This PyTorch HUD API implementation provides a Python library and MCP server for accessing PyTorch's CI/CD analytics data, enabling developers to investigate build failures and trunk health issues. Built with FastMCP, it offers tools for retrieving workflow and job information, analyzing large log files efficiently, executing ClickHouse queries against CI metrics, and monitoring resource utilization. The server exposes both synchronous and asynchronous functions through a standardized interface, making it valuable for PyTorch contributors debugging CI failures, investigating test flakiness, or analyzing performance trends across the CI infrastructure.
暂无评论. 成为第一个评论的人！
登录以参与讨论
Highlight AIRetrieve basic commit information without jobs.
Get aggregated job status counts.
Retrieve jobs filtered by status, workflow, or name.
Obtain detailed failure information for failed jobs.
Fetch the status for recent commits along with job statistics.
Download logs to local storage.
Identify errors, warnings, and other patterns in logs.
Parse and retrieve results from test executions.
Extract specific sections from logs.
Perform searches across multiple log files.
