AWS-native chatbot using Bedrock + Claude

This repository is a sample chatbot using the Anthropic company's LLM Claude, one of the foundational models provided by Amazon Bedrock for generative AI.

Not only text but also images are available with Anthropic's Claude 3. Currently we support Haiku, Sonnet and Opus.

Add your own instruction and give external knowledge as URL or files (a.k.a RAG). The bot can be shared among application users. The customized bot also can be published as stand-alone API (See the detail).

Analyze usage for each user / bot on administrator dashboard. detail

• English 💬
• 日本語 💬 (ドキュメントはこちら)
• 한국어 💬
• 中文 💬
• Français 💬
• Deutsch 💬
• Español 💬
• Italian 💬

• In the us-east-1 region, open Bedrock Model access > Manage model access > Check Anthropic / Claude 3 Haiku, Anthropic / Claude 3 Sonnet and Cohere / Embed Multilingual then Save changes.

• Open CloudShell at the region where you want to deploy
• Run deployment via following commands

git clone https://github.com/aws-samples/bedrock-claude-chat.git
cd bedrock-claude-chat
chmod +x bin.sh
./bin.sh

• After about 30 minutes, you will get the following output, which you can access from your browser

Frontend URL: https://xxxxxxxxx.cloudfront.net

The sign-up screen will appear as shown above, where you can register your email and log in.

It's an architecture built on AWS managed services, eliminating the need for infrastructure management. Utilizing Amazon Bedrock, there's no need to communicate with APIs outside of AWS. This enables deploying scalable, reliable, and secure applications.

• Amazon DynamoDB: NoSQL database for conversation history storage
• Amazon API Gateway + AWS Lambda: Backend API endpoint (AWS Lambda Web Adapter, FastAPI)
• Amazon CloudFront + S3: Frontend application delivery (React, Tailwind CSS)
• AWS WAF: IP address restriction
• Amazon Cognito: User authentication
• Amazon Bedrock: Managed service to utilize foundational models via APIs. Claude is used for chat response and Cohere for vector embedding
• Amazon EventBridge Pipes: Receiving event from DynamoDB stream and launching ECS task to embed external knowledge
• Amazon Elastic Container Service: Run crawling, parsing and embedding tasks. Cohere Multilingual is the model used for embedding.
• Amazon Aurora PostgreSQL: Scalable vector store with pgvector plugin
• Amazon Athena: Query service to analyze S3 bucket

Super-easy Deployment uses AWS CodeBuild to perform deployment by CDK internally. This section describes the procedure for deploying directly with CDK.

• Please have UNIX, Docker and a Node.js runtime environment. If not, you can also use Cloud9

• Clone this repository

git clone https://github.com/aws-samples/bedrock-claude-chat

• Install npm packages

cd bedrock-claude-chat
cd cdk
npm ci

• Install AWS CDK

npm i -g aws-cdk

• Before deploying the CDK, you will need to work with Bootstrap once for the region you are deploying to. In this example, we will deploy to the us-east-1 region. Please replace your account id into <account id>.

cdk bootstrap aws://<account id>/us-east-1

• If necessary, edit the following entries in cdk.json if necessary.

  • bedrockRegion: Region where Bedrock is available. NOTE: Bedrock does NOT support all regions for now.
  • allowedIpV4AddressRanges, allowedIpV6AddressRanges: Allowed IP Address range.

• Deploy this sample project

cdk deploy --require-approval never --all

• You will get output similar to the following. The URL of the web app will be output in BedrockChatStack.FrontendURL, so please access it from your browser.

 ✅  BedrockChatStack

✨  Deployment time: 78.57s

Outputs:
BedrockChatStack.AuthUserPoolClientIdXXXXX = xxxxxxx
BedrockChatStack.AuthUserPoolIdXXXXXX = ap-northeast-1_XXXX
BedrockChatStack.BackendApiBackendApiUrlXXXXX = https://xxxxx.execute-api.ap-northeast-1.amazonaws.com
BedrockChatStack.FrontendURL = https://xxxxx.cloudfront.net

Update enableMistral to true in cdk.json, and run cdk deploy.

...
  "enableMistral": true,

Edit config.py and run cdk deploy.

# See: https://docs.anthropic.com/claude/reference/complete_post
GENERATION_CONFIG = {
    "max_tokens": 2000,
    "top_k": 250,
    "top_p": 0.999,
    "temperature": 0.6,
    "stop_sequences": ["Human: ", "Assistant: "],
}

If using cli and CDK, please cdk destroy. If not, access CloudFormation and then delete BedrockChatStack and FrontendWafStack manually. Please note that FrontendWafStack is in us-east-1 region.

By setting cdk.json in the following CRON format, you can stop and restart Aurora Serverless resources created by the VectorStore construct. Applying this setting can reduce operating costs. By default, Aurora Serverless is always running. Note that it will be executed in UTC time.

...
"rdbSchedules": {
  "stop": {
    "minute": "50",
    "hour": "10",
    "day": "*",
    "month": "*",
    "year": "*"
  },
  "start": {
    "minute": "40",
    "hour": "2",
    "day": "*",
    "month": "*",
    "year": "*"
  }
}

This asset automatically detects the language using i18next-browser-languageDetector. You can switch languages from the application menu. Alternatively, you can use Query String to set the language as shown below.

https://example.com?lng=ja

This sample has self sign up enabled by default. To disable self sign up, open auth.ts and switch selfSignUpEnabled as false, then re-deploy.

const userPool = new UserPool(this, "UserPool", {
  passwordPolicy: {
    requireUppercase: true,
    requireSymbols: true,
    requireDigits: true,
    minLength: 8,
  },
  // Set to false
  selfSignUpEnabled: false,
  signInAliases: {
    username: false,
    email: true,
  },
});

By default, this sample does not restrict the domains for sign-up email addresses. To allow sign-ups only from specific domains, open cdk.json and specify the domains as a list in allowedSignUpEmailDomains.

"allowedSignUpEmailDomains": ["example.com"],

This sample supports external identity provider. Currently we support Google and custom OIDC provider.

See LOCAL DEVELOPMENT.

Thank you for considering contributing to this repository! We welcome bug fixes, language translations (i18n), feature enhancements, and other improvements.

For feature enhancements and other improvements, before creating a Pull Request, we would greatly appreciate it if you could create a Feature Request Issue to discuss the implementation approach and details. For bug fixes and language translations (i18n), proceed with creating a Pull Request directly.

Please also take a look at the following guidelines before contributing:

• Local Development
• CONTRIBUTING

See here.

• Takehiro Suzuki
• Yusuke Wada

This library is licensed under the MIT-0 License. See the LICENSE file.