kjdfklgfYou can check the documentation to understand the structure of the response. First we will create a function to get the latest news bas on the query you provide Step 1 Describe our function Next we will implement a tool setup to describe the composition of the external data function so that the model knows what type of data is requir. This should include the following steps: Integrating external tools into our assistant In this step we will create a function call. It will prompt a conversation with the model to execute the external data function specifi in the tool and dynamically integrate the response.
First we will define an array
To keep track of all conversations we have with the assistant and provide detail context when making new requests. Once this is done we will set up the core functionality of the assistant. from external Hong Kong Telegram Number Data functions to generate comprehensive and relevant reports for you. Step 1 Run our assistant Our last step is to create a function that provides the function query parameters for our research query and handle its execution. Run it in your terminal You should see a response similar to the following. External Data Research Assistant What’s interesting is that the knowlge cutoff for the model is year and month before Apple’s release.
Despite this limitation the
Model provides relevant research reports because we supplement our queries with external data. Others that you can integrate into your assistant can be or anything else that you have access to that India Phone Number List has structur responses. Conclusion What an exciting journey it has been. This tutorial explores key concepts that help us understand how popular artificial intelligence applications work. We then built an AI research assistant that could understand our queries and use them to generate human-like responses. To further enhance our basic example we incorporat external data sources via function calls ensuring that our.
