Calling API to Train Your Own Enterprise Data with Azure OpenAI Service

📚 The video demonstrates how to call the Azure OpenAI API to train custom Enterprise data using Postman and a custom application.

🔧 To get started, an Azure OpenAI resource and a cognitive search resource are needed. The video shows how to create these resources.

🤖 The video showcases the creation of a chatbot using the Microsoft Bot Framework and the calling of the API from the custom application.

👉 You can access the ChatGPT source code in Python or C#.

📥 You can upload and store your data in Azure blob storage.

🔄 You can monitor API calls and inspect the pre-processing status.

🔑 The video discusses how to call an API to train your own enterprise data with Azure OpenAI service.

💡 To call the API, a data source needs to be passed in the JSON body, along with the endpoint and API key.

💻 The video also covers the process of formatting the JSON data and troubleshooting common errors.

🔍 The video demonstrates how to call an API to train your own enterprise data with Azure OpenAI Service.

⚙️ The video explains how to use the streaming endpoint and the coding aspect of calling the API using C sharp.

⏲️ It is mentioned that there is a delay of approximately seven seconds when using the API.

👉 The video demonstrates how to make a standard API call using code to train an enterprise data model with Azure OpenAI Service.

🔄 The presenter modifies the code to call Azure chat GPT using input prompts provided by the user.

🔀 The code includes error handling, retrieves the response from the API call, and allows for customization of the input data.

🔍 The transcript discusses debugging an issue with an API call and identifying the problem.

💡 The speaker demonstrates how to use breakpoints to identify and solve the issue with the API call.

⏱️ The debugging process takes longer when using the emulator compared to the online portal.

🔑 Identifying and fixing an index out of range error in the code.

🔎 Exploring the structure of the data response and understanding its organization.

💡 Learning how to use the Azure OpenAI API to train and deploy a web application.