- 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-