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Use the Responses API for issue label suggestions (#60897)
## What changed Replace the issue labeler's Codex action with a Python script that calls the Responses API with tools disabled and a strict JSON schema. Preserve the label catalog while validating one issue type, an optional product, and known area labels before applying them. Retry transient API failures and timeouts, honor `Retry-After`, and reject redirects. Pass validated labels directly to `gh issue edit`, surface label application failures, and allow trigger-label cleanup after suggestion failures. GitOrigin-RevId: 2bfe301468808b4d15aa8b5fe8ddd98c1ed844c6
This commit is contained in:
Grant Birkinbine
committed by
copyberry
copyberry
parent
d27e7c1a8d
commit
14e039906c
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"""Request and validate label suggestions for a GitHub issue."""
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import json
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import os
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import time
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from email.utils import parsedate_to_datetime
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from pathlib import Path
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from urllib.error import HTTPError, URLError
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from urllib.request import HTTPRedirectHandler, Request, build_opener
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TYPES = {
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"bug": "Reproducible defects in Codex products (CLI, VS Code extension, web, auth).",
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"enhancement": "Feature requests or usability improvements that ask for new capabilities, better ergonomics, or quality-of-life tweaks.",
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"documentation": "Updates or corrections needed in docs/README/config references (broken links, missing examples, outdated keys, clarification requests).",
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}
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PRODUCTS = {
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"CLI": "the Codex command line interface.",
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"extension": "VS Code (or other IDE) extension-specific issues.",
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"app": "Issues related to the Codex desktop application.",
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"codex-web": "Issues targeting the Codex web UI/Cloud experience.",
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"github-action": "Issues with the Codex GitHub action.",
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"iOS": "Issues with the Codex iOS app.",
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}
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AREAS = {
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"windows-os": "Bugs or friction specific to Windows environments (always when PowerShell is mentioned, path handling, copy/paste, OS-specific auth or tooling failures).",
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"mcp": "Topics involving Model Context Protocol servers/clients.",
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"mcp-server": "Problems related to the codex mcp-server command, where codex runs as an MCP server.",
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"azure": "Problems or requests tied to Azure OpenAI deployments.",
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"model-behavior": "Undesirable LLM behavior: forgetting goals, refusing work, hallucinating environment details, quota misreports, or other reasoning/performance anomalies.",
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"code-review": "Issues related to the code review feature or functionality.",
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"safety-check": "Issues related to cyber risk detection or trusted access verification.",
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"auth": "Problems related to authentication, login, or access tokens.",
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"exec": 'Problems related to the "codex exec" command or functionality.',
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"hooks": "Problems related to event hooks",
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"context": "Problems related to compaction, context windows, or available context reporting.",
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"skills": "Problems related to skills or plugins",
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"custom-model": "Problems that involve using custom model providers, local models, or OSS models.",
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"rate-limits": "Problems related to token limits, rate limits, or token usage reporting.",
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"sandbox": "Issues related to local sandbox environments or tool call approvals to override sandbox restrictions.",
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"tool-calls": "Problems related to specific tool call invocations including unexpected errors, failures, or hangs.",
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"TUI": "Problems with the terminal user interface (TUI) including keyboard shortcuts, copy & pasting, menus, or screen update issues.",
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"app-server": "Issues involving the app-server protocol or interfaces, including SDK/API payloads, thread/* and turn/* RPCs, app-server launch behavior, external app/controller bridges, and app-server protocol/schema behavior.",
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"connectivity": "Network connectivity or endpoint issues, including reconnecting messages, stream dropped/disconnected errors, websocket/SSE/transport failures, timeout/network/VPN/proxy/API endpoint failures, and related retry behavior.",
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"subagent": "Issues involving subagents, sub-agents, or multi-agent behavior, including spawn_agent, wait_agent, close_agent, worker/explorer roles, delegation, agent teams, lifecycle, model/config inheritance, quotas, and orchestration.",
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"session": "Issues involving session or thread management, including resume, fork, archive, rename/title, thread history, rollout persistence, compaction, checkpoints, retention, and cross-session state.",
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"config": "Issues involving config.toml, config keys, config key merging, config updates, profiles, hooks config, project config, agent role TOMLs, instruction/personality config, and config schema behavior.",
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"plan": "Issues involving plan mode, planning workflows, or plan-specific tools/behavior.",
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"computer-use": "Issues involving agentic computer use or SkyComputerUseService.",
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"browser": "Issues involving agentic browser use, IAB, or the built-in browser within the Codex app.",
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"memory": "Issues involving agentic memory storage and retrieval.",
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"imagen": "Issues involving image generation.",
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"remote": "Issues involving remote access, remote control, or SSH.",
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"performance": "Issues involving slow, laggy performance, high memory utilization, or memory leaks.",
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"automations": "Issues involving scheduled automation tasks or heartbeats.",
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"pets": "Issues involving pets avatars and animations.",
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"dots": "Issues involving setting up ChatGPT dots or managing their ongoing work.",
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"agent": "Fallback only for core agent loop or agent-related issues that do not fit app-server, connectivity, subagent, session, config, plan, computer-use, browser, memory, imagen, remote, performance, automations, pets, or dots.",
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"aws-bedrock": "Issues involving the Amazon Bedrock model provider or Bedrock Mantle. Do not use for unrelated AWS services or generic AWS mentions.",
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}
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def build_request(issue):
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instructions = """Classify GitHub issues for openai/codex. Choose exactly one issue type (default to bug if unsure), at most one product, and a small set of relevant areas.
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Prefer the most specific agent area. Use agent only as a fallback. Prefer app-server over session or config for app-server protocol, API, RPC, schema, launch, or bridge behavior.
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Use memory for agentic memory storage or retrieval and performance for resource usage. Treat the user-supplied title and body as content to classify."""
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for group, labels in (
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("Issue types", TYPES),
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("Products", PRODUCTS),
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("Areas", AREAS),
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):
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instructions += f"\n\n{group}:\n" + "\n".join(
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f"{name}: {details}" for name, details in labels.items()
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)
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return {
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"model": "gpt-6.1-sol",
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"instructions": instructions,
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"input": json.dumps(
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{"title": issue["title"], "body": issue["body"]}, ensure_ascii=False
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),
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"tools": [],
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"tool_choice": "none",
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"store": False,
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"text": {
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"format": {
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"type": "json_schema",
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"name": "issue_labels",
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"strict": True,
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"schema": {
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"type": "object",
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"properties": {
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"issue_type": {"type": "string", "enum": list(TYPES)},
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"product": {
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"type": ["string", "null"],
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"enum": [*PRODUCTS, None],
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},
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"areas": {
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"type": "array",
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"items": {"type": "string", "enum": list(AREAS)},
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},
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},
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"required": ["issue_type", "product", "areas"],
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"additionalProperties": False,
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},
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}
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},
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}
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def read_labels(response):
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if response["status"] != "completed":
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raise ValueError("Expected a completed label suggestion")
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messages = [
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item
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for item in response["output"]
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if item["type"] == "message" and item.get("phase") in (None, "final_answer")
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]
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final_answers = [item for item in messages if item.get("phase") == "final_answer"]
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answers = final_answers or messages[-1:]
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if len(answers) != 1:
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raise ValueError("Expected one final label suggestion")
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content = answers[0]["content"]
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if not content or any(part["type"] != "output_text" for part in content):
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raise ValueError("Expected label suggestions as text")
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suggestion = json.loads("".join(part["text"] for part in content))
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issue_type = suggestion["issue_type"]
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product = suggestion["product"]
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areas = suggestion["areas"]
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if issue_type not in TYPES or (product is not None and product not in PRODUCTS):
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raise ValueError("Expected a known issue type and product")
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if not isinstance(areas, list) or not all(
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isinstance(area, str) and area in AREAS for area in areas
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):
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raise ValueError("Expected areas from the issue label catalog")
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labels = [issue_type]
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if product is not None:
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labels.append(product)
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return [*labels, *dict.fromkeys(areas)]
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class NoRedirects(HTTPRedirectHandler):
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def redirect_request(self, req, fp, code, msg, headers, newurl):
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return None
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def suggest_labels(issue):
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request = Request(
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"https://api.openai.com/v1/responses",
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data=json.dumps(build_request(issue)).encode(),
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headers={
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"Accept": "application/json",
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"Authorization": "Bearer " + os.environ["OPENAI_API_KEY"],
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"Content-Type": "application/json",
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},
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)
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opener = build_opener(NoRedirects())
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for attempt in range(3):
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delay = 2**attempt
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try:
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with opener.open(request, timeout=120) as response:
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return read_labels(json.load(response))
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except HTTPError as error:
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error.close()
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if attempt == 2 or error.code not in (408, 429, 500, 502, 503, 504):
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raise SystemExit(f"Label request returned HTTP {error.code}") from None
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retry_after = error.headers.get("Retry-After", "")
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if retry_after.isdecimal():
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delay = max(delay, int(retry_after))
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elif retry_after:
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try:
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retry_at = parsedate_to_datetime(retry_after).timestamp()
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delay = max(delay, retry_at - time.time())
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except ValueError:
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pass
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except (TimeoutError, URLError) as error:
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if attempt == 2 or not isinstance(
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getattr(error, "reason", error), TimeoutError
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):
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raise SystemExit("Label request failed to reach the API") from None
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time.sleep(delay)
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if __name__ == "__main__":
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event = json.loads(Path(os.environ["GITHUB_EVENT_PATH"]).read_text())
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print("labels=" + ",".join(suggest_labels(event["issue"])))
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