# Build an AI Line Chatbot using AWS Bedrock

From the [**last article**](https://medium.com/@ar851060/how-to-make-a-line-chatbot-with-aws-lambda-b8b77f79d4cf), I explained how to use build a simple chatbot with AWS Lambda. However, the chatbot we built last time it can only response what you said, it did not **Chat** at all. This time, I try to connect that chatbot with AWS bedrock, and choose a perfect LLM so that it can actually chat with us.


## Steps
1. Get the access of models from AWS bedrock, and choose the suitable model
2. Create a no sql database from DynamoDB
3. Open the permissions from AWS IAM
4. Install boto layers
5. Connect Bedrock and DynamoDB to AWS Lambda

## Get Access of Models from Bedrock
Go to Bedrock console to open the access of models. Scrolling down the side bar to the bottom, you can see `Model access`. Click on it.


After clicking, you will find tons of model names, on top left of the list of model name, you will find `Request access`. Or find `Modify model access`, they are the same link.

:::warning
:warning: What location of server you chose decide which models you can use.
For example, models in Oregon is more than models in Tokyo.
:::

You can get the all access in AWS, and AWS will automatically decide which models you can use. Press `Next` until press `Submit`.

:::info
:information_source: If you want to use Claude models from Anthropic, you need to input additional information for access.
:::

Once you see the `Access status` of all models you selected are green, then this step is completed. The process of waiting access needs some time, so you can do the next step while waiting.

## Create a No SQL Database from DynamoDB

Now, go to the DynamoDB console. Press `Craete tables` to create a table.
You can name whatever you want in `Table name`. Please put **userId** in `Partition key` and set it as `string`.
After creating, click your table which you just created, and under the `General information`, expand `Additional info` and get ARN.

## Open the Permissions from AWS IAM

Go back to the lambda function you wrote in last article. Under `Configuration`, click `Permissions` on the left side bar. Press the link under `Role name`.
After entering IAM, press `Add permissions - Create inline policy`.
- Choose service `Bedrock`. If you are lazy enough (like me), click `All Bedrock actions` in `Actions allowed` and click `all` in `Resources`.
- Choose service `DynamoDB`. If you are lazy enough (like me), click `All Bedrock actions` in `Actions allowed` and click `all` in `Resources`.

Name the policy whatever you want, and create two policies. One is for Bedrock and the other is for DynamoDB.

## Connect Bedrock and DynamoDB to AWS Lambda

First, you need to build a layer for boto3, the AWS python SDK. The way how to build a layer is in the [last article](https://medium.com/@ar851060/how-to-make-a-line-chatbot-with-aws-lambda-b8b77f79d4cf).

Modify my following example code, I used **mistral.mixtral-8x7b-instruct** as my model.

from linebot import (
    LineBotApi, WebhookHandler
)
from linebot.exceptions import (
    InvalidSignatureError
)
from linebot.models import (
    MessageEvent, TextMessage, TextSendMessage,
)

import os
import json
import boto3

client = boto3.client('bedrock-runtime')
line_bot_api = LineBotApi(os.environ['Channel_access_token'])
handler = WebhookHandler(os.environ['Channel_secret'])
modelId = "mistral.mixtral-8x7b-instruct-v0:1"
accept = 'application/json'
contentType = 'application/json'
dynamodb = boto3.resource('dynamodb', region_name='us-west-2')
table = dynamodb.Table('tableName')

def lambda_handler(event, context):
    @handler.add(MessageEvent, message=TextMessage)
    def handle_message(event):
        db_res = table.get_item(
            Key={
                'userId': event.source.user_id
            }
        )
        item = db_res.get('Item')
        
        if item:
            messageText = item['history']
            messageText += "<s>[INST]"+event.message.text+"[/INST]"
        else:
            messageText = "<s>[INST]"+event.message.text+"[/INST]"
            
        mistral_input = json.dumps({
        "prompt": messageText, 
        "max_tokens":500,
        "temperature":0.5,
        "top_p":0.9,
        "top_k":50
        })
            
        response = client.invoke_model(body=mistral_input, modelId=modelId, accept=accept, contentType=contentType)
        response_body = json.loads(response.get("body").read())
        response_text = response_body['outputs'][0]['text']
        
        messageText += response_text + "</s>"
        res_put = table.put_item(
        Item={
            'userId': event.source.user_id,
            'history': messageText
            }
        )
            
        line_bot_api.reply_message(
            event.reply_token,
            TextSendMessage(text=response_text))

    # get X-Line-Signature header value
    signature = event['headers']['x-line-signature']

    # get request body as text
    body = event['body']

    # handle webhook body
    try:
        handler.handle(body, signature)
    except InvalidSignatureError:
        return {
            'statusCode': 502,
            'body': json.dumps("Invalid signature. Please check your channel access token/channel secret.")
            }
    return {
        'statusCode': 200,
        'body': json.dumps("Hello from Lambda!")
        }

Deploy again, and it should be work.

:::success
:bulb: If you want to change the model, please be careful that models from different companies need different structure of input. You can see it in `Bedrock - providers`
:::