docs: add file upload to kickoff guide, clarify flow state population, all languages

- Added new "File Uploads" section to kickoff-crew.mdx with multipart,
  JSON URL, and separate upload + kickoff examples
- Clarified that file-typed fields in flow state schema signal the
  Platform UI to render file dropzones
- Updated flows.mdx File Inputs section to show state population pattern
- Updated files.mdx With Flows section with state schema example
- Applied all changes to en, ar, ko, pt-BR translations

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

.github/workflows/import-time.yml

@@ -0,0 +1,103 @@
+name: Import Time Guard
+
+on:
+  pull_request:
+    paths:
+      - "lib/crewai/src/**"
+      - "lib/crewai/pyproject.toml"
+      - "pyproject.toml"
+
+permissions:
+  contents: read
+
+jobs:
+  import-time:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ["3.12"]
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - uses: astral-sh/setup-uv@v6
+        with:
+          version: "0.11.3"
+          enable-cache: true
+
+      - name: Install the project
+        run: uv sync --all-extras --no-dev
+        env:
+          UV_PYTHON: ${{ matrix.python-version }}
+
+      - name: Benchmark PR branch
+        id: pr
+        run: |
+          result=$(uv run python scripts/benchmark_import_time.py --runs 5 --json)
+          echo "result=$result" >> "$GITHUB_OUTPUT"
+          echo "pr_median=$(echo $result | python3 -c 'import sys,json; print(json.load(sys.stdin)["median_s"])')" >> "$GITHUB_OUTPUT"
+          echo "### PR Branch Import Time" >> "$GITHUB_STEP_SUMMARY"
+          echo "$result" | python3 -c "
+          import sys, json
+          d = json.load(sys.stdin)
+          print(f'- Median: {d[\"median_s\"]}s')
+          print(f'- Mean: {d[\"mean_s\"]}s ± {d[\"stdev_s\"]}s')
+          print(f'- Range: {d[\"min_s\"]}s – {d[\"max_s\"]}s')
+          " >> "$GITHUB_STEP_SUMMARY"
+        env:
+          UV_PYTHON: ${{ matrix.python-version }}
+
+      - name: Checkout base branch
+        run: git checkout ${{ github.event.pull_request.base.sha }}
+
+      - name: Install base branch
+        run: uv sync --all-extras --no-dev
+        env:
+          UV_PYTHON: ${{ matrix.python-version }}
+
+      - name: Benchmark base branch
+        id: base
+        run: |
+          result=$(uv run python scripts/benchmark_import_time.py --runs 5 --json 2>/dev/null || echo '{"median_s": 0}')
+          echo "result=$result" >> "$GITHUB_OUTPUT"
+          echo "base_median=$(echo $result | python3 -c 'import sys,json; print(json.load(sys.stdin)["median_s"])')" >> "$GITHUB_OUTPUT"
+          echo "### Base Branch Import Time" >> "$GITHUB_STEP_SUMMARY"
+          echo "$result" | python3 -c "
+          import sys, json
+          d = json.load(sys.stdin)
+          if d.get('median_s', 0) > 0:
+              print(f'- Median: {d[\"median_s\"]}s')
+          else:
+              print('- Benchmark script not present on base branch (skip comparison)')
+          " >> "$GITHUB_STEP_SUMMARY"
+        env:
+          UV_PYTHON: ${{ matrix.python-version }}
+
+      - name: Compare and gate
+        run: |
+          pr_median=${{ steps.pr.outputs.pr_median }}
+          base_median=${{ steps.base.outputs.base_median }}
+
+          python3 -c "
+          pr = float('$pr_median')
+          base = float('$base_median')
+
+          if base <= 0:
+              print('⏭️  No base benchmark available — skipping comparison.')
+              exit(0)
+
+          change_pct = ((pr - base) / base) * 100
+          print(f'Base: {base:.3f}s')
+          print(f'PR:   {pr:.3f}s')
+          print(f'Change: {change_pct:+.1f}%')
+          print()
+
+          if change_pct > 5:
+              print(f'❌ BLOCKED: Import time regressed by {change_pct:.1f}% (threshold: 5%)')
+              exit(1)
+          elif change_pct > 0:
+              print(f'⚠️  Slight regression ({change_pct:.1f}%) but within 5% threshold.')
+          else:
+              print(f'✅ Import time improved by {abs(change_pct):.1f}%')
+          "

.gitignore

@@ -30,3 +30,4 @@ chromadb-*.lock
 .crewai/memory
 blogs/*
 secrets/*
+UNKNOWN.egg-info/

README.md

@@ -83,6 +83,7 @@ intelligent automations.
 
 ## Table of contents
 
+- [Build with AI](#build-with-ai)
 - [Why CrewAI?](#why-crewai)
 - [Getting Started](#getting-started)
 - [Key Features](#key-features)
@@ -101,6 +102,32 @@ intelligent automations.
 - [Telemetry](#telemetry)
 - [License](#license)
 
+## Build with AI
+
+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
+npx skills add crewaiinc/skills
+```
+
+This installs the official [CrewAI Skills](https://github.com/crewAIInc/skills) — structured instructions that teach coding agents how to scaffold Flows, configure Crews, design agents and tasks, and follow CrewAI patterns.
+
 ## Why CrewAI?
 
 <div align="center" style="margin-bottom: 30px;">

crewai/tools/linear_tool.py

@@ -1,124 +0,0 @@
-import os
-from enum import Enum
-from typing import Any, Type
-
-import httpx
-from crewai.tools import BaseTool
-from pydantic import BaseModel, Field
-
-LINEAR_API_URL = "https://api.linear.app/graphql"
-
-
-class LinearAction(str, Enum):
-    MY_ISSUES = "my_issues"
-    LIST_TEAMS = "list_teams"
-    LIST_PROJECTS = "list_projects"
-
-
-class LinearToolInput(BaseModel):
-    action: LinearAction = Field(
-        description=(
-            "Action to perform: "
-            "'my_issues' — fetch issues assigned to the authenticated user; "
-            "'list_teams' — list all teams in the workspace; "
-            "'list_projects' — list all projects in the workspace."
-        )
-    )
-    first: int = Field(
-        default=25,
-        ge=1,
-        le=250,
-        description="Maximum number of records to return (1–250).",
-    )
-
-
-_QUERIES: dict[LinearAction, str] = {
-    LinearAction.MY_ISSUES: """
-        query MyIssues($first: Int!) {
-          viewer {
-            assignedIssues(first: $first, orderBy: updatedAt) {
-              nodes {
-                id
-                identifier
-                title
-                state { name }
-                priority
-                url
-                updatedAt
-              }
-            }
-          }
-        }
-    """,
-    LinearAction.LIST_TEAMS: """
-        query ListTeams($first: Int!) {
-          teams(first: $first) {
-            nodes {
-              id
-              name
-              key
-              description
-            }
-          }
-        }
-    """,
-    LinearAction.LIST_PROJECTS: """
-        query ListProjects($first: Int!) {
-          projects(first: $first, orderBy: updatedAt) {
-            nodes {
-              id
-              name
-              description
-              state
-              url
-              updatedAt
-            }
-          }
-        }
-    """,
-}
-
-
-def _extract(action: LinearAction, data: dict) -> list[dict]:
-    if action == LinearAction.MY_ISSUES:
-        return data["viewer"]["assignedIssues"]["nodes"]
-    if action == LinearAction.LIST_TEAMS:
-        return data["teams"]["nodes"]
-    if action == LinearAction.LIST_PROJECTS:
-        return data["projects"]["nodes"]
-    return []
-
-
-class LinearTool(BaseTool):
-    name: str = "Linear API Tool"
-    description: str = (
-        "Interact with the Linear project management API. "
-        "Supports fetching your assigned issues, listing teams, and listing projects."
-    )
-    args_schema: Type[BaseModel] = LinearToolInput
-
-    def _run(self, action: LinearAction, first: int = 25) -> Any:
-        api_key = os.environ.get("LINEAR_API_KEY", "")
-        if not api_key:
-            raise EnvironmentError("LINEAR_API_KEY environment variable is not set.")
-
-        query = _QUERIES[action]
-        payload = {"query": query, "variables": {"first": first}}
-        headers = {
-            "Authorization": api_key,
-            "Content-Type": "application/json",
-        }
-
-        response = httpx.post(
-            LINEAR_API_URL,
-            json=payload,
-            headers=headers,
-            timeout=15,
-        )
-        response.raise_for_status()
-
-        body = response.json()
-        if "errors" in body:
-            raise RuntimeError(f"Linear API errors: {body['errors']}")
-
-        return _extract(action, body["data"])

docs/ar/changelog.mdx

@@ -4,6 +4,36 @@ description: "تحديثات المنتج والتحسينات وإصلاحات
 icon: "clock"
 mode: "wide"
 ---
+<Update label="22 أبريل 2026">
+  ## v1.14.3a2
+
+  [عرض الإصدار على GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.3a2)
+
+  ## ما الذي تغير
+
+  ### الميزات
+  - إضافة دعم لـ bedrock V4
+  - إضافة أدوات Daytona sandbox لوظائف محسّنة
+  - إضافة صفحة "البناء باستخدام الذكاء الاصطناعي" — مستندات أصلية للذكاء الاصطناعي لوكلاء البرمجة
+  - إضافة "البناء باستخدام الذكاء الاصطناعي" إلى التنقل في صفحة "البدء" وملفات الصفحات لجميع اللغات (en, ko, pt-BR, ar)
+
+  ### إصلاحات الأخطاء
+  - إصلاح انتشار أسماء @CrewBase الضمنية إلى أحداث الطاقم
+  - حل مشكلة تكرار تهيئة الدفعات في دمج بيانات التنفيذ الوصفية
+  - إصلاح تسلسل حقول مرجع فئة Task لعمليات التحقق من النقاط
+  - التعامل مع نتيجة BaseModel في حلقة إعادة المحاولة للحدود
+  - تحديث python-dotenv إلى الإصدار >=1.2.2 للامتثال الأمني
+
+  ### الوثائق
+  - تحديث سجل التغييرات والإصدار لـ v1.14.3a1
+  - تحديث الأوصاف وتطبيق الترجمات الفعلية
+
+  ## المساهمون
+
+  @MatthiasHowellYopp, @github-actions[bot], @greysonlalonde, @iris-clawd, @lorenzejay, @renatonitta
+
+</Update>
+
 <Update label="21 أبريل 2026">
   ## v1.14.3a1
 

docs/ar/concepts/files.mdx

@@ -117,23 +117,35 @@ task = Task(
 
 ### مع التدفقات
 
-مرر الملفات إلى التدفقات، والتي تنتقل تلقائيًا إلى الأطقم:
+تعمل الحقول من نوع الملف (`File`، `ImageFile`، `PDFFile`) في مخطط حالة التدفق كإشارة لواجهة المنصة. عند النشر، تُعرض هذه الحقول كمناطق سحب وإفلات لرفع الملفات. يمكن أيضًا تمرير الملفات عبر `input_files` في API.
 
 ```python
 from crewai.flow.flow import Flow, start
-from crewai_files import ImageFile
+from crewai_files import File, ImageFile
+from pydantic import BaseModel
 
-class AnalysisFlow(Flow):
+class MyState(BaseModel):
+    document: File           # Renders as file dropzone in Platform UI
+    cover_image: ImageFile   # Image-specific dropzone
+    title: str = ""
+
+class AnalysisFlow(Flow[MyState]):
     @start()
     def analyze(self):
+        # Files are automatically populated in state
+        content = self.state.document.read()
         return self.analysis_crew.kickoff()
 
 flow = AnalysisFlow()
 result = flow.kickoff(
-    input_files={"image": ImageFile(source="data.png")}
+    input_files={"document": File(source="report.pdf")}
 )
 ```
 
+<Note type="info" title="تكامل منصة CrewAI">
+عند النشر على منصة CrewAI، تحصل الحقول من نوع الملف مثل `ImageFile` و `PDFFile` وغيرها في حالة التدفق تلقائيًا على واجهة رفع ملفات. يمكن للمستخدمين سحب وإفلات الملفات مباشرة في واجهة المنصة. يتم تخزين الملفات بشكل آمن وتمريرها إلى الوكلاء باستخدام تحسينات خاصة بالمزود (base64 مضمّن، أو واجهات برمجة لرفع الملفات، أو مراجع URL حسب المزود). للاطلاع على أمثلة استخدام API، راجع [مدخلات الملفات في التدفقات](/ar/concepts/flows#مدخلات-الملفات).
+</Note>
+
 ### مع الوكلاء المستقلين
 
 مرر الملفات مباشرة إلى تشغيل الوكيل:

docs/ar/concepts/flows.mdx

@@ -341,6 +341,90 @@ flow.kickoff()
 
 من خلال توفير خيارات إدارة الحالة غير المهيكلة والمهيكلة، تمكّن تدفقات CrewAI المطورين من بناء سير عمل ذكاء اصطناعي مرن ومتين في آن واحد، ملبيةً مجموعة واسعة من متطلبات التطبيقات.
 
+### مدخلات الملفات
+
+عند استخدام الحالة المهيكلة، يمكنك تضمين حقول من نوع الملف باستخدام فئات من `crewai-files`. تعمل الحقول من نوع الملف في حالة التدفق كإشارة للمنصة — فهي تُعرض تلقائيًا كمناطق سحب وإفلات لرفع الملفات في واجهة علامة تبويب Run ويتم تعبئتها عند رفع الملفات عبر المنصة أو تمريرها عبر `input_files` في API.
+
+```python
+from crewai.flow.flow import Flow, start
+from crewai_files import File, ImageFile, PDFFile
+from pydantic import BaseModel
+
+class MyState(BaseModel):
+    document: File           # Renders as file dropzone in Platform
+    title: str = ""
+
+class MyFlow(Flow[MyState]):
+    @start()
+    def process(self):
+        # File object is automatically populated in state
+        # when uploaded via Platform UI or passed via API
+        content = self.state.document.read()
+        print(f"Processing {self.state.title}: {len(content)} bytes")
+        return content
+```
+
+عند النشر على **منصة CrewAI**، تُعرض الحقول من نوع الملف (`File`، `ImageFile`، `PDFFile` من `crewai-files`) تلقائيًا كمناطق سحب وإفلات لرفع الملفات في واجهة المستخدم. يمكن للمستخدمين سحب وإفلات الملفات، والتي تُملأ بعد ذلك في حالة التدفق الخاص بك.
+
+**بدء التشغيل مع الملفات عبر API:**
+
+تكتشف نقطة النهاية `/kickoff` تنسيق الطلب تلقائيًا:
+- **جسم JSON** ← بدء تشغيل عادي
+- **multipart/form-data** ← رفع ملف + بدء تشغيل
+
+يمكن لمستخدمي API أيضًا تمرير سلاسل URL مباشرة إلى الحقول من نوع الملف — يقوم Pydantic بتحويلها تلقائيًا.
+
+### استخدام API
+
+#### الخيار 1: بدء تشغيل multipart (موصى به)
+
+أرسل الملفات مباشرة مع طلب بدء التشغيل:
+
+```bash
+# With files (multipart) — same endpoint
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -F 'inputs={"company_name": "Einstein"}' \
+  -F 'cover_image=@/path/to/photo.jpg'
+```
+
+يتم تخزين الملفات تلقائيًا وتحويلها إلى كائنات `FileInput`. يتلقى الوكيل الملف مع تحسين خاص بالمزود (base64 مضمّن، أو API لرفع الملفات، أو مرجع URL حسب مزود LLM).
+
+#### الخيار 2: بدء تشغيل JSON (بدون ملفات)
+
+```bash
+# Without files (JSON) — same endpoint
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -H 'Content-Type: application/json' \
+  -d '{"inputs": {"company_name": "Einstein"}}'
+```
+
+#### الخيار 3: رفع منفصل + بدء تشغيل
+
+هذا بديل لرفع multipart عندما تحتاج إلى رفع الملفات بشكل منفصل عن طلب بدء التشغيل. ارفع الملفات أولاً، ثم أشِر إليها بواسطة URL:
+
+```bash
+# Step 1: Upload
+curl -X POST https://your-deployment.crewai.com/files \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -F 'file=@/path/to/photo.jpg' \
+  -F 'field_name=cover_image'
+# Returns: {"url": "https://...", "field_name": "cover_image"}
+
+# Step 2: Kickoff with URL
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -H 'Content-Type: application/json' \
+  -d '{"inputs": {"company_name": "Einstein"}, "input_files": {"cover_image": "https://..."}}'
+```
+
+راجع وثائق Platform API للحصول على تفاصيل كاملة حول نقطة النهاية `/files`.
+
+#### على منصة CrewAI
+
+عند استخدام واجهة المنصة، تُعرض الحقول من نوع الملف تلقائيًا كمناطق سحب وإفلات للرفع. لا حاجة لاستدعاءات API — فقط أفلِت الملف وانقر على تشغيل.
+
 ## استمرارية التدفق
 
 يتيح مزخرف @persist الاستمرارية التلقائية للحالة في تدفقات CrewAI، مما يسمح لك بالحفاظ على حالة التدفق عبر عمليات إعادة التشغيل أو تنفيذات سير العمل المختلفة. يمكن تطبيق هذا المزخرف على مستوى الفئة أو مستوى الدالة، مما يوفر مرونة في كيفية إدارة استمرارية الحالة.

docs/ar/enterprise/guides/kickoff-crew.mdx

@@ -86,6 +86,60 @@ curl -H "Authorization: Bearer YOUR_CREW_TOKEN" https://your-crew-url.crewai.com
 
 رمز الحامل متاح في علامة تبويب Status في صفحة تفاصيل طاقمك.
 
+## رفع الملفات
+
+عندما يتضمن طاقمك أو تدفقك حقول حالة من نوع الملف (باستخدام `ImageFile` أو `PDFFile` أو `File` من `crewai-files`)، تُعرض هذه الحقول تلقائيًا كمناطق سحب وإفلات لرفع الملفات في واجهة علامة تبويب Run. يمكن للمستخدمين سحب وإفلات الملفات مباشرة، وتتولى المنصة التخزين والتسليم إلى وكلائك.
+
+### بدء تشغيل Multipart (موصى به)
+
+أرسل الملفات مباشرة مع طلب بدء التشغيل باستخدام `multipart/form-data`:
+
+```bash
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -F 'inputs={"title": "Report"}' \
+  -F 'document=@/path/to/file.pdf'
+```
+
+يتم تخزين الملفات تلقائيًا وتحويلها إلى كائنات ملفات. يتلقى الوكيل الملف مع تحسين خاص بالمزود (base64 مضمّن، أو API لرفع الملفات، أو مرجع URL حسب مزود LLM).
+
+### بدء تشغيل JSON مع عناوين URL للملفات
+
+إذا كانت لديك ملفات مستضافة بالفعل على عناوين URL، مررها عبر `input_files`:
+
+```bash
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -H 'Content-Type: application/json' \
+  -d '{
+    "inputs": {"title": "Report"},
+    "input_files": {"document": "https://example.com/file.pdf"}
+  }'
+```
+
+### رفع منفصل + بدء تشغيل
+
+ارفع الملفات أولاً، ثم أشِر إليها بواسطة URL:
+
+```bash
+# Step 1: Upload
+curl -X POST https://your-deployment.crewai.com/files \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -F 'file=@/path/to/file.pdf' \
+  -F 'field_name=document'
+# Returns: {"url": "https://...", "field_name": "document"}
+
+# Step 2: Kickoff with URL
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -H 'Content-Type: application/json' \
+  -d '{"inputs": {"title": "Report"}, "input_files": {"document": "https://..."}}'
+```
+
+<Note type="info">
+يعمل رفع الملفات بنفس الطريقة لكل من الطواقم والتدفقات. عرّف حقول من نوع الملف في مخطط حالتك، وستتولى واجهة المنصة وAPI الرفع تلقائيًا.
+</Note>
+
 ### التحقق من صحة الطاقم
 
 قبل تنفيذ العمليات، يمكنك التحقق من أن طاقمك يعمل بشكل صحيح:

docs/ar/guides/coding-tools/build-with-ai.mdx

@@ -0,0 +1,214 @@
+---
+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"
+---
+
+# البناء باستخدام الذكاء الاصطناعي
+
+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.
+
+### وكلاء البرمجة المدعومون
+
+<CardGroup cols={5}>
+  <Card title="Claude Code" icon="message-bot" color="#D97706" />
+  <Card title="Cursor" icon="arrow-pointer" color="#3B82F6" />
+  <Card title="Codex" icon="terminal" color="#10B981" />
+  <Card title="Windsurf" icon="wind" color="#06B6D4" />
+  <Card title="Gemini CLI" icon="sparkles" color="#8B5CF6" />
+</CardGroup>
+
+<Note>
+  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.
+</Note>
+
+---
+
+## 1. Skills — علِّم وكيلك CrewAI
+
+**Skills** حزم تعليمات تمنح وكلاء البرمجة معرفة عميقة بـ CrewAI — كيفية إنشاء هيكل Flows، وضبط Crews، استخدام الأدوات، واتباع اتفاقيات الإطار.
+
+<Tabs>
+  <Tab title="Claude Code (سوق الإضافات)">
+    <img src="https://cdn.simpleicons.org/anthropic/D97706" alt="Anthropic" width="28" style={{display: "inline", verticalAlign: "middle", marginRight: "8px"}} />
+    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 |
+  </Tab>
+  <Tab title="npx (أي وكيل)">
+    يعمل مع Claude Code أو Codex أو Cursor أو Gemini CLI أو أي وكيل برمجة:
+    ```shell
+    npx skills add crewaiinc/skills
+    ```
+    يُجلب من [سجل skills.sh](https://skills.sh/crewaiinc/skills).
+  </Tab>
+</Tabs>
+
+<Steps>
+  <Step title="ثبِّت حزمة المهارات الرسمية">
+    استخدم إحدى الطريقتين أعلاه — سوق إضافات Claude Code أو `npx skills add`. كلاهما يثبّت الحزمة الرسمية [crewAIInc/skills](https://github.com/crewAIInc/skills).
+  </Step>
+  <Step title="يحصل وكيلك فوراً على خبرة CrewAI">
+    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
+  </Step>
+  <Step title="ابدأ البناء">
+    يمكن لوكيلك الآن إنشاء هيكل وبناء مشاريع CrewAI دون أن تعيد شرح الإطار في كل جلسة.
+  </Step>
+</Steps>
+
+<CardGroup cols={2}>
+  <Card title="مفهوم Skills" icon="bolt" href="/ar/concepts/skills">
+    كيف تعمل المهارات في وكلاء CrewAI — الحقن، التفعيل، والأنماط.
+  </Card>
+  <Card title="صفحة Skills" icon="wand-magic-sparkles" href="/ar/skills">
+    نظرة على حزمة crewAIInc/skills وما تتضمنه.
+  </Card>
+  <Card title="AGENTS.md والأدوات" icon="terminal" href="/ar/guides/coding-tools/agents-md">
+    إعداد AGENTS.md لـ Claude Code وCodex وCursor وGemini CLI.
+  </Card>
+  <Card title="سجل skills.sh" icon="globe" href="https://skills.sh/crewaiinc/skills">
+    القائمة الرسمية — المهارات، إحصاءات التثبيت، والتدقيق.
+  </Card>
+</CardGroup>
+
+---
+
+## 2. llms.txt — وثائق مقروءة آلياً
+
+ينشر CrewAI ملف `llms.txt` يمنح المساعدين الذكيين وصولاً مباشراً إلى الوثائق الكاملة بصيغة مقروءة آلياً.
+
+```
+https://docs.crewai.com/llms.txt
+```
+
+<Tabs>
+  <Tab title="ما هو llms.txt؟">
+    [`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.
+
+    ملف `llms.txt` الخاص بـ CrewAI **متاح فعلياً** — يمكن لوكيلك استخدامه الآن.
+  </Tab>
+  <Tab title="كيفية الاستخدام">
+    وجِّه وكيل البرمجة إلى عنوان URL عندما يحتاج إلى مرجع CrewAI:
+
+    ```
+    Fetch https://docs.crewai.com/llms.txt for CrewAI documentation.
+    ```
+
+    يمكن للعديد من وكلاء البرمجة (Claude Code، Cursor، وغيرهما) جلب عناوين URL مباشرة. يحتوي الملف على وثائق منظمة تغطي مفاهيم CrewAI وواجهات البرمجة والأدلة.
+  </Tab>
+  <Tab title="لماذا يهم">
+    - **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
+  </Tab>
+</Tabs>
+
+---
+
+## 3. النشر للمؤسسات
+
+انتقل من crew محلي إلى الإنتاج على **CrewAI AMP** (منصة إدارة الوكلاء) في دقائق.
+
+<Steps>
+  <Step title="ابنِ محلياً">
+    أنشئ الهيكل واختبر crew أو flow:
+    ```bash
+    crewai create crew my_crew
+    cd my_crew
+    crewai run
+    ```
+  </Step>
+  <Step title="جهّز للنشر">
+    تأكد أن هيكل مشروعك جاهز:
+    ```bash
+    crewai deploy --prepare
+    ```
+    راجع [دليل التحضير](/ar/enterprise/guides/prepare-for-deployment) لتفاصيل الهيكل والمتطلبات.
+  </Step>
+  <Step title="انشر على AMP">
+    ادفع إلى منصة CrewAI AMP:
+    ```bash
+    crewai deploy
+    ```
+    يمكنك أيضاً النشر عبر [تكامل GitHub](/ar/enterprise/guides/deploy-to-amp) أو [Crew Studio](/ar/enterprise/guides/enable-crew-studio).
+  </Step>
+  <Step title="الوصول عبر API">
+    يحصل الـ crew المنشور على نقطة نهاية REST. دمجه في أي تطبيق:
+    ```bash
+    curl -X POST https://app.crewai.com/api/v1/crews/<crew-id>/kickoff \
+      -H "Authorization: Bearer $CREWAI_API_KEY" \
+      -H "Content-Type: application/json" \
+      -d '{"inputs": {"topic": "AI agents"}}'
+    ```
+  </Step>
+</Steps>
+
+<CardGroup cols={2}>
+  <Card title="النشر على AMP" icon="rocket" href="/ar/enterprise/guides/deploy-to-amp">
+    دليل النشر الكامل — CLI وGitHub وCrew Studio.
+  </Card>
+  <Card title="مقدمة عن AMP" icon="globe" href="/ar/enterprise/introduction">
+    نظرة على المنصة — ما يوفّره AMP لـ crews في الإنتاج.
+  </Card>
+</CardGroup>
+
+---
+
+## 4. ميزات المؤسسات
+
+CrewAI AMP مُصمَّم لفرق الإنتاج. إليك ما تحصل عليه بعد النشر.
+
+<CardGroup cols={2}>
+  <Card title="المراقبة والرصد" icon="chart-line">
+    مسارات تنفيذ مفصّلة، وسجلات، ومقاييس أداء لكل تشغيل crew. راقب قرارات الوكلاء، استدعاءات الأدوات، وإكمال المهام في الوقت الفعلي.
+  </Card>
+  <Card title="Crew Studio" icon="paintbrush">
+    واجهة منخفضة/بدون كود لإنشاء crews وتخصيصها ونشرها بصرياً — ثم التصدير إلى الشيفرة أو النشر مباشرة.
+  </Card>
+  <Card title="بث الويبهوك" icon="webhook">
+    بث أحداث فورية من تنفيذات الـ crews إلى أنظمتك. تكامل مع Slack أو Zapier أو أي مستهلك ويبهوك.
+  </Card>
+  <Card title="إدارة الفريق" icon="users">
+    SSO وRBAC وضوابط على مستوى المؤسسة. أدر من يمكنه إنشاء crews ونشرها والوصول إليها.
+  </Card>
+  <Card title="مستودع الأدوات" icon="toolbox">
+    انشر وشارك أدواتاً مخصصة عبر مؤسستك. ثبّت أدوات المجتمع من السجل.
+  </Card>
+  <Card title="Factory (استضافة ذاتية)" icon="server">
+    شغّل CrewAI AMP على بنيتك التحتية. قدرات المنصة كاملة مع ضوابط إقامة البيانات والامتثال.
+  </Card>
+</CardGroup>
+
+<AccordionGroup>
+  <Accordion title="لمن مخصص AMP؟">
+    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.
+  </Accordion>
+  <Accordion title="ما خيارات النشر المتاحة؟">
+    - **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
+  </Accordion>
+</AccordionGroup>
+
+<Card title="استكشف CrewAI AMP →" icon="arrow-right" href="https://app.crewai.com">
+  سجّل وانشر أول crew لك في الإنتاج.
+</Card>

docs/docs.json

@@ -79,6 +79,7 @@
                     "group": "Get Started",
                     "pages": [
                       "en/introduction",
+                      "en/guides/coding-tools/build-with-ai",
                       "en/skills",
                       "en/installation",
                       "en/quickstart"
@@ -127,7 +128,8 @@
                         "group": "Coding Tools",
                         "icon": "terminal",
                         "pages": [
-                          "en/guides/coding-tools/agents-md"
+                          "en/guides/coding-tools/agents-md",
+                          "en/guides/coding-tools/build-with-ai"
                         ]
                       },
                       {
@@ -553,6 +555,7 @@
                     "group": "Get Started",
                     "pages": [
                       "en/introduction",
+                      "en/guides/coding-tools/build-with-ai",
                       "en/skills",
                       "en/installation",
                       "en/quickstart"
@@ -601,7 +604,8 @@
                         "group": "Coding Tools",
                         "icon": "terminal",
                         "pages": [
-                          "en/guides/coding-tools/agents-md"
+                          "en/guides/coding-tools/agents-md",
+                          "en/guides/coding-tools/build-with-ai"
                         ]
                       },
                       {
@@ -1027,6 +1031,7 @@
                     "group": "Get Started",
                     "pages": [
                       "en/introduction",
+                      "en/guides/coding-tools/build-with-ai",
                       "en/skills",
                       "en/installation",
                       "en/quickstart"
@@ -1075,7 +1080,8 @@
                         "group": "Coding Tools",
                         "icon": "terminal",
                         "pages": [
-                          "en/guides/coding-tools/agents-md"
+                          "en/guides/coding-tools/agents-md",
+                          "en/guides/coding-tools/build-with-ai"
                         ]
                       },
                       {
@@ -1501,6 +1507,7 @@
                     "group": "Get Started",
                     "pages": [
                       "en/introduction",
+                      "en/guides/coding-tools/build-with-ai",
                       "en/skills",
                       "en/installation",
                       "en/quickstart"
@@ -1549,7 +1556,8 @@
                         "group": "Coding Tools",
                         "icon": "terminal",
                         "pages": [
-                          "en/guides/coding-tools/agents-md"
+                          "en/guides/coding-tools/agents-md",
+                          "en/guides/coding-tools/build-with-ai"
                         ]
                       },
                       {
@@ -1975,6 +1983,7 @@
                     "group": "Get Started",
                     "pages": [
                       "en/introduction",
+                      "en/guides/coding-tools/build-with-ai",
                       "en/skills",
                       "en/installation",
                       "en/quickstart"
@@ -2023,7 +2032,8 @@
                         "group": "Coding Tools",
                         "icon": "terminal",
                         "pages": [
-                          "en/guides/coding-tools/agents-md"
+                          "en/guides/coding-tools/agents-md",
+                          "en/guides/coding-tools/build-with-ai"
                         ]
                       },
                       {
@@ -2449,6 +2459,7 @@
                     "group": "Get Started",
                     "pages": [
                       "en/introduction",
+                      "en/guides/coding-tools/build-with-ai",
                       "en/skills",
                       "en/installation",
                       "en/quickstart"
@@ -2497,7 +2508,8 @@
                         "group": "Coding Tools",
                         "icon": "terminal",
                         "pages": [
-                          "en/guides/coding-tools/agents-md"
+                          "en/guides/coding-tools/agents-md",
+                          "en/guides/coding-tools/build-with-ai"
                         ]
                       },
                       {
@@ -2921,6 +2933,7 @@
                     "group": "Get Started",
                     "pages": [
                       "en/introduction",
+                      "en/guides/coding-tools/build-with-ai",
                       "en/skills",
                       "en/installation",
                       "en/quickstart"
@@ -2969,7 +2982,8 @@
                         "group": "Coding Tools",
                         "icon": "terminal",
                         "pages": [
-                          "en/guides/coding-tools/agents-md"
+                          "en/guides/coding-tools/agents-md",
+                          "en/guides/coding-tools/build-with-ai"
                         ]
                       },
                       {
@@ -3393,6 +3407,7 @@
                     "group": "Get Started",
                     "pages": [
                       "en/introduction",
+                      "en/guides/coding-tools/build-with-ai",
                       "en/skills",
                       "en/installation",
                       "en/quickstart"
@@ -3441,7 +3456,8 @@
                         "group": "Coding Tools",
                         "icon": "terminal",
                         "pages": [
-                          "en/guides/coding-tools/agents-md"
+                          "en/guides/coding-tools/agents-md",
+                          "en/guides/coding-tools/build-with-ai"
                         ]
                       },
                       {
@@ -3866,6 +3882,7 @@
                     "group": "Get Started",
                     "pages": [
                       "en/introduction",
+                      "en/guides/coding-tools/build-with-ai",
                       "en/skills",
                       "en/installation",
                       "en/quickstart"
@@ -3914,7 +3931,8 @@
                         "group": "Coding Tools",
                         "icon": "terminal",
                         "pages": [
-                          "en/guides/coding-tools/agents-md"
+                          "en/guides/coding-tools/agents-md",
+                          "en/guides/coding-tools/build-with-ai"
                         ]
                       },
                       {
@@ -4340,6 +4358,7 @@
                     "group": "Get Started",
                     "pages": [
                       "en/introduction",
+                      "en/guides/coding-tools/build-with-ai",
                       "en/skills",
                       "en/installation",
                       "en/quickstart"
@@ -4388,7 +4407,8 @@
                         "group": "Coding Tools",
                         "icon": "terminal",
                         "pages": [
-                          "en/guides/coding-tools/agents-md"
+                          "en/guides/coding-tools/agents-md",
+                          "en/guides/coding-tools/build-with-ai"
                         ]
                       },
                       {
@@ -4812,6 +4832,7 @@
                     "group": "Get Started",
                     "pages": [
                       "en/introduction",
+                      "en/guides/coding-tools/build-with-ai",
                       "en/skills",
                       "en/installation",
                       "en/quickstart"
@@ -4860,7 +4881,8 @@
                         "group": "Coding Tools",
                         "icon": "terminal",
                         "pages": [
-                          "en/guides/coding-tools/agents-md"
+                          "en/guides/coding-tools/agents-md",
+                          "en/guides/coding-tools/build-with-ai"
                         ]
                       },
                       {
@@ -5317,6 +5339,7 @@
                     "group": "Começando",
                     "pages": [
                       "pt-BR/introduction",
+                      "pt-BR/guides/coding-tools/build-with-ai",
                       "pt-BR/skills",
                       "pt-BR/installation",
                       "pt-BR/quickstart"
@@ -5775,6 +5798,7 @@
                     "group": "Começando",
                     "pages": [
                       "pt-BR/introduction",
+                      "pt-BR/guides/coding-tools/build-with-ai",
                       "pt-BR/skills",
                       "pt-BR/installation",
                       "pt-BR/quickstart"
@@ -6233,6 +6257,7 @@
                     "group": "Começando",
                     "pages": [
                       "pt-BR/introduction",
+                      "pt-BR/guides/coding-tools/build-with-ai",
                       "pt-BR/skills",
                       "pt-BR/installation",
                       "pt-BR/quickstart"
@@ -6691,6 +6716,7 @@
                     "group": "Começando",
                     "pages": [
                       "pt-BR/introduction",
+                      "pt-BR/guides/coding-tools/build-with-ai",
                       "pt-BR/skills",
                       "pt-BR/installation",
                       "pt-BR/quickstart"
@@ -7149,6 +7175,7 @@
                     "group": "Começando",
                     "pages": [
                       "pt-BR/introduction",
+                      "pt-BR/guides/coding-tools/build-with-ai",
                       "pt-BR/skills",
                       "pt-BR/installation",
                       "pt-BR/quickstart"
@@ -7607,6 +7634,7 @@
                     "group": "Começando",
                     "pages": [
                       "pt-BR/introduction",
+                      "pt-BR/guides/coding-tools/build-with-ai",
                       "pt-BR/skills",
                       "pt-BR/installation",
                       "pt-BR/quickstart"
@@ -8064,6 +8092,7 @@
                     "group": "Começando",
                     "pages": [
                       "pt-BR/introduction",
+                      "pt-BR/guides/coding-tools/build-with-ai",
                       "pt-BR/skills",
                       "pt-BR/installation",
                       "pt-BR/quickstart"
@@ -8521,6 +8550,7 @@
                     "group": "Começando",
                     "pages": [
                       "pt-BR/introduction",
+                      "pt-BR/guides/coding-tools/build-with-ai",
                       "pt-BR/skills",
                       "pt-BR/installation",
                       "pt-BR/quickstart"
@@ -8978,6 +9008,7 @@
                     "group": "Começando",
                     "pages": [
                       "pt-BR/introduction",
+                      "pt-BR/guides/coding-tools/build-with-ai",
                       "pt-BR/skills",
                       "pt-BR/installation",
                       "pt-BR/quickstart"
@@ -9434,6 +9465,7 @@
                     "group": "Começando",
                     "pages": [
                       "pt-BR/introduction",
+                      "pt-BR/guides/coding-tools/build-with-ai",
                       "pt-BR/skills",
                       "pt-BR/installation",
                       "pt-BR/quickstart"
@@ -9890,6 +9922,7 @@
                     "group": "Começando",
                     "pages": [
                       "pt-BR/introduction",
+                      "pt-BR/guides/coding-tools/build-with-ai",
                       "pt-BR/skills",
                       "pt-BR/installation",
                       "pt-BR/quickstart"
@@ -10377,6 +10410,7 @@
                     "group": "시작 안내",
                     "pages": [
                       "ko/introduction",
+                      "ko/guides/coding-tools/build-with-ai",
                       "ko/skills",
                       "ko/installation",
                       "ko/quickstart"
@@ -10847,6 +10881,7 @@
                     "group": "시작 안내",
                     "pages": [
                       "ko/introduction",
+                      "ko/guides/coding-tools/build-with-ai",
                       "ko/skills",
                       "ko/installation",
                       "ko/quickstart"
@@ -11317,6 +11352,7 @@
                     "group": "시작 안내",
                     "pages": [
                       "ko/introduction",
+                      "ko/guides/coding-tools/build-with-ai",
                       "ko/skills",
                       "ko/installation",
                       "ko/quickstart"
@@ -11787,6 +11823,7 @@
                     "group": "시작 안내",
                     "pages": [
                       "ko/introduction",
+                      "ko/guides/coding-tools/build-with-ai",
                       "ko/skills",
                       "ko/installation",
                       "ko/quickstart"
@@ -12257,6 +12294,7 @@
                     "group": "시작 안내",
                     "pages": [
                       "ko/introduction",
+                      "ko/guides/coding-tools/build-with-ai",
                       "ko/skills",
                       "ko/installation",
                       "ko/quickstart"
@@ -12727,6 +12765,7 @@
                     "group": "시작 안내",
                     "pages": [
                       "ko/introduction",
+                      "ko/guides/coding-tools/build-with-ai",
                       "ko/skills",
                       "ko/installation",
                       "ko/quickstart"
@@ -13196,6 +13235,7 @@
                     "group": "시작 안내",
                     "pages": [
                       "ko/introduction",
+                      "ko/guides/coding-tools/build-with-ai",
                       "ko/skills",
                       "ko/installation",
                       "ko/quickstart"
@@ -13665,6 +13705,7 @@
                     "group": "시작 안내",
                     "pages": [
                       "ko/introduction",
+                      "ko/guides/coding-tools/build-with-ai",
                       "ko/skills",
                       "ko/installation",
                       "ko/quickstart"
@@ -14134,6 +14175,7 @@
                     "group": "시작 안내",
                     "pages": [
                       "ko/introduction",
+                      "ko/guides/coding-tools/build-with-ai",
                       "ko/skills",
                       "ko/installation",
                       "ko/quickstart"
@@ -14602,6 +14644,7 @@
                     "group": "시작 안내",
                     "pages": [
                       "ko/introduction",
+                      "ko/guides/coding-tools/build-with-ai",
                       "ko/skills",
                       "ko/installation",
                       "ko/quickstart"
@@ -15070,6 +15113,7 @@
                     "group": "시작 안내",
                     "pages": [
                       "ko/introduction",
+                      "ko/guides/coding-tools/build-with-ai",
                       "ko/skills",
                       "ko/installation",
                       "ko/quickstart"
@@ -15569,6 +15613,7 @@
                     "group": "البدء",
                     "pages": [
                       "ar/introduction",
+                      "ar/guides/coding-tools/build-with-ai",
                       "ar/skills",
                       "ar/installation",
                       "ar/quickstart"
@@ -16039,6 +16084,7 @@
                     "group": "البدء",
                     "pages": [
                       "ar/introduction",
+                      "ar/guides/coding-tools/build-with-ai",
                       "ar/skills",
                       "ar/installation",
                       "ar/quickstart"
@@ -16509,6 +16555,7 @@
                     "group": "البدء",
                     "pages": [
                       "ar/introduction",
+                      "ar/guides/coding-tools/build-with-ai",
                       "ar/skills",
                       "ar/installation",
                       "ar/quickstart"
@@ -16979,6 +17026,7 @@
                     "group": "البدء",
                     "pages": [
                       "ar/introduction",
+                      "ar/guides/coding-tools/build-with-ai",
                       "ar/skills",
                       "ar/installation",
                       "ar/quickstart"
@@ -17449,6 +17497,7 @@
                     "group": "البدء",
                     "pages": [
                       "ar/introduction",
+                      "ar/guides/coding-tools/build-with-ai",
                       "ar/skills",
                       "ar/installation",
                       "ar/quickstart"
@@ -17919,6 +17968,7 @@
                     "group": "البدء",
                     "pages": [
                       "ar/introduction",
+                      "ar/guides/coding-tools/build-with-ai",
                       "ar/skills",
                       "ar/installation",
                       "ar/quickstart"
@@ -18388,6 +18438,7 @@
                     "group": "البدء",
                     "pages": [
                       "ar/introduction",
+                      "ar/guides/coding-tools/build-with-ai",
                       "ar/skills",
                       "ar/installation",
                       "ar/quickstart"
@@ -18857,6 +18908,7 @@
                     "group": "البدء",
                     "pages": [
                       "ar/introduction",
+                      "ar/guides/coding-tools/build-with-ai",
                       "ar/skills",
                       "ar/installation",
                       "ar/quickstart"
@@ -19326,6 +19378,7 @@
                     "group": "البدء",
                     "pages": [
                       "ar/introduction",
+                      "ar/guides/coding-tools/build-with-ai",
                       "ar/skills",
                       "ar/installation",
                       "ar/quickstart"
@@ -19794,6 +19847,7 @@
                     "group": "البدء",
                     "pages": [
                       "ar/introduction",
+                      "ar/guides/coding-tools/build-with-ai",
                       "ar/skills",
                       "ar/installation",
                       "ar/quickstart"
@@ -20262,6 +20316,7 @@
                     "group": "البدء",
                     "pages": [
                       "ar/introduction",
+                      "ar/guides/coding-tools/build-with-ai",
                       "ar/skills",
                       "ar/installation",
                       "ar/quickstart"

docs/en/changelog.mdx

@@ -4,6 +4,36 @@ description: "Product updates, improvements, and bug fixes for CrewAI"
 icon: "clock"
 mode: "wide"
 ---
+<Update label="Apr 22, 2026">
+  ## v1.14.3a2
+
+  [View release on GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.3a2)
+
+  ## What's Changed
+
+  ### Features
+  - Add support for bedrock V4
+  - Add Daytona sandbox tools for enhanced functionality
+  - Add 'Build with AI' page — AI-native docs for coding agents
+  - Add Build with AI to Get Started navigation and page files for all languages (en, ko, pt-BR, ar)
+
+  ### Bug Fixes
+  - Fix propagation of implicit @CrewBase names to crew events
+  - Resolve issue with duplicate batch initialization in execution metadata merge
+  - Fix serialization of Task class-reference fields for checkpointing
+  - Handle BaseModel result in guardrail retry loop
+  - Bump python-dotenv to version >=1.2.2 for security compliance
+
+  ### Documentation
+  - Update changelog and version for v1.14.3a1
+  - Update descriptions and apply actual translations
+
+  ## Contributors
+
+  @MatthiasHowellYopp, @github-actions[bot], @greysonlalonde, @iris-clawd, @lorenzejay, @renatonitta
+
+</Update>
+
 <Update label="Apr 21, 2026">
   ## v1.14.3a1
 

docs/en/concepts/files.mdx

@@ -117,23 +117,35 @@ task = Task(
 
 ### With Flows
 
-Pass files to flows, which automatically inherit to crews:
+File-typed fields (`File`, `ImageFile`, `PDFFile`) in your flow's state schema serve as the signal to the Platform UI. When deployed, these fields render as file upload dropzones. Files can also be passed via `input_files` in the API.
 
 ```python
 from crewai.flow.flow import Flow, start
-from crewai_files import ImageFile
+from crewai_files import File, ImageFile
+from pydantic import BaseModel
 
-class AnalysisFlow(Flow):
+class MyState(BaseModel):
+    document: File           # Renders as file dropzone in Platform UI
+    cover_image: ImageFile   # Image-specific dropzone
+    title: str = ""
+
+class AnalysisFlow(Flow[MyState]):
     @start()
     def analyze(self):
+        # Files are automatically populated in state
+        content = self.state.document.read()
         return self.analysis_crew.kickoff()
 
 flow = AnalysisFlow()
 result = flow.kickoff(
-    input_files={"image": ImageFile(source="data.png")}
+    input_files={"document": File(source="report.pdf")}
 )
 ```
 
+<Note type="info" title="CrewAI Platform Integration">
+When deployed on CrewAI Platform, `ImageFile`, `PDFFile`, and other file-typed fields in your flow state automatically get a file upload UI. Users can drag and drop files directly in the Platform interface. Files are stored securely and passed to agents using provider-specific optimizations (inline base64, file upload APIs, or URL references depending on the provider). For API usage examples, see [File Inputs in Flows](/concepts/flows#file-inputs).
+</Note>
+
 ### With Standalone Agents
 
 Pass files directly to agent kickoff:

docs/en/concepts/flows.mdx

@@ -341,6 +341,90 @@ flow.kickoff()
 
 By providing both unstructured and structured state management options, CrewAI Flows empowers developers to build AI workflows that are both flexible and robust, catering to a wide range of application requirements.
 
+### File Inputs
+
+When using structured state, you can include file-typed fields using classes from `crewai-files`. File-typed fields in your flow state serve as the signal to the Platform—they automatically render as file upload dropzones in the Run tab UI and get populated when files are uploaded via the Platform or passed via `input_files` in the API.
+
+```python
+from crewai.flow.flow import Flow, start
+from crewai_files import File, ImageFile, PDFFile
+from pydantic import BaseModel
+
+class MyState(BaseModel):
+    document: File           # Renders as file dropzone in Platform
+    title: str = ""
+
+class MyFlow(Flow[MyState]):
+    @start()
+    def process(self):
+        # File object is automatically populated in state
+        # when uploaded via Platform UI or passed via API
+        content = self.state.document.read()
+        print(f"Processing {self.state.title}: {len(content)} bytes")
+        return content
+```
+
+When deployed on **CrewAI Platform**, file-typed fields (`File`, `ImageFile`, `PDFFile` from `crewai-files`) automatically render as file upload dropzones in the UI. Users can drag and drop files, which are then populated into your flow's state.
+
+**Kicking off with files via API:**
+
+The `/kickoff` endpoint auto-detects the request format:
+- **JSON body** → normal kickoff
+- **multipart/form-data** → file upload + kickoff
+
+API users can also pass URL strings directly to file-typed fields—Pydantic coerces them automatically.
+
+### API Usage
+
+#### Option 1: Multipart kickoff (recommended)
+
+Send files directly with the kickoff request:
+
+```bash
+# With files (multipart) — same endpoint
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -F 'inputs={"company_name": "Einstein"}' \
+  -F 'cover_image=@/path/to/photo.jpg'
+```
+
+Files are automatically stored and converted to `FileInput` objects. The agent receives the file with provider-specific optimization (inline base64, file upload API, or URL reference depending on the LLM provider).
+
+#### Option 2: JSON kickoff (no files)
+
+```bash
+# Without files (JSON) — same endpoint
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -H 'Content-Type: application/json' \
+  -d '{"inputs": {"company_name": "Einstein"}}'
+```
+
+#### Option 3: Separate upload + kickoff
+
+This is an alternative to multipart upload when you need to upload files separately from the kickoff request. Upload files first, then reference them by URL:
+
+```bash
+# Step 1: Upload
+curl -X POST https://your-deployment.crewai.com/files \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -F 'file=@/path/to/photo.jpg' \
+  -F 'field_name=cover_image'
+# Returns: {"url": "https://...", "field_name": "cover_image"}
+
+# Step 2: Kickoff with URL
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -H 'Content-Type: application/json' \
+  -d '{"inputs": {"company_name": "Einstein"}, "input_files": {"cover_image": "https://..."}}'
+```
+
+See the Platform API documentation for full `/files` endpoint details.
+
+#### On CrewAI Platform
+
+When using the Platform UI, file-typed fields automatically render as drag-and-drop upload zones. No API calls needed—just drop the file and click Run.
+
 ## Flow Persistence
 
 The @persist decorator enables automatic state persistence in CrewAI Flows, allowing you to maintain flow state across restarts or different workflow executions. This decorator can be applied at either the class level or method level, providing flexibility in how you manage state persistence.

docs/en/enterprise/guides/kickoff-crew.mdx

@@ -86,6 +86,60 @@ curl -H "Authorization: Bearer YOUR_CREW_TOKEN" https://your-crew-url.crewai.com
 
 Your bearer token is available on the Status tab of your crew's detail page.
 
+## File Uploads
+
+When your crew or flow includes file-typed state fields (using `ImageFile`, `PDFFile`, or `File` from `crewai-files`), these fields automatically render as file upload dropzones in the Run tab UI. Users can drag and drop files directly, and the Platform handles storage and delivery to your agents.
+
+### Multipart Kickoff (Recommended)
+
+Send files directly with the kickoff request using `multipart/form-data`:
+
+```bash
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -F 'inputs={"title": "Report"}' \
+  -F 'document=@/path/to/file.pdf'
+```
+
+Files are automatically stored and converted to file objects. The agent receives the file with provider-specific optimization (inline base64, file upload API, or URL reference depending on the LLM provider).
+
+### JSON Kickoff with File URLs
+
+If you have files already hosted at URLs, pass them via `input_files`:
+
+```bash
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -H 'Content-Type: application/json' \
+  -d '{
+    "inputs": {"title": "Report"},
+    "input_files": {"document": "https://example.com/file.pdf"}
+  }'
+```
+
+### Separate Upload + Kickoff
+
+Upload files first, then reference them by URL:
+
+```bash
+# Step 1: Upload
+curl -X POST https://your-deployment.crewai.com/files \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -F 'file=@/path/to/file.pdf' \
+  -F 'field_name=document'
+# Returns: {"url": "https://...", "field_name": "document"}
+
+# Step 2: Kickoff with URL
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -H 'Content-Type: application/json' \
+  -d '{"inputs": {"title": "Report"}, "input_files": {"document": "https://..."}}'
+```
+
+<Note type="info">
+File uploads work the same way for both crews and flows. Define file-typed fields in your state schema, and the Platform UI and API will handle uploads automatically.
+</Note>
+
 ### Checking Crew Health
 
 Before executing operations, you can verify that your crew is running properly:

docs/en/guides/coding-tools/build-with-ai.mdx

@@ -0,0 +1,214 @@
+---
+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."
+icon: robot
+mode: "wide"
+---
+
+# Build with AI
+
+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.
+
+### Supported Coding Agents
+
+<CardGroup cols={5}>
+  <Card title="Claude Code" icon="message-bot" color="#D97706" />
+  <Card title="Cursor" icon="arrow-pointer" color="#3B82F6" />
+  <Card title="Codex" icon="terminal" color="#10B981" />
+  <Card title="Windsurf" icon="wind" color="#06B6D4" />
+  <Card title="Gemini CLI" icon="sparkles" color="#8B5CF6" />
+</CardGroup>
+
+<Note>
+  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.
+</Note>
+
+---
+
+## 1. Skills — Teach Your Agent CrewAI
+
+**Skills** are instruction packs that give coding agents deep CrewAI knowledge — how to scaffold Flows, configure Crews, use tools, and follow framework conventions.
+
+<Tabs>
+  <Tab title="Claude Code (Plugin Marketplace)">
+    <img src="https://cdn.simpleicons.org/anthropic/D97706" alt="Anthropic" width="28" style={{display: "inline", verticalAlign: "middle", marginRight: "8px"}} />
+    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 |
+  </Tab>
+  <Tab title="npx (Any Agent)">
+    Works with Claude Code, Codex, Cursor, Gemini CLI, or any coding agent:
+    ```shell
+    npx skills add crewaiinc/skills
+    ```
+    Pulls from the [skills.sh registry](https://skills.sh/crewaiinc/skills).
+  </Tab>
+</Tabs>
+
+<Steps>
+  <Step title="Install the official skill pack">
+    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.
+  </Step>
+  <Step title="Your agent gets instant CrewAI expertise">
+    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
+  </Step>
+  <Step title="Start building">
+    Your agent can now scaffold and build CrewAI projects without you re-explaining the framework each session.
+  </Step>
+</Steps>
+
+<CardGroup cols={2}>
+  <Card title="Skills concept" icon="bolt" href="/en/concepts/skills">
+    How skills work in CrewAI agents — injection, activation, and patterns.
+  </Card>
+  <Card title="Skills landing page" icon="wand-magic-sparkles" href="/en/skills">
+    Overview of the crewAIInc/skills pack and what it includes.
+  </Card>
+  <Card title="AGENTS.md & coding tools" icon="terminal" href="/en/guides/coding-tools/agents-md">
+    Set up AGENTS.md for Claude Code, Codex, Cursor, and Gemini CLI.
+  </Card>
+  <Card title="Skills registry (skills.sh)" icon="globe" href="https://skills.sh/crewaiinc/skills">
+    Official listing — skills, install stats, and audits.
+  </Card>
+</CardGroup>
+
+---
+
+## 2. llms.txt — Machine-Readable Docs
+
+CrewAI publishes an `llms.txt` file that gives AI assistants direct access to the full documentation in a machine-readable format.
+
+```
+https://docs.crewai.com/llms.txt
+```
+
+<Tabs>
+  <Tab title="What is 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.
+
+    CrewAI's `llms.txt` is **already live** — your agent can use it right now.
+  </Tab>
+  <Tab title="How to use it">
+    Point your coding agent at the URL when it needs CrewAI reference docs:
+
+    ```
+    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.
+  </Tab>
+  <Tab title="Why it matters">
+    - **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
+  </Tab>
+</Tabs>
+
+---
+
+## 3. Deploy to Enterprise
+
+Go from a local crew to production on **CrewAI AMP** (Agent Management Platform) in minutes.
+
+<Steps>
+  <Step title="Build locally">
+    Scaffold and test your crew or flow:
+    ```bash
+    crewai create crew my_crew
+    cd my_crew
+    crewai run
+    ```
+  </Step>
+  <Step title="Prepare for deployment">
+    Ensure your project structure is ready:
+    ```bash
+    crewai deploy --prepare
+    ```
+    See the [preparation guide](/en/enterprise/guides/prepare-for-deployment) for details on project structure and requirements.
+  </Step>
+  <Step title="Deploy to AMP">
+    Push to the CrewAI AMP platform:
+    ```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).
+  </Step>
+  <Step title="Access via API">
+    Your deployed crew gets a REST API endpoint. Integrate it into any application:
+    ```bash
+    curl -X POST https://app.crewai.com/api/v1/crews/<crew-id>/kickoff \
+      -H "Authorization: Bearer $CREWAI_API_KEY" \
+      -H "Content-Type: application/json" \
+      -d '{"inputs": {"topic": "AI agents"}}'
+    ```
+  </Step>
+</Steps>
+
+<CardGroup cols={2}>
+  <Card title="Deploy to AMP" icon="rocket" href="/en/enterprise/guides/deploy-to-amp">
+    Full deployment guide — CLI, GitHub, and Crew Studio methods.
+  </Card>
+  <Card title="AMP introduction" icon="globe" href="/en/enterprise/introduction">
+    Platform overview — what AMP provides for production crews.
+  </Card>
+</CardGroup>
+
+---
+
+## 4. Enterprise Features
+
+CrewAI AMP is built for production teams. Here's what you get beyond deployment.
+
+<CardGroup cols={2}>
+  <Card title="Observability" icon="chart-line">
+    Detailed execution traces, logs, and performance metrics for every crew run. Monitor agent decisions, tool calls, and task completion in real time.
+  </Card>
+  <Card title="Crew Studio" icon="paintbrush">
+    No-code/low-code interface to create, customize, and deploy crews visually — then export to code or deploy directly.
+  </Card>
+  <Card title="Webhook Streaming" icon="webhook">
+    Stream real-time events from crew executions to your systems. Integrate with Slack, Zapier, or any webhook consumer.
+  </Card>
+  <Card title="Team Management" icon="users">
+    SSO, RBAC, and organization-level controls. Manage who can create, deploy, and access crews across your team.
+  </Card>
+  <Card title="Tool Repository" icon="toolbox">
+    Publish and share custom tools across your organization. Install community tools from the registry.
+  </Card>
+  <Card title="Factory (Self-Hosted)" icon="server">
+    Run CrewAI AMP on your own infrastructure. Full platform capabilities with data residency and compliance controls.
+  </Card>
+</CardGroup>
+
+<AccordionGroup>
+  <Accordion title="Who is AMP for?">
+    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.
+  </Accordion>
+  <Accordion title="What deployment options are available?">
+    - **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
+  </Accordion>
+</AccordionGroup>
+
+<Card title="Explore CrewAI AMP →" icon="arrow-right" href="https://app.crewai.com">
+  Sign up and deploy your first crew to production.
+</Card>

docs/ko/changelog.mdx

@@ -4,6 +4,36 @@ description: "CrewAI의 제품 업데이트, 개선 사항 및 버그 수정"
 icon: "clock"
 mode: "wide"
 ---
+<Update label="2026년 4월 22일">
+  ## v1.14.3a2
+
+  [GitHub 릴리스 보기](https://github.com/crewAIInc/crewAI/releases/tag/1.14.3a2)
+
+  ## 변경 사항
+
+  ### 기능
+  - 베드록 V4 지원 추가
+  - 향상된 기능을 위한 데이토나 샌드박스 도구 추가
+  - 'AI와 함께 빌드' 페이지 추가 — 코딩 에이전트를 위한 AI 네이티브 문서
+  - 모든 언어(en, ko, pt-BR, ar)에 대한 시작하기 탐색 및 페이지 파일에 AI와 함께 빌드 추가
+
+  ### 버그 수정
+  - 크루 이벤트에 대한 암묵적 @CrewBase 이름 전파 수정
+  - 실행 메타데이터 병합에서 중복 배치 초기화 문제 해결
+  - 체크포인트를 위한 Task 클래스 참조 필드 직렬화 수정
+  - 가드레일 재시도 루프에서 BaseModel 결과 처리
+  - 보안 준수를 위해 python-dotenv를 버전 >=1.2.2로 업데이트
+
+  ### 문서
+  - v1.14.3a1에 대한 변경 로그 및 버전 업데이트
+  - 설명 업데이트 및 실제 번역 적용
+
+  ## 기여자
+
+  @MatthiasHowellYopp, @github-actions[bot], @greysonlalonde, @iris-clawd, @lorenzejay, @renatonitta
+
+</Update>
+
 <Update label="2026년 4월 21일">
   ## v1.14.3a1
 

docs/ko/concepts/files.mdx

@@ -117,23 +117,35 @@ task = Task(
 
 ### Flow와 함께
 
-flow에 파일을 전달하면 자동으로 crew에 상속됩니다:
+flow의 상태 스키마에 있는 파일 타입 필드(`File`, `ImageFile`, `PDFFile`)는 플랫폼 UI에 대한 신호 역할을 합니다. 배포 시 이러한 필드는 파일 업로드 드롭존으로 렌더링됩니다. 파일은 API에서 `input_files`를 통해서도 전달할 수 있습니다.
 
 ```python
 from crewai.flow.flow import Flow, start
-from crewai_files import ImageFile
+from crewai_files import File, ImageFile
+from pydantic import BaseModel
 
-class AnalysisFlow(Flow):
+class MyState(BaseModel):
+    document: File           # Renders as file dropzone in Platform UI
+    cover_image: ImageFile   # Image-specific dropzone
+    title: str = ""
+
+class AnalysisFlow(Flow[MyState]):
     @start()
     def analyze(self):
+        # Files are automatically populated in state
+        content = self.state.document.read()
         return self.analysis_crew.kickoff()
 
 flow = AnalysisFlow()
 result = flow.kickoff(
-    input_files={"image": ImageFile(source="data.png")}
+    input_files={"document": File(source="report.pdf")}
 )
 ```
 
+<Note type="info" title="CrewAI 플랫폼 통합">
+CrewAI 플랫폼에 배포하면 flow 상태의 `ImageFile`, `PDFFile` 및 기타 파일 타입 필드가 자동으로 파일 업로드 UI를 갖게 됩니다. 사용자는 플랫폼 인터페이스에서 직접 파일을 드래그 앤 드롭할 수 있습니다. 파일은 안전하게 저장되고 프로바이더별 최적화(인라인 base64, 파일 업로드 API 또는 프로바이더에 따른 URL 참조)를 사용하여 에이전트에 전달됩니다. API 사용 예제는 [Flows의 파일 입력](/ko/concepts/flows#파일-입력)을 참조하세요.
+</Note>
+
 ### 단독 에이전트와 함께
 
 에이전트 킥오프에 직접 파일을 전달합니다:

docs/ko/concepts/flows.mdx

@@ -334,6 +334,90 @@ flow.kickoff()
 
 CrewAI Flows는 비구조적 및 구조적 상태 관리 옵션을 모두 제공함으로써, 개발자들이 다양한 애플리케이션 요구 사항에 맞춰 유연하면서도 견고한 AI 워크플로를 구축할 수 있도록 지원합니다.
 
+### 파일 입력
+
+구조화된 상태를 사용할 때, `crewai-files`의 클래스를 사용하여 파일 타입 필드를 포함할 수 있습니다. flow 상태의 파일 타입 필드는 플랫폼에 대한 신호 역할을 합니다 — Run 탭 UI에서 자동으로 파일 업로드 드롭존으로 렌더링되며, 플랫폼을 통해 파일을 업로드하거나 API에서 `input_files`를 통해 전달할 때 자동으로 채워집니다.
+
+```python
+from crewai.flow.flow import Flow, start
+from crewai_files import File, ImageFile, PDFFile
+from pydantic import BaseModel
+
+class MyState(BaseModel):
+    document: File           # Renders as file dropzone in Platform
+    title: str = ""
+
+class MyFlow(Flow[MyState]):
+    @start()
+    def process(self):
+        # File object is automatically populated in state
+        # when uploaded via Platform UI or passed via API
+        content = self.state.document.read()
+        print(f"Processing {self.state.title}: {len(content)} bytes")
+        return content
+```
+
+**CrewAI 플랫폼**에 배포하면 파일 타입 필드(`crewai-files`의 `File`, `ImageFile`, `PDFFile`)가 UI에서 자동으로 파일 업로드 드롭존으로 렌더링됩니다. 사용자는 파일을 드래그 앤 드롭할 수 있으며, 해당 파일은 flow의 상태에 자동으로 채워집니다.
+
+**API를 통한 파일 포함 시작:**
+
+`/kickoff` 엔드포인트는 요청 형식을 자동으로 감지합니다:
+- **JSON body** → 일반 kickoff
+- **multipart/form-data** → 파일 업로드 + kickoff
+
+API 사용자는 파일 타입 필드에 URL 문자열을 직접 전달할 수도 있습니다 — Pydantic이 자동으로 변환합니다.
+
+### API 사용법
+
+#### 옵션 1: Multipart kickoff (권장)
+
+kickoff 요청과 함께 파일을 직접 전송합니다:
+
+```bash
+# With files (multipart) — same endpoint
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -F 'inputs={"company_name": "Einstein"}' \
+  -F 'cover_image=@/path/to/photo.jpg'
+```
+
+파일은 자동으로 저장되고 `FileInput` 객체로 변환됩니다. 에이전트는 프로바이더별 최적화(LLM 프로바이더에 따라 인라인 base64, 파일 업로드 API 또는 URL 참조)와 함께 파일을 수신합니다.
+
+#### 옵션 2: JSON kickoff (파일 없음)
+
+```bash
+# Without files (JSON) — same endpoint
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -H 'Content-Type: application/json' \
+  -d '{"inputs": {"company_name": "Einstein"}}'
+```
+
+#### 옵션 3: 분리된 업로드 + kickoff
+
+kickoff 요청과 별도로 파일을 업로드해야 할 때 multipart 업로드의 대안입니다. 먼저 파일을 업로드한 다음 URL로 참조합니다:
+
+```bash
+# Step 1: Upload
+curl -X POST https://your-deployment.crewai.com/files \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -F 'file=@/path/to/photo.jpg' \
+  -F 'field_name=cover_image'
+# Returns: {"url": "https://...", "field_name": "cover_image"}
+
+# Step 2: Kickoff with URL
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -H 'Content-Type: application/json' \
+  -d '{"inputs": {"company_name": "Einstein"}, "input_files": {"cover_image": "https://..."}}'
+```
+
+`/files` 엔드포인트에 대한 자세한 내용은 플랫폼 API 문서를 참조하세요.
+
+#### CrewAI 플랫폼에서
+
+플랫폼 UI를 사용할 때 파일 타입 필드는 자동으로 드래그 앤 드롭 업로드 영역으로 렌더링됩니다. API 호출이 필요 없습니다 — 파일을 드롭하고 실행을 클릭하면 됩니다.
+
 ## 플로우 지속성
 
 @persist 데코레이터는 CrewAI 플로우에서 자동 상태 지속성을 활성화하여, 플로우 상태를 재시작이나 다른 워크플로우 실행 간에도 유지할 수 있도록 합니다. 이 데코레이터는 클래스 수준이나 메서드 수준 모두에 적용할 수 있어, 상태 지속성을 관리하는 데 유연성을 제공합니다.

docs/ko/enterprise/guides/kickoff-crew.mdx

@@ -86,6 +86,60 @@ curl -H "Authorization: Bearer YOUR_CREW_TOKEN" https://your-crew-url.crewai.com
 
 베어러 토큰은 crew의 상세 페이지의 Status 탭에서 확인할 수 있습니다.
 
+## 파일 업로드
+
+crew나 flow에 파일 타입 상태 필드(`crewai-files`의 `ImageFile`, `PDFFile`, 또는 `File` 사용)가 포함되어 있으면, 이러한 필드는 Run 탭 UI에서 자동으로 파일 업로드 드롭존으로 렌더링됩니다. 사용자는 파일을 직접 드래그 앤 드롭할 수 있으며, 플랫폼이 저장 및 에이전트 전달을 처리합니다.
+
+### Multipart Kickoff (권장)
+
+`multipart/form-data`를 사용하여 kickoff 요청과 함께 파일을 직접 전송합니다:
+
+```bash
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -F 'inputs={"title": "Report"}' \
+  -F 'document=@/path/to/file.pdf'
+```
+
+파일은 자동으로 저장되고 파일 객체로 변환됩니다. 에이전트는 프로바이더별 최적화(LLM 프로바이더에 따라 인라인 base64, 파일 업로드 API 또는 URL 참조)와 함께 파일을 수신합니다.
+
+### 파일 URL을 포함한 JSON Kickoff
+
+이미 URL에 호스팅된 파일이 있다면 `input_files`를 통해 전달합니다:
+
+```bash
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -H 'Content-Type: application/json' \
+  -d '{
+    "inputs": {"title": "Report"},
+    "input_files": {"document": "https://example.com/file.pdf"}
+  }'
+```
+
+### 분리된 업로드 + Kickoff
+
+먼저 파일을 업로드한 다음 URL로 참조합니다:
+
+```bash
+# Step 1: Upload
+curl -X POST https://your-deployment.crewai.com/files \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -F 'file=@/path/to/file.pdf' \
+  -F 'field_name=document'
+# Returns: {"url": "https://...", "field_name": "document"}
+
+# Step 2: Kickoff with URL
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -H 'Content-Type: application/json' \
+  -d '{"inputs": {"title": "Report"}, "input_files": {"document": "https://..."}}'
+```
+
+<Note type="info">
+파일 업로드는 crew와 flow 모두에서 동일하게 작동합니다. 상태 스키마에 파일 타입 필드를 정의하면 플랫폼 UI와 API가 자동으로 업로드를 처리합니다.
+</Note>
+
 ### 크루 상태 확인
 
 작업을 실행하기 전에 크루가 정상적으로 실행되고 있는지 확인할 수 있습니다:

docs/ko/guides/coding-tools/build-with-ai.mdx

@@ -0,0 +1,214 @@
+---
+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"
+---
+
+# AI와 함께 빌드하기
+
+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.
+
+### 지원 코딩 에이전트
+
+<CardGroup cols={5}>
+  <Card title="Claude Code" icon="message-bot" color="#D97706" />
+  <Card title="Cursor" icon="arrow-pointer" color="#3B82F6" />
+  <Card title="Codex" icon="terminal" color="#10B981" />
+  <Card title="Windsurf" icon="wind" color="#06B6D4" />
+  <Card title="Gemini CLI" icon="sparkles" color="#8B5CF6" />
+</CardGroup>
+
+<Note>
+  이 페이지는 사람과 AI 어시스턴트 모두를 위해 작성되었습니다. 코딩 에이전트라면 CrewAI 맥락은 **Skills**부터, 전체 문서 접근은 **llms.txt**를 사용하세요.
+</Note>
+
+---
+
+## 1. Skills — 에이전트에게 CrewAI 가르치기
+
+**Skills**는 코딩 에이전트에게 Flow 스캐폴딩, Crew 구성, 도구 사용, 프레임워크 관례 등 CrewAI에 대한 깊은 지식을 담은 지침 묶음입니다.
+
+<Tabs>
+  <Tab title="Claude Code (플러그인 마켓플레이스)">
+    <img src="https://cdn.simpleicons.org/anthropic/D97706" alt="Anthropic" width="28" style={{display: "inline", verticalAlign: "middle", marginRight: "8px"}} />
+    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 |
+  </Tab>
+  <Tab title="npx (모든 에이전트)">
+    Claude Code, Codex, Cursor, Gemini CLI 등 모든 코딩 에이전트에서 사용할 수 있습니다.
+    ```shell
+    npx skills add crewaiinc/skills
+    ```
+    [skills.sh 레지스트리](https://skills.sh/crewaiinc/skills)에서 가져옵니다.
+  </Tab>
+</Tabs>
+
+<Steps>
+  <Step title="공식 스킬 팩 설치">
+    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.
+  </Step>
+  <Step title="에이전트가 즉시 CrewAI 전문성을 갖춤">
+    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
+  </Step>
+  <Step title="빌드 시작">
+    매 세션마다 프레임워크를 다시 설명하지 않아도 에이전트가 CrewAI 프로젝트를 스캐폴딩하고 빌드할 수 있습니다.
+  </Step>
+</Steps>
+
+<CardGroup cols={2}>
+  <Card title="Skills 개념" icon="bolt" href="/ko/concepts/skills">
+    CrewAI 에이전트에서 스킬이 동작하는 방식 — 주입, 활성화, 패턴.
+  </Card>
+  <Card title="Skills 랜딩 페이지" icon="wand-magic-sparkles" href="/ko/skills">
+    crewAIInc/skills 팩 개요와 포함 내용.
+  </Card>
+  <Card title="AGENTS.md 및 코딩 도구" icon="terminal" href="/ko/guides/coding-tools/agents-md">
+    Claude Code, Codex, Cursor, Gemini CLI용 AGENTS.md 설정.
+  </Card>
+  <Card title="Skills 레지스트리 (skills.sh)" icon="globe" href="https://skills.sh/crewaiinc/skills">
+    공식 목록 — 스킬, 설치 통계, 감사 정보.
+  </Card>
+</CardGroup>
+
+---
+
+## 2. llms.txt — 기계가 읽을 수 있는 문서
+
+CrewAI는 AI 어시스턴트가 전체 문서에 기계가 읽을 수 있는 형태로 바로 접근할 수 있도록 `llms.txt` 파일을 제공합니다.
+
+```
+https://docs.crewai.com/llms.txt
+```
+
+<Tabs>
+  <Tab title="llms.txt란?">
+    [`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.
+
+    CrewAI의 `llms.txt`는 **이미 제공 중**이며, 에이전트가 바로 사용할 수 있습니다.
+  </Tab>
+  <Tab title="사용 방법">
+    CrewAI 참고 문서가 필요할 때 코딩 에이전트에 URL을 알려 주세요.
+
+    ```
+    Fetch https://docs.crewai.com/llms.txt for CrewAI documentation.
+    ```
+
+    Claude Code, Cursor 등 많은 코딩 에이전트가 URL을 직접 가져올 수 있습니다. 파일에는 CrewAI 개념, API, 가이드를 아우르는 구조화된 문서가 포함되어 있습니다.
+  </Tab>
+  <Tab title="왜 중요한가">
+    - **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
+  </Tab>
+</Tabs>
+
+---
+
+## 3. 엔터프라이즈에 배포
+
+로컬 crew를 몇 분 안에 **CrewAI AMP**(Agent Management Platform) 프로덕션으로 가져가세요.
+
+<Steps>
+  <Step title="로컬에서 빌드">
+    crew 또는 flow를 스캐폴딩하고 테스트합니다.
+    ```bash
+    crewai create crew my_crew
+    cd my_crew
+    crewai run
+    ```
+  </Step>
+  <Step title="배포 준비">
+    프로젝트 구조가 준비되었는지 확인합니다.
+    ```bash
+    crewai deploy --prepare
+    ```
+    구조와 요구 사항은 [준비 가이드](/ko/enterprise/guides/prepare-for-deployment)를 참고하세요.
+  </Step>
+  <Step title="AMP에 배포">
+    CrewAI AMP 플랫폼으로 푸시합니다.
+    ```bash
+    crewai deploy
+    ```
+    [GitHub 연동](/ko/enterprise/guides/deploy-to-amp) 또는 [Crew Studio](/ko/enterprise/guides/enable-crew-studio)로도 배포할 수 있습니다.
+  </Step>
+  <Step title="API로 접근">
+    배포된 crew는 REST API 엔드포인트를 받습니다. 모든 애플리케이션에 통합할 수 있습니다.
+    ```bash
+    curl -X POST https://app.crewai.com/api/v1/crews/<crew-id>/kickoff \
+      -H "Authorization: Bearer $CREWAI_API_KEY" \
+      -H "Content-Type: application/json" \
+      -d '{"inputs": {"topic": "AI agents"}}'
+    ```
+  </Step>
+</Steps>
+
+<CardGroup cols={2}>
+  <Card title="AMP에 배포" icon="rocket" href="/ko/enterprise/guides/deploy-to-amp">
+    전체 배포 가이드 — CLI, GitHub, Crew Studio 방법.
+  </Card>
+  <Card title="AMP 소개" icon="globe" href="/ko/enterprise/introduction">
+    플랫폼 개요 — 프로덕션 crew에 AMP가 제공하는 것.
+  </Card>
+</CardGroup>
+
+---
+
+## 4. 엔터프라이즈 기능
+
+CrewAI AMP는 프로덕션 팀을 위해 만들어졌습니다. 배포 외에 제공되는 것은 다음과 같습니다.
+
+<CardGroup cols={2}>
+  <Card title="관측 가능성" icon="chart-line">
+    모든 crew 실행에 대한 상세 실행 추적, 로그, 성능 지표. 에이전트 결정, 도구 호출, 태스크 완료를 실시간으로 모니터링합니다.
+  </Card>
+  <Card title="Crew Studio" icon="paintbrush">
+    시각적으로 crew를 만들고, 맞춤 설정하고, 배포하는 노코드/로코드 인터페이스 — 코드로 보내거나 바로 배포할 수 있습니다.
+  </Card>
+  <Card title="웹훅 스트리밍" icon="webhook">
+    crew 실행에서 실시간 이벤트를 시스템으로 스트리밍합니다. Slack, Zapier 등 웹훅 소비자와 연동할 수 있습니다.
+  </Card>
+  <Card title="팀 관리" icon="users">
+    SSO, RBAC, 조직 단위 제어. 팀 전체에서 crew 생성·배포·접근 권한을 관리합니다.
+  </Card>
+  <Card title="도구 저장소" icon="toolbox">
+    조직 전체에 맞춤 도구를 게시하고 공유합니다. 레지스트리에서 커뮤니티 도구를 설치합니다.
+  </Card>
+  <Card title="Factory(셀프 호스팅)" icon="server">
+    자체 인프라에서 CrewAI AMP를 실행합니다. 데이터 상주와 규정 준수 제어와 함께 플랫폼 전체 기능을 사용할 수 있습니다.
+  </Card>
+</CardGroup>
+
+<AccordionGroup>
+  <Accordion title="AMP는 누구를 위한 것인가요?">
+    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.
+  </Accordion>
+  <Accordion title="배포 옵션은 무엇이 있나요?">
+    - **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
+  </Accordion>
+</AccordionGroup>
+
+<Card title="CrewAI AMP 살펴보기 →" icon="arrow-right" href="https://app.crewai.com">
+  가입하고 첫 crew를 프로덕션에 배포해 보세요.
+</Card>

docs/pt-BR/changelog.mdx

@@ -4,6 +4,36 @@ description: "Atualizações de produto, melhorias e correções do CrewAI"
 icon: "clock"
 mode: "wide"
 ---
+<Update label="22 abr 2026">
+  ## v1.14.3a2
+
+  [Ver release no GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.3a2)
+
+  ## O que mudou
+
+  ### Recursos
+  - Adicionar suporte para bedrock V4
+  - Adicionar ferramentas de sandbox Daytona para funcionalidade aprimorada
+  - Adicionar página 'Construir com IA' — documentação nativa de IA para agentes de codificação
+  - Adicionar Construir com IA à navegação Começar e arquivos de página para todos os idiomas (en, ko, pt-BR, ar)
+
+  ### Correções de Bugs
+  - Corrigir a propagação de nomes implícitos @CrewBase para eventos da equipe
+  - Resolver problema com inicialização de lote duplicada na mesclagem de metadados de execução
+  - Corrigir a serialização de campos de referência de classe Task para checkpointing
+  - Lidar com o resultado BaseModel no loop de repetição de guardrail
+  - Atualizar python-dotenv para a versão >=1.2.2 para conformidade de segurança
+
+  ### Documentação
+  - Atualizar changelog e versão para v1.14.3a1
+  - Atualizar descrições e aplicar traduções reais
+
+  ## Contributors
+
+  @MatthiasHowellYopp, @github-actions[bot], @greysonlalonde, @iris-clawd, @lorenzejay, @renatonitta
+
+</Update>
+
 <Update label="21 abr 2026">
   ## v1.14.3a1
 

docs/pt-BR/concepts/files.mdx

@@ -117,23 +117,35 @@ task = Task(
 
 ### Com Flows
 
-Passe arquivos para flows, que automaticamente herdam para crews:
+Campos tipados como arquivo (`File`, `ImageFile`, `PDFFile`) no esquema de estado do seu flow servem como sinal para a interface da Plataforma. Quando implantado, esses campos são renderizados como zonas de upload de arquivos. Arquivos também podem ser passados via `input_files` na API.
 
 ```python
 from crewai.flow.flow import Flow, start
-from crewai_files import ImageFile
+from crewai_files import File, ImageFile
+from pydantic import BaseModel
 
-class AnalysisFlow(Flow):
+class MyState(BaseModel):
+    document: File           # Renders as file dropzone in Platform UI
+    cover_image: ImageFile   # Image-specific dropzone
+    title: str = ""
+
+class AnalysisFlow(Flow[MyState]):
     @start()
     def analyze(self):
+        # Files are automatically populated in state
+        content = self.state.document.read()
         return self.analysis_crew.kickoff()
 
 flow = AnalysisFlow()
 result = flow.kickoff(
-    input_files={"image": ImageFile(source="data.png")}
+    input_files={"document": File(source="report.pdf")}
 )
 ```
 
+<Note type="info" title="Integração com a Plataforma CrewAI">
+Quando implantado na Plataforma CrewAI, campos tipados como arquivo como `ImageFile`, `PDFFile` e outros no estado do seu flow recebem automaticamente uma interface de upload de arquivos. Os usuários podem arrastar e soltar arquivos diretamente na interface da Plataforma. Os arquivos são armazenados de forma segura e passados para os agentes usando otimizações específicas do provedor (base64 inline, APIs de upload de arquivo ou referências por URL dependendo do provedor). Para exemplos de uso da API, consulte [Entradas de Arquivos em Flows](/pt-BR/concepts/flows#entradas-de-arquivos).
+</Note>
+
 ### Com Agentes Standalone
 
 Passe arquivos diretamente no kickoff do agente:

docs/pt-BR/concepts/flows.mdx

@@ -173,6 +173,90 @@ Cada estado nos flows do CrewAI recebe automaticamente um identificador único (
 
 Ao oferecer as duas opções de gerenciamento de estado, o CrewAI Flows permite que desenvolvedores criem fluxos de IA que sejam ao mesmo tempo flexíveis e robustos, atendendo a uma ampla variedade de requisitos de aplicação.
 
+### Entradas de Arquivos
+
+Ao usar estado estruturado, você pode incluir campos tipados como arquivo usando classes do `crewai-files`. Campos tipados como arquivo no estado do seu flow servem como sinal para a Plataforma — eles são renderizados automaticamente como zonas de upload de arquivos na aba Run da interface e são preenchidos quando arquivos são enviados via Plataforma ou passados via `input_files` na API.
+
+```python
+from crewai.flow.flow import Flow, start
+from crewai_files import File, ImageFile, PDFFile
+from pydantic import BaseModel
+
+class MyState(BaseModel):
+    document: File           # Renders as file dropzone in Platform
+    title: str = ""
+
+class MyFlow(Flow[MyState]):
+    @start()
+    def process(self):
+        # File object is automatically populated in state
+        # when uploaded via Platform UI or passed via API
+        content = self.state.document.read()
+        print(f"Processing {self.state.title}: {len(content)} bytes")
+        return content
+```
+
+Quando implantado na **Plataforma CrewAI**, campos tipados como arquivo (`File`, `ImageFile`, `PDFFile` do `crewai-files`) são renderizados automaticamente como zonas de upload de arquivos na interface. Os usuários podem arrastar e soltar arquivos, que são então preenchidos no estado do seu flow.
+
+**Iniciando com arquivos via API:**
+
+O endpoint `/kickoff` detecta automaticamente o formato da requisição:
+- **Corpo JSON** → kickoff normal
+- **multipart/form-data** → upload de arquivo + kickoff
+
+Usuários da API também podem passar strings de URL diretamente para campos tipados como arquivo — o Pydantic as converte automaticamente.
+
+### Uso da API
+
+#### Opção 1: Kickoff multipart (recomendado)
+
+Envie arquivos diretamente com a requisição de kickoff:
+
+```bash
+# With files (multipart) — same endpoint
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -F 'inputs={"company_name": "Einstein"}' \
+  -F 'cover_image=@/path/to/photo.jpg'
+```
+
+Os arquivos são armazenados automaticamente e convertidos em objetos `FileInput`. O agente recebe o arquivo com otimização específica do provedor (base64 inline, API de upload de arquivo ou referência por URL dependendo do provedor LLM).
+
+#### Opção 2: Kickoff JSON (sem arquivos)
+
+```bash
+# Without files (JSON) — same endpoint
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -H 'Content-Type: application/json' \
+  -d '{"inputs": {"company_name": "Einstein"}}'
+```
+
+#### Opção 3: Upload separado + kickoff
+
+Esta é uma alternativa ao upload multipart quando você precisa fazer upload dos arquivos separadamente da requisição de kickoff. Faça o upload dos arquivos primeiro e depois referencie-os por URL:
+
+```bash
+# Step 1: Upload
+curl -X POST https://your-deployment.crewai.com/files \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -F 'file=@/path/to/photo.jpg' \
+  -F 'field_name=cover_image'
+# Returns: {"url": "https://...", "field_name": "cover_image"}
+
+# Step 2: Kickoff with URL
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -H 'Content-Type: application/json' \
+  -d '{"inputs": {"company_name": "Einstein"}, "input_files": {"cover_image": "https://..."}}'
+```
+
+Consulte a documentação da API da Plataforma para detalhes completos do endpoint `/files`.
+
+#### Na Plataforma CrewAI
+
+Ao usar a interface da Plataforma, campos tipados como arquivo são renderizados automaticamente como zonas de arrastar e soltar para upload. Nenhuma chamada de API é necessária — basta soltar o arquivo e clicar em Executar.
+
 ## Persistência de Flow
 
 O decorador @persist permite a persistência automática do estado nos flows do CrewAI, garantindo que você mantenha o estado do flow entre reinicializações ou execuções diferentes do workflow. Esse decorador pode ser aplicado tanto ao nível de classe, quanto ao nível de método, oferecendo flexibilidade sobre como gerenciar a persistência do estado.

docs/pt-BR/enterprise/guides/kickoff-crew.mdx

@@ -86,6 +86,60 @@ curl -H "Authorization: Bearer YOUR_CREW_TOKEN" https://your-crew-url.crewai.com
 
 Seu bearer token está disponível na aba Status na página de detalhes do seu crew.
 
+## Upload de Arquivos
+
+Quando seu crew ou flow inclui campos de estado tipados como arquivo (usando `ImageFile`, `PDFFile` ou `File` do `crewai-files`), esses campos são renderizados automaticamente como zonas de upload de arquivos na aba Run da interface. Os usuários podem arrastar e soltar arquivos diretamente, e a Plataforma gerencia o armazenamento e entrega para seus agentes.
+
+### Kickoff Multipart (Recomendado)
+
+Envie arquivos diretamente com a requisição de kickoff usando `multipart/form-data`:
+
+```bash
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -F 'inputs={"title": "Report"}' \
+  -F 'document=@/path/to/file.pdf'
+```
+
+Os arquivos são armazenados automaticamente e convertidos em objetos de arquivo. O agente recebe o arquivo com otimização específica do provedor (base64 inline, API de upload de arquivo ou referência por URL dependendo do provedor LLM).
+
+### Kickoff JSON com URLs de Arquivos
+
+Se você já tem arquivos hospedados em URLs, passe-os via `input_files`:
+
+```bash
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -H 'Content-Type: application/json' \
+  -d '{
+    "inputs": {"title": "Report"},
+    "input_files": {"document": "https://example.com/file.pdf"}
+  }'
+```
+
+### Upload Separado + Kickoff
+
+Faça upload dos arquivos primeiro e depois referencie-os por URL:
+
+```bash
+# Step 1: Upload
+curl -X POST https://your-deployment.crewai.com/files \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -F 'file=@/path/to/file.pdf' \
+  -F 'field_name=document'
+# Returns: {"url": "https://...", "field_name": "document"}
+
+# Step 2: Kickoff with URL
+curl -X POST https://your-deployment.crewai.com/kickoff \
+  -H 'Authorization: Bearer YOUR_TOKEN' \
+  -H 'Content-Type: application/json' \
+  -d '{"inputs": {"title": "Report"}, "input_files": {"document": "https://..."}}'
+```
+
+<Note type="info">
+O upload de arquivos funciona da mesma forma tanto para crews quanto para flows. Defina campos tipados como arquivo no seu esquema de estado, e a interface da Plataforma e a API tratarão os uploads automaticamente.
+</Note>
+
 ### Verificando o Status do Crew
 
 Antes de executar operações, você pode verificar se seu crew está funcionando corretamente:

docs/pt-BR/guides/coding-tools/build-with-ai.mdx

@@ -0,0 +1,214 @@
+---
+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"
+---
+
+# Construa com IA
+
+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.
+
+### Agentes de codificação compatíveis
+
+<CardGroup cols={5}>
+  <Card title="Claude Code" icon="message-bot" color="#D97706" />
+  <Card title="Cursor" icon="arrow-pointer" color="#3B82F6" />
+  <Card title="Codex" icon="terminal" color="#10B981" />
+  <Card title="Windsurf" icon="wind" color="#06B6D4" />
+  <Card title="Gemini CLI" icon="sparkles" color="#8B5CF6" />
+</CardGroup>
+
+<Note>
+  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.
+</Note>
+
+---
+
+## 1. Skills — ensine CrewAI ao seu agente
+
+**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.
+
+<Tabs>
+  <Tab title="Claude Code (Plugin Marketplace)">
+    <img src="https://cdn.simpleicons.org/anthropic/D97706" alt="Anthropic" width="28" style={{display: "inline", verticalAlign: "middle", marginRight: "8px"}} />
+    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 |
+  </Tab>
+  <Tab title="npx (qualquer agente)">
+    Funciona com Claude Code, Codex, Cursor, Gemini CLI ou qualquer agente de codificação:
+    ```shell
+    npx skills add crewaiinc/skills
+    ```
+    Obtido do [registro skills.sh](https://skills.sh/crewaiinc/skills).
+  </Tab>
+</Tabs>
+
+<Steps>
+  <Step title="Instale o pacote oficial de skills">
+    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).
+  </Step>
+  <Step title="Seu agente ganha expertise imediata em CrewAI">
+    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
+  </Step>
+  <Step title="Comece a construir">
+    Seu agente pode estruturar e construir projetos CrewAI sem você precisar reexplicar o framework a cada sessão.
+  </Step>
+</Steps>
+
+<CardGroup cols={2}>
+  <Card title="Conceito de skills" icon="bolt" href="/pt-BR/concepts/skills">
+    Como skills funcionam em agentes CrewAI — injeção, ativação e padrões.
+  </Card>
+  <Card title="Página de skills" icon="wand-magic-sparkles" href="/pt-BR/skills">
+    Visão geral do pacote crewAIInc/skills e do que ele inclui.
+  </Card>
+  <Card title="AGENTS.md e ferramentas" icon="terminal" href="/pt-BR/guides/coding-tools/agents-md">
+    Configure o AGENTS.md para Claude Code, Codex, Cursor e Gemini CLI.
+  </Card>
+  <Card title="Registro skills.sh" icon="globe" href="https://skills.sh/crewaiinc/skills">
+    Listagem oficial — skills, estatísticas de instalação e auditorias.
+  </Card>
+</CardGroup>
+
+---
+
+## 2. llms.txt — documentação legível por máquina
+
+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
+```
+
+<Tabs>
+  <Tab title="O que é llms.txt?">
+    [`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.
+
+    O `llms.txt` do CrewAI **já está no ar** — seu agente pode usar agora.
+  </Tab>
+  <Tab title="Como usar">
+    Indique ao agente de codificação a URL quando precisar da referência do CrewAI:
+
+    ```
+    Fetch https://docs.crewai.com/llms.txt for CrewAI documentation.
+    ```
+
+    Muitos agentes (Claude Code, Cursor etc.) conseguem buscar URLs diretamente. O arquivo contém documentação estruturada sobre conceitos, APIs e guias do CrewAI.
+  </Tab>
+  <Tab title="Por que importa">
+    - **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
+  </Tab>
+</Tabs>
+
+---
+
+## 3. Implantação enterprise
+
+Do crew local à produção no **CrewAI AMP** (Agent Management Platform) em minutos.
+
+<Steps>
+  <Step title="Construa localmente">
+    Estruture e teste seu crew ou flow:
+    ```bash
+    crewai create crew my_crew
+    cd my_crew
+    crewai run
+    ```
+  </Step>
+  <Step title="Prepare a implantação">
+    Garanta que a estrutura do projeto está pronta:
+    ```bash
+    crewai deploy --prepare
+    ```
+    Veja o [guia de preparação](/pt-BR/enterprise/guides/prepare-for-deployment) para detalhes de estrutura e requisitos.
+  </Step>
+  <Step title="Implante no AMP">
+    Envie para a plataforma CrewAI AMP:
+    ```bash
+    crewai deploy
+    ```
+    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).
+  </Step>
+  <Step title="Acesso via API">
+    O crew implantado recebe um endpoint REST. Integre em qualquer aplicação:
+    ```bash
+    curl -X POST https://app.crewai.com/api/v1/crews/<crew-id>/kickoff \
+      -H "Authorization: Bearer $CREWAI_API_KEY" \
+      -H "Content-Type: application/json" \
+      -d '{"inputs": {"topic": "AI agents"}}'
+    ```
+  </Step>
+</Steps>
+
+<CardGroup cols={2}>
+  <Card title="Implantar no AMP" icon="rocket" href="/pt-BR/enterprise/guides/deploy-to-amp">
+    Guia completo de implantação — CLI, GitHub e Crew Studio.
+  </Card>
+  <Card title="Introdução ao AMP" icon="globe" href="/pt-BR/enterprise/introduction">
+    Visão da plataforma — o que o AMP oferece para crews em produção.
+  </Card>
+</CardGroup>
+
+---
+
+## 4. Recursos enterprise
+
+O CrewAI AMP foi feito para equipes em produção. Além da implantação, você obtém:
+
+<CardGroup cols={2}>
+  <Card title="Observabilidade" icon="chart-line">
+    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.
+  </Card>
+  <Card title="Crew Studio" icon="paintbrush">
+    Interface no-code/low-code para criar, personalizar e implantar crews visualmente — exporte para código ou implante direto.
+  </Card>
+  <Card title="Webhook streaming" icon="webhook">
+    Transmita eventos em tempo real das execuções para seus sistemas. Integre com Slack, Zapier ou qualquer consumidor de webhook.
+  </Card>
+  <Card title="Gestão de equipe" icon="users">
+    SSO, RBAC e controles em nível de organização. Gerencie quem pode criar, implantar e acessar crews.
+  </Card>
+  <Card title="Repositório de ferramentas" icon="toolbox">
+    Publique e compartilhe ferramentas customizadas na organização. Instale ferramentas da comunidade a partir do registro.
+  </Card>
+  <Card title="Factory (self-hosted)" icon="server">
+    Execute o CrewAI AMP na sua infraestrutura. Capacidades completas da plataforma com residência de dados e controles de conformidade.
+  </Card>
+</CardGroup>
+
+<AccordionGroup>
+  <Accordion title="Para quem é o AMP?">
+    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.
+  </Accordion>
+  <Accordion title="Quais opções de implantação existem?">
+    - **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
+  </Accordion>
+</AccordionGroup>
+
+<Card title="Conheça o CrewAI AMP →" icon="arrow-right" href="https://app.crewai.com">
+  Cadastre-se e leve seu primeiro crew à produção.
+</Card>

lib/crewai-files/src/crewai_files/__init__.py

@@ -152,4 +152,4 @@ __all__ = [
     "wrap_file_source",
 ]
 
-__version__ = "1.14.3a1"
+__version__ = "1.14.3a2"

lib/crewai-tools/pyproject.toml

@@ -10,7 +10,7 @@ requires-python = ">=3.10, <3.14"
 dependencies = [
     "pytube~=15.0.0",
     "requests>=2.33.0,<3",
-    "crewai==1.14.3a1",
+    "crewai==1.14.3a2",
     "tiktoken~=0.8.0",
     "beautifulsoup4~=4.13.4",
     "python-docx~=1.2.0",
@@ -112,7 +112,7 @@ github = [
 ]
 rag = [
     "python-docx>=1.1.0",
-    "lxml>=5.3.0,<5.4.0",  # Pin to avoid etree import issues in 5.4.0
+    "lxml>=6.1.0,<7",  # 6.1.0+ required for GHSA-vfmq-68hx-4jfw (XXE in iterparse)
 ]
 xml = [
     "unstructured[local-inference, all-docs]>=0.17.2"

lib/crewai-tools/src/crewai_tools/__init__.py

@@ -313,4 +313,4 @@ __all__ = [
     "ZapierActionTools",
 ]
 
-__version__ = "1.14.3a1"
+__version__ = "1.14.3a2"

lib/crewai/pyproject.toml

@@ -24,7 +24,7 @@ dependencies = [
     "tokenizers>=0.21,<1",
     "openpyxl~=3.1.5",
     # Authentication and Security
-    "python-dotenv~=1.1.1",
+    "python-dotenv>=1.2.2,<2",
     "pyjwt>=2.9.0,<3",
     # TUI
     "textual>=7.5.0",
@@ -55,7 +55,7 @@ Repository = "https://github.com/crewAIInc/crewAI"
 
 [project.optional-dependencies]
 tools = [
-    "crewai-tools==1.14.3a1",
+    "crewai-tools==1.14.3a2",
 ]
 embeddings = [
     "tiktoken~=0.8.0"

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.state.checkpoint_config import CheckpointConfig  # noqa: F401
 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:
@@ -46,38 +48,7 @@ def _suppress_pydantic_deprecation_warnings() -> None:
 
 _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()
+__version__ = "1.14.3a2"
 
 _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 @@ try:
     except ImportError:
         pass
 
-    import sys
-
     _full_namespace = {
         **_base_namespace,
         "ToolsHandler": _ToolsHandler,
@@ -191,10 +158,6 @@ try:
     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[

lib/crewai/src/crewai/agent/core.py

@@ -78,8 +78,7 @@ from crewai.knowledge.knowledge import Knowledge
 from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
 from crewai.lite_agent_output import LiteAgentOutput
 from crewai.llms.base_llm import BaseLLM
-from crewai.mcp import MCPServerConfig
-from crewai.mcp.tool_resolver import MCPToolResolver
+from crewai.mcp.config import MCPServerConfig
 from crewai.rag.embeddings.types import EmbedderConfig
 from crewai.security.fingerprint import Fingerprint
 from crewai.skills.loader import activate_skill, discover_skills
@@ -119,6 +118,7 @@ if TYPE_CHECKING:
 
     from crewai.a2a.config import A2AClientConfig, A2AConfig, A2AServerConfig
     from crewai.agents.agent_builder.base_agent import PlatformAppOrAction
+    from crewai.mcp.tool_resolver import MCPToolResolver
     from crewai.task import Task
     from crewai.tools.base_tool import BaseTool
     from crewai.tools.structured_tool import CrewStructuredTool
@@ -1120,6 +1120,8 @@ class Agent(BaseAgent):
         Delegates to :class:`~crewai.mcp.tool_resolver.MCPToolResolver`.
         """
         self._cleanup_mcp_clients()
+        from crewai.mcp.tool_resolver import MCPToolResolver
+
         self._mcp_resolver = MCPToolResolver(agent=self, logger=self._logger)
         return self._mcp_resolver.resolve(mcps)
 

lib/crewai/src/crewai/cli/templates/crew/pyproject.toml

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<3.14"
 dependencies = [
-    "crewai[tools]==1.14.3a1"
+    "crewai[tools]==1.14.3a2"
 ]
 
 [project.scripts]

lib/crewai/src/crewai/cli/templates/flow/pyproject.toml

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<3.14"
 dependencies = [
-    "crewai[tools]==1.14.3a1"
+    "crewai[tools]==1.14.3a2"
 ]
 
 [project.scripts]

lib/crewai/src/crewai/cli/templates/tool/pyproject.toml

@@ -5,7 +5,7 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<3.14"
 dependencies = [
-    "crewai[tools]==1.14.3a1"
+    "crewai[tools]==1.14.3a2"
 ]
 
 [tool.crewai]

lib/crewai/src/crewai/events/__init__.py

@@ -6,112 +6,20 @@ This module provides the event infrastructure that allows users to:
 - Build custom logging and analytics
 - Extend CrewAI with custom event handlers
 - Declare handler dependencies for ordered execution
+
+Event type classes are lazy-loaded on first access to avoid importing
+~12 Pydantic model modules (and their transitive deps) at package init time.
 """
 
 from __future__ import annotations
 
+import importlib
 from typing import TYPE_CHECKING, Any
 
 from crewai.events.base_event_listener import BaseEventListener
 from crewai.events.depends import Depends
 from crewai.events.event_bus import crewai_event_bus
 from crewai.events.handler_graph import CircularDependencyError
-from crewai.events.types.crew_events import (
-    CrewKickoffCompletedEvent,
-    CrewKickoffFailedEvent,
-    CrewKickoffStartedEvent,
-    CrewTestCompletedEvent,
-    CrewTestFailedEvent,
-    CrewTestResultEvent,
-    CrewTestStartedEvent,
-    CrewTrainCompletedEvent,
-    CrewTrainFailedEvent,
-    CrewTrainStartedEvent,
-)
-from crewai.events.types.flow_events import (
-    FlowCreatedEvent,
-    FlowEvent,
-    FlowFinishedEvent,
-    FlowPlotEvent,
-    FlowStartedEvent,
-    HumanFeedbackReceivedEvent,
-    HumanFeedbackRequestedEvent,
-    MethodExecutionFailedEvent,
-    MethodExecutionFinishedEvent,
-    MethodExecutionStartedEvent,
-)
-from crewai.events.types.knowledge_events import (
-    KnowledgeQueryCompletedEvent,
-    KnowledgeQueryFailedEvent,
-    KnowledgeQueryStartedEvent,
-    KnowledgeRetrievalCompletedEvent,
-    KnowledgeRetrievalStartedEvent,
-    KnowledgeSearchQueryFailedEvent,
-)
-from crewai.events.types.llm_events import (
-    LLMCallCompletedEvent,
-    LLMCallFailedEvent,
-    LLMCallStartedEvent,
-    LLMStreamChunkEvent,
-)
-from crewai.events.types.llm_guardrail_events import (
-    LLMGuardrailCompletedEvent,
-    LLMGuardrailStartedEvent,
-)
-from crewai.events.types.logging_events import (
-    AgentLogsExecutionEvent,
-    AgentLogsStartedEvent,
-)
-from crewai.events.types.mcp_events import (
-    MCPConfigFetchFailedEvent,
-    MCPConnectionCompletedEvent,
-    MCPConnectionFailedEvent,
-    MCPConnectionStartedEvent,
-    MCPToolExecutionCompletedEvent,
-    MCPToolExecutionFailedEvent,
-    MCPToolExecutionStartedEvent,
-)
-from crewai.events.types.memory_events import (
-    MemoryQueryCompletedEvent,
-    MemoryQueryFailedEvent,
-    MemoryQueryStartedEvent,
-    MemoryRetrievalCompletedEvent,
-    MemoryRetrievalFailedEvent,
-    MemoryRetrievalStartedEvent,
-    MemorySaveCompletedEvent,
-    MemorySaveFailedEvent,
-    MemorySaveStartedEvent,
-)
-from crewai.events.types.reasoning_events import (
-    AgentReasoningCompletedEvent,
-    AgentReasoningFailedEvent,
-    AgentReasoningStartedEvent,
-    ReasoningEvent,
-)
-from crewai.events.types.skill_events import (
-    SkillActivatedEvent,
-    SkillDiscoveryCompletedEvent,
-    SkillDiscoveryStartedEvent,
-    SkillEvent,
-    SkillLoadFailedEvent,
-    SkillLoadedEvent,
-)
-from crewai.events.types.task_events import (
-    TaskCompletedEvent,
-    TaskEvaluationEvent,
-    TaskFailedEvent,
-    TaskStartedEvent,
-)
-from crewai.events.types.tool_usage_events import (
-    ToolExecutionErrorEvent,
-    ToolSelectionErrorEvent,
-    ToolUsageErrorEvent,
-    ToolUsageEvent,
-    ToolUsageFinishedEvent,
-    ToolUsageStartedEvent,
-    ToolValidateInputErrorEvent,
-)
-
 
 if TYPE_CHECKING:
     from crewai.events.types.agent_events import (
@@ -125,6 +33,223 @@ if TYPE_CHECKING:
         LiteAgentExecutionErrorEvent,
         LiteAgentExecutionStartedEvent,
     )
+    from crewai.events.types.crew_events import (
+        CrewKickoffCompletedEvent,
+        CrewKickoffFailedEvent,
+        CrewKickoffStartedEvent,
+        CrewTestCompletedEvent,
+        CrewTestFailedEvent,
+        CrewTestResultEvent,
+        CrewTestStartedEvent,
+        CrewTrainCompletedEvent,
+        CrewTrainFailedEvent,
+        CrewTrainStartedEvent,
+    )
+    from crewai.events.types.flow_events import (
+        FlowCreatedEvent,
+        FlowEvent,
+        FlowFinishedEvent,
+        FlowPlotEvent,
+        FlowStartedEvent,
+        HumanFeedbackReceivedEvent,
+        HumanFeedbackRequestedEvent,
+        MethodExecutionFailedEvent,
+        MethodExecutionFinishedEvent,
+        MethodExecutionStartedEvent,
+    )
+    from crewai.events.types.knowledge_events import (
+        KnowledgeQueryCompletedEvent,
+        KnowledgeQueryFailedEvent,
+        KnowledgeQueryStartedEvent,
+        KnowledgeRetrievalCompletedEvent,
+        KnowledgeRetrievalStartedEvent,
+        KnowledgeSearchQueryFailedEvent,
+    )
+    from crewai.events.types.llm_events import (
+        LLMCallCompletedEvent,
+        LLMCallFailedEvent,
+        LLMCallStartedEvent,
+        LLMStreamChunkEvent,
+    )
+    from crewai.events.types.llm_guardrail_events import (
+        LLMGuardrailCompletedEvent,
+        LLMGuardrailStartedEvent,
+    )
+    from crewai.events.types.logging_events import (
+        AgentLogsExecutionEvent,
+        AgentLogsStartedEvent,
+    )
+    from crewai.events.types.mcp_events import (
+        MCPConfigFetchFailedEvent,
+        MCPConnectionCompletedEvent,
+        MCPConnectionFailedEvent,
+        MCPConnectionStartedEvent,
+        MCPToolExecutionCompletedEvent,
+        MCPToolExecutionFailedEvent,
+        MCPToolExecutionStartedEvent,
+    )
+    from crewai.events.types.memory_events import (
+        MemoryQueryCompletedEvent,
+        MemoryQueryFailedEvent,
+        MemoryQueryStartedEvent,
+        MemoryRetrievalCompletedEvent,
+        MemoryRetrievalFailedEvent,
+        MemoryRetrievalStartedEvent,
+        MemorySaveCompletedEvent,
+        MemorySaveFailedEvent,
+        MemorySaveStartedEvent,
+    )
+    from crewai.events.types.reasoning_events import (
+        AgentReasoningCompletedEvent,
+        AgentReasoningFailedEvent,
+        AgentReasoningStartedEvent,
+        ReasoningEvent,
+    )
+    from crewai.events.types.skill_events import (
+        SkillActivatedEvent,
+        SkillDiscoveryCompletedEvent,
+        SkillDiscoveryStartedEvent,
+        SkillEvent,
+        SkillLoadFailedEvent,
+        SkillLoadedEvent,
+    )
+    from crewai.events.types.task_events import (
+        TaskCompletedEvent,
+        TaskEvaluationEvent,
+        TaskFailedEvent,
+        TaskStartedEvent,
+    )
+    from crewai.events.types.tool_usage_events import (
+        ToolExecutionErrorEvent,
+        ToolSelectionErrorEvent,
+        ToolUsageErrorEvent,
+        ToolUsageEvent,
+        ToolUsageFinishedEvent,
+        ToolUsageStartedEvent,
+        ToolValidateInputErrorEvent,
+    )
+
+# Map every event class name → its module path for lazy loading
+_LAZY_EVENT_MAPPING: dict[str, str] = {
+    # agent_events
+    "AgentEvaluationCompletedEvent": "crewai.events.types.agent_events",
+    "AgentEvaluationFailedEvent": "crewai.events.types.agent_events",
+    "AgentEvaluationStartedEvent": "crewai.events.types.agent_events",
+    "AgentExecutionCompletedEvent": "crewai.events.types.agent_events",
+    "AgentExecutionErrorEvent": "crewai.events.types.agent_events",
+    "AgentExecutionStartedEvent": "crewai.events.types.agent_events",
+    "LiteAgentExecutionCompletedEvent": "crewai.events.types.agent_events",
+    "LiteAgentExecutionErrorEvent": "crewai.events.types.agent_events",
+    "LiteAgentExecutionStartedEvent": "crewai.events.types.agent_events",
+    # crew_events
+    "CrewKickoffCompletedEvent": "crewai.events.types.crew_events",
+    "CrewKickoffFailedEvent": "crewai.events.types.crew_events",
+    "CrewKickoffStartedEvent": "crewai.events.types.crew_events",
+    "CrewTestCompletedEvent": "crewai.events.types.crew_events",
+    "CrewTestFailedEvent": "crewai.events.types.crew_events",
+    "CrewTestResultEvent": "crewai.events.types.crew_events",
+    "CrewTestStartedEvent": "crewai.events.types.crew_events",
+    "CrewTrainCompletedEvent": "crewai.events.types.crew_events",
+    "CrewTrainFailedEvent": "crewai.events.types.crew_events",
+    "CrewTrainStartedEvent": "crewai.events.types.crew_events",
+    # flow_events
+    "FlowCreatedEvent": "crewai.events.types.flow_events",
+    "FlowEvent": "crewai.events.types.flow_events",
+    "FlowFinishedEvent": "crewai.events.types.flow_events",
+    "FlowPlotEvent": "crewai.events.types.flow_events",
+    "FlowStartedEvent": "crewai.events.types.flow_events",
+    "HumanFeedbackReceivedEvent": "crewai.events.types.flow_events",
+    "HumanFeedbackRequestedEvent": "crewai.events.types.flow_events",
+    "MethodExecutionFailedEvent": "crewai.events.types.flow_events",
+    "MethodExecutionFinishedEvent": "crewai.events.types.flow_events",
+    "MethodExecutionStartedEvent": "crewai.events.types.flow_events",
+    # knowledge_events
+    "KnowledgeQueryCompletedEvent": "crewai.events.types.knowledge_events",
+    "KnowledgeQueryFailedEvent": "crewai.events.types.knowledge_events",
+    "KnowledgeQueryStartedEvent": "crewai.events.types.knowledge_events",
+    "KnowledgeRetrievalCompletedEvent": "crewai.events.types.knowledge_events",
+    "KnowledgeRetrievalStartedEvent": "crewai.events.types.knowledge_events",
+    "KnowledgeSearchQueryFailedEvent": "crewai.events.types.knowledge_events",
+    # llm_events
+    "LLMCallCompletedEvent": "crewai.events.types.llm_events",
+    "LLMCallFailedEvent": "crewai.events.types.llm_events",
+    "LLMCallStartedEvent": "crewai.events.types.llm_events",
+    "LLMStreamChunkEvent": "crewai.events.types.llm_events",
+    # llm_guardrail_events
+    "LLMGuardrailCompletedEvent": "crewai.events.types.llm_guardrail_events",
+    "LLMGuardrailStartedEvent": "crewai.events.types.llm_guardrail_events",
+    # logging_events
+    "AgentLogsExecutionEvent": "crewai.events.types.logging_events",
+    "AgentLogsStartedEvent": "crewai.events.types.logging_events",
+    # mcp_events
+    "MCPConfigFetchFailedEvent": "crewai.events.types.mcp_events",
+    "MCPConnectionCompletedEvent": "crewai.events.types.mcp_events",
+    "MCPConnectionFailedEvent": "crewai.events.types.mcp_events",
+    "MCPConnectionStartedEvent": "crewai.events.types.mcp_events",
+    "MCPToolExecutionCompletedEvent": "crewai.events.types.mcp_events",
+    "MCPToolExecutionFailedEvent": "crewai.events.types.mcp_events",
+    "MCPToolExecutionStartedEvent": "crewai.events.types.mcp_events",
+    # memory_events
+    "MemoryQueryCompletedEvent": "crewai.events.types.memory_events",
+    "MemoryQueryFailedEvent": "crewai.events.types.memory_events",
+    "MemoryQueryStartedEvent": "crewai.events.types.memory_events",
+    "MemoryRetrievalCompletedEvent": "crewai.events.types.memory_events",
+    "MemoryRetrievalFailedEvent": "crewai.events.types.memory_events",
+    "MemoryRetrievalStartedEvent": "crewai.events.types.memory_events",
+    "MemorySaveCompletedEvent": "crewai.events.types.memory_events",
+    "MemorySaveFailedEvent": "crewai.events.types.memory_events",
+    "MemorySaveStartedEvent": "crewai.events.types.memory_events",
+    # reasoning_events
+    "AgentReasoningCompletedEvent": "crewai.events.types.reasoning_events",
+    "AgentReasoningFailedEvent": "crewai.events.types.reasoning_events",
+    "AgentReasoningStartedEvent": "crewai.events.types.reasoning_events",
+    "ReasoningEvent": "crewai.events.types.reasoning_events",
+    # skill_events
+    "SkillActivatedEvent": "crewai.events.types.skill_events",
+    "SkillDiscoveryCompletedEvent": "crewai.events.types.skill_events",
+    "SkillDiscoveryStartedEvent": "crewai.events.types.skill_events",
+    "SkillEvent": "crewai.events.types.skill_events",
+    "SkillLoadFailedEvent": "crewai.events.types.skill_events",
+    "SkillLoadedEvent": "crewai.events.types.skill_events",
+    # task_events
+    "TaskCompletedEvent": "crewai.events.types.task_events",
+    "TaskEvaluationEvent": "crewai.events.types.task_events",
+    "TaskFailedEvent": "crewai.events.types.task_events",
+    "TaskStartedEvent": "crewai.events.types.task_events",
+    # tool_usage_events
+    "ToolExecutionErrorEvent": "crewai.events.types.tool_usage_events",
+    "ToolSelectionErrorEvent": "crewai.events.types.tool_usage_events",
+    "ToolUsageErrorEvent": "crewai.events.types.tool_usage_events",
+    "ToolUsageEvent": "crewai.events.types.tool_usage_events",
+    "ToolUsageFinishedEvent": "crewai.events.types.tool_usage_events",
+    "ToolUsageStartedEvent": "crewai.events.types.tool_usage_events",
+    "ToolValidateInputErrorEvent": "crewai.events.types.tool_usage_events",
+}
+
+_extension_exports: dict[str, Any] = {}
+
+
+def __getattr__(name: str) -> Any:
+    """Lazy import for event types and registered extensions."""
+    if name in _LAZY_EVENT_MAPPING:
+        module_path = _LAZY_EVENT_MAPPING[name]
+        module = importlib.import_module(module_path)
+        val = getattr(module, name)
+        globals()[name] = val  # cache for subsequent access
+        return val
+
+    if name in _extension_exports:
+        value = _extension_exports[name]
+        if isinstance(value, str):
+            module_path, _, attr_name = value.rpartition(".")
+            if module_path:
+                module = importlib.import_module(module_path)
+                return getattr(module, attr_name)
+            return importlib.import_module(value)
+        return value
+
+    msg = f"module {__name__!r} has no attribute {name!r}"
+    raise AttributeError(msg)
 
 
 __all__ = [
@@ -214,42 +339,3 @@ __all__ = [
     "_extension_exports",
     "crewai_event_bus",
 ]
-
-_AGENT_EVENT_MAPPING = {
-    "AgentEvaluationCompletedEvent": "crewai.events.types.agent_events",
-    "AgentEvaluationFailedEvent": "crewai.events.types.agent_events",
-    "AgentEvaluationStartedEvent": "crewai.events.types.agent_events",
-    "AgentExecutionCompletedEvent": "crewai.events.types.agent_events",
-    "AgentExecutionErrorEvent": "crewai.events.types.agent_events",
-    "AgentExecutionStartedEvent": "crewai.events.types.agent_events",
-    "LiteAgentExecutionCompletedEvent": "crewai.events.types.agent_events",
-    "LiteAgentExecutionErrorEvent": "crewai.events.types.agent_events",
-    "LiteAgentExecutionStartedEvent": "crewai.events.types.agent_events",
-}
-
-_extension_exports: dict[str, Any] = {}
-
-
-def __getattr__(name: str) -> Any:
-    """Lazy import for agent events and registered extensions."""
-    if name in _AGENT_EVENT_MAPPING:
-        import importlib
-
-        module_path = _AGENT_EVENT_MAPPING[name]
-        module = importlib.import_module(module_path)
-        return getattr(module, name)
-
-    if name in _extension_exports:
-        import importlib
-
-        value = _extension_exports[name]
-        if isinstance(value, str):
-            module_path, _, attr_name = value.rpartition(".")
-            if module_path:
-                module = importlib.import_module(module_path)
-                return getattr(module, attr_name)
-            return importlib.import_module(value)
-        return value
-
-    msg = f"module {__name__!r} has no attribute {name!r}"
-    raise AttributeError(msg)

lib/crewai/src/crewai/events/listeners/tracing/trace_batch_manager.py

@@ -81,8 +81,11 @@ class TraceBatchManager:
         """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
 

lib/crewai/src/crewai/events/listeners/tracing/trace_listener.py

@@ -60,12 +60,6 @@ from crewai.events.types.crew_events import (
     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 @@ class TraceCollectionListener(BaseEventListener):
             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 @@ class TraceCollectionListener(BaseEventListener):
 
         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 @@ class TraceCollectionListener(BaseEventListener):
             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)

lib/crewai/src/crewai/flow/flow.py

@@ -1503,6 +1503,8 @@ class Flow(BaseModel, Generic[T], metaclass=FlowMeta):
                 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 @@ class Flow(BaseModel, Generic[T], metaclass=FlowMeta):
         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 @@ class Flow(BaseModel, Generic[T], metaclass=FlowMeta):
                     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)
 

lib/crewai/src/crewai/llm.py

@@ -175,6 +175,16 @@ LLM_CONTEXT_WINDOW_SIZES: Final[dict[str, int]] = {
     "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 @@ LLM_CONTEXT_WINDOW_SIZES: Final[dict[str, int]] = {
     "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,

lib/crewai/src/crewai/llms/constants.py

@@ -423,6 +423,34 @@ AZURE_MODELS: list[AzureModels] = [
 
 
 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 @@ BedrockModels: TypeAlias = Literal[
     "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",

lib/crewai/src/crewai/llms/providers/bedrock/completion.py

@@ -2075,6 +2075,9 @@ class BedrockCompletion(BaseLLM):
 
         # Context window sizes for common Bedrock models
         context_windows = {
+            "anthropic.claude-sonnet-4": 200000,
+            "anthropic.claude-opus-4": 200000,
+            "anthropic.claude-haiku-4": 200000,
             "anthropic.claude-3-5-sonnet": 200000,
             "anthropic.claude-3-5-haiku": 200000,
             "anthropic.claude-3-opus": 200000,

lib/crewai/src/crewai/mcp/__init__.py

@@ -2,9 +2,17 @@
 
 This module provides native MCP client functionality, allowing CrewAI agents
 to connect to any MCP-compliant server using various transport types.
+
+Heavy imports (MCPClient, MCPToolResolver, BaseTransport, TransportType) are
+lazy-loaded on first access to avoid pulling in the ``mcp`` SDK (~400ms)
+when only lightweight config/filter types are needed.
 """
 
-from crewai.mcp.client import MCPClient
+from __future__ import annotations
+
+import importlib
+from typing import TYPE_CHECKING, Any
+
 from crewai.mcp.config import (
     MCPServerConfig,
     MCPServerHTTP,
@@ -18,8 +26,28 @@ from crewai.mcp.filters import (
     create_dynamic_tool_filter,
     create_static_tool_filter,
 )
-from crewai.mcp.tool_resolver import MCPToolResolver
-from crewai.mcp.transports.base import BaseTransport, TransportType
+
+if TYPE_CHECKING:
+    from crewai.mcp.client import MCPClient
+    from crewai.mcp.tool_resolver import MCPToolResolver
+    from crewai.mcp.transports.base import BaseTransport, TransportType
+
+_LAZY: dict[str, tuple[str, str]] = {
+    "MCPClient": ("crewai.mcp.client", "MCPClient"),
+    "MCPToolResolver": ("crewai.mcp.tool_resolver", "MCPToolResolver"),
+    "BaseTransport": ("crewai.mcp.transports.base", "BaseTransport"),
+    "TransportType": ("crewai.mcp.transports.base", "TransportType"),
+}
+
+
+def __getattr__(name: str) -> Any:
+    if name in _LAZY:
+        mod_path, attr = _LAZY[name]
+        mod = importlib.import_module(mod_path)
+        val = getattr(mod, attr)
+        globals()[name] = val  # cache for subsequent access
+        return val
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
 
 
 __all__ = [

lib/crewai/src/crewai/project/annotations.py

@@ -237,6 +237,8 @@ def 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

lib/crewai/src/crewai/task.py

@@ -32,6 +32,7 @@ from pydantic import (
     field_validator,
     model_validator,
 )
+from pydantic.functional_serializers import PlainSerializer
 from pydantic_core import PydanticCustomError
 from typing_extensions import Self
 
@@ -86,6 +87,22 @@ from crewai.utilities.printer import PRINTER
 from crewai.utilities.string_utils import interpolate_only
 
 
+def _serialize_model_class(v: type[BaseModel] | None) -> dict[str, Any] | None:
+    """Serialize a Pydantic model class reference to its JSON schema."""
+    return v.model_json_schema() if v else None
+
+
+def _deserialize_model_class(v: Any) -> type[BaseModel] | None:
+    """Hydrate a model class reference from checkpoint data."""
+    if v is None or isinstance(v, type):
+        return v
+    if isinstance(v, dict):
+        from crewai.utilities.pydantic_schema_utils import create_model_from_schema
+
+        return create_model_from_schema(v)
+    return None
+
+
 class Task(BaseModel):
     """Class that represents a task to be executed.
 
@@ -141,15 +158,33 @@ class Task(BaseModel):
         description="Whether the task should be executed asynchronously or not.",
         default=False,
     )
-    output_json: type[BaseModel] | None = Field(
+    output_json: Annotated[
+        type[BaseModel] | None,
+        BeforeValidator(_deserialize_model_class),
+        PlainSerializer(
+            _serialize_model_class, return_type=dict | None, when_used="json"
+        ),
+    ] = Field(
         description="A Pydantic model to be used to create a JSON output.",
         default=None,
     )
-    output_pydantic: type[BaseModel] | None = Field(
+    output_pydantic: Annotated[
+        type[BaseModel] | None,
+        BeforeValidator(_deserialize_model_class),
+        PlainSerializer(
+            _serialize_model_class, return_type=dict | None, when_used="json"
+        ),
+    ] = Field(
         description="A Pydantic model to be used to create a Pydantic output.",
         default=None,
     )
-    response_model: type[BaseModel] | None = Field(
+    response_model: Annotated[
+        type[BaseModel] | None,
+        BeforeValidator(_deserialize_model_class),
+        PlainSerializer(
+            _serialize_model_class, return_type=dict | None, when_used="json"
+        ),
+    ] = Field(
         description="A Pydantic model for structured LLM outputs using native provider features.",
         default=None,
     )
@@ -189,7 +224,13 @@ class Task(BaseModel):
         description="Whether the task should instruct the agent to return the final answer formatted in Markdown",
         default=False,
     )
-    converter_cls: type[Converter] | None = Field(
+    converter_cls: Annotated[
+        type[Converter] | None,
+        BeforeValidator(lambda v: v if v is None or isinstance(v, type) else None),
+        PlainSerializer(
+            _serialize_model_class, return_type=dict | None, when_used="json"
+        ),
+    ] = Field(
         description="A converter class used to export structured output",
         default=None,
     )

lib/crewai/tests/test_crew.py

@@ -8,6 +8,7 @@ from concurrent.futures import Future
 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.crew import Crew
 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."""

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!'"""

lib/crewai/tests/tracing/test_tracing.py

@@ -1640,3 +1640,43 @@ class TestBackendInitializedGatedOnSuccess:
 
         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"

lib/devtools/pyproject.toml

@@ -13,7 +13,7 @@ dependencies = [
     "click~=8.1.7",
     "tomlkit~=0.13.2",
     "openai>=1.83.0,<3",
-    "python-dotenv~=1.1.1",
+    "python-dotenv>=1.2.2,<2",
     "pygithub~=1.59.1",
     "rich>=13.9.4",
 ]

lib/devtools/src/crewai_devtools/__init__.py

@@ -1,3 +1,3 @@
 """CrewAI development tools."""
 
-__version__ = "1.14.3a1"
+__version__ = "1.14.3a2"

pyproject.toml

@@ -164,7 +164,7 @@ info = "Commits must follow Conventional Commits 1.0.0."
 [tool.uv]
 # Pinned to include the security patch releases (authlib 1.6.11,
 # langchain-text-splitters 1.1.2) uploaded on 2026-04-16.
-exclude-newer = "2026-04-17"
+exclude-newer = "2026-04-22"
 
 # composio-core pins rich<14 but textual requires rich>=14.
 # onnxruntime 1.24+ dropped Python 3.10 wheels; cap it so qdrant[fastembed] resolves on 3.10.

scripts/benchmark_import_time.py

@@ -0,0 +1,76 @@
+#!/usr/bin/env python3
+"""Benchmark `import crewai` cold start time.
+
+Usage:
+    python scripts/benchmark_import_time.py [--runs N] [--json]
+
+Spawns a fresh Python subprocess for each run to ensure cold imports.
+Prints median, mean, min, max across all runs.
+With --json, outputs machine-readable results for CI.
+"""
+import argparse
+import json
+import statistics
+import subprocess
+import sys
+
+
+IMPORT_SCRIPT = "import time; t0 = time.perf_counter(); import crewai; print(time.perf_counter() - t0)"
+
+
+def measure_import(python: str = sys.executable) -> float:
+    """Run a single cold-import measurement in a subprocess."""
+    result = subprocess.run(
+        [python, "-c", IMPORT_SCRIPT],
+        capture_output=True,
+        text=True,
+        env={"PATH": "", "VIRTUAL_ENV": "", "PYTHONPATH": ""},
+        timeout=30,
+    )
+    if result.returncode != 0:
+        raise RuntimeError(f"Import failed: {result.stderr.strip()}")
+    return float(result.stdout.strip())
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Benchmark crewai import time")
+    parser.add_argument("--runs", type=int, default=5, help="Number of runs (default: 5)")
+    parser.add_argument("--json", action="store_true", help="Output JSON for CI")
+    parser.add_argument("--threshold", type=float, default=None,
+                        help="Fail if median exceeds this value (seconds)")
+    args = parser.parse_args()
+
+    times = []
+    for i in range(args.runs):
+        t = measure_import()
+        times.append(t)
+        if not args.json:
+            print(f"  Run {i + 1}: {t:.3f}s")
+
+    median = statistics.median(times)
+    mean = statistics.mean(times)
+    stdev = statistics.stdev(times) if len(times) > 1 else 0.0
+
+    result = {
+        "runs": args.runs,
+        "median_s": round(median, 3),
+        "mean_s": round(mean, 3),
+        "stdev_s": round(stdev, 3),
+        "min_s": round(min(times), 3),
+        "max_s": round(max(times), 3),
+    }
+
+    if args.json:
+        print(json.dumps(result))
+    else:
+        print(f"\n  Median: {median:.3f}s")
+        print(f"  Mean:   {mean:.3f}s ± {stdev:.3f}s")
+        print(f"  Range:  {min(times):.3f}s – {max(times):.3f}s")
+
+    if args.threshold and median > args.threshold:
+        print(f"\n  ❌ FAILED: median {median:.3f}s exceeds threshold {args.threshold:.3f}s")
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()

tests/tools/test_linear_tool.py

@@ -1,57 +0,0 @@
-"""
-Test script for LinearTool — runs against the real Linear API.
-
-Usage:
-    LINEAR_API_KEY=lin_api_xxxxxxxxxxxx python tests/tools/test_linear_tool.py
-
-Set LINEAR_API_KEY to your actual Personal API key from:
-  https://linear.app/settings/api  (Profile → API → Personal API keys)
-"""
-
-import json
-import os
-import sys
-
-from crewai.tools.linear_tool import LinearAction, LinearTool
-
-
-def pretty(data: object) -> str:
-    return json.dumps(data, indent=2, default=str)
-
-
-def run_test(tool: LinearTool, label: str, action: LinearAction, first: int = 5) -> None:
-    print(f"\n{'─' * 60}")
-    print(f"  {label}")
-    print(f"{'─' * 60}")
-    try:
-        result = tool._run(action=action, first=first)
-        if not result:
-            print("  (no records returned)")
-        else:
-            print(pretty(result))
-    except Exception as exc:
-        print(f"  ERROR: {exc}", file=sys.stderr)
-
-
-def main() -> None:
-    if not os.environ.get("LINEAR_API_KEY"):
-        print(
-            "ERROR: Set LINEAR_API_KEY before running.\n"
-            "  export LINEAR_API_KEY=lin_api_xxxxxxxxxxxx",
-            file=sys.stderr,
-        )
-        sys.exit(1)
-
-    tool = LinearTool()
-
-    run_test(tool, "My assigned issues (up to 5)", LinearAction.MY_ISSUES, first=5)
-    run_test(tool, "Teams (up to 10)", LinearAction.LIST_TEAMS, first=10)
-    run_test(tool, "Projects (up to 10)", LinearAction.LIST_PROJECTS, first=10)
-
-    print(f"\n{'─' * 60}")
-    print("  All tests complete.")
-    print(f"{'─' * 60}\n")
-
-
-if __name__ == "__main__":
-    main()

uv.lock

@@ -13,7 +13,7 @@ resolution-markers = [
 ]
 
 [options]
-exclude-newer = "2026-04-18T07:00:00Z"
+exclude-newer = "2026-04-17T16:00:00Z"
 
 [manifest]
 members = [
@@ -615,7 +615,7 @@ wheels = [
 
 [[package]]
 name = "bedrock-agentcore"
-version = "1.3.2"
+version = "1.6.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "boto3" },
@@ -627,9 +627,9 @@ dependencies = [
     { name = "uvicorn" },
     { name = "websockets" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/05/90/a11e5a3208b7f607a3eabc8567b7c36767c6e094ec8128fba7ed2f5b3020/bedrock_agentcore-1.3.2.tar.gz", hash = "sha256:1dfae10fd315e078c002e49fd9d9686c41aee71ec8495f21e898a1ef3f782fa3", size = 421197, upload-time = "2026-02-23T20:52:56.202Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/ca/f6/2884c954343e794e3419348f5ffb0276a26f57b30af11f9fe63c4ca535c0/bedrock_agentcore-1.6.0.tar.gz", hash = "sha256:7ea176c3226dc6af8c399a8f9abb58629948cd8ed8675ece9f2f32b94e861b92", size = 512010, upload-time = "2026-03-31T23:10:06.561Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/36/b7/a5cc566901af27314408b95701f8e1d9c286b0aecfa50fc76c53d73efa6f/bedrock_agentcore-1.3.2-py3-none-any.whl", hash = "sha256:3a4e7122f777916f8bd74b42f29eb881415e37fda784a5ff8fab3c813b921706", size = 121703, upload-time = "2026-02-23T20:52:55.038Z" },
+    { url = "https://files.pythonhosted.org/packages/a2/f8/bcf158979324f4f4d171588afffadb2154fa8499701290bfc7bdaf82bd3a/bedrock_agentcore-1.6.0-py3-none-any.whl", hash = "sha256:a4cd02f2bfb80fcc7a8c8835be8d55c778339f8286b071ac3aae579460dd2eb2", size = 164034, upload-time = "2026-03-31T23:10:04.902Z" },
 ]
 
 [[package]]
@@ -719,7 +719,7 @@ wheels = [
 
 [[package]]
 name = "build"
-version = "1.4.2"
+version = "1.4.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "colorama", marker = "os_name == 'nt'" },
@@ -728,9 +728,9 @@ dependencies = [
     { name = "pyproject-hooks" },
     { name = "tomli", marker = "python_full_version < '3.11'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/6c/1d/ab15c8ac57f4ee8778d7633bc6685f808ab414437b8644f555389cdc875e/build-1.4.2.tar.gz", hash = "sha256:35b14e1ee329c186d3f08466003521ed7685ec15ecffc07e68d706090bf161d1", size = 83433, upload-time = "2026-03-25T14:20:27.659Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/3f/16/4b272700dea44c1d2e8ca963ebb3c684efe22b3eba8cfa31c5fdb60de707/build-1.4.3.tar.gz", hash = "sha256:5aa4231ae0e807efdf1fd0623e07366eca2ab215921345a2e38acdd5d0fa0a74", size = 89314, upload-time = "2026-04-10T21:25:40.857Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/4a/57/3b7d4dd193ade4641c865bc2b93aeeb71162e81fc348b8dad020215601ed/build-1.4.2-py3-none-any.whl", hash = "sha256:7a4d8651ea877cb2a89458b1b198f2e69f536c95e89129dbf5d448045d60db88", size = 24643, upload-time = "2026-03-25T14:20:26.568Z" },
+    { url = "https://files.pythonhosted.org/packages/b2/30/f169e1d8b2071beaf8b97088787e30662b1d8fb82f8c0941d14678c0cbf1/build-1.4.3-py3-none-any.whl", hash = "sha256:1bc22b19b383303de8f2c8554c9a32894a58d3f185fe3756b0b20d255bee9a38", size = 26171, upload-time = "2026-04-10T21:25:39.671Z" },
 ]
 
 [[package]]
@@ -1002,7 +1002,7 @@ wheels = [
 
 [[package]]
 name = "commitizen"
-version = "4.13.9"
+version = "4.13.10"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "argcomplete" },
@@ -1019,9 +1019,9 @@ dependencies = [
     { name = "tomlkit" },
     { name = "typing-extensions", marker = "python_full_version < '3.11'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/a6/44/10f95e8178ab5a584298726a4a94ceb83a7f77e00741fec4680df05fedd5/commitizen-4.13.9.tar.gz", hash = "sha256:2b4567ed50555e10920e5bd804a6a4e2c42ec70bb74f14a83f2680fe9eaf9727", size = 64145, upload-time = "2026-02-25T02:40:05.326Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/37/95/da2c71ed6a1c06836cdd4eb60a8b9e1bf05f4ce7029ab508081745171be9/commitizen-4.13.10.tar.gz", hash = "sha256:402b5bcd466be69ba79a3f380be6ba5b55ac658c7d2a93e82fc99668a6eb2673", size = 64106, upload-time = "2026-04-11T06:49:12.907Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/28/22/9b14ee0f17f0aad219a2fb37a293a57b8324d9d195c6ef6807bcd0bf2055/commitizen-4.13.9-py3-none-any.whl", hash = "sha256:d2af3d6a83cacec9d5200e17768942c5de6266f93d932c955986c60c4285f2db", size = 85373, upload-time = "2026-02-25T02:40:03.83Z" },
+    { url = "https://files.pythonhosted.org/packages/11/3a/ad70b3c7dc3da1255668a9396429b1d820c15b74a501668158e4574c1edd/commitizen-4.13.10-py3-none-any.whl", hash = "sha256:95a281317990ac613501fdfe65745cec1fa4042bc5d003a72d332a74926e3039", size = 85746, upload-time = "2026-04-11T06:49:11.167Z" },
 ]
 
 [[package]]
@@ -1382,7 +1382,7 @@ requires-dist = [
     { name = "pydantic", specifier = "~=2.11.9" },
     { name = "pydantic-settings", specifier = "~=2.10.1" },
     { name = "pyjwt", specifier = ">=2.9.0,<3" },
-    { name = "python-dotenv", specifier = "~=1.1.1" },
+    { name = "python-dotenv", specifier = ">=1.2.2,<2" },
     { name = "pyyaml", specifier = "~=6.0" },
     { name = "qdrant-client", extras = ["fastembed"], marker = "extra == 'qdrant'", specifier = "~=1.14.3" },
     { name = "qdrant-edge-py", marker = "extra == 'qdrant-edge'", specifier = ">=0.6.0" },
@@ -1414,7 +1414,7 @@ requires-dist = [
     { name = "click", specifier = "~=8.1.7" },
     { name = "openai", specifier = ">=1.83.0,<3" },
     { name = "pygithub", specifier = "~=1.59.1" },
-    { name = "python-dotenv", specifier = "~=1.1.1" },
+    { name = "python-dotenv", specifier = ">=1.2.2,<2" },
     { name = "rich", specifier = ">=13.9.4" },
     { name = "tomlkit", specifier = "~=0.13.2" },
 ]
@@ -1700,10 +1700,10 @@ wheels = [
 
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