Steps to Create Bot

Photo by Kindel Media at pexel

If you want to develop a ChatBot with Azure and OpenAi in a few simple steps. You can follow the steps below.

1. Design and Requirements Gathering:

• Define the purpose and functionalities of the chatbot.

• Gather requirements for integration with Azure, OpenAI, Langchain, Promo Engineering, Document Intelligence System, KNN-based question similarities with Redis, vector database, and Langchain memory.

1. Azure Setup:

• Create an Azure account if you don't have one.

• Set up Azure Functions for serverless architecture.

• Request access to Azure OpenAI Service.

1. OpenAI Integration:

• Obtain API access to OpenAI.

• Integrate OpenAI's GPT models for natural language understanding and generation into your chatbot.

1. Langchain Integration:

• Explore Langchain's capabilities for language processing and understanding.

• Integrate Langchain into your chatbot for multilingual support or specialized language tasks.

• Implement Langchain memory for retaining context across conversations.

1. Promo Engineering Integration:

• Understand Promo Engineering's features for promotional content generation and analysis.

• Integrate Promo Engineering into your chatbot for creating and optimizing promotional messages.

1. Document Intelligence System Integration:

• Investigate the Document Intelligence System's functionalities for document processing and analysis.

• Integrate Document Intelligence System for tasks such as extracting information from documents or providing insights.

1. Development of Chatbot Logic:

• Develop the core logic of your chatbot using Python.

• Utilize Azure Functions for serverless execution of the chatbot logic.

• Implement KNN-based question similarities using Redis for efficient retrieval and comparison of similar questions.

1. Integration Testing:

• Test the integrated components of the chatbot together to ensure seamless functionality.

1. Azure AI Studio Deployment:

• Deploy LLM model in Azure AI Studio.

• Create an Azure AI Search service.

• Connect Azure AI Search service to Azure AI Studio.

• Add data to the chatbot in the Playground.

• Add data using various methods like uploading files or programmatically creating an index.

• Use Azure AI Search service to index documents by creating an index and defining fields for document properties.

1. Deployment and Monitoring:

• Deploy the chatbot as an App.

• Navigate to the App in Azure.

• Set up monitoring and logging to track performance and user interactions.

1. Continuous Improvement:

• Collect user feedback and analyze chatbot interactions.

• Iterate on the chatbot's design and functionality to enhance user experience and performance.

https://github.com/Azure-Samples/azureai-samples