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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.

2. 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.

3. OpenAI Integration:

   - Obtain API access to OpenAI.

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

4. 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.

5. 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.

6. 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.

7. 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.

8. Integration Testing:

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

9. 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.

10. 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.

11. 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


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