fix: only treat interpolatable placeholders as crew inputs

.github/workflows/docs-broken-links.yml

@@ -13,9 +13,6 @@ on:
       - "docs.json"
   workflow_dispatch:
 
-permissions:
-  contents: read
-
 jobs:
   check-links:
     name: Check broken links

.github/workflows/vulnerability-scan.yml

@@ -64,7 +64,6 @@ jobs:
             --ignore-vuln PYSEC-2025-197 \
             --ignore-vuln PYSEC-2025-210 \
             --ignore-vuln PYSEC-2026-139 \
-            --ignore-vuln GHSA-rrmf-rvhw-rf47 \
             --ignore-vuln PYSEC-2025-211 \
             --ignore-vuln PYSEC-2025-212 \
             --ignore-vuln PYSEC-2025-213 \
@@ -82,7 +81,6 @@ jobs:
         #   PYSEC-2025-183      - pyjwt 2.12.1: disputed weak-encryption claim; key length is application-chosen
         #   PYSEC-2025-189..197 - torch 2.11.0: memory-corruption/DoS in functions only reachable via untrusted models; no fix available
         #   PYSEC-2025-210, PYSEC-2026-139 - torch 2.11.0: profiler/deserialization issues; no fix available
-        #   GHSA-rrmf-rvhw-rf47 - torch 2.11.0 (CVE-2025-3000, alias of PYSEC-2025-194): memory corruption in torch.jit.script, CVSS 1.9, local-only; affected <=2.12.0, no fix available. pip-audit reports it under the GHSA id so the PYSEC ignore above does not catch it.
         #   PYSEC-2025-211..218 - transformers 5.5.4: deserialization/code injection via malicious model checkpoints; no fix available
         #   GHSA-f4j7-r4q5-qw2c - chromadb 1.1.1 (CVE-2026-45829): pre-auth RCE via /api/v2/tenants/{tenant}/databases/{db}/collections when trust_remote_code=true.
         #                         Advisory: vulnerable >=1.0.0,<=1.5.9, firstPatchedVersion=none. We only use chromadb.PersistentClient (lib/crewai/src/crewai/rag/chromadb/factory.py)

.gitignore

@@ -31,5 +31,3 @@ chromadb-*.lock
 blogs/*
 secrets/*
 UNKNOWN.egg-info/
-demos/*
-.crewai/*

.pre-commit-config.yaml

@@ -47,7 +47,6 @@ repos:
           --ignore-vuln PYSEC-2025-197
           --ignore-vuln PYSEC-2025-210
           --ignore-vuln PYSEC-2026-139
-          --ignore-vuln GHSA-rrmf-rvhw-rf47
           --ignore-vuln PYSEC-2025-211
           --ignore-vuln PYSEC-2025-212
           --ignore-vuln PYSEC-2025-213

AGENTS.md

@@ -1,142 +0,0 @@
-# Docs contributor guide
-
-The `docs/` directory is published at [docs.crewai.com](https://docs.crewai.com)
-by [Mintlify](https://www.mintlify.com/). Mintlify watches `docs/docs.json`
-and the MDX files referenced from it.
-
-## TL;DR for editing docs
-
-- Edit MDX under `docs/edge/<lang>/...` (e.g. `docs/edge/en/concepts/agents.mdx`).
-- Your change ships under the **Edge** version selector the moment it merges
-  to `main`. Edge follows `main` and is the channel for unreleased work.
-- On release cut, the current Edge state is frozen into `docs/v<X.Y.Z>/` and
-  that snapshot becomes the new default version in the selector (tag:
-  `Latest`). Canonical URLs (`/<lang>/...`) auto-redirect to the new default.
-- Never modify files under `docs/v*/`. Those are frozen release snapshots
-  and the `docs-snapshots` CI guard rejects writes. The only exception is a
-  release-cut PR (auto-generated by `devtools release` or the manual
-  `scripts/docs/freeze_current_edge.py` wrapper), which uses a
-  `[docs-freeze]` title prefix to opt out.
-- Never delete or rename files under `docs/images/`. Images are append-only.
-  See [Images](#images) below.
-
-## The version model
-
-The site has one rolling channel (Edge) plus one frozen snapshot per
-release.
-
-```
-docs/
-  edge/                  <-- Edge sources (you edit here)
-    en/...
-    pt-BR/  ko/  ar/
-    enterprise-api.*.yaml
-
-  v1.14.7/               <-- frozen snapshot of v1.14.7
-    en/...
-    pt-BR/  ko/  ar/
-    enterprise-api.*.yaml
-  v1.14.6/...
-  ...
-
-  images/                <-- shared, append-only
-  docs.json              <-- Mintlify config: navigation + redirects
-```
-
-`docs/docs.json` lists one navigation block per version per language. Edge
-points at `docs/edge/<lang>/...`; every other version points at its own
-`docs/v<X.Y.Z>/<lang>/...` subtree. Mintlify scopes both the sidebar and the
-in-site search to whichever version the reader selects, so picking
-`v1.10.0` genuinely shows the v1.10.0 docs (and only those).
-
-### URLs and canonical redirects
-
-Each Mintlify version corresponds to its own URL prefix:
-
-- Edge: `/edge/<lang>/<page>` (e.g. `/edge/en/concepts/agents`)
-- Frozen: `/v<X.Y.Z>/<lang>/<page>` (e.g. `/v1.14.7/en/concepts/agents`)
-
-External links to the old, unversioned `/<lang>/<page>` URLs would 404 under
-this layout. To keep them working, `docs.json` ships wildcard redirects:
-
-```jsonc
-{ "source": "/en/:slug*", "destination": "/v1.14.7/en/:slug*", "permanent": false }
-```
-
-The release-cut step rewrites the destination on every release so canonical
-`/<lang>/...` URLs always resolve to the latest stable docs.
-
-## Lifecycle
-
-1. **During development.** You add or edit pages under
-   `docs/edge/<lang>/...` in normal PRs. They land in Edge as soon as the PR
-   merges. Both `/edge/<lang>/<page>` and the version selector's `Edge` entry
-   reflect the change immediately.
-2. **Release cut.** The release engineer runs `devtools release X.Y.Z`. As
-   part of that flow the CLI opens a `[docs-freeze]` PR that copies Edge into
-   `docs/v<X.Y.Z>/`, rewrites internal OpenAPI references, updates
-   `docs/docs.json` to make `v<X.Y.Z>` the new default + `Latest`, and rewires
-   the canonical-URL redirects to the new default. The PR must merge before
-   the tag and PyPI publish run.
-3. **After release.** Edge keeps rolling. Patch fixes to the just-released
-   docs go into Edge and ship with the next release. We do not back-edit
-   frozen snapshots.
-
-See [`RELEASING.md`](RELEASING.md) for the full release runbook.
-
-## Images
-
-Snapshots share a single `docs/images/` directory. If an image is deleted
-or renamed, every frozen snapshot that referenced it breaks. So the rule
-is:
-
-- Adding new images is always fine.
-- Deleting or renaming an existing image fails CI unless the PR is a
-  `[docs-freeze]` release-cut PR.
-- If an asset is wrong, add a new file with a new name and reference the
-  new name in the Edge MDX (`docs/edge/<lang>/...`). Leave the old file
-  alone.
-
-## Local preview
-
-Install the Mintlify CLI and run from `docs/`:
-
-```bash
-npm i -g mintlify
-mintlify dev
-```
-
-Use the version selector at the top of the rendered page to switch between
-Edge and frozen versions.
-
-To check links across every version:
-
-```bash
-mintlify broken-links
-```
-
-CI runs the broken-links check on every PR that touches `docs/**` via
-[`.github/workflows/docs-broken-links.yml`](.github/workflows/docs-broken-links.yml).
-
-## Scripts
-
-- `scripts/docs/freeze_historical_versions.py` — one-time migration that
-  reconstructed `docs/v1.10.0/` through `docs/v1.14.7/` from git tags. You
-  should not need to run this again.
-- `scripts/docs/prefix_version_paths.py` — one-time migration that switched
-  `docs/docs.json` to directory-based versioning, inserted Edge, and added
-  the canonical-URL redirects. You should not need to run this again.
-- `scripts/docs/freeze_current_edge.py` — thin CLI wrapper around
-  `crewai_devtools.docs_versioning.freeze`. `devtools release` calls the
-  same module during its docs PR step; this script is the manual escape
-  hatch (e.g. retroactively freezing a forgotten release).
-
-## CI guards
-
-- [`.github/workflows/docs-snapshots.yml`](.github/workflows/docs-snapshots.yml)
-  enforces the two rules above (frozen snapshots immutable, images
-  append-only). Both checks accept the `[docs-freeze]` PR-title escape
-  hatch.
-- [`.github/workflows/docs-broken-links.yml`](.github/workflows/docs-broken-links.yml)
-  runs `mintlify broken-links` against the whole site, so adding a new
-  page or moving a snapshot file that breaks a link will fail CI.

README.md

@@ -12,8 +12,6 @@
 <p align="center">
   <a href="https://crewai.com">Homepage</a>
   ·
-  <a href="https://crewai.com/open-source">Open Source</a>
-  ·
   <a href="https://docs.crewai.com">Docs</a>
   ·
   <a href="https://app.crewai.com">Start Cloud Trial</a>
@@ -55,20 +53,20 @@
 
 ### Fast and Flexible Multi-Agent Automation Framework
 
-> CrewAI is an open-source Python framework with high-level abstractions and low-level APIs for building production-ready multi-agent workflows.
-> It gives developers autonomous agent collaboration through Crews and precise, event-driven control through Flows.
+> CrewAI is a lean, lightning-fast Python framework built entirely from scratch—completely **independent of LangChain or other agent frameworks**.
+> It empowers developers with both high-level simplicity and precise low-level control, ideal for creating autonomous AI agents tailored to any scenario.
 
-- **CrewAI Crews**: Optimize for autonomy and collaborative intelligence with role-based AI agents.
-- **CrewAI Flows**: Build event-driven automations that combine precise workflow control, single LLM calls, and native support for Crews.
+- **CrewAI Crews**: Optimize for autonomy and collaborative intelligence.
+- **CrewAI Flows**: The **enterprise and production architecture** for building and deploying multi-agent systems. Enable granular, event-driven control, single LLM calls for precise task orchestration and supports Crews natively
 
 With over 100,000 developers certified through our community courses at [learn.crewai.com](https://learn.crewai.com), CrewAI is rapidly becoming the
-standard for production-ready agentic automation.
+standard for enterprise-ready AI automation.
 
 # CrewAI AMP Suite
 
-For organizations that need a commercial control plane around CrewAI, [CrewAI AMP Suite](https://www.crewai.com/enterprise) adds managed deployment, observability, governance, security, and enterprise support.
+CrewAI AMP Suite is a comprehensive bundle tailored for organizations that require secure, scalable, and easy-to-manage agent-driven automation.
 
-You can try one part of the suite, the [Crew Control Plane, for free](https://app.crewai.com).
+You can try one part of the suite the [Crew Control Plane for free](https://app.crewai.com)
 
 ## Crew Control Plane Key Features:
 
@@ -90,6 +88,7 @@ intelligent automations.
 - [Getting Started](#getting-started)
 - [Key Features](#key-features)
 - [Understanding Flows and Crews](#understanding-flows-and-crews)
+- [CrewAI vs LangGraph](#how-crewai-compares)
 - [Examples](#examples)
   - [Quick Tutorial](#quick-tutorial)
   - [Write Job Descriptions](#write-job-descriptions)
@@ -97,11 +96,11 @@ intelligent automations.
   - [Stock Analysis](#stock-analysis)
   - [Using Crews and Flows Together](#using-crews-and-flows-together)
 - [Connecting Your Crew to a Model](#connecting-your-crew-to-a-model)
-- [When to Use CrewAI](#when-to-use-crewai)
+- [How CrewAI Compares](#how-crewai-compares)
+- [Frequently Asked Questions (FAQ)](#frequently-asked-questions-faq)
 - [Contribution](#contribution)
 - [Telemetry](#telemetry)
 - [License](#license)
-- [Frequently Asked Questions (FAQ)](#frequently-asked-questions-faq)
 
 ## Build with AI
 
@@ -135,15 +134,15 @@ This installs the official [CrewAI Skills](https://github.com/crewAIInc/skills)
   <img src="docs/images/asset.png" alt="CrewAI Logo" width="100%">
 </div>
 
-CrewAI unlocks the true potential of multi-agent automation, delivering speed, flexibility, and control through Crews of AI agents and event-driven Flows:
+CrewAI unlocks the true potential of multi-agent automation, delivering the best-in-class combination of speed, flexibility, and control with either Crews of AI Agents or Flows of Events:
 
-- **Purpose-built architecture**: Designed specifically for agent orchestration, with a lightweight Python core and clean primitives for real-world automation.
+- **Standalone Framework**: Built from scratch, independent of LangChain or any other agent framework.
 - **High Performance**: Optimized for speed and minimal resource usage, enabling faster execution.
-- **Flexible Low-Level Customization**: Complete freedom to customize everything from workflows and system architecture to agent behaviors, internal prompts, and execution logic.
-- **Ideal for Every Use Case**: Proven effective for simple tasks, complex workflows, and production-grade automation.
+- **Flexible Low Level Customization**: Complete freedom to customize at both high and low levels - from overall workflows and system architecture to granular agent behaviors, internal prompts, and execution logic.
+- **Ideal for Every Use Case**: Proven effective for both simple tasks and highly complex, real-world, enterprise-grade scenarios.
 - **Robust Community**: Backed by a rapidly growing community of over **100,000 certified** developers offering comprehensive support and resources.
 
-CrewAI empowers developers and teams to build intelligent automations that balance simplicity, flexibility, and production-grade control.
+CrewAI empowers developers and enterprises to confidently build intelligent automations, bridging the gap between simplicity, flexibility, and performance.
 
 ## Getting Started
 
@@ -434,17 +433,16 @@ In addition to the sequential process, you can use the hierarchical process, whi
 
 ## Key Features
 
-CrewAI gives developers a practical foundation for building agentic systems that move from prototype to production: autonomous collaboration where it helps, explicit workflow control where it matters, and Python-native customization throughout.
+CrewAI stands apart as a lean, standalone, high-performance multi-AI Agent framework delivering simplicity, flexibility, and precise control—free from the complexity and limitations found in other agent frameworks.
 
-- **Crews for autonomy**: Model teams of specialized AI agents with roles, goals, tools, and tasks.
-- **Flows for control**: Build event-driven workflows with state, branching, routing, and production logic.
-- **Seamless integration**: Combine Crews and Flows to create complex, real-world automations.
-- **Python-native customization**: Customize prompts, tools, execution paths, state, and integrations without fighting the framework.
-- **Agent-ready capabilities**: Use tools, memory, knowledge, checkpointing, async execution, and MCP/A2A support for more capable production agents.
-- **Production-ready patterns**: Add deterministic steps, human input, structured outputs, and checkpointing as your system grows.
-- **Thriving community**: Backed by robust documentation and over 100,000 certified developers, providing exceptional support and guidance.
+- **Standalone & Lean**: Completely independent from other frameworks like LangChain, offering faster execution and lighter resource demands.
+- **Flexible & Precise**: Easily orchestrate autonomous agents through intuitive [Crews](https://docs.crewai.com/concepts/crews) or precise [Flows](https://docs.crewai.com/concepts/flows), achieving perfect balance for your needs.
+- **Seamless Integration**: Effortlessly combine Crews (autonomy) and Flows (precision) to create complex, real-world automations.
+- **Deep Customization**: Tailor every aspect—from high-level workflows down to low-level internal prompts and agent behaviors.
+- **Reliable Performance**: Consistent results across simple tasks and complex, enterprise-level automations.
+- **Thriving Community**: Backed by robust documentation and over 100,000 certified developers, providing exceptional support and guidance.
 
-Choose CrewAI to build powerful, adaptable, and production-ready AI automations.
+Choose CrewAI to easily build powerful, adaptable, and production-ready AI automations.
 
 ## Examples
 
@@ -582,17 +580,16 @@ CrewAI supports using various LLMs through a variety of connection options. By d
 
 Please refer to the [Connect CrewAI to LLMs](https://docs.crewai.com/how-to/LLM-Connections/) page for details on configuring your agents' connections to models.
 
-## When to Use CrewAI
+## How CrewAI Compares
 
-Use CrewAI when you need more than a single prompt or chatbot: multi-step work, specialized agents, tool use, structured outputs, human review, or workflows that combine autonomous reasoning with explicit business logic.
+**CrewAI's Advantage**: CrewAI combines autonomous agent intelligence with precise workflow control through its unique Crews and Flows architecture. The framework excels at both high-level orchestration and low-level customization, enabling complex, production-grade systems with granular control.
 
-CrewAI is especially useful when you want to:
+- **LangGraph**: While LangGraph provides a foundation for building agent workflows, its approach requires significant boilerplate code and complex state management patterns. The framework's tight coupling with LangChain can limit flexibility when implementing custom agent behaviors or integrating with external systems.
 
-- Coordinate multiple agents with clear roles and tasks.
-- Wrap agent work in deterministic, event-driven workflows.
-- Keep application logic in regular Python.
-- Move from experiment to production without changing frameworks.
-- Add tools, memory, checkpointing, and async execution as your system grows.
+_P.S. CrewAI demonstrates significant performance advantages over LangGraph, executing 5.76x faster in certain cases like this QA task example ([see comparison](https://github.com/crewAIInc/crewAI-examples/tree/main/Notebooks/CrewAI%20Flows%20%26%20Langgraph/QA%20Agent)) while achieving higher evaluation scores with faster completion times in certain coding tasks, like in this example ([detailed analysis](https://github.com/crewAIInc/crewAI-examples/blob/main/Notebooks/CrewAI%20Flows%20%26%20Langgraph/Coding%20Assistant/coding_assistant_eval.ipynb))._
+
+- **Autogen**: While Autogen excels at creating conversational agents capable of working together, it lacks an inherent concept of process. In Autogen, orchestrating agents' interactions requires additional programming, which can become complex and cumbersome as the scale of tasks grows.
+- **ChatDev**: ChatDev introduced the idea of processes into the realm of AI agents, but its implementation is quite rigid. Customizations in ChatDev are limited and not geared towards production environments, which can hinder scalability and flexibility in real-world applications.
 
 ## Contribution
 
@@ -604,19 +601,6 @@ CrewAI is open-source and we welcome contributions. If you're looking to contrib
 - Send a pull request.
 - We appreciate your input!
 
-### Contributing to the docs
-
-The site at [docs.crewai.com](https://docs.crewai.com) is published from
-`docs/` by [Mintlify](https://www.mintlify.com/). The docs use directory-based
-versioning: edits to `docs/edge/<lang>/...` (e.g.
-`docs/edge/en/concepts/agents.mdx`) land under the **Edge** version selector
-immediately and are frozen into a new versioned snapshot under
-`docs/v<X.Y.Z>/` at the next release cut. Frozen snapshots are immutable — CI
-rejects PRs that modify them without a `[docs-freeze]` title prefix. The
-release CLI (`devtools release`) handles the freeze automatically; see
-[`AGENTS.md`](AGENTS.md) for the full contributor guide and
-[`RELEASING.md`](RELEASING.md) for the release-cut runbook.
-
 ### Installing Dependencies
 
 ```bash
@@ -701,7 +685,7 @@ CrewAI is released under the [MIT License](https://github.com/crewAIInc/crewAI/b
 
 - [What exactly is CrewAI?](#q-what-exactly-is-crewai)
 - [How do I install CrewAI?](#q-how-do-i-install-crewai)
-- [Is CrewAI a standalone framework?](#q-is-crewai-a-standalone-framework)
+- [Does CrewAI depend on LangChain?](#q-does-crewai-depend-on-langchain)
 - [Is CrewAI open-source?](#q-is-crewai-open-source)
 - [Does CrewAI collect data from users?](#q-does-crewai-collect-data-from-users)
 
@@ -710,6 +694,7 @@ CrewAI is released under the [MIT License](https://github.com/crewAIInc/crewAI/b
 - [Can CrewAI handle complex use cases?](#q-can-crewai-handle-complex-use-cases)
 - [Can I use CrewAI with local AI models?](#q-can-i-use-crewai-with-local-ai-models)
 - [What makes Crews different from Flows?](#q-what-makes-crews-different-from-flows)
+- [How is CrewAI better than LangChain?](#q-how-is-crewai-better-than-langchain)
 - [Does CrewAI support fine-tuning or training custom models?](#q-does-crewai-support-fine-tuning-or-training-custom-models)
 
 ### Resources and Community
@@ -725,7 +710,7 @@ CrewAI is released under the [MIT License](https://github.com/crewAIInc/crewAI/b
 
 ### Q: What exactly is CrewAI?
 
-A: CrewAI is a lean, fast Python framework built specifically for orchestrating autonomous AI agents and production-ready agentic workflows.
+A: CrewAI is a standalone, lean, and fast Python framework built specifically for orchestrating autonomous AI agents. Unlike frameworks like LangChain, CrewAI does not rely on external dependencies, making it leaner, faster, and simpler.
 
 ### Q: How do I install CrewAI?
 
@@ -741,9 +726,9 @@ For additional tools, use:
 uv pip install 'crewai[tools]'
 ```
 
-### Q: Is CrewAI a standalone framework?
+### Q: Does CrewAI depend on LangChain?
 
-A: Yes. CrewAI is a standalone Python framework with its own primitives for agents, tasks, crews, flows, tools, and orchestration.
+A: No. CrewAI is built entirely from the ground up, with no dependencies on LangChain or other agent frameworks. This ensures a lean, fast, and flexible experience.
 
 ### Q: Can CrewAI handle complex use cases?
 
@@ -757,6 +742,10 @@ A: Absolutely! CrewAI supports various language models, including local ones. To
 
 A: Crews provide autonomous agent collaboration, ideal for tasks requiring flexible decision-making and dynamic interaction. Flows offer precise, event-driven control, ideal for managing detailed execution paths and secure state management. You can seamlessly combine both for maximum effectiveness.
 
+### Q: How is CrewAI better than LangChain?
+
+A: CrewAI provides simpler, more intuitive APIs, faster execution speeds, more reliable and consistent results, robust documentation, and an active community—addressing common criticisms and limitations associated with LangChain.
+
 ### Q: Is CrewAI open-source?
 
 A: Yes, CrewAI is open-source and actively encourages community contributions and collaboration.
@@ -795,11 +784,11 @@ A: Absolutely! CrewAI agents can easily integrate with external tools, APIs, and
 
 ### Q: Is CrewAI suitable for production environments?
 
-A: Yes, CrewAI is designed with production-grade patterns that support reliable, stable, and scalable agentic workflows.
+A: Yes, CrewAI is explicitly designed with production-grade standards, ensuring reliability, stability, and scalability for enterprise deployments.
 
 ### Q: How scalable is CrewAI?
 
-A: CrewAI is highly scalable, supporting simple automations and large-scale workflows involving numerous agents and complex tasks simultaneously.
+A: CrewAI is highly scalable, supporting simple automations and large-scale enterprise workflows involving numerous agents and complex tasks simultaneously.
 
 ### Q: Does CrewAI offer debugging and monitoring tools?
 

conftest.py

@@ -134,21 +134,17 @@ def bedrock_host_matcher(r1: Request, r2: Request) -> bool:  # type: ignore[no-a
     )
 
 
-def _patched_make_vcr_request(
-    httpx_request: Any, real_request_body: Any = None, **kwargs: Any
-) -> Any:
+def _patched_make_vcr_request(httpx_request: Any, **kwargs: Any) -> Any:
     """Patched version of VCR's _make_vcr_request that handles binary content.
 
     The original implementation fails on binary request bodies (like file uploads)
     because it assumes all content can be decoded as UTF-8.
     """
-    raw_body = real_request_body if real_request_body is not None else httpx_request.read()
-    body: Any = raw_body
-    if isinstance(raw_body, bytes):
-        try:
-            body = raw_body.decode("utf-8")
-        except UnicodeDecodeError:
-            body = base64.b64encode(raw_body).decode("ascii")
+    raw_body = httpx_request.read()
+    try:
+        body = raw_body.decode("utf-8")
+    except UnicodeDecodeError:
+        body = base64.b64encode(raw_body).decode("ascii")
     uri = str(httpx_request.url)
     headers = dict(httpx_request.headers)
     return Request(httpx_request.method, uri, body, headers)

docs/ar/changelog.mdx

@@ -4,6 +4,90 @@ description: "تحديثات المنتج والتحسينات وإصلاحات
 icon: "clock"
 mode: "wide"
 ---
+<Update label="8 يونيو 2026">
+  ## v1.14.7a3
+
+  [عرض الإصدار على GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.7a3)
+
+  ## ما الذي تغير
+
+  ### إصلاحات الأخطاء
+  - إصلاح تعرض `ask_for_human_input` في `AgentExecutor` التجريبي
+  - حل مشكلات CVEs الخاصة بـ pip-audit لـ `aiohttp`، `docling`، `docling-core`، و `pip`
+
+  ### إعادة هيكلة
+  - نقل `@start` لقراءة من `FlowDefinition`
+
+  ### الوثائق
+  - تحديث سجل التغييرات والإصدار لـ v1.14.7a2
+
+  ## المساهمون
+
+  @greysonlalonde، @lorenzejay، @vinibrsl
+
+</Update>
+
+<Update label="5 يونيو 2026">
+  ## v1.14.7a2
+
+  [عرض الإصدار على GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.7a2)
+
+  ## ما الذي تغير
+
+  ### الميزات
+  - إضافة دعم تتبع تدفقات المحادثة.
+  - تحديث وثائق تدفق المحادثة لاستخدام `handle_turn`.
+  - عرض السبب الحقيقي لإنهاء المحادثة، ومعلمات العينة، و`response.id` في أحداث LLM.
+  - تصنيف مشغلات DSL كزخارف واعية بالمسار.
+  - تنفيذ واجهة برمجة التطبيقات للدردشة لتدفقات المحادثة.
+  - جعل قفل الخلفية قابلاً للتجاوز في متجر القفل.
+  - تقسيم أحادي تدفق DSL إلى وحدات زخرفية مركزة.
+  - تسطيح استخدام ذاكرة التخزين المؤقت LiteLLM/أعداد الأسباب الفرعية في `_usage_to_dict`.
+  - بناء `FlowDefinition` من بيانات التعريف الخاصة بتدفق DSL.
+
+  ### الوثائق
+  - إضافة دليل NVIDIA Nemotron LLM.
+  - توثيق عمليات نشر المونوريبو.
+  - تحديث سجل التغييرات والإصدار لـ v1.14.7a1.
+
+  ## المساهمون
+
+  @alex-clawd, @gvieira, @lorenzejay, @lucasgomide, @mattatcha, @vinibrsl
+
+</Update>
+
+<Update label="3 يونيو 2026">
+  ## v1.14.7a1
+
+  [عرض الإصدار على GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.7a1)
+
+  ## ما الذي تغير
+
+  ### الميزات
+  - إضافة دعم ملفات الوكلاء المدربين
+  - إضافة مزود LLM الأصلي لـ Snowflake Cortex
+  - إضافة دليل تكامل Databricks
+  - إضافة دليل تكامل Snowflake
+
+  ### إصلاحات الأخطاء
+  - إصلاح CLI عن طريق استعادة `[project.scripts]` في حزمة crewai لتثبيت أداة UV
+  - حل مشكلات موثوقية إدخال الملفات
+  - إصلاح تاريخ نتائج الأدوات غير المكتملة في Snowflake Claude
+  - التعامل مع استدعاءات الأدوات الممثلة كسلاسل لـ Snowflake Claude
+  - إعادة تفعيل مستمعي `or_` متعدد المصادر عبر دورات مدفوعة بالموجه
+
+  ### الأداء
+  - تحسين سرعة استيراد crewai عن طريق تحميل استيرادات docling بشكل كسول
+
+  ### إعادة هيكلة
+  - تقسيم `flow.py` إلى DSL، تعريف، وتشغيل
+
+  ## المساهمون
+
+  @Luzk, @alex-clawd, @devin-ai-integration[bot], @greysonlalonde, @jessemiller, @lorenzejay, @vinibrsl
+
+</Update>
+
 <Update label="28 مايو 2026">
   ## v1.14.6