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update document
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GentleWang1011 committed Sep 9, 2021
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2 changes: 1 addition & 1 deletion document/docs/config/proxy.md
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</table>

### route_table配置
**在2.1.0版本之后开始支持HTTP接口配置,2.1.0之前的版本只支持GRPC配置。**
**在2.1.0版本开始支持HTTP接口配置,2.1.0之前的版本只支持GRPC配置。**

1.GRPC
```yaml
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4 changes: 2 additions & 2 deletions document/docs/index.md
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Expand Up @@ -13,12 +13,12 @@ serving-proxy 是serving-server的代理,对外提供了grpc接口以及http
serving-admin 提供在线集群的可视化操作界面, 可以查看管理集群中各节点的配置以及状态、查看模型列表、流量的调控、并能提供一定的监控的功能。[点击查看详情](./example/admin.md)

• zookeeper
zookeeper 用户各组件的信息同步协调以及服务注册于发现
zookeeper 用户各组件的信息同步协调以及服务注册与发现

### 架构简介
各组件的具体功能以及整个项目的功能如下图所示:
![架构1](img/Structure1.jpg)
![架构2](img/Structure2.jpg)
![架构2](img/Structure2.jpg)

### 源码结构
• fate-serving-register:主要为服务治理相关的逻辑
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5 changes: 2 additions & 3 deletions document/docs/inference/single.md
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"x4": 1.307686
},
"sendToRemoteFeatureData": {
"device_id": "8",
"phone_num": "122222222"
"id": "123"
}
}
}
```
**Note**:
>head中填入系统参数,featureData中为模型所需特征数据,不会传递给Host方,只有sendToRemoteFeatureData中的才会传递给Host方,一般sendToRemoteFeatureData需要包含host方用于匹配样本的id,例如设备号或者手机号
>head中填入系统参数,featureData中为模型所需特征数据,不会传递给Host方,只有sendToRemoteFeatureData中的才会传递给Host方,一般sendToRemoteFeatureData需要包含host方用于匹配样本的id,例如设备号或者手机号等。
#### 响应内容
<table>
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10 changes: 5 additions & 5 deletions document/docs/model/load.md
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![flow](../img/flow.jpg)

### FATE-Flow的配置(以1.4.x 版本为例)
在执行模型的推送和绑定操作之前,需要先配置FATE-Flow,并重启FATE-Flow
**Note** 注意多方都需要修改成各自FATE-Serving的实际部署地址
在执行模型的推送和绑定操作之前,需要先配置FATE-Flow,并重启FATE-Flow
>**Note:** 多方都需要修改成各自FATE-Serving的实际部署地址
#### 未启用注册中心(zookeeper)
修改arch/conf/server_conf.json,填入FATE-Serving集群实际部署serving-server服务的ip:port,如:
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- 192.168.1.1:2181
- 192.168.1.1:2182
```
其中ZOOKEEPER_HOSTS填入FATE-Serving集群实际部署Zookeeper的ip:port
其中zookeeper.hosts填入FATE-Serving集群实际部署Zookeeper的ip:port

• 若zookeeper开启了ACL,则需要添加以下配置,否则略过此步骤。修改部署目录下arch/conf/base_conf.yaml
```yml
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```
其中use与password填入FATE-Serving集群实际部署ZooKeeper的用户名与密码

**Note**: 配置完上述文件后重启Fate-Flow服务以生效
>**Note**: 配置完上述文件后重启Fate-Flow服务以生效
#### 模型发布
配置路径:$pythonpath/fate_flow/examples/publish_load_model.json
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#### 模型绑定
配置路径:$pythonpath/fate_flow/examples/bind_model_service.json
修改内容:自定义service_id,后续将利用该service_id将模型绑定到模型服务中。将实际任务配置(initiator, role, job_parameters)进行修改,请确保model_id及model_version与离线训练的模型的相同
修改内容:自定义service_id,后续将利用该service_id将模型绑定到模型服务中。将实际任务配置(initiator, role, job_parameters)进行修改,请确保model_id及model_version与离线训练的模型相同
配置格式:
```yml
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