b6b4cd0a4c
### 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>
95 lines
3.2 KiB
Python
95 lines
3.2 KiB
Python
import re
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from typing import Annotated
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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_confluence.client import ConfluenceClientV2
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from arcade_confluence.utils import remove_none_values
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@tool(
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requires_auth=Atlassian(
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scopes=["read:space:confluence"],
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)
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)
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async def get_space(
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context: ToolContext,
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space_identifier: Annotated[
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str, "Can be a space's ID or key. Numerical keys are NOT supported"
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],
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) -> Annotated[dict, "The space"]:
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"""Get the details of a space by its ID or key."""
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client = ConfluenceClientV2(context.get_auth_token_or_empty())
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if space_identifier.isdigit():
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return await client.get_space_by_id(space_identifier)
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else:
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return await client.get_space_by_key(space_identifier)
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@tool(
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requires_auth=Atlassian(
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scopes=["read:space:confluence"],
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)
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)
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async def list_spaces(
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context: ToolContext,
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limit: Annotated[
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int, "The maximum number of spaces to return. Defaults to 25. Max is 250"
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] = 25,
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pagination_token: Annotated[
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str | None, "The pagination token to use for the next page of results"
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] = None,
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) -> Annotated[dict, "The spaces"]:
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"""List all spaces sorted by name in ascending order."""
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client = ConfluenceClientV2(context.get_auth_token_or_empty())
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params = {"limit": max(1, min(limit, 250)), "sort": "name", "cursor": pagination_token}
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params = remove_none_values(params)
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spaces = await client.get("spaces", params=params)
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return client.transform_get_spaces_response(spaces)
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@tool(
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requires_auth=Atlassian(
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scopes=[
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"read:page:confluence", # needed for getting the space's root pages
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"read:space:confluence", # needed for when a space key is provided
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"read:hierarchical-content:confluence", # needed for getting the descendents of a page
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],
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)
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)
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async def get_space_hierarchy(
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context: ToolContext,
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space_identifier: Annotated[
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str, "Can be a space's ID or key. Numerical keys are NOT supported"
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],
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) -> Annotated[dict, "The space hierarchy"]:
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"""Retrieve the full hierarchical structure of a Confluence space as a tree structure
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Only structural metadata is returned (not content).
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The response is akin to the sidebar in the Confluence UI.
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Includes all pages, folders, whiteboards, databases,
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smart links, etc. organized by parent-child relationships.
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"""
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client = ConfluenceClientV2(context.get_auth_token_or_empty())
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space = await client.get_space(space_identifier)
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tree = client.create_space_tree(space)
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# Get root pages
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root_pages = await client.get_root_pages_in_space(space["space"]["id"])
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tree["children"] = client.convert_root_pages_to_tree_nodes(root_pages["pages"])
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if not tree["children"]:
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return {}
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# Extract base URL for children URLs. The base URL is the space's URL.
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root_page_url = tree["url"]
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match = re.match(r"(.*?/spaces/[^/]+)", root_page_url)
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children_base_url = match.group(1) if match else ""
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# Get and descendants for each root page
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await client.process_page_descendants(tree["children"], children_base_url)
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return tree
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