parameters injected by the runtime, i.e, self.port, self.host,… (Also not required for FastAPIBaseGateway.)

Let’s suppose you want to implement a ‘/service’ GET endpoint in an HTTP server. Following the steps above, the server implementation might look like the following:

from fastapi import FastAPI
from uvicorn import Server, Config
from jina import Gateway
from docarray import DocList
from docarray.documents import TextDoc


class MyGateway(Gateway):
    async def setup_server(self):
        # step 1: create an app and define the service endpoint
        app = FastAPI(title='Custom Gateway')

        @app.get(path='/service')
        async def my_service(input: str):
            # step 2: convert input request to Documents
            docs = DocList[TextDoc]([TextDoc(text=input)])

            # step 3: send Documents to Executors using GatewayStreamer
            result = None
            async for response_docs in self.streamer.stream_docs(
                docs=docs,
                exec_endpoint='/',
                return_type=DocList[TextDoc]
            ):
                # step 4: convert response docs to server response and return it
                result = response_docs[0].text

            return {'result': result}

        # step 5: implement health-check

        @app.get(path='/')
        def health_check():
            return {}

        # step 6: bind the gateway server to the right port and host
        self.server = Server(Config(app, host=self.host, port=self.port))

Subclass from `FastAPIBaseGateway`#

FastAPIBaseGateway offers a simple API to implement custom Gateways, but is restricted to FastAPI apps.

To implement a custom gateway using FastAPIBaseGateway, simply implement the app() property:

from jina.serve.runtimes.gateway.http.fastapi import FastAPIBaseGateway


class MyGateway(FastAPIBaseGateway):
    @property
    def app(self):
        from fastapi import FastAPI

        app = FastAPI(title='Custom FastAPI Gateway')

        @app.get(path='/endpoint')
        def custom_endpoint():
            return {'message': 'custom-fastapi-gateway'}

        return app

As an example, you can refer to HTTPGateway.

FastAPIBaseGateway is a subclass of Gateway.

Subclass from `Gateway`#

Gateway allows implementing more general cases of Gateways. You can use this class as long as your gateway server is runnable in an asyncio loop.

To implement a custom gateway class using Gateway:

Create a class that inherits from Gateway
Implement a constructor __init__: (This is optional. You don’t need a constructor if your Gateway does not need user-defined attributes.) If your Gateway has __init__, it needs to carry **kwargs in the signature and call super().__init__(**kwargs) in the body:

from jina import Gateway


class MyGateway(Gateway):
    def __init__(self, foo: str, **kwargs):
        super().__init__(**kwargs)
        self.foo = foo

Implement async def setup_server():. This should set up a server runnable on an asyncio loop (and other resources needed for setting up the server). For instance:

from jina import Gateway
from fastapi import FastAPI
from uvicorn import Server, Config


class MyGateway(Gateway):
    async def setup_server(self):
        app = FastAPI(title='My Custom Gateway')

        @app.get(path='/endpoint')
        def custom_endpoint():
            return {'message': 'custom-gateway'}

        self.server = Server(Config(app, host=self.host, port=self.port))

Please refer to the Server Implementation section for details on how to implement the server.

Implement async def run_server():. This should run the server and await for it while serving:

from jina import Gateway


class MyGateway(Gateway):
    ...

    async def run_server(self):
        await self.server.serve()

Implement async def shutdown():. This should stop the server and free all resources associated with it:

from jina import Gateway


class MyGateway(Gateway):
    ...

    async def shutdown(self):
        self.server.should_exit = True
        await self.server.shutdown()

As an example, you can refer to GRPCGateway and WebSocketGateway.

Calling Executors with `GatewayStreamer`#

GatewayStreamer allows you to interface with Executors within the Gateway. An instance of this class knows about the Flow topology and where each Executor lives.

Use this object to send Documents to Executors in the Flow. A GatewayStreamer object connects the custom Gateway with the rest of the Flow.

You can get this object in 2 different ways:

A streamer object (instance of GatewayStreamer) is injected by Jina to your Gateway class.
If your server logic cannot access the Gateway class (for instance separate script), you can still get a streamer object using get_streamer():

from jina.serve.streamer import GatewayStreamer

streamer = GatewayStreamer.get_streamer()

After transforming requests that arrive to the Gateway server into Documents, you can send them to Executors in the Flow using stream_docs().

This method expects a DocList object and an endpoint exposed by the Flow Executors (similar to Jina Client). It returns an AsyncGenerator of DocLists:

from jina.serve.runtimes.gateway.http.fastapi import FastAPIBaseGateway
from docarray import DocList
from docarray.documents import TextDoc
from fastapi import FastAPI


class MyGateway(FastAPIBaseGateway):
    @property
    def app(self):
        app = FastAPI()

        @app.get("/endpoint")
        async def get(text: str):
            result = None
            async for docs in self.streamer.stream_docs(
                docs=DocList[TextDoc]([TextDoc(text=text)]),
                exec_endpoint='/',
                return_type=DocList[TextDoc],
            ):
                result = docs[0].text
            return {'result': result}

        return app

Hint

if you omit the return_type parameter, the gateway streamer can still fetch the Executor output schemas and dynamically construct a DocArray model for it. Even though the dynamically created schema is very similar to original schema, some validation checks can still fail (for instance adding to a typed DocList). It is recommended to always pass the return_type parameter

Recovering Executor errors#

Exceptions raised by an Executor are captured in the server object which can be extracted by using the jina.serve.streamer.stream() method. The stream method returns an AsyncGenerator of a tuple of DocList and an optional jina.excepts.ExecutorError class that be used to check if the Executor has issues processing the input request. The error can be utilized for retries, handling partial responses or returning default responses.

@app.get("/endpoint")
async def get(text: str):
    results = []
    errors = []
    async for for docs, error in self.streamer.stream(
        docs=DocList[TextDoc]([TextDoc(text=text)]),
        exec_endpoint='/',
        return_type=DocList[TextDoc],
    ):
        if error:
            errors.append(error)
        else:
            results.append(docs[0].text)
    return {'results': results, 'errors': [error.name for error in errors]}

Hint

Calling an individual Executor#

Jina injects an executor object into your Gateway class which lets you call individual Executors from the Gateway.

After transforming requests that arrive to the Gateway server into Documents, you can call the Executor in your Python code using self.executor['executor_name'].post(args). This method expects a DocList object and an endpoint exposed by the Executor (similar to Jina Client). It returns a ‘coroutine’ which returns a DocList. Check the method documentation for more information: post()

In this example, we have a Flow with two Executors (executor1 and executor2). We can call them individually using self.executor['executor_name'].post:

from jina.serve.runtimes.gateway.http.fastapi import FastAPIBaseGateway
from jina import Flow, Executor, requests
from docarray import DocList
from docarray.documents import TextDoc
from fastapi import FastAPI
import time

class MyGateway(FastAPIBaseGateway):
    @property
    def app(self):
        app = FastAPI()

        @app.get("/endpoint")
        async def get(text: str):
            toc = time.time()
            docs1 = await self.executor['executor1'].post(on='/', inputs=DocList[TextDoc]([TextDoc(text=text)]), parameters={'k': 'v'}, return_type=DocList[TextDoc])
            docs2 = await self.executor['executor2'].post(on='/', inputs=DocList[TextDoc]([TextDoc(text=text)]), parameters={'k': 'v'}, return_type=DocList[TextDoc])
            return {'result': docs1.text + docs2.text, 'time_taken': time.time() - toc}

        return app

class FirstExec(Executor):
    @requests
    def func(self, docs: DocList[TextDoc], **kwargs) -> DocList[TextDoc]:
        time.sleep(2)
        for doc in docs:
            doc.text += ' saw the first executor'

class SecondExec(Executor):
    @requests
    def func(self, docs: DocList[TextDoc], **kwargs) -> DocList[TextDoc]:
        time.sleep(2)
        for doc in docs:
            doc.text += ' saw the second executor'

with Flow().config_gateway(uses=MyGateway, protocol='http').add(uses=FirstExec, name='executor1').add(uses=SecondExec, name='executor2') as flow:
    import requests as reqlib
    r = reqlib.get(f"http://localhost:{flow.port}/endpoint?text=hello")
    print(r.json())
    assert r.json()['result'] == ['hello saw the first executor', 'hello saw the second executor']
    assert r.json()['time_taken'] > 4

You can also call two Executors in parallel using asyncio. This will overlap their execution times – speeding up the response time of the endpoint. Here is one way to do it:

from jina.serve.runtimes.gateway.http.fastapi import FastAPIBaseGateway
from jina import Flow, Executor, requests
from docarray import DocList
from docarray.documents import TextDoc
from fastapi import FastAPI
import time
import asyncio

class MyGateway(FastAPIBaseGateway):
    @property
    def app(self):
        app = FastAPI()

        @app.get("/endpoint")
        async def get(text: str):
            toc = time.time()
            call1 = self.executor['executor1'].post(on='/', inputs=DocList[TextDoc]([TextDoc(text=text)]), parameters={'k': 'v'}, return_type=DocList[TextDoc])
            call2 = self.executor['executor2'].post(on='/', inputs=DocList[TextDoc]([TextDoc(text=text)]), parameters={'k': 'v'}, return_type=DocList[TextDoc])
            docs1, docs2 = await asyncio.gather(call1, call2)
            return {'result': docs1.text + docs2.text, 'time_taken': time.time() - toc}

        return app

class FirstExec(Executor):
    @requests
    def func(self, docs: DocList[TextDoc], **kwargs) -> DocList[TextDoc]:
        time.sleep(2)
        for doc in docs:
            doc.text += ' saw the first executor'

class SecondExec(Executor):
    @requests
    def func(self, docs: DocList[TextDoc], **kwargs) -> DocList[TextDoc]:
        time.sleep(2)
        for doc in docs:
            doc.text += ' saw the second executor'

with Flow().config_gateway(uses=MyGateway, protocol='http').add(uses=FirstExec, name='executor1').add(uses=SecondExec, name='executor2') as flow:
    import requests as reqlib
    r = reqlib.get(f"http://localhost:{flow.port}/endpoint?text=hello")
    print(r.json())
    assert r.json()['result'] == ['hello saw the first executor', 'hello saw the second executor']
    assert r.json()['time_taken'] < 2.5

Gateway arguments#

Runtime attributes#

Jina injects runtime attributes into the Gateway classes. You can use them to set up your custom gateway:

logger: Jina logger object.
streamer: GatewayStreamer. Use this object to send Documents from the Gateway to Executors. Refer to this section for more information.
runtime_args: argparse.Namespace object containing runtime arguments.
port: main port exposed by the Gateway.
ports: list of all ports exposed by the Gateway.
protocols: list of all protocols supported by the Gateway.
host: Host address to which the Gateway server should be bound.

Use these attributes to implement your Gateway logic. For instance, binding the server to the runtime provided port and host:

from jina import Gateway

class MyGateway(Gateway):
    ...
    async def setup_server(self):
        ...
        self.server = Server(Config(app, host=self.host, port=self.port))

Note

Jina provides the Gateway with a list of ports and protocols to expose. Therefore, a custom Gateway can handle requests on multiple ports using different protocols.

User-defined parameters#

You can also set other parameters by implementing a custom constructor __init__.You can override constructor parameters in the Flow Python API (using uses_with parameter) or in the YAML configuration when including the Gateway. Refer to the Use Custom Gateway section for more information.

Required health-checks#

Jina relies on health-checks to determine the health of the Gateway. In environments like Kubernetes, Docker Compose and Jina Cloud, this information is crucial for orchestrating the Gateway. Since you have full control over your custom gateways, you are always responsible for implementing health-check endpoints:

If the protocol used is gRPC, a health servicer (for instance health.aio.HealthServicer()) from grpcio-health-checking is expected to be added to the gRPC server. Refer to GRPCGateway as an example.
Otherwise, an HTTP GET request to the root path is expected to return a 200 status code.

To test whether your server properly implements health-checks, you can use the command jina ping <protocol>://host:port

Important

Although a Jina Gateway can expose multiple ports and protocols, the runtime only cares about the first exposed port and protocol. Health checks will be sent only to the first port.

Gateway YAML file#

Like Executor config files, a custom Gateway implementation can be associated with a YAML configuration file. Such a configuration can override user-defined parameters and define other runtime arguments (port, protocol, py_modules, etc).

You can define such a configuration in config.yml:

!MyGateway
py_modules: my_gateway.py
with:
  arg1: hello
  arg2: world
port: 12345

For more information, please refer to the Gateway YAML Specifications

Containerize the Custom Gateway#

You may want to dockerize your custom Gateway so you can isolate its dependencies and make it ready to run in the cloud or Kubernetes.

This assumes that you’ve already implemented a custom Gateway class and have defined a config.yml for it. In this case, dockerizing the Gateway is straightforward:

If you need dependencies other than Jina, make sure to add a requirements.txt file (for instance, you use a server library).
Create a Dockerfile as follows:

Use a Jina based image with the standard tag as the base image in your Dockerfile. This ensures that everything needed for Jina to run the Gateway is installed. Make sure the Jina version supports custom Gateways:

FROM jinaai/jina:latest-py38-standard

Alternatively, you can just install jina using pip:

RUN pip install jina

Install everything from requirements.txt if you included it:

RUN pip install -r requirements.txt

Copy source code under the workdir folder:

COPY . /workdir/
WORKDIR /workdir

Use the jina gateway --uses config.yml command as your image’s entrypoint:

ENTRYPOINT ["jina", "gateway", "--uses", "config.yml"]

Once you finish the Dockerfile you should end up with the following file structure:

.
├── my_gateway.py
└── requirements.txt
└── config.yml
└── Dockerfile

You can now build the Docker image:

cd my_gateway
docker build -t gateway-image

Use the Custom Gateway#

You can include the Custom Gateway in a Jina Flow in different formats: Python class, configuration YAML and Docker image:

Flow python API#

Python Class

from jina import Gateway, Flow


class MyGateway(Gateway):
    def __init__(self, arg: str = None, **kwargs):
        super().__init__(**kwargs)
        self.arg = arg

    ...


flow = Flow().config_gateway(
    uses=MyGateway, port=12345, protocol='http', uses_with={'arg': 'value'}
)

YAML configuration

flow = Flow().config_gateway(
    uses='config.yml', port=12345, protocol='http', uses_with={'arg': 'value'}
)

Docker Image

flow = Flow().config_gateway(
    uses='docker://gateway-image',
    port=12345,
    protocol='http',
    uses_with={'arg': 'value'},
)

Flow YAML configuration#

Python Class

!Flow
gateway:
  py_modules: my_gateway/my_gateway.py
  uses: MyGateway
  with:
    arg: value
  protocol: http
  port: 12345

YAML configuration

!Flow
gateway:
  uses: my_gateway/config.yml
  protocol: http
  port: 12345

Docker Image

!Flow
gateway:
  uses: docker://gateway-image
  protocol: http
  port: 12345

Important

When you include a custom Gateway in a Jina Flow, since Jina needs to know about the port and protocol to which health checks will be sent, it is important to specify them when including the Gateway.

Customization#

Implementing the custom Gateway#

Server implementation#

Subclass from FastAPIBaseGateway#

Subclass from Gateway#

Calling Executors with GatewayStreamer#

Recovering Executor errors#

Calling an individual Executor#

Gateway arguments#

Runtime attributes#

User-defined parameters#

Required health-checks#

Gateway YAML file#

Containerize the Custom Gateway#

Use the Custom Gateway#

Flow python API#

Flow YAML configuration#

Subclass from `FastAPIBaseGateway`#

Subclass from `Gateway`#

Calling Executors with `GatewayStreamer`#