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>
48 lines
1.5 KiB
Python
48 lines
1.5 KiB
Python
from arcade_evals import (
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EvalRubric,
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EvalSuite,
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ExpectedToolCall,
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SimilarityCritic,
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tool_eval,
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)
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from arcade_tdk import ToolCatalog
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import arcade_linkedin
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from arcade_linkedin.tools.share import create_text_post
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rubric = EvalRubric(
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fail_threshold=0.85,
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warn_threshold=0.95,
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)
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catalog = ToolCatalog()
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catalog.add_module(arcade_linkedin)
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@tool_eval()
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def linkedin_eval_suite():
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suite = EvalSuite(
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name="LinkedIn Tools Evaluation",
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system_message="You are an AI assistant with access to LinkedIn tools. Use them to help the user with their tasks.",
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catalog=catalog,
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rubric=rubric,
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)
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suite.add_case(
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name="Run code",
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user_message="post this transcription to linkedin. there may be some things that you need to clean up since it was spoken.: 'It is with great pleasure that I announce that I am now a member of the LinkedIn community! I'd like to thank the LinkedIn team for their support and encouragement in my journey to success. hash tag Y2K'",
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expected_tool_calls=[
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ExpectedToolCall(
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func=create_text_post,
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args={
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"text": "It is with great pleasure that I announce that I am now a member of the LinkedIn community! I'd like to thank the LinkedIn team for their support and encouragement in my journey to success. #Y2K",
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},
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)
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],
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critics=[
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SimilarityCritic(critic_field="text", weight=1.0),
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],
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)
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return suite
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