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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>
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100 lines
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---
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title: Apify Actors
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description: "تتيح لك `ApifyActorsTool` استدعاء Apify Actors لتوفير إمكانيات تجريف الويب والزحف واستخراج البيانات وأتمتة الويب لسير عمل CrewAI."
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icon: "); -webkit-mask-image: url('https://upload.wikimedia.org/wikipedia/commons/a/ae/Apify.svg');/*"
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mode: "wide"
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---
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# `ApifyActorsTool`
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دمج [Apify Actors](https://apify.com/actors) في سير عمل CrewAI الخاص بك.
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## الوصف
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تربط `ApifyActorsTool` بين [Apify Actors](https://apify.com/actors)، وهي برامج سحابية لتجريف الويب والأتمتة، وسير عمل CrewAI الخاص بك.
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استخدم أياً من أكثر من 4,000 Actor على [متجر Apify](https://apify.com/store) لحالات استخدام مثل استخراج البيانات من وسائل التواصل الاجتماعي ومحركات البحث والخرائط الإلكترونية ومواقع التجارة الإلكترونية وبوابات السفر أو المواقع العامة.
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للتفاصيل، راجع [تكامل Apify CrewAI](https://docs.apify.com/platform/integrations/crewai) في وثائق Apify.
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## خطوات البدء
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<Steps>
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<Step title="تثبيت التبعيات">
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ثبّت `crewai[tools]` و`langchain-apify` باستخدام pip: `pip install 'crewai[tools]' langchain-apify`.
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</Step>
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<Step title="الحصول على رمز API لـ Apify">
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سجّل في [وحدة تحكم Apify](https://console.apify.com/) واحصل على [رمز API الخاص بك](https://console.apify.com/settings/integrations).
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</Step>
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<Step title="إعداد البيئة">
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عيّن رمز API لـ Apify كمتغير بيئة `APIFY_API_TOKEN` لتمكين وظائف الأداة.
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</Step>
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</Steps>
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## مثال على الاستخدام
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استخدم `ApifyActorsTool` يدوياً لتشغيل [RAG Web Browser Actor](https://apify.com/apify/rag-web-browser) لإجراء بحث ويب:
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```python
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from crewai_tools import ApifyActorsTool
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# Initialize the tool with an Apify Actor
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tool = ApifyActorsTool(actor_name="apify/rag-web-browser")
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# Run the tool with input parameters
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results = tool.run(run_input={"query": "What is CrewAI?", "maxResults": 5})
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# Process the results
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for result in results:
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print(f"URL: {result['metadata']['url']}")
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print(f"Content: {result.get('markdown', 'N/A')[:100]}...")
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```
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### المخرجات المتوقعة
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إليك المخرجات من تشغيل الكود أعلاه:
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```text
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URL: https://www.example.com/crewai-intro
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Content: CrewAI is a framework for building AI-powered workflows...
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URL: https://docs.crewai.com/
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Content: Official documentation for CrewAI...
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```
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تقوم `ApifyActorsTool` تلقائياً بجلب تعريف Actor ومخطط الإدخال من Apify باستخدام `actor_name` المقدم ثم تبني وصف الأداة ومخطط المعاملات. هذا يعني أنك تحتاج فقط إلى تحديد `actor_name` صالح، والأداة تتعامل مع الباقي عند استخدامها مع الوكلاء - دون الحاجة لتحديد `run_input`. إليك كيفية عمل ذلك:
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```python
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from crewai import Agent
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from crewai_tools import ApifyActorsTool
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rag_browser = ApifyActorsTool(actor_name="apify/rag-web-browser")
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agent = Agent(
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role="Research Analyst",
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goal="Find and summarize information about specific topics",
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backstory="You are an experienced researcher with attention to detail",
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tools=[rag_browser],
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)
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```
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يمكنك تشغيل Actors أخرى من [متجر Apify](https://apify.com/store) ببساطة عن طريق تغيير `actor_name` وعند الاستخدام اليدوي، ضبط `run_input` بناءً على مخطط إدخال Actor.
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لمثال على الاستخدام مع الوكلاء، راجع [قالب CrewAI Actor](https://apify.com/templates/python-crewai).
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## الإعداد
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تتطلب `ApifyActorsTool` المدخلات التالية للعمل:
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- **`actor_name`**
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معرّف Apify Actor المراد تشغيله، مثل `"apify/rag-web-browser"`. تصفح جميع Actors على [متجر Apify](https://apify.com/store).
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- **`run_input`**
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قاموس من معاملات الإدخال لـ Actor عند تشغيل الأداة يدوياً.
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- على سبيل المثال، لـ Actor `apify/rag-web-browser`: `{"query": "search term", "maxResults": 5}`
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- راجع [مخطط إدخال](https://apify.com/apify/rag-web-browser/input-schema) Actor لقائمة معاملات الإدخال.
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## الموارد
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- **[Apify](https://apify.com/)**: استكشف منصة Apify.
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- **[كيفية بناء وكيل ذكاء اصطناعي على Apify](https://blog.apify.com/how-to-build-an-ai-agent/)** - دليل شامل خطوة بخطوة لإنشاء ونشر وتسويق وكلاء الذكاء الاصطناعي على منصة Apify.
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- **[RAG Web Browser Actor](https://apify.com/apify/rag-web-browser)**: Actor شائع لبحث الويب لنماذج LLM.
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- **[دليل تكامل CrewAI](https://docs.apify.com/platform/integrations/crewai)**: اتبع الدليل الرسمي لتكامل Apify وCrewAI.
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