Skill

Query Jira Issues and Load Data

JIRA Reader retrieves JIRA issues based on your query. Connects via basic auth, OAuth2, or PAT for server instances.

Works with jira

57
Spark score
out of 100
Updated 4 days ago
Version 0.14.22
Models

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Why it matters

Effortlessly extract and load Jira issues into your data pipeline. This asset connects to your Jira instance to retrieve specific issues based on your queries, making it easy to integrate project data into other systems.

Outcomes

What it gets done

01

Connect to Jira using basic auth, OAuth2, or Personal Access Tokens.

02

Query Jira issues based on custom JQL.

03

Load retrieved Jira issue data for further processing.

04

Integrate Jira data into knowledge bases or other applications.

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/li-reader-readers-jira | bash

Capabilities

What this skill does

Extract

Pulls structured data fields from unstructured text.

Query a database

Writes and executes SQL or NoSQL queries on databases.

RAG index

Chunks, embeds, and indexes documents for semantic retrieval.

Summarize

Condenses long documents or threads into key takeaways.

Overview

JIRA Reader

What it does

The JIRA Reader is a data loader designed to fetch a set of JIRA issues based on a provided query. It acts as a bridge, allowing AI assistants to access and process information directly from your JIRA instance.

How it connects

Use the JIRA Reader when you need to programmatically retrieve specific JIRA issues for analysis, summarization, or integration into other workflows. This is ideal for tasks like tracking project progress, identifying bug reports, or gathering data for reports. Do not use this reader if you need to write data back to JIRA or manage JIRA configurations; it is solely for reading issue data.

Source README

JIRA Reader

pip install llama-index-readers-jira

The Jira loader returns a set of issues based on the query provided to the dataloader.
We can follow three methods to initialize the loader-
1- basic_auth -> this takes a dict with the following keys
basic_auth:{ "email": "email", "api_token": "token", "server_url": "server_url" }
2- Oauth2 -> this takes a dict with the following keys
oauth:{ "cloud_id": "cloud_id", "api_token": "token" }
3- Personal access Token with Server hosted instance
PATauth:{ "server_url": "server_url", "api_token": "token" }

You can follow this link for more information regarding Oauth2 -> https://developer.atlassian.com/cloud/confluence/oauth-2-3lo-apps/

Usage

Here's an example of how to use it

from llama_index.readers.jira import JiraReader

reader = JiraReader(
    email=email, api_token=api_token, server_url="your-jira-server.com"
)
documents = reader.load_data(query="project = <your-project>")

Alternately, you can also use download_loader from llama_index

from llama_index.readers.jira import JiraReader

reader = JiraReader(
    email=email, api_token=api_token, server_url="your-jira-server.com"
)
documents = reader.load_data(query="project = <your-project>")

Discussion

Questions & comments · 0

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