docs: polish Datadog/OTel guides — symmetric paths, auto-provisioned

Adds stub MDX pages for the new Datadog Integration guide in each locale,
with translated frontmatter and a "translation in progress" note. Body
content is English while waiting on full translations, matching the
discoverability of every other Enterprise guide.

Also reframes capture_telemetry_logs.mdx in each locale to match the en
restructure: a translated lead Tip recommending OpenTelemetry as the
vendor-neutral default, and a slimmed-down Datadog tab that points at
the dedicated Datadog Integration guide instead of duplicating its
collector configuration steps.

Registers the new datadog page in the pt-BR/ko/ar edge sidebars where
the old datadog_dashboard entry would have lived. structured_logs is
intentionally not re-stubbed — the schema lives inside the Datadog page
now.

Co-authored-by: Cursor <cursoragent@cursor.com>

docs/edge/ar/changelog.mdx

@@ -4,65 +4,6 @@ description: "تحديثات المنتج والتحسينات وإصلاحات
 icon: "clock"
 mode: "wide"
 ---
-<Update label="18 يونيو 2026">
-  ## v1.14.8a1
-
-  [عرض الإصدار على GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.8a1)
-
-  ## ما الذي تغير
-
-  ### الميزات
-  - إضافة تعبير if اختياري إلى خطوات each.do
-
-  ### إصلاحات الأخطاء
-  - إصلاح مشكلات JSON crew
-
-  ### الوثائق
-  - تحديث snapshot و changelog للإصدار v1.14.8a
-
-  ## المساهمون
-
-  @joaomdmoura, @vinibrsl
-
-</Update>
-
-<Update label="17 يونيو 2026">
-  ## v1.14.8a
-
-  [عرض الإصدار على GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.8a)
-
-  ## ما الذي تغير
-
-  ### الميزات
-  - إضافة إجراء كتلة نصية/كود إلى FlowDefinition
-  - إضافة إجراءات الطاقم إلى FlowDefinition
-  - إضافة إجراء مركب `each` إلى FlowDefinition
-  - تنفيذ دعم وضع DMN في إنشاء الطاقم وتنفيذه
-  - تحسين وظيفة إعادة تعيين الذاكرة ومعالجة الطاقم بتنسيق JSON
-  - إضافة تعبيرات إلى إجراءات FlowDefinition
-  - تنفيذ أدوات تشغيل تعريف التدفق بدون كود Python
-  - دفع التغذية الراجعة البشرية من تعريف التدفق
-  - توصيل التكوين والاستمرارية من FlowDefinition إلى وقت التشغيل
-  - إضافة `crewai run --definition` التجريبية للتدفقات
-  - دعم تراجع نشر ZIP وتشغيل مشاريع الطاقم بتنسيق JSON
-  - تقديم الطواقم بتنسيق JSON أولاً
-
-  ### إصلاحات الأخطاء
-  - إصلاح أداة Exa المكررة
-  - إصلاح استخدام الرموز المجمعة عبر جميع استدعاءات LLM
-  - حل المشكلات المتعلقة بتحميل الطاقم ومنطق التحقق
-
-  ### الوثائق
-  - توثيق حقول FlowDefinition في مخطط JSON
-  - تحديث وثائق التثبيت والبدء السريع لمشاريع الطاقم بتنسيق JSON أولاً
-  - تحديث سجل التغييرات والإصدار لـ v1.14.7
-
-  ## المساهمون
-
-  @gabemilani, @greysonlalonde, @iris-clawd, @joaomdmoura, @lorenzejay, @lucasgomide, @theCyberTech, @vinibrsl
-
-</Update>
-
 <Update label="11 يونيو 2026">
   ## v1.14.7
 

docs/edge/ar/enterprise/guides/datadog.mdx

@@ -25,7 +25,7 @@ CrewAI supports two log-ingestion paths to Datadog — both are first-class and
 
     **Setup:**
     1. Run the Datadog Agent next to your CrewAI containers — see [Datadog's deployment docs](https://docs.datadoghq.com/agent/) for Kubernetes, ECS, or VM setup. Enable log collection (`logs_enabled: true`) and container log collection (`logs_config.container_collect_all: true`).
-    2. Set `CREWAI_LOG_FORMAT=json` as an **automation environment variable** in CrewAI AMP (open your automation → **Settings → Environment Variables**) so each log event is a single line instead of a multi-line traceback. AMP propagates the value to every container in the deployment (API + workers) — don't set it on the container or host directly. See [Enabling JSON output](#enabling-json-output) below for the AMP UI walkthrough and the [log schema reference](#log-schema-reference) for the full field contract.
+    2. Set `CREWAI_LOG_FORMAT=json` on every CrewAI container (API + workers) so each log event is a single line instead of a multi-line traceback. See the [log schema reference](#log-schema-reference) below for the full field contract.
     3. Confirm logs arrive in Datadog Logs with the JSON fields parsed — see [Verify ingestion](#verify-ingestion).
 
     **Pick this path if** you already operate Datadog Agents (e.g. for infrastructure metrics), or your log volume makes per-event ingestion cost a real concern — collapsing tracebacks into single events keeps Agent ingestion cheap at scale.
@@ -81,7 +81,7 @@ When `CREWAI_LOG_FORMAT=json` is set, every log event is emitted as a **single J
 
 ### Enabling JSON output
 
-`CREWAI_LOG_FORMAT=json` must be set as an **automation environment variable** in CrewAI AMP — it is **not** a container, host, or Docker setting. Open your automation in AMP, click the **Settings** icon, and add the variable under the **Environment Variables** section. AMP applies the value to every container in the deployment (API + workers) on the next restart. See [Update Your Crew](./update-crew) for the full UI walkthrough with screenshots.
+Set the `CREWAI_LOG_FORMAT` environment variable to `json` on every container that runs your deployment (API + workers).
 
 ```shell
 CREWAI_LOG_FORMAT=json
@@ -237,7 +237,7 @@ Open [Logs Explorer](https://app.datadoghq.com/logs) and run a query that matche
   <Tab title="Datadog Agent">
     Search `service:crewai* @schema:v1`. You should see structured logs with the JSON fields parsed into Datadog facets. Pick a recent event and verify it has `@automation_id`, `@kickoff_id`, `@execution_id`, `@crewai_version`, and (when running inside a span) `@trace_id` / `@span_id` populated.
 
-    If nothing appears, confirm `CREWAI_LOG_FORMAT=json` is set under your automation's **Environment Variables** in AMP, the deployment was restarted after the change, and the Datadog Agent is tailing container stdout.
+    If nothing appears, confirm `CREWAI_LOG_FORMAT=json` is set on the running container, the deployment was restarted after the change, and the Datadog Agent is tailing container stdout.
   </Tab>
   <Tab title="Datadog OTLP intake">
     Search `source:otlp service:crewai*`. OTLP attributes land with their OpenTelemetry names (`automation_id`, `crewai.kickoff.id`, etc.) rather than the stdout JSON keys, but they map to the same dashboard facets after [facet promotion](#prerequisite-promote-facets).

docs/edge/en/changelog.mdx

@@ -4,65 +4,6 @@ description: "Product updates, improvements, and bug fixes for CrewAI"
 icon: "clock"
 mode: "wide"
 ---
-<Update label="Jun 18, 2026">
-  ## v1.14.8a1
-
-  [View release on GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.8a1)
-
-  ## What's Changed
-
-  ### Features
-  - Add optional if expression to each.do steps
-
-  ### Bug Fixes
-  - Fix JSON crew issues
-
-  ### Documentation
-  - Update snapshot and changelog for v1.14.8a
-
-  ## Contributors
-
-  @joaomdmoura, @vinibrsl
-
-</Update>
-
-<Update label="Jun 17, 2026">
-  ## v1.14.8a
-
-  [View release on GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.8a)
-
-  ## What's Changed
-
-  ### Features
-  - Add script/code block action to FlowDefinition
-  - Add crew actions to FlowDefinition
-  - Add `each` composite action to FlowDefinition
-  - Implement DMN mode support in crew creation and execution
-  - Enhance memory reset functionality and JSON crew handling
-  - Add expressions to FlowDefinition actions
-  - Implement Flow definition run tools without Python code
-  - Drive human feedback from the flow definition
-  - Wire config and persistence from FlowDefinition into the runtime
-  - Add experimental `crewai run --definition` for flows
-  - Support ZIP deployment fallback and JSON crew project env runs
-  - Introduce JSON first crews
-
-  ### Bug Fixes
-  - Fix duplicated Exa tool
-  - Fix aggregate token usage across all LLM calls
-  - Resolve issues with crew loading and validation logic
-
-  ### Documentation
-  - Document FlowDefinition fields in the JSON schema
-  - Update installation and quickstart documentation for JSON-first crew projects
-  - Update changelog and version for v1.14.7
-
-  ## Contributors
-
-  @gabemilani, @greysonlalonde, @iris-clawd, @joaomdmoura, @lorenzejay, @lucasgomide, @theCyberTech, @vinibrsl
-
-</Update>
-
 <Update label="Jun 11, 2026">
   ## v1.14.7
 

docs/edge/en/enterprise/guides/datadog.mdx

@@ -21,7 +21,7 @@ CrewAI supports two log-ingestion paths to Datadog — both are first-class and
 
     **Setup:**
     1. Run the Datadog Agent next to your CrewAI containers — see [Datadog's deployment docs](https://docs.datadoghq.com/agent/) for Kubernetes, ECS, or VM setup. Enable log collection (`logs_enabled: true`) and container log collection (`logs_config.container_collect_all: true`).
-    2. Set `CREWAI_LOG_FORMAT=json` as an **automation environment variable** in CrewAI AMP (open your automation → **Settings → Environment Variables**) so each log event is a single line instead of a multi-line traceback. AMP propagates the value to every container in the deployment (API + workers) — don't set it on the container or host directly. See [Enabling JSON output](#enabling-json-output) below for the AMP UI walkthrough and the [log schema reference](#log-schema-reference) for the full field contract.
+    2. Set `CREWAI_LOG_FORMAT=json` on every CrewAI container (API + workers) so each log event is a single line instead of a multi-line traceback. See the [log schema reference](#log-schema-reference) below for the full field contract.
     3. Confirm logs arrive in Datadog Logs with the JSON fields parsed — see [Verify ingestion](#verify-ingestion).
 
     **Pick this path if** you already operate Datadog Agents (e.g. for infrastructure metrics), or your log volume makes per-event ingestion cost a real concern — collapsing tracebacks into single events keeps Agent ingestion cheap at scale.
@@ -77,7 +77,7 @@ When `CREWAI_LOG_FORMAT=json` is set, every log event is emitted as a **single J
 
 ### Enabling JSON output
 
-`CREWAI_LOG_FORMAT=json` must be set as an **automation environment variable** in CrewAI AMP — it is **not** a container, host, or Docker setting. Open your automation in AMP, click the **Settings** icon, and add the variable under the **Environment Variables** section. AMP applies the value to every container in the deployment (API + workers) on the next restart. See [Update Your Crew](./update-crew) for the full UI walkthrough with screenshots.
+Set the `CREWAI_LOG_FORMAT` environment variable to `json` on every container that runs your deployment (API + workers).
 
 ```shell
 CREWAI_LOG_FORMAT=json
@@ -233,7 +233,7 @@ Open [Logs Explorer](https://app.datadoghq.com/logs) and run a query that matche
   <Tab title="Datadog Agent">
     Search `service:crewai* @schema:v1`. You should see structured logs with the JSON fields parsed into Datadog facets. Pick a recent event and verify it has `@automation_id`, `@kickoff_id`, `@execution_id`, `@crewai_version`, and (when running inside a span) `@trace_id` / `@span_id` populated.
 
-    If nothing appears, confirm `CREWAI_LOG_FORMAT=json` is set under your automation's **Environment Variables** in AMP, the deployment was restarted after the change, and the Datadog Agent is tailing container stdout.
+    If nothing appears, confirm `CREWAI_LOG_FORMAT=json` is set on the running container, the deployment was restarted after the change, and the Datadog Agent is tailing container stdout.
   </Tab>
   <Tab title="Datadog OTLP intake">
     Search `source:otlp service:crewai*`. OTLP attributes land with their OpenTelemetry names (`automation_id`, `crewai.kickoff.id`, etc.) rather than the stdout JSON keys, but they map to the same dashboard facets after [facet promotion](#prerequisite-promote-facets).

docs/edge/en/index.mdx

@@ -28,60 +28,6 @@ mode: "wide"
 
   <div style={{ display: 'flex', flexWrap: 'wrap', gap: 12, justifyContent: 'center' }}>
     <a className="button button-primary" href="/en/quickstart">Get started</a>
-    <button
-      type="button"
-      className="button"
-      onClick={async (event) => {
-        const prompt = `Set up this environment so I can build with CrewAI.
-
-First install the official CrewAI coding-agent skills if this environment supports npx:
-
-npx skills add crewaiinc/skills
-
-If npx is missing or the current agent cannot load skills, do not fail the whole setup. Report the exact issue and continue using the CrewAI docs directly.
-
-Use these CrewAI docs as source of truth before making assumptions:
-- https://skills.crewai.com
-- https://docs.crewai.com/llms.txt
-- https://docs.crewai.com/en/installation
-- https://docs.crewai.com/en/guides/coding-tools/build-with-ai
-
-Setup steps:
-1. Check python3 --version. CrewAI requires Python >=3.10 and <3.14.
-2. Install uv if missing:
-   curl -LsSf https://astral.sh/uv/install.sh | sh
-3. Source the uv environment if needed:
-   source "$HOME/.local/bin/env"
-4. Install the CrewAI CLI:
-   uv tool install crewai
-5. Verify the CLI:
-   crewai version
-   crewai create --help
-6. Create a project:
-   CREWAI_DMN=true crewai create
-7. After project creation, inspect the generated files before editing.
-8. Run:
-   crewai install
-   crewai run
-
-Do not hardcode API keys. Use .env.
-Do not invent CLI flags. Validate with crewai --help or crewai create --help.
-If a command fails, show the exact command and error, explain the likely cause, fix what you can safely fix, and retry once.`;
-        const button = event.currentTarget;
-        try {
-          await navigator.clipboard.writeText(prompt);
-          button.textContent = "Copied";
-        } catch {
-          button.textContent = "Copy failed";
-        } finally {
-          window.setTimeout(() => {
-            button.textContent = "Copy instructions for coding agents";
-          }, 1600);
-        }
-      }}
-    >
-      Copy instructions for coding agents
-    </button>
     <a className="button" href="/en/changelog">View changelog</a>
     <a className="button" href="/en/api-reference/introduction">API Reference</a>
   </div>

docs/edge/en/installation.mdx

@@ -9,60 +9,7 @@ mode: "wide"
 
 Install our coding agent skills (Claude Code, Codex, ...) to quickly get your coding agents up and running with CrewAI.
 
-<button
-  type="button"
-  className="button button-primary"
-  onClick={async (event) => {
-    const prompt = `Set up this environment so I can build with CrewAI.
-
-First install the official CrewAI coding-agent skills if this environment supports npx:
-
-npx skills add crewaiinc/skills
-
-If npx is missing or the current agent cannot load skills, do not fail the whole setup. Report the exact issue and continue using the CrewAI docs directly.
-
-Use these CrewAI docs as source of truth before making assumptions:
-- https://skills.crewai.com
-- https://docs.crewai.com/llms.txt
-- https://docs.crewai.com/en/installation
-- https://docs.crewai.com/en/guides/coding-tools/build-with-ai
-
-Setup steps:
-1. Check python3 --version. CrewAI requires Python >=3.10 and <3.14.
-2. Install uv if missing:
-   curl -LsSf https://astral.sh/uv/install.sh | sh
-3. Source the uv environment if needed:
-   source "$HOME/.local/bin/env"
-4. Install the CrewAI CLI:
-   uv tool install crewai
-5. Verify the CLI:
-   crewai version
-   crewai create --help
-6. Create a project:
-   CREWAI_DMN=true crewai create
-7. After project creation, inspect the generated files before editing.
-8. Run:
-   crewai install
-   crewai run
-
-Do not hardcode API keys. Use .env.
-Do not invent CLI flags. Validate with crewai --help or crewai create --help.
-If a command fails, show the exact command and error, explain the likely cause, fix what you can safely fix, and retry once.`;
-    const button = event.currentTarget;
-    try {
-      await navigator.clipboard.writeText(prompt);
-      button.textContent = "Copied";
-    } catch {
-      button.textContent = "Copy failed";
-    } finally {
-      window.setTimeout(() => {
-        button.textContent = "Copy instructions for coding agents";
-      }, 1600);
-    }
-  }}
->
-  Copy instructions for coding agents
-</button>
+You can install it with `npx skills add crewaiinc/skills`
 
 <iframe src="https://www.loom.com/embed/befb9f68b81f42ad8112bfdd95a780af" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style={{width: "100%", height: "400px"}}></iframe>
 

docs/edge/ko/changelog.mdx

@@ -4,65 +4,6 @@ description: "CrewAI의 제품 업데이트, 개선 사항 및 버그 수정"
 icon: "clock"
 mode: "wide"
 ---
-<Update label="2026년 6월 18일">
-  ## v1.14.8a1
-
-  [GitHub 릴리스 보기](https://github.com/crewAIInc/crewAI/releases/tag/1.14.8a1)
-
-  ## 변경 사항
-
-  ### 기능
-  - 각 do 단계에 선택적 if 표현식을 추가
-
-  ### 버그 수정
-  - JSON 크루 문제 수정
-
-  ### 문서
-  - v1.14.8a의 스냅샷 및 변경 로그 업데이트
-
-  ## 기여자
-
-  @joaomdmoura, @vinibrsl
-
-</Update>
-
-<Update label="2026년 6월 17일">
-  ## v1.14.8a
-
-  [GitHub 릴리스 보기](https://github.com/crewAIInc/crewAI/releases/tag/1.14.8a)
-
-  ## 변경 사항
-
-  ### 기능
-  - FlowDefinition에 스크립트/코드 블록 액션 추가
-  - FlowDefinition에 크루 액션 추가
-  - FlowDefinition에 `each` 복합 액션 추가
-  - 크루 생성 및 실행에서 DMN 모드 지원 구현
-  - 메모리 재설정 기능 및 JSON 크루 처리 기능 향상
-  - FlowDefinition 액션에 표현식 추가
-  - Python 코드 없이 Flow 정의 실행 도구 구현
-  - Flow 정의에서 인간 피드백 유도
-  - FlowDefinition의 구성 및 지속성을 런타임에 연결
-  - 흐름을 위한 실험적 `crewai run --definition` 추가
-  - ZIP 배포 대체 및 JSON 크루 프로젝트 환경 실행 지원
-  - JSON 우선 크루 도입
-
-  ### 버그 수정
-  - 중복된 Exa 도구 수정
-  - 모든 LLM 호출에서 집계 토큰 사용 수정
-  - 크루 로딩 및 검증 로직 관련 문제 해결
-
-  ### 문서
-  - JSON 스키마에서 FlowDefinition 필드 문서화
-  - JSON 우선 크루 프로젝트에 대한 설치 및 빠른 시작 문서 업데이트
-  - v1.14.7에 대한 변경 로그 및 버전 업데이트
-
-  ## 기여자
-
-  @gabemilani, @greysonlalonde, @iris-clawd, @joaomdmoura, @lorenzejay, @lucasgomide, @theCyberTech, @vinibrsl
-
-</Update>
-
 <Update label="2026년 6월 11일">
   ## v1.14.7
 

docs/edge/ko/enterprise/guides/datadog.mdx

@@ -25,7 +25,7 @@ CrewAI supports two log-ingestion paths to Datadog — both are first-class and
 
     **Setup:**
     1. Run the Datadog Agent next to your CrewAI containers — see [Datadog's deployment docs](https://docs.datadoghq.com/agent/) for Kubernetes, ECS, or VM setup. Enable log collection (`logs_enabled: true`) and container log collection (`logs_config.container_collect_all: true`).
-    2. Set `CREWAI_LOG_FORMAT=json` as an **automation environment variable** in CrewAI AMP (open your automation → **Settings → Environment Variables**) so each log event is a single line instead of a multi-line traceback. AMP propagates the value to every container in the deployment (API + workers) — don't set it on the container or host directly. See [Enabling JSON output](#enabling-json-output) below for the AMP UI walkthrough and the [log schema reference](#log-schema-reference) for the full field contract.
+    2. Set `CREWAI_LOG_FORMAT=json` on every CrewAI container (API + workers) so each log event is a single line instead of a multi-line traceback. See the [log schema reference](#log-schema-reference) below for the full field contract.
     3. Confirm logs arrive in Datadog Logs with the JSON fields parsed — see [Verify ingestion](#verify-ingestion).
 
     **Pick this path if** you already operate Datadog Agents (e.g. for infrastructure metrics), or your log volume makes per-event ingestion cost a real concern — collapsing tracebacks into single events keeps Agent ingestion cheap at scale.
@@ -81,7 +81,7 @@ When `CREWAI_LOG_FORMAT=json` is set, every log event is emitted as a **single J
 
 ### Enabling JSON output
 
-`CREWAI_LOG_FORMAT=json` must be set as an **automation environment variable** in CrewAI AMP — it is **not** a container, host, or Docker setting. Open your automation in AMP, click the **Settings** icon, and add the variable under the **Environment Variables** section. AMP applies the value to every container in the deployment (API + workers) on the next restart. See [Update Your Crew](./update-crew) for the full UI walkthrough with screenshots.
+Set the `CREWAI_LOG_FORMAT` environment variable to `json` on every container that runs your deployment (API + workers).
 
 ```shell
 CREWAI_LOG_FORMAT=json
@@ -237,7 +237,7 @@ Open [Logs Explorer](https://app.datadoghq.com/logs) and run a query that matche
   <Tab title="Datadog Agent">
     Search `service:crewai* @schema:v1`. You should see structured logs with the JSON fields parsed into Datadog facets. Pick a recent event and verify it has `@automation_id`, `@kickoff_id`, `@execution_id`, `@crewai_version`, and (when running inside a span) `@trace_id` / `@span_id` populated.
 
-    If nothing appears, confirm `CREWAI_LOG_FORMAT=json` is set under your automation's **Environment Variables** in AMP, the deployment was restarted after the change, and the Datadog Agent is tailing container stdout.
+    If nothing appears, confirm `CREWAI_LOG_FORMAT=json` is set on the running container, the deployment was restarted after the change, and the Datadog Agent is tailing container stdout.
   </Tab>
   <Tab title="Datadog OTLP intake">
     Search `source:otlp service:crewai*`. OTLP attributes land with their OpenTelemetry names (`automation_id`, `crewai.kickoff.id`, etc.) rather than the stdout JSON keys, but they map to the same dashboard facets after [facet promotion](#prerequisite-promote-facets).

docs/edge/pt-BR/changelog.mdx

@@ -4,65 +4,6 @@ description: "Atualizações de produto, melhorias e correções do CrewAI"
 icon: "clock"
 mode: "wide"
 ---
-<Update label="18 jun 2026">
-  ## v1.14.8a1
-
-  [Ver release no GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.8a1)
-
-  ## O que Mudou
-
-  ### Recursos
-  - Adicionar expressão if opcional aos passos each.do
-
-  ### Correções de Bugs
-  - Corrigir problemas de JSON da equipe
-
-  ### Documentação
-  - Atualizar snapshot e changelog para v1.14.8a
-
-  ## Contribuidores
-
-  @joaomdmoura, @vinibrsl
-
-</Update>
-
-<Update label="17 jun 2026">
-  ## v1.14.8a
-
-  [Ver release no GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.8a)
-
-  ## O que Mudou
-
-  ### Recursos
-  - Adicionar ação de bloco de script/código ao FlowDefinition
-  - Adicionar ações de equipe ao FlowDefinition
-  - Adicionar ação composta `each` ao FlowDefinition
-  - Implementar suporte ao modo DMN na criação e execução de equipes
-  - Melhorar a funcionalidade de redefinição de memória e o manuseio de equipes em JSON
-  - Adicionar expressões às ações do FlowDefinition
-  - Implementar ferramentas de execução de definição de fluxo sem código Python
-  - Conduzir feedback humano a partir da definição de fluxo
-  - Conectar configuração e persistência do FlowDefinition ao tempo de execução
-  - Adicionar `crewai run --definition` experimental para fluxos
-  - Suportar fallback de implantação ZIP e execuções de projeto de equipe em JSON
-  - Introduzir equipes em JSON primeiro
-
-  ### Correções de Bugs
-  - Corrigir ferramenta Exa duplicada
-  - Corrigir uso de token agregado em todas as chamadas LLM
-  - Resolver problemas com o carregamento de equipes e lógica de validação
-
-  ### Documentação
-  - Documentar campos do FlowDefinition no esquema JSON
-  - Atualizar documentação de instalação e início rápido para projetos de equipe em JSON-primeiro
-  - Atualizar changelog e versão para v1.14.7
-
-  ## Contribuidores
-
-  @gabemilani, @greysonlalonde, @iris-clawd, @joaomdmoura, @lorenzejay, @lucasgomide, @theCyberTech, @vinibrsl
-
-</Update>
-
 <Update label="11 jun 2026">
   ## v1.14.7
 

docs/edge/pt-BR/enterprise/guides/datadog.mdx

@@ -25,7 +25,7 @@ CrewAI supports two log-ingestion paths to Datadog — both are first-class and
 
     **Setup:**
     1. Run the Datadog Agent next to your CrewAI containers — see [Datadog's deployment docs](https://docs.datadoghq.com/agent/) for Kubernetes, ECS, or VM setup. Enable log collection (`logs_enabled: true`) and container log collection (`logs_config.container_collect_all: true`).
-    2. Set `CREWAI_LOG_FORMAT=json` as an **automation environment variable** in CrewAI AMP (open your automation → **Settings → Environment Variables**) so each log event is a single line instead of a multi-line traceback. AMP propagates the value to every container in the deployment (API + workers) — don't set it on the container or host directly. See [Enabling JSON output](#enabling-json-output) below for the AMP UI walkthrough and the [log schema reference](#log-schema-reference) for the full field contract.
+    2. Set `CREWAI_LOG_FORMAT=json` on every CrewAI container (API + workers) so each log event is a single line instead of a multi-line traceback. See the [log schema reference](#log-schema-reference) below for the full field contract.
     3. Confirm logs arrive in Datadog Logs with the JSON fields parsed — see [Verify ingestion](#verify-ingestion).
 
     **Pick this path if** you already operate Datadog Agents (e.g. for infrastructure metrics), or your log volume makes per-event ingestion cost a real concern — collapsing tracebacks into single events keeps Agent ingestion cheap at scale.
@@ -81,7 +81,7 @@ When `CREWAI_LOG_FORMAT=json` is set, every log event is emitted as a **single J
 
 ### Enabling JSON output
 
-`CREWAI_LOG_FORMAT=json` must be set as an **automation environment variable** in CrewAI AMP — it is **not** a container, host, or Docker setting. Open your automation in AMP, click the **Settings** icon, and add the variable under the **Environment Variables** section. AMP applies the value to every container in the deployment (API + workers) on the next restart. See [Update Your Crew](./update-crew) for the full UI walkthrough with screenshots.
+Set the `CREWAI_LOG_FORMAT` environment variable to `json` on every container that runs your deployment (API + workers).
 
 ```shell
 CREWAI_LOG_FORMAT=json
@@ -237,7 +237,7 @@ Open [Logs Explorer](https://app.datadoghq.com/logs) and run a query that matche
   <Tab title="Datadog Agent">
     Search `service:crewai* @schema:v1`. You should see structured logs with the JSON fields parsed into Datadog facets. Pick a recent event and verify it has `@automation_id`, `@kickoff_id`, `@execution_id`, `@crewai_version`, and (when running inside a span) `@trace_id` / `@span_id` populated.
 
-    If nothing appears, confirm `CREWAI_LOG_FORMAT=json` is set under your automation's **Environment Variables** in AMP, the deployment was restarted after the change, and the Datadog Agent is tailing container stdout.
+    If nothing appears, confirm `CREWAI_LOG_FORMAT=json` is set on the running container, the deployment was restarted after the change, and the Datadog Agent is tailing container stdout.
   </Tab>
   <Tab title="Datadog OTLP intake">
     Search `source:otlp service:crewai*`. OTLP attributes land with their OpenTelemetry names (`automation_id`, `crewai.kickoff.id`, etc.) rather than the stdout JSON keys, but they map to the same dashboard facets after [facet promotion](#prerequisite-promote-facets).

lib/cli/pyproject.toml

@@ -8,7 +8,7 @@ authors = [
 ]
 requires-python = ">=3.10, <3.14"
 dependencies = [
-    "crewai-core==1.14.8a1",
+    "crewai-core==1.14.7",
     "click>=8.1.7,<9",
     "pydantic>=2.11.9,<2.13",
     "pydantic-settings~=2.10.1",

lib/cli/src/crewai_cli/__init__.py

@@ -1 +1 @@
-__version__ = "1.14.8a1"
+__version__ = "1.14.7"

lib/cli/src/crewai_cli/create_json_crew.py

@@ -89,16 +89,13 @@ description = "{name} using crewAI"
 authors = [{{ name = "Your Name", email = "you@example.com" }}]
 requires-python = ">=3.10,<3.14"
 dependencies = [
-    "crewai[tools]==1.14.8a1"
+    "crewai[tools]>=1.14.7"
 ]
 
 [build-system]
 requires = ["hatchling"]
 build-backend = "hatchling.build"
 
-[tool.hatch.build.targets.wheel]
-only-include = ["agents", "crew.jsonc", "tools", "knowledge", "skills"]
-
 [tool.crewai]
 type = "crew"
 """

lib/cli/src/crewai_cli/crew_run_tui.py

@@ -34,25 +34,6 @@ _C_MUTED = "#666666"  # dimmer than _C_DIM for past timeline
 _STEP_NUMBER_RE = re.compile(r"\bstep\s+(\d+)\b", re.IGNORECASE)
 _REFINEMENT_RE = re.compile(r"^\s*step\s+(\d+)\s*:\s*(.+)\s*$", re.IGNORECASE)
 _INTERNAL_TOOL_NAMES = {"create_reasoning_plan"}
-_LOG_ARGS_TEXT_LIMIT = 3_000
-_LOG_RESULT_TEXT_LIMIT = 5_000
-_LOG_TRUNCATION_SUFFIX = "... [truncated]"
-# Background memory saves can emit their start event just after kickoff returns.
-_MEMORY_SAVE_DRAIN_GRACE_SECONDS = 2.0
-
-
-def _is_save_to_memory_tool(tool_name: str | None) -> bool:
-    return (tool_name or "").replace(" ", "_").lower() == "save_to_memory"
-
-
-def _truncate_log_text(value: Any, limit: int) -> str | None:
-    if value is None:
-        return None
-    text = str(value)
-    if len(text) <= limit:
-        return text
-    suffix = _LOG_TRUNCATION_SUFFIX
-    return f"{text[: max(0, limit - len(suffix))]}{suffix}"
 
 
 def _enable_tracing_in_dotenv() -> None:
@@ -538,8 +519,6 @@ FooterKey .footer-key--key {
         self._log_expanded: set[int] = set()
         self._log_scroll_needed: bool = False
         self._log_line_map: list[tuple[int, int, int]] = []
-        self._suppressed_memory_save_event_ids: set[str] = set()
-        self._memory_save_drain_timer: Any = None
 
         self._event_handlers: list[tuple[type, Any]] = []
 
@@ -654,6 +633,7 @@ FooterKey .footer-key--key {
             self.call_from_thread(self._on_crew_failed, str(e))
 
     def _on_crew_done(self, output: str | None) -> None:
+        self._unsubscribe()
         with self._lock:
             self._status = "completed"
             self._final_output = output
@@ -669,8 +649,6 @@ FooterKey .footer-key--key {
             now = time.time()
             for entry in self._log_entries:
                 if entry["status"] == "running":
-                    if entry["tool_name"] == "memory_save":
-                        continue
                     entry["status"] = "timeout"
                     entry["error"] = "No result received before crew completed"
                     entry["duration"] = now - entry["start_time"]
@@ -702,9 +680,9 @@ FooterKey .footer-key--key {
         self.call_later(self._focus_activity_log)
         self._tick_timer.stop()
         self._tick_timer = self.set_interval(1 / 2, self._tick)
-        self._unsubscribe_if_no_running_memory_save(wait_for_queued=True)
 
     def _on_crew_failed(self, error: str) -> None:
+        self._unsubscribe()
         with self._lock:
             self._status = "failed"
             self._error = error
@@ -714,16 +692,12 @@ FooterKey .footer-key--key {
             now = time.time()
             for entry in self._log_entries:
                 if entry["status"] == "running":
-                    if entry["tool_name"] == "memory_save":
-                        continue
                     entry["status"] = "error"
-                    entry["error"] = "No result received before crew failed"
                     entry["duration"] = now - entry["start_time"]
         self._tick()
         self.call_later(self._focus_activity_log)
         self._tick_timer.stop()
         self._tick_timer = self.set_interval(1 / 2, self._tick)
-        self._unsubscribe_if_no_running_memory_save(wait_for_queued=True)
 
     # ── Actions ─────────────────────────────────────────────
 
@@ -1540,53 +1514,6 @@ FooterKey .footer-key--key {
             pass
         self._event_handlers.clear()
 
-    def _has_running_memory_save_locked(self) -> bool:
-        return any(
-            entry["tool_name"] == "memory_save" and entry["status"] == "running"
-            for entry in self._log_entries
-        )
-
-    def _on_memory_save_drain_elapsed(self) -> None:
-        self._memory_save_drain_timer = None
-        self._unsubscribe_if_no_running_memory_save()
-
-    def _schedule_memory_save_drain_unsubscribe(self) -> bool:
-        loop = getattr(self, "_loop", None)
-        if loop is None:
-            return False
-        if getattr(self, "_thread_id", None) != threading.get_ident():
-            try:
-                loop.call_soon_threadsafe(self._schedule_memory_save_drain_unsubscribe)
-            except RuntimeError:
-                return False
-            return True
-        if self._memory_save_drain_timer is not None:
-            self._memory_save_drain_timer.stop()
-        self._memory_save_drain_timer = self.set_timer(
-            _MEMORY_SAVE_DRAIN_GRACE_SECONDS,
-            self._on_memory_save_drain_elapsed,
-            name="memory-save-drain",
-        )
-        return True
-
-    def _unsubscribe_if_no_running_memory_save(
-        self, *, wait_for_queued: bool = False
-    ) -> None:
-        with self._lock:
-            should_unsubscribe = (
-                self._status
-                in {
-                    "completed",
-                    "failed",
-                }
-                and not self._has_running_memory_save_locked()
-            )
-
-        if should_unsubscribe:
-            if wait_for_queued and self._schedule_memory_save_drain_unsubscribe():
-                return
-            self._unsubscribe()
-
     def _subscribe(self) -> None:
         from crewai.events.event_bus import crewai_event_bus
         from crewai.events.types.crew_events import CrewKickoffStartedEvent
@@ -1875,8 +1802,6 @@ FooterKey .footer-key--key {
                         entry["status"] == "running"
                         and entry["tool_name"] != event.tool_name
                     ):
-                        if entry["tool_name"] == "memory_save":
-                            continue
                         entry["status"] = "timeout"
                         entry["error"] = (
                             "No result received before the next tool started"
@@ -1905,7 +1830,6 @@ FooterKey .footer-key--key {
                         "duration": None,
                         "task_idx": self._current_task_idx,
                         "plan_step_number": plan_step_number,
-                        "event_id": event.event_id,
                     }
                 )
             self._complete_step("teal", f"⚡ {event.tool_name}…")
@@ -1999,178 +1923,8 @@ FooterKey .footer-key--key {
             MemoryRetrievalCompletedEvent,
             MemoryRetrievalFailedEvent,
             MemoryRetrievalStartedEvent,
-            MemorySaveCompletedEvent,
-            MemorySaveFailedEvent,
-            MemorySaveStartedEvent,
         )
 
-        def is_nested_save_to_memory_event(event: Any) -> bool:
-            if event.parent_event_id is None:
-                return False
-            state = crewai_event_bus.runtime_state
-            if state is None:
-                return False
-            parent_node = state.event_record.nodes.get(event.parent_event_id)
-            parent_event = getattr(parent_node, "event", None)
-            return getattr(
-                parent_event, "type", None
-            ) == "tool_usage_started" and _is_save_to_memory_tool(
-                getattr(parent_event, "tool_name", None)
-            )
-
-        @crewai_event_bus.on(MemorySaveStartedEvent)
-        def on_memory_save_started(source: Any, event: MemorySaveStartedEvent) -> None:
-            with self._lock:
-                if is_nested_save_to_memory_event(event):
-                    self._suppressed_memory_save_event_ids.add(event.event_id)
-                    return
-                for entry in reversed(self._log_entries):
-                    if (
-                        _is_save_to_memory_tool(entry["tool_name"])
-                        and entry.get("event_id") == event.parent_event_id
-                    ):
-                        self._suppressed_memory_save_event_ids.add(event.event_id)
-                        return
-                for entry in reversed(self._log_entries):
-                    if (
-                        entry["tool_name"] == "memory_save"
-                        and entry.get("started_event_id") == event.event_id
-                    ):
-                        entry["args"] = _truncate_log_text(
-                            event.value, _LOG_ARGS_TEXT_LIMIT
-                        )
-                        return
-                self._log_entries.append(
-                    {
-                        "tool_name": "memory_save",
-                        "status": "running",
-                        "args": _truncate_log_text(event.value, _LOG_ARGS_TEXT_LIMIT),
-                        "result": None,
-                        "error": None,
-                        "start_time": time.time(),
-                        "duration": None,
-                        "task_idx": self._current_task_idx,
-                        "event_id": event.event_id,
-                    }
-                )
-
-        self._register_handler(MemorySaveStartedEvent, on_memory_save_started)
-
-        @crewai_event_bus.on(MemorySaveCompletedEvent)
-        def on_memory_save_completed(
-            source: Any, event: MemorySaveCompletedEvent
-        ) -> None:
-            with self._lock:
-                if (
-                    event.started_event_id in self._suppressed_memory_save_event_ids
-                    or is_nested_save_to_memory_event(event)
-                ):
-                    if event.started_event_id is not None:
-                        self._suppressed_memory_save_event_ids.discard(
-                            event.started_event_id
-                        )
-                else:
-                    for entry in reversed(self._log_entries):
-                        has_started_event_match = (
-                            event.started_event_id is not None
-                            and (
-                                entry.get("event_id") == event.started_event_id
-                                or entry.get("started_event_id")
-                                == event.started_event_id
-                            )
-                        )
-                        has_running_event_without_id = (
-                            event.started_event_id is None
-                            and entry["status"] == "running"
-                        )
-                        if entry["tool_name"] == "memory_save" and (
-                            has_running_event_without_id or has_started_event_match
-                        ):
-                            entry["status"] = "success"
-                            entry["duration"] = event.save_time_ms / 1000
-                            entry["result"] = _truncate_log_text(
-                                event.value, _LOG_RESULT_TEXT_LIMIT
-                            )
-                            entry["error"] = None
-                            entry["started_event_id"] = event.started_event_id
-                            break
-                    else:
-                        self._log_entries.append(
-                            {
-                                "tool_name": "memory_save",
-                                "status": "success",
-                                "args": None,
-                                "result": _truncate_log_text(
-                                    event.value, _LOG_RESULT_TEXT_LIMIT
-                                ),
-                                "error": None,
-                                "start_time": time.time(),
-                                "duration": event.save_time_ms / 1000,
-                                "task_idx": self._current_task_idx,
-                                "started_event_id": event.started_event_id,
-                            }
-                        )
-
-            self._unsubscribe_if_no_running_memory_save(wait_for_queued=True)
-
-        self._register_handler(MemorySaveCompletedEvent, on_memory_save_completed)
-
-        @crewai_event_bus.on(MemorySaveFailedEvent)
-        def on_memory_save_failed(source: Any, event: MemorySaveFailedEvent) -> None:
-            with self._lock:
-                if (
-                    event.started_event_id in self._suppressed_memory_save_event_ids
-                    or is_nested_save_to_memory_event(event)
-                ):
-                    if event.started_event_id is not None:
-                        self._suppressed_memory_save_event_ids.discard(
-                            event.started_event_id
-                        )
-                else:
-                    for idx, entry in reversed(list(enumerate(self._log_entries))):
-                        has_started_event_match = (
-                            event.started_event_id is not None
-                            and (
-                                entry.get("event_id") == event.started_event_id
-                                or entry.get("started_event_id")
-                                == event.started_event_id
-                            )
-                        )
-                        has_running_event_without_id = (
-                            event.started_event_id is None
-                            and entry["status"] == "running"
-                        )
-                        if entry["tool_name"] == "memory_save" and (
-                            has_running_event_without_id or has_started_event_match
-                        ):
-                            entry["status"] = "error"
-                            entry["error"] = event.error
-                            entry["duration"] = time.time() - entry["start_time"]
-                            entry["started_event_id"] = event.started_event_id
-                            self._log_expanded.add(idx)
-                            break
-                    else:
-                        self._log_entries.append(
-                            {
-                                "tool_name": "memory_save",
-                                "status": "error",
-                                "args": _truncate_log_text(
-                                    event.value, _LOG_ARGS_TEXT_LIMIT
-                                ),
-                                "result": None,
-                                "error": event.error,
-                                "start_time": time.time(),
-                                "duration": 0,
-                                "task_idx": self._current_task_idx,
-                                "started_event_id": event.started_event_id,
-                            }
-                        )
-                        self._log_expanded.add(len(self._log_entries) - 1)
-
-            self._unsubscribe_if_no_running_memory_save(wait_for_queued=True)
-
-        self._register_handler(MemorySaveFailedEvent, on_memory_save_failed)
-
         @crewai_event_bus.on(MemoryRetrievalStartedEvent)
         def on_memory_retrieval_started(
             source: Any, event: MemoryRetrievalStartedEvent

lib/cli/src/crewai_cli/run_crew.py

@@ -1,6 +1,5 @@
 from __future__ import annotations
 
-from collections.abc import Callable
 from contextlib import AbstractContextManager, nullcontext
 from enum import Enum
 import os
@@ -8,9 +7,10 @@ from pathlib import Path
 import re
 import subprocess
 import sys
-from typing import TYPE_CHECKING, Any, cast
+from typing import TYPE_CHECKING, Any
 
 import click
+from crewai.project.json_loader import find_crew_json_file
 from crewai_core.constants import CREWAI_TRAINED_AGENTS_FILE_ENV
 from packaging import version
 
@@ -38,15 +38,6 @@ class CrewType(Enum):
 _INPUT_PLACEHOLDER_RE = re.compile(r"(?<!{){([A-Za-z_][A-Za-z0-9_\-]*)}(?!})")
 _CREWAI_CLI_RUNNER_PACKAGE_DIR_ENV = "CREWAI_CLI_RUNNER_PACKAGE_DIR"
 _CREWAI_RUNNER_SOURCE_DIR_ENV = "CREWAI_RUNNER_SOURCE_DIR"
-_FULL_CREWAI_INSTALL_MESSAGE = """\
-CrewAI CLI is installed without the `crewai` package required to run crews.
-
-Install the full CrewAI prerelease package:
-
-  uv tool install --force --prerelease=allow 'crewai[tools]==1.14.8a1'
-
-The quotes are required in zsh so `crewai[tools]` is not treated as a glob.
-"""
 _JSON_CREW_RUNNER_CODE = """
 import importlib.util
 import os
@@ -81,39 +72,12 @@ module_spec.loader.exec_module(module)
 
 from crewai_core.constants import CREWAI_TRAINED_AGENTS_FILE_ENV
 
-try:
-    module._run_json_crew(
-        trained_agents_file=os.getenv(CREWAI_TRAINED_AGENTS_FILE_ENV)
-    )
-except module.click.ClickException as exc:
-    exc.show()
-    raise SystemExit(exc.exit_code)
+module._run_json_crew(
+    trained_agents_file=os.getenv(CREWAI_TRAINED_AGENTS_FILE_ENV)
+)
 """.strip()
 
 
-def _import_find_crew_json_file() -> Callable[[], Path | None]:
-    from crewai.project.json_loader import find_crew_json_file as _find_crew_json_file
-
-    return cast("Callable[[], Path | None]", _find_crew_json_file)
-
-
-def _is_missing_crewai_package(exc: ModuleNotFoundError) -> bool:
-    return bool(exc.name and exc.name.startswith("crewai"))
-
-
-def _full_crewai_install_error() -> click.ClickException:
-    return click.ClickException(_FULL_CREWAI_INSTALL_MESSAGE)
-
-
-def find_crew_json_file() -> Path | None:
-    try:
-        return _import_find_crew_json_file()()
-    except ModuleNotFoundError as exc:
-        if _is_missing_crewai_package(exc):
-            raise _full_crewai_install_error() from exc
-        raise
-
-
 def _has_json_crew() -> bool:
     """Check if this is a JSON-defined crew project.
 

lib/cli/src/crewai_cli/templates/AGENTS.md

@@ -767,11 +767,10 @@ class CustomSearchTool(BaseTool):
 ```python
 from crewai.tools import tool
 
-@tool("WordCount")
-def word_count(text: str) -> str:
-    """Counts the number of words in the given text."""
-    count = len(text.split())
-    return f"Word count: {count}"
+@tool("Calculator")
+def calculator(expression: str) -> str:
+    """Evaluates a mathematical expression and returns the result."""
+    return str(eval(expression))
 ```
 
 ### Built-in Tools (install with `uv add crewai-tools`)

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

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<3.14"
 dependencies = [
-    "crewai[tools]==1.14.8a1"
+    "crewai[tools]==1.14.7"
 ]
 
 [project.scripts]

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

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<3.14"
 dependencies = [
-    "crewai[tools]==1.14.8a1"
+    "crewai[tools]==1.14.7"
 ]
 
 [project.scripts]

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

@@ -5,7 +5,7 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<3.14"
 dependencies = [
-    "crewai[tools]==1.14.8a1"
+    "crewai[tools]==1.14.7"
 ]
 
 [tool.crewai]

lib/cli/tests/test_create_crew.py

@@ -5,10 +5,7 @@ from pathlib import Path
 from unittest import mock
 
 import pytest
-import tomli
 from click.testing import CliRunner
-from packaging.requirements import Requirement
-from packaging.version import Version
 import crewai_cli.create_json_crew as json_crew
 import crewai_cli.tui_picker as tui_picker
 from crewai_cli.create_crew import create_crew, create_folder_structure
@@ -715,14 +712,6 @@ def test_json_create_provider_preselects_default_model(tmp_path, monkeypatch):
     assert not (tmp_path / "json_crew" / "tests").exists()
     assert not (tmp_path / "json_crew" / "config.jsonc").exists()
 
-    pyproject = tomli.loads((tmp_path / "json_crew" / "pyproject.toml").read_text())
-    dependency = pyproject["project"]["dependencies"][0]
-    assert dependency == "crewai[tools]==1.14.8a1"
-    assert Version("1.14.8a1") in Requirement(dependency).specifier
-    assert pyproject["tool"]["hatch"]["build"]["targets"]["wheel"][
-        "only-include"
-    ] == ["agents", "crew.jsonc", "tools", "knowledge", "skills"]
-
     crew_template = (tmp_path / "json_crew" / "crew.jsonc").read_text()
     assert (
         '"guardrail": "Every factual claim needs context support."'

lib/cli/tests/test_crew_run_tui.py

@@ -4,11 +4,6 @@ import time
 import pytest
 
 from crewai.events.event_bus import crewai_event_bus
-from crewai.events.types.memory_events import (
-    MemorySaveCompletedEvent,
-    MemorySaveFailedEvent,
-    MemorySaveStartedEvent,
-)
 from crewai.events.types.observation_events import (
     GoalAchievedEarlyEvent,
     PlanRefinementEvent,
@@ -26,12 +21,7 @@ from crewai.events.types.tool_usage_events import (
 )
 from crewai_cli.command import AuthenticationRequiredError
 from crewai_cli import run_crew
-from crewai_cli.crew_run_tui import (
-    CrewRunApp,
-    _LOG_ARGS_TEXT_LIMIT,
-    _LOG_RESULT_TEXT_LIMIT,
-    _LOG_TRUNCATION_SUFFIX,
-)
+from crewai_cli.crew_run_tui import CrewRunApp
 
 
 def _app_with_plan() -> CrewRunApp:
@@ -345,396 +335,6 @@ def test_internal_reasoning_function_call_is_hidden_from_activity_log() -> None:
     assert app._current_task_steps == []
 
 
-def test_memory_save_events_are_shown_in_activity_log() -> None:
-    app = _app_with_plan()
-    app._current_task_idx = 1
-    app._subscribe()
-    try:
-        _emit_event(
-            MemorySaveStartedEvent(
-                value="2 memories (background)",
-                metadata={},
-                source_type="unified_memory",
-            )
-        )
-        _emit_event(
-            MemorySaveCompletedEvent(
-                value="2 memories saved",
-                metadata={},
-                save_time_ms=123,
-                source_type="unified_memory",
-            )
-        )
-    finally:
-        app._unsubscribe()
-
-    assert len(app._log_entries) == 1
-    assert app._log_entries[0]["tool_name"] == "memory_save"
-    assert app._log_entries[0]["status"] == "success"
-    assert app._log_entries[0]["args"] == "2 memories (background)"
-    assert app._log_entries[0]["result"] == "2 memories saved"
-    assert app._log_entries[0]["error"] is None
-    assert app._log_entries[0]["duration"] == 0.123
-    assert app._log_entries[0]["task_idx"] == 1
-
-
-def test_nested_memory_save_event_is_hidden_for_save_to_memory_tool() -> None:
-    app = _app_with_plan()
-    app._subscribe()
-    try:
-        tool_args = {"contents": ["Fact to remember."]}
-        _emit_event(
-            ToolUsageStartedEvent(
-                tool_name="save_to_memory",
-                tool_args=tool_args,
-            )
-        )
-        _emit_event(
-            MemorySaveStartedEvent(
-                value="Fact to remember.",
-                metadata={},
-                source_type="unified_memory",
-            )
-        )
-        _emit_event(
-            MemorySaveCompletedEvent(
-                value="Fact to remember.",
-                metadata={},
-                save_time_ms=123,
-                source_type="unified_memory",
-            )
-        )
-        now = datetime.now()
-        _emit_event(
-            ToolUsageFinishedEvent(
-                tool_name="save_to_memory",
-                tool_args=tool_args,
-                started_at=now,
-                finished_at=now,
-                output="Saved to memory.",
-            )
-        )
-    finally:
-        app._unsubscribe()
-
-    assert len(app._log_entries) == 1
-    assert app._log_entries[0]["tool_name"] == "save_to_memory"
-    assert app._log_entries[0]["status"] == "success"
-    assert app._log_entries[0]["result"] == "Saved to memory."
-
-
-def test_memory_save_failure_is_shown_in_activity_log() -> None:
-    app = _app_with_plan()
-    app._subscribe()
-    try:
-        _emit_event(
-            MemorySaveStartedEvent(
-                value="background save",
-                metadata={},
-                source_type="unified_memory",
-            )
-        )
-        _emit_event(
-            MemorySaveFailedEvent(
-                value="background save",
-                metadata={},
-                error="embedding connection failed",
-                source_type="unified_memory",
-            )
-        )
-    finally:
-        app._unsubscribe()
-
-    assert app._log_entries[0]["tool_name"] == "memory_save"
-    assert app._log_entries[0]["status"] == "error"
-    assert app._log_entries[0]["error"] == "embedding connection failed"
-    assert app._log_expanded == {0}
-
-
-def test_memory_save_completion_updates_timed_out_row() -> None:
-    app = _app_with_plan()
-    app._subscribe()
-    try:
-        _emit_event(
-            MemorySaveStartedEvent(
-                value="9 memories (background)",
-                metadata={},
-                source_type="unified_memory",
-            )
-        )
-
-        app._log_entries[0]["status"] = "timeout"
-        app._log_entries[0]["error"] = "No result received before crew completed"
-        app._log_entries[0]["duration"] = 8.3
-
-        _emit_event(
-            MemorySaveCompletedEvent(
-                value="9 memories saved",
-                metadata={},
-                save_time_ms=8300,
-                source_type="unified_memory",
-            )
-        )
-    finally:
-        app._unsubscribe()
-
-    assert len(app._log_entries) == 1
-    assert app._log_entries[0]["tool_name"] == "memory_save"
-    assert app._log_entries[0]["status"] == "success"
-    assert app._log_entries[0]["result"] == "9 memories saved"
-    assert app._log_entries[0]["error"] is None
-    assert app._log_entries[0]["duration"] == 8.3
-
-
-def test_memory_save_completion_with_unmatched_id_does_not_update_running_row() -> None:
-    app = _app_with_plan()
-    app._subscribe()
-    try:
-        _emit_event(
-            MemorySaveStartedEvent(
-                value="first background save",
-                metadata={},
-                source_type="unified_memory",
-                parent_event_id="manual-parent",
-            )
-        )
-        _emit_event(
-            MemorySaveStartedEvent(
-                value="second background save",
-                metadata={},
-                source_type="unified_memory",
-                parent_event_id="manual-parent",
-            )
-        )
-
-        _emit_event(
-            MemorySaveCompletedEvent(
-                value="orphan save completed",
-                metadata={},
-                save_time_ms=2800,
-                source_type="unified_memory",
-                parent_event_id="manual-parent",
-                started_event_id="missing-memory-save-start",
-            )
-        )
-    finally:
-        app._unsubscribe()
-
-    assert [entry["status"] for entry in app._log_entries] == [
-        "running",
-        "running",
-        "success",
-    ]
-    assert app._log_entries[0]["args"] == "first background save"
-    assert app._log_entries[1]["args"] == "second background save"
-    assert app._log_entries[2]["result"] == "orphan save completed"
-    assert app._log_entries[2]["started_event_id"] == "missing-memory-save-start"
-
-
-def test_memory_save_failure_with_unmatched_id_does_not_update_running_row() -> None:
-    app = _app_with_plan()
-    app._subscribe()
-    try:
-        _emit_event(
-            MemorySaveStartedEvent(
-                value="first background save",
-                metadata={},
-                source_type="unified_memory",
-                parent_event_id="manual-parent",
-            )
-        )
-        _emit_event(
-            MemorySaveStartedEvent(
-                value="second background save",
-                metadata={},
-                source_type="unified_memory",
-                parent_event_id="manual-parent",
-            )
-        )
-
-        _emit_event(
-            MemorySaveFailedEvent(
-                value="orphan save failed",
-                metadata={},
-                error="embedding connection failed",
-                source_type="unified_memory",
-                parent_event_id="manual-parent",
-                started_event_id="missing-memory-save-start",
-            )
-        )
-    finally:
-        app._unsubscribe()
-
-    assert [entry["status"] for entry in app._log_entries] == [
-        "running",
-        "running",
-        "error",
-    ]
-    assert app._log_entries[0]["args"] == "first background save"
-    assert app._log_entries[1]["args"] == "second background save"
-    assert app._log_entries[2]["args"] == "orphan save failed"
-    assert app._log_entries[2]["error"] == "embedding connection failed"
-    assert app._log_entries[2]["started_event_id"] == "missing-memory-save-start"
-    assert app._log_expanded == {2}
-
-
-def test_memory_save_completion_without_id_does_not_update_stale_row() -> None:
-    app = _app_with_plan()
-    now = time.time()
-    app._log_entries = [
-        {
-            "tool_name": "memory_save",
-            "status": "running",
-            "args": "current background save",
-            "result": None,
-            "error": None,
-            "start_time": now,
-            "duration": None,
-            "task_idx": 1,
-        },
-        {
-            "tool_name": "memory_save",
-            "status": "success",
-            "args": "stale background save",
-            "result": "stale save completed",
-            "error": None,
-            "start_time": now - 10,
-            "duration": 1.0,
-            "task_idx": 1,
-        },
-    ]
-
-    app._subscribe()
-    try:
-        _emit_event(
-            MemorySaveCompletedEvent(
-                value="current save completed",
-                metadata={},
-                save_time_ms=2800,
-                source_type="unified_memory",
-                parent_event_id="manual-parent",
-            )
-        )
-    finally:
-        app._unsubscribe()
-
-    assert [entry["status"] for entry in app._log_entries] == [
-        "success",
-        "success",
-    ]
-    assert app._log_entries[0]["args"] == "current background save"
-    assert app._log_entries[0]["result"] == "current save completed"
-    assert app._log_entries[1]["args"] == "stale background save"
-    assert app._log_entries[1]["result"] == "stale save completed"
-
-
-def test_memory_save_failure_without_id_does_not_update_stale_row() -> None:
-    app = _app_with_plan()
-    now = time.time()
-    app._log_entries = [
-        {
-            "tool_name": "memory_save",
-            "status": "running",
-            "args": "current background save",
-            "result": None,
-            "error": None,
-            "start_time": now,
-            "duration": None,
-            "task_idx": 1,
-        },
-        {
-            "tool_name": "memory_save",
-            "status": "success",
-            "args": "stale background save",
-            "result": "stale save completed",
-            "error": None,
-            "start_time": now - 10,
-            "duration": 1.0,
-            "task_idx": 1,
-        },
-    ]
-
-    app._subscribe()
-    try:
-        _emit_event(
-            MemorySaveFailedEvent(
-                value="current save failed",
-                metadata={},
-                error="embedding connection failed",
-                source_type="unified_memory",
-                parent_event_id="manual-parent",
-            )
-        )
-    finally:
-        app._unsubscribe()
-
-    assert [entry["status"] for entry in app._log_entries] == ["error", "success"]
-    assert app._log_entries[0]["args"] == "current background save"
-    assert app._log_entries[0]["error"] == "embedding connection failed"
-    assert app._log_entries[1]["args"] == "stale background save"
-    assert app._log_entries[1]["result"] == "stale save completed"
-    assert app._log_entries[1]["error"] is None
-    assert app._log_expanded == {0}
-
-
-def test_memory_save_payloads_are_truncated_in_activity_log() -> None:
-    app = _app_with_plan()
-    long_args = "a" * (_LOG_ARGS_TEXT_LIMIT + 10)
-    long_result = "r" * (_LOG_RESULT_TEXT_LIMIT + 10)
-
-    app._subscribe()
-    try:
-        _emit_event(
-            MemorySaveStartedEvent(
-                value=long_args,
-                metadata={},
-                source_type="unified_memory",
-            )
-        )
-        _emit_event(
-            MemorySaveCompletedEvent(
-                value=long_result,
-                metadata={},
-                save_time_ms=8300,
-                source_type="unified_memory",
-            )
-        )
-    finally:
-        app._unsubscribe()
-
-    assert len(app._log_entries[0]["args"]) == _LOG_ARGS_TEXT_LIMIT
-    assert app._log_entries[0]["args"].endswith(_LOG_TRUNCATION_SUFFIX)
-    assert len(app._log_entries[0]["result"]) == _LOG_RESULT_TEXT_LIMIT
-    assert app._log_entries[0]["result"].endswith(_LOG_TRUNCATION_SUFFIX)
-
-
-def test_starting_next_tool_does_not_timeout_memory_save() -> None:
-    app = _app_with_plan()
-    app._subscribe()
-    try:
-        _emit_event(
-            MemorySaveStartedEvent(
-                value="9 memories (background)",
-                metadata={},
-                source_type="unified_memory",
-            )
-        )
-        _emit_event(
-            ToolUsageStartedEvent(
-                tool_name="read_website_content",
-                tool_args={"url": "https://example.com"},
-            )
-        )
-    finally:
-        app._unsubscribe()
-
-    assert app._log_entries[0]["tool_name"] == "memory_save"
-    assert app._log_entries[0]["status"] == "running"
-    assert app._log_entries[0]["error"] is None
-    assert app._log_entries[1]["tool_name"] == "read_website_content"
-    assert app._log_entries[1]["status"] == "running"
-
-
 def test_tool_failure_does_not_override_successful_plan_step_completion() -> None:
     app = _app_with_plan()
     app._subscribe()
@@ -880,187 +480,6 @@ async def test_crew_done_does_not_mark_unfinished_tool_successful() -> None:
     assert app._plan_step_status == {1: "failed", 2: "done", 3: "done"}
 
 
-@pytest.mark.asyncio
-async def test_crew_done_does_not_timeout_memory_save() -> None:
-    app = _app_with_plan()
-
-    async with app.run_test(size=(100, 40)) as pilot:
-        app._log_entries = [
-            {
-                "tool_name": "memory_save",
-                "status": "running",
-                "args": "9 memories (background)",
-                "result": None,
-                "error": None,
-                "start_time": time.time() - 8,
-                "duration": None,
-                "task_idx": 1,
-            },
-            {
-                "tool_name": "search",
-                "status": "running",
-                "args": '{"query": "CrewAI"}',
-                "result": None,
-                "error": None,
-                "start_time": time.time() - 2,
-                "duration": None,
-                "task_idx": 1,
-            },
-        ]
-
-        app._on_crew_done("final output")
-        await pilot.pause()
-
-    assert app._log_entries[0]["status"] == "running"
-    assert app._log_entries[0]["error"] is None
-    assert app._log_entries[1]["status"] == "timeout"
-    assert app._log_entries[1]["error"] == "No result received before crew completed"
-
-
-@pytest.mark.asyncio
-async def test_crew_done_keeps_memory_save_subscription_until_completion(
-    monkeypatch: pytest.MonkeyPatch,
-) -> None:
-    monkeypatch.setattr(
-        "crewai_cli.crew_run_tui._MEMORY_SAVE_DRAIN_GRACE_SECONDS", 0.05
-    )
-    app = _app_with_plan()
-    auto_unsubscribed = False
-
-    async with app.run_test(size=(100, 40)) as pilot:
-        try:
-            assert app._event_handlers
-            started_event = MemorySaveStartedEvent(
-                value="9 memories (background)",
-                metadata={},
-                source_type="unified_memory",
-            )
-            _emit_event(started_event)
-
-            app._on_crew_done("final output")
-            await pilot.pause()
-
-            assert app._log_entries[0]["status"] == "running"
-            assert app._event_handlers
-
-            _emit_event(
-                MemorySaveCompletedEvent(
-                    value="9 memories saved",
-                    metadata={},
-                    save_time_ms=8300,
-                    source_type="unified_memory",
-                    started_event_id=started_event.event_id,
-                )
-            )
-            await pilot.pause()
-
-            assert app._event_handlers
-            await pilot.pause(0.08)
-            auto_unsubscribed = not app._event_handlers
-        finally:
-            app._unsubscribe()
-
-    assert app._log_entries[0]["tool_name"] == "memory_save"
-    assert app._log_entries[0]["status"] == "success"
-    assert app._log_entries[0]["result"] == "9 memories saved"
-    assert app._log_entries[0]["error"] is None
-    assert app._log_entries[0]["duration"] == 8.3
-    assert auto_unsubscribed is True
-
-
-@pytest.mark.asyncio
-async def test_crew_done_waits_for_queued_memory_save_events(
-    monkeypatch: pytest.MonkeyPatch,
-) -> None:
-    monkeypatch.setattr(
-        "crewai_cli.crew_run_tui._MEMORY_SAVE_DRAIN_GRACE_SECONDS", 0.05
-    )
-    app = _app_with_plan()
-    auto_unsubscribed = False
-
-    async with app.run_test(size=(100, 40)) as pilot:
-        try:
-            assert app._event_handlers
-
-            app._on_crew_done("final output")
-
-            assert app._event_handlers
-            started_event = MemorySaveStartedEvent(
-                value="9 memories (background)",
-                metadata={},
-                source_type="unified_memory",
-                parent_event_id="manual-parent",
-            )
-            _emit_event(started_event)
-            await pilot.pause()
-
-            assert app._log_entries[0]["tool_name"] == "memory_save"
-            assert app._log_entries[0]["status"] == "running"
-
-            _emit_event(
-                MemorySaveCompletedEvent(
-                    value="9 memories saved",
-                    metadata={},
-                    save_time_ms=8300,
-                    source_type="unified_memory",
-                    parent_event_id="manual-parent",
-                    started_event_id=started_event.event_id,
-                )
-            )
-            await pilot.pause()
-
-            assert app._event_handlers
-            await pilot.pause(0.08)
-            auto_unsubscribed = not app._event_handlers
-        finally:
-            app._unsubscribe()
-
-    assert app._log_entries[0]["tool_name"] == "memory_save"
-    assert app._log_entries[0]["status"] == "success"
-    assert app._log_entries[0]["args"] == "9 memories (background)"
-    assert app._log_entries[0]["result"] == "9 memories saved"
-    assert app._log_entries[0]["error"] is None
-    assert app._log_entries[0]["duration"] == 8.3
-    assert auto_unsubscribed is True
-
-
-@pytest.mark.asyncio
-async def test_crew_failed_does_not_timeout_memory_save() -> None:
-    app = _app_with_plan()
-
-    async with app.run_test(size=(100, 40)) as pilot:
-        app._log_entries = [
-            {
-                "tool_name": "memory_save",
-                "status": "running",
-                "args": "9 memories (background)",
-                "result": None,
-                "error": None,
-                "start_time": time.time() - 8,
-                "duration": None,
-                "task_idx": 1,
-            },
-            {
-                "tool_name": "search",
-                "status": "running",
-                "args": '{"query": "CrewAI"}',
-                "result": None,
-                "error": None,
-                "start_time": time.time() - 2,
-                "duration": None,
-                "task_idx": 1,
-            },
-        ]
-
-        app._on_crew_failed("boom")
-        await pilot.pause()
-
-    assert app._log_entries[0]["status"] == "running"
-    assert app._log_entries[0]["error"] is None
-    assert app._log_entries[1]["status"] == "error"
-    assert app._log_entries[1]["error"] == "No result received before crew failed"
-
-
 def test_streamed_step_observation_updates_named_step_only() -> None:
     app = _app_with_plan()
 

lib/cli/tests/test_run_crew.py

@@ -5,33 +5,12 @@ from pathlib import Path
 import subprocess
 import sys
 
-import click
 import pytest
 from crewai_core.constants import CREWAI_TRAINED_AGENTS_FILE_ENV
 
 import crewai_cli.run_crew as run_crew_module
 
 
-def test_missing_crewai_package_shows_full_install_hint(monkeypatch):
-    def missing_crewai_package():
-        raise ModuleNotFoundError("No module named 'crewai'", name="crewai")
-
-    monkeypatch.setattr(
-        run_crew_module, "_import_find_crew_json_file", missing_crewai_package
-    )
-
-    with pytest.raises(click.ClickException) as exc_info:
-        run_crew_module.find_crew_json_file()
-
-    message = exc_info.value.message
-    assert "CrewAI CLI is installed without the `crewai` package" in message
-    assert (
-        "uv tool install --force --prerelease=allow 'crewai[tools]==1.14.8a1'"
-        in message
-    )
-    assert "quotes are required in zsh" in message
-
-
 def test_run_crew_forwards_trained_agents_file_to_json_crews(monkeypatch):
     """crewai run -f must reach JSON crews, not only classic subprocess crews."""
     monkeypatch.setattr(run_crew_module, "_has_json_crew", lambda: True)

lib/crewai-core/src/crewai_core/__init__.py

@@ -1 +1 @@
-__version__ = "1.14.8a1"
+__version__ = "1.14.7"

lib/crewai-files/pyproject.toml

@@ -9,7 +9,7 @@ authors = [
 requires-python = ">=3.10, <3.14"
 dependencies = [
     "Pillow~=12.1.1",
-    "pypdf~=6.13.3",
+    "pypdf~=6.10.0",
     "python-magic>=0.4.27",
     "aiocache~=0.12.3",
     "aiofiles~=24.1.0",
@@ -19,8 +19,6 @@ dependencies = [
 
 [tool.uv]
 exclude-newer = "3 days"
-# pypdf 6.13.3 is a security fix newer than the global supply-chain cutoff.
-exclude-newer-package = { pypdf = "2026-06-18T00:00:00Z" }
 
 [build-system]
 requires = ["hatchling"]

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

@@ -152,4 +152,4 @@ __all__ = [
     "wrap_file_source",
 ]
 
-__version__ = "1.14.8a1"
+__version__ = "1.14.7"

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==1.14.8a1",
+    "crewai==1.14.7",
     "tiktoken>=0.8.0,<0.13",
     "beautifulsoup4~=4.13.4",
     "python-docx~=1.2.0",

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

@@ -330,4 +330,4 @@ __all__ = [
     "ZapierActionTools",
 ]
 
-__version__ = "1.14.8a1"
+__version__ = "1.14.7"

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

@@ -32,8 +32,6 @@ class ToolSpecExtractor:
             if name.endswith("Tool") and name not in self.processed_tools:
                 obj = getattr(tools, name, None)
                 if inspect.isclass(obj) and issubclass(obj, BaseTool):
-                    if getattr(obj, "is_deprecated_alias", False):
-                        continue
                     self.extract_tool_info(obj)
                     self.processed_tools.add(name)
         return self.tools_spec

lib/crewai-tools/src/crewai_tools/tools/exa_tools/exa_search_tool.py

@@ -2,7 +2,7 @@ from __future__ import annotations
 
 from builtins import type as type_
 import os
-from typing import Any, ClassVar, TypedDict
+from typing import Any, TypedDict
 import warnings
 
 from crewai.tools import BaseTool, EnvVar
@@ -160,8 +160,6 @@ class ExaSearchTool(BaseTool):
 class EXASearchTool(ExaSearchTool):
     """Deprecated alias for :class:`ExaSearchTool`. Kept for backwards compatibility."""
 
-    is_deprecated_alias: ClassVar[bool] = True
-
     name: str = "ExaSearchTool"
 
     def __init__(self, *args: Any, **kwargs: Any) -> None:

lib/crewai-tools/tests/test_generate_tool_specs.py

@@ -1,4 +1,3 @@
-import builtins
 import json
 from unittest import mock
 
@@ -8,19 +7,6 @@ from pydantic import BaseModel, Field
 import pytest
 
 
-def _getattr_for(tool_name, tool_cls):
-    """Build a getattr side_effect that resolves the patched tool name to
-    ``tool_cls`` while delegating every other lookup (e.g. the
-    ``is_deprecated_alias`` check) to the real builtin."""
-
-    def _getattr(obj, name, *default):
-        if name == tool_name:
-            return tool_cls
-        return builtins.getattr(obj, name, *default)
-
-    return _getattr
-
-
 class MockToolSchema(BaseModel):
     query: str = Field(..., description="The query parameter")
     count: int = Field(5, description="Number of results to return")
@@ -98,10 +84,7 @@ def test_unwrap_schema(extractor):
 def mock_tool_extractor(extractor):
     with (
         mock.patch("crewai_tools.generate_tool_specs.dir", return_value=["MockTool"]),
-        mock.patch(
-            "crewai_tools.generate_tool_specs.getattr",
-            side_effect=_getattr_for("MockTool", MockTool),
-        ),
+        mock.patch("crewai_tools.generate_tool_specs.getattr", return_value=MockTool),
     ):
         extractor.extract_all_tools()
         assert len(extractor.tools_spec) == 1
@@ -240,7 +223,7 @@ def test_intermediate_base_fields_preserved_for_derived_tool(extractor):
         ),
         mock.patch(
             "crewai_tools.generate_tool_specs.getattr",
-            side_effect=_getattr_for("MockDerivedTool", MockDerivedTool),
+            return_value=MockDerivedTool,
         ),
     ):
         extractor.extract_all_tools()
@@ -270,10 +253,7 @@ def test_future_base_tool_field_auto_excluded(extractor):
     by checking that ONLY non-BaseTool fields appear."""
     with (
         mock.patch("crewai_tools.generate_tool_specs.dir", return_value=["MockTool"]),
-        mock.patch(
-            "crewai_tools.generate_tool_specs.getattr",
-            side_effect=_getattr_for("MockTool", MockTool),
-        ),
+        mock.patch("crewai_tools.generate_tool_specs.getattr", return_value=MockTool),
     ):
         extractor.extract_all_tools()
         tool_info = extractor.tools_spec[0]

lib/crewai-tools/tests/tools/exa_search_tool_test.py

@@ -111,11 +111,3 @@ def test_exasearchtool_alias_is_deprecated():
         with pytest.warns(DeprecationWarning, match="ExaSearchTool"):
             tool = EXASearchTool(api_key="test_api_key")
         assert isinstance(tool, ExaSearchTool)
-
-
-def test_deprecated_alias_excluded_from_tool_specs():
-    from crewai_tools.generate_tool_specs import ToolSpecExtractor
-
-    names = {tool["name"] for tool in ToolSpecExtractor().extract_all_tools()}
-    assert "ExaSearchTool" in names
-    assert "EXASearchTool" not in names

lib/crewai-tools/tool.specs.json

@@ -9622,6 +9622,225 @@
         "type": "object"
       }
     },
+    {
+      "description": "Search the web with Exa, the fastest and most accurate web search API.",
+      "env_vars": [
+        {
+          "default": null,
+          "description": "API key for Exa services",
+          "name": "EXA_API_KEY",
+          "required": false
+        },
+        {
+          "default": null,
+          "description": "API url for the Exa services",
+          "name": "EXA_BASE_URL",
+          "required": false
+        }
+      ],
+      "humanized_name": "ExaSearchTool",
+      "init_params_schema": {
+        "$defs": {
+          "EnvVar": {
+            "properties": {
+              "default": {
+                "anyOf": [
+                  {
+                    "type": "string"
+                  },
+                  {
+                    "type": "null"
+                  }
+                ],
+                "default": null,
+                "title": "Default"
+              },
+              "description": {
+                "title": "Description",
+                "type": "string"
+              },
+              "name": {
+                "title": "Name",
+                "type": "string"
+              },
+              "required": {
+                "default": true,
+                "title": "Required",
+                "type": "boolean"
+              }
+            },
+            "required": [
+              "name",
+              "description"
+            ],
+            "title": "EnvVar",
+            "type": "object"
+          }
+        },
+        "description": "Deprecated alias for :class:`ExaSearchTool`. Kept for backwards compatibility.",
+        "properties": {
+          "api_key": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "description": "API key for Exa services",
+            "required": false,
+            "title": "Api Key"
+          },
+          "base_url": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "description": "API server url",
+            "required": false,
+            "title": "Base Url"
+          },
+          "client": {
+            "anyOf": [
+              {},
+              {
+                "type": "null"
+              }
+            ],
+            "default": null,
+            "title": "Client"
+          },
+          "content": {
+            "anyOf": [
+              {
+                "type": "boolean"
+              },
+              {
+                "additionalProperties": true,
+                "type": "object"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": false,
+            "title": "Content"
+          },
+          "highlights": {
+            "anyOf": [
+              {
+                "type": "boolean"
+              },
+              {
+                "additionalProperties": true,
+                "type": "object"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": true,
+            "title": "Highlights"
+          },
+          "summary": {
+            "anyOf": [
+              {
+                "type": "boolean"
+              },
+              {
+                "additionalProperties": true,
+                "type": "object"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": false,
+            "title": "Summary"
+          },
+          "type": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": "auto",
+            "title": "Type"
+          }
+        },
+        "required": [],
+        "title": "EXASearchTool",
+        "type": "object"
+      },
+      "name": "EXASearchTool",
+      "package_dependencies": [
+        "exa_py"
+      ],
+      "run_params_schema": {
+        "properties": {
+          "end_published_date": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null,
+            "description": "End date for the search",
+            "title": "End Published Date"
+          },
+          "include_domains": {
+            "anyOf": [
+              {
+                "items": {
+                  "type": "string"
+                },
+                "type": "array"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null,
+            "description": "List of domains to include in the search",
+            "title": "Include Domains"
+          },
+          "search_query": {
+            "description": "Mandatory search query you want to use to search the internet",
+            "title": "Search Query",
+            "type": "string"
+          },
+          "start_published_date": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null,
+            "description": "Start date for the search",
+            "title": "Start Published Date"
+          }
+        },
+        "required": [
+          "search_query"
+        ],
+        "title": "ExaBaseToolSchema",
+        "type": "object"
+      }
+    },
     {
       "description": "Search the web with Exa, the fastest and most accurate web search API.",
       "env_vars": [

lib/crewai/pyproject.toml

@@ -8,8 +8,8 @@ authors = [
 ]
 requires-python = ">=3.10, <3.14"
 dependencies = [
-    "crewai-core==1.14.8a1",
-    "crewai-cli==1.14.8a1",
+    "crewai-core==1.14.7",
+    "crewai-cli==1.14.7",
     # Core Dependencies
     "pydantic>=2.11.9,<2.13",
     "openai>=2.30.0,<3",
@@ -55,7 +55,7 @@ Repository = "https://github.com/crewAIInc/crewAI"
 
 [project.optional-dependencies]
 tools = [
-    "crewai-tools==1.14.8a1",
+    "crewai-tools==1.14.7",
 ]
 embeddings = [
     "tiktoken>=0.8.0,<0.13"

lib/crewai/src/crewai/__init__.py

@@ -48,7 +48,7 @@ def _suppress_pydantic_deprecation_warnings() -> None:
 
 _suppress_pydantic_deprecation_warnings()
 
-__version__ = "1.14.8a1"
+__version__ = "1.14.7"
 
 _LAZY_IMPORTS: dict[str, tuple[str, str]] = {
     "Memory": ("crewai.memory.unified_memory", "Memory"),

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

@@ -10,7 +10,6 @@ from crewai.flow.conversation import (
     ConversationalInputs,
 )
 from crewai.flow.dsl import HumanFeedbackResult, human_feedback
-from crewai.flow.expressions import Expression
 from crewai.flow.flow import Flow, and_, listen, or_, router, start
 from crewai.flow.flow_config import flow_config
 from crewai.flow.input_provider import InputProvider, InputResponse
@@ -27,7 +26,6 @@ __all__ = [
     "ConsoleProvider",
     "ConversationalConfig",
     "ConversationalInputs",
-    "Expression",
     "Flow",
     "FlowStructure",
     "HumanFeedbackPending",

lib/crewai/src/crewai/flow/dsl/_utils.py

@@ -14,6 +14,7 @@ from crewai.flow.flow_definition import (
     FlowConversationalDefinition,
     FlowConversationalRouterDefinition,
     FlowDefinition,
+    FlowDefinitionDiagnostic,
     FlowDictStateDefinition,
     FlowHumanFeedbackDefinition,
     FlowMethodDefinition,
@@ -22,7 +23,6 @@ from crewai.flow.flow_definition import (
     FlowStateDefinition,
     FlowUnknownStateDefinition,
     _object_ref,
-    log_flow_definition_issues,
 )
 from crewai.flow.flow_wrappers import (
     FlowMethod,
@@ -116,6 +116,7 @@ def _is_json_serializable(value: Any) -> bool:
 
 def _serialize_static_value(
     value: Any,
+    diagnostics: list[FlowDefinitionDiagnostic],
     path: str,
 ) -> Any:
     if value is None or _is_json_serializable(value):
@@ -147,11 +148,12 @@ def _serialize_static_value(
             )
 
     ref = _object_ref(value)
-    logger.warning(
-        "Flow definition value at %s is not fully serializable; "
-        "preserved import reference %s.",
-        path,
-        ref,
+    diagnostics.append(
+        FlowDefinitionDiagnostic(
+            code="non_serializable_value",
+            path=path,
+            message=f"value is not fully serializable; preserved import reference {ref}",
+        )
     )
     return {"ref": ref}
 
@@ -167,7 +169,10 @@ def _state_ref(value: Any) -> str | None:
     return None
 
 
-def _build_state_definition(flow_class: type) -> FlowStateDefinition | None:
+def _build_state_definition(
+    flow_class: type,
+    diagnostics: list[FlowDefinitionDiagnostic],
+) -> FlowStateDefinition | None:
     from pydantic import BaseModel as PydanticBaseModel
 
     state_value = getattr(flow_class, "_initial_state_t", None)
@@ -182,23 +187,29 @@ def _build_state_definition(flow_class: type) -> FlowStateDefinition | None:
     if state_value is dict or isinstance(state_value, dict):
         default = None
         if isinstance(state_value, dict):
-            default = _serialize_static_value(state_value, "state.default")
+            default = _serialize_static_value(state_value, diagnostics, "state.default")
         return FlowDictStateDefinition(default=default)
     if isinstance(state_value, type) and issubclass(state_value, PydanticBaseModel):
         return FlowPydanticStateDefinition(ref=_state_ref(state_value))
     if isinstance(state_value, PydanticBaseModel):
         return FlowPydanticStateDefinition(
             ref=_state_ref(state_value),
-            default=_serialize_static_value(state_value, "state.default"),
+            default=_serialize_static_value(state_value, diagnostics, "state.default"),
+        )
+    diagnostics.append(
+        FlowDefinitionDiagnostic(
+            code="unknown_state_type",
+            path="state",
+            message=f"could not serialize state type {_object_ref(state_value)}",
         )
-    logger.warning(
-        "Flow definition state could not serialize state type %s.",
-        _object_ref(state_value),
     )
     return FlowUnknownStateDefinition(ref=_state_ref(state_value))
 
 
-def _build_config_definition(flow_class: type) -> FlowConfigDefinition:
+def _build_config_definition(
+    flow_class: type,
+    diagnostics: list[FlowDefinitionDiagnostic],
+) -> FlowConfigDefinition:
     config_field_names = set(FlowConfigDefinition.model_fields)
     field_defaults = {
         name: field.get_default(call_default_factory=True)
@@ -214,12 +225,15 @@ def _build_config_definition(flow_class: type) -> FlowConfigDefinition:
                 value if value is None or isinstance(value, str) else _object_ref(value)
             )
         else:
-            values[field_name] = _serialize_static_value(value, f"config.{field_name}")
+            values[field_name] = _serialize_static_value(
+                value, diagnostics, f"config.{field_name}"
+            )
     return FlowConfigDefinition(**values)
 
 
 def _build_human_feedback_definition(
     method: Any,
+    diagnostics: list[FlowDefinitionDiagnostic],
     path: str,
 ) -> FlowHumanFeedbackDefinition | None:
     config = getattr(method, "__human_feedback_config__", None)
@@ -234,7 +248,7 @@ def _build_human_feedback_definition(
         llm=getattr(config, "llm", None),
         default_outcome=getattr(config, "default_outcome", None),
         metadata=_serialize_static_value(
-            getattr(config, "metadata", None), f"{path}.metadata"
+            getattr(config, "metadata", None), diagnostics, f"{path}.metadata"
         ),
         provider=getattr(config, "provider", None),
         learn=bool(getattr(config, "learn", False)),
@@ -259,6 +273,7 @@ def _build_persistence_definition(value: Any) -> FlowPersistenceDefinition | Non
 
 def _build_conversational_router_definition(
     router_config: Any,
+    diagnostics: list[FlowDefinitionDiagnostic],
     path: str,
 ) -> FlowConversationalRouterDefinition | None:
     if router_config is None:
@@ -269,9 +284,12 @@ def _build_conversational_router_definition(
         prompt=getattr(router_config, "prompt", None),
         response_format=_serialize_static_value(
             getattr(router_config, "response_format", None),
+            diagnostics,
             f"{path}.response_format",
         ),
-        llm=_serialize_static_value(getattr(router_config, "llm", None), f"{path}.llm"),
+        llm=_serialize_static_value(
+            getattr(router_config, "llm", None), diagnostics, f"{path}.llm"
+        ),
         routes=[str(route) for route in routes] if routes is not None else None,
         route_descriptions=getattr(router_config, "route_descriptions", None),
         default_intent=getattr(router_config, "default_intent", "converse"),
@@ -282,6 +300,7 @@ def _build_conversational_router_definition(
 
 def _build_conversational_definition(
     flow_class: type,
+    diagnostics: list[FlowDefinitionDiagnostic],
 ) -> FlowConversationalDefinition | None:
     if not _is_conversational_flow(flow_class):
         return None
@@ -305,9 +324,12 @@ def _build_conversational_definition(
     return FlowConversationalDefinition(
         enabled=True,
         system_prompt=getattr(config, "system_prompt", None),
-        llm=_serialize_static_value(getattr(config, "llm", None), "conversational.llm"),
+        llm=_serialize_static_value(
+            getattr(config, "llm", None), diagnostics, "conversational.llm"
+        ),
         router=_build_conversational_router_definition(
             getattr(config, "router", None),
+            diagnostics,
             "conversational.router",
         ),
         answer_from_history_prompt=getattr(config, "answer_from_history_prompt", None),
@@ -318,10 +340,12 @@ def _build_conversational_definition(
         ),
         intent_llm=_serialize_static_value(
             getattr(config, "intent_llm", None),
+            diagnostics,
             "conversational.intent_llm",
         ),
         answer_from_history_llm=_serialize_static_value(
             getattr(config, "answer_from_history_llm", None),
+            diagnostics,
             "conversational.answer_from_history_llm",
         ),
         visible_agent_outputs=(
@@ -341,6 +365,7 @@ def _build_conversational_definition(
 
 def _build_method_definition(
     method: Any,
+    diagnostics: list[FlowDefinitionDiagnostic],
     path: str,
 ) -> FlowMethodDefinition:
     fragment = _get_flow_method_definition(method)
@@ -351,7 +376,9 @@ def _build_method_definition(
             deep=True, update={"do": _method_action(method)}
         )
 
-    human_feedback = _build_human_feedback_definition(method, f"{path}.human_feedback")
+    human_feedback = _build_human_feedback_definition(
+        method, diagnostics, f"{path}.human_feedback"
+    )
     if human_feedback is not None:
         method_definition.human_feedback = human_feedback
         if human_feedback.emit:
@@ -417,6 +444,7 @@ def _build_flow_definition_from_class(
     flow_class: type,
     namespace: dict[str, Any] | None = None,
 ) -> FlowDefinition:
+    diagnostics: list[FlowDefinitionDiagnostic] = []
     methods: dict[str, FlowMethodDefinition] = {}
     flow_methods = _iter_flow_methods(flow_class)
     if namespace is not None:
@@ -428,7 +456,7 @@ def _build_flow_definition_from_class(
 
     for method_name, method in flow_methods.items():
         methods[method_name] = _build_method_definition(
-            method, f"methods.{method_name}"
+            method, diagnostics, f"methods.{method_name}"
         )
 
     description = None
@@ -439,13 +467,15 @@ def _build_flow_definition_from_class(
     definition = FlowDefinition(
         name=getattr(flow_class, "__name__", "Flow"),
         description=description,
-        state=_build_state_definition(flow_class),
-        config=_build_config_definition(flow_class),
+        state=_build_state_definition(flow_class, diagnostics),
+        config=_build_config_definition(flow_class, diagnostics),
         persist=_build_persistence_definition(flow_class),
-        conversational=_build_conversational_definition(flow_class),
+        conversational=_build_conversational_definition(flow_class, diagnostics),
         methods=methods,
+        diagnostics=diagnostics,
     )
-    log_flow_definition_issues(definition)
+    definition.diagnostics.extend(definition.validate_contract())
+    definition.log_diagnostics()
     return definition
 
 

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

@@ -1,329 +0,0 @@
-"""Runtime expression support for FlowDefinition CEL expressions."""
-
-from __future__ import annotations
-
-from collections.abc import Iterable
-import json
-from typing import TYPE_CHECKING, Any, TypeAlias, cast
-
-from crewai.utilities.serialization import to_serializable
-
-
-if TYPE_CHECKING:
-    from crewai.flow.runtime import Flow
-else:
-    from typing_extensions import TypeAliasType
-
-
-_CEL_MACROS_WITH_LOCAL_BINDINGS = frozenset(
-    {"all", "exists", "exists_one", "filter", "map"}
-)
-if TYPE_CHECKING:
-    ExpressionData: TypeAlias = (
-        str
-        | int
-        | float
-        | bool
-        | None
-        | list["ExpressionData"]
-        | dict[str, "ExpressionData"]
-    )
-else:
-    ExpressionData = TypeAliasType(
-        "ExpressionData",
-        str
-        | int
-        | float
-        | bool
-        | None
-        | list["ExpressionData"]
-        | dict[str, "ExpressionData"],
-    )
-
-__all__ = [
-    "Expression",
-    "ExpressionData",
-    "ExpressionError",
-]
-
-
-class ExpressionError(ValueError):
-    """An expression failed to parse, validate, render, or evaluate."""
-
-
-class Expression:
-    """CEL expression helper used for definition-time checks and runtime rendering."""
-
-    def __init__(
-        self, value: ExpressionData, *, context: dict[str, Any] | None = None
-    ) -> None:
-        self.value = value
-        self.context = context
-
-    @classmethod
-    def from_flow(
-        cls,
-        value: ExpressionData,
-        flow: Flow[Any],
-        *,
-        local_context: dict[str, Any] | None = None,
-    ) -> Expression:
-        """Build an expression with the standard Flow runtime context."""
-        return cls(value, context=cls._flow_context(flow, local_context=local_context))
-
-    def validate_expression(
-        self,
-        *,
-        allowed_roots: Iterable[str],
-        source: str = "CEL expression",
-    ) -> None:
-        """Validate a full CEL expression without evaluating it."""
-        allowed = frozenset(allowed_roots)
-        expression = self._require_cel_source(cast(str, self.value), source=source)
-        roots = self._collect_root_identifiers(
-            self._compile_cel(expression, source=source)
-        )
-        unknown = sorted(root for root in roots if root not in allowed)
-        if unknown:
-            allowed_list = ", ".join(sorted(allowed))
-            unknown_list = ", ".join(repr(root) for root in unknown)
-            raise ExpressionError(
-                f"unknown CEL root at {source}: {unknown_list}; "
-                f"allowed roots: {allowed_list}. Reference flow data through one "
-                "of those roots, for example state.field or outputs.step_name."
-            )
-
-    def validate_template(
-        self,
-        *,
-        allowed_roots: Iterable[str],
-        source: str = "with block",
-    ) -> None:
-        """Validate nested strings fully wrapped in ``${...}`` as CEL."""
-        self._validate_template_value(
-            self.value, allowed_roots=allowed_roots, source=source
-        )
-
-    def evaluate(self, context: dict[str, Any] | None = None) -> Any:
-        """Evaluate this value as a full CEL expression."""
-        resolved_context = self.context if context is None else context
-        return self._evaluate_cel(
-            self._require_cel_source(cast(str, self.value)),
-            resolved_context or {},
-        )
-
-    def render_template(self, context: dict[str, Any] | None = None) -> Any:
-        """Evaluate nested strings fully wrapped in ``${...}`` as CEL."""
-        resolved_context = self.context if context is None else context
-        return self._render_template_value(self.value, resolved_context or {})
-
-    @staticmethod
-    def _validate_template_value(
-        value: ExpressionData,
-        *,
-        allowed_roots: Iterable[str],
-        source: str,
-    ) -> None:
-        if isinstance(value, str):
-            expression = Expression._expression_marker_source(value, source=source)
-            if expression is not None:
-                Expression(expression).validate_expression(
-                    allowed_roots=allowed_roots, source=source
-                )
-            return
-        if isinstance(value, dict):
-            for key, item in value.items():
-                item_source = f"{source}.{key}" if isinstance(key, str) else source
-                Expression._validate_template_value(
-                    item, allowed_roots=allowed_roots, source=item_source
-                )
-            return
-        if isinstance(value, list):
-            for index, item in enumerate(value):
-                Expression._validate_template_value(
-                    item,
-                    allowed_roots=allowed_roots,
-                    source=f"{source}[{index}]",
-                )
-
-    @staticmethod
-    def _flow_context(
-        flow: Flow[Any], local_context: dict[str, Any] | None = None
-    ) -> dict[str, Any]:
-        from crewai.flow.runtime._outputs import outputs_by_name
-
-        local_outputs = local_context.get("outputs") if local_context else None
-        outputs = outputs_by_name(
-            flow._method_outputs,
-            local_outputs=local_outputs,
-            serialize=True,
-        )
-        context: dict[str, Any] = {
-            "state": flow._copy_and_serialize_state(),
-            "outputs": outputs,
-        }
-        if local_context:
-            context.update(
-                {
-                    key: to_serializable(value, max_depth=0)
-                    for key, value in local_context.items()
-                    if key not in {"outputs", "state"}
-                }
-            )
-        return context
-
-    @staticmethod
-    def _render_template_value(value: ExpressionData, context: dict[str, Any]) -> Any:
-        if isinstance(value, str):
-            return Expression._render_template_string(value, context)
-        if isinstance(value, dict):
-            return {
-                key: Expression._render_template_value(item, context)
-                for key, item in value.items()
-            }
-        if isinstance(value, list):
-            return [Expression._render_template_value(item, context) for item in value]
-        return value
-
-    @staticmethod
-    def _render_template_string(value: str, context: dict[str, Any]) -> Any:
-        expression = Expression._expression_marker_source(value)
-        if expression is None:
-            return value
-        return Expression._evaluate_cel(expression, context)
-
-    @staticmethod
-    def _expression_marker_source(
-        value: str, *, source: str | None = None
-    ) -> str | None:
-        """Return CEL source when the trimmed string starts with ``${`` and ends with ``}``."""
-        stripped = value.strip()
-        if not stripped.startswith("${"):
-            return None
-        if not stripped.endswith("}"):
-            return None
-
-        expression = stripped[2:-1].strip()
-        if not expression:
-            if source is None:
-                raise ExpressionError("empty CEL expression in with block")
-            raise ExpressionError(f"empty CEL expression at {source}")
-        return expression
-
-    @staticmethod
-    def _evaluate_cel(expression: str, context: dict[str, Any]) -> Any:
-        try:
-            from celpy import Environment
-            from celpy.adapter import CELJSONEncoder, json_to_cel
-            from celpy.evaluation import Context
-
-            environment = Environment()
-            program = environment.program(
-                Expression._compile_cel(expression, environment=environment)
-            )
-            result = program.evaluate(cast(Context, json_to_cel(context)))
-            return json.loads(json.dumps(result, cls=CELJSONEncoder))
-        except Exception as e:
-            raise ExpressionError(
-                f"failed to evaluate CEL expression {expression!r}: {e}"
-            ) from e
-
-    @staticmethod
-    def _compile_cel(
-        expression: str,
-        *,
-        source: str | None = None,
-        environment: Any | None = None,
-    ) -> Any:
-        if environment is None:
-            from celpy import Environment
-
-            environment = Environment()
-        try:
-            return environment.compile(expression)
-        except Exception as e:
-            if source is None:
-                raise
-            raise ExpressionError(
-                f"invalid CEL expression at {source}: {expression!r}. "
-                f"Check the CEL syntax. Parser details: {e}"
-            ) from e
-
-    @staticmethod
-    def _require_cel_source(value: str, *, source: str | None = None) -> str:
-        expression = value.strip()
-        if expression.startswith("${") and expression.endswith("}"):
-            expression = expression[2:-1].strip()
-        if expression:
-            return expression
-        if source is None:
-            raise ExpressionError("empty CEL expression")
-        raise ExpressionError(
-            f"empty CEL expression at {source}. Provide a CEL expression such as "
-            "state.topic or outputs.step_name."
-        )
-
-    @staticmethod
-    def _collect_root_identifiers(
-        tree: Any, local_roots: frozenset[str] = frozenset()
-    ) -> set[str]:
-        """Collect CEL root identifiers, excluding receiver macro local variables."""
-        data = getattr(tree, "data", None)
-        children = list(getattr(tree, "children", []) or [])
-
-        if data == "ident" and children:
-            name = str(children[0])
-            return set() if name in local_roots else {name}
-
-        if data == "ident_arg":
-            return Expression._collect_root_identifiers_from(
-                children[1:], local_roots=local_roots
-            )
-
-        if data == "member_dot_arg":
-            roots = (
-                Expression._collect_root_identifiers(children[0], local_roots)
-                if children
-                else set()
-            )
-            nested_locals = frozenset(
-                {*local_roots, *Expression._receiver_macro_local_roots(children)}
-            )
-            roots.update(
-                Expression._collect_root_identifiers_from(
-                    children[2:], local_roots=nested_locals
-                )
-            )
-            return roots
-
-        return Expression._collect_root_identifiers_from(
-            children, local_roots=local_roots
-        )
-
-    @staticmethod
-    def _collect_root_identifiers_from(
-        trees: Iterable[Any], *, local_roots: frozenset[str]
-    ) -> set[str]:
-        return set().union(
-            *(Expression._collect_root_identifiers(tree, local_roots) for tree in trees)
-        )
-
-    @staticmethod
-    def _receiver_macro_local_roots(children: list[Any]) -> set[str]:
-        if len(children) < 3 or str(children[1]) not in _CEL_MACROS_WITH_LOCAL_BINDINGS:
-            return set()
-        exprlist = children[2]
-        exprs = list(getattr(exprlist, "children", []) or [])
-        if exprs and (name := Expression._single_identifier_name(exprs[0])):
-            return {name}
-        return set()
-
-    @staticmethod
-    def _single_identifier_name(tree: Any) -> str | None:
-        data = getattr(tree, "data", None)
-        children = list(getattr(tree, "children", []) or [])
-        if data == "ident" and children:
-            return str(children[0])
-        if len(children) != 1:
-            return None
-        return Expression._single_identifier_name(children[0])

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

@@ -12,12 +12,13 @@ from __future__ import annotations
 import json
 import logging
 import re
-from typing import Annotated, Any, Literal, TypeAlias, cast
+from typing import Annotated, Any, Literal as TypingLiteral, TypeAlias
 
 from pydantic import (
     BaseModel,
     ConfigDict,
     Field,
+    RootModel,
     field_serializer,
     model_validator,
 )
@@ -27,21 +28,16 @@ from crewai.flow.conversational_definition import (
     FlowConversationalDefinition,
     FlowConversationalRouterDefinition,
 )
-from crewai.flow.expressions import ExpressionData
-from crewai.project.crew_definition import AgentDefinition, CrewDefinition
+from crewai.project.crew_definition import CrewDefinition
 
 
 logger = logging.getLogger(__name__)
 
 FlowDefinitionCondition = str | dict[str, Any]
 _STEP_NAME_PATTERN = re.compile(r"^[A-Za-z_][A-Za-z0-9_]*$")
-_BASE_CEL_ROOTS = frozenset({"outputs", "state"})
-_EACH_STEP_CEL_ROOTS = frozenset({"item", "outputs", "state"})
 
 __all__ = [
     "FlowActionDefinition",
-    "FlowAgentActionDefinition",
-    "FlowAtomicActionDefinition",
     "FlowCodeActionDefinition",
     "FlowConfigDefinition",
     "FlowConversationalDefinition",
@@ -49,16 +45,16 @@ __all__ = [
     "FlowCrewActionDefinition",
     "FlowDefinition",
     "FlowDefinitionCondition",
+    "FlowDefinitionDiagnostic",
     "FlowDictStateDefinition",
     "FlowEachActionDefinition",
-    "FlowEachStepDefinition",
+    "FlowEachInnerActionDefinition",
     "FlowExpressionActionDefinition",
     "FlowHumanFeedbackDefinition",
     "FlowJsonSchemaStateDefinition",
     "FlowMethodDefinition",
     "FlowPersistenceDefinition",
     "FlowPydanticStateDefinition",
-    "FlowScriptActionDefinition",
     "FlowStateDefinition",
     "FlowToolActionDefinition",
     "FlowUnknownStateDefinition",
@@ -73,12 +69,21 @@ def _object_ref(value: Any) -> str:
     return f"{module}:{qualname}" if module and qualname else repr(value)
 
 
+class FlowDefinitionDiagnostic(BaseModel):
+    """A non-fatal Flow Definition build or validation diagnostic."""
+
+    code: str
+    message: str
+    severity: TypingLiteral["warning", "error"] = "warning"
+    path: str | None = None
+
+
 class FlowDictStateDefinition(BaseModel):
     """Static description of a plain dictionary Flow state contract."""
 
     model_config = ConfigDict(extra="forbid")
 
-    type: Literal["dict"] = Field(
+    type: TypingLiteral["dict"] = Field(
         default="dict",
         description="Plain dictionary state with optional default values.",
         examples=["dict"],
@@ -95,7 +100,7 @@ class FlowPydanticStateDefinition(BaseModel):
 
     model_config = ConfigDict(extra="forbid")
 
-    type: Literal["pydantic"] = Field(
+    type: TypingLiteral["pydantic"] = Field(
         default="pydantic",
         description="Importable Pydantic model used as the Flow state type.",
         examples=["pydantic"],
@@ -130,7 +135,7 @@ class FlowJsonSchemaStateDefinition(BaseModel):
 
     model_config = ConfigDict(extra="forbid")
 
-    type: Literal["json_schema"] = Field(
+    type: TypingLiteral["json_schema"] = Field(
         default="json_schema",
         description="Inline JSON Schema used as the Flow state contract.",
         examples=["json_schema"],
@@ -157,7 +162,7 @@ class FlowUnknownStateDefinition(BaseModel):
 
     model_config = ConfigDict(extra="forbid")
 
-    type: Literal["unknown"] = Field(
+    type: TypingLiteral["unknown"] = Field(
         default="unknown",
         description="Unknown state representation; runtime falls back to dictionary state.",
         examples=["unknown"],
@@ -186,46 +191,14 @@ FlowStateDefinition: TypeAlias = Annotated[
 class FlowConfigDefinition(BaseModel):
     """Serializable Flow-level configuration."""
 
-    tracing: bool | None = Field(
-        default=None,
-        description="Override for flow tracing; when omitted, runtime defaults apply.",
-        examples=[True],
-    )
-    stream: bool = Field(
-        default=False,
-        description="Whether the flow should emit streaming events when supported.",
-        examples=[True],
-    )
-    memory: dict[str, Any] | None = Field(
-        default=None,
-        description="Serializable memory configuration passed to flow execution.",
-        examples=[{"enabled": True}],
-    )
-    input_provider: str | None = Field(
-        default=None,
-        description="Import reference or provider key used to supply flow inputs.",
-        examples=["my_project.inputs:load_inputs"],
-    )
-    suppress_flow_events: bool = Field(
-        default=False,
-        description="Disable flow event emission for this definition.",
-        examples=[False],
-    )
-    max_method_calls: int = Field(
-        default=100,
-        description="Maximum number of method executions allowed during one kickoff.",
-        examples=[20],
-    )
-    defer_trace_finalization: bool = Field(
-        default=False,
-        description="Defer trace finalization so callers can complete tracing later.",
-        examples=[False],
-    )
-    checkpoint: bool | dict[str, Any] | None = Field(
-        default=None,
-        description="Checkpointing configuration, or true to use default checkpointing.",
-        examples=[True, {"enabled": True}],
-    )
+    tracing: bool | None = None
+    stream: bool = False
+    memory: dict[str, Any] | None = None
+    input_provider: str | None = None
+    suppress_flow_events: bool = False
+    max_method_calls: int = 100
+    defer_trace_finalization: bool = False
+    checkpoint: bool | dict[str, Any] | None = None
 
 
 class FlowPersistenceDefinition(BaseModel):
@@ -237,21 +210,9 @@ class FlowPersistenceDefinition(BaseModel):
     serialized config.
     """
 
-    enabled: bool = Field(
-        default=False,
-        description="Whether persistence is enabled for this flow or method.",
-        examples=[True],
-    )
-    verbose: bool = Field(
-        default=False,
-        description="Whether persistence should emit verbose diagnostic output.",
-        examples=[False],
-    )
-    persistence: Any = Field(
-        default=None,
-        description="Persistence backend configuration or import reference.",
-        examples=[{"ref": "my_project.persistence:FlowStore"}],
-    )
+    enabled: bool = False
+    verbose: bool = False
+    persistence: Any = None
 
     @field_serializer("persistence", when_used="json")
     def _serialize_persistence(self, value: Any) -> Any:
@@ -277,53 +238,15 @@ class FlowHumanFeedbackDefinition(BaseModel):
     a serialized config (``llm``) or a ``module:qualname`` ref (``provider``).
     """
 
-    message: str = Field(
-        description="Prompt shown to the human reviewer when feedback is requested.",
-        examples=["Review the research summary before publishing."],
-    )
-    emit: list[str] | None = Field(
-        default=None,
-        description=(
-            "Allowed feedback outcomes. When set, the method routes like a router "
-            "using the selected outcome."
-        ),
-        examples=[["approved", "revise"]],
-    )
-    llm: Any = Field(
-        default="gpt-4o-mini",
-        description="LLM configuration used to assist or process human feedback.",
-        examples=["gpt-4o-mini"],
-    )
-    default_outcome: str | None = Field(
-        default=None,
-        description="Outcome to use when feedback cannot be collected.",
-        examples=["revise"],
-    )
-    metadata: dict[str, Any] | None = Field(
-        default=None,
-        description="Serializable metadata attached to the feedback request.",
-        examples=[{"team": "research"}],
-    )
-    provider: Any = Field(
-        default=None,
-        description="Feedback provider configuration or import reference.",
-        examples=["my_project.feedback:provider"],
-    )
-    learn: bool = Field(
-        default=False,
-        description="Whether feedback should be recorded for later learning workflows.",
-        examples=[True],
-    )
-    learn_source: str = Field(
-        default="hitl",
-        description="Source label attached to learned feedback records.",
-        examples=["hitl"],
-    )
-    learn_strict: bool = Field(
-        default=False,
-        description="Whether learning should enforce strict validation of feedback data.",
-        examples=[False],
-    )
+    message: str
+    emit: list[str] | None = None
+    llm: Any = "gpt-4o-mini"
+    default_outcome: str | None = None
+    metadata: dict[str, Any] | None = None
+    provider: Any = None
+    learn: bool = False
+    learn_source: str = "hitl"
+    learn_strict: bool = False
 
     @field_serializer("llm", when_used="json")
     def _serialize_llm(self, value: Any) -> dict[str, Any] | str | None:
@@ -343,124 +266,30 @@ class FlowHumanFeedbackDefinition(BaseModel):
 class FlowCodeActionDefinition(BaseModel):
     """A Flow method action that executes importable Python code."""
 
-    model_config = ConfigDict(
-        populate_by_name=True,
-        extra="forbid",
-    )
+    model_config = ConfigDict(populate_by_name=True, extra="forbid")
 
-    call: Literal["code"] = Field(
-        default="code",
-        description="Action discriminator. Use code to call importable Python.",
-        examples=["code"],
-    )
-    ref: str = Field(
-        description="Import reference for the callable, formatted as module:qualname.",
-        examples=["my_project.flows:normalize_topic"],
-    )
-    with_: dict[str, ExpressionData] | None = Field(
-        default=None,
-        alias="with",
-        description=(
-            "Keyword arguments passed to the callable. String values are evaluated "
-            "as CEL only when the trimmed value starts with ${ and ends with }; "
-            "all other values are literal."
-        ),
-        examples=[{"topic": "${state.topic}"}],
-    )
+    call: TypingLiteral["code"] = "code"
+    ref: str
+    with_: dict[str, Any] | None = Field(default=None, alias="with")
 
 
 class FlowToolActionDefinition(BaseModel):
     """A Flow method action that invokes a CrewAI tool."""
 
-    model_config = ConfigDict(
-        populate_by_name=True,
-        extra="forbid",
-    )
+    model_config = ConfigDict(populate_by_name=True, extra="forbid")
 
-    call: Literal["tool"] = Field(
-        description="Action discriminator. Use tool to instantiate and run a CrewAI tool.",
-        examples=["tool"],
-    )
-    ref: str = Field(
-        description="Import reference for a BaseTool class, formatted as module:qualname.",
-        examples=["my_project.tools:SearchTool"],
-    )
-    with_: dict[str, ExpressionData] | None = Field(
-        default=None,
-        alias="with",
-        description=(
-            "Tool input arguments. String values are evaluated as CEL only when "
-            "the trimmed value starts with ${ and ends with }; all other values "
-            "are literal."
-        ),
-        examples=[{"query": "${outputs.normalize_topic}", "limit": 5}],
-    )
+    call: TypingLiteral["tool"]
+    ref: str
+    with_: dict[str, Any] | None = Field(default=None, alias="with")
 
 
 class FlowCrewActionDefinition(BaseModel):
     """A Flow method action that builds and kicks off a CrewAI crew."""
 
-    model_config = ConfigDict(
-        populate_by_name=True,
-        extra="forbid",
-    )
+    model_config = ConfigDict(populate_by_name=True, extra="forbid")
 
-    call: Literal["crew"] = Field(
-        description="Action discriminator. Use crew to run an inline Crew definition.",
-        examples=["crew"],
-    )
-    with_: CrewDefinition = Field(
-        alias="with",
-        description="Inline Crew definition to load and execute for this action.",
-        examples=[
-            {
-                "name": "inline_research",
-                "agents": {
-                    "researcher": {
-                        "role": "Researcher",
-                        "goal": "Research {topic}",
-                        "backstory": "Knows the domain.",
-                    }
-                },
-                "tasks": [
-                    {
-                        "name": "research_task",
-                        "description": "Research {topic}",
-                        "expected_output": "Findings about {topic}",
-                        "agent": "researcher",
-                    }
-                ],
-                "inputs": {"topic": "${state.topic}"},
-            }
-        ],
-    )
-
-
-class FlowAgentActionDefinition(BaseModel):
-    """A Flow method action that builds and kicks off a CrewAI agent."""
-
-    model_config = ConfigDict(
-        populate_by_name=True,
-        extra="forbid",
-    )
-
-    call: Literal["agent"] = Field(
-        description="Action discriminator. Use agent to run an inline Agent definition.",
-        examples=["agent"],
-    )
-    with_: AgentDefinition = Field(
-        alias="with",
-        description="Inline Agent definition to load and execute for this action.",
-        examples=[
-            {
-                "role": "Analyst",
-                "goal": "Answer user questions",
-                "backstory": "Precise and concise.",
-                "settings": {"llm": "openai/gpt-4o-mini"},
-                "input": "${state.question}",
-            }
-        ],
-    )
+    call: TypingLiteral["crew"]
+    with_: CrewDefinition = Field(alias="with")
 
 
 class FlowExpressionActionDefinition(BaseModel):
@@ -468,143 +297,66 @@ class FlowExpressionActionDefinition(BaseModel):
 
     model_config = ConfigDict(extra="forbid")
 
-    call: Literal["expression"] = Field(
-        description="Action discriminator. Use expression to evaluate a CEL expression.",
-        examples=["expression"],
-    )
-    expr: str = Field(
-        description="CEL expression evaluated against state, outputs, and local context.",
-        examples=["state.topic", "outputs.normalize_topic"],
-    )
+    call: TypingLiteral["expression"]
+    expr: str
 
 
-class FlowScriptActionDefinition(BaseModel):
-    """A Flow method action that executes trusted inline Python."""
-
-    model_config = ConfigDict(extra="forbid")
-
-    call: Literal["script"] = Field(
-        description="Action discriminator. Use script to execute trusted inline Python.",
-        examples=["script"],
-    )
-    code: str = Field(
-        description=(
-            "Trusted Python source executed as a generated function. Runtime values are "
-            "passed as state, outputs, input, and item; they are not interpolated into "
-            "the source. This is not sandboxed."
-        ),
-        examples=[
-            "state['normalized_topic'] = input.strip()\n"
-            "return state['normalized_topic']"
-        ],
-    )
-    language: Literal["python"] = Field(
-        default="python",
-        description="Script language. Only python is currently supported.",
-        examples=["python"],
-    )
-
-
-FlowAtomicActionDefinition: TypeAlias = Annotated[
+FlowInnerActionDefinition = (
     FlowCodeActionDefinition
     | FlowToolActionDefinition
     | FlowCrewActionDefinition
-    | FlowAgentActionDefinition
     | FlowExpressionActionDefinition
-    | FlowScriptActionDefinition,
-    Field(discriminator="call"),
-]
+)
 
 
-class FlowEachStepDefinition(BaseModel):
-    """One named step inside an ``each`` composite action."""
-
-    model_config = ConfigDict(
-        populate_by_name=True,
-        extra="forbid",
-    )
-
-    name: str = Field(
-        description="Step name used to reference this step's output.",
-        examples=["clean"],
-    )
-    if_: str | None = Field(
-        default=None,
-        alias="if",
-        description=(
-            "Optional CEL expression evaluated against state, outputs, and local "
-            "context. When present, the step runs only if the expression evaluates "
-            "to true."
-        ),
-        examples=["item.kind == 'invoice'"],
-    )
-    action: FlowAtomicActionDefinition = Field(
-        description="Atomic action to run for this step.",
-        examples=[{"call": "script", "code": "return item.strip()"}],
-    )
+class FlowEachInnerActionDefinition(RootModel[dict[str, FlowInnerActionDefinition]]):
+    """One named action inside an ``each`` composite action."""
 
     @model_validator(mode="after")
-    def _validate_step_name(self) -> FlowEachStepDefinition:
-        _validate_step_name(self.name, field="each.do step names")
+    def _validate_action_mapping(self) -> FlowEachInnerActionDefinition:
+        if len(self.root) != 1:
+            raise ValueError("each.do entries must be one-key mappings")
+        _validate_step_name(self.name, field="each.do action names")
         return self
 
+    @property
+    def name(self) -> str:
+        return next(iter(self.root))
+
+    @property
+    def action(self) -> FlowInnerActionDefinition:
+        return next(iter(self.root.values()))
+
 
 class FlowEachActionDefinition(BaseModel):
     """A composite action that runs a sequential mini-pipeline for each item."""
 
-    model_config = ConfigDict(
-        populate_by_name=True,
-        extra="forbid",
-    )
+    model_config = ConfigDict(populate_by_name=True, extra="forbid")
 
-    call: Literal["each"] = Field(
-        description=(
-            "Action discriminator. Use each to run a sequence of actions for every "
-            "item in an input list."
-        ),
-        examples=["each"],
-    )
-    in_: str = Field(
-        alias="in",
-        description="CEL expression that must evaluate to the list to iterate.",
-        examples=["state.rows"],
-    )
-    do: list[FlowEachStepDefinition] = Field(
-        description=(
-            "Ordered steps to run for each item. Each step has a name, optional "
-            "if expression, and atomic action."
-        ),
-        examples=[
-            [
-                {
-                    "name": "clean",
-                    "action": {"call": "script", "code": "return item.strip()"},
-                },
-                {
-                    "name": "tag",
-                    "if": "outputs.clean != ''",
-                    "action": {"call": "expression", "expr": "outputs.clean"},
-                },
-            ]
-        ],
-    )
+    call: TypingLiteral["each"]
+    in_: str = Field(alias="in")
+    do: list[FlowEachInnerActionDefinition]
 
     @model_validator(mode="after")
-    def _validate_step_list(self) -> FlowEachActionDefinition:
+    def _validate_inner_action_list(self) -> FlowEachActionDefinition:
         if not self.do:
-            raise ValueError("each.do must contain at least one step")
+            raise ValueError("each.do must contain at least one action")
+
+        seen: set[str] = set()
+        for inner_action in self.do:
+            name = inner_action.name
+            if name in seen:
+                raise ValueError(f"each.do action names must be unique: {name!r}")
+            seen.add(name)
 
-        _validate_step_list(self.do, field="each.do")
         return self
 
 
-FlowActionDefinition: TypeAlias = (
+FlowActionDefinition = (
     FlowCodeActionDefinition
     | FlowToolActionDefinition
     | FlowCrewActionDefinition
-    | FlowAgentActionDefinition
     | FlowExpressionActionDefinition
-    | FlowScriptActionDefinition
     | FlowEachActionDefinition
 )
 
@@ -612,48 +364,14 @@ FlowActionDefinition: TypeAlias = (
 class FlowMethodDefinition(BaseModel):
     """Static definition of one Flow method and its execution roles."""
 
-    description: str | None = Field(
-        default=None,
-        description="Human-readable summary of what this method does.",
-        examples=["Normalize the incoming topic."],
-    )
-    do: FlowActionDefinition = Field(
-        description="Action executed when this method runs.",
-        examples=[{"call": "script", "code": "return input.strip()"}],
-    )
-    start: bool | FlowDefinitionCondition | None = Field(
-        default=None,
-        description=(
-            "Marks a start method. True starts unconditionally; a condition starts "
-            "when the kickoff inputs or events satisfy it."
-        ),
-        examples=[True],
-    )
-    listen: FlowDefinitionCondition | None = Field(
-        default=None,
-        description="Trigger condition that runs this method after upstream events.",
-        examples=["seed", {"or": ["approved", "revise"]}],
-    )
-    router: bool = Field(
-        default=False,
-        description="Whether the method output should be treated as the next event name.",
-        examples=[True],
-    )
-    emit: list[str] | None = Field(
-        default=None,
-        description="Declared router events this method may emit.",
-        examples=[["approved", "revise"]],
-    )
-    human_feedback: FlowHumanFeedbackDefinition | None = Field(
-        default=None,
-        description="Optional human feedback step applied after the method action.",
-        examples=[{"message": "Review the research summary before publishing."}],
-    )
-    persist: FlowPersistenceDefinition | None = Field(
-        default=None,
-        description="Method-level persistence override.",
-        examples=[{"enabled": True}],
-    )
+    description: str | None = None
+    do: FlowActionDefinition
+    start: bool | FlowDefinitionCondition | None = None
+    listen: FlowDefinitionCondition | None = None
+    router: bool = False
+    emit: list[str] | None = None
+    human_feedback: FlowHumanFeedbackDefinition | None = None
+    persist: FlowPersistenceDefinition | None = None
 
     @model_validator(mode="after")
     def _canonicalize_human_feedback_routing(self) -> FlowMethodDefinition:
@@ -679,57 +397,19 @@ class FlowMethodDefinition(BaseModel):
 class FlowDefinition(BaseModel):
     """Static, serializable definition of a Flow."""
 
-    model_config = ConfigDict(
-        populate_by_name=True,
-        arbitrary_types_allowed=True,
-    )
+    model_config = ConfigDict(populate_by_name=True, arbitrary_types_allowed=True)
 
-    schema_: Literal["crewai.flow/v1"] = Field(
-        default="crewai.flow/v1",
-        alias="schema",
-        description="Flow Definition schema identifier and version.",
-        examples=["crewai.flow/v1"],
-    )
-    name: str = Field(
-        description="Unique flow name used in logs, events, and traces.",
-        examples=["ResearchFlow"],
-    )
-    description: str | None = Field(
-        default=None,
-        description="Human-readable summary of the flow.",
-        examples=["Normalize a topic and prepare it for research."],
-    )
-    state: FlowStateDefinition | None = Field(
-        default=None,
-        description="State contract for kickoff inputs and runtime state.",
-        examples=[{"type": "dict", "default": {"topic": "AI agents"}}],
-    )
-    config: FlowConfigDefinition = Field(
-        default_factory=FlowConfigDefinition,
-        description="Serializable flow-level runtime configuration.",
-        examples=[{"stream": True, "max_method_calls": 20}],
-    )
-    persist: FlowPersistenceDefinition | None = Field(
-        default=None,
-        description="Flow-level persistence configuration.",
-        examples=[{"enabled": True}],
-    )
-    conversational: FlowConversationalDefinition | None = Field(
-        default=None,
-        description="Conversational flow configuration, when the flow supports chat.",
-    )
-    methods: dict[str, FlowMethodDefinition] = Field(
-        default_factory=dict,
-        description="Mapping of method names to method definitions.",
-        examples=[
-            {
-                "seed": {
-                    "start": True,
-                    "do": {"call": "expression", "expr": "state.topic"},
-                }
-            }
-        ],
+    schema_: TypingLiteral["crewai.flow/v1"] = Field(
+        default="crewai.flow/v1", alias="schema"
     )
+    name: str
+    description: str | None = None
+    state: FlowStateDefinition | None = None
+    config: FlowConfigDefinition = Field(default_factory=FlowConfigDefinition)
+    persist: FlowPersistenceDefinition | None = None
+    conversational: FlowConversationalDefinition | None = None
+    methods: dict[str, FlowMethodDefinition] = Field(default_factory=dict)
+    diagnostics: list[FlowDefinitionDiagnostic] = Field(default_factory=list)
 
     @model_validator(mode="after")
     def _validate_method_names(self) -> FlowDefinition:
@@ -737,16 +417,6 @@ class FlowDefinition(BaseModel):
             _validate_step_name(method_name, field="Flow method names")
         return self
 
-    @model_validator(mode="after")
-    def _validate_cel_expressions(self) -> FlowDefinition:
-        for method_name, method in self.methods.items():
-            _validate_action_cel(
-                method.do,
-                path=f"methods.{method_name}.do",
-                allowed_roots=_BASE_CEL_ROOTS,
-            )
-        return self
-
     def to_dict(self, *, exclude_none: bool = True) -> dict[str, Any]:
         """Serialize the definition to a JSON/YAML-ready dictionary."""
         return self.model_dump(by_alias=True, exclude_none=exclude_none, mode="json")
@@ -766,9 +436,13 @@ class FlowDefinition(BaseModel):
 
     @classmethod
     def from_dict(cls, data: dict[str, Any]) -> FlowDefinition:
-        """Load a definition from a dictionary."""
+        """Load a definition from a dictionary and attach diagnostics."""
+        serialized_diagnostics = _deserialize_diagnostics(data.get("diagnostics", []))
         definition = cls.model_validate(data)
-        log_flow_definition_issues(definition)
+        definition.diagnostics = _merge_diagnostics(
+            serialized_diagnostics, definition.validate_contract()
+        )
+        definition.log_diagnostics()
         return definition
 
     @classmethod
@@ -789,153 +463,122 @@ class FlowDefinition(BaseModel):
         """Return the JSON Schema for the Flow Definition contract."""
         return cls.model_json_schema(by_alias=True)
 
+    def validate_contract(self) -> list[FlowDefinitionDiagnostic]:
+        """Validate the static contract without rejecting dynamic routing."""
+        diagnostics: list[FlowDefinitionDiagnostic] = []
+        for method_name, method in self.methods.items():
+            path = f"methods.{method_name}"
+            if method.router and not method.is_start and method.listen is None:
+                diagnostics.append(
+                    FlowDefinitionDiagnostic(
+                        code="router_without_trigger",
+                        severity="error",
+                        path=path,
+                        message="router: true requires either start or listen",
+                    )
+                )
+            if method.emit and not method.router:
+                diagnostics.append(
+                    FlowDefinitionDiagnostic(
+                        code="emit_without_router",
+                        path=f"{path}.emit",
+                        message="emit is only used by routers to declare downstream events",
+                    )
+                )
+            if method.human_feedback:
+                human_feedback_config = method.human_feedback
+                if human_feedback_config.emit and not human_feedback_config.llm:
+                    diagnostics.append(
+                        FlowDefinitionDiagnostic(
+                            code="human_feedback_llm_required",
+                            severity="error",
+                            path=f"{path}.human_feedback.llm",
+                            message="llm is required when human_feedback.emit is set",
+                        )
+                    )
+                if (
+                    human_feedback_config.default_outcome is not None
+                    and not human_feedback_config.emit
+                ):
+                    diagnostics.append(
+                        FlowDefinitionDiagnostic(
+                            code="human_feedback_default_requires_emit",
+                            severity="error",
+                            path=f"{path}.human_feedback.default_outcome",
+                            message="default_outcome requires human_feedback.emit",
+                        )
+                    )
+                elif (
+                    human_feedback_config.default_outcome is not None
+                    and human_feedback_config.emit
+                ):
+                    if (
+                        human_feedback_config.default_outcome
+                        not in human_feedback_config.emit
+                    ):
+                        diagnostics.append(
+                            FlowDefinitionDiagnostic(
+                                code="human_feedback_default_not_in_emit",
+                                severity="error",
+                                path=f"{path}.human_feedback.default_outcome",
+                                message="default_outcome must be one of human_feedback.emit",
+                            )
+                        )
+
+        return diagnostics
+
+    def with_diagnostics(self) -> FlowDefinition:
+        """Attach fresh diagnostics and return this definition."""
+        self.diagnostics = self.validate_contract()
+        self.log_diagnostics()
+        return self
+
+    def log_diagnostics(self) -> None:
+        """Emit all attached diagnostics through the flow definition logger."""
+        _log_flow_definition_diagnostics(self.name, self.diagnostics)
+
+
+def _log_flow_definition_diagnostics(
+    definition_name: str,
+    diagnostics: list[FlowDefinitionDiagnostic],
+) -> None:
+    for diagnostic in diagnostics:
+        level = logging.ERROR if diagnostic.severity == "error" else logging.WARNING
+        path = f" at {diagnostic.path}" if diagnostic.path else ""
+        logger.log(
+            level,
+            "Flow definition diagnostic for %s%s [%s]: %s",
+            definition_name,
+            path,
+            diagnostic.code,
+            diagnostic.message,
+        )
+
+
+def _deserialize_diagnostics(value: Any) -> list[FlowDefinitionDiagnostic]:
+    return [FlowDefinitionDiagnostic.model_validate(item) for item in value or []]
+
 
 def _validate_step_name(name: str, *, field: str) -> None:
     if not isinstance(name, str) or not _STEP_NAME_PATTERN.fullmatch(name):
         raise ValueError(f"{field} must match {_STEP_NAME_PATTERN.pattern}")
 
 
-def _validate_step_list(steps: list[FlowEachStepDefinition], *, field: str) -> None:
-    seen: set[str] = set()
-    for step in steps:
-        name = step.name
-        if name in seen:
-            raise ValueError(f"{field} step names must be unique: {name!r}")
-        seen.add(name)
-
-
-def _validate_action_cel(
-    action: FlowActionDefinition,
-    *,
-    path: str,
-    allowed_roots: frozenset[str],
-) -> None:
-    from crewai.flow.expressions import Expression
-
-    if isinstance(action, FlowExpressionActionDefinition):
-        Expression(action.expr).validate_expression(
-            allowed_roots=allowed_roots, source=f"{path}.expr"
-        )
-        return
-
-    if isinstance(action, (FlowCodeActionDefinition, FlowToolActionDefinition)):
-        if action.with_ is not None:
-            Expression(action.with_).validate_template(
-                allowed_roots=allowed_roots, source=f"{path}.with"
+def _merge_diagnostics(
+    *diagnostic_groups: list[FlowDefinitionDiagnostic],
+) -> list[FlowDefinitionDiagnostic]:
+    diagnostics: list[FlowDefinitionDiagnostic] = []
+    seen: set[tuple[str, str, str | None, str]] = set()
+    for group in diagnostic_groups:
+        for diagnostic in group:
+            key = (
+                diagnostic.code,
+                diagnostic.severity,
+                diagnostic.path,
+                diagnostic.message,
             )
-        return
-
-    if isinstance(action, FlowCrewActionDefinition):
-        Expression(cast(ExpressionData, action.with_.inputs)).validate_template(
-            allowed_roots=allowed_roots,
-            source=f"{path}.with.inputs",
-        )
-        return
-
-    if isinstance(action, FlowAgentActionDefinition):
-        Expression(cast(ExpressionData, action.with_.input)).validate_template(
-            allowed_roots=allowed_roots,
-            source=f"{path}.with.input",
-        )
-        return
-
-    if isinstance(action, FlowEachActionDefinition):
-        Expression(action.in_).validate_expression(
-            allowed_roots=_BASE_CEL_ROOTS,
-            source=f"{path}.in",
-        )
-        for index, step in enumerate(action.do):
-            step_path = f"{path}.do[{index}]"
-            if step.if_ is not None:
-                Expression(step.if_).validate_expression(
-                    allowed_roots=_EACH_STEP_CEL_ROOTS,
-                    source=f"{step_path}.if",
-                )
-            _validate_action_cel(
-                step.action,
-                path=f"{step_path}.action",
-                allowed_roots=_EACH_STEP_CEL_ROOTS,
-            )
-        return
-
-    if isinstance(action, FlowScriptActionDefinition):
-        return
-
-    raise TypeError(
-        f"no CEL validation defined for action type {type(action).__name__} at "
-        f"{path}; add a branch to _validate_action_cel for it."
-    )
-
-
-def log_flow_definition_issues(definition: FlowDefinition) -> None:
-    for method_name, method in definition.methods.items():
-        path = f"methods.{method_name}"
-        if method.router and not method.is_start and method.listen is None:
-            _log_flow_definition_issue(
-                definition.name,
-                code="router_without_trigger",
-                severity="error",
-                path=path,
-                message="router: true requires either start or listen",
-            )
-        if method.emit and not method.router:
-            _log_flow_definition_issue(
-                definition.name,
-                code="emit_without_router",
-                path=f"{path}.emit",
-                message="emit is only used by routers to declare downstream events",
-            )
-        if method.human_feedback:
-            human_feedback_config = method.human_feedback
-            if human_feedback_config.emit and not human_feedback_config.llm:
-                _log_flow_definition_issue(
-                    definition.name,
-                    code="human_feedback_llm_required",
-                    severity="error",
-                    path=f"{path}.human_feedback.llm",
-                    message="llm is required when human_feedback.emit is set",
-                )
-            if (
-                human_feedback_config.default_outcome is not None
-                and not human_feedback_config.emit
-            ):
-                _log_flow_definition_issue(
-                    definition.name,
-                    code="human_feedback_default_requires_emit",
-                    severity="error",
-                    path=f"{path}.human_feedback.default_outcome",
-                    message="default_outcome requires human_feedback.emit",
-                )
-            elif (
-                human_feedback_config.default_outcome is not None
-                and human_feedback_config.emit
-                and human_feedback_config.default_outcome
-                not in human_feedback_config.emit
-            ):
-                _log_flow_definition_issue(
-                    definition.name,
-                    code="human_feedback_default_not_in_emit",
-                    severity="error",
-                    path=f"{path}.human_feedback.default_outcome",
-                    message="default_outcome must be one of human_feedback.emit",
-                )
-
-
-def _log_flow_definition_issue(
-    definition_name: str,
-    *,
-    code: str,
-    message: str,
-    severity: Literal["warning", "error"] = "warning",
-    path: str | None = None,
-) -> None:
-    level = logging.ERROR if severity == "error" else logging.WARNING
-    location = f" at {path}" if path else ""
-    logger.log(
-        level,
-        "Flow definition issue for %s%s [%s]: %s",
-        definition_name,
-        location,
-        code,
-        message,
-    )
+            if key in seen:
+                continue
+            seen.add(key)
+            diagnostics.append(diagnostic)
+    return diagnostics

lib/crewai/src/crewai/flow/runtime/__init__.py

@@ -121,7 +121,7 @@ from crewai.flow.human_feedback import (
 )
 from crewai.flow.input_provider import InputProvider
 from crewai.flow.persistence.base import FlowPersistence
-from crewai.flow.runtime._actions import FlowScriptExecutionDisabledError, build_action
+from crewai.flow.runtime._actions import build_action
 from crewai.flow.runtime._refs import resolve_instance_ref, resolve_ref
 from crewai.flow.types import (
     FlowExecutionData,
@@ -1090,8 +1090,6 @@ class Flow(BaseModel, Generic[T], metaclass=FlowMeta):
         def build(name: str, definition: FlowMethodDefinition) -> Callable[..., Any]:
             try:
                 return build_action(self, definition.do)
-            except FlowScriptExecutionDisabledError:
-                raise
             except Exception as e:
                 unresolved.append(f"{name}: {e}")
                 return lambda *args, **kwargs: None

lib/crewai/src/crewai/flow/runtime/_actions.py

@@ -2,27 +2,22 @@
 
 from __future__ import annotations
 
-import ast
 import asyncio
-from collections.abc import Awaitable, Callable
+from collections.abc import Callable
 import contextvars
 import inspect
-import os
 from typing import TYPE_CHECKING, Any, Protocol, cast
 
-from crewai.flow.expressions import Expression, ExpressionData
 from crewai.flow.flow_definition import (
     FlowActionDefinition,
-    FlowAgentActionDefinition,
     FlowCodeActionDefinition,
     FlowCrewActionDefinition,
     FlowEachActionDefinition,
-    FlowEachStepDefinition,
+    FlowEachInnerActionDefinition,
     FlowExpressionActionDefinition,
-    FlowScriptActionDefinition,
     FlowToolActionDefinition,
 )
-from crewai.flow.runtime._outputs import outputs_by_name
+from crewai.flow.runtime._expressions import evaluate_expression, render_with_block
 from crewai.flow.runtime._refs import InvalidRefError, resolve_ref
 
 
@@ -30,18 +25,10 @@ if TYPE_CHECKING:
     from crewai.flow.runtime import Flow
 
 
-__all__ = ["FlowScriptExecutionDisabledError", "build_action"]
+__all__ = ["build_action"]
 
 LocalContext = dict[str, Any]
-NestedStepRunner = Callable[[LocalContext], Awaitable[Any]]
-NestedStep = tuple[str, str | None, NestedStepRunner]
 _LOCAL_CONTEXT_KWARG = "__flow_definition_local_context"
-_ALLOW_SCRIPT_EXECUTION_ENV_VAR = "CREWAI_ALLOW_FLOW_SCRIPT_EXECUTION"
-_TRUSTED_SCRIPT_EXECUTION_VALUES = frozenset({"1", "true", "yes"})
-
-
-class FlowScriptExecutionDisabledError(RuntimeError):
-    """Raised when a flow definition tries to execute inline script code."""
 
 
 class _BuiltAction(Protocol):
@@ -68,9 +55,9 @@ class CodeAction:
         if self.definition.with_ is None:
             return self.handler(*args, **kwargs)
         return self.handler(
-            **Expression.from_flow(
-                self.definition.with_, self.flow, local_context=local_context
-            ).render_template()
+            **render_with_block(
+                self.flow, self.definition.with_, local_context=local_context
+            )
         )
 
     def _resolve_handler(self) -> Callable[..., Any]:
@@ -96,9 +83,7 @@ class ToolAction:
     def run(self, *_args: Any, **kwargs: Any) -> Any:
         local_context = _pop_local_context(kwargs)
         return self.tool.run(
-            **Expression.from_flow(
-                self.kwargs, self.flow, local_context=local_context
-            ).render_template()
+            **render_with_block(self.flow, self.kwargs, local_context=local_context)
         )
 
     def _build_tool(self) -> Any:
@@ -132,44 +117,13 @@ class CrewAction:
 
         local_context = _pop_local_context(kwargs)
         crew_definition = self.definition.with_
-        inputs = Expression.from_flow(
-            cast(ExpressionData, crew_definition.inputs),
-            self.flow,
-            local_context=local_context,
-        ).render_template()
+        inputs = render_with_block(
+            self.flow, crew_definition.inputs, local_context=local_context
+        )
         crew, _ = load_crew_from_definition(crew_definition, source="crew action")
         return await crew.kickoff_async(inputs=inputs)
 
 
-class AgentAction:
-    definition_type = FlowAgentActionDefinition
-
-    def __init__(self, flow: Flow[Any], definition: FlowAgentActionDefinition) -> None:
-        self.flow = flow
-        self.definition = definition
-
-    async def run(self, *_args: Any, **kwargs: Any) -> Any:
-        from crewai.project.json_loader import load_agent_from_definition
-
-        local_context = _pop_local_context(kwargs)
-        rendered_input = Expression.from_flow(
-            cast(ExpressionData, self.definition.with_.input),
-            self.flow,
-            local_context=local_context,
-        ).render_template()
-        if not isinstance(rendered_input, str):
-            raise ValueError("agent input must render to a string")
-
-        agent, response_format = load_agent_from_definition(
-            self.definition.with_,
-            source="agent action",
-        )
-        return await agent.kickoff_async(
-            rendered_input,
-            response_format=response_format,
-        )
-
-
 class ExpressionAction:
     definition_type = FlowExpressionActionDefinition
 
@@ -181,71 +135,10 @@ class ExpressionAction:
 
     def run(self, *_args: Any, **kwargs: Any) -> Any:
         local_context = _pop_local_context(kwargs)
-        return Expression.from_flow(
-            self.definition.expr, self.flow, local_context=local_context
-        ).evaluate()
-
-
-class ScriptAction:
-    definition_type = FlowScriptActionDefinition
-
-    def __init__(self, flow: Flow[Any], definition: FlowScriptActionDefinition) -> None:
-        self.flow = flow
-        self.definition = definition
-        self.handler = self._compile_handler()
-
-    def run(self, *args: Any, **kwargs: Any) -> Any:
-        local_context = _pop_local_context(kwargs)
-        return self.handler(
-            state=self.flow.state,
-            outputs=outputs_by_name(
-                self.flow._method_outputs,
-                local_outputs=local_context.get("outputs") if local_context else None,
-            ),
-            input=args[0] if args else None,
-            item=local_context.get("item") if local_context else None,
+        return evaluate_expression(
+            self.flow, self.definition.expr, local_context=local_context
         )
 
-    def _compile_handler(self) -> Callable[..., Any]:
-        raw = os.environ.get(_ALLOW_SCRIPT_EXECUTION_ENV_VAR, "")
-        if raw.strip().lower() not in _TRUSTED_SCRIPT_EXECUTION_VALUES:
-            raise FlowScriptExecutionDisabledError(
-                "Flow script execution is disabled by default. "
-                f"Set {_ALLOW_SCRIPT_EXECUTION_ENV_VAR}=1 to enable it only for "
-                "trusted flow definitions."
-            )
-
-        filename = f"crewai.flow.script.{self.flow._definition.name}"
-        module = ast.parse(self.definition.code, filename=filename)
-        function = ast.FunctionDef(
-            name="_flow_script",
-            args=ast.arguments(
-                posonlyargs=[],
-                args=[ast.arg(arg) for arg in ("state", "outputs", "input", "item")],
-                vararg=None,
-                kwonlyargs=[],
-                kw_defaults=[],
-                kwarg=None,
-                defaults=[],
-            ),
-            body=module.body or [ast.Pass()],
-            decorator_list=[],
-            returns=None,
-            type_comment=None,
-            type_params=[],
-        )
-        module.body = [function]
-        ast.fix_missing_locations(module)
-
-        # The YAML here is trusted project source authored by the code owner,
-        # so this has the same trust boundary as using custom tools. We
-        # intentionally do not interpolate user input and runtime values are passed
-        # as function arguments. This is still arbitrary trusted Python execution,
-        # so it remains disabled by default behind `CREWAI_ALLOW_FLOW_SCRIPT_EXECUTION`
-        namespace: dict[str, Any] = {"__name__": filename}
-        exec(compile(module, filename, "exec"), namespace)  # nosec B102 # noqa: S102
-        return cast(Callable[..., Any], namespace["_flow_script"])
-
 
 class EachAction:
     definition_type = FlowEachActionDefinition
@@ -253,13 +146,13 @@ class EachAction:
     def __init__(self, flow: Flow[Any], definition: FlowEachActionDefinition) -> None:
         self.flow = flow
         self.definition = definition
-        self.steps: list[NestedStep] = [
-            (step.name, step.if_, self._build_step_action(step))
-            for step in definition.do
+        self.inner_actions = [
+            (inner_action.name, self._build_inner_action(inner_action))
+            for inner_action in definition.do
         ]
 
     async def run(self, *_args: Any, **_kwargs: Any) -> list[Any]:
-        items = Expression.from_flow(self.definition.in_, self.flow).evaluate()
+        items = evaluate_expression(self.flow, self.definition.in_)
         if not isinstance(items, list):
             raise ValueError("each.in must evaluate to an array")
 
@@ -267,32 +160,22 @@ class EachAction:
 
         for item in items:
             local_outputs: dict[str, Any] = {}
-            local_context = {"item": item, "outputs": local_outputs}
             last_output: Any = None
-            for name, condition, run_step_action in self.steps:
-                if condition is not None and not self._condition_matches(
-                    condition, local_context
-                ):
-                    continue
-
-                last_output = await run_step_action(local_context)
+            for name, run_inner_action in self.inner_actions:
+                last_output = await run_inner_action(
+                    {"item": item, "outputs": local_outputs}
+                )
                 local_outputs[name] = last_output
             results.append(last_output)
 
         return results
 
-    def _condition_matches(self, condition: str, local_context: LocalContext) -> bool:
-        result = Expression.from_flow(
-            condition, self.flow, local_context=local_context
-        ).evaluate()
-        if not isinstance(result, bool):
-            raise ValueError("if expression must evaluate to a boolean")
-        return result
+    def _build_inner_action(
+        self, inner_action: FlowEachInnerActionDefinition
+    ) -> Callable[[LocalContext], Any]:
+        run_action = build_action(self.flow, inner_action.action)
 
-    def _build_step_action(self, step: FlowEachStepDefinition) -> NestedStepRunner:
-        run_action = build_action(self.flow, step.action)
-
-        async def run_step_action(local_context: LocalContext) -> Any:
+        async def run_inner_action(local_context: LocalContext) -> Any:
             kwargs = {_LOCAL_CONTEXT_KWARG: local_context}
             if inspect.iscoroutinefunction(run_action):
                 result = run_action(**kwargs)
@@ -307,17 +190,15 @@ class EachAction:
                 result = await result
             return result
 
-        return run_step_action
+        return run_inner_action
 
 
 _ACTION_TYPES: tuple[_ActionType, ...] = (
     EachAction,
     CodeAction,
     ToolAction,
-    AgentAction,
     CrewAction,
     ExpressionAction,
-    ScriptAction,
 )
 
 

lib/crewai/src/crewai/flow/runtime/_expressions.py

@@ -0,0 +1,157 @@
+"""Runtime expression support for FlowDefinition CEL expressions."""
+
+from __future__ import annotations
+
+from itertools import pairwise
+import json
+import re
+from typing import TYPE_CHECKING, Any, cast
+
+from crewai.utilities.serialization import to_serializable
+
+
+if TYPE_CHECKING:
+    from crewai.flow.runtime import Flow
+
+
+_EXPRESSION_PATTERN = re.compile(r"\$\{([^{}]*)\}")
+
+__all__ = ["FlowExpressionError", "evaluate_expression", "render_with_block"]
+
+
+class FlowExpressionError(ValueError):
+    """A FlowDefinition expression failed to parse or evaluate."""
+
+
+def render_with_block(
+    flow: Flow[Any], value: Any, local_context: dict[str, Any] | None = None
+) -> Any:
+    """Render CEL expressions inside a FlowDefinition ``with:`` payload."""
+    context = _expression_context(flow, local_context=local_context)
+    return _render_value(value, context)
+
+
+def evaluate_expression(
+    flow: Flow[Any], expression: str, local_context: dict[str, Any] | None = None
+) -> Any:
+    """Evaluate a FlowDefinition CEL expression against runtime context."""
+    expression = expression.strip()
+    if not expression:
+        raise FlowExpressionError("empty CEL expression")
+    return _eval_cel(expression, _expression_context(flow, local_context=local_context))
+
+
+def _expression_context(
+    flow: Flow[Any], local_context: dict[str, Any] | None = None
+) -> dict[str, Any]:
+    outputs = _outputs_by_name(flow._method_outputs)
+    context: dict[str, Any] = {
+        "state": flow._copy_and_serialize_state(),
+        "outputs": outputs,
+    }
+    if local_context:
+        local_values = {
+            key: to_serializable(value, max_depth=0)
+            for key, value in local_context.items()
+        }
+        local_outputs = local_values.pop("outputs", None)
+        local_values.pop("state", None)
+        context.update(local_values)
+        if local_outputs is not None:
+            if not isinstance(local_outputs, dict):
+                raise TypeError("flow definition local outputs must be a mapping")
+            context["outputs"] = {**outputs, **local_outputs}
+    return context
+
+
+def _outputs_by_name(method_outputs: list[Any]) -> dict[str, Any]:
+    outputs: dict[str, Any] = {}
+    for entry in method_outputs:
+        method = ""
+        output = entry
+        if isinstance(entry, dict) and "output" in entry:
+            method = str(entry.get("method", ""))
+            output = entry["output"]
+        outputs[method] = to_serializable(output, max_depth=0)
+    return outputs
+
+
+def _render_value(value: Any, context: dict[str, Any]) -> Any:
+    if isinstance(value, str):
+        return _render_string(value, context)
+    if isinstance(value, dict):
+        return {key: _render_value(item, context) for key, item in value.items()}
+    if isinstance(value, list):
+        return [_render_value(item, context) for item in value]
+    return value
+
+
+def _render_string(value: str, context: dict[str, Any]) -> Any:
+    matches = list(_EXPRESSION_PATTERN.finditer(value))
+    if not matches:
+        _raise_for_invalid_interpolation(value)
+        return value
+
+    _raise_for_literal_braces(value[: matches[0].start()])
+    for previous, current in pairwise(matches):
+        _raise_for_literal_braces(value[previous.end() : current.start()])
+    _raise_for_literal_braces(value[matches[-1].end() :])
+
+    if len(matches) == 1 and matches[0].span() == (0, len(value)):
+        expression = matches[0].group(1).strip()
+        if not expression:
+            raise FlowExpressionError("empty CEL expression in with block")
+        return _eval_cel(expression, context)
+
+    rendered: list[str] = []
+    position = 0
+    for match in matches:
+        start, end = match.span()
+        literal = value[position:start]
+        rendered.append(literal)
+
+        expression = match.group(1).strip()
+        if not expression:
+            raise FlowExpressionError("empty CEL expression in with block")
+        result = _eval_cel(expression, context)
+        rendered.append(result if isinstance(result, str) else json.dumps(result))
+        position = end
+
+    literal = value[position:]
+    rendered.append(literal)
+
+    return "".join(rendered)
+
+
+def _raise_for_invalid_interpolation(value: str) -> None:
+    if "${" not in value:
+        return
+    raise FlowExpressionError(
+        "invalid CEL interpolation in with block: expressions must be enclosed "
+        "as ${...} and cannot contain braces"
+    )
+
+
+def _raise_for_literal_braces(value: str) -> None:
+    if "{" not in value and "}" not in value:
+        return
+    raise FlowExpressionError(
+        "invalid CEL interpolation in with block: expressions must be enclosed "
+        "as ${...} and cannot contain braces"
+    )
+
+
+def _eval_cel(expression: str, context: dict[str, Any]) -> Any:
+    try:
+        from celpy import Environment
+        from celpy.adapter import CELJSONEncoder, json_to_cel
+        from celpy.evaluation import Context
+
+        environment = Environment()
+        program = environment.program(environment.compile(expression))
+        result = program.evaluate(cast(Context, json_to_cel(context)))
+        return json.loads(json.dumps(result, cls=CELJSONEncoder))
+    except Exception as e:
+        raise FlowExpressionError(
+            f"failed to evaluate CEL expression {expression!r}: {e}"
+        ) from e

lib/crewai/src/crewai/flow/runtime/_outputs.py

@@ -1,40 +0,0 @@
-"""Shared FlowDefinition runtime output helpers."""
-
-from __future__ import annotations
-
-from collections.abc import Mapping
-from typing import Any, TypedDict
-
-from crewai.utilities.serialization import to_serializable
-
-
-class _MethodOutput(TypedDict):
-    method: str
-    output: Any
-
-
-def outputs_by_name(
-    method_outputs: list[_MethodOutput],
-    *,
-    local_outputs: Mapping[str, Any] | None = None,
-    serialize: bool = False,
-) -> dict[str, Any]:
-    outputs: dict[str, Any] = {}
-    for entry in method_outputs:
-        outputs[entry["method"]] = _output_value(entry["output"], serialize=serialize)
-
-    if local_outputs is not None:
-        outputs.update(
-            {
-                key: _output_value(output, serialize=serialize)
-                for key, output in local_outputs.items()
-            }
-        )
-
-    return outputs
-
-
-def _output_value(value: Any, *, serialize: bool) -> Any:
-    if not serialize:
-        return value
-    return to_serializable(value, max_depth=0)

lib/crewai/src/crewai/memory/unified_memory.py

@@ -3,9 +3,7 @@
 from __future__ import annotations
 
 from concurrent.futures import Future, ThreadPoolExecutor
-from contextlib import suppress
 import contextvars
-import copy
 from datetime import datetime
 import threading
 import time
@@ -55,24 +53,6 @@ def _default_embedder() -> OpenAIEmbeddingFunction:
     return build_embedder(spec)
 
 
-def _non_streaming_analysis_llm(llm: Any) -> Any:
-    """Return an isolated non-streaming LLM for internal memory analysis."""
-    if not isinstance(llm, BaseLLM):
-        return llm
-
-    try:
-        analysis_llm = copy.copy(llm)
-    except Exception:
-        try:
-            analysis_llm = llm.model_copy(deep=False)
-        except Exception:
-            return llm
-
-    with suppress(Exception):
-        analysis_llm.stream = False
-    return analysis_llm
-
-
 class Memory(BaseModel):
     """Unified memory: standalone, LLM-analyzed, with intelligent recall flow.
 
@@ -220,9 +200,7 @@ class Memory(BaseModel):
             query_analysis_threshold=self.query_analysis_threshold,
         )
 
-        self._llm_instance = (
-            None if isinstance(self.llm, str) else _non_streaming_analysis_llm(self.llm)
-        )
+        self._llm_instance = None if isinstance(self.llm, str) else self.llm
         self._embedder_instance = (
             self.embedder
             if (self.embedder is not None and not isinstance(self.embedder, dict))

lib/crewai/src/crewai/project/__init__.py

@@ -15,22 +15,16 @@ from crewai.project.annotations import (
 )
 from crewai.project.crew_base import CrewBase
 from crewai.project.crew_definition import (
-    AgentDefinition,
     CrewAgentDefinition,
     CrewDefinition,
     CrewTaskDefinition,
     PythonReferenceDefinition,
 )
 from crewai.project.crew_loader import load_crew, load_crew_and_kickoff
-from crewai.project.json_loader import (
-    load_agent,
-    load_agent_from_definition,
-    strip_jsonc_comments,
-)
+from crewai.project.json_loader import load_agent, strip_jsonc_comments
 
 
 __all__ = [
-    "AgentDefinition",
     "CrewAgentDefinition",
     "CrewBase",
     "CrewDefinition",
@@ -44,7 +38,6 @@ __all__ = [
     "crew",
     "llm",
     "load_agent",
-    "load_agent_from_definition",
     "load_crew",
     "load_crew_and_kickoff",
     "output_json",

lib/crewai/src/crewai/project/crew_definition.py

@@ -8,7 +8,6 @@ from pydantic import BaseModel, ConfigDict, Field, field_validator, model_valida
 
 
 __all__ = [
-    "AgentDefinition",
     "CrewAgentDefinition",
     "CrewDefinition",
     "CrewTaskDefinition",
@@ -54,20 +53,6 @@ class CrewAgentDefinition(BaseModel):
         return value or {}
 
 
-class AgentDefinition(CrewAgentDefinition):
-    """Inline agent definition used by a Flow agent action."""
-
-    input: str
-    response_format: PythonReferenceDefinition | None = None
-
-    @field_validator("input", mode="before")
-    @classmethod
-    def _validate_input(cls, value: Any) -> Any:
-        if not isinstance(value, str):
-            raise ValueError("agent.input must be a string")
-        return value
-
-
 class CrewTaskDefinition(BaseModel):
     """Task definition used by a crew definition."""
 

lib/crewai/src/crewai/project/json_loader.py

@@ -207,18 +207,19 @@ def load_jsonc_file(source: str | Path) -> Any:
     return parse_jsonc(path.read_text(encoding="utf-8"), source=path)
 
 
-def _instantiate_agent_from_data(
-    defn: dict[str, Any], source_label: str, root: Path
-) -> Any:
-    """Resolve the agent class and kwargs from definition data and instantiate it."""
+def load_agent(source: str | Path) -> Any:
+    """Load an existing ``Agent`` from a ``.json`` / ``.jsonc`` definition file."""
+    path = Path(source)
+    defn = _expect_object(load_jsonc_file(path), path)
+    root = path.parent.parent if path.parent.name == "agents" else path.parent
     agent_class = _agent_class_from_definition(
         defn,
-        f"{source_label}: type",
+        f"{path}: type",
         project_root=root,
     )
     agent_kwargs = _agent_kwargs_from_definition(
         defn,
-        source_label,
+        path,
         agent_class=agent_class,
         project_root=root,
     )
@@ -226,50 +227,9 @@ def _instantiate_agent_from_data(
     try:
         return agent_class(**agent_kwargs)
     except ValidationError as exc:
-        raise JSONProjectError(_format_validation_error(source_label, exc)) from exc
+        raise JSONProjectError(_format_validation_error(path, exc)) from exc
     except Exception as exc:
-        raise JSONProjectError(f"{source_label}: failed to load agent: {exc}") from exc
-
-
-def load_agent(source: str | Path) -> Any:
-    """Load an existing ``Agent`` from a ``.json`` / ``.jsonc`` definition file."""
-    path = Path(source)
-    defn = _expect_object(load_jsonc_file(path), path)
-    root = path.parent.parent if path.parent.name == "agents" else path.parent
-    return _instantiate_agent_from_data(defn, str(path), root)
-
-
-def load_agent_from_definition(
-    definition: dict[str, Any] | Any,
-    *,
-    source: str | Path = "<inline agent>",
-    project_root: str | Path | None = None,
-) -> tuple[Any, type[BaseModel] | None]:
-    """Load an ``Agent`` and optional kickoff response model from an inline definition."""
-    from crewai.project.crew_definition import AgentDefinition
-
-    root = Path(project_root) if project_root is not None else Path.cwd()
-    source_label = str(source)
-    agent_definition = (
-        definition
-        if isinstance(definition, AgentDefinition)
-        else AgentDefinition.model_validate(definition)
-    )
-    definition_data = agent_definition.model_dump(mode="python", exclude_none=True)
-    response_format_ref = definition_data.pop("response_format", None)
-    definition_data.pop("input", None)
-
-    agent = _instantiate_agent_from_data(definition_data, source_label, root)
-
-    response_format = None
-    if response_format_ref is not None:
-        response_format = _resolve_model_class(
-            response_format_ref,
-            f"{source_label}: response_format",
-            root,
-        )
-
-    return agent, response_format
+        raise JSONProjectError(f"{path}: failed to load agent: {exc}") from exc
 
 
 def validate_crew_project(

lib/crewai/tests/memory/test_unified_memory.py

@@ -19,39 +19,6 @@ from crewai.memory.types import (
 )
 
 
-def test_memory_analysis_llm_is_isolated_from_streaming_agent_llm(
-    tmp_path: Path,
-) -> None:
-    """Memory analysis should not share a mutable streaming LLM with the agent UI."""
-    from crewai.llms.base_llm import BaseLLM
-    from crewai.memory.unified_memory import Memory
-    from crewai.utilities.types import LLMMessage
-
-    class FakeStreamingLLM(BaseLLM):
-        def call(
-            self,
-            messages: str | list[LLMMessage],
-            tools: list[dict] | None = None,
-            callbacks: list | None = None,
-            available_functions: dict | None = None,
-            from_task: object | None = None,
-            from_agent: object | None = None,
-            response_model: type | None = None,
-        ) -> str:
-            return ""
-
-    agent_llm = FakeStreamingLLM(model="fake-model", stream=True)
-    mem = Memory(
-        storage=str(tmp_path / "db"),
-        llm=agent_llm,
-        embedder=lambda texts: [[0.1] for _ in texts],
-    )
-
-    assert mem._llm is not agent_llm
-    assert mem._llm.stream is False
-
-    agent_llm.stream = True
-    assert mem._llm.stream is False
 
 
 def test_memory_record_defaults() -> None:

lib/crewai/tests/project/test_json_loader.py

@@ -7,7 +7,6 @@ from pathlib import Path
 import sys
 
 import pytest
-from pydantic import BaseModel
 
 from crewai.llms.base_llm import BaseLLM
 from crewai.project.json_loader import (
@@ -15,7 +14,6 @@ from crewai.project.json_loader import (
     _looks_like_windows_absolute_path,
     find_json_project_file,
     load_agent,
-    load_agent_from_definition,
     strip_jsonc_comments,
 )
 
@@ -360,30 +358,6 @@ class TestLoadAgent:
             load_agent(Path("/nonexistent/agent.json"))
 
 
-class TestLoadAgentFromDefinition:
-    def test_resolves_response_format_from_project_module(self, tmp_path: Path):
-        (tmp_path / "models.py").write_text(
-            "from pydantic import BaseModel\n"
-            "class AnswerModel(BaseModel):\n"
-            "    answer: str\n"
-        )
-
-        _, response_format = load_agent_from_definition(
-            {
-                "role": "Analyst",
-                "goal": "Analyze data",
-                "backstory": "Data expert.",
-                "input": "Summarize this",
-                "response_format": {"python": "models.AnswerModel"},
-            },
-            source="agent action",
-            project_root=tmp_path,
-        )
-
-        assert issubclass(response_format, BaseModel)
-        assert response_format.__name__ == "AnswerModel"
-
-
 class TestResolveTools:
     def test_unknown_tool_raises_with_guidance(self):
         from crewai.project.json_loader import JSONProjectError, _resolve_tools

lib/crewai/tests/test_checkpoint.py

@@ -631,7 +631,7 @@ class TestLegacyMethodOutputsRestore:
         assert restored.method_outputs == ["first", "second"]
 
     def test_restore_legacy_outputs_evaluates_expressions(self) -> None:
-        from crewai.flow.expressions import Expression
+        from crewai.flow.runtime._expressions import _expression_context
 
         flow = Flow()
         flow._method_outputs = ["legacy"]
@@ -642,14 +642,17 @@ class TestLegacyMethodOutputsRestore:
             cfg = CheckpointConfig(restore_from=loc)
             restored = Flow.from_checkpoint(cfg)
 
-        context = Expression._flow_context(restored)
+        context = _expression_context(restored)
         assert context["outputs"] == {"": "legacy"}
 
-    def test_raw_legacy_outputs_property_remains_readable(self) -> None:
+    def test_raw_legacy_outputs_remain_readable(self) -> None:
+        from crewai.flow.runtime._expressions import _expression_context
+
         flow = Flow()
         flow._method_outputs = ["legacy"]
 
         assert flow.method_outputs == ["legacy"]
+        assert _expression_context(flow)["outputs"] == {"": "legacy"}
 
 
 class TestAgentCheckpoint:

lib/crewai/tests/test_flow_definition.py

@@ -37,8 +37,6 @@ def test_flow_public_exports_are_explicit():
     }
     assert set(flow_definition.__all__) == {
         "FlowActionDefinition",
-        "FlowAgentActionDefinition",
-        "FlowAtomicActionDefinition",
         "FlowCodeActionDefinition",
         "FlowConfigDefinition",
         "FlowConversationalDefinition",
@@ -46,16 +44,16 @@ def test_flow_public_exports_are_explicit():
         "FlowCrewActionDefinition",
         "FlowDefinition",
         "FlowDefinitionCondition",
+        "FlowDefinitionDiagnostic",
         "FlowDictStateDefinition",
         "FlowEachActionDefinition",
-        "FlowEachStepDefinition",
+        "FlowEachInnerActionDefinition",
         "FlowExpressionActionDefinition",
         "FlowHumanFeedbackDefinition",
         "FlowJsonSchemaStateDefinition",
         "FlowMethodDefinition",
         "FlowPersistenceDefinition",
         "FlowPydanticStateDefinition",
-        "FlowScriptActionDefinition",
         "FlowStateDefinition",
         "FlowToolActionDefinition",
         "FlowUnknownStateDefinition",
@@ -64,126 +62,6 @@ def test_flow_public_exports_are_explicit():
     assert "calculate_node_levels" not in flow_visualization.__all__
 
 
-def test_flow_definition_json_schema_carries_reference_descriptions():
-    schema = flow_definition.FlowDefinition.json_schema()
-    defs = schema["$defs"]
-
-    assert schema["properties"]["schema"]["description"]
-    assert schema["properties"]["methods"]["description"]
-    assert "diagnostics" not in schema["properties"]
-
-    method_properties = defs["FlowMethodDefinition"]["properties"]
-    assert method_properties["do"]["description"] == "Action executed when this method runs."
-    assert "Trigger condition" in method_properties["listen"]["description"]
-
-    script_properties = defs["FlowScriptActionDefinition"]["properties"]
-    assert "trusted inline Python" in script_properties["call"]["description"]
-    assert "not interpolated" in script_properties["code"]["description"]
-    assert "not sandboxed" in script_properties["code"]["description"]
-
-    agent_properties = defs["FlowAgentActionDefinition"]["properties"]
-    assert "Inline Agent definition" in agent_properties["with"]["description"]
-    assert "run an inline Agent" in agent_properties["call"]["description"]
-
-    state_schema = next(
-        branch
-        for branch in schema["properties"]["state"]["anyOf"]
-        if "discriminator" in branch
-    )
-    assert state_schema["discriminator"]["propertyName"] == "type"
-    assert state_schema["discriminator"]["mapping"] == {
-        "dict": "#/$defs/FlowDictStateDefinition",
-        "json_schema": "#/$defs/FlowJsonSchemaStateDefinition",
-        "pydantic": "#/$defs/FlowPydanticStateDefinition",
-        "unknown": "#/$defs/FlowUnknownStateDefinition",
-    }
-
-    dict_state_properties = defs["FlowDictStateDefinition"]["properties"]
-    assert dict_state_properties["type"]["description"]
-    assert "ref" not in dict_state_properties
-
-    json_schema_state_properties = defs["FlowJsonSchemaStateDefinition"]["properties"]
-    assert json_schema_state_properties["json_schema"]["description"]
-    assert "json_schema" in defs["FlowJsonSchemaStateDefinition"]["required"]
-
-    pydantic_state_properties = defs["FlowPydanticStateDefinition"]["properties"]
-    assert "Fallback JSON Schema" in pydantic_state_properties["json_schema"][
-        "description"
-    ]
-
-    each_properties = defs["FlowEachActionDefinition"]["properties"]
-    assert "list to iterate" in each_properties["in"]["description"]
-    assert "Ordered steps" in each_properties["do"]["description"]
-
-    step_properties = defs["FlowEachStepDefinition"]["properties"]
-    assert "runs only if" in step_properties["if"]["description"]
-
-
-def test_flow_definition_json_schema_carries_field_examples_only():
-    schema = flow_definition.FlowDefinition.json_schema()
-    defs = schema["$defs"]
-
-    for model_name in [
-        "FlowDefinition",
-        "FlowCodeActionDefinition",
-        "FlowToolActionDefinition",
-        "FlowAgentActionDefinition",
-        "FlowCrewActionDefinition",
-        "FlowExpressionActionDefinition",
-        "FlowScriptActionDefinition",
-        "FlowEachActionDefinition",
-        "FlowEachStepDefinition",
-        "FlowMethodDefinition",
-        "FlowDictStateDefinition",
-        "FlowJsonSchemaStateDefinition",
-        "FlowPydanticStateDefinition",
-        "FlowUnknownStateDefinition",
-        "FlowConfigDefinition",
-        "FlowPersistenceDefinition",
-        "FlowHumanFeedbackDefinition",
-    ]:
-        model_schema = schema if model_name == "FlowDefinition" else defs[model_name]
-        assert "examples" not in model_schema
-
-    assert schema["properties"]["name"]["examples"] == ["ResearchFlow"]
-    assert schema["properties"]["schema"]["examples"] == ["crewai.flow/v1"]
-    assert schema["properties"]["methods"]["examples"][0]["seed"]["do"] == {
-        "call": "expression",
-        "expr": "state.topic",
-    }
-
-    script_properties = defs["FlowScriptActionDefinition"]["properties"]
-    assert script_properties["call"]["examples"] == ["script"]
-    assert "input.strip()" in script_properties["code"]["examples"][0]
-    assert script_properties["language"]["examples"] == ["python"]
-
-    action_properties = defs["FlowCodeActionDefinition"]["properties"]
-    assert action_properties["ref"]["examples"] == [
-        "my_project.flows:normalize_topic"
-    ]
-    assert action_properties["with"]["examples"] == [{"topic": "${state.topic}"}]
-
-    agent_properties = defs["FlowAgentActionDefinition"]["properties"]
-    assert agent_properties["call"]["examples"] == ["agent"]
-    assert agent_properties["with"]["examples"][0]["input"] == "${state.question}"
-
-    each_properties = defs["FlowEachActionDefinition"]["properties"]
-    assert each_properties["in"]["examples"] == ["state.rows"]
-    assert each_properties["do"]["examples"][0][0]["name"] == "clean"
-    assert each_properties["do"]["examples"][0][0]["action"]["call"] == "script"
-    assert each_properties["do"]["examples"][0][1]["if"] == "outputs.clean != ''"
-
-    step_properties = defs["FlowEachStepDefinition"]["properties"]
-    assert step_properties["if"]["examples"] == ["item.kind == 'invoice'"]
-
-    method_properties = defs["FlowMethodDefinition"]["properties"]
-    assert method_properties["listen"]["examples"] == [
-        "seed",
-        {"or": ["approved", "revise"]},
-    ]
-    assert method_properties["emit"]["examples"] == [["approved", "revise"]]
-
-
 def test_flow_state_definition_uses_discriminated_branches():
     definition = flow_definition.FlowDefinition.model_validate(
         {
@@ -355,7 +233,7 @@ def test_flow_definition_maps_dsl_to_static_contract():
     assert review.human_feedback.learn_strict is True
 
     assert definition.methods["audit"].listen == {"and": ["begin", "process"]}
-    assert "diagnostics" not in definition.to_dict()
+    assert definition.diagnostics == []
 
 
 def test_flow_definition_excludes_conversational_builtins_for_regular_flows():
@@ -437,8 +315,7 @@ def test_flow_definition_uses_collapsed_conversational_router_start():
     assert methods["route_conversation"].router is True
 
 
-def test_flow_definition_serializes_human_feedback_metadata(caplog):
-    caplog.set_level(logging.WARNING, logger="crewai.flow.dsl._utils")
+def test_flow_definition_serializes_human_feedback_metadata():
     marker = object()
 
     class MetadataFlow(Flow):
@@ -457,9 +334,9 @@ def test_flow_definition_serializes_human_feedback_metadata(caplog):
     assert review.human_feedback is not None
     assert review.human_feedback.metadata == {"ref": "builtins:dict"}
     assert any(
-        "methods.review.human_feedback.metadata" in record.message
-        and "not fully serializable" in record.message
-        for record in caplog.records
+        diagnostic.code == "non_serializable_value"
+        and diagnostic.path == "methods.review.human_feedback.metadata"
+        for diagnostic in definition.diagnostics
     )
     definition.to_json()
 
@@ -604,16 +481,14 @@ def test_each_action_round_trips_json_and_yaml():
                         "in": "state.rows",
                         "do": [
                             {
-                                "name": "normalize",
-                                "action": {
+                                "normalize": {
                                     "call": "tool",
                                     "ref": "my_tools:NormalizeRowTool",
                                     "with": {"row": "${ item }"},
                                 }
                             },
                             {
-                                "name": "save",
-                                "action": {
+                                "save": {
                                     "call": "code",
                                     "ref": "my_flow:save_row",
                                     "with": {
@@ -700,6 +575,7 @@ def test_flow_definition_allows_dynamic_router_emit():
     definition = DynamicRouterFlow.flow_definition()
 
     assert definition.methods["decide"].emit is None
+    assert definition.diagnostics == []
 
 
 def test_flow_definition_infers_literal_router_emit():
@@ -852,15 +728,16 @@ def test_flow_definition_accepts_explicit_router_events():
     assert definition.methods["decide"].emit == ["left", "right"]
 
 
-def test_flow_definition_ignores_legacy_diagnostics_loaded_from_contract():
+def test_flow_definition_preserves_diagnostics_loaded_from_contract():
     definition = flow_definition.FlowDefinition.from_dict(
         {
             "schema": "crewai.flow/v1",
             "name": "LoadedDiagnosticsFlow",
             "methods": {
-                "begin": {
-                    "do": {"ref": "loaded_flows:LoadedDiagnosticsFlow.begin"},
-                    "start": True,
+                "decision": {
+                    "do": {"ref": "loaded_flows:LoadedDiagnosticsFlow.decision"},
+                    "router": True,
+                    "emit": ["continue"],
                 }
             },
             "diagnostics": [
@@ -880,13 +757,13 @@ def test_flow_definition_ignores_legacy_diagnostics_loaded_from_contract():
         }
     )
 
-    assert "diagnostics" not in definition.to_dict()
+    codes = [diagnostic.code for diagnostic in definition.diagnostics]
+    assert "serialized_warning" in codes
+    assert codes.count("router_without_trigger") == 1
 
 
-def test_router_start_false_without_listen_logs_missing_trigger(caplog):
-    caplog.set_level(logging.ERROR, logger="crewai.flow.flow_definition")
-
-    flow_definition.FlowDefinition.from_dict(
+def test_router_start_false_without_listen_reports_missing_trigger():
+    definition = flow_definition.FlowDefinition.from_dict(
         {
             "schema": "crewai.flow/v1",
             "name": "LoadedFlow",
@@ -902,10 +779,9 @@ def test_router_start_false_without_listen_logs_missing_trigger(caplog):
     )
 
     assert any(
-        record.levelno == logging.ERROR
-        and "router_without_trigger" in record.message
-        and "methods.decision" in record.message
-        for record in caplog.records
+        diagnostic.code == "router_without_trigger"
+        and diagnostic.path == "methods.decision"
+        for diagnostic in definition.diagnostics
     )
 
 
@@ -933,7 +809,7 @@ def test_router_human_feedback_preserves_existing_router_metadata():
     assert method.human_feedback is not None
 
 
-def test_dynamic_router_flow_definition_allows_dynamic_emit():
+def test_dynamic_router_flow_definition_has_no_diagnostics():
     class LazyDynamicRouterFlow(Flow):
         @start()
         def begin(self):
@@ -944,7 +820,7 @@ def test_dynamic_router_flow_definition_allows_dynamic_emit():
             return self.state["dynamic_event"]
 
     definition = LazyDynamicRouterFlow.flow_definition()
-    assert definition.methods["decide"].emit is None
+    assert definition.diagnostics == []
 
 
 def test_dynamic_router_string_listener_is_valid_contract():
@@ -963,7 +839,7 @@ def test_dynamic_router_string_listener_is_valid_contract():
 
     definition = DynamicRouterListenerFlow.flow_definition()
 
-    assert definition.methods["handle"].listen == "dynamic_event"
+    assert definition.diagnostics == []
 
 
 def test_static_string_listener_is_allowed_by_contract():
@@ -983,7 +859,7 @@ def test_static_string_listener_is_allowed_by_contract():
             },
         }
     )
-    assert definition.methods["handle"].listen == "begni"
+    assert definition.diagnostics == []
 
 
 def test_start_false_not_classified_as_start_method():
@@ -1048,10 +924,10 @@ def test_flow_definition_cache_is_not_reused_by_subclasses():
     assert set(child_definition.methods) == {"child_step"}
 
 
-def test_flow_definition_logs_validation_issues_when_loaded_from_contract(caplog):
+def test_flow_definition_logs_diagnostics_when_loaded_from_contract(caplog):
     caplog.set_level(logging.WARNING, logger="crewai.flow.flow_definition")
 
-    flow_definition.FlowDefinition.from_dict(
+    definition = flow_definition.FlowDefinition.from_dict(
         {
             "schema": "crewai.flow/v1",
             "name": "LoadedFlow",
@@ -1065,6 +941,10 @@ def test_flow_definition_logs_validation_issues_when_loaded_from_contract(caplog
         }
     )
 
+    assert any(
+        diagnostic.code == "router_without_trigger"
+        for diagnostic in definition.diagnostics
+    )
     assert any(
         record.levelno == logging.ERROR
         and "LoadedFlow" in record.message

lib/crewai/tests/test_flow_from_definition.py

@@ -26,7 +26,6 @@ from crewai.flow.flow_config import flow_config
 from crewai.flow.flow_definition import FlowConfigDefinition, FlowDefinition
 from crewai.flow.persistence import persist
 from crewai.flow.persistence.base import FlowPersistence
-from crewai.flow.runtime._actions import FlowScriptExecutionDisabledError
 from crewai.state.checkpoint_config import CheckpointConfig
 from crewai.tools import BaseTool
 from crewai.types.streaming import FlowStreamingOutput
@@ -114,7 +113,7 @@ class EachActionFlow(Flow):
         except RuntimeError:
             pass
         else:
-            raise RuntimeError("each step ran on the event loop")
+            raise RuntimeError("inner action ran on the event loop")
 
         from crewai.flow.flow_context import current_flow_method_name
 
@@ -644,7 +643,7 @@ methods:
     assert flow.kickoff(inputs={"topic": "ai"}) == "found:ai agents"
 
 
-def test_tool_action_treats_embedded_cel_marker_as_literal():
+def test_tool_action_rejects_braces_in_embedded_cel_input():
     definition = FlowDefinition.from_dict(
         {
             "schema": "crewai.flow/v1",
@@ -660,62 +659,16 @@ def test_tool_action_treats_embedded_cel_marker_as_literal():
                             "prefix": "${'p}x'}",
                         },
                     },
-                },
+                }
             },
         }
     )
 
-    assert Flow.from_definition(definition).kickoff() == "p}x:wrapped ${'a}b'} value"
+    with pytest.raises(ValueError, match="cannot contain braces"):
+        Flow.from_definition(definition).kickoff()
 
 
-def test_tool_action_treats_marker_with_trailing_text_as_literal():
-    definition = FlowDefinition.from_dict(
-        {
-            "schema": "crewai.flow/v1",
-            "name": "ToolFlow",
-            "methods": {
-                "search": {
-                    "start": True,
-                    "do": {
-                        "call": "tool",
-                        "ref": f"{__name__}:StaticSearchTool",
-                        "with": {
-                            "search_query": "${state.topic} extra",
-                            "prefix": "p",
-                        },
-                    },
-                },
-            },
-        }
-    )
-
-    assert Flow.from_definition(definition).kickoff() == "p:${state.topic} extra"
-
-
-def test_tool_action_rejects_adjacent_markers_as_invalid_cel():
-    with pytest.raises(ValidationError, match="invalid CEL expression"):
-        FlowDefinition.from_dict(
-            {
-                "schema": "crewai.flow/v1",
-                "name": "ToolFlow",
-                "methods": {
-                    "search": {
-                        "start": True,
-                        "do": {
-                            "call": "tool",
-                            "ref": f"{__name__}:StaticSearchTool",
-                            "with": {
-                                "search_query": "${'a'}${'b'}",
-                                "prefix": "p",
-                            },
-                        },
-                    },
-                },
-            }
-        )
-
-
-def test_tool_action_accepts_braces_in_full_cel_marker():
+def test_tool_action_rejects_braces_in_full_cel_input():
     definition = FlowDefinition.from_dict(
         {
             "schema": "crewai.flow/v1",
@@ -728,15 +681,16 @@ def test_tool_action_accepts_braces_in_full_cel_marker():
                         "ref": f"{__name__}:StaticSearchTool",
                         "with": {
                             "search_query": "${{'query': 'ai agents'}.query}",
-                            "prefix": "${'p}x'}",
+                            "prefix": "found",
                         },
                     },
-                },
+                }
             },
         }
     )
 
-    assert Flow.from_definition(definition).kickoff() == "p}x:ai agents"
+    with pytest.raises(ValueError, match="cannot contain braces"):
+        Flow.from_definition(definition).kickoff()
 
 
 def test_tool_action_renders_latest_output_by_method_name():
@@ -811,166 +765,6 @@ methods:
     )
 
 
-def test_agent_action_runs_inline_yaml_definition(monkeypatch: pytest.MonkeyPatch):
-    from crewai import Agent
-
-    async def fake_kickoff_async(
-        self: Agent, messages: str, **_kwargs: Any
-    ) -> dict[str, Any]:
-        return {"agent": self.role, "input": messages}
-
-    monkeypatch.setattr(Agent, "kickoff_async", fake_kickoff_async)
-
-    yaml_str = """
-schema: crewai.flow/v1
-name: AgentFlow
-methods:
-  answer:
-    do:
-      call: agent
-      with:
-        role: Analyst
-        goal: Answer questions
-        backstory: Knows things.
-        input: "${state.question}"
-    start: true
-"""
-
-    flow = Flow.from_definition(FlowDefinition.from_yaml(yaml_str))
-
-    assert flow.kickoff(inputs={"question": "What is CrewAI?"}) == {
-        "agent": "Analyst",
-        "input": "What is CrewAI?",
-    }
-
-
-def test_agent_action_runs_inside_each(monkeypatch: pytest.MonkeyPatch):
-    from crewai import Agent
-
-    async def fake_kickoff_async(
-        self: Agent, messages: str, **_kwargs: Any
-    ) -> str:
-        return f"{self.role}:{messages}"
-
-    monkeypatch.setattr(Agent, "kickoff_async", fake_kickoff_async)
-
-    yaml_str = """
-schema: crewai.flow/v1
-name: AgentEachFlow
-methods:
-  answer_each:
-    do:
-      call: each
-      in: state.questions
-      do:
-        - name: answer
-          action:
-            call: agent
-            with:
-              role: Analyst
-              goal: Answer questions
-              backstory: Knows things.
-              input: "${item}"
-    start: true
-"""
-
-    flow = Flow.from_definition(FlowDefinition.from_yaml(yaml_str))
-
-    assert flow.kickoff(inputs={"questions": ["one", "two"]}) == [
-        "Analyst:one",
-        "Analyst:two",
-    ]
-
-
-def test_agent_action_round_trips_with_inline_definition():
-    definition = FlowDefinition.from_dict(
-        {
-            "schema": "crewai.flow/v1",
-            "name": "AgentFlow",
-            "methods": {
-                "answer": {
-                    "start": True,
-                    "do": {
-                        "call": "agent",
-                        "with": {
-                            "role": "Analyst",
-                            "goal": "Answer questions",
-                            "backstory": "Knows things.",
-                            "settings": {"verbose": True},
-                            "input": "${state.question}",
-                        },
-                    },
-                }
-            },
-        }
-    )
-
-    round_trip = FlowDefinition.from_yaml(definition.to_yaml())
-    action = round_trip.to_dict()["methods"]["answer"]["do"]
-
-    assert action["call"] == "agent"
-    assert action["with"]["role"] == "Analyst"
-    assert action["with"]["input"] == "${state.question}"
-    assert action["with"]["settings"] == {"verbose": True}
-
-
-def test_agent_action_json_schema_describes_inline_agent_definitions():
-    schema_defs = FlowDefinition.json_schema()["$defs"]
-
-    assert set(schema_defs["AgentDefinition"]["properties"]) >= {
-        "role",
-        "goal",
-        "backstory",
-        "settings",
-        "input",
-        "response_format",
-    }
-
-
-def test_agent_action_rejects_non_string_input_in_definition():
-    with pytest.raises(ValidationError, match="agent.input must be a string"):
-        FlowDefinition.from_dict(
-            {
-                "schema": "crewai.flow/v1",
-                "name": "AgentFlow",
-                "methods": {
-                    "answer": {
-                        "start": True,
-                        "do": {
-                            "call": "agent",
-                            "with": {
-                                "role": "Analyst",
-                                "goal": "Answer questions",
-                                "backstory": "Knows things.",
-                                "input": 123,
-                            },
-                        },
-                    }
-                },
-            }
-        )
-
-
-def test_agent_action_reports_invalid_cel_expression():
-    yaml_str = """
-schema: crewai.flow/v1
-name: AgentFlow
-methods:
-  answer:
-    do:
-      call: agent
-      with:
-        role: Analyst
-        goal: Answer questions
-        backstory: Knows things.
-        input: "${state.}"
-    start: true
-"""
-
-    with pytest.raises(ValidationError, match="invalid CEL expression"):
-        FlowDefinition.from_yaml(yaml_str)
-
-
 def test_crew_action_runs_inline_yaml_definition(monkeypatch: pytest.MonkeyPatch):
     from crewai import Crew
 
@@ -1231,8 +1025,10 @@ methods:
     start: true
 """
 
-    with pytest.raises(ValidationError, match="invalid CEL expression"):
-        FlowDefinition.from_yaml(yaml_str)
+    flow = Flow.from_definition(FlowDefinition.from_yaml(yaml_str))
+
+    with pytest.raises(ValueError, match="failed to evaluate CEL expression"):
+        flow.kickoff()
 
 
 def test_code_action_renders_keyword_inputs():
@@ -1284,8 +1080,7 @@ methods:
       call: each
       in: state.rows
       do:
-        - name: normalize
-          action:
+        - normalize:
             call: code
             ref: {__name__}:EachActionFlow.normalize_row
             with:
@@ -1301,7 +1096,7 @@ methods:
     ]
 
 
-def test_each_action_runs_sync_steps_off_event_loop_with_context():
+def test_each_action_runs_sync_inner_actions_off_event_loop_with_context():
     yaml_str = f"""
 schema: crewai.flow/v1
 name: EachFlow
@@ -1311,8 +1106,7 @@ methods:
       call: each
       in: state.rows
       do:
-        - name: threaded
-          action:
+        - threaded:
             call: code
             ref: {__name__}:EachActionFlow.require_threaded_context
             with:
@@ -1328,7 +1122,7 @@ methods:
     assert flow.inner_thread_id != caller_thread_id
 
 
-def test_each_action_runs_async_tool_results_from_sync_steps():
+def test_each_action_runs_async_tool_results_from_sync_inner_actions():
     yaml_str = f"""
 schema: crewai.flow/v1
 name: EachFlow
@@ -1338,8 +1132,7 @@ methods:
       call: each
       in: state.rows
       do:
-        - name: async_tool
-          action:
+        - async_tool:
             call: tool
             ref: {__name__}:AsyncResultTool
             with:
@@ -1352,120 +1145,7 @@ methods:
     assert flow.kickoff(inputs={"rows": ["a", "b"]}) == ["async:a", "async:b"]
 
 
-def test_script_action_requires_explicit_opt_in():
-    yaml_str = """
-schema: crewai.flow/v1
-name: ScriptFlow
-methods:
-  normalize:
-    do:
-      call: script
-      code: |
-        return "blocked"
-    start: true
-"""
-
-    with pytest.raises(
-        FlowScriptExecutionDisabledError,
-        match="CREWAI_ALLOW_FLOW_SCRIPT_EXECUTION=1",
-    ) as exc_info:
-        Flow.from_definition(FlowDefinition.from_yaml(yaml_str))
-    assert "methods with unresolvable actions" not in str(exc_info.value)
-
-
-def test_script_action_runs_python_imports_mutates_state_and_returns_value(
-    monkeypatch: pytest.MonkeyPatch,
-):
-    monkeypatch.setenv("CREWAI_ALLOW_FLOW_SCRIPT_EXECUTION", "1")
-
-    yaml_str = """
-schema: crewai.flow/v1
-name: ScriptFlow
-methods:
-  normalize:
-    do:
-      call: script
-      code: |
-        import math
-
-        state["rounded"] = math.ceil(state["raw_score"])
-        return f"rounded:{state['rounded']}"
-    start: true
-"""
-
-    flow = Flow.from_definition(FlowDefinition.from_yaml(yaml_str))
-
-    assert flow.kickoff(inputs={"raw_score": 3.2}) == "rounded:4"
-    assert flow.state["rounded"] == 4
-
-
-def test_script_listener_reads_trigger_input_and_outputs(
-    monkeypatch: pytest.MonkeyPatch,
-):
-    monkeypatch.setenv("CREWAI_ALLOW_FLOW_SCRIPT_EXECUTION", "1")
-
-    yaml_str = """
-schema: crewai.flow/v1
-name: ScriptFlow
-methods:
-  seed:
-    do:
-      call: expression
-      expr: "'alpha'"
-    start: true
-  combine:
-    do:
-      call: script
-      code: |
-        state["input_matches_output"] = input == outputs["seed"]
-        return f"{outputs['seed']}:{input}"
-    listen: seed
-"""
-
-    flow = Flow.from_definition(FlowDefinition.from_yaml(yaml_str))
-
-    assert flow.kickoff() == "alpha:alpha"
-    assert flow.state["input_matches_output"] is True
-
-
-def test_script_each_action_reads_item_and_step_outputs(
-    monkeypatch: pytest.MonkeyPatch,
-):
-    monkeypatch.setenv("CREWAI_ALLOW_FLOW_SCRIPT_EXECUTION", "1")
-
-    yaml_str = """
-schema: crewai.flow/v1
-name: ScriptEachFlow
-methods:
-  seed:
-    do:
-      call: expression
-      expr: "'global'"
-    start: true
-  process_rows:
-    do:
-      call: each
-      in: state.rows
-      do:
-        - name: clean
-          action:
-            call: script
-            code: |
-              return item.strip()
-        - name: tag
-          action:
-            call: script
-            code: |
-              return f"{outputs['seed']}:{outputs['clean']}"
-    listen: seed
-"""
-
-    flow = Flow.from_definition(FlowDefinition.from_yaml(yaml_str))
-
-    assert flow.kickoff(inputs={"rows": [" a ", " b "]}) == ["global:a", "global:b"]
-
-
-def test_each_action_uses_iteration_outputs_between_steps():
+def test_each_action_uses_iteration_outputs_between_nested_actions():
     yaml_str = f"""
 schema: crewai.flow/v1
 name: EachFlow
@@ -1475,15 +1155,13 @@ methods:
       call: each
       in: state.rows
       do:
-        - name: normalize
-          action:
+        - normalize:
             call: code
             ref: {__name__}:EachActionFlow.normalize_row
             with:
               row: "${{item}}"
               prefix: saved
-        - name: save
-          action:
+        - save:
             call: code
             ref: {__name__}:EachActionFlow.save_row
             with:
@@ -1500,7 +1178,7 @@ methods:
     ]
 
 
-def test_each_action_resets_step_outputs_between_iterations():
+def test_each_action_resets_inner_outputs_between_iterations():
     yaml_str = """
 schema: crewai.flow/v1
 name: EachFlow
@@ -1510,12 +1188,10 @@ methods:
       call: each
       in: state.rows
       do:
-        - name: leak_check
-          action:
+        - leak_check:
             call: expression
             expr: "has(outputs.previous) ? outputs.previous : 'empty'"
-        - name: previous
-          action:
+        - previous:
             call: expression
             expr: item
     start: true
@@ -1529,7 +1205,7 @@ methods:
     ]
 
 
-def test_each_action_preserves_flow_outputs_and_prefers_step_outputs():
+def test_each_action_preserves_flow_outputs_and_prefers_inner_outputs():
     yaml_str = """
 schema: crewai.flow/v1
 name: EachFlow
@@ -1544,16 +1220,13 @@ methods:
       call: each
       in: state.rows
       do:
-        - name: before_shadow
-          action:
+        - before_shadow:
             call: expression
             expr: "outputs.seed + ':' + item"
-        - name: seed
-          action:
+        - seed:
             call: expression
             expr: "'local:' + item"
-        - name: after_shadow
-          action:
+        - after_shadow:
             call: expression
             expr: "outputs.seed"
     listen: seed
@@ -1571,130 +1244,6 @@ methods:
     ]
 
 
-def test_each_action_runs_simple_if_clauses():
-    yaml_str = """
-schema: crewai.flow/v1
-name: EachIfFlow
-methods:
-  process_rows:
-    do:
-      call: each
-      in: state.rows
-      do:
-        - name: kind
-          action:
-            call: expression
-            expr: item.kind
-        - name: kept
-          if: "outputs.kind == 'keep'"
-          action:
-            call: expression
-            expr: "'kept:' + item.value"
-        - name: skipped
-          if: "outputs.kind != 'keep'"
-          action:
-            call: expression
-            expr: "'skipped:' + item.value"
-    start: true
-"""
-
-    flow = Flow.from_definition(FlowDefinition.from_yaml(yaml_str))
-
-    assert flow.kickoff(
-        inputs={
-            "rows": [
-                {"kind": "keep", "value": "a"},
-                {"kind": "drop", "value": "b"},
-            ]
-        }
-    ) == ["kept:a", "skipped:b"]
-
-
-def test_each_action_accepts_expression_markers_in_explicit_cel_fields():
-    yaml_str = """
-schema: crewai.flow/v1
-name: EachIfFlow
-methods:
-  process_rows:
-    do:
-      call: each
-      in: "${state.rows}"
-      do:
-        - name: kind
-          action:
-            call: expression
-            expr: "${item.kind}"
-        - name: kept
-          if: "${outputs.kind == 'keep'}"
-          action:
-            call: expression
-            expr: "${item.value}"
-    start: true
-"""
-
-    flow = Flow.from_definition(FlowDefinition.from_yaml(yaml_str))
-
-    assert flow.kickoff(inputs={"rows": [{"kind": "keep", "value": "a"}]}) == ["a"]
-
-
-def test_each_action_skipped_if_keeps_previous_output():
-    yaml_str = """
-schema: crewai.flow/v1
-name: EachIfFlow
-methods:
-  process_rows:
-    do:
-      call: each
-      in: state.rows
-      do:
-        - name: original
-          action:
-            call: expression
-            expr: item.value
-        - name: maybe_included
-          if: item.include
-          action:
-            call: expression
-            expr: "'included:' + item.value"
-    start: true
-"""
-
-    flow = Flow.from_definition(FlowDefinition.from_yaml(yaml_str))
-
-    assert flow.kickoff(
-        inputs={
-            "rows": [
-                {"include": True, "value": "a"},
-                {"include": False, "value": "b"},
-            ]
-        }
-    ) == ["included:a", "b"]
-
-
-def test_each_action_if_condition_must_be_boolean():
-    yaml_str = """
-schema: crewai.flow/v1
-name: EachIfFlow
-methods:
-  process_rows:
-    do:
-      call: each
-      in: state.rows
-      do:
-        - name: value
-          if: item.value
-          action:
-            call: expression
-            expr: item.value
-    start: true
-"""
-
-    flow = Flow.from_definition(FlowDefinition.from_yaml(yaml_str))
-
-    with pytest.raises(ValueError, match="if expression must evaluate to a boolean"):
-        flow.kickoff(inputs={"rows": [{"value": "truthy"}]})
-
-
 def test_each_action_empty_list_returns_empty_and_listener_runs_once():
     yaml_str = f"""
 schema: crewai.flow/v1
@@ -1705,8 +1254,7 @@ methods:
       call: each
       in: state.rows
       do:
-        - name: normalize
-          action:
+        - normalize:
             call: code
             ref: {__name__}:EachActionFlow.normalize_row
             with:
@@ -1755,12 +1303,7 @@ def test_each_action_rejects_non_list_inputs(expr, inputs):
                     "do": {
                         "call": "each",
                         "in": expr,
-                        "do": [
-                            {
-                                "name": "value",
-                                "action": {"call": "expression", "expr": "item"},
-                            }
-                        ],
+                        "do": [{"value": {"call": "expression", "expr": "item"}}],
                     },
                 }
             },
@@ -1776,25 +1319,15 @@ def test_each_action_rejects_non_list_inputs(expr, inputs):
     "action_do",
     [
         [],
-        [{"value": {"call": "expression", "expr": "item"}}],
-        [{"name": "1bad", "action": {"call": "expression", "expr": "item"}}],
-        [{"name": "missing_action"}],
-        [{"action": {"call": "expression", "expr": "item"}}],
+        [{"first": {"call": "expression", "expr": "item"}, "second": {"call": "expression", "expr": "item"}}],
+        [{"1bad": {"call": "expression", "expr": "item"}}],
         [
-            {
-                "name": "value",
-                "if": "true",
-                "then": [],
-                "action": {"call": "expression", "expr": "item"},
-            }
-        ],
-        [
-            {"name": "same", "action": {"call": "expression", "expr": "item"}},
-            {"name": "same", "action": {"call": "expression", "expr": "item"}},
+            {"same": {"call": "expression", "expr": "item"}},
+            {"same": {"call": "expression", "expr": "item"}},
         ],
     ],
 )
-def test_each_action_validates_step_shape(action_do):
+def test_each_action_validates_inner_action_shape(action_do):
     with pytest.raises(ValidationError):
         FlowDefinition.from_dict(
             {
@@ -1814,26 +1347,6 @@ def test_each_action_validates_step_shape(action_do):
         )
 
 
-def test_if_clauses_are_rejected_at_method_level():
-    with pytest.raises(ValidationError):
-        FlowDefinition.from_dict(
-            {
-                "schema": "crewai.flow/v1",
-                "name": "TopLevelIfFlow",
-                "methods": {
-                    "process": {
-                        "start": True,
-                        "do": {
-                            "call": "expression",
-                            "if": "true",
-                            "expr": "'ok'",
-                        },
-                    }
-                },
-            }
-        )
-
-
 def test_each_action_rejects_nested_each_actions():
     with pytest.raises(ValidationError):
         FlowDefinition.from_dict(
@@ -1848,14 +1361,12 @@ def test_each_action_rejects_nested_each_actions():
                             "in": "state.rows",
                             "do": [
                                 {
-                                    "name": "nested",
-                                    "action": {
+                                    "nested": {
                                         "call": "each",
                                         "in": "state.children",
                                         "do": [
                                             {
-                                                "name": "child",
-                                                "action": {
+                                                "child": {
                                                     "call": "expression",
                                                     "expr": "item",
                                                 }
@@ -1881,8 +1392,7 @@ methods:
       call: each
       in: state.rows
       do:
-        - name: validate
-          action:
+        - validate:
             call: code
             ref: {__name__}:EachActionFlow.fail_on_bad_row
             with:
@@ -1920,28 +1430,8 @@ def test_expression_action_round_trips():
     assert Flow.from_definition(definition).kickoff(inputs={"score": 90}) == "qualified"
 
 
-def test_explicit_cel_fields_accept_expression_markers():
-    definition = FlowDefinition.from_dict(
-        {
-            "schema": "crewai.flow/v1",
-            "name": "ExpressionFlow",
-            "methods": {
-                "classify": {
-                    "start": True,
-                    "do": {
-                        "call": "expression",
-                        "expr": "${state.score >= 80 ? 'qualified' : 'nurture'}",
-                    },
-                }
-            },
-        }
-    )
-
-    assert Flow.from_definition(definition).kickoff(inputs={"score": 90}) == "qualified"
-
-
 def test_expression_local_context_recurses_into_dataclass_values():
-    from crewai.flow.expressions import Expression
+    from crewai.flow.runtime._expressions import evaluate_expression
 
     class Payload(BaseModel):
         name: str
@@ -1951,37 +1441,15 @@ def test_expression_local_context_recurses_into_dataclass_values():
         payload: Payload
 
     assert (
-        Expression.from_flow(
-            "item.payload.name",
+        evaluate_expression(
             Flow(),
+            "item.payload.name",
             local_context={"item": Row(payload=Payload(name="qualified"))},
-        ).evaluate()
+        )
         == "qualified"
     )
 
 
-def test_expression_empty_context_overrides_stored_context():
-    from crewai.flow.expressions import Expression, ExpressionError
-
-    expression = Expression("state.score", context={"state": {"score": 90}})
-
-    assert expression.evaluate() == 90
-    with pytest.raises(ExpressionError):
-        expression.evaluate({})
-
-
-def test_expression_template_empty_context_overrides_stored_context():
-    from crewai.flow.expressions import Expression, ExpressionError
-
-    expression = Expression(
-        {"score": "${state.score}"}, context={"state": {"score": 90}}
-    )
-
-    assert expression.render_template() == {"score": 90}
-    with pytest.raises(ExpressionError):
-        expression.render_template({})
-
-
 def test_expression_action_can_route_like_if_else():
     yaml_str = f"""
 schema: crewai.flow/v1
@@ -2033,24 +1501,10 @@ methods:
     start: true
 """
 
-    with pytest.raises(ValidationError, match="invalid CEL expression"):
-        FlowDefinition.from_yaml(yaml_str)
+    flow = Flow.from_definition(FlowDefinition.from_yaml(yaml_str))
 
-
-def test_expression_action_rejects_unknown_cel_root():
-    yaml_str = """
-schema: crewai.flow/v1
-name: ExpressionFlow
-methods:
-  classify:
-    do:
-      call: expression
-      expr: "score >= 80"
-    start: true
-"""
-
-    with pytest.raises(ValidationError, match="unknown CEL root"):
-        FlowDefinition.from_yaml(yaml_str)
+    with pytest.raises(ValueError, match="failed to evaluate CEL expression"):
+        flow.kickoff()
 
 
 def test_tool_action_requires_module_qualname_ref():

lib/devtools/src/crewai_devtools/__init__.py

@@ -1,3 +1,3 @@
 """CrewAI development tools."""
 
-__version__ = "1.14.8a1"
+__version__ = "1.14.7"

pyproject.toml

@@ -171,8 +171,6 @@ info = "Commits must follow Conventional Commits 1.0.0."
 
 [tool.uv]
 exclude-newer = "3 days"
-# pypdf 6.13.3 is a security fix newer than the global supply-chain cutoff.
-exclude-newer-package = { pypdf = "2026-06-18T00:00:00Z" }
 
 # composio-core pins rich<14 but textual requires rich>=14.
 # onnxruntime 1.24+ dropped Python 3.10 wheels; cap it so qdrant[fastembed] resolves on 3.10.
@@ -182,8 +180,7 @@ exclude-newer-package = { pypdf = "2026-06-18T00:00:00Z" }
 # langchain-text-splitters <1.1.2 has GHSA-fv5p-p927-qmxr (SSRF bypass in split_text_from_url).
 # transformers 4.57.6 has CVE-2026-1839; force 5.4+ (docling 2.84 allows huggingface-hub>=1).
 # cryptography 46.0.6 has CVE-2026-39892; force 46.0.7+.
-# pypdf <6.10.2 has GHSA-4pxv-j86v-mhcw, GHSA-7gw9-cf7v-778f, GHSA-x284-j5p8-9c5p.
-# pypdf <6.13.3 has GHSA-jm82-fx9c-mx94; force 6.13.3+.
+# pypdf <6.10.2 has GHSA-4pxv-j86v-mhcw, GHSA-7gw9-cf7v-778f, GHSA-x284-j5p8-9c5p; force 6.10.2+.
 # uv <0.11.15 has GHSA-4gg8-gxpx-9rph (and earlier GHSA-pjjw-68hj-v9mw); force 0.11.15+.
 # 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).
@@ -208,7 +205,7 @@ override-dependencies = [
     "urllib3>=2.7.0",
     "transformers>=5.4.0; python_version >= '3.10'",
     "cryptography>=46.0.7",
-    "pypdf>=6.13.3,<7",
+    "pypdf>=6.10.2,<7",
     "uv>=0.11.15,<1",
     "python-multipart>=0.0.27,<1",
     "gitpython>=3.1.50,<4",

uv.lock

@@ -16,9 +16,6 @@ resolution-markers = [
 exclude-newer = "0001-01-01T00:00:00Z" # This has no effect and is included for backwards compatibility when using relative exclude-newer values.
 exclude-newer-span = "P3D"
 
-[options.exclude-newer-package]
-pypdf = "2026-06-18T00:00:00Z"
-
 [manifest]
 members = [
     "crewai",
@@ -43,7 +40,7 @@ overrides = [
     { name = "pillow", specifier = ">=12.1.1" },
     { name = "pip", specifier = ">=26.1.2" },
     { name = "pydantic-settings", specifier = ">=2.14.0" },
-    { name = "pypdf", specifier = ">=6.13.3,<7" },
+    { name = "pypdf", specifier = ">=6.10.2,<7" },
     { name = "python-multipart", specifier = ">=0.0.27,<1" },
     { name = "rich", specifier = ">=13.7.1" },
     { name = "starlette", specifier = ">=1.3.1" },
@@ -1587,7 +1584,7 @@ requires-dist = [
     { name = "aiofiles", specifier = "~=24.1.0" },
     { name = "av", specifier = "~=13.0.0" },
     { name = "pillow", specifier = "~=12.1.1" },
-    { name = "pypdf", specifier = "~=6.13.3" },
+    { name = "pypdf", specifier = "~=6.10.0" },
     { name = "python-magic", specifier = ">=0.4.27" },
     { name = "tinytag", specifier = "~=2.2.1" },
 ]
@@ -7191,14 +7188,14 @@ wheels = [
 
 [[package]]
 name = "pypdf"
-version = "6.13.3"
+version = "6.13.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "typing-extensions", marker = "python_full_version < '3.11'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/17/18/9947cc201af9ccf76720fd3347bf4f70eb882ce3fcf4cb05f7443e4cf871/pypdf-6.13.3.tar.gz", hash = "sha256:f3cb822769725f1bac658c406cfc9460399043f3750c2d3e4650e0a85eacabd7", size = 6484063, upload-time = "2026-06-17T15:22:00.898Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/15/d9/9d12fa0d9660d03320725ff686c961b645a4218940a82296e1272d9e1ff0/pypdf-6.13.1.tar.gz", hash = "sha256:4841d8a4c1589e5833915dc0c7ddfacff80a2e0bcbeb5d1e681fecaa1674b03a", size = 6477811, upload-time = "2026-06-08T11:01:49.344Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/94/56/2967e621598987905fb8cdfadd8f8de6b5c68c9351f0523c4df8409f28f1/pypdf-6.13.3-py3-none-any.whl", hash = "sha256:c6e3f86afb625791510b02ad5480e94b63970bb957df75d44657c282ecc52224", size = 347288, upload-time = "2026-06-17T15:21:59.512Z" },
+    { url = "https://files.pythonhosted.org/packages/fe/dd/8f03e0a5788a5d1feb4550617c3e6db5e9099eaee248a3e482ddaeacbbb0/pypdf-6.13.1-py3-none-any.whl", hash = "sha256:e555e4ce3f561ef069307622f1374136ba964ca6ca24f24158701decaf83ed9b", size = 346259, upload-time = "2026-06-08T11:01:47.741Z" },
 ]
 
 [[package]]