README.md 5.2 KB
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<p align="center">
    <br>
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<img src='https://paddle-serving.bj.bcebos.com/imdb-demo%2FLogoMakr-3Bd2NM-300dpi.png' width = "600" height = "130">
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    <br>
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    <a href="https://travis-ci.com/PaddlePaddle/Serving">
        <img alt="Build Status" src="https://img.shields.io/travis/com/PaddlePaddle/Serving/develop">
    </a>
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    <img alt="Release" src="https://img.shields.io/badge/Release-0.0.3-yellowgreen">
    <img alt="Issues" src="https://img.shields.io/github/issues/PaddlePaddle/Serving">
    <img alt="License" src="https://img.shields.io/github/license/PaddlePaddle/Serving">
    <img alt="Slack" src="https://img.shields.io/badge/Join-Slack-green">
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    <br>
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<h2 align="center">Motivation</h2>
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Paddle Serving helps deep learning developers deploy an online inference service without much effort. **The goal of this project**: once you have trained a deep neural nets with [Paddle](https://github.com/PaddlePaddle/Paddle), you already have a model inference service. A demo of serving is as follows:
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<p align="center">
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    <img src="doc/demo.gif" width="700">
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</p>
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<h2 align="center">Key Features</h2>

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- Integrate with Paddle training pipeline seemlessly, most paddle models can be deployed **with one line command**.
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- **Industrial serving features** supported, such as models management, online loading, online A/B testing etc.
- **Distributed Key-Value indexing** supported that is especially useful for large scale sparse features as model inputs.
- **Highly concurrent and efficient communication** between clients and servers.
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- **Multiple programming languages** supported on client side, such as Golang, C++ and python
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- **Extensible framework design** that can support model serving beyond Paddle.
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<h2 align="center">Installation</h2>
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We highly recommend you to run Paddle Serving in Docker, please visit [Run in Docker](https://github.com/PaddlePaddle/Serving/blob/develop/doc/RUN_IN_DOCKER.md)

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```shell
pip install paddle-serving-client
pip install paddle-serving-server
```

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<h2 align="center">Quick Start Example</h2>
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### Boston House Price Prediction model
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``` shell
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wget --no-check-certificate https://paddle-serving.bj.bcebos.com/uci_housing.tar.gz
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tar -xzf uci_housing.tar.gz
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```
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Paddle Serving provides HTTP and RPC based service for users to access

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### HTTP service
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``` shell
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python -m paddle_serving_server.web_serve --model uci_housing_model --thread 10 --port 9292 --name uci
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```
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<center>

- thread: Concurrency of current service
- port: Exposed port of current service to users
- name: Service name, can be used to generate HTTP request url
- model: Path of paddle model directory to be served

</center>

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``` shell
curl -H "Content-Type:application/json" -X POST -d '{"x": [0.0137, -0.1136, 0.2553, -0.0692, 0.0582, -0.0727, -0.1583, -0.0584, 0.6283, 0.4919, 0.1856, 0.0795, -0.0332], "fetch":["price"]}' http://127.0.0.1:9292/uci/prediction
```
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### RPC service
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``` shell
python -m paddle_serving_server.serve --model uci_housing_model --thread 10 --port 9292
```
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- thread: Concurrency of current service
- port: Exposed port of current service to users
- model: Path of paddle model directory to be served

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``` python
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# A user can visit rpc service through paddle_serving_client API
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from paddle_serving_client import Client

client = Client()
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client.load_client_config("uci_housing_client/serving_client_conf.prototxt")
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client.connect(["127.0.0.1:9292"])
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data = [0.0137, -0.1136, 0.2553, -0.0692, 0.0582, -0.0727,
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        -0.1583, -0.0584, 0.6283, 0.4919, 0.1856, 0.0795, -0.0332]
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fetch_map = client.predict(feed={"x": data}, fetch=["price"])
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print(fetch_map)
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```

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<h2 align="center">Models waiting for you to deploy</h2>
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<center>

|      Model Name      	|              Resnet50              	|
|:--------------------:	|:----------------------------------:	|
|      Package URL     	|           To be released           	|
|      Description     	| Get the representation of an image 	|
| Training Data Source 	|              Imagenet              	|

</center>


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<h2 align="center">Document</h2>
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### New to Paddle Serving
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- [How to save a servable model?](doc/SAVE.md)
- [An end-to-end tutorial from training to serving](doc/END_TO_END.md)
- [Write Bert-as-Service in 10 minutes](doc/Bert_10_mins.md)
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### Developers
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- [How to config Serving native operators on server side?](doc/SERVER_DAG.md)
- [How to develop a new Serving operator](doc/NEW_OPERATOR.md)
- [Golang client](doc/IMDB_GO_CLIENT.md)
- [Compile from source code(Chinese)](doc/COMPILE.md)
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### About Efficiency
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- [How profile serving efficiency?(Chinese)](https://github.com/PaddlePaddle/Serving/tree/develop/python/examples/util)
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### FAQ
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- [FAQ(Chinese)](doc/FAQ.md)
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### Design
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- [Design Doc(Chinese)](doc/DESIGN.md)
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### Join Community

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To connect with other users and contributors, welcome to join our [Slack channel](https://paddleserving.slack.com/archives/CUBPKHKMJ)

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### Contribution
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If you want to contribute code to Paddle Serving, please reference [Contribution Guidelines](doc/CONTRIBUTE.md)
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### Feedback
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For any feedback or to report a bug, please propose a [GitHub Issue](https://github.com/PaddlePaddle/Serving/issues).

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### License

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[Apache 2.0 License](https://github.com/PaddlePaddle/Serving/blob/develop/LICENSE)