Видео

All the best!

You could use Google Vertex AI Agents for that. Pls see: ruclips.net/video/H6nUoszwcrM/видео.html

Your question is not clear to me. Do you get an error when you start chatting with the bot Or at some other point?

Glad you liked it!

May I know cost wise which one is better. AWS vs Azure vs GCP. And in the industry which one preferred?

Depends on what services you are using. AWS is most popular.

You can query data in Redshift directly from QuickSight. Athena is not needed.

@@ArchitectureBytes thanks for the update

Since the question mentions 'adhoc analysis' - Amazon Athena is a good choice. QuickSight excels at BI and Reporting.

@@ArchitectureBytes Thank you!

Do you mean you want to become an expert in Amazon Connect? If so, you can start with this Tutorial.

In that case, you can paste a template json yourself.

Glad you found it useful! IoT Playlist: ruclips.net/p/PLGhcieJ42HtHoIO3AGuCD00PZ7EhNNGtw

In the tutorial - Phone number is attached to the Amazon Connect Flow (ProductFlow) - which in turn uses Lex Bot. I guess you are asking - if we can we assign Phone Number directly to the Lex Bot (or an Intent)? As of today - I don't see a way to attach a Phone Number directly to a Lex Bot.

@@ArchitectureBytesWell actually what I wanted to see is if there is some way to ask about the products just like you did in the example but through a call. Carching the customer inputs and reproducing the bot responses until you get the goodbyeIntent but all of this in a phone call

@@juanpa9590 Yes of course - pls see the demo at 14:55 - Customer Support via Phone Call!

The QnA Intent (ProductIntent) is a built-in Gen AI intent, it can answer questions automatically from the Knowledge Base using a foundation model (LLM)

@@ArchitectureBytes @ 5:17 in the video, you have the option to click into the fulfillment area and designate what you want to happen as a next step in the Success Response and others. For example, you can Wait for Users Input or go to Intent, or go to Slot within and Intent, to name a few options. I'm curious about what you've selected because I have the same intent created. Is your next step truly set on nothing? If it's set on Wait for Users Input, I found it interesting that when the user said Thanks, it clicked over to the good bye intent. That's all great and designed well. I'm just curious how you get the QnA intent to break out of AI mode and get back to pre-made intents. Thanks

Ok I understand your question now. For the ProductIntent (QnA Intent) I have not set any specific options in Fulfillment or Closing Response, and there is no Initial Response or Slot options available here. My understanding is that, each user prompt is evaluated independently every-time to determine the most appropriate intent to handle it. However there are scenarios where conversation can get "stuck" - particularly if the intent's fulfillment requires multiple steps or slots to be filled. In such cases, the chatbot may expect the user to provide specific information to complete the current intent before moving on to another one. And if the default behavior is not the best, you can guide the conversation in desired direction by providing 'Next step in Conversation'

Glad it was helpful!

What kind of complete course?

Once data reaches AWS IoT Core (on cloud), you can use IoT Core Rules to send data to a service that can store data in a database (DynamoDB, Timestream etc). From there it should be easy to visualize the data using QuickSight, Grafana etc

What happens when you click "Preview Web Experience" button 06:31 ? Please point out the video timestamp where you are stuck.

Please make sure that your Agent Instructions are clear and accurate. In addition you can provide Examples 11:28. The above two are the most important measures to take. You can also play with Temperature settings under Settings > Gen AI > Temperature. A lower temperature settings reduces randomness of tokens selection (therefore response).

​@@ArchitectureBytes i get JSON schema, have i modify in this schema & how i get url for this schema, like at 6:07, and at 7:15 how will get python code (flask import) & i am working on multiple tools on the same agent, is it will be work?

@@ManikantaKomma In the Open API Schema The 'url' is url of your Google Cloud Function (without function name at the end). Path has the Cloud function name. OperationId is the method name in function. If 'flask' dependency is not automatically handled, then in the requirements.txt file present alongside the CloudFunction python file - add a line 'flask'. Of course you can use multiple tools in an agent - this is shown in this tutorial itself.

@@ArchitectureBytes i given multiple examples but and getting hallucinations results and getting Failed to generate response, Temperature option not visible in Gen AI

@@ManikantaKomma What's there in your Data Store? Is it 'Cloud Storage' with unstructured documents (pdf?) from a bucket? By hallucination - do you mean it gives you incorrect information? Or it says it doesn't have the information (which is not exactly hallucination)?

Automatically

AI Agents already use RAG techniques. Please see this video to understand RAG better: ruclips.net/video/buTi1AarFDs/видео.html

Sure. What is the problem / error message?