### 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>
138 lines
4.6 KiB
Python
138 lines
4.6 KiB
Python
from typing import Annotated, Optional
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from arcade_tdk import ToolContext, tool
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from arcade_tdk.auth import Dropbox
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from arcade_tdk.errors import ToolExecutionError
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from arcade_dropbox.constants import Endpoint, ItemCategory
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from arcade_dropbox.exceptions import DropboxApiError
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from arcade_dropbox.utils import (
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build_dropbox_json,
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clean_dropbox_entries,
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parse_dropbox_path,
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send_dropbox_request,
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)
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@tool(
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requires_auth=Dropbox(
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scopes=["files.metadata.read"],
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)
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)
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async def list_items_in_folder(
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context: ToolContext,
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folder_path: Annotated[
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str,
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"The path to the folder to list the contents of. E.g. '/AcmeInc/Reports'. "
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"Defaults to an empty string (list items in the Dropbox root folder).",
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] = "",
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limit: Annotated[
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int,
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"The maximum number of items to return. Defaults to 100. Maximum allowed is 2000.",
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] = 100,
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cursor: Annotated[
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Optional[str],
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"The cursor token for the next page of results. "
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"Defaults to None (returns the first page of results).",
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] = None,
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) -> Annotated[
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dict, "Dictionary containing the list of files and folders in the specified folder path"
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]:
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"""Provides a dictionary containing the list of items in the specified folder path.
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Note 1: when paginating, it is not necessary to provide any other argument besides the cursor.
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Note 2: when paginating, any given item (file or folder) may be returned in multiple pages.
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"""
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limit = min(limit, 2000)
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try:
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result = await send_dropbox_request(
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context.get_auth_token_or_empty(),
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endpoint=Endpoint.LIST_FOLDER,
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path=parse_dropbox_path(folder_path),
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limit=limit,
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cursor=cursor,
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)
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except DropboxApiError as api_error:
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return {"error": api_error.message}
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return {
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"items": clean_dropbox_entries(result["entries"]),
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"cursor": result.get("cursor"),
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"has_more": result.get("has_more", False),
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}
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@tool(
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requires_auth=Dropbox(
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scopes=["files.metadata.read"],
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)
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)
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async def search_files_and_folders(
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context: ToolContext,
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keywords: Annotated[
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str,
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"The keywords to search for. E.g. 'quarterly report'. "
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"Maximum length allowed by the Dropbox API is 1000 characters. ",
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],
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search_in_folder_path: Annotated[
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Optional[str],
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"Restricts the search to the specified folder path. E.g. '/AcmeInc/Reports'. "
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"Defaults to None (search in the entire Dropbox).",
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] = None,
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filter_by_category: Annotated[
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Optional[list[ItemCategory]],
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"Restricts the search to the specified category(ies) of items. "
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"Provide None, one or multiple, if needed. Defaults to None (returns all categories).",
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] = None,
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limit: Annotated[
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int,
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"The maximum number of items to return. Defaults to 100. Maximum allowed is 1000.",
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] = 100,
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cursor: Annotated[
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Optional[str],
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"The cursor token for the next page of results. Defaults to None (first page of results).",
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] = None,
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) -> Annotated[dict, "List of items in the specified folder path matching the search criteria"]:
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"""Returns a list of items in the specified folder path matching the search criteria.
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Note 1: the Dropbox API will return up to 10,000 (ten thousand) items cumulatively across
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multiple pagination requests using the cursor token.
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Note 2: when paginating, it is not necessary to provide any other argument besides the cursor.
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Note 3: when paginating, any given item (file or folder) may be returned in multiple pages.
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"""
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if len(keywords) > 1000:
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raise ToolExecutionError(
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"The keywords argument must be a string with up to 1000 characters."
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)
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limit = min(limit, 1000)
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filter_by_category = filter_by_category or []
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options = build_dropbox_json(
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file_status="active",
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filename_only=False,
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path=parse_dropbox_path(search_in_folder_path),
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max_results=limit,
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file_categories=[category.value for category in filter_by_category],
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)
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try:
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result = await send_dropbox_request(
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context.get_auth_token_or_empty(),
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endpoint=Endpoint.SEARCH_FILES,
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query=keywords,
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options=options,
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cursor=cursor,
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)
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except DropboxApiError as api_error:
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return {"error": api_error.message}
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return {
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"items": clean_dropbox_entries([
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match["metadata"]["metadata"] for match in result["matches"]
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]),
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"cursor": result.get("cursor"),
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"has_more": result.get("has_more", False),
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}
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