GitHubIssueCommenter
This component posts comments to GitHub issues using the GitHub API.
| Most common position in a pipeline | After a Chat Generator that provides the comment text to post or right at the beginning of a pipeline |
| Mandatory init variables | "github_token": GitHub personal access token. Can be set with GITHUB_TOKEN env var. |
| Mandatory run variables | "url": A GitHub issue URL "comment": Comment text to post |
| Output variables | "success": Boolean indicating whether the comment was posted successfully |
| API reference | GitHub |
| GitHub link | https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/github |
Overview
GitHubIssueCommenter takes a GitHub issue URL and comment text, then posts the comment to the specified issue.
The component requires authentication with a GitHub personal access token since posting comments is an authenticated operation.
Authorization
This component requires GitHub authentication with a personal access token. You can set the token using the GITHUB_TOKEN environment variable, or pass it directly during initialization via the github_token parameter.
To create a personal access token, visit GitHub's token settings page. Make sure to grant the appropriate permissions for repository access and issue management.
Installation
Install the GitHub integration with pip:
pip install github-haystack
Usage
Repository Placeholder
To run the following code snippets, you need to replace the
owner/repowith your own GitHub repository name.
On its own
Basic usage with environment variable authentication:
from haystack_integrations.components.connectors.github import GitHubIssueCommenter
commenter = GitHubIssueCommenter()
result = commenter.run(
url="https://github.com/owner/repo/issues/123",
comment="Thanks for reporting this issue! We'll look into it."
)
print(result)
{'success': True}
In a pipeline
The following pipeline analyzes a GitHub issue and automatically posts a response:
from haystack import Pipeline
from haystack.components.builders.chat_prompt_builder import ChatPromptBuilder
from haystack.components.converters import OutputAdapter
from haystack.components.generators.chat import OpenAIChatGenerator
from haystack.dataclasses import ChatMessage
from haystack_integrations.components.connectors.github import GitHubIssueViewer, GitHubIssueCommenter
issue_viewer = GitHubIssueViewer()
issue_commenter = GitHubIssueCommenter()
prompt_template = [
ChatMessage.from_system("You are a helpful assistant that analyzes GitHub issues and creates appropriate responses."),
ChatMessage.from_user(
"Based on the following GitHub issue:\n"
"{% for document in documents %}"
"{% if document.meta.type == 'issue' %}"
"**Issue Title:** {{ document.meta.title }}\n"
"**Issue Description:** {{ document.content }}\n"
"{% endif %}"
"{% endfor %}\n"
"Generate a helpful response comment for this issue. Keep it professional and concise."
)
]
prompt_builder = ChatPromptBuilder(template=prompt_template, required_variables="*")
llm = OpenAIChatGenerator(model="gpt-4o-mini")
adapter = OutputAdapter(template="{{ replies[-1].text }}", output_type=str)
pipeline = Pipeline()
pipeline.add_component("issue_viewer", issue_viewer)
pipeline.add_component("prompt_builder", prompt_builder)
pipeline.add_component("llm", llm)
pipeline.add_component("adapter", adapter)
pipeline.add_component("issue_commenter", issue_commenter)
pipeline.connect("issue_viewer.documents", "prompt_builder.documents")
pipeline.connect("prompt_builder.prompt", "llm.messages")
pipeline.connect("llm.replies", "adapter.replies")
pipeline.connect("adapter", "issue_commenter.comment")
issue_url = "https://github.com/owner/repo/issues/123"
result = pipeline.run(data={
"issue_viewer": {"url": issue_url},
"issue_commenter": {"url": issue_url}
})
print(f"Comment posted successfully: {result['issue_commenter']['success']}")
Comment posted successfully: True
Updated 2 days ago