mirror of
https://github.com/Sea-Haven-Industries/open-swe.git
synced 2026-09-30 20:53:15 +00:00
Adam Moussa
b3fc62da80
Plan step C4 (docs/upstream-sync/domain-reorg/reorg-build-plan.md, approved
decisions 1-2): split the 2,590-line agent/webapp.py monolith into
agent/webhooks/common.py (shared verify/dispatch helpers), agent/api/app.py
(composition), agent/api/health.py (/health + /webhooks/run-complete), and
per-source {github,linear,slack,jira,confluence}_routes.py. Atlassian
Connect lifecycle + descriptor routes (/connect/*) fold into
confluence_routes.py; webapp.py becomes the upstream-shaped compatibility
shim (from .api.app import app). langgraph.json http.app stays
agent.webapp:app via the shim.
Fork content, upstream layout: linear/slack route files verified
content-identical to upstream 8356eb34 and taken verbatim; github_routes is
upstream + the fork's CI auto-fix trigger wiring; jira/confluence routes are
fork-only, transformed to the same common.X / service.X module-attribute
style. All signature verification (GitHub HMAC, Slack, Linear
timestamp-freshness, verify_jira_secret + opt-in HMAC/timestamp/IP
allowlist, Connect JWT/qsh), token-attribution gating, TID-COLLIDE-01 repo
binding, _is_repo_auto_review_enabled gates, and public-repo org gate move
unchanged.
Handlers rewired from webapp.X to common.X; test monkeypatch sites across
26 files + conftest.py + e2e/harness.py retargeted to
webhook_common/handler/route modules per upstream's pattern. Residual
agent.webapp importers: only the shim, langgraph.json http.app, Makefile
uvicorn target, and docs (doc-path updates land in C7).
Gates: ruff check + format, pytest --co, full unit (1637 passed), full
Playwright E2E vs real langgraph dev (9/9), residual-importer sweep.
262 lines
11 KiB
Python
262 lines
11 KiB
Python
"""Linear webhook handler — moved out of common.py (behavior-identical).
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Helpers and constants stay in common.py; they are accessed through the module
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object (``common.X``) so tests that monkeypatch them keep working.
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"""
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from typing import Any
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from urllib.parse import urlparse
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import httpx
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from langchain_core.messages.content import create_text_block
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from . import common
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async def process_linear_issue( # noqa: PLR0912, PLR0915
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issue_data: dict[str, Any], repo_config: dict[str, str]
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) -> None:
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"""Process a Linear issue by creating a new LangGraph thread and run.
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Args:
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issue_data: The Linear issue data from webhook (basic info only).
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repo_config: The repo configuration with owner and name.
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"""
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issue_id = issue_data.get("id", "")
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common.logger.info(
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"Processing Linear issue %s for repo %s/%s",
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issue_id,
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repo_config.get("owner"),
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repo_config.get("name"),
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)
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triggering_comment_id = issue_data.get("triggering_comment_id", "")
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if triggering_comment_id:
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await common.react_to_linear_comment(triggering_comment_id, "👀")
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thread_id = common.generate_thread_id_from_issue(issue_id)
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full_issue = await common.fetch_linear_issue_details(issue_id)
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if not full_issue:
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full_issue = issue_data
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user_name = None
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# Actor email for token attribution: restricted to the comment author only.
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# The creator/assignee fallback chain is intentionally excluded here so a PR
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# is never opened as a non-actor.
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actor_email = None
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comment_author = issue_data.get("comment_author", {})
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if comment_author:
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actor_email = comment_author.get("email")
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user_name = comment_author.get("name")
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# User email with full fallback chain for display, model selection, and
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# @mention instructions.
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user_email = actor_email
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if not user_email:
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creator = full_issue.get("creator", {})
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if creator:
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user_email = creator.get("email")
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user_name = user_name or creator.get("name")
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if not user_email:
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assignee = full_issue.get("assignee", {})
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if assignee:
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user_email = assignee.get("email")
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user_name = user_name or assignee.get("name")
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common.logger.info("User email for issue %s: %s", issue_id, user_email)
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title = full_issue.get("title", "No title")
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description = full_issue.get("description") or "No description"
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image_urls: list[str] = []
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description_image_urls = common.extract_image_urls(description)
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if description_image_urls:
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image_urls.extend(description_image_urls)
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common.logger.debug(
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"Found %d image URL(s) in issue description",
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len(description_image_urls),
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)
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comments = full_issue.get("comments", {}).get("nodes", [])
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comments_text = ""
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triggering_comment = issue_data.get("triggering_comment", "")
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triggering_comment_id = issue_data.get("triggering_comment_id", "")
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bot_message_prefixes = (
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"🔐 **GitHub Authentication Required**",
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"✅ **Pull Request Created**",
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"✅ **Pull Request Updated**",
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"**Pull Request Created**",
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"**Pull Request Updated**",
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"🤖 **Agent Response**",
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"❌ **Agent Error**",
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)
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comment_ids: set[str] = set()
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comment_id_to_index: dict[str, int] = {}
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if comments:
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for i, comment in enumerate(comments):
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comment_id = comment.get("id", "")
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if comment_id:
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comment_ids.add(comment_id)
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comment_id_to_index[comment_id] = i
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relevant_comments = []
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trigger_index = None
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if triggering_comment_id:
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trigger_index = comment_id_to_index.get(triggering_comment_id)
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if trigger_index is not None:
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relevant_comments = comments[trigger_index:]
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common.logger.debug(
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"Using triggering comment index %d to build relevant comments",
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trigger_index,
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)
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else:
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relevant_comments = common.get_recent_comments(comments, bot_message_prefixes)
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if relevant_comments:
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comments_text = "\n\n## Comments:\n"
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for comment in relevant_comments:
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user = comment.get("user") or {}
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author = user.get("name", "User")
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body = comment.get("body", "")
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body_image_urls = common.extract_image_urls(body)
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if body_image_urls:
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image_urls.extend(body_image_urls)
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common.logger.debug(
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"Found %d image URL(s) in comment by %s",
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len(body_image_urls),
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author,
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)
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if any(body.startswith(prefix) for prefix in bot_message_prefixes):
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continue
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comments_text += f"\n**{author}:** {body}\n"
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if triggering_comment and triggering_comment_id not in comment_ids:
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if not comments_text:
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comments_text = "\n\n## Comments:\n"
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trigger_author = comment_author.get("name", "Unknown")
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trigger_body = triggering_comment
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trigger_image_urls = common.extract_image_urls(trigger_body)
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if trigger_image_urls:
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image_urls.extend(trigger_image_urls)
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common.logger.debug(
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"Found %d image URL(s) in triggering comment by %s",
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len(trigger_image_urls),
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trigger_author,
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)
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comments_text += f"\n**{trigger_author}:** {trigger_body}\n"
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common.logger.debug(
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"Appended triggering comment %s not present in issue comments list",
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triggering_comment_id or "<missing-id>",
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)
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identifier = full_issue.get("identifier", "") or issue_data.get("identifier", "")
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ticket_url = full_issue.get("url", "") or issue_data.get("url", "")
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ticket_url_line = f"## Linear Ticket URL: {ticket_url}\n\n" if ticket_url else ""
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triggered_by_line = f"## Triggered by: {user_name}\n\n" if user_name else ""
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tag_instruction = (
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f"When calling linear_comment, tag @{user_name} if you are asking them a question, need their input, or are notifying them of something important (e.g. a completed PR). For simple answers, tagging is not required."
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if user_name
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else ""
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)
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prompt = (
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f"Please work on the following issue:\n\n"
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f"## Repository: {repo_config.get('owner')}/{repo_config.get('name')}\n\n"
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f"## Title: {title}\n\n"
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f"{triggered_by_line}"
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f"## Linear Ticket: {identifier} - Ticket ID: {issue_id}\n\n"
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f"{ticket_url_line}"
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f"## Description:\n{description}\n"
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f"{comments_text}\n\n"
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"Please analyze this issue and implement the necessary changes. "
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"If you open a PR for this issue, make sure the PR description links back to "
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"this Linear ticket and follows this repository's PR conventions for the title, body, "
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"release note, and/or changelog. Inspect AGENTS.md, PR templates, "
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".changelog/README.md, and nearby docs before choosing the PR title/body format. "
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f"When you're done, commit and push your changes. {tag_instruction}"
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)
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content_blocks: list[dict[str, Any]] = [create_text_block(prompt)]
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# Resolve the GitHub login from the actor's Linear email via the same
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# user-mapping store Slack uses, so PRs open *as the triggering user* and the
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# thread is tagged for the dashboard. Restricted to the comment author so
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# token attribution never falls back to creator/assignee.
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mapped_login = await common.resolve_login_from_email_async(actor_email) if actor_email else None
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image_model_override: tuple[str, str] | None = None
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if image_urls:
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image_urls = common.dedupe_urls(image_urls)
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resolved_model_id = await common.resolve_agent_model_id(mapped_login)
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if not common.model_supports_images(resolved_model_id):
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fallback_model_id, fallback_effort = common.default_vision_model_pair()
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common.logger.info(
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"Using vision fallback model %s for %d Linear image(s); configured model %s "
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"does not support images",
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fallback_model_id,
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len(image_urls),
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resolved_model_id,
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)
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resolved_model_id = fallback_model_id
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image_model_override = (fallback_model_id, fallback_effort)
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common.logger.info("Preparing %d image(s) for multimodal content", len(image_urls))
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common.logger.debug("Image hosts: %s", [urlparse(u).hostname for u in image_urls])
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async with httpx.AsyncClient(timeout=common.DEFAULT_HTTP_TIMEOUT) as client:
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for image_url in image_urls:
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image_block = await common.fetch_image_block(image_url, client)
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if image_block:
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content_blocks.append(image_block)
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common.logger.info("Built %d content block(s) for prompt", len(content_blocks))
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linear_project_id = ""
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linear_issue_number = ""
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if identifier and "-" in identifier:
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parts = identifier.split("-", 1)
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linear_project_id = parts[0]
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linear_issue_number = parts[1]
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configurable: dict[str, Any] = {
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"repo": repo_config,
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"linear_issue": {
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"id": issue_id,
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"title": title,
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"url": full_issue.get("url", "") or issue_data.get("url", ""),
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"identifier": identifier,
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"linear_project_id": linear_project_id,
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"linear_issue_number": linear_issue_number,
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"triggering_user_name": user_name or "",
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},
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"user_email": user_email,
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"source": "linear",
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}
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if mapped_login:
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configurable["github_login"] = mapped_login
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if image_model_override:
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configurable["agent_model_id"] = image_model_override[0]
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configurable["agent_effort"] = image_model_override[1]
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await common.upsert_agent_thread_owner_metadata(
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thread_id,
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source="linear",
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repo_config=repo_config,
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github_login=mapped_login or "",
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user_email=user_email or "",
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title=title or identifier or "Linear issue",
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source_context={"linear_issue": configurable["linear_issue"]},
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)
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run = await common.dispatch_agent_run(
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thread_id,
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content_blocks,
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configurable,
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source="linear",
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metadata=common._AGENT_VERSION_METADATA,
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)
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common.logger.info(
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"LangGraph run dispatched for thread %s (run=%s)",
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thread_id,
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run.get("run_id") if isinstance(run, dict) else None,
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)
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await common.post_linear_trace_comment(issue_id, thread_id, triggering_comment_id)
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