fix: round-trip safety for input_provider, memory scopes, embedder class

- input_provider: enforce InputProvider protocol via dedicated validator/serializer; reject non-class dotted paths in _dotted_path_to_instance - MemoryScope/MemorySlice: allow restore without live Memory; expose bind() to reattach the dependency post-restore - Knowledge.embedder: add BeforeValidator that resolves provider_class dotted paths back to a BaseEmbeddingsProvider subclass
fix: backfill legacy discriminators and add source validation context
2026-05-20 16:38:10 +00:00 · 2026-05-21 00:30:14 +08:00 · 2026-05-21 00:22:53 +08:00 · 2026-05-21 00:17:52 +08:00 · 2026-05-21 00:12:20 +08:00 · 2026-05-20 22:33:43 +08:00
69 changed files with 3940 additions and 264 deletions
--- a/.github/workflows/build-uv-cache.yml
+++ b/.github/workflows/build-uv-cache.yml
@@ -26,7 +26,7 @@ jobs:
        uses: actions/checkout@v4

      - name: Install uv
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@d0cc045d04ccac9d8b7881df0226f9e82c39688e # v6
        with:
          version: "0.11.3"
          python-version: ${{ matrix.python-version }}
--- a/.github/workflows/generate-tool-specs.yml
+++ b/.github/workflows/generate-tool-specs.yml
@@ -22,10 +22,10 @@ jobs:
    steps:
      - name: Generate GitHub App token
        id: app-token
-        uses: tibdex/github-app-token@v2
+        uses: actions/create-github-app-token@bcd2ba49218906704ab6c1aa796996da409d3eb1 # v3.2.0
        with:
-          app_id: ${{ secrets.CREWAI_TOOL_SPECS_APP_ID }}
-          private_key: ${{ secrets.CREWAI_TOOL_SPECS_PRIVATE_KEY }}
+          app-id: ${{ secrets.CREWAI_TOOL_SPECS_APP_ID }}
+          private-key: ${{ secrets.CREWAI_TOOL_SPECS_PRIVATE_KEY }}

      - name: Checkout code
        uses: actions/checkout@v4
@@ -34,7 +34,7 @@ jobs:
          token: ${{ steps.app-token.outputs.token }}

      - name: Install uv
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@d0cc045d04ccac9d8b7881df0226f9e82c39688e # v6
        with:
          version: "0.11.3"
          python-version: "3.12"
--- a/.github/workflows/linter.yml
+++ b/.github/workflows/linter.yml
@@ -13,7 +13,7 @@ jobs:
      code: ${{ steps.filter.outputs.code }}
    steps:
      - uses: actions/checkout@v4
-      - uses: dorny/paths-filter@v3
+      - uses: dorny/paths-filter@d1c1ffe0248fe513906c8e24db8ea791d46f8590 # v3
        id: filter
        with:
          filters: |
@@ -41,7 +41,7 @@ jobs:
            uv-main-py3.11-

      - name: Install uv
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@d0cc045d04ccac9d8b7881df0226f9e82c39688e # v6
        with:
          version: "0.11.3"
          python-version: "3.11"
--- a/.github/workflows/nightly.yml
+++ b/.github/workflows/nightly.yml
@@ -44,7 +44,7 @@ jobs:
      - uses: actions/checkout@v4

      - name: Install uv
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@d0cc045d04ccac9d8b7881df0226f9e82c39688e # v6
        with:
          version: "0.11.3"
          python-version: "3.12"
@@ -103,7 +103,7 @@ jobs:
      contents: read
    steps:
      - name: Install uv
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@d0cc045d04ccac9d8b7881df0226f9e82c39688e # v6
        with:
          version: "0.11.3"
          python-version: "3.12"
--- a/.github/workflows/pr-size.yml
+++ b/.github/workflows/pr-size.yml
@@ -10,7 +10,7 @@ jobs:
    permissions:
      pull-requests: write
    steps:
-      - uses: codelytv/pr-size-labeler@v1
+      - uses: codelytv/pr-size-labeler@095a41fca88b8764fd9e008ad269bcdb82bb38b9 # v1
        with:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
          xs_label: "size/XS"
--- a/.github/workflows/pr-title.yml
+++ b/.github/workflows/pr-title.yml
@@ -12,7 +12,7 @@ jobs:
  pr-title:
    runs-on: ubuntu-latest
    steps:
-      - uses: amannn/action-semantic-pull-request@v5
+      - uses: amannn/action-semantic-pull-request@e32d7e603df1aa1ba07e981f2a23455dee596825 # v5
        continue-on-error: true
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
--- a/.github/workflows/publish.yml
+++ b/.github/workflows/publish.yml
@@ -34,7 +34,7 @@ jobs:
          python-version: "3.12"

      - name: Install uv
-        uses: astral-sh/setup-uv@v4
+        uses: astral-sh/setup-uv@38f3f104447c67c051c4a08e39b64a148898af3a # v4

      - name: Build packages
        run: |
@@ -63,7 +63,7 @@ jobs:
          ref: ${{ inputs.release_tag || github.ref }}

      - name: Install uv
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@d0cc045d04ccac9d8b7881df0226f9e82c39688e # v6
        with:
          version: "0.11.3"
          python-version: "3.12"
@@ -159,7 +159,7 @@ jobs:

      - name: Notify Slack
        if: success()
-        uses: slackapi/slack-github-action@v2.1.0
+        uses: slackapi/slack-github-action@b0fa283ad8fea605de13dc3f449259339835fc52 # v2.1.0
        with:
          webhook: ${{ secrets.SLACK_WEBHOOK_URL }}
          webhook-type: incoming-webhook
--- a/.github/workflows/tests.yml
+++ b/.github/workflows/tests.yml
@@ -13,7 +13,7 @@ jobs:
      code: ${{ steps.filter.outputs.code }}
    steps:
      - uses: actions/checkout@v4
-      - uses: dorny/paths-filter@v3
+      - uses: dorny/paths-filter@d1c1ffe0248fe513906c8e24db8ea791d46f8590 # v3
        id: filter
        with:
          filters: |
@@ -51,7 +51,7 @@ jobs:
            uv-main-py${{ matrix.python-version }}-

      - name: Install uv
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@d0cc045d04ccac9d8b7881df0226f9e82c39688e # v6
        with:
          version: "0.11.3"
          python-version: ${{ matrix.python-version }}
--- a/.github/workflows/type-checker.yml
+++ b/.github/workflows/type-checker.yml
@@ -13,7 +13,7 @@ jobs:
      code: ${{ steps.filter.outputs.code }}
    steps:
      - uses: actions/checkout@v4
-      - uses: dorny/paths-filter@v3
+      - uses: dorny/paths-filter@d1c1ffe0248fe513906c8e24db8ea791d46f8590 # v3
        id: filter
        with:
          filters: |
@@ -48,7 +48,7 @@ jobs:
            uv-main-py${{ matrix.python-version }}-

      - name: Install uv
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@d0cc045d04ccac9d8b7881df0226f9e82c39688e # v6
        with:
          version: "0.11.3"
          python-version: ${{ matrix.python-version }}
--- a/.github/workflows/update-test-durations.yml
+++ b/.github/workflows/update-test-durations.yml
@@ -38,7 +38,7 @@ jobs:
            uv-main-py${{ matrix.python-version }}-

      - name: Install uv
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@d0cc045d04ccac9d8b7881df0226f9e82c39688e # v6
        with:
          version: "0.11.3"
          python-version: ${{ matrix.python-version }}
--- a/.github/workflows/vulnerability-scan.yml
+++ b/.github/workflows/vulnerability-scan.yml
@@ -31,7 +31,7 @@ jobs:
            uv-main-py3.11-

      - name: Install uv
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@d0cc045d04ccac9d8b7881df0226f9e82c39688e # v6
        with:
          version: "0.11.3"
          python-version: "3.11"
@@ -46,11 +46,39 @@ jobs:
      - name: Run pip-audit
        run: |
          uv run pip-audit --desc --aliases --skip-editable --format json --output pip-audit-report.json \
-            --ignore-vuln CVE-2026-3219 \
-            --ignore-vuln GHSA-r374-rxx8-8654
+            --ignore-vuln PYSEC-2024-277 \
+            --ignore-vuln PYSEC-2026-89 \
+            --ignore-vuln PYSEC-2026-97 \
+            --ignore-vuln PYSEC-2025-148 \
+            --ignore-vuln PYSEC-2025-183 \
+            --ignore-vuln PYSEC-2025-189 \
+            --ignore-vuln PYSEC-2025-190 \
+            --ignore-vuln PYSEC-2025-191 \
+            --ignore-vuln PYSEC-2025-192 \
+            --ignore-vuln PYSEC-2025-193 \
+            --ignore-vuln PYSEC-2025-194 \
+            --ignore-vuln PYSEC-2025-195 \
+            --ignore-vuln PYSEC-2025-196 \
+            --ignore-vuln PYSEC-2025-197 \
+            --ignore-vuln PYSEC-2025-210 \
+            --ignore-vuln PYSEC-2026-139 \
+            --ignore-vuln PYSEC-2025-211 \
+            --ignore-vuln PYSEC-2025-212 \
+            --ignore-vuln PYSEC-2025-213 \
+            --ignore-vuln PYSEC-2025-214 \
+            --ignore-vuln PYSEC-2025-215 \
+            --ignore-vuln PYSEC-2025-216 \
+            --ignore-vuln PYSEC-2025-217 \
+            --ignore-vuln PYSEC-2025-218
        # Ignored CVEs:
-        #   CVE-2026-3219      - pip 26.0.1 (GHSA-58qw-9mgm-455v): no fix available, archive handling issue
-        #   GHSA-r374-rxx8-8654 - paramiko 4.0.0 (SHA-1 in rsakey.py): no fix available; transitive via composio-core
+        #   PYSEC-2024-277      - joblib 1.5.3: disputed; NumpyArrayWrapper only used with trusted caches
+        #   PYSEC-2026-89       - markdown 3.10.2: DoS via malformed HTML; fix 3.8.1 — already past, advisory range is stale
+        #   PYSEC-2026-97       - nltk 3.9.4: arbitrary file read in filestring(); no fix available
+        #   PYSEC-2025-148      - onnx 1.21.0: path traversal in save_external_data; no fix available
+        #   PYSEC-2025-183      - pyjwt 2.12.1: disputed weak-encryption claim; key length is application-chosen
+        #   PYSEC-2025-189..197 - torch 2.11.0: memory-corruption/DoS in functions only reachable via untrusted models; no fix available
+        #   PYSEC-2025-210, PYSEC-2026-139 - torch 2.11.0: profiler/deserialization issues; no fix available
+        #   PYSEC-2025-211..218 - transformers 5.5.4: deserialization/code injection via malicious model checkpoints; no fix available
        continue-on-error: true

      - name: Display results
--- a/docs/ar/changelog.mdx
+++ b/docs/ar/changelog.mdx
@@ -4,6 +4,86 @@ description: "تحديثات المنتج والتحسينات وإصلاحات
 icon: "clock"
 mode: "wide"
 ---
+<Update label="19 مايو 2026">
+  ## v1.14.5
+
+  [عرض الإصدار على GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.5)
+
+  ## ما الذي تغير
+
+  ### الميزات
+  - إلغاء استخدام `CrewAgentExecutor`، وتعيين وكلاء الطاقم الافتراضيين إلى `AgentExecutor`
+  - تحسين أدوات صندوق الرمل Daytona
+  - إضافة معلمة بدء `restore_from_state_id`
+  - إضافة تسليط الضوء على `ExaSearchTool`، وإعادة تسميته من `EXASearchTool`
+
+  ### إصلاحات الأخطاء
+  - إصلاح تسرب الذاكرة في `git.py` باستخدام `cached_property`
+  - عرض استدعاءات الأدوات المتدفقة عندما تكون `available_functions` غائبة
+  - ضمان تحميل أحداث `skills` للتتبع
+  - تصحيح مسار نقطة النهاية للحالة من `/{kickoff_id}/status` إلى `/status/{kickoff_id}`
+  - استعادة كتلة الشيفرة المفقودة في دليل التدفق الأول للغة البرتغالية (pt-BR)
+  - منع `result_as_answer` من إرجاع رسائل الخطأ أو الكتل المرتبطة كإجابة نهائية
+  - الحفاظ على مخرجات المهام عبر تفريغ الدفعات غير المتزامنة
+  - دائمًا استعادة `task.output_pydantic` في كتلة finally
+  - التعامل مع إدخال `BaseModel` في `convert_to_model`
+
+  ### الوثائق
+  - تحديث سجل التغييرات والإصدار لـ v1.14.5
+  - إضافة دليل ترقية OSS و انتقال الطاقم إلى التدفق
+  - توثيق متغيرات البيئة الإضافية لأدوات المطور
+  - إضافة وثائق لـ `TavilyGetResearch`
+
+  ### إعادة الهيكلة
+  - استخراج واجهة سطر الأوامر إلى حزمة مستقلة `crewai-cli`
+
+  ## المساهمون
+
+  @NIK-TIGER-BILL, @akaKuruma, @cgoeppinger, @github-actions[bot], @greysonlalonde, @heitorado, @irfaan101, @iris-clawd, @lorenzejay, @manisrinivasan2k1, @minasami-pr, @mislavivanda, @theCyberTech, @theishangoswami, @wishhyt
+
+</Update>
+
+<Update label="18 مايو 2026">
+  ## v1.14.5a7
+
+  [عرض الإصدار على GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.5a7)
+
+  ## ما الذي تغير
+
+  ### الوثائق
+  - تحديث سجل التغييرات والإصدار لـ v1.14.5a6
+
+  ### تغييرات كسرية
+  - إلغاء حقل function_calling_llm
+
+  ## المساهمون
+
+  @greysonlalonde, @heitorado
+
+</Update>
+
+<Update label="15 مايو 2026">
+  ## v1.14.5a6
+
+  [عرض الإصدار على GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.5a6)
+
+  ## ما الذي تغير
+
+  ### إصلاحات الأخطاء
+  - إصلاح استدعاءات الأدوات المتدفقة عندما تكون available_functions غائبة
+  - رفع اعتماد langsmith إلى الإصدار >=0.8.0 لمعالجة GHSA-3644-q5cj-c5c7
+  - حل مشاكل الأماكن الشاغرة لكتل التعليمات البرمجية غير المترجمة في وثائق البرتغالية البرازيلية
+
+  ### الوثائق
+  - إضافة وثائق لـ TavilyGetResearch
+  - تحديث سجل التغييرات والإصدار لـ v1.14.5a5
+
+  ## المساهمون
+
+  @greysonlalonde, @heitorado, @iris-clawd, @lorenzejay, @manisrinivasan2k1
+
+</Update>
+
 <Update label="13 مايو 2026">
  ## v1.14.5a5

--- a/docs/ar/concepts/flows.mdx
+++ b/docs/ar/concepts/flows.mdx
@@ -29,6 +29,7 @@ from crewai.flow.flow import Flow, listen, start
 from dotenv import load_dotenv
 from litellm import completion

+load_dotenv()

 class ExampleFlow(Flow):
    model = "gpt-4o-mini"
--- a/docs/ar/enterprise/guides/enable-crew-studio.mdx
+++ b/docs/ar/enterprise/guides/enable-crew-studio.mdx
@@ -146,7 +146,6 @@ Crew Studio هو طريقة مبتكرة لإنشاء طواقم وكلاء ال

  </Step>

-{" "}
 <Step title="الإجابة على الأسئلة">
  أجب على أسئلة التوضيح من مساعد الطاقم لتنقيح
  متطلباتك.
@@ -161,12 +160,10 @@ Crew Studio هو طريقة مبتكرة لإنشاء طواقم وكلاء ال

  </Step>

-{" "}
 <Step title="الموافقة أو التعديل">
  وافق على الخطة أو اطلب تغييرات إذا لزم الأمر.
 </Step>

-{" "}
 <Step title="التنزيل أو النشر">
  نزّل الكود للتخصيص أو انشر مباشرة على المنصة.
 </Step>
--- a/docs/ar/learn/llm-selection-guide.mdx
+++ b/docs/ar/learn/llm-selection-guide.mdx
@@ -802,7 +802,6 @@ The tables below show a representative sample of current top-performing models a
    Begin with well-established models like **GPT-4.1**, **Claude 3.7 Sonnet**, or **Gemini 2.0 Flash** that offer good performance across multiple dimensions and have extensive real-world validation.
  </Step>

-{" "}
 <Step title="Identify Specialized Needs">
  Determine if your crew has specific requirements (coding, reasoning, speed)
  that would benefit from specialized models like **Claude 4 Sonnet** for
@@ -810,7 +809,6 @@ The tables below show a representative sample of current top-performing models a
  consider fast inference providers like **Groq** alongside model selection.
 </Step>

-{" "}
 <Step title="Implement Multi-Model Strategy">
  Use different models for different agents based on their roles.
  High-capability models for managers and complex tasks, efficient models for
--- a/docs/docs.json
+++ b/docs/docs.json
--- a/docs/en/changelog.mdx
+++ b/docs/en/changelog.mdx
@@ -4,6 +4,86 @@ description: "Product updates, improvements, and bug fixes for CrewAI"
 icon: "clock"
 mode: "wide"
 ---
+<Update label="May 19, 2026">
+  ## v1.14.5
+
+  [View release on GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.5)
+
+  ## What's Changed
+
+  ### Features
+  - Deprecate `CrewAgentExecutor`, default Crew agents to `AgentExecutor`
+  - Improve Daytona sandbox tools
+  - Add `restore_from_state_id` kickoff parameter
+  - Add highlights to `ExaSearchTool`, rename from `EXASearchTool`
+
+  ### Bug Fixes
+  - Fix memory leak in `git.py` by using `cached_property`
+  - Surface streamed tool calls when `available_functions` is absent
+  - Ensure `skills` loading events for traces
+  - Correct status endpoint path from `/{kickoff_id}/status` to `/status/{kickoff_id}`
+  - Restore missing code block in pt-BR first-flow guide
+  - Prevent `result_as_answer` from returning hook-block or error messages as final answer
+  - Preserve task outputs across async batch flush
+  - Always restore `task.output_pydantic` in finally block
+  - Handle `BaseModel` input in `convert_to_model`
+
+  ### Documentation
+  - Update changelog and version for v1.14.5
+  - Add OSS upgrade & crew-to-flow migration guide
+  - Document additional env vars for devtools
+  - Add docs for `TavilyGetResearch`
+
+  ### Refactoring
+  - Extract CLI into standalone `crewai-cli` package
+
+  ## Contributors
+
+  @NIK-TIGER-BILL, @akaKuruma, @cgoeppinger, @github-actions[bot], @greysonlalonde, @heitorado, @irfaan101, @iris-clawd, @lorenzejay, @manisrinivasan2k1, @minasami-pr, @mislavivanda, @theCyberTech, @theishangoswami, @wishhyt
+
+</Update>
+
+<Update label="May 18, 2026">
+  ## v1.14.5a7
+
+  [View release on GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.5a7)
+
+  ## What's Changed
+
+  ### Documentation
+  - Update changelog and version for v1.14.5a6
+
+  ### Breaking Changes
+  - Deprecate function_calling_llm field
+
+  ## Contributors
+
+  @greysonlalonde, @heitorado
+
+</Update>
+
+<Update label="May 15, 2026">
+  ## v1.14.5a6
+
+  [View release on GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.5a6)
+
+  ## What's Changed
+
+  ### Bug Fixes
+  - Fix streamed tool calls when available_functions is absent
+  - Bump langsmith dependency to version >=0.8.0 to address GHSA-3644-q5cj-c5c7
+  - Resolve untranslated code block placeholders in Brazilian Portuguese documentation
+
+  ### Documentation
+  - Add documentation for TavilyGetResearch
+  - Update changelog and version for v1.14.5a5
+
+  ## Contributors
+
+  @greysonlalonde, @heitorado, @iris-clawd, @lorenzejay, @manisrinivasan2k1
+
+</Update>
+
 <Update label="May 13, 2026">
  ## v1.14.5a5

--- a/docs/en/concepts/flows.mdx
+++ b/docs/en/concepts/flows.mdx
@@ -29,6 +29,7 @@ from crewai.flow.flow import Flow, listen, start
 from dotenv import load_dotenv
 from litellm import completion

+load_dotenv()

 class ExampleFlow(Flow):
    model = "gpt-4o-mini"
--- a/docs/en/enterprise/guides/enable-crew-studio.mdx
+++ b/docs/en/enterprise/guides/enable-crew-studio.mdx
@@ -146,7 +146,6 @@ Here's a typical workflow for creating a crew with Crew Studio:

  </Step>

-{" "}
 <Step title="Answer Questions">
  Respond to clarifying questions from the Crew Assistant to refine your
  requirements.
@@ -161,12 +160,10 @@ Here's a typical workflow for creating a crew with Crew Studio:

  </Step>

-{" "}
 <Step title="Approve or Modify">
  Approve the plan or request changes if necessary.
 </Step>

-{" "}
 <Step title="Download or Deploy">
  Download the code for customization or deploy directly to the platform.
 </Step>
--- a/docs/en/guides/flows/mastering-flow-state.mdx
+++ b/docs/en/guides/flows/mastering-flow-state.mdx
@@ -313,9 +313,9 @@ flow1 = PersistentCounterFlow()
 result1 = flow1.kickoff()
 print(f"First run result: {result1}")

-# Second run - state is automatically loaded
+# Second run - pass the ID to load the persisted state
 flow2 = PersistentCounterFlow()
-result2 = flow2.kickoff()
+result2 = flow2.kickoff(inputs={"id": flow1.state.id})
 print(f"Second run result: {result2}")  # Will be higher due to persisted state
 ```

--- a/docs/en/learn/llm-selection-guide.mdx
+++ b/docs/en/learn/llm-selection-guide.mdx
@@ -805,7 +805,6 @@ The tables below show a representative sample of current top-performing models a
    Begin with well-established models like **GPT-4.1**, **Claude 3.7 Sonnet**, or **Gemini 2.0 Flash** that offer good performance across multiple dimensions and have extensive real-world validation.
  </Step>

-{" "}
 <Step title="Identify Specialized Needs">
  Determine if your crew has specific requirements (coding, reasoning, speed)
  that would benefit from specialized models like **Claude 4 Sonnet** for
@@ -813,7 +812,6 @@ The tables below show a representative sample of current top-performing models a
  consider fast inference providers like **Groq** alongside model selection.
 </Step>

-{" "}
 <Step title="Implement Multi-Model Strategy">
  Use different models for different agents based on their roles.
  High-capability models for managers and complex tasks, efficient models for
--- a/docs/ko/changelog.mdx
+++ b/docs/ko/changelog.mdx
@@ -4,6 +4,86 @@ description: "CrewAI의 제품 업데이트, 개선 사항 및 버그 수정"
 icon: "clock"
 mode: "wide"
 ---
+<Update label="2026년 5월 19일">
+  ## v1.14.5
+
+  [GitHub 릴리스 보기](https://github.com/crewAIInc/crewAI/releases/tag/1.14.5)
+
+  ## 변경 사항
+
+  ### 기능
+  - `CrewAgentExecutor` 사용 중단, 기본 Crew 에이전트를 `AgentExecutor`로 설정
+  - Daytona 샌드박스 도구 개선
+  - `restore_from_state_id` 시작 매개변수 추가
+  - `ExaSearchTool`에 하이라이트 추가, 이름을 `EXASearchTool`에서 변경
+
+  ### 버그 수정
+  - `git.py`에서 `cached_property`를 사용하여 메모리 누수 수정
+  - `available_functions`가 없을 때 스트리밍 도구 호출 표시
+  - 추적을 위한 `skills` 로딩 이벤트 보장
+  - 상태 엔드포인트 경로를 `/{kickoff_id}/status`에서 `/status/{kickoff_id}`로 수정
+  - pt-BR 첫 흐름 가이드에서 누락된 코드 블록 복원
+  - `result_as_answer`가 후크 블록이나 오류 메시지를 최종 답변으로 반환하지 않도록 방지
+  - 비동기 배치 플러시 간 작업 출력 보존
+  - 항상 finally 블록에서 `task.output_pydantic` 복원
+  - `convert_to_model`에서 `BaseModel` 입력 처리
+
+  ### 문서화
+  - v1.14.5에 대한 변경 로그 및 버전 업데이트
+  - OSS 업그레이드 및 Crew-투-흐름 마이그레이션 가이드 추가
+  - 개발 도구를 위한 추가 환경 변수 문서화
+  - `TavilyGetResearch`에 대한 문서 추가
+
+  ### 리팩토링
+  - CLI를 독립형 `crewai-cli` 패키지로 추출
+
+  ## 기여자
+
+  @NIK-TIGER-BILL, @akaKuruma, @cgoeppinger, @github-actions[bot], @greysonlalonde, @heitorado, @irfaan101, @iris-clawd, @lorenzejay, @manisrinivasan2k1, @minasami-pr, @mislavivanda, @theCyberTech, @theishangoswami, @wishhyt
+
+</Update>
+
+<Update label="2026년 5월 18일">
+  ## v1.14.5a7
+
+  [GitHub 릴리스 보기](https://github.com/crewAIInc/crewAI/releases/tag/1.14.5a7)
+
+  ## 변경 사항
+
+  ### 문서
+  - v1.14.5a6의 변경 로그 및 버전 업데이트
+
+  ### 주요 변경 사항
+  - function_calling_llm 필드 사용 중단
+
+  ## 기여자
+
+  @greysonlalonde, @heitorado
+
+</Update>
+
+<Update label="2026년 5월 15일">
+  ## v1.14.5a6
+
+  [GitHub 릴리스 보기](https://github.com/crewAIInc/crewAI/releases/tag/1.14.5a6)
+
+  ## 변경 사항
+
+  ### 버그 수정
+  - available_functions가 없을 때 스트리밍 도구 호출 수정
+  - GHSA-3644-q5cj-c5c7 문제를 해결하기 위해 langsmith 의존성을 버전 >=0.8.0으로 업데이트
+  - 브라질 포르투갈어 문서에서 번역되지 않은 코드 블록 자리 표시자 해결
+
+  ### 문서
+  - TavilyGetResearch에 대한 문서 추가
+  - v1.14.5a5에 대한 변경 로그 및 버전 업데이트
+
+  ## 기여자
+
+  @greysonlalonde, @heitorado, @iris-clawd, @lorenzejay, @manisrinivasan2k1
+
+</Update>
+
 <Update label="2026년 5월 13일">
  ## v1.14.5a5

--- a/docs/ko/concepts/flows.mdx
+++ b/docs/ko/concepts/flows.mdx
@@ -29,6 +29,7 @@ from crewai.flow.flow import Flow, listen, start
 from dotenv import load_dotenv
 from litellm import completion

+load_dotenv()

 class ExampleFlow(Flow):
    model = "gpt-4o-mini"
--- a/docs/ko/enterprise/guides/enable-crew-studio.mdx
+++ b/docs/ko/enterprise/guides/enable-crew-studio.mdx
@@ -145,7 +145,6 @@ LLM 연결과 기본 설정을 구성했다면 이제 Crew Studio 사용을 시

  </Step>

-{" "}
 <Step title="질문에 답하기">
  crew assistant가 요구 사항을 구체화할 수 있도록 하는 추가 질문에 답변하세요.
 </Step>
@@ -159,12 +158,10 @@ LLM 연결과 기본 설정을 구성했다면 이제 Crew Studio 사용을 시

  </Step>

-{" "}
 <Step title="승인 또는 수정">
  계획을 승인하거나 필요하다면 변경을 요청하세요.
 </Step>

-{" "}
 <Step title="다운로드 또는 배포">
  사용자화를 위해 코드를 다운로드하거나 플랫폼에 직접 배포하세요.
 </Step>
--- a/docs/ko/learn/llm-selection-guide.mdx
+++ b/docs/ko/learn/llm-selection-guide.mdx
@@ -797,7 +797,6 @@ LLM 선택을 최적화하고자 하는 팀을 위해 **CrewAI AMP 플랫폼**
    여러 차원에서 우수한 성능을 제공하며 실제 환경에서 광범위하게 검증된 **GPT-4.1**, **Claude 3.7 Sonnet**, **Gemini 2.0 Flash**와 같은 잘 알려진 모델부터 시작하십시오.
  </Step>

-{" "}
 <Step title="특화된 요구 사항 식별">
  crew에 코드 작성, reasoning, 속도 등 특정 요구가 있는지 확인하고, 이러한
  요구에 부합하는 **Claude 4 Sonnet**(개발용) 또는 **o3**(복잡한 분석용)과 같은
@@ -805,7 +804,6 @@ LLM 선택을 최적화하고자 하는 팀을 위해 **CrewAI AMP 플랫폼**
  더불어 **Groq**와 같은 빠른 추론 제공자를 고려할 수 있습니다.
 </Step>

-{" "}
 <Step title="다중 모델 전략 구현">
  각 에이전트의 역할에 따라 다양한 모델을 사용하세요. 관리자와 복잡한 작업에는
  고성능 모델을, 일상적 운영에는 효율적인 모델을 적용합니다.
--- a/docs/pt-BR/changelog.mdx
+++ b/docs/pt-BR/changelog.mdx
@@ -4,6 +4,86 @@ description: "Atualizações de produto, melhorias e correções do CrewAI"
 icon: "clock"
 mode: "wide"
 ---
+<Update label="19 mai 2026">
+  ## v1.14.5
+
+  [Ver release no GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.5)
+
+  ## O que Mudou
+
+  ### Recursos
+  - Deprecar `CrewAgentExecutor`, definir agentes Crew como `AgentExecutor`
+  - Melhorar ferramentas do sandbox Daytona
+  - Adicionar parâmetro de início `restore_from_state_id`
+  - Adicionar destaques ao `ExaSearchTool`, renomeando de `EXASearchTool`
+
+  ### Correções de Bugs
+  - Corrigir vazamento de memória em `git.py` usando `cached_property`
+  - Exibir chamadas de ferramentas transmitidas quando `available_functions` está ausente
+  - Garantir eventos de carregamento de `skills` para rastros
+  - Corrigir caminho do endpoint de status de `/{kickoff_id}/status` para `/status/{kickoff_id}`
+  - Restaurar bloco de código ausente no guia de primeiro fluxo em pt-BR
+  - Impedir que `result_as_answer` retorne mensagens de bloqueio de hook ou de erro como resposta final
+  - Preservar saídas de tarefas durante o descarregamento assíncrono em lote
+  - Sempre restaurar `task.output_pydantic` no bloco finally
+  - Lidar com entrada de `BaseModel` em `convert_to_model`
+
+  ### Documentação
+  - Atualizar changelog e versão para v1.14.5
+  - Adicionar guia de migração de atualização OSS & crew-to-flow
+  - Documentar variáveis de ambiente adicionais para devtools
+  - Adicionar documentação para `TavilyGetResearch`
+
+  ### Refatoração
+  - Extrair CLI para o pacote autônomo `crewai-cli`
+
+  ## Contribuidores
+
+  @NIK-TIGER-BILL, @akaKuruma, @cgoeppinger, @github-actions[bot], @greysonlalonde, @heitorado, @irfaan101, @iris-clawd, @lorenzejay, @manisrinivasan2k1, @minasami-pr, @mislavivanda, @theCyberTech, @theishangoswami, @wishhyt
+
+</Update>
+
+<Update label="18 mai 2026">
+  ## v1.14.5a7
+
+  [Ver release no GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.5a7)
+
+  ## O que Mudou
+
+  ### Documentação
+  - Atualizar changelog e versão para v1.14.5a6
+
+  ### Mudanças Quebradoras
+  - Depreciar o campo function_calling_llm
+
+  ## Contributors
+
+  @greysonlalonde, @heitorado
+
+</Update>
+
+<Update label="15 mai 2026">
+  ## v1.14.5a6
+
+  [Ver release no GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.5a6)
+
+  ## O que mudou
+
+  ### Correções de Bugs
+  - Corrigir chamadas de ferramentas transmitidas quando available_functions está ausente
+  - Atualizar a dependência langsmith para a versão >=0.8.0 para resolver GHSA-3644-q5cj-c5c7
+  - Resolver espaços reservados de blocos de código não traduzidos na documentação em português brasileiro
+
+  ### Documentação
+  - Adicionar documentação para TavilyGetResearch
+  - Atualizar changelog e versão para v1.14.5a5
+
+  ## Contributors
+
+  @greysonlalonde, @heitorado, @iris-clawd, @lorenzejay, @manisrinivasan2k1
+
+</Update>
+
 <Update label="13 mai 2026">
  ## v1.14.5a5

--- a/docs/pt-BR/concepts/flows.mdx
+++ b/docs/pt-BR/concepts/flows.mdx
@@ -24,7 +24,63 @@ Os flows permitem que você crie fluxos de trabalho estruturados e orientados po
 Vamos criar um Flow simples no qual você usará a OpenAI para gerar uma cidade aleatória em uma tarefa e, em seguida, usará essa cidade para gerar uma curiosidade em outra tarefa.

 ```python Code
-# (O código não é traduzido)
+
+from crewai.flow.flow import Flow, listen, start
+from dotenv import load_dotenv
+from litellm import completion
+
+load_dotenv()
+
+class ExampleFlow(Flow):
+    model = "gpt-4o-mini"
+
+    @start()
+    def generate_city(self):
+        print("Starting flow")
+        # Cada estado do flow recebe automaticamente um ID único
+        print(f"Flow State ID: {self.state['id']}")
+
+        response = completion(
+            model=self.model,
+            messages=[
+                {
+                    "role": "user",
+                    "content": "Return the name of a random city in the world.",
+                },
+            ],
+        )
+
+        random_city = response["choices"][0]["message"]["content"]
+        # Armazena a cidade no nosso estado
+        self.state["city"] = random_city
+        print(f"Random City: {random_city}")
+
+        return random_city
+
+    @listen(generate_city)
+    def generate_fun_fact(self, random_city):
+        response = completion(
+            model=self.model,
+            messages=[
+                {
+                    "role": "user",
+                    "content": f"Tell me a fun fact about {random_city}",
+                },
+            ],
+        )
+
+        fun_fact = response["choices"][0]["message"]["content"]
+        # Armazena a curiosidade no nosso estado
+        self.state["fun_fact"] = fun_fact
+        return fun_fact
+
+
+
+flow = ExampleFlow()
+flow.plot()
+result = flow.kickoff()
+
+print(f"Generated fun fact: {result}")
 ```

 Na ilustração acima, criamos um Flow simples que gera uma cidade aleatória usando a OpenAI e depois cria uma curiosidade sobre essa cidade. O Flow consiste em duas tarefas: `generate_city` e `generate_fun_fact`. A tarefa `generate_city` é o ponto de início do Flow, enquanto a tarefa `generate_fun_fact` fica escutando o resultado da tarefa `generate_city`.
@@ -56,12 +112,16 @@ O decorador `@listen()` pode ser usado de várias formas:
 1. **Escutando um Método pelo Nome**: Você pode passar o nome do método ao qual deseja escutar como string. Quando esse método concluir, o método ouvinte será chamado.

   ```python Code
-   # (O código não é traduzido)
+   @listen("generate_city")
+   def generate_fun_fact(self, random_city):
+       # Implementação
   ```

 2. **Escutando um Método Diretamente**: Você pode passar o próprio método. Quando esse método concluir, o método ouvinte será chamado.
   ```python Code
-   # (O código não é traduzido)
+   @listen(generate_city)
+   def generate_fun_fact(self, random_city):
+       # Implementação
   ```

 ### Saída de um Flow
@@ -76,7 +136,24 @@ Veja como acessar a saída final:

 <CodeGroup>
 ```python Code
-# (O código não é traduzido)
+from crewai.flow.flow import Flow, listen, start
+
+class OutputExampleFlow(Flow):
+    @start()
+    def first_method(self):
+        return "Output from first_method"
+
+    @listen(first_method)
+    def second_method(self, first_output):
+        return f"Second method received: {first_output}"
+
+
+flow = OutputExampleFlow()
+flow.plot("my_flow_plot")
+final_output = flow.kickoff()
+
+print("---- Final Output ----")
+print(final_output)
 ```

 ```text Output
@@ -97,8 +174,34 @@ Além de recuperar a saída final, você pode acessar e atualizar o estado dentr
 Veja um exemplo de como atualizar e acessar o estado:

 <CodeGroup>
+
 ```python Code
-# (O código não é traduzido)
+from crewai.flow.flow import Flow, listen, start
+from pydantic import BaseModel
+
+class ExampleState(BaseModel):
+    counter: int = 0
+    message: str = ""
+
+class StateExampleFlow(Flow[ExampleState]):
+
+    @start()
+    def first_method(self):
+        self.state.message = "Hello from first_method"
+        self.state.counter += 1
+
+    @listen(first_method)
+    def second_method(self):
+        self.state.message += " - updated by second_method"
+        self.state.counter += 1
+        return self.state.message
+
+flow = StateExampleFlow()
+flow.plot("my_flow_plot")
+final_output = flow.kickoff()
+print(f"Final Output: {final_output}")
+print("Final State:")
+print(flow.state)
 ```

 ```text Output
@@ -128,7 +231,33 @@ Essa abordagem oferece flexibilidade, permitindo que o desenvolvedor adicione ou
 Mesmo com estados não estruturados, os flows do CrewAI geram e mantêm automaticamente um identificador único (UUID) para cada instância de estado.

 ```python Code
-# (O código não é traduzido)
+from crewai.flow.flow import Flow, listen, start
+
+class UnstructuredExampleFlow(Flow):
+
+    @start()
+    def first_method(self):
+        # O estado inclui automaticamente um campo 'id'
+        print(f"State ID: {self.state['id']}")
+        self.state['counter'] = 0
+        self.state['message'] = "Hello from structured flow"
+
+    @listen(first_method)
+    def second_method(self):
+        self.state['counter'] += 1
+        self.state['message'] += " - updated"
+
+    @listen(second_method)
+    def third_method(self):
+        self.state['counter'] += 1
+        self.state['message'] += " - updated again"
+
+        print(f"State after third_method: {self.state}")
+
+
+flow = UnstructuredExampleFlow()
+flow.plot("my_flow_plot")
+flow.kickoff()
 ```

 ![Flow Visual image](/images/crewai-flow-3.png)
@@ -148,7 +277,39 @@ Ao usar modelos como o `BaseModel` da Pydantic, os desenvolvedores podem definir
 Cada estado nos flows do CrewAI recebe automaticamente um identificador único (UUID) para ajudar no rastreamento e gerenciamento. Esse ID é gerado e mantido automaticamente pelo sistema de flows.

 ```python Code
-# (O código não é traduzido)
+from crewai.flow.flow import Flow, listen, start
+from pydantic import BaseModel
+
+
+class ExampleState(BaseModel):
+    # Nota: o campo 'id' é adicionado automaticamente a todos os estados
+    counter: int = 0
+    message: str = ""
+
+
+class StructuredExampleFlow(Flow[ExampleState]):
+
+    @start()
+    def first_method(self):
+        # Acesse o ID gerado automaticamente, se necessário
+        print(f"State ID: {self.state.id}")
+        self.state.message = "Hello from structured flow"
+
+    @listen(first_method)
+    def second_method(self):
+        self.state.counter += 1
+        self.state.message += " - updated"
+
+    @listen(second_method)
+    def third_method(self):
+        self.state.counter += 1
+        self.state.message += " - updated again"
+
+        print(f"State after third_method: {self.state}")
+
+
+flow = StructuredExampleFlow()
+flow.kickoff()
 ```

 ![Flow Visual image](/images/crewai-flow-3.png)
@@ -182,7 +343,19 @@ O decorador @persist permite a persistência automática do estado nos flows do
 Quando aplicado no nível da classe, o decorador @persist garante a persistência automática de todos os estados dos métodos do flow:

 ```python
-# (O código não é traduzido)
+@persist  # Usa SQLiteFlowPersistence por padrão
+class MyFlow(Flow[MyState]):
+    @start()
+    def initialize_flow(self):
+        # Este método terá seu estado persistido automaticamente
+        self.state.counter = 1
+        print("Initialized flow. State ID:", self.state.id)
+
+    @listen(initialize_flow)
+    def next_step(self):
+        # O estado (incluindo self.state.id) é recarregado automaticamente
+        self.state.counter += 1
+        print("Flow state is persisted. Counter:", self.state.counter)
 ```

 ### Persistência no Nível de Método
@@ -190,7 +363,14 @@ Quando aplicado no nível da classe, o decorador @persist garante a persistênci
 Para um controle mais granular, você pode aplicar @persist em métodos específicos:

 ```python
-# (O código não é traduzido)
+class AnotherFlow(Flow[dict]):
+    @persist  # Persiste apenas o estado deste método
+    @start()
+    def begin(self):
+        if "runs" not in self.state:
+            self.state["runs"] = 0
+        self.state["runs"] += 1
+        print("Method-level persisted runs:", self.state["runs"])
 ```

 ### Forking de Estado Persistido
@@ -282,8 +462,29 @@ A arquitetura de persistência enfatiza precisão técnica e opções de persona
 A função `or_` nos flows permite escutar múltiplos métodos e acionar o método ouvinte quando qualquer um dos métodos especificados gerar uma saída.

 <CodeGroup>
+
 ```python Code
-# (O código não é traduzido)
+from crewai.flow.flow import Flow, listen, or_, start
+
+class OrExampleFlow(Flow):
+
+    @start()
+    def start_method(self):
+        return "Hello from the start method"
+
+    @listen(start_method)
+    def second_method(self):
+        return "Hello from the second method"
+
+    @listen(or_(start_method, second_method))
+    def logger(self, result):
+        print(f"Logger: {result}")
+
+
+
+flow = OrExampleFlow()
+flow.plot("my_flow_plot")
+flow.kickoff()
 ```

 ```text Output
@@ -302,8 +503,28 @@ A função `or_` serve para escutar vários métodos e disparar o método ouvint
 A função `and_` nos flows permite escutar múltiplos métodos e acionar o método ouvinte apenas quando todos os métodos especificados emitirem uma saída.

 <CodeGroup>
+
 ```python Code
-# (O código não é traduzido)
+from crewai.flow.flow import Flow, and_, listen, start
+
+class AndExampleFlow(Flow):
+
+    @start()
+    def start_method(self):
+        self.state["greeting"] = "Hello from the start method"
+
+    @listen(start_method)
+    def second_method(self):
+        self.state["joke"] = "What do computers eat? Microchips."
+
+    @listen(and_(start_method, second_method))
+    def logger(self):
+        print("---- Logger ----")
+        print(self.state)
+
+flow = AndExampleFlow()
+flow.plot()
+flow.kickoff()
 ```

 ```text Output
@@ -323,8 +544,42 @@ O decorador `@router()` nos flows permite definir lógica de roteamento condicio
 Você pode especificar diferentes rotas conforme a saída do método, permitindo controlar o fluxo de execução de forma dinâmica.

 <CodeGroup>
+
 ```python Code
-# (O código não é traduzido)
+import random
+from crewai.flow.flow import Flow, listen, router, start
+from pydantic import BaseModel
+
+class ExampleState(BaseModel):
+    success_flag: bool = False
+
+class RouterFlow(Flow[ExampleState]):
+
+    @start()
+    def start_method(self):
+        print("Starting the structured flow")
+        random_boolean = random.choice([True, False])
+        self.state.success_flag = random_boolean
+
+    @router(start_method)
+    def second_method(self):
+        if self.state.success_flag:
+            return "success"
+        else:
+            return "failed"
+
+    @listen("success")
+    def third_method(self):
+        print("Third method running")
+
+    @listen("failed")
+    def fourth_method(self):
+        print("Fourth method running")
+
+
+flow = RouterFlow()
+flow.plot("my_flow_plot")
+flow.kickoff()
 ```

 ```text Output
@@ -401,7 +656,105 @@ Para um guia completo sobre feedback humano em flows, incluindo feedback assínc
 Os agentes podem ser integrados facilmente aos seus flows, oferecendo uma alternativa leve às crews completas quando você precisar executar tarefas simples e focadas. Veja um exemplo de como utilizar um agente em um flow para realizar uma pesquisa de mercado:

 ```python
-# (O código não é traduzido)
+import asyncio
+from typing import Any, Dict, List
+
+from crewai_tools import SerperDevTool
+from pydantic import BaseModel, Field
+
+from crewai.agent import Agent
+from crewai.flow.flow import Flow, listen, start
+
+
+# Define um formato de saída estruturado
+class MarketAnalysis(BaseModel):
+    key_trends: List[str] = Field(description="List of identified market trends")
+    market_size: str = Field(description="Estimated market size")
+    competitors: List[str] = Field(description="Major competitors in the space")
+
+
+# Define o estado do flow
+class MarketResearchState(BaseModel):
+    product: str = ""
+    analysis: MarketAnalysis | None = None
+
+
+# Cria uma classe de flow
+class MarketResearchFlow(Flow[MarketResearchState]):
+    @start()
+    def initialize_research(self) -> Dict[str, Any]:
+        print(f"Starting market research for {self.state.product}")
+        return {"product": self.state.product}
+
+    @listen(initialize_research)
+    async def analyze_market(self) -> Dict[str, Any]:
+        # Cria um agente para pesquisa de mercado
+        analyst = Agent(
+            role="Market Research Analyst",
+            goal=f"Analyze the market for {self.state.product}",
+            backstory="You are an experienced market analyst with expertise in "
+            "identifying market trends and opportunities.",
+            tools=[SerperDevTool()],
+            verbose=True,
+        )
+
+        # Define a consulta de pesquisa
+        query = f"""
+        Research the market for {self.state.product}. Include:
+        1. Key market trends
+        2. Market size
+        3. Major competitors
+
+        Format your response according to the specified structure.
+        """
+
+        # Executa a análise com formato de saída estruturado
+        result = await analyst.kickoff_async(query, response_format=MarketAnalysis)
+        if result.pydantic:
+            print("result", result.pydantic)
+        else:
+            print("result", result)
+
+        # Retorna a análise para atualizar o estado
+        return {"analysis": result.pydantic}
+
+    @listen(analyze_market)
+    def present_results(self, analysis) -> None:
+        print("\nMarket Analysis Results")
+        print("=====================")
+
+        if isinstance(analysis, dict):
+            # Se recebemos um dict com a chave 'analysis', extrai o objeto de análise real
+            market_analysis = analysis.get("analysis")
+        else:
+            market_analysis = analysis
+
+        if market_analysis and isinstance(market_analysis, MarketAnalysis):
+            print("\nKey Market Trends:")
+            for trend in market_analysis.key_trends:
+                print(f"- {trend}")
+
+            print(f"\nMarket Size: {market_analysis.market_size}")
+
+            print("\nMajor Competitors:")
+            for competitor in market_analysis.competitors:
+                print(f"- {competitor}")
+        else:
+            print("No structured analysis data available.")
+            print("Raw analysis:", analysis)
+
+
+# Exemplo de uso
+async def run_flow():
+    flow = MarketResearchFlow()
+    flow.plot("MarketResearchFlowPlot")
+    result = await flow.kickoff_async(inputs={"product": "AI-powered chatbots"})
+    return result
+
+
+# Executa o flow
+if __name__ == "__main__":
+    asyncio.run(run_flow())
 ```

 ![Flow Visual image](/images/crewai-flow-7.png)
@@ -463,7 +816,50 @@ No arquivo `main.py`, você cria seu flow e conecta as crews. É possível defin
 Veja um exemplo de como conectar a `poem_crew` no arquivo `main.py`:

 ```python Code
-# (O código não é traduzido)
+#!/usr/bin/env python
+from random import randint
+
+from pydantic import BaseModel
+from crewai.flow.flow import Flow, listen, start
+from .crews.poem_crew.poem_crew import PoemCrew
+
+class PoemState(BaseModel):
+    sentence_count: int = 1
+    poem: str = ""
+
+class PoemFlow(Flow[PoemState]):
+
+    @start()
+    def generate_sentence_count(self):
+        print("Generating sentence count")
+        self.state.sentence_count = randint(1, 5)
+
+    @listen(generate_sentence_count)
+    def generate_poem(self):
+        print("Generating poem")
+        result = PoemCrew().crew().kickoff(inputs={"sentence_count": self.state.sentence_count})
+
+        print("Poem generated", result.raw)
+        self.state.poem = result.raw
+
+    @listen(generate_poem)
+    def save_poem(self):
+        print("Saving poem")
+        with open("poem.txt", "w") as f:
+            f.write(self.state.poem)
+
+def kickoff():
+    poem_flow = PoemFlow()
+    poem_flow.kickoff()
+
+
+def plot():
+    poem_flow = PoemFlow()
+    poem_flow.plot("PoemFlowPlot")
+
+if __name__ == "__main__":
+    kickoff()
+    plot()
 ```

 Neste exemplo, a classe `PoemFlow` define um fluxo que gera a quantidade de frases, usa a `PoemCrew` para gerar um poema e, depois, salva o poema em um arquivo. O flow inicia com o método `kickoff()`, e o gráfico é gerado pelo método `plot()`.
@@ -515,7 +911,8 @@ O CrewAI oferece duas formas práticas de gerar plots dos seus flows:
 Se estiver trabalhando diretamente com uma instância do flow, basta chamar o método `plot()` do objeto. Isso criará um arquivo HTML com o plot interativo do seu flow.

 ```python Code
-# (O código não é traduzido)
+# Considerando que você já tem uma instância do flow
+flow.plot("my_flow_plot")
 ```

 Esse comando gera um arquivo chamado `my_flow_plot.html` no diretório atual. Abra esse arquivo em um navegador para visualizar o plot interativo.
--- a/docs/pt-BR/enterprise/guides/enable-crew-studio.mdx
+++ b/docs/pt-BR/enterprise/guides/enable-crew-studio.mdx
@@ -146,7 +146,6 @@ Veja um fluxo de trabalho típico para criação de um crew com o Crew Studio:

  </Step>

-{" "}
 <Step title="Responder Perguntas">
  Responda às perguntas de esclarecimento do Crew Assistant para refinar seus
  requisitos.
@@ -161,12 +160,10 @@ Veja um fluxo de trabalho típico para criação de um crew com o Crew Studio:

  </Step>

-{" "}
 <Step title="Aprovar ou Modificar">
  Aprove o plano ou solicite alterações, se necessário.
 </Step>

-{" "}
 <Step title="Baixar ou Fazer Deploy">
  Baixe o código para personalização ou faça o deploy diretamente na plataforma.
 </Step>
--- a/docs/pt-BR/guides/flows/mastering-flow-state.mdx
+++ b/docs/pt-BR/guides/flows/mastering-flow-state.mdx
@@ -63,7 +63,60 @@ Com estado não estruturado:
 Veja um exemplo simples de gerenciamento de estado não estruturado:

 ```python
-# código não traduzido
+from crewai.flow.flow import Flow, listen, start
+
+class UnstructuredStateFlow(Flow):
+    @start()
+    def initialize_data(self):
+        print("Initializing flow data")
+        # Adiciona pares chave-valor ao estado
+        self.state["user_name"] = "Alex"
+        self.state["preferences"] = {
+            "theme": "dark",
+            "language": "English"
+        }
+        self.state["items"] = []
+
+        # O estado do flow recebe automaticamente um ID único
+        print(f"Flow ID: {self.state['id']}")
+
+        return "Initialized"
+
+    @listen(initialize_data)
+    def process_data(self, previous_result):
+        print(f"Previous step returned: {previous_result}")
+
+        # Acessa e modifica o estado
+        user = self.state["user_name"]
+        print(f"Processing data for {user}")
+
+        # Adiciona itens a uma lista no estado
+        self.state["items"].append("item1")
+        self.state["items"].append("item2")
+
+        # Adiciona um novo par chave-valor
+        self.state["processed"] = True
+
+        return "Processed"
+
+    @listen(process_data)
+    def generate_summary(self, previous_result):
+        # Acessa múltiplos valores do estado
+        user = self.state["user_name"]
+        theme = self.state["preferences"]["theme"]
+        items = self.state["items"]
+        processed = self.state.get("processed", False)
+
+        summary = f"User {user} has {len(items)} items with {theme} theme. "
+        summary += "Data is processed." if processed else "Data is not processed."
+
+        return summary
+
+# Executa o flow
+flow = UnstructuredStateFlow()
+result = flow.kickoff()
+print(f"Final result: {result}")
+print(f"Final state: {flow.state}")
 ```

 ### Quando Usar Estado Não Estruturado
@@ -94,7 +147,63 @@ Ao utilizar estado estruturado:
 Veja como implementar o gerenciamento de estado estruturado:

 ```python
-# código não traduzido
+from crewai.flow.flow import Flow, listen, start
+from pydantic import BaseModel, Field
+from typing import List, Dict, Optional
+
+# Define o modelo de estado
+class UserPreferences(BaseModel):
+    theme: str = "light"
+    language: str = "English"
+
+class AppState(BaseModel):
+    user_name: str = ""
+    preferences: UserPreferences = UserPreferences()
+    items: List[str] = []
+    processed: bool = False
+    completion_percentage: float = 0.0
+
+# Cria um flow com estado tipado
+class StructuredStateFlow(Flow[AppState]):
+    @start()
+    def initialize_data(self):
+        print("Initializing flow data")
+        # Define valores do estado (com checagem de tipo)
+        self.state.user_name = "Taylor"
+        self.state.preferences.theme = "dark"
+
+        # O campo ID está disponível automaticamente
+        print(f"Flow ID: {self.state.id}")
+
+        return "Initialized"
+
+    @listen(initialize_data)
+    def process_data(self, previous_result):
+        print(f"Processing data for {self.state.user_name}")
+
+        # Modifica o estado (com checagem de tipo)
+        self.state.items.append("item1")
+        self.state.items.append("item2")
+        self.state.processed = True
+        self.state.completion_percentage = 50.0
+
+        return "Processed"
+
+    @listen(process_data)
+    def generate_summary(self, previous_result):
+        # Acessa o estado (com autocompletar)
+        summary = f"User {self.state.user_name} has {len(self.state.items)} items "
+        summary += f"with {self.state.preferences.theme} theme. "
+        summary += "Data is processed." if self.state.processed else "Data is not processed."
+        summary += f" Completion: {self.state.completion_percentage}%"
+
+        return summary
+
+# Executa o flow
+flow = StructuredStateFlow()
+result = flow.kickoff()
+print(f"Final result: {result}")
+print(f"Final state: {flow.state}")
 ```

 ### Benefícios do Estado Estruturado
@@ -138,7 +247,29 @@ Independente de você usar estado estruturado ou não estruturado, é possível
 Métodos do flow podem retornar valores que serão passados como argumento para métodos listeners:

 ```python
-# código não traduzido
+from crewai.flow.flow import Flow, listen, start
+
+class DataPassingFlow(Flow):
+    @start()
+    def generate_data(self):
+        # Este valor de retorno será passado para os métodos listeners
+        return "Generated data"
+
+    @listen(generate_data)
+    def process_data(self, data_from_previous_step):
+        print(f"Received: {data_from_previous_step}")
+        # Você pode modificar os dados e repassá-los adiante
+        processed_data = f"{data_from_previous_step} - processed"
+        # Também atualiza o estado
+        self.state["last_processed"] = processed_data
+        return processed_data
+
+    @listen(process_data)
+    def finalize_data(self, processed_data):
+        print(f"Received processed data: {processed_data}")
+        # Acessa tanto os dados passados quanto o estado
+        last_processed = self.state.get("last_processed", "")
+        return f"Final: {processed_data} (from state: {last_processed})"
 ```

 Esse padrão permite combinar passagem de dados direta com atualizações de estado para obter máxima flexibilidade.
@@ -156,7 +287,36 @@ O decorador `@persist()` automatiza a persistência de estado, salvando o estado
 Ao aplicar em nível de classe, `@persist()` salva o estado após cada execução de método:

 ```python
-# código não traduzido
+from crewai.flow.flow import Flow, listen, start
+from crewai.flow.persistence import persist
+from pydantic import BaseModel
+
+class CounterState(BaseModel):
+    value: int = 0
+
+@persist()  # Aplica à classe inteira do flow
+class PersistentCounterFlow(Flow[CounterState]):
+    @start()
+    def increment(self):
+        self.state.value += 1
+        print(f"Incremented to {self.state.value}")
+        return self.state.value
+
+    @listen(increment)
+    def double(self, value):
+        self.state.value = value * 2
+        print(f"Doubled to {self.state.value}")
+        return self.state.value
+
+# Primeira execução
+flow1 = PersistentCounterFlow()
+result1 = flow1.kickoff()
+print(f"First run result: {result1}")
+
+# Segunda execução - passa o ID para carregar o estado persistido
+flow2 = PersistentCounterFlow()
+result2 = flow2.kickoff(inputs={"id": flow1.state.id})
+print(f"Second run result: {result2}")  # Será maior devido ao estado persistido
 ```

 #### Persistência em Nível de Método
@@ -164,7 +324,26 @@ Ao aplicar em nível de classe, `@persist()` salva o estado após cada execuçã
 Para mais controle, você pode aplicar `@persist()` em métodos específicos:

 ```python
-# código não traduzido
+from crewai.flow.flow import Flow, listen, start
+from crewai.flow.persistence import persist
+
+class SelectivePersistFlow(Flow):
+    @start()
+    def first_step(self):
+        self.state["count"] = 1
+        return "First step"
+
+    @persist()  # Persiste apenas após este método
+    @listen(first_step)
+    def important_step(self, prev_result):
+        self.state["count"] += 1
+        self.state["important_data"] = "This will be persisted"
+        return "Important step completed"
+
+    @listen(important_step)
+    def final_step(self, prev_result):
+        self.state["count"] += 1
+        return f"Complete with count {self.state['count']}"
 ```

 #### Forking de Estado Persistido
@@ -216,7 +395,45 @@ Notas sobre o comportamento:
 Você pode usar o estado para implementar lógicas condicionais complexas em seus flows:

 ```python
-# código não traduzido
+from crewai.flow.flow import Flow, listen, router, start
+from pydantic import BaseModel
+
+class PaymentState(BaseModel):
+    amount: float = 0.0
+    is_approved: bool = False
+    retry_count: int = 0
+
+class PaymentFlow(Flow[PaymentState]):
+    @start()
+    def process_payment(self):
+        # Simula o processamento do pagamento
+        self.state.amount = 100.0
+        self.state.is_approved = self.state.amount < 1000
+        return "Payment processed"
+
+    @router(process_payment)
+    def check_approval(self, previous_result):
+        if self.state.is_approved:
+            return "approved"
+        elif self.state.retry_count < 3:
+            return "retry"
+        else:
+            return "rejected"
+
+    @listen("approved")
+    def handle_approval(self):
+        return f"Payment of ${self.state.amount} approved!"
+
+    @listen("retry")
+    def handle_retry(self):
+        self.state.retry_count += 1
+        print(f"Retrying payment (attempt {self.state.retry_count})...")
+        # Aqui poderia ser implementada a lógica de retry
+        return "Retry initiated"
+
+    @listen("rejected")
+    def handle_rejection(self):
+        return f"Payment of ${self.state.amount} rejected after {self.state.retry_count} retries."
 ```

 ### Manipulações Complexas de Estado
@@ -224,7 +441,60 @@ Você pode usar o estado para implementar lógicas condicionais complexas em seu
 Para transformar estados complexos, você pode criar métodos dedicados:

 ```python
-# código não traduzido
+from crewai.flow.flow import Flow, listen, start
+from pydantic import BaseModel
+from typing import List, Dict
+
+class UserData(BaseModel):
+    name: str
+    active: bool = True
+    login_count: int = 0
+
+class ComplexState(BaseModel):
+    users: Dict[str, UserData] = {}
+    active_user_count: int = 0
+
+class TransformationFlow(Flow[ComplexState]):
+    @start()
+    def initialize(self):
+        # Adiciona alguns usuários
+        self.add_user("alice", "Alice")
+        self.add_user("bob", "Bob")
+        self.add_user("charlie", "Charlie")
+        return "Initialized"
+
+    @listen(initialize)
+    def process_users(self, _):
+        # Incrementa contagens de login
+        for user_id in self.state.users:
+            self.increment_login(user_id)
+
+        # Desativa um usuário
+        self.deactivate_user("bob")
+
+        # Atualiza a contagem de ativos
+        self.update_active_count()
+
+        return f"Processed {len(self.state.users)} users"
+
+    # Métodos auxiliares para transformações de estado
+    def add_user(self, user_id: str, name: str):
+        self.state.users[user_id] = UserData(name=name)
+        self.update_active_count()
+
+    def increment_login(self, user_id: str):
+        if user_id in self.state.users:
+            self.state.users[user_id].login_count += 1
+
+    def deactivate_user(self, user_id: str):
+        if user_id in self.state.users:
+            self.state.users[user_id].active = False
+            self.update_active_count()
+
+    def update_active_count(self):
+        self.state.active_user_count = sum(
+            1 for user in self.state.users.values() if user.active
+        )
 ```

 Esse padrão de criar métodos auxiliares mantém seus métodos de flow limpos, enquanto permite manipulações complexas de estado.
@@ -238,7 +508,71 @@ Um dos padrões mais poderosos na CrewAI é combinar o gerenciamento de estado d
 Você pode usar o estado do flow para parametrizar crews:

 ```python
-# código não traduzido
+from crewai.flow.flow import Flow, listen, start
+from crewai import Agent, Crew, Process, Task
+from pydantic import BaseModel
+
+class ResearchState(BaseModel):
+    topic: str = ""
+    depth: str = "medium"
+    results: str = ""
+
+class ResearchFlow(Flow[ResearchState]):
+    @start()
+    def get_parameters(self):
+        # Em uma aplicação real, isso pode vir da entrada do usuário
+        self.state.topic = "Artificial Intelligence Ethics"
+        self.state.depth = "deep"
+        return "Parameters set"
+
+    @listen(get_parameters)
+    def execute_research(self, _):
+        # Cria os agentes
+        researcher = Agent(
+            role="Research Specialist",
+            goal=f"Research {self.state.topic} in {self.state.depth} detail",
+            backstory="You are an expert researcher with a talent for finding accurate information."
+        )
+
+        writer = Agent(
+            role="Content Writer",
+            goal="Transform research into clear, engaging content",
+            backstory="You excel at communicating complex ideas clearly and concisely."
+        )
+
+        # Cria as tarefas
+        research_task = Task(
+            description=f"Research {self.state.topic} with {self.state.depth} analysis",
+            expected_output="Comprehensive research notes in markdown format",
+            agent=researcher
+        )
+
+        writing_task = Task(
+            description=f"Create a summary on {self.state.topic} based on the research",
+            expected_output="Well-written article in markdown format",
+            agent=writer,
+            context=[research_task]
+        )
+
+        # Cria e executa a crew
+        research_crew = Crew(
+            agents=[researcher, writer],
+            tasks=[research_task, writing_task],
+            process=Process.sequential,
+            verbose=True
+        )
+
+        # Executa a crew e armazena o resultado no estado
+        result = research_crew.kickoff()
+        self.state.results = result.raw
+
+        return "Research completed"
+
+    @listen(execute_research)
+    def summarize_results(self, _):
+        # Acessa os resultados armazenados
+        result_length = len(self.state.results)
+        return f"Research on {self.state.topic} completed with {result_length} characters of results."
 ```

 ### Manipulando Saídas de Crews no Estado
@@ -246,7 +580,21 @@ Você pode usar o estado do flow para parametrizar crews:
 Quando um crew finaliza, é possível processar sua saída e armazená-la no estado do flow:

 ```python
-# código não traduzido
+@listen(execute_crew)
+def process_crew_results(self, _):
+    # Faz parsing dos resultados brutos (assumindo saída em JSON)
+    import json
+    try:
+        results_dict = json.loads(self.state.raw_results)
+        self.state.processed_results = {
+            "title": results_dict.get("title", ""),
+            "main_points": results_dict.get("main_points", []),
+            "conclusion": results_dict.get("conclusion", "")
+        }
+        return "Results processed successfully"
+    except json.JSONDecodeError:
+        self.state.error = "Failed to parse crew results as JSON"
+        return "Error processing results"
 ```

 ## Boas Práticas para Gerenciamento de Estado
@@ -256,7 +604,19 @@ Quando um crew finaliza, é possível processar sua saída e armazená-la no est
 Projete seu estado para conter somente o necessário:

 ```python
-# Exemplo não traduzido
+# Abrangente demais
+class BloatedState(BaseModel):
+    user_data: Dict = {}
+    system_settings: Dict = {}
+    temporary_calculations: List = []
+    debug_info: Dict = {}
+    # ...muitos outros campos
+
+# Melhor: estado focado
+class FocusedState(BaseModel):
+    user_id: str
+    preferences: Dict[str, str]
+    completion_status: Dict[str, bool]
 ```

 ### 2. Use Estado Estruturado em Flows Complexos
@@ -264,7 +624,23 @@ Projete seu estado para conter somente o necessário:
 À medida que seus flows evoluem em complexidade, o estado estruturado se torna cada vez mais valioso:

 ```python
-# Exemplo não traduzido
+# Flow simples pode usar estado não estruturado
+class SimpleGreetingFlow(Flow):
+    @start()
+    def greet(self):
+        self.state["name"] = "World"
+        return f"Hello, {self.state['name']}!"
+
+# Flow complexo se beneficia de estado estruturado
+class UserRegistrationState(BaseModel):
+    username: str
+    email: str
+    verification_status: bool = False
+    registration_date: datetime = Field(default_factory=datetime.now)
+    last_login: Optional[datetime] = None
+
+class RegistrationFlow(Flow[UserRegistrationState]):
+    # Métodos com acesso ao estado fortemente tipado
 ```

 ### 3. Documente Transições de Estado
@@ -272,7 +648,18 @@ Projete seu estado para conter somente o necessário:
 Para flows complexos, documente como o estado muda ao longo da execução:

 ```python
-# Exemplo não traduzido
+@start()
+def initialize_order(self):
+    """
+    Initialize order state with empty values.
+
+    State before: {}
+    State after: {order_id: str, items: [], status: 'new'}
+    """
+    self.state.order_id = str(uuid.uuid4())
+    self.state.items = []
+    self.state.status = "new"
+    return "Order initialized"
 ```

 ### 4. Trate Erros de Estado de Forma Elegante
@@ -280,7 +667,18 @@ Para flows complexos, documente como o estado muda ao longo da execução:
 Implemente tratamento de erros ao acessar o estado:

 ```python
-# Exemplo não traduzido
+@listen(previous_step)
+def process_data(self, _):
+    try:
+        # Tenta acessar um valor que pode não existir
+        user_preference = self.state.preferences.get("theme", "default")
+    except (AttributeError, KeyError):
+        # Trata o erro de forma elegante
+        self.state.errors = self.state.get("errors", [])
+        self.state.errors.append("Failed to access preferences")
+        user_preference = "default"
+
+    return f"Used preference: {user_preference}"
 ```

 ### 5. Use o Estado Para Acompanhar o Progresso
@@ -288,7 +686,30 @@ Implemente tratamento de erros ao acessar o estado:
 Aproveite o estado para monitorar o progresso em flows de longa duração:

 ```python
-# Exemplo não traduzido
+class ProgressTrackingFlow(Flow):
+    @start()
+    def initialize(self):
+        self.state["total_steps"] = 3
+        self.state["current_step"] = 0
+        self.state["progress"] = 0.0
+        self.update_progress()
+        return "Initialized"
+
+    def update_progress(self):
+        """Helper method to calculate and update progress"""
+        if self.state.get("total_steps", 0) > 0:
+            self.state["progress"] = (self.state.get("current_step", 0) /
+                                    self.state["total_steps"]) * 100
+            print(f"Progress: {self.state['progress']:.1f}%")
+
+    @listen(initialize)
+    def step_one(self, _):
+        # Realiza o trabalho...
+        self.state["current_step"] = 1
+        self.update_progress()
+        return "Step 1 complete"
+
+    # Etapas adicionais...
 ```

 ### 6. Prefira Operações Imutáveis Quando Possível
@@ -296,7 +717,22 @@ Aproveite o estado para monitorar o progresso em flows de longa duração:
 Especialmente com estado estruturado, prefira operações imutáveis para maior clareza:

 ```python
-# Exemplo não traduzido
+# Em vez de modificar listas no local:
+self.state.items.append(new_item)  # Operação mutável
+
+# Considere criar um novo estado:
+from pydantic import BaseModel
+from typing import List
+
+class ItemState(BaseModel):
+    items: List[str] = []
+
+class ImmutableFlow(Flow[ItemState]):
+    @start()
+    def add_item(self):
+        # Cria uma nova lista com o item adicionado
+        self.state.items = [*self.state.items, "new item"]
+        return "Item added"
 ```

 ## Depurando o Estado do Flow
@@ -306,7 +742,24 @@ Especialmente com estado estruturado, prefira operações imutáveis para maior
 Ao desenvolver, adicione logs para acompanhar mudanças no estado:

 ```python
-# Exemplo não traduzido
+import logging
+logging.basicConfig(level=logging.INFO)
+
+class LoggingFlow(Flow):
+    def log_state(self, step_name):
+        logging.info(f"State after {step_name}: {self.state}")
+
+    @start()
+    def initialize(self):
+        self.state["counter"] = 0
+        self.log_state("initialize")
+        return "Initialized"
+
+    @listen(initialize)
+    def increment(self, _):
+        self.state["counter"] += 1
+        self.log_state("increment")
+        return f"Incremented to {self.state['counter']}"
 ```

 ### Visualizando o Estado
@@ -314,7 +767,30 @@ Ao desenvolver, adicione logs para acompanhar mudanças no estado:
 Você pode adicionar métodos para visualizar seu estado durante o debug:

 ```python
-# Exemplo não traduzido
+def visualize_state(self):
+    """Create a simple visualization of the current state"""
+    import json
+    from rich.console import Console
+    from rich.panel import Panel
+
+    console = Console()
+
+    if hasattr(self.state, "model_dump"):
+        # Pydantic v2
+        state_dict = self.state.model_dump()
+    elif hasattr(self.state, "dict"):
+        # Pydantic v1
+        state_dict = self.state.dict()
+    else:
+        # Estado não estruturado
+        state_dict = dict(self.state)
+
+    # Remove o id para uma saída mais limpa
+    if "id" in state_dict:
+        state_dict.pop("id")
+
+    state_json = json.dumps(state_dict, indent=2, default=str)
+    console.print(Panel(state_json, title="Current Flow State"))
 ```

 ## Conclusão
--- a/docs/pt-BR/learn/llm-selection-guide.mdx
+++ b/docs/pt-BR/learn/llm-selection-guide.mdx
@@ -797,7 +797,6 @@ As tabelas abaixo mostram uma amostra dos modelos de maior destaque em cada cate
    Inicie com opções consagradas como **GPT-4.1**, **Claude 3.7 Sonnet** ou **Gemini 2.0 Flash**, que oferecem bom desempenho e ampla validação.
  </Step>

-{" "}
 <Step title="Identifique Demandas Especializadas">
  Descubra se sua crew possui requisitos específicos (código, raciocínio,
  velocidade) que justifiquem modelos como **Claude 4 Sonnet** para
@@ -805,7 +804,6 @@ As tabelas abaixo mostram uma amostra dos modelos de maior destaque em cada cate
  velocidade, considere Groq aliado à seleção do modelo.
 </Step>

-{" "}
 <Step title="Implemente Estratégia Multi-Modelo">
  Use modelos diferentes para agentes distintos conforme o papel. Modelos de
  alta capacidade para managers e tarefas complexas, eficientes para rotinas.
--- a/lib/cli/pyproject.toml
+++ b/lib/cli/pyproject.toml
@@ -8,7 +8,7 @@ authors = [
 ]
 requires-python = ">=3.10, <3.14"
 dependencies = [
-    "crewai-core==1.14.5a5",
+    "crewai-core==1.14.5",
    "click~=8.1.7",
    "pydantic>=2.11.9,<2.13",
    "pydantic-settings~=2.10.1",
--- a/lib/cli/src/crewai_cli/init.py
+++ b/lib/cli/src/crewai_cli/init.py
@@ -1 +1 @@
-__version__ = "1.14.5a5"
+__version__ = "1.14.5"
--- a/lib/cli/src/crewai_cli/deploy/main.py
+++ b/lib/cli/src/crewai_cli/deploy/main.py
@@ -1,5 +1,6 @@
 from typing import Any

+from crewai_core.plus_api import CreateCrewPayload
 from rich.console import Console

 from crewai_cli import git
@@ -161,7 +162,7 @@ class DeployCommand(BaseCommand, PlusAPIMixin):
        self,
        env_vars: dict[str, str],
        remote_repo_url: str,
-    ) -> dict[str, Any]:
+    ) -> CreateCrewPayload:
        """
        Create the payload for crew creation.

@@ -172,6 +173,8 @@ class DeployCommand(BaseCommand, PlusAPIMixin):
        Returns:
            Dict[str, Any]: The payload for crew creation.
        """
+        if not self.project_name:
+            raise ValueError("project_name is required to create a deployment payload")
        return {
            "deploy": {
                "name": self.project_name,
--- a/lib/cli/src/crewai_cli/git.py
+++ b/lib/cli/src/crewai_cli/git.py
@@ -1,4 +1,4 @@
-from functools import lru_cache
+from functools import cached_property
 import subprocess


@@ -9,7 +9,7 @@ class Repository:
        if not self.is_git_installed():
            raise ValueError("Git is not installed or not found in your PATH.")

-        if not self.is_git_repo():
+        if not self.is_git_repo:
            raise ValueError(f"{self.path} is not a Git repository.")

        self.fetch()
@@ -40,13 +40,9 @@ class Repository:
            encoding="utf-8",
        ).strip()

-    @lru_cache(maxsize=None)  # noqa: B019
+    @cached_property  # noqa: B019
    def is_git_repo(self) -> bool:
-        """Check if the current directory is a git repository.
-
-        Notes:
-          - TODO: This method is cached to avoid redundant checks, but using lru_cache on methods can lead to memory leaks
-        """
+        """Check if the current directory is a git repository."""
        try:
            subprocess.check_output(
                ["git", "rev-parse", "--is-inside-work-tree"],  # noqa: S607
--- a/lib/crewai-core/src/crewai_core/init.py
+++ b/lib/crewai-core/src/crewai_core/init.py
@@ -1 +1 @@
-__version__ = "1.14.5a5"
+__version__ = "1.14.5"
--- a/lib/crewai-core/src/crewai_core/plus_api.py
+++ b/lib/crewai-core/src/crewai_core/plus_api.py
@@ -3,36 +3,161 @@
 from __future__ import annotations

 import os
-from typing import Any
+from typing import Any, Final, Literal, TypedDict, cast
 from urllib.parse import urljoin

 import httpx
+from typing_extensions import NotRequired

 from crewai_core.constants import DEFAULT_CREWAI_ENTERPRISE_URL
 from crewai_core.settings import Settings
 from crewai_core.version import get_crewai_version


+HttpMethod = Literal["GET", "POST", "PATCH", "DELETE"]
+
+
+class AvailableExport(TypedDict):
+    name: str
+
+
+class EnvVarEntry(TypedDict):
+    name: str
+    description: str
+    required: bool
+    default: str | None
+
+
+class ToolMetadata(TypedDict):
+    name: str
+    module: str
+    humanized_name: str
+    description: str
+    run_params_schema: dict[str, Any]
+    init_params_schema: dict[str, Any]
+    env_vars: list[EnvVarEntry]
+
+
+class ToolsMetadataPayload(TypedDict):
+    package: str
+    tools: list[ToolMetadata] | None
+
+
+class PublishToolPayload(TypedDict):
+    handle: str
+    public: bool
+    version: str
+    file: str
+    description: str | None
+    available_exports: list[AvailableExport] | None
+    tools_metadata: ToolsMetadataPayload | None
+
+
+class CrewDeploymentSpec(TypedDict):
+    name: str
+    repo_clone_url: str
+    env: dict[str, str]
+
+
+class CreateCrewPayload(TypedDict):
+    deploy: CrewDeploymentSpec
+
+
+class _WithUserIdentifier(TypedDict):
+    user_identifier: NotRequired[str]
+
+
+class LoginPayload(_WithUserIdentifier):
+    pass
+
+
+class TraceExecutionContext(TypedDict):
+    crew_fingerprint: str | None
+    crew_name: str | None
+    flow_name: str | None
+    crewai_version: str
+    privacy_level: str
+
+
+class TraceExecutionMetadata(TypedDict):
+    expected_duration_estimate: int
+    agent_count: int
+    task_count: int
+    flow_method_count: int
+    execution_started_at: str
+
+
+class TraceBatchInitPayload(_WithUserIdentifier):
+    trace_id: str
+    execution_type: str
+    execution_context: TraceExecutionContext
+    execution_metadata: TraceExecutionMetadata
+    ephemeral_trace_id: NotRequired[str]
+
+
+class TraceBatchMetadata(TypedDict):
+    events_count: int
+    batch_sequence: int
+    is_final_batch: bool
+
+
+class TraceEventsPayload(TypedDict):
+    events: list[dict[str, Any]]
+    batch_metadata: TraceBatchMetadata
+
+
+class TraceFinalizePayload(TypedDict):
+    status: Literal["completed"]
+    duration_ms: float | None
+    final_event_count: int
+
+
+class TraceFailedPayload(TypedDict):
+    status: Literal["failed"]
+    failure_reason: str
+
+
+Headers = TypedDict(
+    "Headers",
+    {
+        "Content-Type": str,
+        "User-Agent": str,
+        "X-Crewai-Version": str,
+        "Authorization": NotRequired[str],
+        "X-Crewai-Organization-Id": NotRequired[str],
+    },
+)
+
+
+class RequestKwargs(TypedDict):
+    headers: dict[str, str]
+    json: NotRequired[Any]
+    params: NotRequired[dict[str, str]]
+    timeout: NotRequired[float]
+
+
 class PlusAPI:
    """Client for working with the CrewAI+ API."""

-    TOOLS_RESOURCE = "/crewai_plus/api/v1/tools"
-    ORGANIZATIONS_RESOURCE = "/crewai_plus/api/v1/me/organizations"
-    CREWS_RESOURCE = "/crewai_plus/api/v1/crews"
-    AGENTS_RESOURCE = "/crewai_plus/api/v1/agents"
-    TRACING_RESOURCE = "/crewai_plus/api/v1/tracing"
-    EPHEMERAL_TRACING_RESOURCE = "/crewai_plus/api/v1/tracing/ephemeral"
-    INTEGRATIONS_RESOURCE = "/crewai_plus/api/v1/integrations"
+    TOOLS_RESOURCE: Final = "/crewai_plus/api/v1/tools"
+    ORGANIZATIONS_RESOURCE: Final = "/crewai_plus/api/v1/me/organizations"
+    CREWS_RESOURCE: Final = "/crewai_plus/api/v1/crews"
+    AGENTS_RESOURCE: Final = "/crewai_plus/api/v1/agents"
+    TRACING_RESOURCE: Final = "/crewai_plus/api/v1/tracing"
+    EPHEMERAL_TRACING_RESOURCE: Final = "/crewai_plus/api/v1/tracing/ephemeral"
+    INTEGRATIONS_RESOURCE: Final = "/crewai_plus/api/v1/integrations"

    def __init__(self, api_key: str | None = None) -> None:
+        version = get_crewai_version()
        self.api_key = api_key
-        self.headers = {
+        self.headers: Headers = {
            "Content-Type": "application/json",
-            "User-Agent": f"CrewAI-CLI/{get_crewai_version()}",
-            "X-Crewai-Version": get_crewai_version(),
+            "User-Agent": f"CrewAI-CLI/{version}",
+            "X-Crewai-Version": version,
        }
        if api_key:
            self.headers["Authorization"] = f"Bearer {api_key}"
+
        settings = Settings()
        if settings.org_uuid:
            self.headers["X-Crewai-Organization-Id"] = settings.org_uuid
@@ -44,17 +169,30 @@ class PlusAPI:
        )

    def _make_request(
-        self, method: str, endpoint: str, **kwargs: Any
+        self,
+        method: HttpMethod,
+        endpoint: str,
+        *,
+        json: Any = None,
+        params: dict[str, str] | None = None,
+        timeout: float | None = None,
+        verify: bool = True,
    ) -> httpx.Response:
        url = urljoin(self.base_url, endpoint)
-        verify = kwargs.pop("verify", True)
+        request_kwargs: RequestKwargs = {"headers": cast(dict[str, str], self.headers)}
+        if json is not None:
+            request_kwargs["json"] = json
+        if params is not None:
+            request_kwargs["params"] = params
+        if timeout is not None:
+            request_kwargs["timeout"] = timeout
        with httpx.Client(trust_env=False, verify=verify) as client:
-            return client.request(method, url, headers=self.headers, **kwargs)
+            return client.request(method, url, **request_kwargs)

    def login_to_tool_repository(
        self, user_identifier: str | None = None
    ) -> httpx.Response:
-        payload = {}
+        payload: LoginPayload = {}
        if user_identifier:
            payload["user_identifier"] = user_identifier
        return self._make_request("POST", f"{self.TOOLS_RESOURCE}/login", json=payload)
@@ -65,7 +203,7 @@ class PlusAPI:
    async def get_agent(self, handle: str) -> httpx.Response:
        url = urljoin(self.base_url, f"{self.AGENTS_RESOURCE}/{handle}")
        async with httpx.AsyncClient() as client:
-            return await client.get(url, headers=self.headers)
+            return await client.get(url, headers=cast(dict[str, str], self.headers))

    def publish_tool(
        self,
@@ -74,10 +212,10 @@ class PlusAPI:
        version: str,
        description: str | None,
        encoded_file: str,
-        available_exports: list[dict[str, Any]] | None = None,
-        tools_metadata: list[dict[str, Any]] | None = None,
+        available_exports: list[AvailableExport] | None = None,
+        tools_metadata: list[ToolMetadata] | None = None,
    ) -> httpx.Response:
-        params = {
+        params: PublishToolPayload = {
            "handle": handle,
            "public": is_public,
            "version": version,
@@ -129,13 +267,13 @@ class PlusAPI:
    def list_crews(self) -> httpx.Response:
        return self._make_request("GET", self.CREWS_RESOURCE)

-    def create_crew(self, payload: dict[str, Any]) -> httpx.Response:
+    def create_crew(self, payload: CreateCrewPayload) -> httpx.Response:
        return self._make_request("POST", self.CREWS_RESOURCE, json=payload)

    def get_organizations(self) -> httpx.Response:
        return self._make_request("GET", self.ORGANIZATIONS_RESOURCE)

-    def initialize_trace_batch(self, payload: dict[str, Any]) -> httpx.Response:
+    def initialize_trace_batch(self, payload: TraceBatchInitPayload) -> httpx.Response:
        return self._make_request(
            "POST",
            f"{self.TRACING_RESOURCE}/batches",
@@ -144,7 +282,7 @@ class PlusAPI:
        )

    def initialize_ephemeral_trace_batch(
-        self, payload: dict[str, Any]
+        self, payload: TraceBatchInitPayload
    ) -> httpx.Response:
        return self._make_request(
            "POST",
@@ -153,7 +291,7 @@ class PlusAPI:
        )

    def send_trace_events(
-        self, trace_batch_id: str, payload: dict[str, Any]
+        self, trace_batch_id: str, payload: TraceEventsPayload
    ) -> httpx.Response:
        return self._make_request(
            "POST",
@@ -163,7 +301,7 @@ class PlusAPI:
        )

    def send_ephemeral_trace_events(
-        self, trace_batch_id: str, payload: dict[str, Any]
+        self, trace_batch_id: str, payload: TraceEventsPayload
    ) -> httpx.Response:
        return self._make_request(
            "POST",
@@ -173,7 +311,7 @@ class PlusAPI:
        )

    def finalize_trace_batch(
-        self, trace_batch_id: str, payload: dict[str, Any]
+        self, trace_batch_id: str, payload: TraceFinalizePayload
    ) -> httpx.Response:
        return self._make_request(
            "PATCH",
@@ -183,7 +321,7 @@ class PlusAPI:
        )

    def finalize_ephemeral_trace_batch(
-        self, trace_batch_id: str, payload: dict[str, Any]
+        self, trace_batch_id: str, payload: TraceFinalizePayload
    ) -> httpx.Response:
        return self._make_request(
            "PATCH",
@@ -195,20 +333,28 @@ class PlusAPI:
    def mark_trace_batch_as_failed(
        self, trace_batch_id: str, error_message: str
    ) -> httpx.Response:
+        payload: TraceFailedPayload = {
+            "status": "failed",
+            "failure_reason": error_message,
+        }
        return self._make_request(
            "PATCH",
            f"{self.TRACING_RESOURCE}/batches/{trace_batch_id}",
-            json={"status": "failed", "failure_reason": error_message},
+            json=payload,
            timeout=30,
        )

    def mark_ephemeral_trace_batch_as_failed(
        self, trace_batch_id: str, error_message: str
    ) -> httpx.Response:
+        payload: TraceFailedPayload = {
+            "status": "failed",
+            "failure_reason": error_message,
+        }
        return self._make_request(
            "PATCH",
            f"{self.EPHEMERAL_TRACING_RESOURCE}/batches/{trace_batch_id}",
-            json={"status": "failed", "failure_reason": error_message},
+            json=payload,
            timeout=30,
        )

--- a/lib/crewai-files/src/crewai_files/init.py
+++ b/lib/crewai-files/src/crewai_files/init.py
@@ -152,4 +152,4 @@ __all__ = [
    "wrap_file_source",
 ]

-__version__ = "1.14.5a5"
+__version__ = "1.14.5"
--- a/lib/crewai-tools/pyproject.toml
+++ b/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==1.14.5a5",
+    "crewai==1.14.5",
    "tiktoken>=0.8.0,<0.13",
    "beautifulsoup4~=4.13.4",
    "python-docx~=1.2.0",
--- a/lib/crewai-tools/src/crewai_tools/init.py
+++ b/lib/crewai-tools/src/crewai_tools/init.py
@@ -330,4 +330,4 @@ __all__ = [
    "ZapierActionTools",
 ]

-__version__ = "1.14.5a5"
+__version__ = "1.14.5"
--- a/lib/crewai/pyproject.toml
+++ b/lib/crewai/pyproject.toml
@@ -8,8 +8,8 @@ authors = [
 ]
 requires-python = ">=3.10, <3.14"
 dependencies = [
-    "crewai-core==1.14.5a5",
-    "crewai-cli==1.14.5a5",
+    "crewai-core==1.14.5",
+    "crewai-cli==1.14.5",
    # Core Dependencies
    "pydantic>=2.11.9,<2.13",
    "openai>=2.30.0,<3",
@@ -54,7 +54,7 @@ Repository = "https://github.com/crewAIInc/crewAI"

 [project.optional-dependencies]
 tools = [
-    "crewai-tools==1.14.5a5",
+    "crewai-tools==1.14.5",
 ]
 embeddings = [
    "tiktoken>=0.8.0,<0.13"
@@ -105,7 +105,7 @@ a2a = [
     "aiocache[redis,memcached]~=0.12.3",
 ]
 file-processing = [
-    "crewai-files==1.14.5a5",
+    "crewai-files",
 ]
 qdrant-edge = [
    "qdrant-edge-py>=0.6.0",
--- a/lib/crewai/src/crewai/init.py
+++ b/lib/crewai/src/crewai/init.py
@@ -48,7 +48,7 @@ def _suppress_pydantic_deprecation_warnings() -> None:

 _suppress_pydantic_deprecation_warnings()

-__version__ = "1.14.5a5"
+__version__ = "1.14.5"

 _LAZY_IMPORTS: dict[str, tuple[str, str]] = {
    "Memory": ("crewai.memory.unified_memory", "Memory"),
--- a/lib/crewai/src/crewai/agent/core.py
+++ b/lib/crewai/src/crewai/agent/core.py
@@ -220,7 +220,11 @@ class Agent(BaseAgent):
        str | BaseLLM | None,
        BeforeValidator(_validate_llm_ref),
        PlainSerializer(_serialize_llm_ref, return_type=dict | None, when_used="json"),
-    ] = Field(description="Language model that will run the agent.", default=None)
+    ] = Field(
+        description="Language model that will run the agent.",
+        default=None,
+        deprecated="function_calling_llm is deprecated and will be removed in a future release.",
+    )
    system_template: str | None = Field(
        default=None, description="System format for the agent."
    )
--- a/lib/crewai/src/crewai/agents/agent_adapters/langgraph/langgraph_adapter.py
+++ b/lib/crewai/src/crewai/agents/agent_adapters/langgraph/langgraph_adapter.py
@@ -51,7 +51,10 @@ class LangGraphAgentAdapter(BaseAgentAdapter):
    _graph: Any = PrivateAttr(default=None)
    _memory: Any = PrivateAttr(default=None)
    _max_iterations: int = PrivateAttr(default=10)
-    function_calling_llm: Any = Field(default=None)
+    function_calling_llm: Any = Field(
+        default=None,
+        deprecated="function_calling_llm is deprecated and will be removed in a future release.",
+    )
    step_callback: SerializableCallable | None = Field(default=None)

    model: str = Field(default="gpt-4o")
--- a/lib/crewai/src/crewai/agents/agent_adapters/openai_agents/openai_adapter.py
+++ b/lib/crewai/src/crewai/agents/agent_adapters/openai_agents/openai_adapter.py
@@ -60,7 +60,10 @@ class OpenAIAgentAdapter(BaseAgentAdapter):
    _openai_agent: OpenAIAgentProtocol = PrivateAttr()
    _logger: Logger = PrivateAttr(default_factory=Logger)
    _active_thread: str | None = PrivateAttr(default=None)
-    function_calling_llm: Any = Field(default=None)
+    function_calling_llm: Any = Field(
+        default=None,
+        deprecated="function_calling_llm is deprecated and will be removed in a future release.",
+    )
    step_callback: Any = Field(default=None)
    _tool_adapter: OpenAIAgentToolAdapter = PrivateAttr()
    _converter_adapter: OpenAIConverterAdapter = PrivateAttr()
--- a/lib/crewai/src/crewai/agents/agent_builder/base_agent.py
+++ b/lib/crewai/src/crewai/agents/agent_builder/base_agent.py
@@ -127,6 +127,13 @@ def _validate_executor_ref(value: Any) -> Any:
    return value


+def _serialize_executor_ref(value: Any) -> dict[str, Any] | None:
+    if value is None:
+        return None
+    result: dict[str, Any] = value.model_dump(mode="json")
+    return result
+
+
 def _serialize_llm_ref(value: Any) -> dict[str, Any] | None:
    if value is None:
        return None
@@ -251,14 +258,13 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
    max_iter: int = Field(
        default=25, description="Maximum iterations for an agent to execute a task"
    )
-    agent_executor: SerializeAsAny[BaseAgentExecutor] | None = Field(
-        default=None, description="An instance of the CrewAgentExecutor class."
-    )
-
-    @field_validator("agent_executor", mode="before")
-    @classmethod
-    def _validate_agent_executor(cls, v: Any) -> Any:
-        return _validate_executor_ref(v)
+    agent_executor: Annotated[
+        SerializeAsAny[BaseAgentExecutor] | None,
+        BeforeValidator(_validate_executor_ref),
+        PlainSerializer(
+            _serialize_executor_ref, return_type=dict | None, when_used="json"
+        ),
+    ] = Field(default=None, description="An instance of the CrewAgentExecutor class.")

    llm: Annotated[
        str | BaseLLM | None,
@@ -326,7 +332,13 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
        default=None,
        description="List of MCP server references. Supports 'https://server.com/path' for external servers and bare slugs like 'notion' for connected MCP integrations. Use '#tool_name' suffix for specific tools.",
    )
-    memory: bool | Memory | MemoryScope | MemorySlice | None = Field(
+    memory: (
+        bool
+        | Annotated[
+            Memory | MemoryScope | MemorySlice, Field(discriminator="memory_kind")
+        ]
+        | None
+    ) = Field(
        default=None,
        description=(
            "Enable agent memory. Pass True for default Memory(), "
--- a/lib/crewai/src/crewai/crew.py
+++ b/lib/crewai/src/crewai/crew.py
@@ -223,7 +223,13 @@ class Crew(FlowTrackable, BaseModel):
    ] = Field(default_factory=list)
    process: Process = Field(default=Process.sequential)
    verbose: bool = Field(default=False)
-    memory: bool | Memory | MemoryScope | MemorySlice | None = Field(
+    memory: (
+        bool
+        | Annotated[
+            Memory | MemoryScope | MemorySlice, Field(discriminator="memory_kind")
+        ]
+        | None
+    ) = Field(
        default=False,
        description=(
            "Enable crew memory. Pass True for default Memory(), "
@@ -251,7 +257,11 @@ class Crew(FlowTrackable, BaseModel):
        str | LLM | None,
        BeforeValidator(_validate_llm_ref),
        PlainSerializer(_serialize_llm_ref, return_type=dict | None, when_used="json"),
-    ] = Field(description="Language model that will run the agent.", default=None)
+    ] = Field(
+        description="Language model that will run the agent.",
+        default=None,
+        deprecated="function_calling_llm is deprecated and will be removed in a future release.",
+    )
    config: Json[dict[str, Any]] | dict[str, Any] | None = Field(default=None)
    id: UUID4 = Field(default_factory=uuid.uuid4, frozen=True)
    share_crew: bool | None = Field(default=False)
--- a/lib/crewai/src/crewai/events/listeners/tracing/trace_batch_manager.py
+++ b/lib/crewai/src/crewai/events/listeners/tracing/trace_batch_manager.py
@@ -6,6 +6,14 @@ import time
 from typing import Any
 import uuid

+from crewai_core.plus_api import (
+    TraceBatchInitPayload,
+    TraceBatchMetadata,
+    TraceEventsPayload,
+    TraceExecutionContext,
+    TraceExecutionMetadata,
+    TraceFinalizePayload,
+)
 from crewai_core.settings import Settings
 from rich.console import Console
 from rich.panel import Panel
@@ -123,25 +131,27 @@ class TraceBatchManager:
            return None

        try:
-            payload = {
+            execution_context: TraceExecutionContext = {
+                "crew_fingerprint": execution_metadata.get("crew_fingerprint"),
+                "crew_name": execution_metadata.get("crew_name", None),
+                "flow_name": execution_metadata.get("flow_name", None),
+                "crewai_version": self.current_batch.version,
+                "privacy_level": user_context.get("privacy_level", "standard"),
+            }
+            execution_metadata_payload: TraceExecutionMetadata = {
+                "expected_duration_estimate": execution_metadata.get(
+                    "expected_duration_estimate", 300
+                ),
+                "agent_count": execution_metadata.get("agent_count", 0),
+                "task_count": execution_metadata.get("task_count", 0),
+                "flow_method_count": execution_metadata.get("flow_method_count", 0),
+                "execution_started_at": datetime.now(timezone.utc).isoformat(),
+            }
+            payload: TraceBatchInitPayload = {
                "trace_id": self.current_batch.batch_id,
                "execution_type": execution_metadata.get("execution_type", "crew"),
-                "execution_context": {
-                    "crew_fingerprint": execution_metadata.get("crew_fingerprint"),
-                    "crew_name": execution_metadata.get("crew_name", None),
-                    "flow_name": execution_metadata.get("flow_name", None),
-                    "crewai_version": self.current_batch.version,
-                    "privacy_level": user_context.get("privacy_level", "standard"),
-                },
-                "execution_metadata": {
-                    "expected_duration_estimate": execution_metadata.get(
-                        "expected_duration_estimate", 300
-                    ),
-                    "agent_count": execution_metadata.get("agent_count", 0),
-                    "task_count": execution_metadata.get("task_count", 0),
-                    "flow_method_count": execution_metadata.get("flow_method_count", 0),
-                    "execution_started_at": datetime.now(timezone.utc).isoformat(),
-                },
+                "execution_context": execution_context,
+                "execution_metadata": execution_metadata_payload,
            }
            if use_ephemeral:
                payload["ephemeral_trace_id"] = self.current_batch.batch_id
@@ -264,13 +274,14 @@ class TraceBatchManager:
        if not self.plus_api or not self.trace_batch_id or not self.event_buffer:
            return 500
        try:
-            payload = {
+            batch_metadata: TraceBatchMetadata = {
+                "events_count": len(self.event_buffer),
+                "batch_sequence": 1,
+                "is_final_batch": False,
+            }
+            payload: TraceEventsPayload = {
                "events": [event.to_dict() for event in self.event_buffer],
-                "batch_metadata": {
-                    "events_count": len(self.event_buffer),
-                    "batch_sequence": 1,
-                    "is_final_batch": False,
-                },
+                "batch_metadata": batch_metadata,
            }

            response = (
@@ -364,7 +375,7 @@ class TraceBatchManager:
            return

        try:
-            payload = {
+            payload: TraceFinalizePayload = {
                "status": "completed",
                "duration_ms": self.calculate_duration("execution"),
                "final_event_count": events_count,
--- a/lib/crewai/src/crewai/flow/flow.py
+++ b/lib/crewai/src/crewai/flow/flow.py
@@ -159,6 +159,36 @@ def _resolve_persistence(value: Any) -> Any:
    return value


+def _serialize_persistence(value: Any) -> dict[str, Any] | None:
+    if value is None:
+        return None
+    if isinstance(value, FlowPersistence):
+        return value.model_dump(mode="json")
+    return None
+
+
+def _validate_input_provider(value: Any) -> Any:
+    if value is None or isinstance(value, InputProvider):
+        return value
+    from crewai.types.callback import _dotted_path_to_instance
+
+    resolved = _dotted_path_to_instance(value)
+    if resolved is None or isinstance(resolved, InputProvider):
+        return resolved
+    raise ValueError(
+        f"Resolved input_provider {resolved!r} does not implement the "
+        "InputProvider protocol (missing request_input)."
+    )
+
+
+def _serialize_input_provider(value: Any) -> str | None:
+    if value is None:
+        return None
+    from crewai.types.callback import _instance_to_dotted_path
+
+    return _instance_to_dotted_path(value)
+
+
 _INITIAL_STATE_CLASS_MARKER = "__crewai_pydantic_class_schema__"


@@ -949,15 +979,29 @@ class Flow(BaseModel, Generic[T], metaclass=FlowMeta):
    name: str | None = Field(default=None)
    tracing: bool | None = Field(default=None)
    stream: bool = Field(default=False)
-    memory: Memory | MemoryScope | MemorySlice | None = Field(default=None)
-    input_provider: InputProvider | None = Field(default=None)
+    memory: (
+        Annotated[
+            Memory | MemoryScope | MemorySlice, Field(discriminator="memory_kind")
+        ]
+        | None
+    ) = Field(default=None)
+    input_provider: Annotated[
+        InputProvider | None,
+        BeforeValidator(_validate_input_provider),
+        PlainSerializer(
+            _serialize_input_provider, return_type=str | None, when_used="json"
+        ),
+    ] = Field(default=None)
    suppress_flow_events: bool = Field(default=False)
    human_feedback_history: list[HumanFeedbackResult] = Field(default_factory=list)
    last_human_feedback: HumanFeedbackResult | None = Field(default=None)

    persistence: Annotated[
-        SerializeAsAny[FlowPersistence] | Any,
+        SerializeAsAny[FlowPersistence] | None,
        BeforeValidator(lambda v, _: _resolve_persistence(v)),
+        PlainSerializer(
+            _serialize_persistence, return_type=dict | None, when_used="json"
+        ),
    ] = Field(default=None)
    max_method_calls: int = Field(default=100)

--- a/lib/crewai/src/crewai/knowledge/knowledge.py
+++ b/lib/crewai/src/crewai/knowledge/knowledge.py
@@ -1,16 +1,95 @@
 import os
+from typing import Annotated, Any

-from pydantic import BaseModel, ConfigDict, Field
+from pydantic import BaseModel, BeforeValidator, ConfigDict, Field, PlainSerializer

 from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
+from crewai.knowledge.source.crew_docling_source import CrewDoclingSource
+from crewai.knowledge.source.csv_knowledge_source import CSVKnowledgeSource
+from crewai.knowledge.source.excel_knowledge_source import ExcelKnowledgeSource
+from crewai.knowledge.source.json_knowledge_source import JSONKnowledgeSource
+from crewai.knowledge.source.pdf_knowledge_source import PDFKnowledgeSource
+from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
+from crewai.knowledge.source.text_file_knowledge_source import (
+    TextFileKnowledgeSource,
+)
 from crewai.knowledge.storage.knowledge_storage import KnowledgeStorage
+from crewai.rag.core.base_embeddings_provider import BaseEmbeddingsProvider
 from crewai.rag.embeddings.types import EmbedderConfig
 from crewai.rag.types import SearchResult


+_KNOWN_SOURCES: dict[str, type[BaseKnowledgeSource]] = {
+    "string": StringKnowledgeSource,
+    "docling": CrewDoclingSource,
+    "csv": CSVKnowledgeSource,
+    "excel": ExcelKnowledgeSource,
+    "json": JSONKnowledgeSource,
+    "pdf": PDFKnowledgeSource,
+    "text_file": TextFileKnowledgeSource,
+}
+
+
+def _resolve_knowledge_sources(value: Any) -> Any:
+    """Coerce list of dicts into typed BaseKnowledgeSource subclasses via source_type.
+
+    Pass-through for anything else (existing instances, mocks).
+    """
+    if not isinstance(value, list):
+        return value
+    resolved: list[Any] = []
+    for idx, item in enumerate(value):
+        if isinstance(item, dict):
+            tag = item.get("source_type")
+            cls = _KNOWN_SOURCES.get(tag) if isinstance(tag, str) else None
+            if cls is None:
+                resolved.append(item)
+            else:
+                try:
+                    resolved.append(cls.model_validate(item))
+                except Exception as exc:
+                    raise ValueError(
+                        f"Failed to validate knowledge source at index {idx} "
+                        f"with source_type={tag!r}: {exc}"
+                    ) from exc
+        else:
+            resolved.append(item)
+    return resolved
+
+
 os.environ["TOKENIZERS_PARALLELISM"] = "false"  # removes logging from fastembed


+def _serialize_embedder_spec(value: Any) -> dict[str, Any] | None:
+    if value is None:
+        return None
+    if isinstance(value, BaseEmbeddingsProvider):
+        return value.model_dump(mode="json")
+    if isinstance(value, type) and issubclass(value, BaseEmbeddingsProvider):
+        return {"provider_class": f"{value.__module__}.{value.__qualname__}"}
+    if isinstance(value, dict):
+        return value
+    raise TypeError(
+        f"Cannot serialize embedder of type {type(value).__name__}: "
+        "expected ProviderSpec dict, BaseEmbeddingsProvider instance, or subclass."
+    )
+
+
+def _validate_embedder_spec(value: Any) -> Any:
+    """Resolve provider_class dotted-path dicts back to a class on restore."""
+    if isinstance(value, dict) and set(value.keys()) == {"provider_class"}:
+        from crewai.types.callback import _resolve_dotted_path
+
+        cls = _resolve_dotted_path(value["provider_class"])
+        if not isinstance(cls, type) or not issubclass(cls, BaseEmbeddingsProvider):
+            raise ValueError(
+                f"provider_class {value['provider_class']!r} did not resolve to a "
+                "BaseEmbeddingsProvider subclass."
+            )
+        return cls
+    return value
+
+
 class Knowledge(BaseModel):
    """
    Knowledge is a collection of sources and setup for the vector store to save and query relevant context.
@@ -20,10 +99,19 @@ class Knowledge(BaseModel):
        embedder: EmbedderConfig | None = None
    """

-    sources: list[BaseKnowledgeSource] = Field(default_factory=list)
+    sources: Annotated[
+        list[BaseKnowledgeSource],
+        BeforeValidator(_resolve_knowledge_sources),
+    ] = Field(default_factory=list)
    model_config = ConfigDict(arbitrary_types_allowed=True)
    storage: KnowledgeStorage | None = Field(default=None)
-    embedder: EmbedderConfig | None = None
+    embedder: Annotated[
+        EmbedderConfig | None,
+        BeforeValidator(_validate_embedder_spec),
+        PlainSerializer(
+            _serialize_embedder_spec, return_type=dict | None, when_used="json"
+        ),
+    ] = None
    collection_name: str | None = None

    def __init__(
--- a/lib/crewai/src/crewai/knowledge/source/base_knowledge_source.py
+++ b/lib/crewai/src/crewai/knowledge/source/base_knowledge_source.py
@@ -13,7 +13,9 @@ class BaseKnowledgeSource(BaseModel, ABC):
    chunk_size: int = 4000
    chunk_overlap: int = 200
    chunks: list[str] = Field(default_factory=list)
-    chunk_embeddings: list[np.ndarray[Any, np.dtype[Any]]] = Field(default_factory=list)
+    chunk_embeddings: list[np.ndarray[Any, np.dtype[Any]]] = Field(
+        default_factory=list, exclude=True
+    )

    model_config = ConfigDict(arbitrary_types_allowed=True)
    storage: KnowledgeStorage | None = Field(default=None)
--- a/lib/crewai/src/crewai/knowledge/source/crew_docling_source.py
+++ b/lib/crewai/src/crewai/knowledge/source/crew_docling_source.py
@@ -2,7 +2,7 @@ from __future__ import annotations

 from collections.abc import Iterator
 from pathlib import Path
-from typing import TYPE_CHECKING, Any
+from typing import TYPE_CHECKING, Any, Literal
 from urllib.parse import urlparse


@@ -45,6 +45,7 @@ class CrewDoclingSource(BaseKnowledgeSource):

    _logger: Logger = Logger(verbose=True)

+    source_type: Literal["docling"] = "docling"
    file_path: list[Path | str] | None = Field(default=None)
    file_paths: list[Path | str] = Field(default_factory=list)
    chunks: list[str] = Field(default_factory=list)
--- a/lib/crewai/src/crewai/knowledge/source/csv_knowledge_source.py
+++ b/lib/crewai/src/crewai/knowledge/source/csv_knowledge_source.py
@@ -1,5 +1,6 @@
 import csv
 from pathlib import Path
+from typing import Literal

 from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledgeSource

@@ -7,6 +8,8 @@ from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledge
 class CSVKnowledgeSource(BaseFileKnowledgeSource):
    """A knowledge source that stores and queries CSV file content using embeddings."""

+    source_type: Literal["csv"] = "csv"
+
    def load_content(self) -> dict[Path, str]:
        """Load and preprocess CSV file content."""
        content_dict = {}
--- a/lib/crewai/src/crewai/knowledge/source/excel_knowledge_source.py
+++ b/lib/crewai/src/crewai/knowledge/source/excel_knowledge_source.py
@@ -1,6 +1,6 @@
 from pathlib import Path
 from types import ModuleType
-from typing import Any
+from typing import Any, Literal

 from pydantic import Field, field_validator

@@ -16,6 +16,7 @@ class ExcelKnowledgeSource(BaseKnowledgeSource):

    _logger: Logger = Logger(verbose=True)

+    source_type: Literal["excel"] = "excel"
    file_path: Path | list[Path] | str | list[str] | None = Field(
        default=None,
        description="[Deprecated] The path to the file. Use file_paths instead.",
--- a/lib/crewai/src/crewai/knowledge/source/json_knowledge_source.py
+++ b/lib/crewai/src/crewai/knowledge/source/json_knowledge_source.py
@@ -1,6 +1,6 @@
 import json
 from pathlib import Path
-from typing import Any
+from typing import Any, Literal

 from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledgeSource

@@ -8,6 +8,8 @@ from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledge
 class JSONKnowledgeSource(BaseFileKnowledgeSource):
    """A knowledge source that stores and queries JSON file content using embeddings."""

+    source_type: Literal["json"] = "json"
+
    def load_content(self) -> dict[Path, str]:
        """Load and preprocess JSON file content."""
        content: dict[Path, str] = {}
--- a/lib/crewai/src/crewai/knowledge/source/pdf_knowledge_source.py
+++ b/lib/crewai/src/crewai/knowledge/source/pdf_knowledge_source.py
@@ -1,5 +1,6 @@
 from pathlib import Path
 from types import ModuleType
+from typing import Literal

 from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledgeSource

@@ -7,6 +8,8 @@ from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledge
 class PDFKnowledgeSource(BaseFileKnowledgeSource):
    """A knowledge source that stores and queries PDF file content using embeddings."""

+    source_type: Literal["pdf"] = "pdf"
+
    def load_content(self) -> dict[Path, str]:
        """Load and preprocess PDF file content."""
        pdfplumber = self._import_pdfplumber()
--- a/lib/crewai/src/crewai/knowledge/source/string_knowledge_source.py
+++ b/lib/crewai/src/crewai/knowledge/source/string_knowledge_source.py
@@ -1,4 +1,4 @@
-from typing import Any
+from typing import Any, Literal

 from pydantic import Field

@@ -8,6 +8,7 @@ from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
 class StringKnowledgeSource(BaseKnowledgeSource):
    """A knowledge source that stores and queries plain text content using embeddings."""

+    source_type: Literal["string"] = "string"
    content: str = Field(...)
    collection_name: str | None = Field(default=None)

--- a/lib/crewai/src/crewai/knowledge/source/text_file_knowledge_source.py
+++ b/lib/crewai/src/crewai/knowledge/source/text_file_knowledge_source.py
@@ -1,4 +1,5 @@
 from pathlib import Path
+from typing import Literal

 from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledgeSource

@@ -6,6 +7,8 @@ from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledge
 class TextFileKnowledgeSource(BaseFileKnowledgeSource):
    """A knowledge source that stores and queries text file content using embeddings."""

+    source_type: Literal["text_file"] = "text_file"
+
    def load_content(self) -> dict[Path, str]:
        """Load and preprocess text file content."""
        content = {}
--- a/lib/crewai/src/crewai/llm.py
+++ b/lib/crewai/src/crewai/llm.py
@@ -940,6 +940,21 @@ class LLM(BaseLLM):
                self._track_token_usage_internal(usage_info)
            self._handle_streaming_callbacks(callbacks, usage_info, last_chunk)

+            if accumulated_tool_args and not available_functions:
+                tool_calls_list: list[ChatCompletionDeltaToolCall] = [
+                    ChatCompletionDeltaToolCall(
+                        index=idx,
+                        function=Function(
+                            name=tool_arg.function.name,
+                            arguments=tool_arg.function.arguments,
+                        ),
+                    )
+                    for idx, tool_arg in sorted(accumulated_tool_args.items())
+                    if tool_arg.function.name
+                ]
+                if tool_calls_list:
+                    return tool_calls_list
+
            if not tool_calls or not available_functions:
                if response_model and self.is_litellm:
                    instructor_instance = InternalInstructor(
@@ -1535,8 +1550,7 @@ class LLM(BaseLLM):
            if usage_info:
                self._track_token_usage_internal(usage_info)

-            if accumulated_tool_args and available_functions:
-                # Convert accumulated tool args to ChatCompletionDeltaToolCall objects
+            if accumulated_tool_args:
                tool_calls_list: list[ChatCompletionDeltaToolCall] = [
                    ChatCompletionDeltaToolCall(
                        index=idx,
@@ -1545,21 +1559,24 @@ class LLM(BaseLLM):
                            arguments=tool_arg.function.arguments,
                        ),
                    )
-                    for idx, tool_arg in accumulated_tool_args.items()
+                    for idx, tool_arg in sorted(accumulated_tool_args.items())
                    if tool_arg.function.name
                ]

                if tool_calls_list:
-                    result = self._handle_streaming_tool_calls(
-                        tool_calls=tool_calls_list,
-                        accumulated_tool_args=accumulated_tool_args,
-                        available_functions=available_functions,
-                        from_task=from_task,
-                        from_agent=from_agent,
-                        response_id=response_id,
-                    )
-                    if result is not None:
-                        return result
+                    if available_functions:
+                        result = self._handle_streaming_tool_calls(
+                            tool_calls=tool_calls_list,
+                            accumulated_tool_args=accumulated_tool_args,
+                            available_functions=available_functions,
+                            from_task=from_task,
+                            from_agent=from_agent,
+                            response_id=response_id,
+                        )
+                        if result is not None:
+                            return result
+                    else:
+                        return tool_calls_list

            usage_dict = self._usage_to_dict(usage_info)
            self._handle_emit_call_events(
--- a/lib/crewai/src/crewai/memory/memory_scope.py
+++ b/lib/crewai/src/crewai/memory/memory_scope.py
@@ -6,6 +6,7 @@ from datetime import datetime
 from typing import Any, Literal

 from pydantic import BaseModel, ConfigDict, Field, PrivateAttr, model_validator
+from typing_extensions import Self

 from crewai.memory.types import (
    _RECALL_OVERSAMPLE_FACTOR,
@@ -21,6 +22,8 @@ class MemoryScope(BaseModel):

    model_config = ConfigDict(arbitrary_types_allowed=True)

+    memory_kind: Literal["scope"] = "scope"
+
    root_path: str = Field(default="/")

    _memory: Memory = PrivateAttr()
@@ -34,17 +37,25 @@ class MemoryScope(BaseModel):
            return data
        if not isinstance(data, dict):
            raise ValueError(f"Expected dict or MemoryScope, got {type(data).__name__}")
-        if "memory" not in data:
-            raise ValueError("MemoryScope requires a 'memory' key")
-        memory = data.pop("memory")
+        memory = data.pop("memory", None)
        instance: MemoryScope = handler(data)
-        instance._memory = memory
+        if memory is not None:
+            instance._memory = memory
        root = instance.root_path.rstrip("/") or ""
        if root and not root.startswith("/"):
            root = "/" + root
        instance._root = root
        return instance

+    def bind(self, memory: Memory) -> Self:
+        """Rebind the runtime ``Memory`` dependency after restore.
+
+        Required after deserializing from a checkpoint, since the live
+        ``Memory`` cannot be serialized.
+        """
+        self._memory = memory
+        return self
+
    @property
    def read_only(self) -> bool:
        """Whether the underlying memory is read-only."""
@@ -191,6 +202,8 @@ class MemorySlice(BaseModel):

    model_config = ConfigDict(arbitrary_types_allowed=True)

+    memory_kind: Literal["slice"] = "slice"
+
    scopes: list[str] = Field(default_factory=list)
    categories: list[str] | None = Field(default=None)
    read_only: bool = Field(default=True)
@@ -205,14 +218,18 @@ class MemorySlice(BaseModel):
            return data
        if not isinstance(data, dict):
            raise ValueError(f"Expected dict or MemorySlice, got {type(data).__name__}")
-        if "memory" not in data:
-            raise ValueError("MemorySlice requires a 'memory' key")
-        memory = data.pop("memory")
+        memory = data.pop("memory", None)
        data["scopes"] = [s.rstrip("/") or "/" for s in data.get("scopes", [])]
        instance: MemorySlice = handler(data)
-        instance._memory = memory
+        if memory is not None:
+            instance._memory = memory
        return instance

+    def bind(self, memory: Memory) -> Self:
+        """Rebind the runtime ``Memory`` dependency after restore."""
+        self._memory = memory
+        return self
+
    def remember(
        self,
        content: str,
--- a/lib/crewai/src/crewai/memory/unified_memory.py
+++ b/lib/crewai/src/crewai/memory/unified_memory.py
@@ -63,6 +63,8 @@ class Memory(BaseModel):

    model_config = ConfigDict(arbitrary_types_allowed=True)

+    memory_kind: Literal["memory"] = "memory"
+
    llm: Annotated[BaseLLM | str, PlainValidator(_passthrough)] = Field(
        default="gpt-4o-mini",
        description="LLM for analysis (model name or BaseLLM instance).",
--- a/lib/crewai/src/crewai/state/runtime.py
+++ b/lib/crewai/src/crewai/state/runtime.py
@@ -113,12 +113,48 @@ def _migrate(data: dict[str, Any]) -> dict[str, Any]:
        )

    # --- migrations in version order ---
-    # if stored < Version("X.Y.Z"):
-    #     data.setdefault("some_field", "default")
+    if stored < Version("1.14.6"):
+        for entity in data.get("entities") or []:
+            _backfill_discriminators(entity)

    return data


+def _backfill_memory_kind(value: Any) -> None:
+    """Infer ``memory_kind`` from structural fields on legacy memory dicts."""
+    if not isinstance(value, dict) or "memory_kind" in value:
+        return
+    if "scopes" in value:
+        value["memory_kind"] = "slice"
+    elif "root_path" in value:
+        value["memory_kind"] = "scope"
+    else:
+        value["memory_kind"] = "memory"
+
+
+def _backfill_source_type(source: Any) -> None:
+    """Infer ``source_type`` for legacy knowledge source dicts when possible."""
+    if not isinstance(source, dict) or "source_type" in source:
+        return
+    if "content" in source:
+        source["source_type"] = "string"
+
+
+def _backfill_discriminators(entity: Any) -> None:
+    """Walk an entity dict and backfill discriminator fields added in 1.14.6."""
+    if not isinstance(entity, dict):
+        return
+    _backfill_memory_kind(entity.get("memory"))
+    for agent in entity.get("agents") or []:
+        _backfill_memory_kind(agent.get("memory") if isinstance(agent, dict) else None)
+    for container in (entity.get("knowledge"), entity):
+        if isinstance(container, dict):
+            for src in (
+                container.get("sources") or container.get("knowledge_sources") or []
+            ):
+                _backfill_source_type(src)
+
+
 class RuntimeState(RootModel):  # type: ignore[type-arg]
    root: list[Entity]
    _provider: BaseProvider = PrivateAttr(default_factory=JsonProvider)
--- a/lib/crewai/src/crewai/types/callback.py
+++ b/lib/crewai/src/crewai/types/callback.py
@@ -150,3 +150,55 @@ SerializableCallable = Annotated[
    PlainSerializer(callable_to_string, return_type=str, when_used="json"),
    WithJsonSchema({"type": "string"}),
 ]
+
+
+def _instance_to_dotted_path(value: Any) -> str:
+    """Serialize an instance to a dotted path naming its class."""
+    cls = type(value)
+    module = getattr(cls, "__module__", None)
+    qualname = getattr(cls, "__qualname__", None)
+    if module is None or qualname is None:
+        raise ValueError(
+            f"Cannot serialize {value!r}: class missing __module__ or __qualname__. "
+            "Use a module-level class for checkpointable instances."
+        )
+    if qualname.endswith("<lambda>") or "<locals>" in qualname:
+        raise ValueError(
+            f"Cannot serialize {value!r}: class defined in <locals>. "
+            "Use a module-level class for checkpointable instances."
+        )
+    return f"{module}.{qualname}"
+
+
+def _dotted_path_to_instance(value: Any) -> Any:
+    """Resolve a dotted path to a class and instantiate it with no args.
+
+    If *value* is already a non-string object it is returned as-is.
+    """
+    if value is None or not isinstance(value, str):
+        return value
+    if "." not in value:
+        raise ValueError(
+            f"Invalid provider path {value!r}: expected 'module.name' format"
+        )
+    if not os.environ.get("CREWAI_DESERIALIZE_CALLBACKS"):
+        raise ValueError(
+            f"Refusing to resolve provider path {value!r}: "
+            "set CREWAI_DESERIALIZE_CALLBACKS=1 to allow. "
+            "Only enable this for trusted checkpoint data."
+        )
+    cls = _resolve_dotted_path(value)
+    if not inspect.isclass(cls):
+        raise ValueError(
+            f"Invalid provider path {value!r}: expected a class, got "
+            f"{type(cls).__name__}"
+        )
+    return cls()
+
+
+SerializableInstance = Annotated[
+    Any,
+    BeforeValidator(_dotted_path_to_instance),
+    PlainSerializer(_instance_to_dotted_path, return_type=str, when_used="json"),
+    WithJsonSchema({"type": "string"}),
+]
--- a/lib/crewai/src/crewai/utilities/project_utils.py
+++ b/lib/crewai/src/crewai/utilities/project_utils.py
@@ -13,6 +13,7 @@ import sys
 import types
 from typing import Any, cast, get_type_hints

+from crewai_core.plus_api import AvailableExport, EnvVarEntry, ToolMetadata
 from crewai_core.project import (
    get_project_description as get_project_description,
    get_project_name as get_project_name,
@@ -279,7 +280,7 @@ def is_valid_tool(obj: Any) -> bool:
    return isinstance(obj, Tool)


-def extract_available_exports(dir_path: str = "src") -> list[dict[str, Any]]:
+def extract_available_exports(dir_path: str = "src") -> list[AvailableExport]:
    """Extract available tool classes from the project's __init__.py files.

    Only includes classes that inherit from BaseTool or functions decorated with @tool.
@@ -338,7 +339,7 @@ def _load_module_from_file(
        sys.modules.pop(module_name, None)


-def _load_tools_from_init(init_file: Path) -> list[dict[str, Any]]:
+def _load_tools_from_init(init_file: Path) -> list[AvailableExport]:
    """Load and validate tools from a given __init__.py file."""
    try:
        with _load_module_from_file(init_file) as module:
@@ -392,7 +393,7 @@ def _print_no_tools_warning() -> None:
    )


-def extract_tools_metadata(dir_path: str = "src") -> list[dict[str, Any]]:
+def extract_tools_metadata(dir_path: str = "src") -> list[ToolMetadata]:
    """
    Extract rich metadata from tool classes in the project.

@@ -404,7 +405,7 @@ def extract_tools_metadata(dir_path: str = "src") -> list[dict[str, Any]]:
    - init_params_schema: JSON Schema for __init__ params (filtered)
    - env_vars: List of environment variable dicts
    """
-    tools_metadata: list[dict[str, Any]] = []
+    tools_metadata: list[ToolMetadata] = []

    for init_file in Path(dir_path).glob("**/__init__.py"):
        tools = _extract_tool_metadata_from_init(init_file)
@@ -413,7 +414,7 @@ def extract_tools_metadata(dir_path: str = "src") -> list[dict[str, Any]]:
    return tools_metadata


-def _extract_tool_metadata_from_init(init_file: Path) -> list[dict[str, Any]]:
+def _extract_tool_metadata_from_init(init_file: Path) -> list[ToolMetadata]:
    """
    Load module from init file and extract metadata from valid tool classes.
    """
@@ -428,7 +429,7 @@ def _extract_tool_metadata_from_init(init_file: Path) -> list[dict[str, Any]]:
            if not exported_names:
                return []

-            tools_metadata = []
+            tools_metadata: list[ToolMetadata] = []
            for name in exported_names:
                obj = getattr(module, name, None)
                if obj is None or not (
@@ -446,7 +447,7 @@ def _extract_tool_metadata_from_init(init_file: Path) -> list[dict[str, Any]]:
        return []


-def _extract_single_tool_metadata(tool_class: type) -> dict[str, Any] | None:
+def _extract_single_tool_metadata(tool_class: type) -> ToolMetadata | None:
    """
    Extract metadata from a single tool class.
    """
@@ -470,19 +471,17 @@ def _extract_single_tool_metadata(tool_class: type) -> dict[str, Any] | None:
        except (TypeError, ValueError):
            module = tool_class.__module__

-        return {
-            "name": tool_class.__name__,
-            "module": module,
-            "humanized_name": _extract_field_default(
-                fields.get("name"), fallback=tool_class.__name__
+        return ToolMetadata(
+            name=tool_class.__name__,
+            module=module,
+            humanized_name=str(
+                _extract_field_default(fields.get("name"), fallback=tool_class.__name__)
            ),
-            "description": str(
-                _extract_field_default(fields.get("description"))
-            ).strip(),
-            "run_params_schema": _extract_run_params_schema(fields.get("args_schema")),
-            "init_params_schema": _extract_init_params_schema(tool_class),
-            "env_vars": _extract_env_vars(fields.get("env_vars")),
-        }
+            description=str(_extract_field_default(fields.get("description"))).strip(),
+            run_params_schema=_extract_run_params_schema(fields.get("args_schema")),
+            init_params_schema=_extract_init_params_schema(tool_class),
+            env_vars=_extract_env_vars(fields.get("env_vars")),
+        )

    except Exception:
        return None
@@ -597,7 +596,7 @@ def _extract_init_params_schema(tool_class: type) -> dict[str, Any]:
        return {}


-def _extract_env_vars(env_vars_field: dict[str, Any] | None) -> list[dict[str, Any]]:
+def _extract_env_vars(env_vars_field: dict[str, Any] | None) -> list[EnvVarEntry]:
    """
    Extract environment variable definitions from env_vars field.
    """
--- a/lib/crewai/tests/test_llm.py
+++ b/lib/crewai/tests/test_llm.py
@@ -624,12 +624,15 @@ def test_handle_streaming_tool_calls_no_available_functions(
        ],
        tools=[get_weather_tool_schema],
    )
-    assert response == ""
+    assert isinstance(response, list)
+    assert len(response) == 1
+    assert response[0].function.name == "get_weather"
+    assert response[0].function.arguments == '{"location":"New York, NY"}'

    assert_event_count(
        mock_emit=mock_emit,
        expected_stream_chunk=9,
-        expected_completed_llm_call=1,
+        expected_completed_llm_call=0,
        expected_final_chunk_result='{"location":"New York, NY"}',
    )

--- a/lib/devtools/src/crewai_devtools/init.py
+++ b/lib/devtools/src/crewai_devtools/init.py
@@ -1,3 +1,3 @@
 """CrewAI development tools."""

-__version__ = "1.14.5a5"
+__version__ = "1.14.5"
--- a/lib/devtools/src/crewai_devtools/cli.py
+++ b/lib/devtools/src/crewai_devtools/cli.py
@@ -3,6 +3,7 @@
 from collections.abc import Mapping
 import os
 from pathlib import Path
+import re
 import subprocess
 import sys
 import tempfile
@@ -355,8 +356,19 @@ def update_pyproject_dependencies(

    workspace_packages = _DEFAULT_WORKSPACE_PACKAGES + (extra_packages or [])

+    current_extra: str | None = None
+    extra_header = re.compile(r"^\s*([A-Za-z0-9_-]+)\s*=\s*\[")
+
    for i, line in enumerate(lines):
+        match = extra_header.match(line)
+        if match:
+            current_extra = match.group(1)
+        elif line.strip().startswith("]"):
+            current_extra = None
+
        for pkg in workspace_packages:
+            if pkg == "crewai-files" and current_extra == "file-processing":
+                continue
            if f"{pkg}==" in line:
                stripped = line.lstrip()
                indent = line[: len(line) - len(stripped)]
@@ -732,18 +744,23 @@ def _is_prerelease(version: str) -> bool:
    return any(indicator in v for indicator in _PRERELEASE_INDICATORS)


-def get_commits_from_last_tag(tag_name: str, version: str) -> tuple[str, str]:
+def get_commits_from_last_tag(
+    tag_name: str, version: str, cwd: Path | None = None
+) -> tuple[str, str]:
    """Get commits from the last tag, excluding current version.

    Args:
        tag_name: Current tag name (e.g., "v1.0.0").
        version: Current version (e.g., "1.0.0").
+        cwd: Directory to run git commands in (defaults to current).

    Returns:
        Tuple of (commit_range, commits) where commits is newline-separated.
    """
    try:
-        all_tags = run_command(["git", "tag", "--sort=-version:refname"]).split("\n")
+        all_tags = run_command(
+            ["git", "tag", "--sort=-version:refname"], cwd=cwd
+        ).split("\n")
        prev_tags = [t for t in all_tags if t and t != tag_name and t != f"v{version}"]

        if not _is_prerelease(version):
@@ -752,22 +769,30 @@ def get_commits_from_last_tag(tag_name: str, version: str) -> tuple[str, str]:
        if prev_tags:
            last_tag = prev_tags[0]
            commit_range = f"{last_tag}..HEAD"
-            commits = run_command(["git", "log", commit_range, "--pretty=format:%s"])
+            commits = run_command(
+                ["git", "log", commit_range, "--pretty=format:%s"], cwd=cwd
+            )
        else:
            commit_range = "HEAD"
-            commits = run_command(["git", "log", "--pretty=format:%s"])
+            commits = run_command(["git", "log", "--pretty=format:%s"], cwd=cwd)
    except subprocess.CalledProcessError:
        commit_range = "HEAD"
-        commits = run_command(["git", "log", "--pretty=format:%s"])
+        commits = run_command(["git", "log", "--pretty=format:%s"], cwd=cwd)

    return commit_range, commits


-def get_github_contributors(commit_range: str) -> list[str]:
+def get_github_contributors(
+    commit_range: str,
+    repo: str = "crewAIInc/crewAI",
+    cwd: Path | None = None,
+) -> list[str]:
    """Get GitHub usernames from commit range using GitHub API.

    Args:
        commit_range: Git commit range (e.g., "abc123..HEAD").
+        repo: GitHub repo in ``owner/name`` form to resolve commits against.
+        cwd: Directory to run git commands in (defaults to current).

    Returns:
        List of GitHub usernames sorted alphabetically.
@@ -779,10 +804,10 @@ def get_github_contributors(commit_range: str) -> list[str]:
            gh_token = None

        g = Github(login_or_token=gh_token) if gh_token else Github()
-        github_repo = g.get_repo("crewAIInc/crewAI")
+        github_repo = g.get_repo(repo)

        commit_shas = run_command(
-            ["git", "log", commit_range, "--pretty=format:%H"]
+            ["git", "log", commit_range, "--pretty=format:%H"], cwd=cwd
        ).split("\n")

        contributors = set()
@@ -922,9 +947,26 @@ def _generate_release_notes(
    version: str,
    tag_name: str,
    no_edit: bool,
+    cwd: Path | None = None,
+    gh_repo: str = "crewAIInc/crewAI",
+    openai_client: OpenAI | None = None,
+    bump_already_done: bool = True,
 ) -> tuple[str, OpenAI, bool]:
    """Generate, display, and optionally edit release notes.

+    Args:
+        version: Version being released.
+        tag_name: Tag name for the release.
+        no_edit: Skip the interactive edit prompt.
+        cwd: Directory to run git commands in (defaults to current).
+        gh_repo: GitHub repo (``owner/name``) for resolving contributors.
+        openai_client: Reuse an existing OpenAI client if provided.
+        bump_already_done: True when the ``feat: bump versions to <version>``
+            commit for the current release is already in history (the real
+            release path). False in previews where no bump exists yet — the
+            most recent bump commit is the *previous* version and must be
+            used as the range start.
+
    Returns:
        Tuple of (release_notes, openai_client, is_prerelease).
    """
@@ -939,7 +981,8 @@ def _generate_release_notes(
                    "log",
                    "--grep=^feat: bump versions to",
                    "--format=%H %s",
-                ]
+                ],
+                cwd=cwd,
            )
            bump_entries = [
                line for line in prev_bump_output.strip().split("\n") if line.strip()
@@ -947,7 +990,8 @@ def _generate_release_notes(

            is_stable = not _is_prerelease(version)
            prev_commit = None
-            for entry in bump_entries[1:]:
+            scan_entries = bump_entries[1:] if bump_already_done else bump_entries
+            for entry in scan_entries:
                bump_ver = entry.split("feat: bump versions to", 1)[-1].strip()
                if is_stable and _is_prerelease(bump_ver):
                    continue
@@ -957,7 +1001,7 @@ def _generate_release_notes(
            if prev_commit:
                commit_range = f"{prev_commit}..HEAD"
                commits = run_command(
-                    ["git", "log", commit_range, "--pretty=format:%s"]
+                    ["git", "log", commit_range, "--pretty=format:%s"], cwd=cwd
                )

                commit_lines = [
@@ -967,14 +1011,21 @@ def _generate_release_notes(
                ]
                commits = "\n".join(commit_lines)
            else:
-                commit_range, commits = get_commits_from_last_tag(tag_name, version)
+                commit_range, commits = get_commits_from_last_tag(
+                    tag_name, version, cwd=cwd
+                )

        except subprocess.CalledProcessError:
-            commit_range, commits = get_commits_from_last_tag(tag_name, version)
+            commit_range, commits = get_commits_from_last_tag(
+                tag_name, version, cwd=cwd
+            )

-        github_contributors = get_github_contributors(commit_range)
+        github_contributors = get_github_contributors(
+            commit_range, repo=gh_repo, cwd=cwd
+        )

-        openai_client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
+        if openai_client is None:
+            openai_client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))

        if commits.strip():
            contributors_section = ""
@@ -1532,7 +1583,13 @@ def _wait_for_pr_merged(branch: str, cwd: Path) -> None:
        time.sleep(_PR_MERGE_POLL_INTERVAL)


-def _release_enterprise(version: str, is_prerelease: bool, dry_run: bool) -> None:
+def _release_enterprise(
+    version: str,
+    is_prerelease: bool,
+    dry_run: bool,
+    no_edit: bool = False,
+    openai_client: OpenAI | None = None,
+) -> None:
    """Clone the enterprise repo, bump versions, and create a release PR.

    Expects ENTERPRISE_REPO, ENTERPRISE_VERSION_DIRS, and
@@ -1542,6 +1599,8 @@ def _release_enterprise(version: str, is_prerelease: bool, dry_run: bool) -> Non
        version: New version string.
        is_prerelease: Whether this is a pre-release version.
        dry_run: Show what would be done without making changes.
+        no_edit: Skip the interactive release-notes edit prompt.
+        openai_client: Reuse OpenAI client from earlier phases if available.
    """
    if (
        not _ENTERPRISE_REPO
@@ -1559,7 +1618,6 @@ def _release_enterprise(version: str, is_prerelease: bool, dry_run: bool) -> Non
    )

    if dry_run:
-        console.print(f"[dim][DRY RUN][/dim] Would clone {enterprise_repo}")
        for d in _ENTERPRISE_VERSION_DIRS:
            console.print(f"[dim][DRY RUN][/dim] Would update versions in {d}")
        console.print(
@@ -1570,6 +1628,26 @@ def _release_enterprise(version: str, is_prerelease: bool, dry_run: bool) -> Non
            "[dim][DRY RUN][/dim] Would create bump PR, wait for merge, "
            "then tag and release"
        )
+
+        with tempfile.TemporaryDirectory() as tmp:
+            repo_dir = Path(tmp) / enterprise_repo.split("/")[-1]
+            console.print(f"\nCloning {enterprise_repo} (read-only preview)...")
+            run_command(["gh", "repo", "clone", enterprise_repo, str(repo_dir)])
+            console.print(f"[green]✓[/green] Cloned {enterprise_repo}")
+
+            _generate_release_notes(
+                version,
+                version,
+                no_edit,
+                cwd=repo_dir,
+                gh_repo=enterprise_repo,
+                openai_client=openai_client,
+                bump_already_done=False,
+            )
+            console.print(
+                "[dim][DRY RUN][/dim] Would tag and create GitHub release "
+                "with the notes above"
+            )
        return

    with tempfile.TemporaryDirectory() as tmp:
@@ -1682,8 +1760,18 @@ def _release_enterprise(version: str, is_prerelease: bool, dry_run: bool) -> Non
        run_command(["git", "pull"], cwd=repo_dir)

        tag_name = version
+
+        release_notes, _, _ = _generate_release_notes(
+            version,
+            tag_name,
+            no_edit,
+            cwd=repo_dir,
+            gh_repo=enterprise_repo,
+            openai_client=openai_client,
+        )
+
        run_command(
-            ["git", "tag", "-a", tag_name, "-m", f"Release {version}"],
+            ["git", "tag", "-a", tag_name, "-m", release_notes],
            cwd=repo_dir,
        )
        run_command(["git", "push", "origin", tag_name], cwd=repo_dir)
@@ -1699,7 +1787,7 @@ def _release_enterprise(version: str, is_prerelease: bool, dry_run: bool) -> Non
            "--title",
            tag_name,
            "--notes",
-            f"Release {version}",
+            release_notes,
        ]
        if is_prerelease:
            gh_cmd.append("--prerelease")
@@ -1998,7 +2086,7 @@ def tag(dry_run: bool, no_edit: bool) -> None:
            console.print("[green]✓[/green] main branch up to date")

        release_notes, openai_client, is_prerelease = _generate_release_notes(
-            version, tag_name, no_edit
+            version, tag_name, no_edit, bump_already_done=True
        )

        docs_branch = _update_docs_and_create_pr(
@@ -2109,7 +2197,7 @@ def release(

    if skip_to_enterprise:
        try:
-            _release_enterprise(version, is_prerelease, dry_run)
+            _release_enterprise(version, is_prerelease, dry_run, no_edit=no_edit)
        except BaseException as e:
            _print_release_error(e)
            _resume_hint(
@@ -2205,7 +2293,7 @@ def release(
            console.print("[green]✓[/green] main branch up to date")

        release_notes, openai_client, is_prerelease = _generate_release_notes(
-            version, tag_name, no_edit
+            version, tag_name, no_edit, bump_already_done=not dry_run
        )

        docs_branch = _update_docs_and_create_pr(
@@ -2259,7 +2347,13 @@ def release(

    if not skip_enterprise:
        try:
-            _release_enterprise(version, is_prerelease, dry_run)
+            _release_enterprise(
+                version,
+                is_prerelease,
+                dry_run,
+                no_edit=no_edit,
+                openai_client=openai_client,
+            )
        except BaseException as e:
            _print_release_error(e)
            _resume_hint(
--- a/lib/devtools/tests/test_toml_updates.py
+++ b/lib/devtools/tests/test_toml_updates.py
@@ -282,6 +282,25 @@ class TestUpdatePyprojectDependencies:
        assert '"crewai-files==2.0.0"' in result
        assert '"requests>=2.0"' in result

+    def test_skips_crewai_files_in_file_processing_extra(self, tmp_path: Path) -> None:
+        pyproject = tmp_path / "pyproject.toml"
+        pyproject.write_text(
+            dedent("""\
+            [project.optional-dependencies]
+            file-processing = [
+                "crewai-files==1.0.0",
+            ]
+            other = [
+                "crewai-files==1.0.0",
+            ]
+        """)
+        )
+
+        update_pyproject_dependencies(pyproject, "2.0.0")
+        result = pyproject.read_text()
+        assert '"crewai-files==1.0.0"' in result
+        assert '"crewai-files==2.0.0"' in result
+
    def test_leaves_bare_crewai_pin_alone(self, tmp_path: Path) -> None:
        """`crewai==` must not collide with `crewai-core==` etc."""
        pyproject = tmp_path / "pyproject.toml"
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -185,8 +185,10 @@ exclude-newer = "3 days"
 # python-multipart <0.0.27 has GHSA-pp6c-gr5w-3c5g (DoS via unbounded multipart headers).
 # gitpython <3.1.50 has GHSA-mv93-w799-cj2w (config_writer newline injection bypassing the 3.1.49 patch -> RCE via core.hooksPath).
 # urllib3 <2.7.0 has GHSA-qccp-gfcp-xxvc (ProxyManager cross-origin redirect leaks Authorization/Cookie) and GHSA-mf9v-mfxr-j63j (streaming decompression-bomb bypass); force 2.7.0+.
-# langsmith <0.7.31 has GHSA-rr7j-v2q5-chgv (streaming token redaction bypass); force 0.7.31+.
+# langsmith <0.8.0 has GHSA-3644-q5cj-c5c7 (public prompt manifest deserialization, SSRF/secret disclosure); force 0.8.0+.
 # authlib <1.6.11 has GHSA-jj8c-mmj3-mmgv (CSRF bypass in cache-based state storage).
+# pip <26.1.1 has GHSA-58qw-9mgm-455v (archive handling); OSV considers 26.1.1 unaffected.
+# paramiko <5.0.0 has GHSA-r374-rxx8-8654 (SHA-1 in rsakey.py); OSV considers 5.0.0 unaffected. Transitive via composio-core.
 # litellm 1.83.8+ hard-pins openai==2.24.0, missing openai.types.responses used by crewai;
 # override to >=2.30.0 (the version litellm 1.83.7 used) until upstream relaxes the pin.
 override-dependencies = [
@@ -203,8 +205,10 @@ override-dependencies = [
    "uv>=0.11.6,<1",
    "python-multipart>=0.0.27,<1",
    "gitpython>=3.1.50,<4",
-    "langsmith>=0.7.31,<0.8",
+    "langsmith>=0.8.0,<1",
    "authlib>=1.6.11",
+    "pip>=26.1.1",
+    "paramiko>=5.0.0",
 ]

 [tool.uv.workspace]
--- a/uv.lock
+++ b/uv.lock
@@ -13,7 +13,7 @@ resolution-markers = [
 ]

 [options]
-exclude-newer = "2026-05-08T16:33:02.834109Z"
+exclude-newer = "2026-05-17T14:20:01.778505Z"
 exclude-newer-span = "P3D"

 [manifest]
@@ -31,10 +31,12 @@ overrides = [
    { name = "gitpython", specifier = ">=3.1.50,<4" },
    { name = "langchain-core", specifier = ">=1.3.3,<2" },
    { name = "langchain-text-splitters", specifier = ">=1.1.2,<2" },
-    { name = "langsmith", specifier = ">=0.7.31,<0.8" },
+    { name = "langsmith", specifier = ">=0.8.0,<1" },
    { name = "onnxruntime", marker = "python_full_version < '3.11'", specifier = "<1.24" },
    { name = "openai", specifier = ">=2.30.0,<3" },
+    { name = "paramiko", specifier = ">=5.0.0" },
    { name = "pillow", specifier = ">=12.1.1" },
+    { name = "pip", specifier = ">=26.1.1" },
    { name = "pypdf", specifier = ">=6.10.2,<7" },
    { name = "python-multipart", specifier = ">=0.0.27,<1" },
    { name = "rich", specifier = ">=13.7.1" },
@@ -3268,11 +3270,11 @@ wheels = [

 [[package]]
 name = "idna"
-version = "3.11"
+version = "3.15"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/6f/6d/0703ccc57f3a7233505399edb88de3cbd678da106337b9fcde432b65ed60/idna-3.11.tar.gz", hash = "sha256:795dafcc9c04ed0c1fb032c2aa73654d8e8c5023a7df64a53f39190ada629902", size = 194582, upload-time = "2025-10-12T14:55:20.501Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/82/77/7b3966d0b9d1d31a36ddf1746926a11dface89a83409bf1483f0237aa758/idna-3.15.tar.gz", hash = "sha256:ca962446ea538f7092a95e057da437618e886f4d349216d2b1e294abfdb65fdc", size = 199245, upload-time = "2026-05-12T22:45:57.011Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl", hash = "sha256:771a87f49d9defaf64091e6e6fe9c18d4833f140bd19464795bc32d966ca37ea", size = 71008, upload-time = "2025-10-12T14:55:18.883Z" },
+    { url = "https://files.pythonhosted.org/packages/d2/23/408243171aa9aaba178d3e2559159c24c1171a641aa83b67bdd3394ead8e/idna-3.15-py3-none-any.whl", hash = "sha256:048adeaf8c2d788c40fee287673ccaa74c24ffd8dcf09ffa555a2fbb59f10ac8", size = 72340, upload-time = "2026-05-12T22:45:55.733Z" },
 ]

 [[package]]
@@ -3888,7 +3890,7 @@ sdist = { url = "https://files.pythonhosted.org/packages/0e/72/a3add0e4eec4eb9e2

 [[package]]
 name = "langsmith"
-version = "0.7.32"
+version = "0.8.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "httpx" },
@@ -3901,9 +3903,9 @@ dependencies = [
    { name = "xxhash" },
    { name = "zstandard" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/2f/b4/a0b4a501bee6b8a741ce29f8c48155b132118483cddc6f9247735ddb38fa/langsmith-0.7.32.tar.gz", hash = "sha256:b59b8e106d0e4c4842e158229296086e2aa7c561e3f602acda73d3ad0062e915", size = 1184518, upload-time = "2026-04-15T23:42:41.885Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/de/8a/1e8ea5e8bab2a65fa95bd36229ef38e8723ec46e430e20ca2d953487a7f1/langsmith-0.8.3.tar.gz", hash = "sha256:767ff7a8d136ed42926bf99059ac631dc6883542d6e3104b32e71c7625e1fa05", size = 4460330, upload-time = "2026-05-07T19:56:56.18Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/62/bc/148f98ac7dad73ac5e1b1c985290079cfeeb9ba13d760a24f25002beb2c9/langsmith-0.7.32-py3-none-any.whl", hash = "sha256:e1fde928990c4c52f47dc5132708cec674355d9101723d564183e965f383bf5f", size = 378272, upload-time = "2026-04-15T23:42:39.905Z" },
+    { url = "https://files.pythonhosted.org/packages/98/a9/51e644c1f1dbc3dd7d22dfd6412eab206d538c81e024e4f287373544bdcb/langsmith-0.8.3-py3-none-any.whl", hash = "sha256:b2e40e308222fa0beb2dccee3b4b30bfee9062d7a4f20a3e3e93df3c51a08ab4", size = 399048, upload-time = "2026-05-07T19:56:53.994Z" },
 ]

 [[package]]
@@ -5788,7 +5790,7 @@ wheels = [

 [[package]]
 name = "paramiko"
-version = "4.0.0"
+version = "5.0.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "bcrypt" },
@@ -5796,9 +5798,9 @@ dependencies = [
    { name = "invoke" },
    { name = "pynacl" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/1f/e7/81fdcbc7f190cdb058cffc9431587eb289833bdd633e2002455ca9bb13d4/paramiko-4.0.0.tar.gz", hash = "sha256:6a25f07b380cc9c9a88d2b920ad37167ac4667f8d9886ccebd8f90f654b5d69f", size = 1630743, upload-time = "2025-08-04T01:02:03.711Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/62/93/dcc25d52f49022ae6175d15e6bd751f1acc99b98bc61fc55e5155a7be2e7/paramiko-5.0.0.tar.gz", hash = "sha256:36763b5b95c2a0dcfdf1abc48e48156ee425b21efe2f0e787c2dd5a95c0e5e79", size = 1548586, upload-time = "2026-05-09T18:28:52.256Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/a9/90/a744336f5af32c433bd09af7854599682a383b37cfd78f7de263de6ad6cb/paramiko-4.0.0-py3-none-any.whl", hash = "sha256:0e20e00ac666503bf0b4eda3b6d833465a2b7aff2e2b3d79a8bba5ef144ee3b9", size = 223932, upload-time = "2025-08-04T01:02:02.029Z" },
+    { url = "https://files.pythonhosted.org/packages/82/5b/eadf6d45de38d30ab603f49393b6cd2cbe7e233af8cf90197e32782b68a9/paramiko-5.0.0-py3-none-any.whl", hash = "sha256:b7044611c30140d9a75261653210e2002977b71a0497ff3ba0d98d7edbf62f7c", size = 208919, upload-time = "2026-05-09T18:28:50.295Z" },
 ]

 [[package]]
@@ -6060,11 +6062,11 @@ wheels = [

 [[package]]
 name = "pip"
-version = "26.1"
+version = "26.1.1"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/73/7e/d2b04004e1068ad4fdfa2f227b839b5d03e602e47cdbbf49de71137c9546/pip-26.1.tar.gz", hash = "sha256:81e13ebcca3ffa8cc85e4deff5c27e1ee26dea0aa7fc2f294a073ac208806ff3", size = 1840316, upload-time = "2026-04-26T21:00:05.406Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/b6/48/cb9b7a682f6fe01a4221e1728941dd4ac3cd9090a17db3779d6ff490b602/pip-26.1.1.tar.gz", hash = "sha256:d36762751d156a4ee895de8af39aa0abeeeb577f93a2eca6ab62467bbf0f8a78", size = 1840400, upload-time = "2026-05-04T19:02:21.248Z" }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/3a/eb/fea4d1d51c49832120f7f285d07306db3960f423a2612c6057caf3e8196f/pip-26.1.1-py3-none-any.whl", hash = "sha256:99cb1c2899893b075ff56e4ed0af55669a955b49ad7fb8d8603ecdaf4ed653fb", size = 1812777, upload-time = "2026-05-04T19:02:18.9Z" },
 ]

 [[package]]
Author	SHA1	Message	Date
Greyson LaLonde	0f3a57b3b9	fix: round-trip safety for input_provider, memory scopes, embedder class - input_provider: enforce InputProvider protocol via dedicated validator/serializer; reject non-class dotted paths in _dotted_path_to_instance - MemoryScope/MemorySlice: allow restore without live Memory; expose bind() to reattach the dependency post-restore - Knowledge.embedder: add BeforeValidator that resolves provider_class dotted paths back to a BaseEmbeddingsProvider subclass	2026-05-21 00:30:14 +08:00
Greyson LaLonde	b07c1439a3	fix: backfill legacy discriminators and add source validation context	2026-05-21 00:22:53 +08:00
Greyson LaLonde	97e959cb0c	fix: raise on unrecognized embedder shape in serializer	2026-05-21 00:17:52 +08:00
Greyson LaLonde	752d9b45d6	fix: harden RuntimeState serialization across entity fields Adds missing serializers, discriminators, and exclude markers on entity fields that previously crashed model_dump_json or restored ambiguously: - Flow.persistence: add _serialize_persistence; drop \| Any escape hatch - Flow.input_provider: SerializableInstance dotted-path round-trip - BaseAgent.agent_executor: add _serialize_executor_ref - BaseAgent.tools_handler / cache_handler: exclude=True - Memory / MemoryScope / MemorySlice: memory_kind Literal discriminator - Knowledge.storage / .embedder: exclude live client, serialize spec - BaseKnowledgeSource subclasses: source_type Literal + dict-resolver - BaseKnowledgeSource.storage / chunk_embeddings: exclude=True	2026-05-21 00:12:20 +08:00
Greyson LaLonde	7cc1a7bb41	fix(deps): bump pip and paramiko to drop pip-audit ignores Some checks are pending Build uv cache / build-cache (3.10) (push) Waiting to run Details Build uv cache / build-cache (3.11) (push) Waiting to run Details Build uv cache / build-cache (3.12) (push) Waiting to run Details Build uv cache / build-cache (3.13) (push) Waiting to run Details CodeQL Advanced / Analyze (actions) (push) Waiting to run Details CodeQL Advanced / Analyze (python) (push) Waiting to run Details Vulnerability Scan / pip-audit (push) Waiting to run Details OSV no longer flags pip 26.1.1 (GHSA-58qw-9mgm-455v) or paramiko 5.0.0 (GHSA-r374-rxx8-8654), so override both to those minimums and remove the corresponding --ignore-vuln entries. paramiko is pulled in transitively via composio-core.	2026-05-20 22:33:43 +08:00
Greyson LaLonde	09ffe87fbb	ci: ignore pip-audit findings without published fixes Adds joblib, markdown, nltk, onnx, pyjwt, torch and transformers advisories that have no fixed version available (or are disputed) to the pip-audit ignore list. Rationale recorded next to each ID.	2026-05-20 21:40:30 +08:00
Greyson LaLonde	14af56b74d	ci: pin third-party actions to commit SHAs Replaces version tags (e.g. astral-sh/setup-uv@v6, slackapi/slack-github-action@v2.1.0) with full commit SHAs across every workflow. Mitigates supply-chain risk from mutable tags.	2026-05-20 19:01:53 +08:00
Greyson LaLonde	35f693cf68	chore: tighten typing across plus_api client Some checks failed CodeQL Advanced / Analyze (actions) (push) Has been cancelled Details CodeQL Advanced / Analyze (python) (push) Has been cancelled Details Vulnerability Scan / pip-audit (push) Has been cancelled Details Adds typed containers for wire payloads, literal aliases for HTTP method and log type, and Ffnal markers on resource constants. Updates upstream returns in project_utils.py and deploy/main.py to match the new contracts.	2026-05-20 01:43:48 +08:00
Greyson LaLonde	da15554d81	feat: generate categorized release notes for enterprise	2026-05-20 00:24:26 +08:00
Greyson LaLonde	284533464f	fix: bump idna to 3.15 to address GHSA-65pc-fj4g-8rjx Some checks failed CodeQL Advanced / Analyze (actions) (push) Has been cancelled Details CodeQL Advanced / Analyze (python) (push) Has been cancelled Details Vulnerability Scan / pip-audit (push) Has been cancelled Details Build uv cache / build-cache (3.10) (push) Has been cancelled Details Build uv cache / build-cache (3.11) (push) Has been cancelled Details Build uv cache / build-cache (3.12) (push) Has been cancelled Details Build uv cache / build-cache (3.13) (push) Has been cancelled Details Check Documentation Broken Links / Check broken links (push) Has been cancelled Details	2026-05-19 23:38:34 +08:00
Tiago Freire	024e230b2c	docs: remove {" "} JSX expressions breaking <Steps> render (#5857 ) ## Overview Prettier-inserted bare `{" "}` lines between sibling `<Step>` elements caused Mintlify's `<Steps>` to crash with "Cannot read properties of undefined (reading 'stepNumber')", leaving the page body blank. ### Affected pages (en/ar/ko/pt-BR): - enterprise/guides/enable-crew-studio - learn/llm-selection-guide	2026-05-19 10:44:53 -04:00
Greyson LaLonde	a4c90b6912	docs: update changelog and version for v1.14.5 Some checks failed CodeQL Advanced / Analyze (actions) (push) Has been cancelled Details CodeQL Advanced / Analyze (python) (push) Has been cancelled Details Check Documentation Broken Links / Check broken links (push) Has been cancelled Details Vulnerability Scan / pip-audit (push) Has been cancelled Details Nightly Canary Release / Check for new commits (push) Has been cancelled Details Nightly Canary Release / Build nightly packages (push) Has been cancelled Details Nightly Canary Release / Publish nightly to PyPI (push) Has been cancelled Details Mark stale issues and pull requests / stale (push) Has been cancelled Details	2026-05-19 03:19:40 +08:00
Greyson LaLonde	c50da7a6f2	feat: bump versions to 1.14.5	2026-05-19 03:11:26 +08:00
Irfaan Mansoori	e8aa870f90	fix: memory leak in git.py by using cached_property Some checks failed CodeQL Advanced / Analyze (actions) (push) Has been cancelled Details CodeQL Advanced / Analyze (python) (push) Has been cancelled Details Check Documentation Broken Links / Check broken links (push) Has been cancelled Details Vulnerability Scan / pip-audit (push) Has been cancelled Details Co-authored-by: Greyson LaLonde <greyson.r.lalonde@gmail.com>	2026-05-18 21:55:57 +08:00
Greyson LaLonde	14cd81eec6	docs: update changelog and version for v1.14.5a7	2026-05-18 21:13:34 +08:00
Greyson LaLonde	a6225da326	feat: bump versions to 1.14.5a7	2026-05-18 21:08:46 +08:00
Greyson LaLonde	259d334e38	chore(devtools): skip pinning crewai-files in file-processing extra	2026-05-18 21:00:37 +08:00
Greyson LaLonde	42aa8a777c	chore: deprecate function_calling_llm field	2026-05-18 20:49:11 +08:00
Heitor Carvalho	a95d26763f	docs: update changelog and version for v1.14.5a6 (#5828 ) Some checks failed CodeQL Advanced / Analyze (actions) (push) Has been cancelled Details CodeQL Advanced / Analyze (python) (push) Has been cancelled Details Check Documentation Broken Links / Check broken links (push) Has been cancelled Details Vulnerability Scan / pip-audit (push) Has been cancelled Details Build uv cache / build-cache (3.10) (push) Has been cancelled Details Build uv cache / build-cache (3.11) (push) Has been cancelled Details Build uv cache / build-cache (3.12) (push) Has been cancelled Details Build uv cache / build-cache (3.13) (push) Has been cancelled Details Nightly Canary Release / Check for new commits (push) Has been cancelled Details Nightly Canary Release / Build nightly packages (push) Has been cancelled Details Nightly Canary Release / Publish nightly to PyPI (push) Has been cancelled Details Mark stale issues and pull requests / stale (push) Has been cancelled Details	2026-05-15 17:05:04 -03:00
Heitor Carvalho	65ec783aae	feat: bump versions to 1.14.5a6 (#5827 )	2026-05-15 16:51:59 -03:00
Greyson LaLonde	eefe0e42ac	fix: surface streamed tool calls when available_functions is absent	2026-05-16 02:46:35 +08:00
Greyson LaLonde	75bb882911	fix(deps): bump langsmith to >=0.8.0 for GHSA-3644-q5cj-c5c7 Some checks failed CodeQL Advanced / Analyze (actions) (push) Has been cancelled Details CodeQL Advanced / Analyze (python) (push) Has been cancelled Details Vulnerability Scan / pip-audit (push) Has been cancelled Details Build uv cache / build-cache (3.10) (push) Has been cancelled Details Build uv cache / build-cache (3.11) (push) Has been cancelled Details Build uv cache / build-cache (3.12) (push) Has been cancelled Details Build uv cache / build-cache (3.13) (push) Has been cancelled Details	2026-05-15 21:32:52 +08:00
iris-clawd	c36827b45b	fix(docs/pt-BR): replace untranslated code block placeholders (#5781 ) Some checks failed CodeQL Advanced / Analyze (actions) (push) Has been cancelled Details CodeQL Advanced / Analyze (python) (push) Has been cancelled Details Check Documentation Broken Links / Check broken links (push) Has been cancelled Details Vulnerability Scan / pip-audit (push) Has been cancelled Details Nightly Canary Release / Check for new commits (push) Has been cancelled Details Nightly Canary Release / Build nightly packages (push) Has been cancelled Details Nightly Canary Release / Publish nightly to PyPI (push) Has been cancelled Details Mark stale issues and pull requests / stale (push) Has been cancelled Details * fix(docs/pt-BR): replace untranslated code block placeholders Replace all `# (O código não é traduzido)` and `# código não traduzido` placeholder comments in the PT-BR docs with the actual code from the English source files. Files fixed: - docs/pt-BR/concepts/flows.mdx (~15 placeholders → real code) - docs/pt-BR/guides/flows/mastering-flow-state.mdx (~17 placeholders → real code) Code itself is kept in English per i18n conventions. Inline # comments within code blocks have been translated to Portuguese. * fix(docs/pt-BR): address CodeRabbit review comments - flows.mdx: add missing load_dotenv() call after imports - mastering-flow-state.mdx: fix PersistentCounterFlow second-run example to pass inputs={"id": flow1.state.id} to kickoff(), matching the documented resume pattern; update comment accordingly	2026-05-13 12:23:18 -03:00