Lex BedrockAgentIntent controlling Fulfilled

The behavior you're experiencing with your Lex bot using a BedrockAgentIntent is related to how Lex handles intent fulfillment and context management. To address this issue and control the behavior, you can consider the following approaches:

1. Use Context Management: Implement context management in your Lex bot to maintain the conversation state. You can set output contexts when the BedrockAgentIntent is fulfilled, and then use input contexts to ensure that the same intent remains active for follow-up interactions. This way, you can prevent the conversation from defaulting to the FallbackIntent after each response.

2. Modify Intent Configuration: Review the configuration of your BedrockAgentIntent in Lex. Ensure that it's set up to handle multiple turns of conversation rather than being marked as fulfilled after a single response. You may need to adjust the fulfillment settings or dialog management options for the intent.

3. Implement a Custom Lambda Function: Consider using a Lambda function as a code hook for your BedrockAgentIntent. This function can help manage the conversation flow, determine when the intent should be truly fulfilled, and prevent premature transitions to the FallbackIntent.

4. Utilize Session Attributes: Make use of session attributes in Lex to maintain state information between turns. You can set specific attributes when the BedrockAgentIntent is invoked and check for these attributes in subsequent turns to determine whether to continue with the same intent or allow a transition to other intents.

5. Adjust Confidence Thresholds: Review and possibly adjust the confidence thresholds for intent recognition in your Lex bot. This can help ensure that the BedrockAgentIntent is more likely to be triggered in follow-up utterances instead of defaulting to the FallbackIntent.

6. Implement a Custom Parser: If the default parsing in Lex doesn't meet your needs, consider implementing a custom parser. This can give you more control over how the bot processes and interprets user inputs, potentially helping to maintain the conversation within the BedrockAgentIntent.

7. Refine Prompts and Responses: Ensure that the prompts and responses from your BedrockAgentIntent are designed to encourage continued interaction within the same context, rather than appearing to conclude the conversation.

By implementing one or more of these strategies, you should be able to better control the behavior of your Lex bot and maintain a more interactive conversation flow when using the BedrockAgentIntent. Remember to test thoroughly after making changes to ensure the desired behavior is achieved.

Sources
Setting intent context for your Lex V2 bot - Amazon Lex
Bedrock agent accuracy | AWS re:Post
Control agent session context - Amazon Bedrock