### Overview Major restructuring from monolithic `arcade-ai` package to modular library architecture with standardized uv-based dependency management.  ### New Package Structure - **`arcade-tdk`** - Lightweight toolkit development kit (core decorators, auth) - **`arcade-core`** - Core execution engine and catalog functionality - **`arcade-serve`** - FastAPI/MCP server components - **`arcade-ai`** - Meta package that includes CLI functionality. Optionally include evals via the `evals` extra. Optionally include all packages via the `all` extra. ### Key Benefits - **Lighter Dependencies**: Toolkits now depend only on `arcade-tdk` (~2 deps) vs full `arcade-ai` (~30+ deps) - **Faster Builds**: uv provides 10-100x faster dependency resolution and installation - **Better Modularity**: Clear separation of concerns, consumers import only what they need - **Standard Tooling**: Eliminates custom poetry scripts, uses standard Python packaging ### Migration Impact - All 20 toolkits converted from poetry → uv with `arcade-tdk` dependencies plus `arcade-ai[evals]` and `arcade-serve` dev dependencies. When developing locally, devs should install toolkits via `make install-local`. - Modern Python 3.10+ type hints throughout - Standardized build system with hatchling backend - Enhanced Makefile with robust toolkit management commands - Removed `arcade dev` CLI command - Reduce the number of files created by `arcade new` and add an option to not generate a tests and evals folder. This foundation enables faster development cycles and cleaner dependency chains for the growing toolkit ecosystem. ### Todo After this PR is merged - [ ] Post-merge workflow(s) (release & publish containers, etc) - [ ] Release order plan. @EricGustin suggests releasing in the following order: 1. `arcade-core` version 0.1.0 2. `arcade-serve` version 0.1.0 and `arcade-tdk` version 0.1.0 3. `arcade-ai` version 2.0.0 4. Patch release for all toolkits (all changes in toolkits are internal refactors) - [ ] [Update docs](https://github.com/ArcadeAI/docs/pull/318) --------- Co-authored-by: Eric Gustin <eric@arcade.dev> Co-authored-by: Eric Gustin <34000337+EricGustin@users.noreply.github.com>
164 lines
6 KiB
Python
164 lines
6 KiB
Python
from typing import Annotated, Any
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from arcade_tdk import ToolContext, tool
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from arcade_tdk.auth import Atlassian
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from arcade_tdk.errors import ToolExecutionError
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from arcade_jira.client import JiraClient
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from arcade_jira.constants import IssueCommentOrderBy
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from arcade_jira.exceptions import MultipleItemsFoundError, NotFoundError
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from arcade_jira.utils import (
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add_pagination_to_response,
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build_adf_doc,
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clean_comment_dict,
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find_multiple_unique_users,
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remove_none_values,
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)
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@tool(requires_auth=Atlassian(scopes=["read:jira-work"]))
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async def get_comment_by_id(
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context: ToolContext,
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issue_id: Annotated[str, "The ID or key of the issue to retrieve the comment from."],
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comment_id: Annotated[str, "The ID of the comment to retrieve"],
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include_adf_content: Annotated[
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bool,
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"Whether to include the ADF (Atlassian Document Format) content of the comment in the "
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"response. Defaults to False (return only the HTML rendered content).",
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] = False,
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) -> Annotated[dict[str, Any], "Information about the comment"]:
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"""Get a comment by its ID."""
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client = JiraClient(context.get_auth_token_or_empty())
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response = await client.get(
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f"issue/{issue_id}/comment/{comment_id}",
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params={"expand": "renderedBody"},
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)
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if not response:
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return {
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"comment": None,
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"message": f"No comment found with ID '{comment_id}' in the issue '{issue_id}'.",
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"query": {"issue_id": issue_id, "comment_id": comment_id},
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}
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return {"comment": clean_comment_dict(response, include_adf_content)}
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@tool(requires_auth=Atlassian(scopes=["read:jira-work"]))
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async def get_issue_comments(
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context: ToolContext,
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issue: Annotated[str, "The ID or key of the issue to retrieve"],
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limit: Annotated[
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int,
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"The maximum number of comments to retrieve. Min 1, max 100, default 100.",
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] = 100,
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offset: Annotated[
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int,
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"The number of comments to skip. Defaults to 0 (start from the first comment).",
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] = 0,
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order_by: Annotated[
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IssueCommentOrderBy | None,
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"The order in which to return the comments. "
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f"Defaults to '{IssueCommentOrderBy.CREATED_DATE_DESCENDING.value}' (most recent first).",
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] = IssueCommentOrderBy.CREATED_DATE_DESCENDING,
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include_adf_content: Annotated[
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bool,
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"Whether to include the ADF (Atlassian Document Format) content of the comment in the "
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"response. Defaults to False (return only the HTML rendered content).",
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] = False,
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) -> Annotated[dict[str, Any], "Information about the issue comments"]:
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"""Get the comments of a Jira issue by its ID."""
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limit = max(min(limit, 100), 1)
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client = JiraClient(context.get_auth_token_or_empty())
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api_response = await client.get(
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f"issue/{issue}/comment",
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params=remove_none_values({
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"expand": "renderedBody",
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"maxResults": limit,
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"startAt": offset,
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"orderBy": order_by.to_api_value() if order_by else None,
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}),
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)
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comments = [
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clean_comment_dict(comment, include_adf_content)
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for comment in api_response["comments"][:limit]
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]
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response = {
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"issue": issue,
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"comments": comments,
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"isLast": api_response.get("isLast"),
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}
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return add_pagination_to_response(response, comments, limit, offset)
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@tool(
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requires_auth=Atlassian(
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scopes=[
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"write:jira-work", # Needed to add the comment
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"read:jira-work", # Needed to get the issue data
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"read:jira-user", # Needed to resolve user ID from name or email (mention_users)
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],
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),
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)
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async def add_comment_to_issue(
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context: ToolContext,
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issue: Annotated[str, "The ID or key of the issue to comment on."],
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body: Annotated[str, "The body of the comment to add to the issue."],
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reply_to_comment: Annotated[
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str | None,
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"Quote a previous comment as a reply to it. Provide the comment's ID. "
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"Must be a comment from the same issue. Defaults to None (no quoted comment).",
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] = None,
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mention_users: Annotated[
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list[str] | None,
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"The users to mention in the comment. Provide the user display name, email address, or ID. "
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"Ex: 'John Doe' or 'john.doe@example.com'. Defaults to None (no user mentions).",
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] = None,
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) -> Annotated[dict[str, Any], "Information about the comment created"]:
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"""Add a comment to a Jira issue."""
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if not body:
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raise ToolExecutionError(message="Comment body cannot be empty.")
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client = JiraClient(context.get_auth_token_or_empty())
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adf_body = build_adf_doc(body)
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if mention_users:
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try:
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users = await find_multiple_unique_users(context, mention_users, exact_match=True)
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except (NotFoundError, MultipleItemsFoundError) as exc:
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return {"error": f"Failed to mention user: {exc.message}"}
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mentions = [
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{
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"type": "mention",
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"attrs": {"accessLevel": "", "id": user["id"], "text": f"@{user['name']}"},
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}
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for user in users
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]
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adf_body["content"][0]["content"] = mentions + adf_body["content"][0]["content"]
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if reply_to_comment:
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quote_comment = await get_comment_by_id(context, issue, reply_to_comment, True)
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if not quote_comment["comment"]:
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raise ToolExecutionError(
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message=f"Cannot quote comment. No comment found with ID '{reply_to_comment}'."
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)
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quote = {
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"type": "blockquote",
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"content": quote_comment["comment"]["adf_body"]["content"],
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}
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adf_body["content"] = [quote] + adf_body["content"]
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response = await client.post(
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f"issue/{issue}/comment",
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json_data={
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"expand": "renderedBody",
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"body": adf_body,
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},
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)
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return {
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"success": True,
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"message": f"Comment successfully created for the issue '{issue}'.",
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"comment": {"id": response["id"], "created_at": response["created"]},
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}
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