### 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>
49 lines
1.6 KiB
Python
49 lines
1.6 KiB
Python
import json
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from unittest.mock import patch
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import pytest
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from arcade_tdk import ToolContext, ToolSecretItem
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from arcade_search.tools import search_google
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@pytest.fixture
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def mock_context():
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return ToolContext(secrets=[ToolSecretItem(key="serp_api_key", value="fake_api_key")])
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@pytest.mark.asyncio
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async def test_search_google_success(mock_context):
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with (
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patch("arcade_search.utils.SerpClient") as MockClient,
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):
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mock_client_instance = MockClient.return_value
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mock_client_instance.search.return_value.as_dict.return_value = {
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"organic_results": [
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{"title": "Result 1", "link": "http://example.com/1"},
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{"title": "Result 2", "link": "http://example.com/2"},
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{"title": "Result 3", "link": "http://example.com/3"},
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]
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}
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result = await search_google(mock_context, "test query", 2)
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expected_result = json.dumps([
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{"title": "Result 1", "link": "http://example.com/1"},
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{"title": "Result 2", "link": "http://example.com/2"},
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])
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assert result == expected_result
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@pytest.mark.asyncio
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async def test_search_google_no_results(mock_context):
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with (
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patch("arcade_search.utils.SerpClient") as MockClient,
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):
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mock_client_instance = MockClient.return_value
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mock_client_instance.search.return_value.as_dict.return_value = {"organic_results": []}
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result = await search_google(mock_context, "test query", 2)
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expected_result = json.dumps([])
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assert result == expected_result
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