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@@ -55,47 +55,75 @@ Alternatively, you can use Lambda Function URL to replace ALB, see [example](htt
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### Deployment
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Please follow the steps below to deploy the Bedrock Proxy APIs into your AWS account. Only supports regions where Amazon Bedrock is available (such as `us-west-2`). The deployment will take approximately **3-5 minutes** 🕒.
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Please follow the steps below to deploy the Bedrock Proxy APIs into your AWS account. Only supports regions where Amazon Bedrock is available (such as `us-west-2`). The deployment will take approximately **10-15 minutes** 🕒.
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**Step 1: Create your own API key in Secrets Manager (MUST)**
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> **Note:** This step is to use any string (without spaces) you like to create a custom API Key (credential) that will be used to access the proxy API later. This key does not have to match your actual OpenAI key, and you don't need to have an OpenAI API key. please keep the key safe and private.
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1. Open the AWS Management Console and navigate to the AWS Secrets Manager service.
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2. Click on "Store a new secret" button.
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2. Click on "Store a new secret" button.
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3. In the "Choose secret type" page, select:
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Secret type: Other type of secret
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Key/value pairs:
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- Key: api_key
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- Value: Enter your API key value
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Click "Next"
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4. In the "Configure secret" page:
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Secret name: Enter a name (e.g., "BedrockProxyAPIKey")
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Description: (Optional) Add a description of your secret
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5. Click "Next" and review all your settings and click "Store"
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After creation, you'll see your secret in the Secrets Manager console. Make note of the secret ARN.
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After creation, you'll see your secret in the Secrets Manager console. Make note of the secret ARN.
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**Step 2: Build and push container images to ECR**
4. On the "Specify stack details" page, provide the following information:
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- Stack name: Change the stack name if needed.
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- ApiKeySecretArn: Enter the secret ARN you used for storing the API key.
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Click "Next".
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5. On the "Configure stack options" page, you can leave the default settings or customize them according to your needs. Click "Next".
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6. On the "Review" page, review the details of the stack you're about to create. Check the "I acknowledge that AWS CloudFormation might create IAM resources" checkbox at the bottom. Click "Create stack".
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6. On the "Configure stack options" page, you can leave the default settings or customize them according to your needs. Click "Next".
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7. On the "Review" page, review all details. Check the "I acknowledge that AWS CloudFormation might create IAM resources" checkbox at the bottom. Click "Submit".
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That is it! 🎉 Once deployed, click the CloudFormation stack and go to **Outputs** tab, you can find the API Base URL from `APIBaseUrl`, the value should look like `http://xxxx.xxx.elb.amazonaws.com/api/v1`.
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@@ -247,12 +275,6 @@ Note that not all models are available in those regions.
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You can use the [Models API](./docs/Usage.md#models-api) to get/refresh a list of supported models in the current region.
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### Can I build and use my own ECR image
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Yes, you can clone the repo and build the container image by yourself (`src/Dockerfile`) and then push to your ECR repo. You can use `scripts/push-to-ecr.sh`
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Replace the repo url in the CloudFormation template before you deploy.
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### Can I run this locally
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Yes, you can run this locally, e.g. run below command under `src` folder:
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### How to upgrade?
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To use the latest features, you don't need to redeploy the CloudFormation stack. You simply need to pull the latest image.
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To do so, depends on which version you deployed:
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-**Lambda version**: Go to AWS Lambda console, find the Lambda function, then find and click the `Deploy new image` button and click save.
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-**Fargate version**: Go to ECS console, click the ECS cluster, go the `Tasks` tab, select the only task that is running and simply click `Stop selected` menu. A new task with latest image will start automatically.
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To use the latest features, you need follow the deployment guide to redeploy the application. You can upgrade the existing CloudFormation stack to get the latest changes.
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