From d45ed61db588803a37650d0db07bf415fd993cad Mon Sep 17 00:00:00 2001 From: MatthiasHowellYopp <106839070+MatthiasHowellYopp@users.noreply.github.com> Date: Tue, 21 Apr 2026 09:09:13 -0400 Subject: [PATCH 1/6] feat: added bedrock V4 support --- lib/crewai/src/crewai/llm.py | 39 ++ lib/crewai/src/crewai/llms/constants.py | 56 +++ .../llms/providers/bedrock/completion.py | 3 + uv.lock | 382 +++++++++--------- 4 files changed, 297 insertions(+), 183 deletions(-) diff --git a/lib/crewai/src/crewai/llm.py b/lib/crewai/src/crewai/llm.py index db126954e1..fb8461c04f 100644 --- a/lib/crewai/src/crewai/llm.py +++ b/lib/crewai/src/crewai/llm.py @@ -175,6 +175,16 @@ "us.amazon.nova-pro-v1:0": 300000, "us.amazon.nova-micro-v1:0": 128000, "us.amazon.nova-lite-v1:0": 300000, + # Claude 4 models + "us.anthropic.claude-opus-4-7": 1000000, + "us.anthropic.claude-sonnet-4-6": 1000000, + "us.anthropic.claude-opus-4-6-v1": 1000000, + "us.anthropic.claude-opus-4-5-20251101-v1:0": 200000, + "us.anthropic.claude-haiku-4-5-20251001-v1:0": 200000, + "us.anthropic.claude-sonnet-4-5-20250929-v1:0": 200000, + "us.anthropic.claude-opus-4-1-20250805-v1:0": 200000, + "us.anthropic.claude-opus-4-20250514-v1:0": 200000, + "us.anthropic.claude-sonnet-4-20250514-v1:0": 200000, "us.anthropic.claude-3-5-sonnet-20240620-v1:0": 200000, "us.anthropic.claude-3-5-haiku-20241022-v1:0": 200000, "us.anthropic.claude-3-5-sonnet-20241022-v2:0": 200000, @@ -193,15 +203,44 @@ "eu.anthropic.claude-3-5-sonnet-20240620-v1:0": 200000, "eu.anthropic.claude-3-sonnet-20240229-v1:0": 200000, "eu.anthropic.claude-3-haiku-20240307-v1:0": 200000, + # Claude 4 EU + "eu.anthropic.claude-opus-4-7": 1000000, + "eu.anthropic.claude-sonnet-4-6": 1000000, + "eu.anthropic.claude-opus-4-6-v1": 1000000, + "eu.anthropic.claude-opus-4-5-20251101-v1:0": 200000, + "eu.anthropic.claude-haiku-4-5-20251001-v1:0": 200000, + "eu.anthropic.claude-sonnet-4-5-20250929-v1:0": 200000, + "eu.anthropic.claude-opus-4-1-20250805-v1:0": 200000, + "eu.anthropic.claude-opus-4-20250514-v1:0": 200000, + "eu.anthropic.claude-sonnet-4-20250514-v1:0": 200000, "eu.meta.llama3-2-3b-instruct-v1:0": 131000, "eu.meta.llama3-2-1b-instruct-v1:0": 131000, "apac.anthropic.claude-3-5-sonnet-20240620-v1:0": 200000, "apac.anthropic.claude-3-5-sonnet-20241022-v2:0": 200000, "apac.anthropic.claude-3-sonnet-20240229-v1:0": 200000, "apac.anthropic.claude-3-haiku-20240307-v1:0": 200000, + # Claude 4 APAC + "apac.anthropic.claude-opus-4-7": 1000000, + "apac.anthropic.claude-sonnet-4-6": 1000000, + "apac.anthropic.claude-opus-4-6-v1": 1000000, + "apac.anthropic.claude-opus-4-5-20251101-v1:0": 200000, + "apac.anthropic.claude-haiku-4-5-20251001-v1:0": 200000, + "apac.anthropic.claude-sonnet-4-5-20250929-v1:0": 200000, + "apac.anthropic.claude-opus-4-1-20250805-v1:0": 200000, + "apac.anthropic.claude-opus-4-20250514-v1:0": 200000, + "apac.anthropic.claude-sonnet-4-20250514-v1:0": 200000, "amazon.nova-pro-v1:0": 300000, "amazon.nova-micro-v1:0": 128000, "amazon.nova-lite-v1:0": 300000, + "anthropic.claude-opus-4-7": 1000000, + "anthropic.claude-sonnet-4-6": 1000000, + "anthropic.claude-opus-4-6-v1": 1000000, + "anthropic.claude-opus-4-5-20251101-v1:0": 200000, + "anthropic.claude-haiku-4-5-20251001-v1:0": 200000, + "anthropic.claude-sonnet-4-5-20250929-v1:0": 200000, + "anthropic.claude-opus-4-1-20250805-v1:0": 200000, + "anthropic.claude-opus-4-20250514-v1:0": 200000, + "anthropic.claude-sonnet-4-20250514-v1:0": 200000, "anthropic.claude-3-5-sonnet-20240620-v1:0": 200000, "anthropic.claude-3-5-haiku-20241022-v1:0": 200000, "anthropic.claude-3-5-sonnet-20241022-v2:0": 200000, diff --git a/lib/crewai/src/crewai/llms/constants.py b/lib/crewai/src/crewai/llms/constants.py index 595a0a30dd..260c23dafb 100644 --- a/lib/crewai/src/crewai/llms/constants.py +++ b/lib/crewai/src/crewai/llms/constants.py @@ -423,6 +423,34 @@ BedrockModels: TypeAlias = Literal[ + # Inference profiles (regional) - Claude 4 + "us.anthropic.claude-sonnet-4-5-20250929-v1:0", + "us.anthropic.claude-sonnet-4-20250514-v1:0", + "us.anthropic.claude-opus-4-5-20251101-v1:0", + "us.anthropic.claude-opus-4-20250514-v1:0", + "us.anthropic.claude-opus-4-1-20250805-v1:0", + "us.anthropic.claude-haiku-4-5-20251001-v1:0", + "us.anthropic.claude-sonnet-4-6", + "us.anthropic.claude-opus-4-6-v1", + # Inference profiles - shorter versions + "us.anthropic.claude-sonnet-4-5-v1:0", + "us.anthropic.claude-opus-4-5-v1:0", + "us.anthropic.claude-opus-4-6-v1:0", + "us.anthropic.claude-haiku-4-5-v1:0", + "eu.anthropic.claude-sonnet-4-5-v1:0", + "eu.anthropic.claude-opus-4-5-v1:0", + "eu.anthropic.claude-haiku-4-5-v1:0", + "apac.anthropic.claude-sonnet-4-5-v1:0", + "apac.anthropic.claude-opus-4-5-v1:0", + "apac.anthropic.claude-haiku-4-5-v1:0", + # Global inference profiles + "global.anthropic.claude-sonnet-4-5-20250929-v1:0", + "global.anthropic.claude-sonnet-4-20250514-v1:0", + "global.anthropic.claude-opus-4-5-20251101-v1:0", + "global.anthropic.claude-opus-4-6-v1", + "global.anthropic.claude-haiku-4-5-20251001-v1:0", + "global.anthropic.claude-sonnet-4-6", + # Direct model IDs "ai21.jamba-1-5-large-v1:0", "ai21.jamba-1-5-mini-v1:0", "amazon.nova-lite-v1:0", @@ -496,6 +524,34 @@ "twelvelabs.pegasus-1-2-v1:0", ] BEDROCK_MODELS: list[BedrockModels] = [ + # Inference profiles (regional) - Claude 4 + "us.anthropic.claude-sonnet-4-5-20250929-v1:0", + "us.anthropic.claude-sonnet-4-20250514-v1:0", + "us.anthropic.claude-opus-4-5-20251101-v1:0", + "us.anthropic.claude-opus-4-20250514-v1:0", + "us.anthropic.claude-opus-4-1-20250805-v1:0", + "us.anthropic.claude-haiku-4-5-20251001-v1:0", + "us.anthropic.claude-sonnet-4-6", + "us.anthropic.claude-opus-4-6-v1", + # Inference profiles - shorter versions + "us.anthropic.claude-sonnet-4-5-v1:0", + "us.anthropic.claude-opus-4-5-v1:0", + "us.anthropic.claude-opus-4-6-v1:0", + "us.anthropic.claude-haiku-4-5-v1:0", + "eu.anthropic.claude-sonnet-4-5-v1:0", + "eu.anthropic.claude-opus-4-5-v1:0", + "eu.anthropic.claude-haiku-4-5-v1:0", + "apac.anthropic.claude-sonnet-4-5-v1:0", + "apac.anthropic.claude-opus-4-5-v1:0", + "apac.anthropic.claude-haiku-4-5-v1:0", + # Global inference profiles + "global.anthropic.claude-sonnet-4-5-20250929-v1:0", + "global.anthropic.claude-sonnet-4-20250514-v1:0", + "global.anthropic.claude-opus-4-5-20251101-v1:0", + "global.anthropic.claude-opus-4-6-v1", + "global.anthropic.claude-haiku-4-5-20251001-v1:0", + "global.anthropic.claude-sonnet-4-6", + # Direct model IDs "ai21.jamba-1-5-large-v1:0", "ai21.jamba-1-5-mini-v1:0", "amazon.nova-lite-v1:0", diff --git a/lib/crewai/src/crewai/llms/providers/bedrock/completion.py b/lib/crewai/src/crewai/llms/providers/bedrock/completion.py index 54c222c859..cd323eac00 100644 --- a/lib/crewai/src/crewai/llms/providers/bedrock/completion.py +++ b/lib/crewai/src/crewai/llms/providers/bedrock/completion.py @@ -2075,6 +2075,9 @@ def get_context_window_size(self) -> int: # Context 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b/lib/crewai/src/crewai/__init__.py index 444cb5d070..b59fc893de 100644 --- a/lib/crewai/src/crewai/__init__.py +++ b/lib/crewai/src/crewai/__init__.py @@ -1,10 +1,9 @@ -import contextvars -import threading -from typing import Any -import urllib.request +import importlib +import sys +from typing import TYPE_CHECKING, Annotated, Any import warnings -from pydantic import PydanticUserError +from pydantic import Field, PydanticUserError from crewai.agent.core import Agent from crewai.agent.planning_config import PlanningConfig @@ -20,7 +19,10 @@ from crewai.task import Task from crewai.tasks.llm_guardrail import LLMGuardrail from crewai.tasks.task_output import TaskOutput -from crewai.telemetry.telemetry import Telemetry + + +if TYPE_CHECKING: + from crewai.memory.unified_memory import Memory def _suppress_pydantic_deprecation_warnings() -> None: @@ -47,37 +49,6 @@ def filtered_warn( _suppress_pydantic_deprecation_warnings() __version__ = "1.14.3a1" -_telemetry_submitted = False - - -def _track_install() -> None: - """Track package installation/first-use via Scarf analytics.""" - global _telemetry_submitted - - if _telemetry_submitted or Telemetry._is_telemetry_disabled(): - return - - try: - pixel_url = "https://api.scarf.sh/v2/packages/CrewAI/crewai/docs/00f2dad1-8334-4a39-934e-003b2e1146db" - - req = urllib.request.Request(pixel_url) # noqa: S310 - req.add_header("User-Agent", f"CrewAI-Python/{__version__}") - - with urllib.request.urlopen(req, timeout=2): # noqa: S310 - _telemetry_submitted = True - except Exception: # noqa: S110 - pass - - -def _track_install_async() -> None: - """Track installation in background thread to avoid blocking imports.""" - if not Telemetry._is_telemetry_disabled(): - ctx = contextvars.copy_context() - thread = threading.Thread(target=ctx.run, args=(_track_install,), daemon=True) - thread.start() - - -_track_install_async() _LAZY_IMPORTS: dict[str, tuple[str, str]] = { "Memory": ("crewai.memory.unified_memory", "Memory"), @@ -88,8 +59,6 @@ def __getattr__(name: str) -> Any: """Lazily import heavy modules (e.g. Memory → lancedb) on first access.""" if name in _LAZY_IMPORTS: module_path, attr = _LAZY_IMPORTS[name] - import importlib - mod = importlib.import_module(module_path) val = getattr(mod, attr) globals()[name] = val @@ -147,8 +116,6 @@ def __getattr__(name: str) -> Any: except ImportError: pass - import sys - _full_namespace = { **_base_namespace, "ToolsHandler": _ToolsHandler, @@ -191,10 +158,6 @@ def __getattr__(name: str) -> Any: Flow.model_rebuild(force=True, _types_namespace=_full_namespace) _AgentExecutor.model_rebuild(force=True, _types_namespace=_full_namespace) - from typing import Annotated - - from pydantic import Field - from crewai.state.runtime import RuntimeState Entity = Annotated[ From 84a4d47aa7496843ad59d11f0ee5c60207d92af1 Mon Sep 17 00:00:00 2001 From: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com> Date: Tue, 21 Apr 2026 08:55:39 -0700 Subject: [PATCH 3/6] updated descriptions and applied the actual translations (#5572) --- README.md | 10 + docs/ar/guides/coding-tools/build-with-ai.mdx | 181 ++++++++++-------- docs/en/guides/coding-tools/build-with-ai.mdx | 13 +- docs/ko/guides/coding-tools/build-with-ai.mdx | 181 ++++++++++-------- .../guides/coding-tools/build-with-ai.mdx | 179 +++++++++-------- 5 files changed, 309 insertions(+), 255 deletions(-) diff --git a/README.md b/README.md index bcb6634aa3..817f5155fe 100644 --- a/README.md +++ b/README.md @@ -109,7 +109,17 @@ Using an AI coding agent? Teach it CrewAI best practices in one command: **Claude Code:** ```shell /plugin marketplace add crewAIInc/skills +/plugin install crewai-skills@crewai-plugins +/reload-plugins ``` +Four skills that activate automatically when you ask relevant CrewAI questions: + +| Skill | When it runs | +|-------|--------------| +| `getting-started` | Scaffolding new projects, choosing between `LLM.call()` / `Agent` / `Crew` / `Flow`, wiring `crew.py` / `main.py` | +| `design-agent` | Configuring agents — role, goal, backstory, tools, LLMs, memory, guardrails | +| `design-task` | Writing task descriptions, dependencies, structured output (`output_pydantic`, `output_json`), human review | +| `ask-docs` | Querying the live [CrewAI docs MCP server](https://docs.crewai.com/mcp) for up-to-date API details | **Cursor, Codex, Windsurf, and others ([skills.sh](https://skills.sh/crewaiinc/skills)):** ```shell diff --git a/docs/ar/guides/coding-tools/build-with-ai.mdx b/docs/ar/guides/coding-tools/build-with-ai.mdx index 744ad1bf47..4ea73abb9b 100644 --- a/docs/ar/guides/coding-tools/build-with-ai.mdx +++ b/docs/ar/guides/coding-tools/build-with-ai.mdx @@ -1,15 +1,15 @@ --- -title: "Build with AI" -description: "Everything AI coding agents need to build, deploy, and scale with CrewAI — skills, machine-readable docs, deployment, and enterprise features." +title: "البناء باستخدام الذكاء الاصطناعي" +description: "كل ما يحتاجه وكلاء البرمجة بالذكاء الاصطناعي للبناء والنشر والتوسع مع CrewAI — المهارات، وثائق مقروءة آلياً، النشر، وميزات المؤسسات." icon: robot mode: "wide" --- -# Build with AI +# البناء باستخدام الذكاء الاصطناعي -CrewAI is AI-native. This page brings together everything an AI coding agent needs to build with CrewAI — whether you're Claude Code, Codex, Cursor, Gemini CLI, or any other assistant helping a developer ship crews and flows. +CrewAI مُصمَّم أصلاً للعمل مع الذكاء الاصطناعي. تجمع هذه الصفحة ما يحتاجه وكيل البرمجة بالذكاء الاصطناعي للبناء مع CrewAI — سواءً كان Claude Code أو Codex أو Cursor أو Gemini CLI أو أي مساعد آخر يساعد المطوّر على إيصال الـ crews والـ flows. -### Supported Coding Agents +### وكلاء البرمجة المدعومون @@ -20,128 +20,139 @@ CrewAI is AI-native. This page brings together everything an AI coding agent nee - This page is designed to be consumed by both humans and AI assistants. If you're a coding agent, start with **Skills** to get CrewAI context, then use **llms.txt** for full docs access. + صُممت هذه الصفحة للبشر وللمساعدين الذكيين على حدٍّ سواء. إذا كنت وكيل برمجة، ابدأ بـ **Skills** للحصول على سياق CrewAI، ثم استخدم **llms.txt** للوصول الكامل إلى الوثائق. --- -## 1. Skills — Teach Your Agent CrewAI +## 1. Skills — علِّم وكيلك CrewAI -**Skills** are instruction packs that give coding agents deep CrewAI knowledge — how to scaffold Flows, configure Crews, use tools, and follow framework conventions. +**Skills** حزم تعليمات تمنح وكلاء البرمجة معرفة عميقة بـ CrewAI — كيفية إنشاء هيكل Flows، وضبط Crews، استخدام الأدوات، واتباع اتفاقيات الإطار. - + Anthropic - CrewAI skills are available in the **Claude Code plugin marketplace** — the same distribution channel used by top AI-native companies: - ``` + مهارات CrewAI متاحة في **سوق إضافات Claude Code** — نفس قناة التوزيع التي تستخدمها شركات رائدة في مجال الذكاء الاصطناعي: + ```shell /plugin marketplace add crewAIInc/skills + /plugin install crewai-skills@crewai-plugins + /reload-plugins ``` + + تُفعَّل أربع مهارات تلقائياً عند طرح أسئلة متعلقة بـ CrewAI: + + | المهارة | متى تُستخدم | + |---------|-------------| + | `getting-started` | مشاريع جديدة، الاختيار بين `LLM.call()` / `Agent` / `Crew` / `Flow`، ربط `crew.py` / `main.py` | + | `design-agent` | ضبط الوكلاء — الدور، الهدف، الخلفية، الأدوات، نماذج اللغة، الذاكرة، الحدود الآمنة | + | `design-task` | وصف المهام، التبعيات، المخرجات المنظمة (`output_pydantic`، `output_json`)، المراجعة البشرية | + | `ask-docs` | الاستعلام من [خادم CrewAI docs MCP](https://docs.crewai.com/mcp) للحصول على تفاصيل واجهة البرمجة الحالية | - - Works with Claude Code, Codex, Cursor, Gemini CLI, or any coding agent: + + يعمل مع Claude Code أو Codex أو Cursor أو Gemini CLI أو أي وكيل برمجة: ```shell npx skills add crewaiinc/skills ``` - Pulls from the [skills.sh registry](https://skills.sh/crewaiinc/skills). + يُجلب من [سجل skills.sh](https://skills.sh/crewaiinc/skills). - - Use either method above — the Claude Code plugin marketplace or `npx skills add`. Both install the official [crewAIInc/skills](https://github.com/crewAIInc/skills) pack. + + استخدم إحدى الطريقتين أعلاه — سوق إضافات Claude Code أو `npx skills add`. كلاهما يثبّت الحزمة الرسمية [crewAIInc/skills](https://github.com/crewAIInc/skills). - - The skill pack teaches your agent: - - **Flows** — stateful apps, steps, and crew kickoffs - - **Crews & Agents** — YAML-first patterns, roles, tasks, delegation - - **Tools & Integrations** — search, APIs, MCP servers, and common CrewAI tools - - **Project layout** — CLI scaffolds and repo conventions - - **Up-to-date patterns** — tracks current CrewAI docs and best practices + + تعلّم الحزمة وكيلك: + - **Flows** — تطبيقات ذات حالة، خطوات، وتشغيل crews + - **Crews والوكلاء** — أنماط YAML أولاً، الأدوار، المهام، التفويض + - **الأدوات والتكاملات** — البحث، واجهات API، خوادم MCP، وأدوات CrewAI الشائعة + - **هيكل المشروع** — هياكل CLI واتفاقيات المستودع + - **أنماط محدثة** — يتماشى مع وثائق CrewAI الحالية وأفضل الممارسات - - Your agent can now scaffold and build CrewAI projects without you re-explaining the framework each session. + + يمكن لوكيلك الآن إنشاء هيكل وبناء مشاريع CrewAI دون أن تعيد شرح الإطار في كل جلسة. - - How skills work in CrewAI agents — injection, activation, and patterns. + + كيف تعمل المهارات في وكلاء CrewAI — الحقن، التفعيل، والأنماط. - - Overview of the crewAIInc/skills pack and what it includes. + + نظرة على حزمة crewAIInc/skills وما تتضمنه. - - Set up AGENTS.md for Claude Code, Codex, Cursor, and Gemini CLI. + + إعداد AGENTS.md لـ Claude Code وCodex وCursor وGemini CLI. - - Official listing — skills, install stats, and audits. + + القائمة الرسمية — المهارات، إحصاءات التثبيت، والتدقيق. --- -## 2. llms.txt — Machine-Readable Docs +## 2. llms.txt — وثائق مقروءة آلياً -CrewAI publishes an `llms.txt` file that gives AI assistants direct access to the full documentation in a machine-readable format. +ينشر CrewAI ملف `llms.txt` يمنح المساعدين الذكيين وصولاً مباشراً إلى الوثائق الكاملة بصيغة مقروءة آلياً. ``` https://docs.crewai.com/llms.txt ``` - - [`llms.txt`](https://llmstxt.org/) is an emerging standard for making documentation consumable by large language models. Instead of scraping HTML, your agent can fetch a single structured text file with all the content it needs. + + [`llms.txt`](https://llmstxt.org/) معيار ناشئ لجعل الوثائق قابلة للاستهلاك من قبل نماذج اللغة الكبيرة. بدلاً من استخراج HTML، يمكن لوكيلك جلب ملف نصي واحد منظم بكل المحتوى المطلوب. - CrewAI's `llms.txt` is **already live** — your agent can use it right now. + ملف `llms.txt` الخاص بـ CrewAI **متاح فعلياً** — يمكن لوكيلك استخدامه الآن. - - Point your coding agent at the URL when it needs CrewAI reference docs: + + وجِّه وكيل البرمجة إلى عنوان URL عندما يحتاج إلى مرجع CrewAI: ``` Fetch https://docs.crewai.com/llms.txt for CrewAI documentation. ``` - Many coding agents (Claude Code, Cursor, etc.) can fetch URLs directly. The file contains structured documentation covering all CrewAI concepts, APIs, and guides. + يمكن للعديد من وكلاء البرمجة (Claude Code، Cursor، وغيرهما) جلب عناوين URL مباشرة. يحتوي الملف على وثائق منظمة تغطي مفاهيم CrewAI وواجهات البرمجة والأدلة. - - - **No scraping required** — clean, structured content in one request - - **Always up-to-date** — served directly from docs.crewai.com - - **Optimized for LLMs** — formatted for context windows, not browsers - - **Complements skills** — skills teach patterns, llms.txt provides reference + + - **دون استخراج ويب** — محتوى نظيف ومنظم في طلب واحد + - **دائماً محدث** — يُقدَّم مباشرة من docs.crewai.com + - **محسّن لنماذج اللغة** — مُنسَّق لنوافذ السياق لا للمتصفحات + - **يُكمّل Skills** — المهارات تعلّم الأنماط، وllms.txt يوفّر المرجع --- -## 3. Deploy to Enterprise +## 3. النشر للمؤسسات -Go from a local crew to production on **CrewAI AMP** (Agent Management Platform) in minutes. +انتقل من crew محلي إلى الإنتاج على **CrewAI AMP** (منصة إدارة الوكلاء) في دقائق. - - Scaffold and test your crew or flow: + + أنشئ الهيكل واختبر crew أو flow: ```bash crewai create crew my_crew cd my_crew crewai run ``` - - Ensure your project structure is ready: + + تأكد أن هيكل مشروعك جاهز: ```bash crewai deploy --prepare ``` - See the [preparation guide](/en/enterprise/guides/prepare-for-deployment) for details on project structure and requirements. + راجع [دليل التحضير](/ar/enterprise/guides/prepare-for-deployment) لتفاصيل الهيكل والمتطلبات. - - Push to the CrewAI AMP platform: + + ادفع إلى منصة CrewAI AMP: ```bash crewai deploy ``` - You can also deploy via [GitHub integration](/en/enterprise/guides/deploy-to-amp) or [Crew Studio](/en/enterprise/guides/enable-crew-studio). + يمكنك أيضاً النشر عبر [تكامل GitHub](/ar/enterprise/guides/deploy-to-amp) أو [Crew Studio](/ar/enterprise/guides/enable-crew-studio). - - Your deployed crew gets a REST API endpoint. Integrate it into any application: + + يحصل الـ crew المنشور على نقطة نهاية REST. دمجه في أي تطبيق: ```bash curl -X POST https://app.crewai.com/api/v1/crews//kickoff \ -H "Authorization: Bearer $CREWAI_API_KEY" \ @@ -152,55 +163,55 @@ Go from a local crew to production on **CrewAI AMP** (Agent Management Platform) - - Full deployment guide — CLI, GitHub, and Crew Studio methods. + + دليل النشر الكامل — CLI وGitHub وCrew Studio. - - Platform overview — what AMP provides for production crews. + + نظرة على المنصة — ما يوفّره AMP لـ crews في الإنتاج. --- -## 4. Enterprise Features +## 4. ميزات المؤسسات -CrewAI AMP is built for production teams. Here's what you get beyond deployment. +CrewAI AMP مُصمَّم لفرق الإنتاج. إليك ما تحصل عليه بعد النشر. - - Detailed execution traces, logs, and performance metrics for every crew run. Monitor agent decisions, tool calls, and task completion in real time. + + مسارات تنفيذ مفصّلة، وسجلات، ومقاييس أداء لكل تشغيل crew. راقب قرارات الوكلاء، استدعاءات الأدوات، وإكمال المهام في الوقت الفعلي. - No-code/low-code interface to create, customize, and deploy crews visually — then export to code or deploy directly. + واجهة منخفضة/بدون كود لإنشاء crews وتخصيصها ونشرها بصرياً — ثم التصدير إلى الشيفرة أو النشر مباشرة. - - Stream real-time events from crew executions to your systems. Integrate with Slack, Zapier, or any webhook consumer. + + بث أحداث فورية من تنفيذات الـ crews إلى أنظمتك. تكامل مع Slack أو Zapier أو أي مستهلك ويبهوك. - - SSO, RBAC, and organization-level controls. Manage who can create, deploy, and access crews across your team. + + SSO وRBAC وضوابط على مستوى المؤسسة. أدر من يمكنه إنشاء crews ونشرها والوصول إليها. - - Publish and share custom tools across your organization. Install community tools from the registry. + + انشر وشارك أدواتاً مخصصة عبر مؤسستك. ثبّت أدوات المجتمع من السجل. - - Run CrewAI AMP on your own infrastructure. Full platform capabilities with data residency and compliance controls. + + شغّل CrewAI AMP على بنيتك التحتية. قدرات المنصة كاملة مع ضوابط إقامة البيانات والامتثال. - - AMP is for teams that need to move AI agent workflows from prototypes to production — with observability, access controls, and scalable infrastructure. Whether you're a startup or enterprise, AMP handles the operational complexity so you can focus on building agents. + + لفرق تحتاج نقل سير عمل وكلاء الذكاء الاصطناعي من النماذج الأولية إلى الإنتاج — مع المراقبة وضوابط الوصول والبنية التحتية القابلة للتوسع. سواءً كنت ناشئاً أو مؤسسة كبيرة، يتولى AMP التعقيد التشغيلي لتتفرغ لبناء الوكلاء. - - - **Cloud (app.crewai.com)** — managed by CrewAI, fastest path to production - - **Factory (self-hosted)** — run on your own infrastructure for full data control - - **Hybrid** — mix cloud and self-hosted based on sensitivity requirements + + - **السحابة (app.crewai.com)** — تُدار من CrewAI، أسرع طريق إلى الإنتاج + - **Factory (استضافة ذاتية)** — على بنيتك التحتية لسيطرة كاملة على البيانات + - **هجين** — دمج السحابة والاستضافة الذاتية حسب حساسية البيانات - - Sign up at [app.crewai.com](https://app.crewai.com) to see current plans. Enterprise and Factory pricing is available on request. + + سجّل في [app.crewai.com](https://app.crewai.com) لمعرفة الخطط الحالية. تسعير المؤسسات وFactory متاح عند الطلب. - - Sign up and deploy your first crew to production. + + سجّل وانشر أول crew لك في الإنتاج. diff --git a/docs/en/guides/coding-tools/build-with-ai.mdx b/docs/en/guides/coding-tools/build-with-ai.mdx index 744ad1bf47..2badb284e4 100644 --- a/docs/en/guides/coding-tools/build-with-ai.mdx +++ b/docs/en/guides/coding-tools/build-with-ai.mdx @@ -33,9 +33,20 @@ CrewAI is AI-native. This page brings together everything an AI coding agent nee Anthropic CrewAI skills are available in the **Claude Code plugin marketplace** — the same distribution channel used by top AI-native companies: - ``` + ```shell /plugin marketplace add crewAIInc/skills + /plugin install crewai-skills@crewai-plugins + /reload-plugins ``` + + Four skills activate automatically when you ask relevant CrewAI questions: + + | Skill | When it runs | + |-------|--------------| + | `getting-started` | Scaffolding new projects, choosing between `LLM.call()` / `Agent` / `Crew` / `Flow`, wiring `crew.py` / `main.py` | + | `design-agent` | Configuring agents — role, goal, backstory, tools, LLMs, memory, guardrails | + | `design-task` | Writing task descriptions, dependencies, structured output (`output_pydantic`, `output_json`), human review | + | `ask-docs` | Querying the live [CrewAI docs MCP server](https://docs.crewai.com/mcp) for up-to-date API details | Works with Claude Code, Codex, Cursor, Gemini CLI, or any coding agent: diff --git a/docs/ko/guides/coding-tools/build-with-ai.mdx b/docs/ko/guides/coding-tools/build-with-ai.mdx index 744ad1bf47..22f6b25d85 100644 --- a/docs/ko/guides/coding-tools/build-with-ai.mdx +++ b/docs/ko/guides/coding-tools/build-with-ai.mdx @@ -1,15 +1,15 @@ --- -title: "Build with AI" -description: "Everything AI coding agents need to build, deploy, and scale with CrewAI — skills, machine-readable docs, deployment, and enterprise features." +title: "AI와 함께 빌드하기" +description: "CrewAI로 빌드·배포·확장하는 데 필요한 모든 것 — 스킬, 기계가 읽을 수 있는 문서, 배포, 엔터프라이즈 기능을 AI 코딩 에이전트용으로 정리했습니다." icon: robot mode: "wide" --- -# Build with AI +# AI와 함께 빌드하기 -CrewAI is AI-native. This page brings together everything an AI coding agent needs to build with CrewAI — whether you're Claude Code, Codex, Cursor, Gemini CLI, or any other assistant helping a developer ship crews and flows. +CrewAI는 AI 네이티브입니다. 이 페이지는 Claude Code, Codex, Cursor, Gemini CLI 등 개발자가 crew와 flow를 배포하도록 돕는 코딩 에이전트가 CrewAI로 빌드할 때 필요한 내용을 한곳에 모았습니다. -### Supported Coding Agents +### 지원 코딩 에이전트 @@ -20,128 +20,139 @@ CrewAI is AI-native. This page brings together everything an AI coding agent nee - This page is designed to be consumed by both humans and AI assistants. If you're a coding agent, start with **Skills** to get CrewAI context, then use **llms.txt** for full docs access. + 이 페이지는 사람과 AI 어시스턴트 모두를 위해 작성되었습니다. 코딩 에이전트라면 CrewAI 맥락은 **Skills**부터, 전체 문서 접근은 **llms.txt**를 사용하세요. --- -## 1. Skills — Teach Your Agent CrewAI +## 1. Skills — 에이전트에게 CrewAI 가르치기 -**Skills** are instruction packs that give coding agents deep CrewAI knowledge — how to scaffold Flows, configure Crews, use tools, and follow framework conventions. +**Skills**는 코딩 에이전트에게 Flow 스캐폴딩, Crew 구성, 도구 사용, 프레임워크 관례 등 CrewAI에 대한 깊은 지식을 담은 지침 묶음입니다. - + Anthropic - CrewAI skills are available in the **Claude Code plugin marketplace** — the same distribution channel used by top AI-native companies: - ``` + CrewAI 스킬은 **Claude Code 플러그인 마켓플레이스**에서 제공됩니다. AI 네이티브 기업들이 쓰는 것과 같은 배포 채널입니다. + ```shell /plugin marketplace add crewAIInc/skills + /plugin install crewai-skills@crewai-plugins + /reload-plugins ``` + + CrewAI와 관련된 질문을 하면 다음 네 가지 스킬이 자동으로 활성화됩니다. + + | 스킬 | 실행 시점 | + |------|-------------| + | `getting-started` | 새 프로젝트 스캐폴딩, `LLM.call()` / `Agent` / `Crew` / `Flow` 선택, `crew.py` / `main.py` 연결 | + | `design-agent` | 에이전트 구성 — 역할, 목표, 배경 이야기, 도구, LLM, 메모리, 가드레일 | + | `design-task` | 태스크 설명, 의존성, 구조화된 출력(`output_pydantic`, `output_json`), 사람 검토 | + | `ask-docs` | 최신 API 정보를 위해 [CrewAI 문서 MCP 서버](https://docs.crewai.com/mcp) 조회 | - - Works with Claude Code, Codex, Cursor, Gemini CLI, or any coding agent: + + Claude Code, Codex, Cursor, Gemini CLI 등 모든 코딩 에이전트에서 사용할 수 있습니다. ```shell npx skills add crewaiinc/skills ``` - Pulls from the [skills.sh registry](https://skills.sh/crewaiinc/skills). + [skills.sh 레지스트리](https://skills.sh/crewaiinc/skills)에서 가져옵니다. - - Use either method above — the Claude Code plugin marketplace or `npx skills add`. Both install the official [crewAIInc/skills](https://github.com/crewAIInc/skills) pack. + + 위 방법 중 하나를 사용하세요 — Claude Code 플러그인 마켓플레이스 또는 `npx skills add`. 둘 다 공식 [crewAIInc/skills](https://github.com/crewAIInc/skills) 팩을 설치합니다. - - The skill pack teaches your agent: - - **Flows** — stateful apps, steps, and crew kickoffs - - **Crews & Agents** — YAML-first patterns, roles, tasks, delegation - - **Tools & Integrations** — search, APIs, MCP servers, and common CrewAI tools - - **Project layout** — CLI scaffolds and repo conventions - - **Up-to-date patterns** — tracks current CrewAI docs and best practices + + 스킬 팩이 에이전트에게 알려 주는 내용: + - **Flow** — 상태ful 앱, 단계, crew 킥오프 + - **Crew 및 에이전트** — YAML 우선 패턴, 역할, 태스크, 위임 + - **도구 및 통합** — 검색, API, MCP 서버, 일반적인 CrewAI 도구 + - **프로젝트 레이아웃** — CLI 스캐폴드와 저장소 관례 + - **최신 패턴** — 현재 CrewAI 문서와 모범 사례 반영 - - Your agent can now scaffold and build CrewAI projects without you re-explaining the framework each session. + + 매 세션마다 프레임워크를 다시 설명하지 않아도 에이전트가 CrewAI 프로젝트를 스캐폴딩하고 빌드할 수 있습니다. - - How skills work in CrewAI agents — injection, activation, and patterns. + + CrewAI 에이전트에서 스킬이 동작하는 방식 — 주입, 활성화, 패턴. - - Overview of the crewAIInc/skills pack and what it includes. + + crewAIInc/skills 팩 개요와 포함 내용. - - Set up AGENTS.md for Claude Code, Codex, Cursor, and Gemini CLI. + + Claude Code, Codex, Cursor, Gemini CLI용 AGENTS.md 설정. - - Official listing — skills, install stats, and audits. + + 공식 목록 — 스킬, 설치 통계, 감사 정보. --- -## 2. llms.txt — Machine-Readable Docs +## 2. llms.txt — 기계가 읽을 수 있는 문서 -CrewAI publishes an `llms.txt` file that gives AI assistants direct access to the full documentation in a machine-readable format. +CrewAI는 AI 어시스턴트가 전체 문서에 기계가 읽을 수 있는 형태로 바로 접근할 수 있도록 `llms.txt` 파일을 제공합니다. ``` https://docs.crewai.com/llms.txt ``` - - [`llms.txt`](https://llmstxt.org/) is an emerging standard for making documentation consumable by large language models. Instead of scraping HTML, your agent can fetch a single structured text file with all the content it needs. + + [`llms.txt`](https://llmstxt.org/)는 문서를 대규모 언어 모델이 소비하기 쉽게 만드는 새로운 표준입니다. HTML을 스크래핑하는 대신, 필요한 내용이 담긴 하나의 구조화된 텍스트 파일을 가져올 수 있습니다. - CrewAI's `llms.txt` is **already live** — your agent can use it right now. + CrewAI의 `llms.txt`는 **이미 제공 중**이며, 에이전트가 바로 사용할 수 있습니다. - - Point your coding agent at the URL when it needs CrewAI reference docs: + + CrewAI 참고 문서가 필요할 때 코딩 에이전트에 URL을 알려 주세요. ``` Fetch https://docs.crewai.com/llms.txt for CrewAI documentation. ``` - Many coding agents (Claude Code, Cursor, etc.) can fetch URLs directly. The file contains structured documentation covering all CrewAI concepts, APIs, and guides. + Claude Code, Cursor 등 많은 코딩 에이전트가 URL을 직접 가져올 수 있습니다. 파일에는 CrewAI 개념, API, 가이드를 아우르는 구조화된 문서가 포함되어 있습니다. - - - **No scraping required** — clean, structured content in one request - - **Always up-to-date** — served directly from docs.crewai.com - - **Optimized for LLMs** — formatted for context windows, not browsers - - **Complements skills** — skills teach patterns, llms.txt provides reference + + - **스크래핑 불필요** — 한 번의 요청으로 깔끔한 구조화 콘텐츠 + - **항상 최신** — docs.crewai.com에서 직접 제공 + - **LLM에 최적화** — 브라우저가 아니라 컨텍스트 윈도우에 맞게 포맷 + - **스킬과 상호 보완** — 스킬은 패턴을, llms.txt는 참조를 제공 --- -## 3. Deploy to Enterprise +## 3. 엔터프라이즈에 배포 -Go from a local crew to production on **CrewAI AMP** (Agent Management Platform) in minutes. +로컬 crew를 몇 분 안에 **CrewAI AMP**(Agent Management Platform) 프로덕션으로 가져가세요. - - Scaffold and test your crew or flow: + + crew 또는 flow를 스캐폴딩하고 테스트합니다. ```bash crewai create crew my_crew cd my_crew crewai run ``` - - Ensure your project structure is ready: + + 프로젝트 구조가 준비되었는지 확인합니다. ```bash crewai deploy --prepare ``` - See the [preparation guide](/en/enterprise/guides/prepare-for-deployment) for details on project structure and requirements. + 구조와 요구 사항은 [준비 가이드](/ko/enterprise/guides/prepare-for-deployment)를 참고하세요. - - Push to the CrewAI AMP platform: + + CrewAI AMP 플랫폼으로 푸시합니다. ```bash crewai deploy ``` - You can also deploy via [GitHub integration](/en/enterprise/guides/deploy-to-amp) or [Crew Studio](/en/enterprise/guides/enable-crew-studio). + [GitHub 연동](/ko/enterprise/guides/deploy-to-amp) 또는 [Crew Studio](/ko/enterprise/guides/enable-crew-studio)로도 배포할 수 있습니다. - - Your deployed crew gets a REST API endpoint. Integrate it into any application: + + 배포된 crew는 REST API 엔드포인트를 받습니다. 모든 애플리케이션에 통합할 수 있습니다. ```bash curl -X POST https://app.crewai.com/api/v1/crews//kickoff \ -H "Authorization: Bearer $CREWAI_API_KEY" \ @@ -152,55 +163,55 @@ Go from a local crew to production on **CrewAI AMP** (Agent Management Platform) - - Full deployment guide — CLI, GitHub, and Crew Studio methods. + + 전체 배포 가이드 — CLI, GitHub, Crew Studio 방법. - - Platform overview — what AMP provides for production crews. + + 플랫폼 개요 — 프로덕션 crew에 AMP가 제공하는 것. --- -## 4. Enterprise Features +## 4. 엔터프라이즈 기능 -CrewAI AMP is built for production teams. Here's what you get beyond deployment. +CrewAI AMP는 프로덕션 팀을 위해 만들어졌습니다. 배포 외에 제공되는 것은 다음과 같습니다. - - Detailed execution traces, logs, and performance metrics for every crew run. Monitor agent decisions, tool calls, and task completion in real time. + + 모든 crew 실행에 대한 상세 실행 추적, 로그, 성능 지표. 에이전트 결정, 도구 호출, 태스크 완료를 실시간으로 모니터링합니다. - No-code/low-code interface to create, customize, and deploy crews visually — then export to code or deploy directly. + 시각적으로 crew를 만들고, 맞춤 설정하고, 배포하는 노코드/로코드 인터페이스 — 코드로 보내거나 바로 배포할 수 있습니다. - - Stream real-time events from crew executions to your systems. Integrate with Slack, Zapier, or any webhook consumer. + + crew 실행에서 실시간 이벤트를 시스템으로 스트리밍합니다. Slack, Zapier 등 웹훅 소비자와 연동할 수 있습니다. - - SSO, RBAC, and organization-level controls. Manage who can create, deploy, and access crews across your team. + + SSO, RBAC, 조직 단위 제어. 팀 전체에서 crew 생성·배포·접근 권한을 관리합니다. - - Publish and share custom tools across your organization. Install community tools from the registry. + + 조직 전체에 맞춤 도구를 게시하고 공유합니다. 레지스트리에서 커뮤니티 도구를 설치합니다. - - Run CrewAI AMP on your own infrastructure. Full platform capabilities with data residency and compliance controls. + + 자체 인프라에서 CrewAI AMP를 실행합니다. 데이터 상주와 규정 준수 제어와 함께 플랫폼 전체 기능을 사용할 수 있습니다. - - AMP is for teams that need to move AI agent workflows from prototypes to production — with observability, access controls, and scalable infrastructure. Whether you're a startup or enterprise, AMP handles the operational complexity so you can focus on building agents. + + AI 에이전트 워크플로를 프로토타입에서 프로덕션으로 옮겨야 하는 팀을 위한 제품입니다. 관측 가능성, 접근 제어, 확장 가능한 인프라를 제공합니다. 스타트업이든 대기업이든 운영 복잡도는 AMP가 맡고, 에이전트 구축에 집중할 수 있습니다. - - - **Cloud (app.crewai.com)** — managed by CrewAI, fastest path to production - - **Factory (self-hosted)** — run on your own infrastructure for full data control - - **Hybrid** — mix cloud and self-hosted based on sensitivity requirements + + - **클라우드 (app.crewai.com)** — CrewAI가 관리, 프로덕션까지 가장 빠른 경로 + - **Factory(셀프 호스팅)** — 데이터 통제를 위해 자체 인프라에서 실행 + - **하이브리드** — 민감도에 따라 클라우드와 셀프 호스팅을 혼합 - - Sign up at [app.crewai.com](https://app.crewai.com) to see current plans. Enterprise and Factory pricing is available on request. + + [app.crewai.com](https://app.crewai.com)에 가입하면 현재 요금제를 확인할 수 있습니다. 엔터프라이즈 및 Factory 가격은 문의 시 안내합니다. - - Sign up and deploy your first crew to production. + + 가입하고 첫 crew를 프로덕션에 배포해 보세요. diff --git a/docs/pt-BR/guides/coding-tools/build-with-ai.mdx b/docs/pt-BR/guides/coding-tools/build-with-ai.mdx index 744ad1bf47..bc697ea109 100644 --- a/docs/pt-BR/guides/coding-tools/build-with-ai.mdx +++ b/docs/pt-BR/guides/coding-tools/build-with-ai.mdx @@ -1,15 +1,15 @@ --- -title: "Build with AI" -description: "Everything AI coding agents need to build, deploy, and scale with CrewAI — skills, machine-readable docs, deployment, and enterprise features." +title: "Construa com IA" +description: "Tudo o que agentes de codificação com IA precisam para criar, implantar e escalar com CrewAI — skills, documentação legível por máquina, implantação e recursos enterprise." icon: robot mode: "wide" --- -# Build with AI +# Construa com IA -CrewAI is AI-native. This page brings together everything an AI coding agent needs to build with CrewAI — whether you're Claude Code, Codex, Cursor, Gemini CLI, or any other assistant helping a developer ship crews and flows. +O CrewAI é nativo de IA. Esta página reúne o que um agente de codificação com IA precisa para construir com CrewAI — seja Claude Code, Codex, Cursor, Gemini CLI ou qualquer outro assistente que ajude um desenvolvedor a entregar crews e flows. -### Supported Coding Agents +### Agentes de codificação compatíveis @@ -20,128 +20,139 @@ CrewAI is AI-native. This page brings together everything an AI coding agent nee - This page is designed to be consumed by both humans and AI assistants. If you're a coding agent, start with **Skills** to get CrewAI context, then use **llms.txt** for full docs access. + Esta página serve para humanos e para assistentes de IA. Se você é um agente de codificação, comece por **Skills** para obter contexto do CrewAI e depois use **llms.txt** para acesso completo à documentação. --- -## 1. Skills — Teach Your Agent CrewAI +## 1. Skills — ensine CrewAI ao seu agente -**Skills** are instruction packs that give coding agents deep CrewAI knowledge — how to scaffold Flows, configure Crews, use tools, and follow framework conventions. +**Skills** são pacotes de instruções que dão aos agentes de codificação conhecimento profundo do CrewAI — como estruturar Flows, configurar Crews, usar ferramentas e seguir convenções do framework. Anthropic - CrewAI skills are available in the **Claude Code plugin marketplace** — the same distribution channel used by top AI-native companies: - ``` + As skills do CrewAI estão no **plugin marketplace do Claude Code** — o mesmo canal usado por empresas líderes em IA: + ```shell /plugin marketplace add crewAIInc/skills + /plugin install crewai-skills@crewai-plugins + /reload-plugins ``` + + Quatro skills são ativadas automaticamente quando você faz perguntas relevantes sobre CrewAI: + + | Skill | Quando é usada | + |-------|----------------| + | `getting-started` | Novos projetos, escolha entre `LLM.call()` / `Agent` / `Crew` / `Flow`, arquivos `crew.py` / `main.py` | + | `design-agent` | Configurar agentes — papel, objetivo, história, ferramentas, LLMs, memória, guardrails | + | `design-task` | Descrever tarefas, dependências, saída estruturada (`output_pydantic`, `output_json`), revisão humana | + | `ask-docs` | Consultar o [servidor MCP da documentação CrewAI](https://docs.crewai.com/mcp) em tempo real para detalhes de API | - - Works with Claude Code, Codex, Cursor, Gemini CLI, or any coding agent: + + Funciona com Claude Code, Codex, Cursor, Gemini CLI ou qualquer agente de codificação: ```shell npx skills add crewaiinc/skills ``` - Pulls from the [skills.sh registry](https://skills.sh/crewaiinc/skills). + Obtido do [registro skills.sh](https://skills.sh/crewaiinc/skills). - - Use either method above — the Claude Code plugin marketplace or `npx skills add`. Both install the official [crewAIInc/skills](https://github.com/crewAIInc/skills) pack. + + Use um dos métodos acima — o plugin marketplace do Claude Code ou `npx skills add`. Ambos instalam o pacote oficial [crewAIInc/skills](https://github.com/crewAIInc/skills). - - The skill pack teaches your agent: - - **Flows** — stateful apps, steps, and crew kickoffs - - **Crews & Agents** — YAML-first patterns, roles, tasks, delegation - - **Tools & Integrations** — search, APIs, MCP servers, and common CrewAI tools - - **Project layout** — CLI scaffolds and repo conventions - - **Up-to-date patterns** — tracks current CrewAI docs and best practices + + O pacote ensina ao seu agente: + - **Flows** — apps com estado, passos e disparo de crews + - **Crews e agentes** — padrões YAML-first, papéis, tarefas, delegação + - **Ferramentas e integrações** — busca, APIs, servidores MCP e ferramentas comuns do CrewAI + - **Estrutura do projeto** — scaffolds da CLI e convenções de repositório + - **Padrões atualizados** — alinhado à documentação e às melhores práticas atuais do CrewAI - - Your agent can now scaffold and build CrewAI projects without you re-explaining the framework each session. + + Seu agente pode estruturar e construir projetos CrewAI sem você precisar reexplicar o framework a cada sessão. - - How skills work in CrewAI agents — injection, activation, and patterns. + + Como skills funcionam em agentes CrewAI — injeção, ativação e padrões. - - Overview of the crewAIInc/skills pack and what it includes. + + Visão geral do pacote crewAIInc/skills e do que ele inclui. - - Set up AGENTS.md for Claude Code, Codex, Cursor, and Gemini CLI. + + Configure o AGENTS.md para Claude Code, Codex, Cursor e Gemini CLI. - - Official listing — skills, install stats, and audits. + + Listagem oficial — skills, estatísticas de instalação e auditorias. --- -## 2. llms.txt — Machine-Readable Docs +## 2. llms.txt — documentação legível por máquina -CrewAI publishes an `llms.txt` file that gives AI assistants direct access to the full documentation in a machine-readable format. +O CrewAI publica um arquivo `llms.txt` que dá aos assistentes de IA acesso direto à documentação completa em formato legível por máquinas. ``` https://docs.crewai.com/llms.txt ``` - - [`llms.txt`](https://llmstxt.org/) is an emerging standard for making documentation consumable by large language models. Instead of scraping HTML, your agent can fetch a single structured text file with all the content it needs. + + [`llms.txt`](https://llmstxt.org/) é um padrão emergente para tornar a documentação consumível por grandes modelos de linguagem. Em vez de fazer scraping de HTML, seu agente pode buscar um único arquivo de texto estruturado com o conteúdo necessário. - CrewAI's `llms.txt` is **already live** — your agent can use it right now. + O `llms.txt` do CrewAI **já está no ar** — seu agente pode usar agora. - - Point your coding agent at the URL when it needs CrewAI reference docs: + + Indique ao agente de codificação a URL quando precisar da referência do CrewAI: ``` Fetch https://docs.crewai.com/llms.txt for CrewAI documentation. ``` - Many coding agents (Claude Code, Cursor, etc.) can fetch URLs directly. The file contains structured documentation covering all CrewAI concepts, APIs, and guides. + Muitos agentes (Claude Code, Cursor etc.) conseguem buscar URLs diretamente. O arquivo contém documentação estruturada sobre conceitos, APIs e guias do CrewAI. - - - **No scraping required** — clean, structured content in one request - - **Always up-to-date** — served directly from docs.crewai.com - - **Optimized for LLMs** — formatted for context windows, not browsers - - **Complements skills** — skills teach patterns, llms.txt provides reference + + - **Sem scraping** — conteúdo limpo e estruturado em uma requisição + - **Sempre atualizado** — servido diretamente de docs.crewai.com + - **Otimizado para LLMs** — formatado para janelas de contexto, não para navegadores + - **Complementa as skills** — skills ensinam padrões; llms.txt fornece referência --- -## 3. Deploy to Enterprise +## 3. Implantação enterprise -Go from a local crew to production on **CrewAI AMP** (Agent Management Platform) in minutes. +Do crew local à produção no **CrewAI AMP** (Agent Management Platform) em minutos. - - Scaffold and test your crew or flow: + + Estruture e teste seu crew ou flow: ```bash crewai create crew my_crew cd my_crew crewai run ``` - - Ensure your project structure is ready: + + Garanta que a estrutura do projeto está pronta: ```bash crewai deploy --prepare ``` - See the [preparation guide](/en/enterprise/guides/prepare-for-deployment) for details on project structure and requirements. + Veja o [guia de preparação](/pt-BR/enterprise/guides/prepare-for-deployment) para detalhes de estrutura e requisitos. - - Push to the CrewAI AMP platform: + + Envie para a plataforma CrewAI AMP: ```bash crewai deploy ``` - You can also deploy via [GitHub integration](/en/enterprise/guides/deploy-to-amp) or [Crew Studio](/en/enterprise/guides/enable-crew-studio). + Também é possível implantar pela [integração com GitHub](/pt-BR/enterprise/guides/deploy-to-amp) ou pelo [Crew Studio](/pt-BR/enterprise/guides/enable-crew-studio). - - Your deployed crew gets a REST API endpoint. Integrate it into any application: + + O crew implantado recebe um endpoint REST. Integre em qualquer aplicação: ```bash curl -X POST https://app.crewai.com/api/v1/crews//kickoff \ -H "Authorization: Bearer $CREWAI_API_KEY" \ @@ -152,55 +163,55 @@ Go from a local crew to production on **CrewAI AMP** (Agent Management Platform) - - Full deployment guide — CLI, GitHub, and Crew Studio methods. + + Guia completo de implantação — CLI, GitHub e Crew Studio. - - Platform overview — what AMP provides for production crews. + + Visão da plataforma — o que o AMP oferece para crews em produção. --- -## 4. Enterprise Features +## 4. Recursos enterprise -CrewAI AMP is built for production teams. Here's what you get beyond deployment. +O CrewAI AMP foi feito para equipes em produção. Além da implantação, você obtém: - - Detailed execution traces, logs, and performance metrics for every crew run. Monitor agent decisions, tool calls, and task completion in real time. + + Traces de execução, logs e métricas de desempenho para cada execução de crew. Monitore decisões de agentes, chamadas de ferramentas e conclusão de tarefas em tempo real. - No-code/low-code interface to create, customize, and deploy crews visually — then export to code or deploy directly. + Interface no-code/low-code para criar, personalizar e implantar crews visualmente — exporte para código ou implante direto. - - Stream real-time events from crew executions to your systems. Integrate with Slack, Zapier, or any webhook consumer. + + Transmita eventos em tempo real das execuções para seus sistemas. Integre com Slack, Zapier ou qualquer consumidor de webhook. - - SSO, RBAC, and organization-level controls. Manage who can create, deploy, and access crews across your team. + + SSO, RBAC e controles em nível de organização. Gerencie quem pode criar, implantar e acessar crews. - - Publish and share custom tools across your organization. Install community tools from the registry. + + Publique e compartilhe ferramentas customizadas na organização. Instale ferramentas da comunidade a partir do registro. - - Run CrewAI AMP on your own infrastructure. Full platform capabilities with data residency and compliance controls. + + Execute o CrewAI AMP na sua infraestrutura. Capacidades completas da plataforma com residência de dados e controles de conformidade. - - AMP is for teams that need to move AI agent workflows from prototypes to production — with observability, access controls, and scalable infrastructure. Whether you're a startup or enterprise, AMP handles the operational complexity so you can focus on building agents. + + Para equipes que precisam levar fluxos de agentes de IA do protótipo à produção — com observabilidade, controles de acesso e infraestrutura escalável. De startups a grandes empresas, o AMP cuida da complexidade operacional para você focar nos agentes. - - - **Cloud (app.crewai.com)** — managed by CrewAI, fastest path to production - - **Factory (self-hosted)** — run on your own infrastructure for full data control - - **Hybrid** — mix cloud and self-hosted based on sensitivity requirements + + - **Nuvem (app.crewai.com)** — gerenciada pela CrewAI, caminho mais rápido para produção + - **Factory (self-hosted)** — na sua infraestrutura para controle total dos dados + - **Híbrido** — combine nuvem e self-hosted conforme a sensibilidade dos dados - - Sign up at [app.crewai.com](https://app.crewai.com) to see current plans. Enterprise and Factory pricing is available on request. + + Cadastre-se em [app.crewai.com](https://app.crewai.com) para ver os planos atuais. Preços enterprise e Factory sob consulta. - - Sign up and deploy your first crew to production. + + Cadastre-se e leve seu primeiro crew à produção. From 6d153284d4de4d3c4a5f458a91e36761e2074190 Mon Sep 17 00:00:00 2001 From: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com> Date: Tue, 21 Apr 2026 10:12:24 -0700 Subject: [PATCH 4/6] =?UTF-8?q?fix:=20merge=20execution=20metadata=20on=20?= =?UTF-8?q?duplicate=20batch=20initialization=20in=20Tr=E2=80=A6=20(#5573)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * fix: merge execution metadata on duplicate batch initialization in TraceBatchManager - Updated TraceBatchManager to merge execution metadata when a batch is initialized multiple times. - Enhanced logging to reflect the merging of metadata during duplicate initialization. - Added a test case to verify that execution metadata is correctly merged when initializing a batch after a lazy action. * drop env events emitting from traces listener --- .../listeners/tracing/trace_batch_manager.py | 5 ++- .../listeners/tracing/trace_listener.py | 30 +------------- lib/crewai/src/crewai/flow/flow.py | 7 +++- lib/crewai/tests/tracing/test_tracing.py | 40 +++++++++++++++++++ 4 files changed, 52 insertions(+), 30 deletions(-) diff --git a/lib/crewai/src/crewai/events/listeners/tracing/trace_batch_manager.py b/lib/crewai/src/crewai/events/listeners/tracing/trace_batch_manager.py index d2a0912f60..e35fe66e1e 100644 --- a/lib/crewai/src/crewai/events/listeners/tracing/trace_batch_manager.py +++ b/lib/crewai/src/crewai/events/listeners/tracing/trace_batch_manager.py @@ -81,8 +81,11 @@ def initialize_batch( """Initialize a new trace batch (thread-safe)""" with self._batch_ready_cv: if self.current_batch is not None: + # Lazy init (e.g. DefaultEnvEvent) may have created the batch without + # execution_type; merge metadata from a later flow/crew initializer. + self.current_batch.execution_metadata.update(execution_metadata) logger.debug( - "Batch already initialized, skipping duplicate initialization" + "Batch already initialized, merged execution metadata and skipped duplicate initialization" ) return self.current_batch diff --git a/lib/crewai/src/crewai/events/listeners/tracing/trace_listener.py b/lib/crewai/src/crewai/events/listeners/tracing/trace_listener.py index c4cc6cb71b..046bc0f1a8 100644 --- a/lib/crewai/src/crewai/events/listeners/tracing/trace_listener.py +++ b/lib/crewai/src/crewai/events/listeners/tracing/trace_listener.py @@ -60,12 +60,6 @@ CrewKickoffFailedEvent, CrewKickoffStartedEvent, ) -from crewai.events.types.env_events import ( - CCEnvEvent, - CodexEnvEvent, - CursorEnvEvent, - DefaultEnvEvent, -) from crewai.events.types.flow_events import ( FlowCreatedEvent, FlowFinishedEvent, @@ -212,7 +206,6 @@ def setup_listeners(self, crewai_event_bus: CrewAIEventsBus) -> None: self._listeners_setup = True return - self._register_env_event_handlers(crewai_event_bus) self._register_flow_event_handlers(crewai_event_bus) self._register_context_event_handlers(crewai_event_bus) self._register_action_event_handlers(crewai_event_bus) @@ -221,25 +214,6 @@ def setup_listeners(self, crewai_event_bus: CrewAIEventsBus) -> None: self._listeners_setup = True - def _register_env_event_handlers(self, event_bus: CrewAIEventsBus) -> None: - """Register handlers for environment context events.""" - - @event_bus.on(CCEnvEvent) - def on_cc_env(source: Any, event: CCEnvEvent) -> None: - self._handle_action_event("cc_env", source, event) - - @event_bus.on(CodexEnvEvent) - def on_codex_env(source: Any, event: CodexEnvEvent) -> None: - self._handle_action_event("codex_env", source, event) - - @event_bus.on(CursorEnvEvent) - def on_cursor_env(source: Any, event: CursorEnvEvent) -> None: - self._handle_action_event("cursor_env", source, event) - - @event_bus.on(DefaultEnvEvent) - def on_default_env(source: Any, event: DefaultEnvEvent) -> None: - self._handle_action_event("default_env", source, event) - def _register_flow_event_handlers(self, event_bus: CrewAIEventsBus) -> None: """Register handlers for flow events.""" @@ -286,8 +260,8 @@ def on_crew_started(source: Any, event: CrewKickoffStartedEvent) -> None: if self.batch_manager.batch_owner_type != "flow": # Always call _initialize_crew_batch to claim ownership. # If batch was already initialized by a concurrent action event - # (race condition with DefaultEnvEvent), initialize_batch() returns - # early but batch_owner_type is still correctly set to "crew". + # (e.g. LLM/tool before crew_kickoff_started), initialize_batch() + # returns early but batch_owner_type is still correctly set to "crew". # Skip only when a parent flow already owns the batch. self._initialize_crew_batch(source, event) self._handle_trace_event("crew_kickoff_started", source, event) diff --git a/lib/crewai/src/crewai/flow/flow.py b/lib/crewai/src/crewai/flow/flow.py index 88457f7aad..b363ebc714 100644 --- a/lib/crewai/src/crewai/flow/flow.py +++ b/lib/crewai/src/crewai/flow/flow.py @@ -1503,6 +1503,8 @@ async def resume_async(self, feedback: str = "") -> Any: except Exception: logger.warning("FlowStartedEvent handler failed", exc_info=True) + get_env_context() + context = self._pending_feedback_context emit = context.emit default_outcome = context.default_outcome @@ -2004,7 +2006,6 @@ def kickoff( restored = apply_checkpoint(self, from_checkpoint) if restored is not None: return restored.kickoff(inputs=inputs, input_files=input_files) - get_env_context() if self.stream: result_holder: list[Any] = [] current_task_info: TaskInfo = { @@ -2206,6 +2207,10 @@ async def run_flow() -> None: f"Flow started with ID: {self.flow_id}", color="bold magenta" ) + # After FlowStarted (when not suppressed): env events must not pre-empt + # trace batch init with implicit "crew" execution_type. + get_env_context() + if inputs is not None and "id" not in inputs: self._initialize_state(inputs) diff --git a/lib/crewai/tests/tracing/test_tracing.py b/lib/crewai/tests/tracing/test_tracing.py index 640aca832f..38bb060bdf 100644 --- a/lib/crewai/tests/tracing/test_tracing.py +++ b/lib/crewai/tests/tracing/test_tracing.py @@ -1640,3 +1640,43 @@ def test_backend_initialized_false_on_failure(self): assert bm.backend_initialized is False assert bm.trace_batch_id is None + + +class TestTraceBatchManagerDuplicateInitMerge: + """Second initialize_batch call merges execution_metadata (flow after lazy action).""" + + def test_duplicate_initialize_merges_execution_metadata(self): + with ( + patch( + "crewai.events.listeners.tracing.trace_batch_manager.should_auto_collect_first_time_traces", + return_value=True, + ), + patch( + "crewai.events.listeners.tracing.trace_batch_manager.is_tracing_enabled_in_context", + return_value=True, + ), + ): + bm = TraceBatchManager() + bm.initialize_batch( + user_context={"privacy_level": "standard"}, + execution_metadata={ + "crew_name": "Unknown Crew", + "crewai_version": "9.9.9", + }, + ) + first_batch_id = bm.current_batch.batch_id + bm.initialize_batch( + user_context={"privacy_level": "standard"}, + execution_metadata={ + "flow_name": "ResearchFlow", + "execution_type": "flow", + "crewai_version": "9.9.9", + "execution_start": "2026-01-01T00:00:00+00:00", + }, + ) + + assert bm.current_batch.batch_id == first_batch_id + meta = bm.current_batch.execution_metadata + assert meta.get("execution_type") == "flow" + assert meta.get("flow_name") == "ResearchFlow" + assert meta.get("crew_name") == "Unknown Crew" From d4f9f875f7bcc9ee3e16d92e85465e1d5903bdd6 Mon Sep 17 00:00:00 2001 From: Greyson LaLonde Date: Wed, 22 Apr 2026 01:22:19 +0800 Subject: [PATCH 5/6] fix: bump python-dotenv to >=1.2.2 for GHSA-mf9w-mj56-hr94 --- lib/crewai/pyproject.toml | 2 +- lib/devtools/pyproject.toml | 2 +- uv.lock | 41 ++++++++++++++++++------------------- 3 files changed, 22 insertions(+), 23 deletions(-) diff --git a/lib/crewai/pyproject.toml b/lib/crewai/pyproject.toml index 4956c81f0c..5b3c81850c 100644 --- a/lib/crewai/pyproject.toml +++ b/lib/crewai/pyproject.toml @@ -24,7 +24,7 @@ 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Apr 2026 15:57:19 -0300 Subject: [PATCH 6/6] fix: propagate implicit @CrewBase names to crew events (#5574) * fix: propagate implicit @CrewBase names to crew events * test: appease static analysis for @CrewBase kickoff test --------- Co-authored-by: Greyson LaLonde --- lib/crewai/src/crewai/project/annotations.py | 2 + lib/crewai/tests/test_crew.py | 57 ++++++++++++++++++++ lib/crewai/tests/test_project.py | 51 +++++++++++++++++- 3 files changed, 109 insertions(+), 1 deletion(-) diff --git a/lib/crewai/src/crewai/project/annotations.py b/lib/crewai/src/crewai/project/annotations.py index c198c979a0..b4b4b69d38 100644 --- a/lib/crewai/src/crewai/project/annotations.py +++ b/lib/crewai/src/crewai/project/annotations.py @@ -237,6 +237,8 @@ def wrapper(self: CrewInstance, *args: Any, **kwargs: Any) -> Crew: self.tasks = instantiated_tasks crew_instance: Crew = _call_method(meth, self, *args, **kwargs) + if "name" not in crew_instance.model_fields_set: + crew_instance.name = getattr(self, "_crew_name", None) or crew_instance.name def callback_wrapper( hook: Callable[Concatenate[CrewInstance, P2], R2], instance: CrewInstance diff --git a/lib/crewai/tests/test_crew.py b/lib/crewai/tests/test_crew.py index 9db9ef4e2f..3d6fe4602e 100644 --- a/lib/crewai/tests/test_crew.py +++ b/lib/crewai/tests/test_crew.py @@ -8,6 +8,7 @@ from hashlib import md5 import re import sys +from typing import Any, cast from unittest.mock import ANY, MagicMock, call, patch from crewai.agent import Agent @@ -17,6 +18,7 @@ from crewai.crews.crew_output import CrewOutput from crewai.events.event_bus import crewai_event_bus from crewai.events.types.crew_events import ( + CrewKickoffStartedEvent, CrewTestCompletedEvent, CrewTestStartedEvent, CrewTrainCompletedEvent, @@ -4741,6 +4743,61 @@ def test_default_crew_name(researcher, writer): assert crew.name == "crew" +@pytest.mark.parametrize( + "explicit_name,expected", + [ + (None, "ResearchAutomation"), + ("My Research Automation", "My Research Automation"), + ], + ids=["class_name_from_decorator", "explicit_name_preserved"], +) +def test_crew_kickoff_started_emits_display_name( + researcher, writer, explicit_name, expected +): + """Kickoff events should use the decorator-provided display name when implicit.""" + from crewai.crews.utils import prepare_kickoff + from crewai.project import CrewBase, agent, crew, task + + @CrewBase + class ResearchAutomation: + agents_config = None + tasks_config = None + + @agent + def researcher(self): + return researcher + + @task + def first_task(self): + return Task( + description="Task 1", + expected_output="output", + agent=self.researcher(), + ) + + @crew + def crew(self): + crew_kwargs: dict[str, Any] = { + "agents": self.agents, + "tasks": self.tasks, + } + if explicit_name is not None: + crew_kwargs["name"] = explicit_name + return Crew(**crew_kwargs) + + captured: list[str | None] = [] + with crewai_event_bus.scoped_handlers(): + + @crewai_event_bus.on(CrewKickoffStartedEvent) + def _capture(_source: Any, event: CrewKickoffStartedEvent) -> None: + captured.append(event.crew_name) + + automation_cls = cast(type[Any], ResearchAutomation) + prepare_kickoff(cast(Any, automation_cls()).crew(), inputs=None) + + assert captured == [expected] + + @pytest.mark.vcr() def test_memory_remember_receives_task_content(): """With memory=True, extract_memories receives raw content with task, agent, expected output, and result.""" diff --git a/lib/crewai/tests/test_project.py b/lib/crewai/tests/test_project.py index 9d7f332da4..368afe7fd6 100644 --- a/lib/crewai/tests/test_project.py +++ b/lib/crewai/tests/test_project.py @@ -1,4 +1,4 @@ -from typing import Any, ClassVar +from typing import Any, ClassVar, cast from unittest.mock import Mock, create_autospec, patch import pytest @@ -261,6 +261,55 @@ def test_crew_name(): assert crew._crew_name == "InternalCrew" +def test_crew_decorator_propagates_class_name_to_instance(): + """@crew-decorated factory method should set Crew.name to the decorated class name.""" + sample_agent = Agent(role="r", goal="g", backstory="b") + sample_task = Task(description="d", expected_output="o", agent=sample_agent) + + @CrewBase + class ImplicitNameCrewFactory: + agents_config = None + tasks_config = None + agents: list[BaseAgent] = [sample_agent] + tasks: list[Task] = [sample_task] + + @crew + def crew(self): + return Crew( + agents=[sample_agent], + tasks=[sample_task], + ) + + factory_cls = cast(type[Any], ImplicitNameCrewFactory) + crew_instance: Crew = cast(Any, factory_cls()).crew() + assert crew_instance.name == "ImplicitNameCrewFactory" + + +def test_crew_decorator_preserves_explicit_name(): + """Explicit Crew(name=...) inside @crew should win over the @CrewBase class name.""" + sample_agent = Agent(role="r", goal="g", backstory="b") + sample_task = Task(description="d", expected_output="o", agent=sample_agent) + + @CrewBase + class NamedCrewFactory: + agents_config = None + tasks_config = None + agents: list[BaseAgent] = [sample_agent] + tasks: list[Task] = [sample_task] + + @crew + def crew(self): + return Crew( + name="My Explicit Name", + agents=[sample_agent], + tasks=[sample_task], + ) + + factory_cls = cast(type[Any], NamedCrewFactory) + crew_instance: Crew = cast(Any, factory_cls()).crew() + assert crew_instance.name == "My Explicit Name" + + @tool def simple_tool(): """Return 'Hi!'"""