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* feat: adopt directory-based docs versioning with Edge channel Switch docs.crewai.com from navigation-only versioning (every version selector entry rendered the same docs/<lang>/* source files) to Mintlify's directory-based versioning so each version selector entry renders its own snapshot. Add an "Edge" channel under docs/edge/<lang>/* that always reflects main HEAD for unreleased work, eliminating pre-release leakage onto frozen release labels. External links to canonical /<lang>/* URLs are preserved via wildcard redirects that always land on the current default version. Layout: - docs/edge/<lang>/* rolling source (you edit here) - docs/edge/enterprise-api.*.yaml - docs/v<X.Y.Z>/<lang>/* frozen, immutable snapshots - docs/v<X.Y.Z>/enterprise-api.*.yaml - docs/images/ shared, append-only - docs/docs.json nav + redirects URLs follow the Mintlify-idiomatic shape: /edge/<lang>/<page> for Edge, /v<X.Y.Z>/<lang>/<page> for every frozen snapshot. The wildcard redirects /<lang>/:slug* -> /<default>/<lang>/:slug* keep stale links working, and every freeze rewrites them (plus all per-section/per-page redirects) so destinations always resolve to the current default without depending on a second redirect hop. Release flow integration (devtools release): - New module crewai_devtools.docs_versioning.freeze() materialises docs/v<X.Y.Z>/ from docs/edge/, rewrites openapi: refs inside the snapshot, inserts the version into every language block in docs.json, and refreshes all redirect destinations. - _update_docs_and_create_pr() in cli.py now calls that freeze during Phase 2 of devtools release. Edge changelogs are updated first (so the snapshot freeze picks them up), then the snapshot is staged alongside docs.json, branched as docs/freeze-v<X.Y.Z>, and the PR is titled [docs-freeze] docs: snapshot and changelog for v<X.Y.Z> — the title prefix the new CI guard reads. - The PR still gates tag, GitHub release, PyPI publish, and the enterprise release as before; no new PRs are added. - Pre-releases (1.X.YaN, 1.X.YbN, ...) skip the snapshot — they ride Edge — and the docs PR title omits the [docs-freeze] prefix. - docs_check (AI-generated docs scaffolding) writes to docs/edge/<lang>/* so newly-generated unreleased docs land in Edge and never accidentally touch a frozen snapshot. Migration scripts (one-shot): - scripts/docs/freeze_historical_versions.py reconstructs all 16 historical snapshots (v1.10.0 .. v1.14.7) from git tags via git archive | tar, rewriting openapi: MDX refs so each snapshot reads its own enterprise-api YAML rather than the live one. - scripts/docs/prefix_version_paths.py one-shot-migrates docs.json: rewrites every page path in 16 versioned blocks to point under docs/v<X.Y.Z>/, inserts a new Edge entry per language, tags v1.14.7 as Latest (default), prunes pages whose target file doesn't exist in the snapshot (e.g. docs/ar/ didn't exist before v1.12.0), and writes the wildcard + per-section redirects. - scripts/docs/freeze_current_edge.py is now a thin CLI wrapper around docs_versioning.freeze for manual one-off freezes (e.g. retroactively snapshotting a forgotten release). CI guards (.github/workflows/docs-snapshots.yml): - Frozen snapshots under docs/v[0-9]*/ are immutable; only PRs whose title contains [docs-freeze] (i.e. release-cut PRs generated by devtools release or the manual wrapper) may modify them. - Images under docs/images/ are append-only since snapshots share a single image directory. Deleting or renaming an image breaks every historical snapshot that still references it. Restored docs/images/crewai-otel-export.png from PR #3673; it was deleted in PR #4908 but v1.10.0 / v1.10.1 snapshots still reference it. Restoring instead of editing the snapshots preserves historical rendering fidelity and validates the new append-only rule retroactively. Tests: - lib/devtools/tests/test_docs_versioning.py covers the freeze: file copy, openapi rewrite, version insertion, default demotion, redirect upserts, per-section redirect rewriting, idempotency, and invalid inputs. Verified locally with mintlify broken-links: 0 broken links across the full site (Edge + 16 frozen versions, 4 locales). AGENTS.md (repo root) is the contributor guide for the new model; RELEASING.md is the release-cut runbook; README's Contribution section links to both. Co-authored-by: Cursor <cursoragent@cursor.com> * style: resolve linter issues --------- Co-authored-by: Cursor <cursoragent@cursor.com>
127 lines
5.0 KiB
Plaintext
127 lines
5.0 KiB
Plaintext
---
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title: MultiOn Tool
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description: The `MultiOnTool` empowers CrewAI agents with the capability to navigate and interact with the web through natural language instructions.
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icon: globe
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mode: "wide"
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---
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## Overview
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The `MultiOnTool` is designed to wrap [MultiOn's](https://docs.multion.ai/welcome) web browsing capabilities, enabling CrewAI agents to control web browsers using natural language instructions. This tool facilitates seamless web browsing, making it an essential asset for projects requiring dynamic web data interaction and automation of web-based tasks.
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## Installation
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To use this tool, you need to install the MultiOn package:
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```shell
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uv add multion
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```
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You'll also need to install the MultiOn browser extension and enable API usage.
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## Steps to Get Started
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To effectively use the `MultiOnTool`, follow these steps:
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1. **Install CrewAI**: Ensure that the `crewai[tools]` package is installed in your Python environment.
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2. **Install and use MultiOn**: Follow [MultiOn documentation](https://docs.multion.ai/learn/browser-extension) for installing the MultiOn Browser Extension.
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3. **Enable API Usage**: Click on the MultiOn extension in the extensions folder of your browser (not the hovering MultiOn icon on the web page) to open the extension configurations. Click the API Enabled toggle to enable the API.
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## Example
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The following example demonstrates how to initialize the tool and execute a web browsing task:
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```python Code
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from crewai import Agent, Task, Crew
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from crewai_tools import MultiOnTool
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# Initialize the tool
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multion_tool = MultiOnTool(api_key="YOUR_MULTION_API_KEY", local=False)
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# Define an agent that uses the tool
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browser_agent = Agent(
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role="Browser Agent",
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goal="Control web browsers using natural language",
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backstory="An expert browsing agent.",
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tools=[multion_tool],
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verbose=True,
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)
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# Example task to search and summarize news
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browse_task = Task(
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description="Summarize the top 3 trending AI News headlines",
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expected_output="A summary of the top 3 trending AI News headlines",
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agent=browser_agent,
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)
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# Create and run the crew
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crew = Crew(agents=[browser_agent], tasks=[browse_task])
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result = crew.kickoff()
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```
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## Parameters
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The `MultiOnTool` accepts the following parameters during initialization:
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- **api_key**: Optional. Specifies the MultiOn API key. If not provided, it will look for the `MULTION_API_KEY` environment variable.
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- **local**: Optional. Set to `True` to run the agent locally on your browser. Make sure the MultiOn browser extension is installed and API Enabled is checked. Default is `False`.
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- **max_steps**: Optional. Sets the maximum number of steps the MultiOn agent can take for a command. Default is `3`.
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## Usage
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When using the `MultiOnTool`, the agent will provide natural language instructions that the tool translates into web browsing actions. The tool returns the results of the browsing session along with a status.
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```python Code
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# Example of using the tool with an agent
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browser_agent = Agent(
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role="Web Browser Agent",
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goal="Search for and summarize information from the web",
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backstory="An expert at finding and extracting information from websites.",
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tools=[multion_tool],
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verbose=True,
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)
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# Create a task for the agent
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search_task = Task(
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description="Search for the latest AI news on TechCrunch and summarize the top 3 headlines",
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expected_output="A summary of the top 3 AI news headlines from TechCrunch",
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agent=browser_agent,
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)
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# Run the task
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crew = Crew(agents=[browser_agent], tasks=[search_task])
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result = crew.kickoff()
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```
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If the status returned is `CONTINUE`, the agent should be instructed to reissue the same instruction to continue execution.
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## Implementation Details
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The `MultiOnTool` is implemented as a subclass of `BaseTool` from CrewAI. It wraps the MultiOn client to provide web browsing capabilities:
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```python Code
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class MultiOnTool(BaseTool):
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"""Tool to wrap MultiOn Browse Capabilities."""
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name: str = "Multion Browse Tool"
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description: str = """Multion gives the ability for LLMs to control web browsers using natural language instructions.
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If the status is 'CONTINUE', reissue the same instruction to continue execution
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"""
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# Implementation details...
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def _run(self, cmd: str, *args: Any, **kwargs: Any) -> str:
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"""
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Run the Multion client with the given command.
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Args:
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cmd (str): The detailed and specific natural language instruction for web browsing
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*args (Any): Additional arguments to pass to the Multion client
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**kwargs (Any): Additional keyword arguments to pass to the Multion client
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"""
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# Implementation details...
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```
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## Conclusion
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The `MultiOnTool` provides a powerful way to integrate web browsing capabilities into CrewAI agents. By enabling agents to interact with websites through natural language instructions, it opens up a wide range of possibilities for web-based tasks, from data collection and research to automated interactions with web services. |