Jira 工具包集成

使用 LangChain Python 与 Jira 工具包集成。

本笔记本介绍如何使用 Jira 工具包。

Jira 工具包允许智能体与给定的 Jira 实例交互，执行诸如搜索问题和创建问题等操作。该工具封装了 atlassian-python-api 库，更多信息请见：atlassian-python-api.readthedocs.io/jira.html

安装和设置

要使用此工具，您必须首先将其设置为环境变量： JIRA_INSTANCE_URL, JIRA_CLOUD

您可以选择两种认证方法：

• API token 认证：设置 JIRA_API_TOKEN（如果需要则包括 JIRA_USERNAME）环境变量
• OAuth2.0 认证：将 JIRA_OAUTH2 环境变量设置为一个字典，其字段为 “client_id” 和 “token”，其中 “token” 是一个至少包含 “access_token” 和 “token_type” 的字典

pip install -qU  atlassian-python-api

pip install -qU langchain-community langchain-openai

import os

from langchain.agents import create_agent
from langchain_community.agent_toolkits.jira.toolkit import JiraToolkit
from langchain_community.utilities.jira import JiraAPIWrapper
from langchain_openai import OpenAI

对于 API token 认证

os.environ["JIRA_API_TOKEN"] = "abc"
os.environ["JIRA_USERNAME"] = "123"
os.environ["JIRA_INSTANCE_URL"] = "https://jira.atlassian.com"
os.environ["OPENAI_API_KEY"] = "xyz"
os.environ["JIRA_CLOUD"] = "True"

对于 OAuth2.0 认证

os.environ["JIRA_OAUTH2"] = (
    '{"client_id": "123", "token": {"access_token": "abc", "token_type": "bearer"}}'
)
os.environ["JIRA_INSTANCE_URL"] = "https://jira.atlassian.com"
os.environ["OPENAI_API_KEY"] = "xyz"
os.environ["JIRA_CLOUD"] = "True"

llm = OpenAI(temperature=0)
jira = JiraAPIWrapper()
toolkit = JiraToolkit.from_jira_api_wrapper(jira)

工具使用

让我们看看 Jira 工具包中包含哪些单独的工具：

[(tool.name, tool.description) for tool in toolkit.get_tools()]

[('JQL Query',
  '\n    This tool is a wrapper around atlassian-python-api\'s Jira jql API, useful when you need to search for Jira issues.\n    The input to this tool is a JQL query string, and will be passed into atlassian-python-api\'s Jira `jql` function,\n    For example, to find all the issues in project "Test" assigned to the me, you would pass in the following string:\n    project = Test AND assignee = currentUser()\n    or to find issues with summaries that contain the word "test", you would pass in the following string:\n    summary ~ \'test\'\n    '),
 ('Get Projects',
  "\n    This tool is a wrapper around atlassian-python-api's Jira project API, \n    useful when you need to fetch all the projects the user has access to, find out how many projects there are, or as an intermediary step that involv searching by projects. \n    there is no input to this tool.\n    "),
 ('Create Issue',
  '\n    This tool is a wrapper around atlassian-python-api\'s Jira issue_create API, useful when you need to create a Jira issue. \n    The input to this tool is a dictionary specifying the fields of the Jira issue, and will be passed into atlassian-python-api\'s Jira `issue_create` function.\n    For example, to create a low priority task called "test issue" with description "test description", you would pass in the following dictionary: \n    {{"summary": "test issue", "description": "test description", "issuetype": {{"name": "Task"}}, "priority": {{"name": "Low"}}}}\n    '),
 ('Catch all Jira API call',
  '\n    This tool is a wrapper around atlassian-python-api\'s Jira API.\n    There are other dedicated tools for fetching all projects, and creating and searching for issues, \n    use this tool if you need to perform any other actions allowed by the atlassian-python-api Jira API.\n    The input to this tool is a dictionary specifying a function from atlassian-python-api\'s Jira API, \n    as well as a list of arguments and dictionary of keyword arguments to pass into the function.\n    For example, to get all the users in a group, while increasing the max number of results to 100, you would\n    pass in the following dictionary: {{"function": "get_all_users_from_group", "args": ["group"], "kwargs": {{"limit":100}} }}\n    or to find out how many projects are in the Jira instance, you would pass in the following string:\n    {{"function": "projects"}}\n    For more information on the Jira API, refer to https://atlassian-python-api.readthedocs.io/jira.html\n    '),
 ('Create confluence page',
  'This tool is a wrapper around atlassian-python-api\'s Confluence \natlassian-python-api API, useful when you need to create a Confluence page. The input to this tool is a dictionary \nspecifying the fields of the Confluence page, and will be passed into atlassian-python-api\'s Confluence `create_page` \nfunction. For example, to create a page in the DEMO space titled "This is the title" with body "This is the body. You can use \n<strong>HTML tags</strong>!", you would pass in the following dictionary: {{"space": "DEMO", "title":"This is the \ntitle","body":"This is the body. You can use <strong>HTML tags</strong>!"}} ')]

agent = create_agent(
    model=llm,
    tools=toolkit.get_tools(),
    verbose=True,
)

agent.invoke(
    {
        "input": "make a new issue in project PW to remind me to make more fried rice"
    }
)

> Entering new AgentExecutor chain...
 I need to create an issue in project PW
Action: Create Issue
Action Input: {"summary": "Make more fried rice", "description": "Reminder to make more fried rice", "issuetype": {"name": "Task"}, "priority": {"name": "Low"}, "project": {"key": "PW"}}
Observation: None
Thought: I now know the final answer
Final Answer: A new issue has been created in project PW with the summary "Make more fried rice" and description "Reminder to make more fried rice".

> Finished chain.

'A new issue has been created in project PW with the summary "Make more fried rice" and description "Reminder to make more fried rice".'

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