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64 lines
2.2 KiB
Markdown
64 lines
2.2 KiB
Markdown
## 构建方法
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确认本机已安装 Docker，然后根据操作系统选择对应的构建命令，并在 `ai-proxy` 目录下执行。构建产物将输出至 `out` 目录。
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***Linux/macOS:***
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```shell
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DOCKER_BUILDKIT=1; docker build --build-arg PLUGIN_NAME=ai-proxy --build-arg EXTRA_TAGS=proxy_wasm_version_0_2_100 --build-arg BUILDER=higress-registry.cn-hangzhou.cr.aliyuncs.com/plugins/wasm-go-builder:go1.19-tinygo0.28.1-oras1.0.0 -t ai-proxy:0.0.1 --output ./out ../..
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```
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***Windows:***
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```powershell
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$env:DOCKER_BUILDKIT=1; docker build --build-arg PLUGIN_NAME=ai-proxy --build-arg EXTRA_TAGS=proxy_wasm_version_0_2_100 --build-arg BUILDER=higress-registry.cn-hangzhou.cr.aliyuncs.com/plugins/wasm-go-builder:go1.19-tinygo0.28.1-oras1.0.0 -t ai-proxy:0.0.1 --output .\out ..\..
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```
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## 本地运行
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参考：https://higress.io/zh-cn/docs/user/wasm-go
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需要注意的是，higress/plugins/wasm-go/extensions/ai-proxy/envoy.yaml中的clusters字段，记得改成你需要地址，比如混元的话：就会有如下的一个cluster的配置：
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```yaml
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<省略>
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static_resources:
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<省略>
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clusters:
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load_assignment:
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cluster_name: moonshot
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endpoints:
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- lb_endpoints:
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- endpoint:
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address:
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socket_address:
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address: hunyuan.tencentcloudapi.com
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port_value: 443
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transport_socket:
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name: envoy.transport_sockets.tls
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typed_config:
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"@type": type.googleapis.com/envoy.extensions.transport_sockets.tls.v3.UpstreamTlsContext
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"sni": "hunyuan.tencentcloudapi.com"
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```
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而后你就可以在本地的pod中查看相应的输出，请求样例如下：
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```sh
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curl --location 'http://127.0.0.1:10000/v1/chat/completions' \
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--header 'Content-Type: application/json' \
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--data '{
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"model": "gpt-3",
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"messages": [
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{
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"role": "system",
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"content": "你是一个名专业的开发人员！"
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},
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{
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"role": "user",
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"content": "你好，你是谁？"
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}
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],
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"temperature": 0.3,
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"stream": false
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}'
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```
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## 测试须知
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由于 `ai-proxy` 插件使用了 Higress 对数据面定制的特殊功能，因此在测试时需要使用版本不低于 1.4.0-rc.1 的 Higress Gateway 镜像。 |