### 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>
188 lines
6.5 KiB
Python
188 lines
6.5 KiB
Python
from typing import Annotated, Any
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from arcade_tdk import ToolContext, tool
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from firecrawl import FirecrawlApp
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from arcade_web.tools.models import Formats
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# TODO: Support actions. This would enable clicking, scrolling, screenshotting, etc.
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# TODO: Support extract.
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# TODO: Support headers param?
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@tool(requires_secrets=["FIRECRAWL_API_KEY"])
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async def scrape_url(
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context: ToolContext,
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url: Annotated[str, "URL to scrape"],
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formats: Annotated[
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list[Formats] | None, "Formats to retrieve. Defaults to ['markdown']."
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] = None,
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only_main_content: Annotated[
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bool | None,
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"Only return the main content of the page excluding headers, navs, footers, etc.",
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] = True,
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include_tags: Annotated[list[str] | None, "List of tags to include in the output"] = None,
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exclude_tags: Annotated[list[str] | None, "List of tags to exclude from the output"] = None,
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wait_for: Annotated[
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int | None,
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"Specify a delay in milliseconds before fetching the content, allowing the page "
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"sufficient time to load.",
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] = 10,
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timeout: Annotated[int | None, "Timeout in milliseconds for the request"] = 30000,
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) -> Annotated[dict[str, Any], "Scraped data in specified formats"]:
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"""Scrape a URL using Firecrawl and return the data in specified formats."""
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api_key = context.get_secret("FIRECRAWL_API_KEY")
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formats = formats or [Formats.MARKDOWN]
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app = FirecrawlApp(api_key=api_key)
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params = {
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"formats": formats,
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"onlyMainContent": only_main_content,
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"includeTags": include_tags or [],
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"excludeTags": exclude_tags or [],
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"waitFor": wait_for,
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"timeout": timeout,
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}
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response = app.scrape_url(url, params=params)
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return dict(response)
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# TODO: Support scrapeOptions.
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@tool(requires_secrets=["FIRECRAWL_API_KEY"])
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async def crawl_website(
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context: ToolContext,
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url: Annotated[str, "URL to crawl"],
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exclude_paths: Annotated[list[str] | None, "URL patterns to exclude from the crawl"] = None,
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include_paths: Annotated[list[str] | None, "URL patterns to include in the crawl"] = None,
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max_depth: Annotated[int, "Maximum depth to crawl relative to the entered URL"] = 2,
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ignore_sitemap: Annotated[bool, "Ignore the website sitemap when crawling"] = True,
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limit: Annotated[int, "Limit the number of pages to crawl"] = 10,
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allow_backward_links: Annotated[
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bool,
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"Enable navigation to previously linked pages and enable crawling "
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"sublinks that are not children of the 'url' input parameter.",
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] = False,
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allow_external_links: Annotated[bool, "Allow following links to external websites"] = False,
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webhook: Annotated[
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str | None,
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"The URL to send a POST request to when the crawl is started, updated and completed.",
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] = None,
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async_crawl: Annotated[bool, "Run the crawl asynchronously"] = True,
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) -> Annotated[dict[str, Any], "Crawl status and data"]:
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"""
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Crawl a website using Firecrawl. If the crawl is asynchronous, then returns the crawl ID.
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If the crawl is synchronous, then returns the crawl data.
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"""
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api_key = context.get_secret("FIRECRAWL_API_KEY")
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app = FirecrawlApp(api_key=api_key)
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params = {
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"limit": limit,
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"excludePaths": exclude_paths or [],
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"includePaths": include_paths or [],
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"maxDepth": max_depth,
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"ignoreSitemap": ignore_sitemap,
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"allowBackwardLinks": allow_backward_links,
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"allowExternalLinks": allow_external_links,
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}
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if webhook:
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params["webhook"] = webhook
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if async_crawl:
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response = app.async_crawl_url(url, params=params)
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if (
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"url" in response
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): # Url isn't clickable, so removing it since only the ID is needed to check status
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del response["url"]
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else:
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response = app.crawl_url(url, params=params)
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return dict(response)
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@tool(requires_secrets=["FIRECRAWL_API_KEY"])
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async def get_crawl_status(
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context: ToolContext,
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crawl_id: Annotated[str, "The ID of the crawl job"],
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) -> Annotated[dict[str, Any], "Crawl status information"]:
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"""
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Get the status of a Firecrawl 'crawl' that is either in progress or recently completed.
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"""
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api_key = context.get_secret("FIRECRAWL_API_KEY")
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app = FirecrawlApp(api_key=api_key)
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crawl_status = app.check_crawl_status(crawl_id)
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if "data" in crawl_status:
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del crawl_status["data"]
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return dict(crawl_status)
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# TODO: Support responses greater than 10 MB. If the response is greater than 10 MB,
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# then the Firecrawl API response will have a next_url field.
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@tool(requires_secrets=["FIRECRAWL_API_KEY"])
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async def get_crawl_data(
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context: ToolContext,
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crawl_id: Annotated[str, "The ID of the crawl job"],
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) -> Annotated[dict[str, Any], "Crawl data information"]:
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"""
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Get the data of a Firecrawl 'crawl' that is either in progress or recently completed.
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"""
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api_key = context.get_secret("FIRECRAWL_API_KEY")
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app = FirecrawlApp(api_key=api_key)
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crawl_data = app.check_crawl_status(crawl_id)
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return dict(crawl_data)
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@tool(requires_secrets=["FIRECRAWL_API_KEY"])
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async def cancel_crawl(
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context: ToolContext,
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crawl_id: Annotated[str, "The ID of the asynchronous crawl job to cancel"],
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) -> Annotated[dict[str, Any], "Cancellation status information"]:
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"""
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Cancel an asynchronous crawl job that is in progress using the Firecrawl API.
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"""
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api_key = context.get_secret("FIRECRAWL_API_KEY")
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app = FirecrawlApp(api_key=api_key)
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cancellation_status = app.cancel_crawl(crawl_id)
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return dict(cancellation_status)
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@tool(requires_secrets=["FIRECRAWL_API_KEY"])
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async def map_website(
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context: ToolContext,
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url: Annotated[str, "The base URL to start crawling from"],
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search: Annotated[str | None, "Search query to use for mapping"] = None,
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ignore_sitemap: Annotated[bool, "Ignore the website sitemap when crawling"] = True,
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include_subdomains: Annotated[bool, "Include subdomains of the website"] = False,
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limit: Annotated[int, "Maximum number of links to return"] = 5000,
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) -> Annotated[dict[str, Any], "Website map data"]:
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"""
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Map a website from a single URL to a map of the entire website.
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"""
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api_key = context.get_secret("FIRECRAWL_API_KEY")
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app = FirecrawlApp(api_key=api_key)
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params: dict[str, Any] = {
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"ignoreSitemap": ignore_sitemap,
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"includeSubdomains": include_subdomains,
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"limit": limit,
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}
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if search:
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params["search"] = search
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map_result = app.map_url(url, params=params)
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return dict(map_result)
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