OpenAI Chat text retrieval
The project aims to create a system that efficiently retrieves and organizes various document types (Word, PDF, Excel) for easy access. It will use natural language understanding and Large Language Models (LLMs) from Azure OpenAI to interpret user queries and generate relevant outputs from the documents. Customization and fine-tuning of LLMs will enhance accuracy. A user-friendly interface will facilitate interaction. Performance optimization ensures fast responses, scalability, and robustness.
PROCESS WORKFLOW OVERVIEW
In this solution, your documents are stored in Azure Blob Storage, and you'll fine-tune an Azure OpenAI model using these documents. Once fine-tuned, the model will understand the content better. Then, you'll integrate it with Azure Cognitive Search, which will index and make your documents searchable. When users ask questions, the model will process these queries, extracting relevant information from the documents. This combined with Cognitive Search will ensure users get accurate responses. You'll create a simple user interface for users to input queries and receive answers generated by the model and search results. Testing, user feedback, and regular maintenance will help ensure the system works smoothly and continues to improve over time