飞书多维表格利用 Amazon Bedrock AI 能力赋能业务

git clone https://github.com/Lark-Base-Team/field-demo.git

├── config.json // 本地调试授权的配置文件├── package-lock.json├── package.json├── src│   └── index.ts // 项目入口文件└── tsconfig.json

# 安装依赖npm install# 启动本地服务npm run start

// 定义捷径的入参  formItems: [    {        key: 'prompt',        label: t('prompt'),        component: FieldComponent.Input,        props: {            placeholder: t('prompt_placeholder')        },        validator: {            required: true,        }    },    {        key: 'bedrockEndpoint',        label: t('endpoint'),        component: FieldComponent.Input,        props: {            placeholder: t('endpoint_placeholder')        },        validator: {            required: true,        }    },    {        key: 'accessKey',        label: t('accessKey'),        component: FieldComponent.Input,        props: {            placeholder: t('accessKey_placeholder'),        },        validator: {            required: true,        }    },    {        key: 'secretKey',        label: t('secretKey'),        component: FieldComponent.Input,        props: {            placeholder: t('secretKey_placeholder'),        },        validator: {            required: true,        }    },    {        key: 'modelType',        label: t('modelType'),        component: FieldComponent.SingleSelect,        props: {            placeholder: t('modelType_placeholder'),            options: [                { label: 'Amazon Nova Pro', value: 'amazon.nova-pro-v1:0' },                { label: 'Amazon Nova Lite', value: 'amazon.nova-lite-v1:0' },                { label: 'Amazon Nova Micro', value: 'amazon.nova-micro-v1:0' },                { label: 'DeepSeek R1', value: 'deepseek.r1-v1:0' }            ]        },        validator: {            required: true,        }    }  ],  // 定义捷径的返回结果类型  resultType: {    type: FieldType.Text,  },  // formItemParams 为运行时传入的字段参数，对应字段配置里的 formItems （如引用的依赖字段）  execute: async (formItemParams , context) => {    const { prompt, modelType, bedrockEndpoint, accessKey, secretKey } = formItemParams;    /** 为方便查看日志，使用此方法替代console.log */    function debugLog(arg: any) {      console.log(JSON.stringify({        formItemParams,        context,        arg      }))    }
    // 创建 Bedrock Runtime 客户端    const client = new BedrockRuntimeClient({       endpoint: bedrockEndpoint, // 设置你的 Amazon Bedrock endpoint      credentials: {          accessKeyId: accessKey,          secretAccessKey:  secretKey,      }    });
    const message = {      content: [{ text: prompt }],      role: ConversationRole.USER,    };
    const request = {      modelId: modelType.value,      messages: [message],      inferenceConfig: {        maxTokens: 1000, // The maximum response length        temperature: 0.7, // Using temperature for randomness control      },    };
    try {        const response = await client.send(new ConverseCommand(request));        console.log(response.output.message.content[0].text);        const generatedText = response.output.message.content[0].text;
        return {            code: FieldCode.Success,            data: generatedText        };    } catch (error) {        console.error('调用 Amazon Bedrock API 时出错:', error);        return {            code: FieldCode.Error,            errorMessage: '调用 Amazon Bedrock API 时出错'        };    }  },