Google Vertex AI Agent Builder Tutorial 

You would add that information to Agent instructions. When invoking a Tool (eg. OpenAPI) - agent passes parameters based on available information whether provided explicitly by the end user or available in the instructions. Your Open API Schema definition (eg. param name, description) should be well defined. Your instruction could be something like: Always assume that City name is Chicago. So, if your Tool (API) expects City as parameter, it would get Chicago as parameter, and agent will not need to ask for this information from the end user.

@@ArchitectureBytes Thank you for the reply! Will this work if the parameter is not a predefined one? Let's say my system where the chatbot is deployed on decides the City Name and I would like to send that as a parameter. How can my instructions be something like "Get the City name from the System" and how can i send it? My user interface is using integration

You can instruct the Agent to fetch City name by invoking a Tool (API). Please watch the video completely - it shows how Agents are instructed to invoke Tools. I also suggest that you watch this video (AI Agent Architecture) to understand how Agents work: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-FEU6-Il8jjw.html

Yes, in the tutorial we are passing productId to the function - the OpenAPI schema defines this interface.

Yes, it works. You could create separate Tools of type Data Store - for each Data Store, and have your Agent Instructions point to them. Make sure Data Store is connected to the Application. Remember that upon creating a new Data Store - it takes some time to import/index the data. So, agent can use it only after that.

Please see the Readme in github repository linked in video description. Did you update the OpenAPI Schema with your own cloud function URL, name and operationId as suggested?

@@ArchitectureBytes I fixed the problem with the getProductQuantity, but i can't integrate dialogflow. can you help me with this?

You mean integrate with the Dialogflow Messenger? What problem are you facing?

Yes! This tutorial demonstrates that.

@@ArchitectureBytes Thank you so much.

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)?