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>
52 lines
1.6 KiB
Python
52 lines
1.6 KiB
Python
from typing import Annotated
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from arcade_tdk import ToolContext, tool
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from e2b_code_interpreter import Sandbox
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from arcade_code_sandbox.tools.models import E2BSupportedLanguage
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# See https://e2b.dev/docs to learn more about E2B
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@tool(requires_secrets=["E2B_API_KEY"])
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def run_code(
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context: ToolContext,
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code: Annotated[str, "The code to run"],
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language: Annotated[
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E2BSupportedLanguage, "The language of the code"
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] = E2BSupportedLanguage.PYTHON,
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) -> Annotated[str, "The sandbox execution as a JSON string"]:
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"""
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Run code in a sandbox and return the output.
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"""
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api_key = context.get_secret("E2B_API_KEY")
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with Sandbox(api_key=api_key) as sbx:
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execution = sbx.run_code(code=code, language=language)
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return str(execution.to_json())
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# Note: Not recommended to use tool_choice='generate' with this tool
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# since it contains base64 encoded image.
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@tool(requires_secrets=["E2B_API_KEY"])
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def create_static_matplotlib_chart(
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context: ToolContext,
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code: Annotated[str, "The Python code to run"],
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) -> Annotated[dict, "A dictionary with the following keys: base64_image, logs, error"]:
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"""
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Run the provided Python code to generate a static matplotlib chart.
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The resulting chart is returned as a base64 encoded image.
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"""
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api_key = context.get_secret("E2B_API_KEY")
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with Sandbox(api_key=api_key) as sbx:
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execution = sbx.run_code(code=code)
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result = {
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"base64_image": execution.results[0].png if execution.results else None,
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"logs": execution.logs.to_json(),
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"error": execution.error.to_json() if execution.error else None,
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}
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return result
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