arcade-mcp/toolkits/search/arcade_search/tools/google_news.py
Sam Partee b6b4cd0a4c
🏗️ Restructure: Multi-Package Architecture + uv Migration (#412)
### Overview
Major restructuring from monolithic `arcade-ai` package to modular
library architecture with standardized uv-based dependency management.

![arcade-ai Monorepo
(2)](https://github.com/user-attachments/assets/25f102b0-bb87-4a04-9701-d227d05664b1)

### 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>
2025-06-11 16:48:17 -07:00

47 lines
1.9 KiB
Python

from typing import Annotated, Any
from arcade_tdk import ToolContext, tool
from arcade_tdk.errors import ToolExecutionError
from arcade_search.constants import DEFAULT_GOOGLE_NEWS_COUNTRY, DEFAULT_GOOGLE_NEWS_LANGUAGE
from arcade_search.exceptions import CountryNotFoundError, LanguageNotFoundError
from arcade_search.google_data import COUNTRY_CODES, LANGUAGE_CODES
from arcade_search.utils import call_serpapi, extract_news_results, prepare_params
@tool(requires_secrets=["SERP_API_KEY"])
async def search_news_stories(
context: ToolContext,
keywords: Annotated[
str,
"Keywords to search for news articles. E.g. 'Apple launches new iPhone'.",
],
country_code: Annotated[
str | None,
"2-character country code to search for news articles. E.g. 'us' (United States). "
f"Defaults to '{DEFAULT_GOOGLE_NEWS_COUNTRY}'.",
] = None,
language_code: Annotated[
str,
"2-character language code to search for news articles. E.g. 'en' (English). "
f"Defaults to '{DEFAULT_GOOGLE_NEWS_LANGUAGE}'.",
] = DEFAULT_GOOGLE_NEWS_LANGUAGE,
limit: Annotated[
int | None,
"Maximum number of news articles to return. Defaults to None "
"(returns all results found by the API).",
] = None,
) -> Annotated[dict[str, list[dict[str, Any]]], "News results."]:
"""Search for news articles related to a given query."""
if not keywords:
raise ToolExecutionError("Keywords are required to search for news articles.")
if country_code and country_code not in COUNTRY_CODES:
raise CountryNotFoundError(country_code)
if language_code not in LANGUAGE_CODES:
raise LanguageNotFoundError(language_code)
params = prepare_params("google_news", q=keywords, gl=country_code, hl=language_code)
results = call_serpapi(context, params)
return {"news_results": extract_news_results(results, limit=limit)}