jsontovectorsrch's Introduction

Load Files from Jira into CogSearch

The issues from Jira are loaded into CogSearch by following below steps

Establish a connection with Jira using the Python SDK.
Retrieve the required issues from Jira using the JQL query and Search method.
Use Azure open ai to index the issue content.
Index the parsed chunks into Azure Cognitive Search.
Repeat the process for all the required files.

Using the Azure Storage Pyhon SDK to fetch the file stream and use PYPDF and Document Intelligence to chunk the page in memory and create a vector index

https://developer.atlassian.com/cloud/jira/platform/rest/v3/api-group-issue-search/#api-rest-api-3-search-post
Refer to https://github.com/MSUSAzureAccelerators/Azure-Cognitive-Search-Azure-OpenAI-Accelerator/blob/main/04-Complex-Docs.ipynb for loading large documents using PYPDF and Document Intelligence-

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