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
3.1 KiB
Python
95 lines
3.1 KiB
Python
from typing import Annotated, Any
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from arcade_tdk import ToolContext
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from arcade_tdk.errors import ToolExecutionError
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from arcade_tdk.tool import tool
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from arcade_search.enums import WalmartSortBy
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from arcade_search.utils import (
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call_serpapi,
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extract_walmart_product_details,
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extract_walmart_results,
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get_walmart_last_page_integer,
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prepare_params,
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)
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@tool(requires_secrets=["SERP_API_KEY"])
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async def search_walmart_products(
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context: ToolContext,
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keywords: Annotated[str, "Keywords to search for. E.g. 'apple iphone' or 'samsung galaxy'"],
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sort_by: Annotated[
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WalmartSortBy,
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"Sort the results by the specified criteria. "
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f"Defaults to '{WalmartSortBy.RELEVANCE.value}'.",
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] = WalmartSortBy.RELEVANCE,
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min_price: Annotated[
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float | None,
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"Minimum price to filter the results by. E.g. 100.00",
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] = None,
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max_price: Annotated[
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float | None,
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"Maximum price to filter the results by. E.g. 100.00",
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] = None,
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next_day_delivery: Annotated[
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bool,
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"Filters products that are eligible for next day delivery. "
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"Defaults to False (returns all products, regardless of delivery status).",
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] = False,
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page: Annotated[
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int,
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"Page number to fetch. Defaults to 1 (first page of results). "
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"The maximum page value is 100.",
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] = 1,
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) -> Annotated[dict[str, Any], "List of Walmart products matching the search query."]:
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"""Search Walmart products using SerpAPI."""
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if page > 100:
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raise ToolExecutionError(f"The maximum page value for Walmart search is 100, got {page}.")
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sort_by_value = sort_by.to_api_value()
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params = prepare_params(
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"walmart",
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query=keywords,
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sort=sort_by_value,
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# When the user selects a sorting option, we have to disable the relevance sorting
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# using the soft_sort parameter.
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soft_sort=not sort_by_value,
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min_price=min_price,
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max_price=max_price,
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nd_en=next_day_delivery,
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page=page,
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include_filters=False,
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)
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response = call_serpapi(context, params)
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return {
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"products": extract_walmart_results(response.get("organic_results", [])),
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"current_page": page,
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"last_available_page": get_walmart_last_page_integer(response),
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}
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@tool(requires_secrets=["SERP_API_KEY"])
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async def get_walmart_product_details(
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context: ToolContext,
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item_id: Annotated[
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str,
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"Item ID. E.g. '414600577'. This can be retrieved from the search results of the "
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f"{search_walmart_products.__tool_name__} tool.",
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],
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) -> Annotated[dict[str, Any], "Product details"]:
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"""Get product details from Walmart."""
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params = prepare_params("walmart_product", product_id=item_id)
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response = call_serpapi(context, params)
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product_result = response.get("product_result")
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if not product_result:
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return {
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"product_details": None,
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"message": f"No product details found for item ID '{item_id}'.",
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}
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return {"product_details": extract_walmart_product_details(product_result)}
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