chore: update crewAI and tools dependencies to latest versions (#3444)

- Updated `crewai-tools` dependency from version 0.65.0 to 0.69.0 in `pyproject.toml` and `uv.lock`.
- Bumped crewAI version from 0.175.0 to 0.177.0 in `__init__.py`.
- Updated dependency versions in CLI templates for crew, flow, and tool projects to reflect the new crewAI version.

.github/workflows/linter.yml

@@ -15,8 +15,19 @@ jobs:
       - name: Fetch Target Branch
         run: git fetch origin $TARGET_BRANCH --depth=1
 
-      - name: Install Ruff
-        run: pip install ruff
+      - name: Install uv
+        uses: astral-sh/setup-uv@v6
+        with:
+          enable-cache: true
+          cache-dependency-glob: |
+            **/pyproject.toml
+            **/uv.lock
+
+      - name: Set up Python
+        run: uv python install 3.11
+
+      - name: Install dependencies
+        run: uv sync --dev --no-install-project
 
       - name: Get Changed Python Files
         id: changed-files
@@ -33,4 +44,4 @@ jobs:
           echo "${{ steps.changed-files.outputs.files }}" \
             | tr ' ' '\n' \
             | grep -v 'src/crewai/cli/templates/' \
-            | xargs -I{} ruff check "{}"
+            | xargs -I{} uv run ruff check "{}"

.github/workflows/security-checker.yml

@@ -10,14 +10,20 @@ jobs:
       - name: Checkout code
         uses: actions/checkout@v4
 
-      - name: Set up Python
-        uses: actions/setup-python@v5
+      - name: Install uv
+        uses: astral-sh/setup-uv@v6
         with:
-          python-version: "3.11.9"
+          enable-cache: true
+          cache-dependency-glob: |
+            **/pyproject.toml
+            **/uv.lock
+
+      - name: Set up Python
+        run: uv python install 3.11
 
       - name: Install dependencies
-        run: pip install bandit
+        run: uv sync --dev --no-install-project
 
       - name: Run Bandit
-        run: bandit -c pyproject.toml -r src/ -ll
+        run: uv run bandit -c pyproject.toml -r src/ -ll
 

.github/workflows/tests.yml

@@ -24,7 +24,7 @@ jobs:
         uses: actions/checkout@v4
 
       - name: Install uv
-        uses: astral-sh/setup-uv@v3
+        uses: astral-sh/setup-uv@v6
         with:
           enable-cache: true
           cache-dependency-glob: |

.github/workflows/type-checker.yml

@@ -6,21 +6,78 @@ permissions:
   contents: write
 
 jobs:
-  type-checker:
+  type-checker-matrix:
+    name: type-checker (${{ matrix.python-version }})
     runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.10", "3.11", "3.12", "3.13"]
 
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
-
-      - name: Setup Python
-        uses: actions/setup-python@v5
         with:
-          python-version: "3.11.9"
+          fetch-depth: 0 # Fetch all history for proper diff
 
-      - name: Install Requirements
+      - name: Install uv
+        uses: astral-sh/setup-uv@v6
+        with:
+          enable-cache: true
+          cache-dependency-glob: |
+            **/pyproject.toml
+            **/uv.lock
+
+      - name: Set up Python ${{ matrix.python-version }}
+        run: uv python install ${{ matrix.python-version }}
+
+      - name: Install dependencies
+        run: uv sync --dev --no-install-project
+
+      - name: Get changed Python files
+        id: changed-files
         run: |
-          pip install mypy
+          # Get the list of changed Python files compared to the base branch
+          echo "Fetching changed files..."
+          git diff --name-only --diff-filter=ACMRT origin/${{ github.base_ref }}...HEAD -- '*.py' > changed_files.txt
 
-      - name: Run type checks
-        run: mypy src
+          # Filter for files in src/ and tests/ directories
+          grep -E "^(src/|tests/)" changed_files.txt > filtered_changed_files.txt || true
+
+          # Check if there are any changed files
+          if [ -s filtered_changed_files.txt ]; then
+            echo "Changed Python files in src/ and tests/:"
+            cat filtered_changed_files.txt
+            echo "has_changes=true" >> $GITHUB_OUTPUT
+            # Convert newlines to spaces for mypy command
+            echo "files=$(cat filtered_changed_files.txt | tr '\n' ' ')" >> $GITHUB_OUTPUT
+          else
+            echo "No Python files changed in src/ or tests/"
+            echo "has_changes=false" >> $GITHUB_OUTPUT
+          fi
+
+      - name: Run type checks on changed files
+        if: steps.changed-files.outputs.has_changes == 'true'
+        run: |
+          echo "Running mypy on changed files with Python ${{ matrix.python-version }}..."
+          uv run mypy ${{ steps.changed-files.outputs.files }}
+
+      - name: No files to check
+        if: steps.changed-files.outputs.has_changes == 'false'
+        run: echo "No Python files in src/ or tests/ were modified - skipping type checks"
+
+  # Summary job to provide single status for branch protection
+  type-checker:
+    name: type-checker
+    runs-on: ubuntu-latest
+    needs: type-checker-matrix
+    if: always()
+    steps:
+      - name: Check matrix results
+        run: |
+          if [ "${{ needs.type-checker-matrix.result }}" == "success" ] || [ "${{ needs.type-checker-matrix.result }}" == "skipped" ]; then
+            echo "✅ All type checks passed"
+          else
+            echo "❌ Type checks failed"
+            exit 1
+          fi

.pre-commit-config.yaml

@@ -1,7 +1,14 @@
 repos:
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.8.2
+    rev: v0.12.11
     hooks:
       - id: ruff
-        args: ["--fix"]
+        args: ["--config", "pyproject.toml"]
       - id: ruff-format
+        args: ["--config", "pyproject.toml"]
+  
+  - repo: https://github.com/pre-commit/mirrors-mypy
+    rev: v1.17.1
+    hooks:
+      - id: mypy
+        args: ["--config-file", "pyproject.toml"]

.ruff.toml

@@ -1,4 +0,0 @@
-exclude = [
-    "templates",
-    "__init__.py",
-]

README.md

@@ -418,10 +418,10 @@ Choose CrewAI to easily build powerful, adaptable, and production-ready AI autom
 
 You can test different real life examples of AI crews in the [CrewAI-examples repo](https://github.com/crewAIInc/crewAI-examples?tab=readme-ov-file):
 
-- [Landing Page Generator](https://github.com/crewAIInc/crewAI-examples/tree/main/landing_page_generator)
+- [Landing Page Generator](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/landing_page_generator)
 - [Having Human input on the execution](https://docs.crewai.com/how-to/Human-Input-on-Execution)
-- [Trip Planner](https://github.com/crewAIInc/crewAI-examples/tree/main/trip_planner)
-- [Stock Analysis](https://github.com/crewAIInc/crewAI-examples/tree/main/stock_analysis)
+- [Trip Planner](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/trip_planner)
+- [Stock Analysis](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/stock_analysis)
 
 ### Quick Tutorial
 
@@ -429,19 +429,19 @@ You can test different real life examples of AI crews in the [CrewAI-examples re
 
 ### Write Job Descriptions
 
-[Check out code for this example](https://github.com/crewAIInc/crewAI-examples/tree/main/job-posting) or watch a video below:
+[Check out code for this example](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/job-posting) or watch a video below:
 
 [![Jobs postings](https://img.youtube.com/vi/u98wEMz-9to/maxresdefault.jpg)](https://www.youtube.com/watch?v=u98wEMz-9to "Jobs postings")
 
 ### Trip Planner
 
-[Check out code for this example](https://github.com/crewAIInc/crewAI-examples/tree/main/trip_planner) or watch a video below:
+[Check out code for this example](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/trip_planner) or watch a video below:
 
 [![Trip Planner](https://img.youtube.com/vi/xis7rWp-hjs/maxresdefault.jpg)](https://www.youtube.com/watch?v=xis7rWp-hjs "Trip Planner")
 
 ### Stock Analysis
 
-[Check out code for this example](https://github.com/crewAIInc/crewAI-examples/tree/main/stock_analysis) or watch a video below:
+[Check out code for this example](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/stock_analysis) or watch a video below:
 
 [![Stock Analysis](https://img.youtube.com/vi/e0Uj4yWdaAg/maxresdefault.jpg)](https://www.youtube.com/watch?v=e0Uj4yWdaAg "Stock Analysis")
 

docs/docs.json

@@ -320,6 +320,7 @@
                   "en/enterprise/guides/update-crew",
                   "en/enterprise/guides/enable-crew-studio",
                   "en/enterprise/guides/azure-openai-setup",
+                  "en/enterprise/guides/automation-triggers",
                   "en/enterprise/guides/hubspot-trigger",
                   "en/enterprise/guides/react-component-export",
                   "en/enterprise/guides/salesforce-trigger",
@@ -658,6 +659,7 @@
                   "pt-BR/enterprise/guides/update-crew",
                   "pt-BR/enterprise/guides/enable-crew-studio",
                   "pt-BR/enterprise/guides/azure-openai-setup",
+                  "pt-BR/enterprise/guides/automation-triggers",
                   "pt-BR/enterprise/guides/hubspot-trigger",
                   "pt-BR/enterprise/guides/react-component-export",
                   "pt-BR/enterprise/guides/salesforce-trigger",
@@ -1007,6 +1009,7 @@
                   "ko/enterprise/guides/update-crew",
                   "ko/enterprise/guides/enable-crew-studio",
                   "ko/enterprise/guides/azure-openai-setup",
+                  "ko/enterprise/guides/automation-triggers",
                   "ko/enterprise/guides/hubspot-trigger",
                   "ko/enterprise/guides/react-component-export",
                   "ko/enterprise/guides/salesforce-trigger",

docs/en/concepts/cli.mdx

@@ -282,7 +282,25 @@ Watch this video tutorial for a step-by-step demonstration of deploying your cre
   allowfullscreen
 ></iframe>
 
-### 11. API Keys
+### 12. Login
+
+Authenticate with CrewAI Enterprise using a secure device code flow (no email entry required).
+
+```shell Terminal
+crewai login
+```
+
+What happens:
+- A verification URL and short code are displayed in your terminal
+- Your browser opens to the verification URL
+- Enter/confirm the code to complete authentication
+
+Notes:
+- The OAuth2 provider and domain are configured via `crewai config` (defaults use `login.crewai.com`)
+- After successful login, the CLI also attempts to authenticate to the Tool Repository automatically
+- If you reset your configuration, run `crewai login` again to re-authenticate
+
+### 13. API Keys
 
 When running ```crewai create crew``` command, the CLI will show you a list of available LLM providers to choose from, followed by model selection for your chosen provider.
 
@@ -310,7 +328,7 @@ See the following link for each provider's key name:
 
 * [LiteLLM Providers](https://docs.litellm.ai/docs/providers)
 
-### 12. Configuration Management
+### 14. Configuration Management
 
 Manage CLI configuration settings for CrewAI.
 
@@ -385,6 +403,10 @@ Reset all configuration to defaults:
 crewai config reset
 ```
 
+<Tip>
+After resetting configuration, re-run `crewai login` to authenticate again.
+</Tip>
+
 <Note>
 Configuration settings are stored in `~/.config/crewai/settings.json`. Some settings like organization name and UUID are read-only and managed through authentication and organization commands. Tool repository related settings are hidden and cannot be set directly by users.
 </Note>

docs/en/concepts/event-listener.mdx

@@ -44,12 +44,12 @@ To create a custom event listener, you need to:
 Here's a simple example of a custom event listener class:
 
 ```python
-from crewai.utilities.events import (
+from crewai.events import (
     CrewKickoffStartedEvent,
     CrewKickoffCompletedEvent,
     AgentExecutionCompletedEvent,
 )
-from crewai.utilities.events.base_event_listener import BaseEventListener
+from crewai.events import BaseEventListener
 
 class MyCustomListener(BaseEventListener):
     def __init__(self):
@@ -146,7 +146,7 @@ my_project/
 
 ```python
 # my_custom_listener.py
-from crewai.utilities.events.base_event_listener import BaseEventListener
+from crewai.events import BaseEventListener
 # ... import events ...
 
 class MyCustomListener(BaseEventListener):
@@ -279,7 +279,7 @@ Additional fields vary by event type. For example, `CrewKickoffCompletedEvent` i
 For temporary event handling (useful for testing or specific operations), you can use the `scoped_handlers` context manager:
 
 ```python
-from crewai.utilities.events import crewai_event_bus, CrewKickoffStartedEvent
+from crewai.events import crewai_event_bus, CrewKickoffStartedEvent
 
 with crewai_event_bus.scoped_handlers():
     @crewai_event_bus.on(CrewKickoffStartedEvent)

docs/en/concepts/flows.mdx

@@ -97,7 +97,13 @@ The state's unique ID and stored data can be useful for tracking flow executions
 
 ### @start()
 
-The `@start()` decorator is used to mark a method as the starting point of a Flow. When a Flow is started, all the methods decorated with `@start()` are executed in parallel. You can have multiple start methods in a Flow, and they will all be executed when the Flow is started.
+The `@start()` decorator marks entry points for a Flow. You can:
+
+- Declare multiple unconditional starts: `@start()`
+- Gate a start on a prior method or router label: `@start("method_or_label")`
+- Provide a callable condition to control when a start should fire
+
+All satisfied `@start()` methods will execute (often in parallel) when the Flow begins or resumes.
 
 ### @listen()
 

docs/en/concepts/knowledge.mdx

@@ -24,6 +24,41 @@ For file-based Knowledge Sources, make sure to place your files in a `knowledge`
 Also, use relative paths from the `knowledge` directory when creating the source.
 </Tip>
 
+### Vector store (RAG) client configuration
+
+CrewAI exposes a provider-neutral RAG client abstraction for vector stores. The default provider is ChromaDB, and Qdrant is supported as well. You can switch providers using configuration utilities.
+
+Supported today:
+- ChromaDB (default)
+- Qdrant
+
+```python Code
+from crewai.rag.config.utils import set_rag_config, get_rag_client, clear_rag_config
+
+# ChromaDB (default)
+from crewai.rag.chromadb.config import ChromaDBConfig
+set_rag_config(ChromaDBConfig())
+chromadb_client = get_rag_client()
+
+# Qdrant
+from crewai.rag.qdrant.config import QdrantConfig
+set_rag_config(QdrantConfig())
+qdrant_client = get_rag_client()
+
+# Example operations (same API for any provider)
+client = qdrant_client  # or chromadb_client
+client.create_collection(collection_name="docs")
+client.add_documents(
+    collection_name="docs",
+    documents=[{"id": "1", "content": "CrewAI enables collaborative AI agents."}],
+)
+results = client.search(collection_name="docs", query="collaborative agents", limit=3)
+
+clear_rag_config()  # optional reset
+```
+
+This RAG client is separate from Knowledge’s built-in storage. Use it when you need direct vector-store control or custom retrieval pipelines.
+
 ### Basic String Knowledge Example
 
 ```python Code
@@ -681,11 +716,11 @@ CrewAI emits events during the knowledge retrieval process that you can listen f
 #### Example: Monitoring Knowledge Retrieval
 
 ```python
-from crewai.utilities.events import (
+from crewai.events import (
     KnowledgeRetrievalStartedEvent,
     KnowledgeRetrievalCompletedEvent,
+    BaseEventListener,
 )
-from crewai.utilities.events.base_event_listener import BaseEventListener
 
 class KnowledgeMonitorListener(BaseEventListener):
     def setup_listeners(self, crewai_event_bus):

docs/en/concepts/llms.mdx

@@ -733,10 +733,10 @@ CrewAI supports streaming responses from LLMs, allowing your application to rece
     CrewAI emits events for each chunk received during streaming:
 
     ```python
-    from crewai.utilities.events import (
+    from crewai.events import (
       LLMStreamChunkEvent
     )
-    from crewai.utilities.events.base_event_listener import BaseEventListener
+    from crewai.events import BaseEventListener
 
     class MyCustomListener(BaseEventListener):
         def setup_listeners(self, crewai_event_bus):
@@ -758,8 +758,8 @@ CrewAI supports streaming responses from LLMs, allowing your application to rece
 
     ```python
     from crewai import LLM, Agent, Task, Crew
-    from crewai.utilities.events import LLMStreamChunkEvent
-    from crewai.utilities.events.base_event_listener import BaseEventListener
+    from crewai.events import LLMStreamChunkEvent
+    from crewai.events import BaseEventListener
 
     class MyCustomListener(BaseEventListener):
         def setup_listeners(self, crewai_event_bus):

docs/en/concepts/memory.mdx

@@ -738,6 +738,17 @@ print(f"OpenAI: {openai_time:.2f}s")
 print(f"Ollama: {ollama_time:.2f}s")
 ```
 
+### Entity Memory batching behavior
+
+Entity Memory supports batching when saving multiple entities at once. When you pass a list of `EntityMemoryItem`, the system:
+
+- Emits a single MemorySaveStartedEvent with `entity_count`
+- Saves each entity internally, collecting any partial errors
+- Emits MemorySaveCompletedEvent with aggregate metadata (saved count, errors)
+- Raises a partial-save exception if some entities failed (includes counts)
+
+This improves performance and observability when writing many entities in one operation.
+
 ## 2. External Memory 
 External Memory provides a standalone memory system that operates independently from the crew's built-in memory. This is ideal for specialized memory providers or cross-application memory sharing.
 
@@ -1041,8 +1052,8 @@ CrewAI emits the following memory-related events:
 Track memory operation timing to optimize your application:
 
 ```python
-from crewai.utilities.events.base_event_listener import BaseEventListener
-from crewai.utilities.events import (
+from crewai.events import (
+    BaseEventListener,
     MemoryQueryCompletedEvent,
     MemorySaveCompletedEvent
 )
@@ -1076,8 +1087,8 @@ memory_monitor = MemoryPerformanceMonitor()
 Log memory operations for debugging and insights:
 
 ```python
-from crewai.utilities.events.base_event_listener import BaseEventListener
-from crewai.utilities.events import (
+from crewai.events import (
+    BaseEventListener,
     MemorySaveStartedEvent,
     MemoryQueryStartedEvent,
     MemoryRetrievalCompletedEvent
@@ -1117,8 +1128,8 @@ memory_logger = MemoryLogger()
 Capture and respond to memory errors:
 
 ```python
-from crewai.utilities.events.base_event_listener import BaseEventListener
-from crewai.utilities.events import (
+from crewai.events import (
+    BaseEventListener,
     MemorySaveFailedEvent,
     MemoryQueryFailedEvent
 )
@@ -1167,8 +1178,8 @@ error_tracker = MemoryErrorTracker(notify_email="admin@example.com")
 Memory events can be forwarded to analytics and monitoring platforms to track performance metrics, detect anomalies, and visualize memory usage patterns:
 
 ```python
-from crewai.utilities.events.base_event_listener import BaseEventListener
-from crewai.utilities.events import (
+from crewai.events import (
+    BaseEventListener,
     MemoryQueryCompletedEvent,
     MemorySaveCompletedEvent
 )

docs/en/concepts/tasks.mdx

@@ -59,6 +59,12 @@ crew = Crew(
 | **Output Pydantic** _(optional)_ | `output_pydantic` | `Optional[Type[BaseModel]]`   | A Pydantic model for task output.                                                                                    |
 | **Callback** _(optional)_        | `callback`        | `Optional[Any]`               | Function/object to be executed after task completion.                                                                |
 | **Guardrail** _(optional)_       | `guardrail`       | `Optional[Callable]`             | Function to validate task output before proceeding to next task.                                                  |
+| **Guardrail Max Retries** _(optional)_ | `guardrail_max_retries` | `Optional[int]`     | Maximum number of retries when guardrail validation fails. Defaults to 3.                                         |
+
+<Note type="warning" title="Deprecated: max_retries">
+  The task attribute `max_retries` is deprecated and will be removed in v1.0.0.
+  Use `guardrail_max_retries` instead to control retry attempts when a guardrail fails.
+</Note>
 
 ## Creating Tasks
 
@@ -431,7 +437,7 @@ When a guardrail returns `(False, error)`:
 2. The agent attempts to fix the issue
 3. The process repeats until:
    - The guardrail returns `(True, result)`
-   - Maximum retries are reached
+   - Maximum retries are reached (`guardrail_max_retries`)
 
 Example with retry handling:
 ```python Code
@@ -452,7 +458,7 @@ task = Task(
     expected_output="A valid JSON object",
     agent=analyst,
     guardrail=validate_json_output,
-    max_retries=3  # Limit retry attempts
+    guardrail_max_retries=3  # Limit retry attempts
 )
 ```
 

docs/en/enterprise/features/integrations.mdx

@@ -59,7 +59,7 @@ Before using Authentication Integrations, ensure you have:
 3. Click **Connect** on your desired service from the Authentication Integrations section
 4. Complete the OAuth authentication flow
 5. Grant necessary permissions for your use case
-6. Get your Enterprise Token from your [CrewAI Enterprise](https://app.crewai.com) account page - https://app.crewai.com/crewai_plus/settings/account
+6. All set! Get your Enterprise Token from your [CrewAI Enterprise](https://app.crewai.com) in **Integration** tab
 
 <Frame>
   ![Integrations](/images/enterprise/enterprise_action_auth_token.png)

docs/en/enterprise/features/traces.mdx

@@ -141,6 +141,16 @@ Traces are invaluable for troubleshooting issues with your crews:
   </Step>
 </Steps>
 
+## Performance and batching
+
+CrewAI batches trace uploads to reduce overhead on high-volume runs:
+
+- A TraceBatchManager buffers events and sends them in batches via the Plus API client
+- Reduces network chatter and improves reliability on flaky connections
+- Automatically enabled in the default trace listener; no configuration needed
+
+This yields more stable tracing under load while preserving detailed task/agent telemetry.
+
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
   Contact our support team for assistance with trace analysis or any other CrewAI Enterprise features.
 </Card>

docs/en/enterprise/guides/automation-triggers.mdx

@@ -0,0 +1,178 @@
+---
+title: "Automation Triggers"
+description: "Automatically execute your CrewAI workflows when specific events occur in connected integrations"
+icon: "bolt"
+---
+
+Automation triggers enable you to automatically run your CrewAI deployments when specific events occur in your connected integrations, creating powerful event-driven workflows that respond to real-time changes in your business systems.
+
+## Overview
+
+With automation triggers, you can:
+
+- **Respond to real-time events** - Automatically execute workflows when specific conditions are met
+- **Integrate with external systems** - Connect with platforms like Gmail, Outlook, OneDrive, JIRA, Slack, Stripe and more
+- **Scale your automation** - Handle high-volume events without manual intervention
+- **Maintain context** - Access trigger data within your crews and flows
+
+## Managing Automation Triggers
+
+### Viewing Available Triggers
+
+To access and manage your automation triggers:
+
+1. Navigate to your deployment in the CrewAI dashboard
+2. Click on the **Triggers** tab to view all available trigger integrations
+
+<Frame>
+  <img src="/images/enterprise/list-available-triggers.png" alt="List of available automation triggers" />
+</Frame>
+
+This view shows all the trigger integrations available for your deployment, along with their current connection status.
+
+### Enabling and Disabling Triggers
+
+Each trigger can be easily enabled or disabled using the toggle switch:
+
+<Frame>
+  <img src="/images/enterprise/trigger-selected.png" alt="Enable or disable triggers with toggle" />
+</Frame>
+
+- **Enabled (blue toggle)**: The trigger is active and will automatically execute your deployment when the specified events occur
+- **Disabled (gray toggle)**: The trigger is inactive and will not respond to events
+
+Simply click the toggle to change the trigger state. Changes take effect immediately.
+
+### Monitoring Trigger Executions
+
+Track the performance and history of your triggered executions:
+
+<Frame>
+  <img src="/images/enterprise/list-executions.png" alt="List of executions triggered by automation" />
+</Frame>
+
+## Building Automation
+
+Before building your automation, it's helpful to understand the structure of trigger payloads that your crews and flows will receive.
+
+### Payload Samples Repository
+
+We maintain a comprehensive repository with sample payloads from various trigger sources to help you build and test your automations:
+
+**🔗 [CrewAI Enterprise Trigger Payload Samples](https://github.com/crewAIInc/crewai-enterprise-trigger-payload-samples)**
+
+This repository contains:
+
+- **Real payload examples** from different trigger sources (Gmail, Google Drive, etc.)
+- **Payload structure documentation** showing the format and available fields
+
+### Triggers with Crew
+
+Your existing crew definitions work seamlessly with triggers, you just need to have a task to parse the received payload:
+
+```python
+@CrewBase
+class MyAutomatedCrew:
+    @agent
+    def researcher(self) -> Agent:
+        return Agent(
+            config=self.agents_config['researcher'],
+        )
+
+    @task
+    def parse_trigger_payload(self) -> Task:
+        return Task(
+            config=self.tasks_config['parse_trigger_payload'],
+            agent=self.researcher(),
+        )
+
+    @task
+    def analyze_trigger_content(self) -> Task:
+        return Task(
+            config=self.tasks_config['analyze_trigger_data'],
+            agent=self.researcher(),
+        )
+```
+
+The crew will automatically receive and can access the trigger payload through the standard CrewAI context mechanisms.
+
+<Note>
+  Crew and Flow inputs can include `crewai_trigger_payload`. CrewAI automatically injects this payload:
+  - Tasks: appended to the first task's description by default ("Trigger Payload: {crewai_trigger_payload}")
+  - Control via `allow_crewai_trigger_context`: set `True` to always inject, `False` to never inject
+  - Flows: any `@start()` method that accepts a `crewai_trigger_payload` parameter will receive it
+</Note>
+
+### Integration with Flows
+
+For flows, you have more control over how trigger data is handled:
+
+#### Accessing Trigger Payload
+
+All `@start()` methods in your flows will accept an additional parameter called `crewai_trigger_payload`:
+
+```python
+from crewai.flow import Flow, start, listen
+
+class MyAutomatedFlow(Flow):
+    @start()
+    def handle_trigger(self, crewai_trigger_payload: dict = None):
+        """
+        This start method can receive trigger data
+        """
+        if crewai_trigger_payload:
+            # Process the trigger data
+            trigger_id = crewai_trigger_payload.get('id')
+            event_data = crewai_trigger_payload.get('payload', {})
+
+            # Store in flow state for use by other methods
+            self.state.trigger_id = trigger_id
+            self.state.trigger_type = event_data
+
+            return event_data
+
+        # Handle manual execution
+        return None
+
+    @listen(handle_trigger)
+    def process_data(self, trigger_data):
+        """
+        Process the data from the trigger
+        """
+        # ... process the trigger
+```
+
+#### Triggering Crews from Flows
+
+When kicking off a crew within a flow that was triggered, pass the trigger payload as it:
+
+```python
+@start()
+def delegate_to_crew(self, crewai_trigger_payload: dict = None):
+    """
+    Delegate processing to a specialized crew
+    """
+    crew = MySpecializedCrew()
+
+    # Pass the trigger payload to the crew
+    result = crew.crew().kickoff(
+        inputs={
+            'a_custom_parameter': "custom_value",
+            'crewai_trigger_payload': crewai_trigger_payload
+        },
+    )
+
+    return result
+```
+
+## Troubleshooting
+
+**Trigger not firing:**
+- Verify the trigger is enabled
+- Check integration connection status
+
+**Execution failures:**
+- Check the execution logs for error details
+- If you are developing, make sure the inputs include the `crewai_trigger_payload` parameter with the correct payload
+
+Automation triggers transform your CrewAI deployments into responsive, event-driven systems that can seamlessly integrate with your existing business processes and tools.

docs/en/guides/flows/mastering-flow-state.mdx

@@ -348,6 +348,31 @@ class SelectivePersistFlow(Flow):
 
 ## Advanced State Patterns
 
+### Conditional starts and resumable execution
+
+Flows support conditional `@start()` and resumable execution for HITL/cyclic scenarios:
+
+```python
+from crewai.flow.flow import Flow, start, listen, and_, or_
+
+class ResumableFlow(Flow):
+    @start()  # unconditional start
+    def init(self):
+        ...
+
+    # Conditional start: run after "init" or external trigger name
+    @start("init")
+    def maybe_begin(self):
+        ...
+
+    @listen(and_(init, maybe_begin))
+    def proceed(self):
+        ...
+```
+
+- Conditional `@start()` accepts a method name, a router label, or a callable condition.
+- During resume, listeners continue from prior checkpoints; cycle/router branches honor resumption flags.
+
 ### State-Based Conditional Logic
 
 You can use state to implement complex conditional logic in your flows:

docs/en/installation.mdx

@@ -30,6 +30,12 @@ Watch this video tutorial for a step-by-step demonstration of the installation p
   If you need to update Python, visit [python.org/downloads](https://python.org/downloads)
 </Note>
 
+<Note>
+  **OpenAI SDK Requirement**
+
+  CrewAI 0.175.0 requires `openai >= 1.13.3`. If you manage dependencies yourself, ensure your environment satisfies this constraint to avoid import/runtime issues.
+</Note>
+
 CrewAI uses the `uv` as its dependency management and package handling tool. It simplifies project setup and execution, offering a seamless experience.
 
 If you haven't installed `uv` yet, follow **step 1** to quickly get it set up on your system, else you can skip to **step 2**.

docs/en/tools/database-data/weaviatevectorsearchtool.mdx

@@ -1,13 +1,13 @@
 ---
 title: Weaviate Vector Search
-description: The `WeaviateVectorSearchTool` is designed to search a Weaviate vector database for semantically similar documents.
+description: The `WeaviateVectorSearchTool` is designed to search a Weaviate vector database for semantically similar documents using hybrid search.
 icon: network-wired
 ---
 
 ## Overview
 
 
-The `WeaviateVectorSearchTool` is specifically crafted for conducting semantic searches within documents stored in a Weaviate vector database. This tool allows you to find semantically similar documents to a given query, leveraging the power of vector embeddings for more accurate and contextually relevant search results.
+The `WeaviateVectorSearchTool` is specifically crafted for conducting semantic searches within documents stored in a Weaviate vector database. This tool allows you to find semantically similar documents to a given query, leveraging the power of vector and keyword search for more accurate and contextually relevant search results.
 
 [Weaviate](https://weaviate.io/) is a vector database that stores and queries vector embeddings, enabling semantic search capabilities.
 
@@ -39,6 +39,7 @@ from crewai_tools import WeaviateVectorSearchTool
 tool = WeaviateVectorSearchTool(
     collection_name='example_collections',
     limit=3,
+    alpha=0.75,
     weaviate_cluster_url="https://your-weaviate-cluster-url.com",
     weaviate_api_key="your-weaviate-api-key",
 )
@@ -63,6 +64,7 @@ The `WeaviateVectorSearchTool` accepts the following parameters:
 - **weaviate_cluster_url**: Required. The URL of the Weaviate cluster.
 - **weaviate_api_key**: Required. The API key for the Weaviate cluster.
 - **limit**: Optional. The number of results to return. Default is `3`.
+- **alpha**: Optional. Controls the weighting between vector and keyword (BM25) search. alpha = 0 -> BM25 only, alpha = 1 -> vector search only. Default is `0.75`.
 - **vectorizer**: Optional. The vectorizer to use. If not provided, it will use `text2vec_openai` with the `nomic-embed-text` model.
 - **generative_model**: Optional. The generative model to use. If not provided, it will use OpenAI's `gpt-4o`.
 
@@ -78,6 +80,7 @@ from weaviate.classes.config import Configure
 tool = WeaviateVectorSearchTool(
     collection_name='example_collections',
     limit=3,
+    alpha=0.75,
     vectorizer=Configure.Vectorizer.text2vec_openai(model="nomic-embed-text"),
     generative_model=Configure.Generative.openai(model="gpt-4o-mini"),
     weaviate_cluster_url="https://your-weaviate-cluster-url.com",
@@ -128,6 +131,7 @@ with test_docs.batch.dynamic() as batch:
 tool = WeaviateVectorSearchTool(
     collection_name='example_collections', 
     limit=3,
+    alpha=0.75,
     weaviate_cluster_url="https://your-weaviate-cluster-url.com",
     weaviate_api_key="your-weaviate-api-key",
 )
@@ -145,6 +149,7 @@ from crewai_tools import WeaviateVectorSearchTool
 weaviate_tool = WeaviateVectorSearchTool(
     collection_name='example_collections',
     limit=3,
+    alpha=0.75,
     weaviate_cluster_url="https://your-weaviate-cluster-url.com",
     weaviate_api_key="your-weaviate-api-key",
 )

docs/ko/concepts/event-listener.mdx

@@ -44,12 +44,12 @@ Prompt Tracing을 통해 다음과 같은 작업이 가능합니다:
 아래는 커스텀 이벤트 리스너 클래스의 간단한 예시입니다:
 
 ```python
-from crewai.utilities.events import (
+from crewai.events import (
     CrewKickoffStartedEvent,
     CrewKickoffCompletedEvent,
     AgentExecutionCompletedEvent,
 )
-from crewai.utilities.events.base_event_listener import BaseEventListener
+from crewai.events import BaseEventListener
 
 class MyCustomListener(BaseEventListener):
     def __init__(self):
@@ -146,7 +146,7 @@ my_project/
 
 ```python
 # my_custom_listener.py
-from crewai.utilities.events.base_event_listener import BaseEventListener
+from crewai.events import BaseEventListener
 # ... import events ...
 
 class MyCustomListener(BaseEventListener):
@@ -279,7 +279,7 @@ CrewAI는 여러분이 청취할 수 있는 다양한 이벤트를 제공합니
 임시 이벤트 처리가 필요한 경우(테스트 또는 특정 작업에 유용함), `scoped_handlers` 컨텍스트 관리자를 사용할 수 있습니다:
 
 ```python
-from crewai.utilities.events import crewai_event_bus, CrewKickoffStartedEvent
+from crewai.events import crewai_event_bus, CrewKickoffStartedEvent
 
 with crewai_event_bus.scoped_handlers():
     @crewai_event_bus.on(CrewKickoffStartedEvent)

docs/ko/concepts/knowledge.mdx

@@ -683,11 +683,11 @@ CrewAI는 knowledge 검색 과정에서 이벤트를 발생시키며, 이벤트
 #### 예시: Knowledge Retrieval 모니터링
 
 ```python
-from crewai.utilities.events import (
+from crewai.events import (
     KnowledgeRetrievalStartedEvent,
     KnowledgeRetrievalCompletedEvent,
+    BaseEventListener,
 )
-from crewai.utilities.events.base_event_listener import BaseEventListener
 
 class KnowledgeMonitorListener(BaseEventListener):
     def setup_listeners(self, crewai_event_bus):

docs/ko/concepts/llms.mdx

@@ -731,10 +731,10 @@ CrewAI는 LLM의 스트리밍 응답을 지원하여, 애플리케이션이 출
     CrewAI는 스트리밍 중 수신되는 각 청크에 대해 이벤트를 발생시킵니다:
 
     ```python
-    from crewai.utilities.events import (
+    from crewai.events import (
       LLMStreamChunkEvent
     )
-    from crewai.utilities.events.base_event_listener import BaseEventListener
+    from crewai.events import BaseEventListener
 
     class MyCustomListener(BaseEventListener):
         def setup_listeners(self, crewai_event_bus):
@@ -756,8 +756,8 @@ CrewAI는 LLM의 스트리밍 응답을 지원하여, 애플리케이션이 출
 
     ```python
     from crewai import LLM, Agent, Task, Crew
-    from crewai.utilities.events import LLMStreamChunkEvent
-    from crewai.utilities.events.base_event_listener import BaseEventListener
+    from crewai.events import LLMStreamChunkEvent
+    from crewai.events import BaseEventListener
 
     class MyCustomListener(BaseEventListener):
         def setup_listeners(self, crewai_event_bus):

docs/ko/concepts/memory.mdx

@@ -985,8 +985,8 @@ CrewAI는 다음과 같은 메모리 관련 이벤트를 발생시킵니다:
 애플리케이션을 최적화하기 위해 메모리 작업 타이밍을 추적하세요:
 
 ```python
-from crewai.utilities.events.base_event_listener import BaseEventListener
-from crewai.utilities.events import (
+from crewai.events import (
+    BaseEventListener,
     MemoryQueryCompletedEvent,
     MemorySaveCompletedEvent
 )
@@ -1020,8 +1020,8 @@ memory_monitor = MemoryPerformanceMonitor()
 디버깅 및 인사이트를 위해 메모리 작업을 로깅합니다:
 
 ```python
-from crewai.utilities.events.base_event_listener import BaseEventListener
-from crewai.utilities.events import (
+from crewai.events import (
+    BaseEventListener,
     MemorySaveStartedEvent,
     MemoryQueryStartedEvent,
     MemoryRetrievalCompletedEvent
@@ -1061,8 +1061,8 @@ memory_logger = MemoryLogger()
 메모리 오류를 캡처하고 대응합니다:
 
 ```python
-from crewai.utilities.events.base_event_listener import BaseEventListener
-from crewai.utilities.events import (
+from crewai.events import (
+    BaseEventListener,
     MemorySaveFailedEvent,
     MemoryQueryFailedEvent
 )
@@ -1111,8 +1111,8 @@ error_tracker = MemoryErrorTracker(notify_email="admin@example.com")
 메모리 이벤트는 분석 및 모니터링 플랫폼으로 전달되어 성능 지표를 추적하고, 이상 징후를 감지하며, 메모리 사용 패턴을 시각화할 수 있습니다:
 
 ```python
-from crewai.utilities.events.base_event_listener import BaseEventListener
-from crewai.utilities.events import (
+from crewai.events import (
+    BaseEventListener,
     MemoryQueryCompletedEvent,
     MemorySaveCompletedEvent
 )

docs/ko/concepts/tasks.mdx

@@ -59,6 +59,7 @@ crew = Crew(
 | **Pydantic 출력** _(선택 사항)_   | `output_pydantic`     | `Optional[Type[BaseModel]]`       | 태스크 출력용 Pydantic 모델입니다.                                                                             |
 | **콜백** _(선택 사항)_            | `callback`            | `Optional[Any]`                  | 태스크 완료 후 실행할 함수/객체입니다.                                                                         |
 | **가드레일** _(선택 사항)_        | `guardrail`           | `Optional[Callable]`                | 다음 태스크로 진행하기 전에 태스크 출력을 검증하는 함수입니다.                                               |
+| **가드레일 최대 재시도** _(선택 사항)_ | `guardrail_max_retries` | `Optional[int]`          | 가드레일 검증 실패 시 최대 재시도 횟수입니다. 기본값은 3입니다.                                                |
 
 ## 작업 생성하기
 
@@ -448,7 +449,7 @@ task = Task(
     expected_output="A valid JSON object",
     agent=analyst,
     guardrail=validate_json_output,
-    max_retries=3  # Limit retry attempts
+    guardrail_max_retries=3  # 재시도 횟수 제한
 )
 ```
 
@@ -899,4 +900,4 @@ except RuntimeError as e:
 작업(task)은 CrewAI 에이전트의 행동을 이끄는 원동력입니다.
 작업과 그 결과를 적절하게 정의함으로써, 에이전트가 독립적으로 또는 협업 단위로 효과적으로 작동할 수 있는 기반을 마련할 수 있습니다.
 작업에 적합한 도구를 장착하고, 실행 과정을 이해하며, 견고한 검증 절차를 따르는 것은 CrewAI의 잠재력을 극대화하는 데 필수적입니다.
-이를 통해 에이전트가 할당된 작업에 효과적으로 준비되고, 작업이 의도대로 수행될 수 있습니다.
+이를 통해 에이전트가 할당된 작업에 효과적으로 준비되고, 작업이 의도대로 수행될 수 있습니다.

docs/ko/enterprise/features/integrations.mdx

@@ -58,7 +58,7 @@ Authentication Integrations를 사용하기 전에 다음이 준비되어 있는
 3. Authentication Integrations 섹션에서 원하는 서비스의 **Connect** 버튼을 클릭합니다.
 4. OAuth 인증 과정을 완료합니다.
 5. 사용 사례에 필요한 권한을 부여합니다.
-6. [CrewAI Enterprise](https://app.crewai.com) 계정 페이지 - https://app.crewai.com/crewai_plus/settings/account 에서 Enterprise Token을 받습니다.
+6. 완료! [CrewAI Enterprise](https://app.crewai.com)의 **Integration** 탭에서 Enterprise Token을 받습니다.
 
 <Frame>
   ![Integrations](/images/enterprise/enterprise_action_auth_token.png)
@@ -176,4 +176,4 @@ crew를 배포하고 각 통합을 특정 사용자에게 범위 지정할 수
 
 <Card title="도움이 필요하신가요?" icon="headset" href="mailto:support@crewai.com">
   통합 설정이나 문제 해결에 대한 지원이 필요하시면 저희 지원팀에 문의하세요.
-</Card>
+</Card>

docs/ko/enterprise/guides/automation-triggers.mdx

@@ -0,0 +1,171 @@
+---
+title: "자동화 트리거"
+description: "연결된 통합에서 특정 이벤트가 발생할 때 CrewAI 워크플로우를 자동으로 실행합니다"
+icon: "bolt"
+---
+
+자동화 트리거를 사용하면 연결된 통합에서 특정 이벤트가 발생할 때 CrewAI 배포를 자동으로 실행할 수 있어, 비즈니스 시스템의 실시간 변화에 반응하는 강력한 이벤트 기반 워크플로우를 만들 수 있습니다.
+
+## 개요
+
+자동화 트리거를 사용하면 다음을 수행할 수 있습니다:
+
+- **실시간 이벤트에 응답** - 특정 조건이 충족될 때 워크플로우를 자동으로 실행
+- **외부 시스템과 통합** - Gmail, Outlook, OneDrive, JIRA, Slack, Stripe 등의 플랫폼과 연결
+- **자동화 확장** - 수동 개입 없이 대용량 이벤트 처리
+- **컨텍스트 유지** - crew와 flow 내에서 트리거 데이터에 액세스
+
+## 자동화 트리거 관리
+
+### 사용 가능한 트리거 보기
+
+자동화 트리거에 액세스하고 관리하려면:
+
+1. CrewAI 대시보드에서 배포로 이동
+2. **트리거** 탭을 클릭하여 사용 가능한 모든 트리거 통합 보기
+
+<Frame>
+  <img src="/images/enterprise/list-available-triggers.png" alt="사용 가능한 자동화 트리거 목록" />
+</Frame>
+
+이 보기는 배포에 사용 가능한 모든 트리거 통합과 현재 연결 상태를 보여줍니다.
+
+### 트리거 활성화 및 비활성화
+
+각 트리거는 토글 스위치를 사용하여 쉽게 활성화하거나 비활성화할 수 있습니다:
+
+<Frame>
+  <img src="/images/enterprise/trigger-selected.png" alt="토글로 트리거 활성화 또는 비활성화" />
+</Frame>
+
+- **활성화됨 (파란색 토글)**: 트리거가 활성 상태이며 지정된 이벤트가 발생할 때 배포를 자동으로 실행합니다
+- **비활성화됨 (회색 토글)**: 트리거가 비활성 상태이며 이벤트에 응답하지 않습니다
+
+토글을 클릭하기만 하면 트리거 상태를 변경할 수 있습니다. 변경 사항은 즉시 적용됩니다.
+
+### 트리거 실행 모니터링
+
+트리거된 실행의 성능과 기록을 추적합니다:
+
+<Frame>
+  <img src="/images/enterprise/list-executions.png" alt="자동화에 의해 트리거된 실행 목록" />
+</Frame>
+
+## 자동화 구축
+
+자동화를 구축하기 전에 crew와 flow가 받을 트리거 페이로드의 구조를 이해하는 것이 도움이 됩니다.
+
+### 페이로드 샘플 저장소
+
+자동화를 구축하고 테스트하는 데 도움이 되도록 다양한 트리거 소스의 샘플 페이로드가 포함된 포괄적인 저장소를 유지 관리하고 있습니다:
+
+**🔗 [CrewAI Enterprise 트리거 페이로드 샘플](https://github.com/crewAIInc/crewai-enterprise-trigger-payload-samples)**
+
+이 저장소에는 다음이 포함되어 있습니다:
+
+- **실제 페이로드 예제** - 다양한 트리거 소스(Gmail, Google Drive 등)에서 가져온 예제
+- **페이로드 구조 문서** - 형식과 사용 가능한 필드를 보여주는 문서
+
+### Crew와 트리거
+
+기존 crew 정의는 트리거와 완벽하게 작동하며, 받은 페이로드를 분석하는 작업만 있으면 됩니다:
+
+```python
+@CrewBase
+class MyAutomatedCrew:
+    @agent
+    def researcher(self) -> Agent:
+        return Agent(
+            config=self.agents_config['researcher'],
+        )
+
+    @task
+    def parse_trigger_payload(self) -> Task:
+        return Task(
+            config=self.tasks_config['parse_trigger_payload'],
+            agent=self.researcher(),
+        )
+
+    @task
+    def analyze_trigger_content(self) -> Task:
+        return Task(
+            config=self.tasks_config['analyze_trigger_data'],
+            agent=self.researcher(),
+        )
+```
+
+crew는 자동으로 트리거 페이로드를 받고 표준 CrewAI 컨텍스트 메커니즘을 통해 액세스할 수 있습니다.
+
+### Flow와의 통합
+
+flow의 경우 트리거 데이터 처리 방법을 더 세밀하게 제어할 수 있습니다:
+
+#### 트리거 페이로드 액세스
+
+flow의 모든 `@start()` 메서드는 `crewai_trigger_payload`라는 추가 매개변수를 허용합니다:
+
+```python
+from crewai.flow import Flow, start, listen
+
+class MyAutomatedFlow(Flow):
+    @start()
+    def handle_trigger(self, crewai_trigger_payload: dict = None):
+        """
+        이 start 메서드는 트리거 데이터를 받을 수 있습니다
+        """
+        if crewai_trigger_payload:
+            # 트리거 데이터 처리
+            trigger_id = crewai_trigger_payload.get('id')
+            event_data = crewai_trigger_payload.get('payload', {})
+
+            # 다른 메서드에서 사용할 수 있도록 flow 상태에 저장
+            self.state.trigger_id = trigger_id
+            self.state.trigger_type = event_data
+
+            return event_data
+
+        # 수동 실행 처리
+        return None
+
+    @listen(handle_trigger)
+    def process_data(self, trigger_data):
+        """
+        트리거 데이터 처리
+        """
+        # ... 트리거 처리
+```
+
+#### Flow에서 Crew 트리거하기
+
+트리거된 flow 내에서 crew를 시작할 때 트리거 페이로드를 전달합니다:
+
+```python
+@start()
+def delegate_to_crew(self, crewai_trigger_payload: dict = None):
+    """
+    전문 crew에 처리 위임
+    """
+    crew = MySpecializedCrew()
+
+    # crew에 트리거 페이로드 전달
+    result = crew.crew().kickoff(
+        inputs={
+            'a_custom_parameter': "custom_value",
+            'crewai_trigger_payload': crewai_trigger_payload
+        },
+    )
+
+    return result
+```
+
+## 문제 해결
+
+**트리거가 작동하지 않는 경우:**
+- 트리거가 활성화되어 있는지 확인
+- 통합 연결 상태 확인
+
+**실행 실패:**
+- 오류 세부 정보는 실행 로그 확인
+- 개발 중인 경우 입력에 올바른 페이로드가 포함된 `crewai_trigger_payload` 매개변수가 포함되어 있는지 확인
+
+자동화 트리거는 CrewAI 배포를 기존 비즈니스 프로세스 및 도구와 완벽하게 통합할 수 있는 반응형 이벤트 기반 시스템으로 변환합니다.

docs/pt-BR/concepts/event-listener.mdx

@@ -44,12 +44,12 @@ Para criar um listener de evento personalizado, você precisa:
 Veja um exemplo simples de uma classe de listener de evento personalizado:
 
 ```python
-from crewai.utilities.events import (
+from crewai.events import (
     CrewKickoffStartedEvent,
     CrewKickoffCompletedEvent,
     AgentExecutionCompletedEvent,
 )
-from crewai.utilities.events.base_event_listener import BaseEventListener
+from crewai.events import BaseEventListener
 
 class MeuListenerPersonalizado(BaseEventListener):
     def __init__(self):
@@ -146,7 +146,7 @@ my_project/
 
 ```python
 # my_custom_listener.py
-from crewai.utilities.events.base_event_listener import BaseEventListener
+from crewai.events import BaseEventListener
 # ... importe events ...
 
 class MyCustomListener(BaseEventListener):
@@ -268,7 +268,7 @@ Campos adicionais variam pelo tipo de evento. Por exemplo, `CrewKickoffCompleted
 Para lidar temporariamente com eventos (útil para testes ou operações específicas), você pode usar o context manager `scoped_handlers`:
 
 ```python
-from crewai.utilities.events import crewai_event_bus, CrewKickoffStartedEvent
+from crewai.events import crewai_event_bus, CrewKickoffStartedEvent
 
 with crewai_event_bus.scoped_handlers():
     @crewai_event_bus.on(CrewKickoffStartedEvent)

docs/pt-BR/concepts/knowledge.mdx

@@ -681,11 +681,11 @@ O CrewAI emite eventos durante o processo de recuperação de knowledge que voc
 #### Exemplo: Monitorando Recuperação de Knowledge
 
 ```python
-from crewai.utilities.events import (
+from crewai.events import (
     KnowledgeRetrievalStartedEvent,
     KnowledgeRetrievalCompletedEvent,
+    BaseEventListener,
 )
-from crewai.utilities.events.base_event_listener import BaseEventListener
 
 class KnowledgeMonitorListener(BaseEventListener):
     def setup_listeners(self, crewai_event_bus):

docs/pt-BR/concepts/llms.mdx

@@ -708,10 +708,10 @@ O CrewAI suporta respostas em streaming de LLMs, permitindo que sua aplicação
     O CrewAI emite eventos para cada chunk recebido durante o streaming:
 
     ```python
-    from crewai.utilities.events import (
+    from crewai.events import (
       LLMStreamChunkEvent
     )
-    from crewai.utilities.events.base_event_listener import BaseEventListener
+    from crewai.events import BaseEventListener
 
     class MyCustomListener(BaseEventListener):
         def setup_listeners(self, crewai_event_bus):

docs/pt-BR/concepts/tasks.mdx

@@ -59,6 +59,7 @@ crew = Crew(
 | **Output Pydantic** _(opcional)_ | `output_pydantic` | `Optional[Type[BaseModel]]`  | Um modelo Pydantic para a saída da tarefa.                                                                         |
 | **Callback** _(opcional)_        | `callback`        | `Optional[Any]`              | Função/objeto a ser executado após a conclusão da tarefa.                                                          |
 | **Guardrail** _(opcional)_       | `guardrail`       | `Optional[Callable]`             | Função para validar a saída da tarefa antes de prosseguir para a próxima tarefa.                                |
+| **Max Tentativas Guardrail** _(opcional)_ | `guardrail_max_retries` | `Optional[int]`    | Número máximo de tentativas quando a validação do guardrail falha. Padrão é 3.                                   |
 
 ## Criando Tarefas
 
@@ -450,7 +451,7 @@ task = Task(
     expected_output="Um objeto JSON válido",
     agent=analyst,
     guardrail=validate_json_output,
-    max_retries=3  # Limite de tentativas
+    guardrail_max_retries=3  # Limite de tentativas
 )
 ```
 
@@ -935,7 +936,7 @@ task = Task(
     description="Gerar dados",
     expected_output="Dados válidos",
     guardrail=validate_data,
-    max_retries=5  # Sobrescreve o limite padrão de tentativas
+    guardrail_max_retries=5  # Sobrescreve o limite padrão de tentativas
 )
 ```
 

docs/pt-BR/enterprise/features/integrations.mdx

@@ -58,7 +58,7 @@ Antes de usar as Integrações de Autenticação, certifique-se de que você pos
 3. Clique em **Conectar** no serviço desejado na seção Integrações de Autenticação
 4. Complete o fluxo de autenticação OAuth
 5. Conceda as permissões necessárias para seu caso de uso
-6. Obtenha seu Token Enterprise na sua página de conta do [CrewAI Enterprise](https://app.crewai.com) - https://app.crewai.com/crewai_plus/settings/account
+6. Pronto! Obtenha seu Token Enterprise do [CrewAI Enterprise](https://app.crewai.com) na aba **Integration**
 
 <Frame>
   ![Integrações](/images/enterprise/enterprise_action_auth_token.png)
@@ -176,4 +176,4 @@ Use o `user_bearer_token` para direcionar a integração a um usuário específi
 
 <Card title="Precisa de ajuda?" icon="headset" href="mailto:support@crewai.com">
   Entre em contato com nosso time de suporte para assistência com a configuração de integrações ou solução de problemas.
-</Card>
+</Card>

docs/pt-BR/enterprise/guides/automation-triggers.mdx

@@ -0,0 +1,171 @@
+---
+title: "Triggers de Automação"
+description: "Execute automaticamente seus workflows CrewAI quando eventos específicos ocorrem em integrações conectadas"
+icon: "bolt"
+---
+
+Os triggers de automação permitem executar automaticamente suas implantações CrewAI quando eventos específicos ocorrem em suas integrações conectadas, criando workflows poderosos orientados por eventos que respondem a mudanças em tempo real em seus sistemas de negócio.
+
+## Visão Geral
+
+Com triggers de automação, você pode:
+
+- **Responder a eventos em tempo real** - Execute workflows automaticamente quando condições específicas forem atendidas
+- **Integrar com sistemas externos** - Conecte com plataformas como Gmail, Outlook, OneDrive, JIRA, Slack, Stripe e muito mais
+- **Escalar sua automação** - Lide com eventos de alto volume sem intervenção manual
+- **Manter contexto** - Acesse dados do trigger dentro de suas crews e flows
+
+## Gerenciando Triggers de Automação
+
+### Visualizando Triggers Disponíveis
+
+Para acessar e gerenciar seus triggers de automação:
+
+1. Navegue até sua implantação no painel do CrewAI
+2. Clique na aba **Triggers** para visualizar todas as integrações de trigger disponíveis
+
+<Frame>
+  <img src="/images/enterprise/list-available-triggers.png" alt="Lista de triggers de automação disponíveis" />
+</Frame>
+
+Esta visualização mostra todas as integrações de trigger disponíveis para sua implantação, junto com seus status de conexão atuais.
+
+### Habilitando e Desabilitando Triggers
+
+Cada trigger pode ser facilmente habilitado ou desabilitado usando o botão de alternância:
+
+<Frame>
+  <img src="/images/enterprise/trigger-selected.png" alt="Habilitar ou desabilitar triggers com alternância" />
+</Frame>
+
+- **Habilitado (alternância azul)**: O trigger está ativo e executará automaticamente sua implantação quando os eventos especificados ocorrerem
+- **Desabilitado (alternância cinza)**: O trigger está inativo e não responderá a eventos
+
+Simplesmente clique na alternância para mudar o estado do trigger. As alterações entram em vigor imediatamente.
+
+### Monitorando Execuções de Trigger
+
+Acompanhe o desempenho e histórico de suas execuções acionadas:
+
+<Frame>
+  <img src="/images/enterprise/list-executions.png" alt="Lista de execuções acionadas por automação" />
+</Frame>
+
+## Construindo Automação
+
+Antes de construir sua automação, é útil entender a estrutura dos payloads de trigger que suas crews e flows receberão.
+
+### Repositório de Amostras de Payload
+
+Mantemos um repositório abrangente com amostras de payload de várias fontes de trigger para ajudá-lo a construir e testar suas automações:
+
+**🔗 [Amostras de Payload de Trigger CrewAI Enterprise](https://github.com/crewAIInc/crewai-enterprise-trigger-payload-samples)**
+
+Este repositório contém:
+
+- **Exemplos reais de payload** de diferentes fontes de trigger (Gmail, Google Drive, etc.)
+- **Documentação da estrutura de payload** mostrando o formato e campos disponíveis
+
+### Triggers com Crew
+
+Suas definições de crew existentes funcionam perfeitamente com triggers, você só precisa ter uma tarefa para analisar o payload recebido:
+
+```python
+@CrewBase
+class MinhaCrewAutomatizada:
+    @agent
+    def pesquisador(self) -> Agent:
+        return Agent(
+            config=self.agents_config['pesquisador'],
+        )
+
+    @task
+    def analisar_payload_trigger(self) -> Task:
+        return Task(
+            config=self.tasks_config['analisar_payload_trigger'],
+            agent=self.pesquisador(),
+        )
+
+    @task
+    def analisar_conteudo_trigger(self) -> Task:
+        return Task(
+            config=self.tasks_config['analisar_dados_trigger'],
+            agent=self.pesquisador(),
+        )
+```
+
+A crew receberá automaticamente e pode acessar o payload do trigger através dos mecanismos de contexto padrão do CrewAI.
+
+### Integração com Flows
+
+Para flows, você tem mais controle sobre como os dados do trigger são tratados:
+
+#### Acessando Payload do Trigger
+
+Todos os métodos `@start()` em seus flows aceitarão um parâmetro adicional chamado `crewai_trigger_payload`:
+
+```python
+from crewai.flow import Flow, start, listen
+
+class MeuFlowAutomatizado(Flow):
+    @start()
+    def lidar_com_trigger(self, crewai_trigger_payload: dict = None):
+        """
+        Este método start pode receber dados do trigger
+        """
+        if crewai_trigger_payload:
+            # Processa os dados do trigger
+            trigger_id = crewai_trigger_payload.get('id')
+            dados_evento = crewai_trigger_payload.get('payload', {})
+
+            # Armazena no estado do flow para uso por outros métodos
+            self.state.trigger_id = trigger_id
+            self.state.trigger_type = dados_evento
+
+            return dados_evento
+
+        # Lida com execução manual
+        return None
+
+    @listen(lidar_com_trigger)
+    def processar_dados(self, dados_trigger):
+        """
+        Processa os dados do trigger
+        """
+        # ... processa o trigger
+```
+
+#### Acionando Crews a partir de Flows
+
+Ao iniciar uma crew dentro de um flow que foi acionado, passe o payload do trigger conforme ele:
+
+```python
+@start()
+def delegar_para_crew(self, crewai_trigger_payload: dict = None):
+    """
+    Delega processamento para uma crew especializada
+    """
+    crew = MinhaCrewEspecializada()
+
+    # Passa o payload do trigger para a crew
+    resultado = crew.crew().kickoff(
+        inputs={
+            'parametro_personalizado': "valor_personalizado",
+            'crewai_trigger_payload': crewai_trigger_payload
+        },
+    )
+
+    return resultado
+```
+
+## Solução de Problemas
+
+**Trigger não está sendo disparado:**
+- Verifique se o trigger está habilitado
+- Verifique o status de conexão da integração
+
+**Falhas de execução:**
+- Verifique os logs de execução para detalhes do erro
+- Se você está desenvolvendo, certifique-se de que as entradas incluem o parâmetro `crewai_trigger_payload` com o payload correto
+
+Os triggers de automação transformam suas implantações CrewAI em sistemas responsivos orientados por eventos que podem se integrar perfeitamente com seus processos de negócio e ferramentas existentes.

pyproject.toml

@@ -48,7 +48,7 @@ Documentation = "https://docs.crewai.com"
 Repository = "https://github.com/crewAIInc/crewAI"
 
 [project.optional-dependencies]
-tools = ["crewai-tools~=0.62.1"]
+tools = ["crewai-tools~=0.69.0"]
 embeddings = [
     "tiktoken~=0.8.0"
 ]
@@ -68,12 +68,16 @@ docling = [
 aisuite = [
     "aisuite>=0.1.10",
 ]
+qdrant = [
+    "qdrant-client[fastembed]>=1.14.3",
+]
 
 [tool.uv]
 dev-dependencies = [
-    "ruff>=0.8.2",
-    "mypy>=1.10.0",
-    "pre-commit>=3.6.0",
+    "ruff>=0.12.11",
+    "mypy>=1.17.1",
+    "pre-commit>=4.3.0",
+    "bandit>=1.8.6",
     "pillow>=10.2.0",
     "cairosvg>=2.7.1",
     "pytest>=8.0.0",
@@ -85,15 +89,41 @@ dev-dependencies = [
     "pytest-timeout>=2.3.1",
     "pytest-xdist>=3.6.1",
     "pytest-split>=0.9.0",
+    "types-requests==2.32.*",
+    "types-pyyaml==6.0.*",
+    "types-regex==2024.11.6.*",
+    "types-appdirs==1.4.*",
 ]
 
 [project.scripts]
 crewai = "crewai.cli.cli:crewai"
 
+[tool.ruff]
+exclude = [
+    "src/crewai/cli/templates",
+]
+fix = true
+
+[tool.ruff.lint]
+select = [
+    "B006",
+    "UP006",
+    "UP007",
+    "UP035",
+    "UP037",
+    "UP004",
+    "UP008",
+    "UP010",
+    "UP018",
+    "UP031",
+    "UP032",
+    "I001",
+    "I002",
+]
+
 [tool.mypy]
-ignore_missing_imports = true
-disable_error_code = 'import-untyped'
-exclude = ["cli/templates"]
+strict = true
+exclude = ["src/crewai/cli/templates"]
 
 [tool.bandit]
 exclude_dirs = ["src/crewai/cli/templates"]

src/crewai/__init__.py

@@ -1,4 +1,30 @@
 import warnings
+from typing import Any
+
+
+def _suppress_pydantic_deprecation_warnings() -> None:
+    """Suppress Pydantic deprecation warnings using targeted monkey patch."""
+    original_warn = warnings.warn
+
+    def filtered_warn(
+        message: Any,
+        category: type | None = None,
+        stacklevel: int = 1,
+        source: Any = None,
+    ) -> Any:
+        if (
+            category
+            and hasattr(category, "__module__")
+            and category.__module__ == "pydantic.warnings"
+        ):
+            return None
+        return original_warn(message, category, stacklevel + 1, source)
+
+    setattr(warnings, "warn", filtered_warn)
+
+
+_suppress_pydantic_deprecation_warnings()
+
 import threading
 import urllib.request
 
@@ -15,17 +41,10 @@ from crewai.tasks.llm_guardrail import LLMGuardrail
 from crewai.tasks.task_output import TaskOutput
 from crewai.telemetry.telemetry import Telemetry
 
-warnings.filterwarnings(
-    "ignore",
-    message="Pydantic serializer warnings:",
-    category=UserWarning,
-    module="pydantic.main",
-)
-
 _telemetry_submitted = False
 
 
-def _track_install():
+def _track_install() -> None:
     """Track package installation/first-use via Scarf analytics."""
     global _telemetry_submitted
 
@@ -36,7 +55,7 @@ def _track_install():
         pixel_url = "https://api.scarf.sh/v2/packages/CrewAI/crewai/docs/00f2dad1-8334-4a39-934e-003b2e1146db"
 
         req = urllib.request.Request(pixel_url)
-        req.add_header('User-Agent', f'CrewAI-Python/{__version__}')
+        req.add_header("User-Agent", f"CrewAI-Python/{__version__}")
 
         with urllib.request.urlopen(req, timeout=2):  # nosec B310
             _telemetry_submitted = True
@@ -45,7 +64,7 @@ def _track_install():
         pass
 
 
-def _track_install_async():
+def _track_install_async() -> None:
     """Track installation in background thread to avoid blocking imports."""
     if not Telemetry._is_telemetry_disabled():
         thread = threading.Thread(target=_track_install, daemon=True)
@@ -54,7 +73,7 @@ def _track_install_async():
 
 _track_install_async()
 
-__version__ = "0.165.1"
+__version__ = "0.177.0"
 __all__ = [
     "Agent",
     "Crew",

src/crewai/agent.py

@@ -1,7 +1,18 @@
 import shutil
 import subprocess
 import time
-from typing import Any, Callable, Dict, List, Literal, Optional, Sequence, Tuple, Type, Union
+from typing import (
+    Any,
+    Callable,
+    Dict,
+    List,
+    Literal,
+    Optional,
+    Sequence,
+    Tuple,
+    Type,
+    Union,
+)
 
 from pydantic import Field, InstanceOf, PrivateAttr, model_validator
 
@@ -27,17 +38,17 @@ from crewai.utilities.agent_utils import (
 )
 from crewai.utilities.constants import TRAINED_AGENTS_DATA_FILE, TRAINING_DATA_FILE
 from crewai.utilities.converter import generate_model_description
-from crewai.utilities.events.agent_events import (
+from crewai.events.types.agent_events import (
     AgentExecutionCompletedEvent,
     AgentExecutionErrorEvent,
     AgentExecutionStartedEvent,
 )
-from crewai.utilities.events.crewai_event_bus import crewai_event_bus
-from crewai.utilities.events.memory_events import (
+from crewai.events.event_bus import crewai_event_bus
+from crewai.events.types.memory_events import (
     MemoryRetrievalStartedEvent,
     MemoryRetrievalCompletedEvent,
 )
-from crewai.utilities.events.knowledge_events import (
+from crewai.events.types.knowledge_events import (
     KnowledgeQueryCompletedEvent,
     KnowledgeQueryFailedEvent,
     KnowledgeQueryStartedEvent,
@@ -162,7 +173,7 @@ class Agent(BaseAgent):
     )
     guardrail: Optional[Union[Callable[[Any], Tuple[bool, Any]], str]] = Field(
         default=None,
-        description="Function or string description of a guardrail to validate agent output"
+        description="Function or string description of a guardrail to validate agent output",
     )
     guardrail_max_retries: int = Field(
         default=3, description="Maximum number of retries when guardrail fails"
@@ -276,7 +287,7 @@ class Agent(BaseAgent):
         self._inject_date_to_task(task)
 
         if self.tools_handler:
-            self.tools_handler.last_used_tool = {}  # type: ignore # Incompatible types in assignment (expression has type "dict[Never, Never]", variable has type "ToolCalling")
+            self.tools_handler.last_used_tool = None
 
         task_prompt = task.prompt()
 
@@ -309,15 +320,20 @@ class Agent(BaseAgent):
                 event=MemoryRetrievalStartedEvent(
                     task_id=str(task.id) if task else None,
                     source_type="agent",
+                    from_agent=self,
+                    from_task=task,
                 ),
             )
 
             start_time = time.time()
+
             contextual_memory = ContextualMemory(
                 self.crew._short_term_memory,
                 self.crew._long_term_memory,
                 self.crew._entity_memory,
                 self.crew._external_memory,
+                agent=self,
+                task=task,
             )
             memory = contextual_memory.build_context_for_task(task, context)
             if memory.strip() != "":
@@ -330,13 +346,14 @@ class Agent(BaseAgent):
                     memory_content=memory,
                     retrieval_time_ms=(time.time() - start_time) * 1000,
                     source_type="agent",
+                    from_agent=self,
+                    from_task=task,
                 ),
             )
         knowledge_config = (
             self.knowledge_config.model_dump() if self.knowledge_config else {}
         )
 
-
         if self.knowledge or (self.crew and self.crew.knowledge):
             crewai_event_bus.emit(
                 self,

src/crewai/agents/__init__.py

@@ -1,5 +1,5 @@
-from .cache.cache_handler import CacheHandler
-from .parser import CrewAgentParser
-from .tools_handler import ToolsHandler
+from crewai.agents.cache.cache_handler import CacheHandler
+from crewai.agents.parser import parse, AgentAction, AgentFinish, OutputParserException
+from crewai.agents.tools_handler import ToolsHandler
 
-__all__ = ["CacheHandler", "CrewAgentParser", "ToolsHandler"]
+__all__ = ["CacheHandler", "parse", "AgentAction", "AgentFinish", "OutputParserException", "ToolsHandler"]

src/crewai/agents/agent_adapters/langgraph/langgraph_adapter.py

@@ -1,4 +1,4 @@
-from typing import Any, AsyncIterable, Dict, List, Optional
+from typing import Any, Dict, List, Optional
 
 from pydantic import Field, PrivateAttr
 
@@ -14,15 +14,14 @@ from crewai.tools.agent_tools.agent_tools import AgentTools
 from crewai.tools.base_tool import BaseTool
 from crewai.utilities import Logger
 from crewai.utilities.converter import Converter
-from crewai.utilities.events import crewai_event_bus
-from crewai.utilities.events.agent_events import (
+from crewai.events.event_bus import crewai_event_bus
+from crewai.events.types.agent_events import (
     AgentExecutionCompletedEvent,
     AgentExecutionErrorEvent,
     AgentExecutionStartedEvent,
 )
 
 try:
-    from langchain_core.messages import ToolMessage
     from langgraph.checkpoint.memory import MemorySaver
     from langgraph.prebuilt import create_react_agent
 

src/crewai/agents/agent_adapters/openai_agents/openai_adapter.py

@@ -10,8 +10,8 @@ from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.tools import BaseTool
 from crewai.tools.agent_tools.agent_tools import AgentTools
 from crewai.utilities import Logger
-from crewai.utilities.events import crewai_event_bus
-from crewai.utilities.events.agent_events import (
+from crewai.events.event_bus import crewai_event_bus
+from crewai.events.types.agent_events import (
     AgentExecutionCompletedEvent,
     AgentExecutionErrorEvent,
     AgentExecutionStartedEvent,

src/crewai/agents/agent_builder/base_agent_executor_mixin.py

@@ -7,7 +7,7 @@ from crewai.utilities import I18N
 from crewai.utilities.converter import ConverterError
 from crewai.utilities.evaluators.task_evaluator import TaskEvaluator
 from crewai.utilities.printer import Printer
-from crewai.utilities.events.event_listener import event_listener
+from crewai.events.event_listener import event_listener
 
 if TYPE_CHECKING:
     from crewai.agents.agent_builder.base_agent import BaseAgent
@@ -43,7 +43,6 @@ class CrewAgentExecutorMixin:
                         metadata={
                             "observation": self.task.description,
                         },
-                        agent=self.agent.role,
                     )
             except Exception as e:
                 print(f"Failed to add to short term memory: {e}")
@@ -65,7 +64,6 @@ class CrewAgentExecutorMixin:
                         "description": self.task.description,
                         "messages": self.messages,
                     },
-                    agent=self.agent.role,
                 )
             except Exception as e:
                 print(f"Failed to add to external memory: {e}")
@@ -100,8 +98,8 @@ class CrewAgentExecutorMixin:
                 )
                 self.crew._long_term_memory.save(long_term_memory)
 
-                for entity in evaluation.entities:
-                    entity_memory = EntityMemoryItem(
+                entity_memories = [
+                    EntityMemoryItem(
                         name=entity.name,
                         type=entity.type,
                         description=entity.description,
@@ -109,7 +107,10 @@ class CrewAgentExecutorMixin:
                             [f"- {r}" for r in entity.relationships]
                         ),
                     )
-                    self.crew._entity_memory.save(entity_memory)
+                    for entity in evaluation.entities
+                ]
+                if entity_memories:
+                    self.crew._entity_memory.save(entity_memories)
             except AttributeError as e:
                 print(f"Missing attributes for long term memory: {e}")
                 pass
@@ -158,7 +159,9 @@ class CrewAgentExecutorMixin:
             self._printer.print(content=prompt, color="bold_yellow")
             response = input()
             if response.strip() != "":
-                self._printer.print(content="\nProcessing your feedback...", color="cyan")
+                self._printer.print(
+                    content="\nProcessing your feedback...", color="cyan"
+                )
             return response
         finally:
             event_listener.formatter.resume_live_updates()

src/crewai/agents/constants.py

@@ -0,0 +1,27 @@
+"""Constants for agent-related modules."""
+
+import re
+from typing import Final
+
+# crewai.agents.parser constants
+
+FINAL_ANSWER_ACTION: Final[str] = "Final Answer:"
+MISSING_ACTION_AFTER_THOUGHT_ERROR_MESSAGE: Final[str] = (
+    "I did it wrong. Invalid Format: I missed the 'Action:' after 'Thought:'. I will do right next, and don't use a tool I have already used.\n"
+)
+MISSING_ACTION_INPUT_AFTER_ACTION_ERROR_MESSAGE: Final[str] = (
+    "I did it wrong. Invalid Format: I missed the 'Action Input:' after 'Action:'. I will do right next, and don't use a tool I have already used.\n"
+)
+FINAL_ANSWER_AND_PARSABLE_ACTION_ERROR_MESSAGE: Final[str] = (
+    "I did it wrong. Tried to both perform Action and give a Final Answer at the same time, I must do one or the other"
+)
+UNABLE_TO_REPAIR_JSON_RESULTS: Final[list[str]] = ['""', "{}"]
+ACTION_INPUT_REGEX: Final[re.Pattern[str]] = re.compile(
+    r"Action\s*\d*\s*:\s*(.*?)\s*Action\s*\d*\s*Input\s*\d*\s*:\s*(.*)", re.DOTALL
+)
+ACTION_REGEX: Final[re.Pattern[str]] = re.compile(
+    r"Action\s*\d*\s*:\s*(.*?)", re.DOTALL
+)
+ACTION_INPUT_ONLY_REGEX: Final[re.Pattern[str]] = re.compile(
+    r"\s*Action\s*\d*\s*Input\s*\d*\s*:\s*(.*)", re.DOTALL
+)

src/crewai/agents/crew_agent_executor.py

@@ -30,11 +30,11 @@ from crewai.utilities.constants import MAX_LLM_RETRY, TRAINING_DATA_FILE
 from crewai.utilities.logger import Logger
 from crewai.utilities.tool_utils import execute_tool_and_check_finality
 from crewai.utilities.training_handler import CrewTrainingHandler
-from crewai.utilities.events.agent_events import (
+from crewai.events.types.logging_events import (
     AgentLogsStartedEvent,
     AgentLogsExecutionEvent,
 )
-from crewai.utilities.events.crewai_event_bus import crewai_event_bus
+from crewai.events.event_bus import crewai_event_bus
 
 
 class CrewAgentExecutor(CrewAgentExecutorMixin):
@@ -54,11 +54,11 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
         tools_description: str,
         tools_handler: ToolsHandler,
         step_callback: Any = None,
-        original_tools: List[Any] = [],
+        original_tools: List[Any] | None = None,
         function_calling_llm: Any = None,
         respect_context_window: bool = False,
         request_within_rpm_limit: Optional[Callable[[], bool]] = None,
-        callbacks: List[Any] = [],
+        callbacks: List[Any] | None = None,
     ):
         self._i18n: I18N = I18N()
         self.llm: BaseLLM = llm
@@ -70,10 +70,10 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
         self.tools_names = tools_names
         self.stop = stop_words
         self.max_iter = max_iter
-        self.callbacks = callbacks
+        self.callbacks = callbacks or []
         self._printer: Printer = Printer()
         self.tools_handler = tools_handler
-        self.original_tools = original_tools
+        self.original_tools = original_tools or []
         self.step_callback = step_callback
         self.use_stop_words = self.llm.supports_stop_words()
         self.tools_description = tools_description
@@ -122,7 +122,6 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
             handle_unknown_error(self._printer, e)
             raise
 
-
         if self.ask_for_human_input:
             formatted_answer = self._handle_human_feedback(formatted_answer)
 
@@ -156,7 +155,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                     messages=self.messages,
                     callbacks=self.callbacks,
                     printer=self._printer,
-                    from_task=self.task
+                    from_task=self.task,
                 )
                 formatted_answer = process_llm_response(answer, self.use_stop_words)
 

src/crewai/agents/parser.py

@@ -1,50 +1,67 @@
-import re
-from typing import Any, Optional, Union
+"""Agent output parsing module for ReAct-style LLM responses.
+
+This module provides parsing functionality for agent outputs that follow
+the ReAct (Reasoning and Acting) format, converting them into structured
+AgentAction or AgentFinish objects.
+"""
+
+from dataclasses import dataclass
 
 from json_repair import repair_json
 
+from crewai.agents.constants import (
+    ACTION_INPUT_REGEX,
+    ACTION_REGEX,
+    ACTION_INPUT_ONLY_REGEX,
+    FINAL_ANSWER_ACTION,
+    MISSING_ACTION_AFTER_THOUGHT_ERROR_MESSAGE,
+    MISSING_ACTION_INPUT_AFTER_ACTION_ERROR_MESSAGE,
+    UNABLE_TO_REPAIR_JSON_RESULTS,
+)
 from crewai.utilities import I18N
 
-FINAL_ANSWER_ACTION = "Final Answer:"
-MISSING_ACTION_AFTER_THOUGHT_ERROR_MESSAGE = "I did it wrong. Invalid Format: I missed the 'Action:' after 'Thought:'. I will do right next, and don't use a tool I have already used.\n"
-MISSING_ACTION_INPUT_AFTER_ACTION_ERROR_MESSAGE = "I did it wrong. Invalid Format: I missed the 'Action Input:' after 'Action:'. I will do right next, and don't use a tool I have already used.\n"
-FINAL_ANSWER_AND_PARSABLE_ACTION_ERROR_MESSAGE = "I did it wrong. Tried to both perform Action and give a Final Answer at the same time, I must do one or the other"
+_I18N = I18N()
 
 
+@dataclass
 class AgentAction:
+    """Represents an action to be taken by an agent."""
+
     thought: str
     tool: str
     tool_input: str
     text: str
-    result: str
-
-    def __init__(self, thought: str, tool: str, tool_input: str, text: str):
-        self.thought = thought
-        self.tool = tool
-        self.tool_input = tool_input
-        self.text = text
+    result: str | None = None
 
 
+@dataclass
 class AgentFinish:
+    """Represents the final answer from an agent."""
+
     thought: str
     output: str
     text: str
 
-    def __init__(self, thought: str, output: str, text: str):
-        self.thought = thought
-        self.output = output
-        self.text = text
-
 
 class OutputParserException(Exception):
-    error: str
+    """Exception raised when output parsing fails.
 
-    def __init__(self, error: str):
+    Attributes:
+        error: The error message.
+    """
+
+    def __init__(self, error: str) -> None:
+        """Initialize OutputParserException.
+
+        Args:
+            error: The error message.
+        """
         self.error = error
+        super().__init__(error)
 
 
-class CrewAgentParser:
-    """Parses ReAct-style LLM calls that have a single tool input.
+def parse(text: str) -> AgentAction | AgentFinish:
+    """Parse agent output text into AgentAction or AgentFinish.
 
     Expects output to be in one of two formats.
 
@@ -62,108 +79,117 @@ class CrewAgentParser:
 
     Thought: agent thought here
     Final Answer: The temperature is 100 degrees
+
+    Args:
+        text: The agent output text to parse.
+
+    Returns:
+        AgentAction or AgentFinish based on the content.
+
+    Raises:
+        OutputParserException: If the text format is invalid.
     """
+    thought = _extract_thought(text)
+    includes_answer = FINAL_ANSWER_ACTION in text
+    action_match = ACTION_INPUT_REGEX.search(text)
 
-    _i18n: I18N = I18N()
-    agent: Any = None
+    if includes_answer:
+        final_answer = text.split(FINAL_ANSWER_ACTION)[-1].strip()
+        # Check whether the final answer ends with triple backticks.
+        if final_answer.endswith("```"):
+            # Count occurrences of triple backticks in the final answer.
+            count = final_answer.count("```")
+            # If count is odd then it's an unmatched trailing set; remove it.
+            if count % 2 != 0:
+                final_answer = final_answer[:-3].rstrip()
+        return AgentFinish(thought=thought, output=final_answer, text=text)
 
-    def __init__(self, agent: Optional[Any] = None):
-        self.agent = agent
+    elif action_match:
+        action = action_match.group(1)
+        clean_action = _clean_action(action)
 
-    @staticmethod
-    def parse_text(text: str) -> Union[AgentAction, AgentFinish]:
-        """
-        Static method to parse text into an AgentAction or AgentFinish without needing to instantiate the class.
+        action_input = action_match.group(2).strip()
 
-        Args:
-            text: The text to parse.
+        tool_input = action_input.strip(" ").strip('"')
+        safe_tool_input = _safe_repair_json(tool_input)
 
-        Returns:
-            Either an AgentAction or AgentFinish based on the parsed content.
-        """
-        parser = CrewAgentParser()
-        return parser.parse(text)
-
-    def parse(self, text: str) -> Union[AgentAction, AgentFinish]:
-        thought = self._extract_thought(text)
-        includes_answer = FINAL_ANSWER_ACTION in text
-        regex = (
-            r"Action\s*\d*\s*:[\s]*(.*?)[\s]*Action\s*\d*\s*Input\s*\d*\s*:[\s]*(.*)"
+        return AgentAction(
+            thought=thought, tool=clean_action, tool_input=safe_tool_input, text=text
         )
-        action_match = re.search(regex, text, re.DOTALL)
-        if includes_answer:
-            final_answer = text.split(FINAL_ANSWER_ACTION)[-1].strip()
-            # Check whether the final answer ends with triple backticks.
-            if final_answer.endswith("```"):
-                # Count occurrences of triple backticks in the final answer.
-                count = final_answer.count("```")
-                # If count is odd then it's an unmatched trailing set; remove it.
-                if count % 2 != 0:
-                    final_answer = final_answer[:-3].rstrip()
-            return AgentFinish(thought, final_answer, text)
 
-        elif action_match:
-            action = action_match.group(1)
-            clean_action = self._clean_action(action)
+    if not ACTION_REGEX.search(text):
+        raise OutputParserException(
+            f"{MISSING_ACTION_AFTER_THOUGHT_ERROR_MESSAGE}\n{_I18N.slice('final_answer_format')}",
+        )
+    elif not ACTION_INPUT_ONLY_REGEX.search(text):
+        raise OutputParserException(
+            MISSING_ACTION_INPUT_AFTER_ACTION_ERROR_MESSAGE,
+        )
+    else:
+        err_format = _I18N.slice("format_without_tools")
+        error = f"{err_format}"
+        raise OutputParserException(
+            error,
+        )
 
-            action_input = action_match.group(2).strip()
 
-            tool_input = action_input.strip(" ").strip('"')
-            safe_tool_input = self._safe_repair_json(tool_input)
+def _extract_thought(text: str) -> str:
+    """Extract the thought portion from the text.
 
-            return AgentAction(thought, clean_action, safe_tool_input, text)
+    Args:
+        text: The full agent output text.
 
-        if not re.search(r"Action\s*\d*\s*:[\s]*(.*?)", text, re.DOTALL):
-            raise OutputParserException(
-                f"{MISSING_ACTION_AFTER_THOUGHT_ERROR_MESSAGE}\n{self._i18n.slice('final_answer_format')}",
-            )
-        elif not re.search(
-            r"[\s]*Action\s*\d*\s*Input\s*\d*\s*:[\s]*(.*)", text, re.DOTALL
-        ):
-            raise OutputParserException(
-                MISSING_ACTION_INPUT_AFTER_ACTION_ERROR_MESSAGE,
-            )
-        else:
-            format = self._i18n.slice("format_without_tools")
-            error = f"{format}"
-            raise OutputParserException(
-                error,
-            )
+    Returns:
+        The extracted thought string.
+    """
+    thought_index = text.find("\nAction")
+    if thought_index == -1:
+        thought_index = text.find("\nFinal Answer")
+    if thought_index == -1:
+        return ""
+    thought = text[:thought_index].strip()
+    # Remove any triple backticks from the thought string
+    thought = thought.replace("```", "").strip()
+    return thought
 
-    def _extract_thought(self, text: str) -> str:
-        thought_index = text.find("\nAction")
-        if thought_index == -1:
-            thought_index = text.find("\nFinal Answer")
-        if thought_index == -1:
-            return ""
-        thought = text[:thought_index].strip()
-        # Remove any triple backticks from the thought string
-        thought = thought.replace("```", "").strip()
-        return thought
 
-    def _clean_action(self, text: str) -> str:
-        """Clean action string by removing non-essential formatting characters."""
-        return text.strip().strip("*").strip()
+def _clean_action(text: str) -> str:
+    """Clean action string by removing non-essential formatting characters.
 
-    def _safe_repair_json(self, tool_input: str) -> str:
-        UNABLE_TO_REPAIR_JSON_RESULTS = ['""', "{}"]
+    Args:
+        text: The action text to clean.
 
-        # Skip repair if the input starts and ends with square brackets
-        # Explanation: The JSON parser has issues handling inputs that are enclosed in square brackets ('[]').
-        # These are typically valid JSON arrays or strings that do not require repair. Attempting to repair such inputs
-        # might lead to unintended alterations, such as wrapping the entire input in additional layers or modifying
-        # the structure in a way that changes its meaning. By skipping the repair for inputs that start and end with
-        # square brackets, we preserve the integrity of these valid JSON structures and avoid unnecessary modifications.
-        if tool_input.startswith("[") and tool_input.endswith("]"):
-            return tool_input
+    Returns:
+        The cleaned action string.
+    """
+    return text.strip().strip("*").strip()
 
-        # Before repair, handle common LLM issues:
-        # 1. Replace """ with " to avoid JSON parser errors
 
-        tool_input = tool_input.replace('"""', '"')
+def _safe_repair_json(tool_input: str) -> str:
+    """Safely repair JSON input.
 
-        result = repair_json(tool_input)
-        if result in UNABLE_TO_REPAIR_JSON_RESULTS:
-            return tool_input
+    Args:
+        tool_input: The tool input string to repair.
 
-        return str(result)
+    Returns:
+        The repaired JSON string or original if repair fails.
+    """
+    # Skip repair if the input starts and ends with square brackets
+    # Explanation: The JSON parser has issues handling inputs that are enclosed in square brackets ('[]').
+    # These are typically valid JSON arrays or strings that do not require repair. Attempting to repair such inputs
+    # might lead to unintended alterations, such as wrapping the entire input in additional layers or modifying
+    # the structure in a way that changes its meaning. By skipping the repair for inputs that start and end with
+    # square brackets, we preserve the integrity of these valid JSON structures and avoid unnecessary modifications.
+    if tool_input.startswith("[") and tool_input.endswith("]"):
+        return tool_input
+
+    # Before repair, handle common LLM issues:
+    # 1. Replace """ with " to avoid JSON parser errors
+
+    tool_input = tool_input.replace('"""', '"')
+
+    result = repair_json(tool_input)
+    if result in UNABLE_TO_REPAIR_JSON_RESULTS:
+        return tool_input
+
+    return str(result)

src/crewai/agents/tools_handler.py

@@ -1,29 +1,41 @@
-from typing import Any, Optional, Union
+"""Tools handler for managing tool execution and caching."""
 
-from ..tools.cache_tools.cache_tools import CacheTools
-from ..tools.tool_calling import InstructorToolCalling, ToolCalling
-from .cache.cache_handler import CacheHandler
+from crewai.tools.cache_tools.cache_tools import CacheTools
+from crewai.tools.tool_calling import InstructorToolCalling, ToolCalling
+from crewai.agents.cache.cache_handler import CacheHandler
 
 
 class ToolsHandler:
-    """Callback handler for tool usage."""
+    """Callback handler for tool usage.
 
-    last_used_tool: ToolCalling = {}  # type: ignore # BUG?: Incompatible types in assignment (expression has type "Dict[...]", variable has type "ToolCalling")
-    cache: Optional[CacheHandler]
+    Attributes:
+        last_used_tool: The most recently used tool calling instance.
+        cache: Optional cache handler for storing tool outputs.
+    """
 
-    def __init__(self, cache: Optional[CacheHandler] = None):
-        """Initialize the callback handler."""
-        self.cache = cache
-        self.last_used_tool = {}  # type: ignore # BUG?: same as above
+    def __init__(self, cache: CacheHandler | None = None) -> None:
+        """Initialize the callback handler.
+
+        Args:
+            cache: Optional cache handler for storing tool outputs.
+        """
+        self.cache: CacheHandler | None = cache
+        self.last_used_tool: ToolCalling | InstructorToolCalling | None = None
 
     def on_tool_use(
         self,
-        calling: Union[ToolCalling, InstructorToolCalling],
+        calling: ToolCalling | InstructorToolCalling,
         output: str,
         should_cache: bool = True,
-    ) -> Any:
-        """Run when tool ends running."""
-        self.last_used_tool = calling  # type: ignore # BUG?: Incompatible types in assignment (expression has type "Union[ToolCalling, InstructorToolCalling]", variable has type "ToolCalling")
+    ) -> None:
+        """Run when tool ends running.
+
+        Args:
+            calling: The tool calling instance.
+            output: The output from the tool execution.
+            should_cache: Whether to cache the tool output.
+        """
+        self.last_used_tool = calling
         if self.cache and should_cache and calling.tool_name != CacheTools().name:
             self.cache.add(
                 tool=calling.tool_name,

src/crewai/cli/authentication/constants.py

@@ -1,6 +1 @@
 ALGORITHMS = ["RS256"]
-
-#TODO: The AUTH0 constants should be removed after WorkOS migration is completed
-AUTH0_DOMAIN = "crewai.us.auth0.com"
-AUTH0_CLIENT_ID = "DEVC5Fw6NlRoSzmDCcOhVq85EfLBjKa8"
-AUTH0_AUDIENCE = "https://crewai.us.auth0.com/api/v2/"

src/crewai/cli/authentication/main.py

@@ -7,24 +7,27 @@ from rich.console import Console
 from pydantic import BaseModel, Field
 
 
-from .utils import TokenManager, validate_jwt_token
-from urllib.parse import quote
-from crewai.cli.plus_api import PlusAPI
+from .utils import validate_jwt_token
+from crewai.cli.shared.token_manager import TokenManager
 from crewai.cli.config import Settings
-from crewai.cli.authentication.constants import (
-    AUTH0_AUDIENCE,
-    AUTH0_CLIENT_ID,
-    AUTH0_DOMAIN,
-)
 
 console = Console()
 
 
 class Oauth2Settings(BaseModel):
-    provider: str = Field(description="OAuth2 provider used for authentication (e.g., workos, okta, auth0).")
-    client_id: str = Field(description="OAuth2 client ID issued by the provider, used during authentication requests.")
-    domain: str = Field(description="OAuth2 provider's domain (e.g., your-org.auth0.com) used for issuing tokens.")
-    audience: Optional[str] = Field(description="OAuth2 audience value, typically used to identify the target API or resource.", default=None)
+    provider: str = Field(
+        description="OAuth2 provider used for authentication (e.g., workos, okta, auth0)."
+    )
+    client_id: str = Field(
+        description="OAuth2 client ID issued by the provider, used during authentication requests."
+    )
+    domain: str = Field(
+        description="OAuth2 provider's domain (e.g., your-org.auth0.com) used for issuing tokens."
+    )
+    audience: Optional[str] = Field(
+        description="OAuth2 audience value, typically used to identify the target API or resource.",
+        default=None,
+    )
 
     @classmethod
     def from_settings(cls):
@@ -44,11 +47,15 @@ class ProviderFactory:
         settings = settings or Oauth2Settings.from_settings()
 
         import importlib
-        module = importlib.import_module(f"crewai.cli.authentication.providers.{settings.provider.lower()}")
+
+        module = importlib.import_module(
+            f"crewai.cli.authentication.providers.{settings.provider.lower()}"
+        )
         provider = getattr(module, f"{settings.provider.capitalize()}Provider")
 
         return provider(settings)
 
+
 class AuthenticationCommand:
     def __init__(self):
         self.token_manager = TokenManager()
@@ -58,26 +65,12 @@ class AuthenticationCommand:
         """Sign up to CrewAI+"""
         console.print("Signing in to CrewAI Enterprise...\n", style="bold blue")
 
-        # TODO: WORKOS - Next line and conditional are temporary until migration to WorkOS is complete.
-        user_provider = self._determine_user_provider()
-        if user_provider == "auth0":
-            settings = Oauth2Settings(
-                provider="auth0",
-                client_id=AUTH0_CLIENT_ID,
-                domain=AUTH0_DOMAIN,
-                audience=AUTH0_AUDIENCE
-            )
-            self.oauth2_provider = ProviderFactory.from_settings(settings)
-        # End of temporary code.
-
         device_code_data = self._get_device_code()
         self._display_auth_instructions(device_code_data)
 
         return self._poll_for_token(device_code_data)
 
-    def _get_device_code(
-        self
-    ) -> Dict[str, Any]:
+    def _get_device_code(self) -> Dict[str, Any]:
         """Get the device code to authenticate the user."""
 
         device_code_payload = {
@@ -86,7 +79,9 @@ class AuthenticationCommand:
             "audience": self.oauth2_provider.get_audience(),
         }
         response = requests.post(
-            url=self.oauth2_provider.get_authorize_url(), data=device_code_payload, timeout=20
+            url=self.oauth2_provider.get_authorize_url(),
+            data=device_code_payload,
+            timeout=20,
         )
         response.raise_for_status()
         return response.json()
@@ -97,9 +92,7 @@ class AuthenticationCommand:
         console.print("2. Enter the following code: ", device_code_data["user_code"])
         webbrowser.open(device_code_data["verification_uri_complete"])
 
-    def _poll_for_token(
-        self, device_code_data: Dict[str, Any]
-    ) -> None:
+    def _poll_for_token(self, device_code_data: Dict[str, Any]) -> None:
         """Polls the server for the token until it is received, or max attempts are reached."""
 
         token_payload = {
@@ -112,7 +105,9 @@ class AuthenticationCommand:
 
         attempts = 0
         while True and attempts < 10:
-            response = requests.post(self.oauth2_provider.get_token_url(), data=token_payload, timeout=30)
+            response = requests.post(
+                self.oauth2_provider.get_token_url(), data=token_payload, timeout=30
+            )
             token_data = response.json()
 
             if response.status_code == 200:
@@ -192,30 +187,3 @@ class AuthenticationCommand:
                 "\nRun [bold]crewai login[/bold] to try logging in again.\n",
                 style="yellow",
             )
-
-    # TODO: WORKOS - This method is temporary until migration to WorkOS is complete.
-    def _determine_user_provider(self) -> str:
-        """Determine which provider to use for authentication."""
-
-        console.print(
-            "Enter your CrewAI Enterprise account email: ", style="bold blue", end=""
-        )
-        email = input()
-        email_encoded = quote(email)
-
-        # It's not correct to call this method directly, but it's temporary until migration is complete.
-        response = PlusAPI("")._make_request(
-            "GET", f"/crewai_plus/api/v1/me/provider?email={email_encoded}"
-        )
-
-        if response.status_code == 200:
-            if response.json().get("provider") == "auth0":
-                return "auth0"
-            else:
-                return "workos"
-        else:
-            console.print(
-                "Error: Failed to authenticate with crewai enterprise. Ensure that you are using the latest crewai version and please try again. If the problem persists, contact support@crewai.com.",
-                style="red",
-            )
-            raise SystemExit

src/crewai/cli/authentication/token.py

@@ -1,4 +1,4 @@
-from .utils import TokenManager
+from crewai.cli.shared.token_manager import TokenManager
 
 
 class AuthError(Exception):

src/crewai/cli/authentication/utils.py

@@ -1,12 +1,5 @@
-import json
-import os
-import sys
-from datetime import datetime
-from pathlib import Path
-from typing import Optional
 import jwt
 from jwt import PyJWKClient
-from cryptography.fernet import Fernet
 
 
 def validate_jwt_token(
@@ -67,118 +60,3 @@ def validate_jwt_token(
         raise Exception(f"JWKS or key processing error: {str(e)}")
     except jwt.InvalidTokenError as e:
         raise Exception(f"Invalid token: {str(e)}")
-
-
-class TokenManager:
-    def __init__(self, file_path: str = "tokens.enc") -> None:
-        """
-        Initialize the TokenManager class.
-
-        :param file_path: The file path to store the encrypted tokens. Default is "tokens.enc".
-        """
-        self.file_path = file_path
-        self.key = self._get_or_create_key()
-        self.fernet = Fernet(self.key)
-
-    def _get_or_create_key(self) -> bytes:
-        """
-        Get or create the encryption key.
-
-        :return: The encryption key.
-        """
-        key_filename = "secret.key"
-        key = self.read_secure_file(key_filename)
-
-        if key is not None:
-            return key
-
-        new_key = Fernet.generate_key()
-        self.save_secure_file(key_filename, new_key)
-        return new_key
-
-    def save_tokens(self, access_token: str, expires_at: int) -> None:
-        """
-        Save the access token and its expiration time.
-
-        :param access_token: The access token to save.
-        :param expires_at: The UNIX timestamp of the expiration time.
-        """
-        expiration_time = datetime.fromtimestamp(expires_at)
-        data = {
-            "access_token": access_token,
-            "expiration": expiration_time.isoformat(),
-        }
-        encrypted_data = self.fernet.encrypt(json.dumps(data).encode())
-        self.save_secure_file(self.file_path, encrypted_data)
-
-    def get_token(self) -> Optional[str]:
-        """
-        Get the access token if it is valid and not expired.
-
-        :return: The access token if valid and not expired, otherwise None.
-        """
-        encrypted_data = self.read_secure_file(self.file_path)
-
-        decrypted_data = self.fernet.decrypt(encrypted_data)  # type: ignore
-        data = json.loads(decrypted_data)
-
-        expiration = datetime.fromisoformat(data["expiration"])
-        if expiration <= datetime.now():
-            return None
-
-        return data["access_token"]
-
-    def get_secure_storage_path(self) -> Path:
-        """
-        Get the secure storage path based on the operating system.
-
-        :return: The secure storage path.
-        """
-        if sys.platform == "win32":
-            # Windows: Use %LOCALAPPDATA%
-            base_path = os.environ.get("LOCALAPPDATA")
-        elif sys.platform == "darwin":
-            # macOS: Use ~/Library/Application Support
-            base_path = os.path.expanduser("~/Library/Application Support")
-        else:
-            # Linux and other Unix-like: Use ~/.local/share
-            base_path = os.path.expanduser("~/.local/share")
-
-        app_name = "crewai/credentials"
-        storage_path = Path(base_path) / app_name
-
-        storage_path.mkdir(parents=True, exist_ok=True)
-
-        return storage_path
-
-    def save_secure_file(self, filename: str, content: bytes) -> None:
-        """
-        Save the content to a secure file.
-
-        :param filename: The name of the file.
-        :param content: The content to save.
-        """
-        storage_path = self.get_secure_storage_path()
-        file_path = storage_path / filename
-
-        with open(file_path, "wb") as f:
-            f.write(content)
-
-        # Set appropriate permissions (read/write for owner only)
-        os.chmod(file_path, 0o600)
-
-    def read_secure_file(self, filename: str) -> Optional[bytes]:
-        """
-        Read the content of a secure file.
-
-        :param filename: The name of the file.
-        :return: The content of the file if it exists, otherwise None.
-        """
-        storage_path = self.get_secure_storage_path()
-        file_path = storage_path / filename
-
-        if not file_path.exists():
-            return None
-
-        with open(file_path, "rb") as f:
-            return f.read()

src/crewai/cli/config.py

@@ -11,6 +11,7 @@ from crewai.cli.constants import (
     CREWAI_ENTERPRISE_DEFAULT_OAUTH2_CLIENT_ID,
     CREWAI_ENTERPRISE_DEFAULT_OAUTH2_DOMAIN,
 )
+from crewai.cli.shared.token_manager import TokenManager
 
 DEFAULT_CONFIG_PATH = Path.home() / ".config" / "crewai" / "settings.json"
 
@@ -53,6 +54,7 @@ HIDDEN_SETTINGS_KEYS = [
     "tool_repository_password",
 ]
 
+
 class Settings(BaseModel):
     enterprise_base_url: Optional[str] = Field(
         default=DEFAULT_CLI_SETTINGS["enterprise_base_url"],
@@ -74,12 +76,12 @@ class Settings(BaseModel):
 
     oauth2_provider: str = Field(
         description="OAuth2 provider used for authentication (e.g., workos, okta, auth0).",
-        default=DEFAULT_CLI_SETTINGS["oauth2_provider"]
+        default=DEFAULT_CLI_SETTINGS["oauth2_provider"],
     )
 
     oauth2_audience: Optional[str] = Field(
         description="OAuth2 audience value, typically used to identify the target API or resource.",
-        default=DEFAULT_CLI_SETTINGS["oauth2_audience"]
+        default=DEFAULT_CLI_SETTINGS["oauth2_audience"],
     )
 
     oauth2_client_id: str = Field(
@@ -89,7 +91,7 @@ class Settings(BaseModel):
 
     oauth2_domain: str = Field(
         description="OAuth2 provider's domain (e.g., your-org.auth0.com) used for issuing tokens.",
-        default=DEFAULT_CLI_SETTINGS["oauth2_domain"]
+        default=DEFAULT_CLI_SETTINGS["oauth2_domain"],
     )
 
     def __init__(self, config_path: Path = DEFAULT_CONFIG_PATH, **data):
@@ -116,6 +118,7 @@ class Settings(BaseModel):
         """Reset all settings to default values"""
         self._reset_user_settings()
         self._reset_cli_settings()
+        self._clear_auth_tokens()
         self.dump()
 
     def dump(self) -> None:
@@ -139,3 +142,7 @@ class Settings(BaseModel):
         """Reset all CLI settings to default values"""
         for key in CLI_SETTINGS_KEYS:
             setattr(self, key, DEFAULT_CLI_SETTINGS.get(key))
+
+    def _clear_auth_tokens(self) -> None:
+        """Clear all authentication tokens"""
+        TokenManager().clear_tokens()

src/crewai/cli/plus_api.py

@@ -117,17 +117,19 @@ class PlusAPI:
     def get_organizations(self) -> requests.Response:
         return self._make_request("GET", self.ORGANIZATIONS_RESOURCE)
 
-    def send_trace_batch(self, payload) -> requests.Response:
-        return self._make_request("POST", self.TRACING_RESOURCE, json=payload)
-
     def initialize_trace_batch(self, payload) -> requests.Response:
         return self._make_request(
-            "POST", f"{self.TRACING_RESOURCE}/batches", json=payload
+            "POST",
+            f"{self.TRACING_RESOURCE}/batches",
+            json=payload,
+            timeout=30,
         )
 
     def initialize_ephemeral_trace_batch(self, payload) -> requests.Response:
         return self._make_request(
-            "POST", f"{self.EPHEMERAL_TRACING_RESOURCE}/batches", json=payload
+            "POST",
+            f"{self.EPHEMERAL_TRACING_RESOURCE}/batches",
+            json=payload,
         )
 
     def send_trace_events(self, trace_batch_id: str, payload) -> requests.Response:
@@ -135,6 +137,7 @@ class PlusAPI:
             "POST",
             f"{self.TRACING_RESOURCE}/batches/{trace_batch_id}/events",
             json=payload,
+            timeout=30,
         )
 
     def send_ephemeral_trace_events(
@@ -144,6 +147,7 @@ class PlusAPI:
             "POST",
             f"{self.EPHEMERAL_TRACING_RESOURCE}/batches/{trace_batch_id}/events",
             json=payload,
+            timeout=30,
         )
 
     def finalize_trace_batch(self, trace_batch_id: str, payload) -> requests.Response:
@@ -151,6 +155,7 @@ class PlusAPI:
             "PATCH",
             f"{self.TRACING_RESOURCE}/batches/{trace_batch_id}/finalize",
             json=payload,
+            timeout=30,
         )
 
     def finalize_ephemeral_trace_batch(
@@ -160,4 +165,5 @@ class PlusAPI:
             "PATCH",
             f"{self.EPHEMERAL_TRACING_RESOURCE}/batches/{trace_batch_id}/finalize",
             json=payload,
+            timeout=30,
         )

src/crewai/cli/settings/main.py

@@ -10,8 +10,9 @@ console = Console()
 class SettingsCommand(BaseCommand):
     """A class to handle CLI configuration commands."""
 
-    def __init__(self, settings_kwargs: dict[str, Any] = {}):
+    def __init__(self, settings_kwargs: dict[str, Any] | None = None):
         super().__init__()
+        settings_kwargs = settings_kwargs or {}
         self.settings = Settings(**settings_kwargs)
 
     def list(self) -> None:

src/crewai/cli/shared/token_manager.py

@@ -0,0 +1,141 @@
+import json
+import os
+import sys
+from datetime import datetime
+from pathlib import Path
+from typing import Optional
+from cryptography.fernet import Fernet
+
+
+class TokenManager:
+    def __init__(self, file_path: str = "tokens.enc") -> None:
+        """
+        Initialize the TokenManager class.
+
+        :param file_path: The file path to store the encrypted tokens. Default is "tokens.enc".
+        """
+        self.file_path = file_path
+        self.key = self._get_or_create_key()
+        self.fernet = Fernet(self.key)
+
+    def _get_or_create_key(self) -> bytes:
+        """
+        Get or create the encryption key.
+
+        :return: The encryption key.
+        """
+        key_filename = "secret.key"
+        key = self.read_secure_file(key_filename)
+
+        if key is not None:
+            return key
+
+        new_key = Fernet.generate_key()
+        self.save_secure_file(key_filename, new_key)
+        return new_key
+
+    def save_tokens(self, access_token: str, expires_at: int) -> None:
+        """
+        Save the access token and its expiration time.
+
+        :param access_token: The access token to save.
+        :param expires_at: The UNIX timestamp of the expiration time.
+        """
+        expiration_time = datetime.fromtimestamp(expires_at)
+        data = {
+            "access_token": access_token,
+            "expiration": expiration_time.isoformat(),
+        }
+        encrypted_data = self.fernet.encrypt(json.dumps(data).encode())
+        self.save_secure_file(self.file_path, encrypted_data)
+
+    def get_token(self) -> Optional[str]:
+        """
+        Get the access token if it is valid and not expired.
+
+        :return: The access token if valid and not expired, otherwise None.
+        """
+        encrypted_data = self.read_secure_file(self.file_path)
+        if encrypted_data is None:
+            return None
+
+        decrypted_data = self.fernet.decrypt(encrypted_data)  # type: ignore
+        data = json.loads(decrypted_data)
+
+        expiration = datetime.fromisoformat(data["expiration"])
+        if expiration <= datetime.now():
+            return None
+
+        return data["access_token"]
+
+    def clear_tokens(self) -> None:
+        """
+        Clear the tokens.
+        """
+        self.delete_secure_file(self.file_path)
+
+    def get_secure_storage_path(self) -> Path:
+        """
+        Get the secure storage path based on the operating system.
+
+        :return: The secure storage path.
+        """
+        if sys.platform == "win32":
+            # Windows: Use %LOCALAPPDATA%
+            base_path = os.environ.get("LOCALAPPDATA")
+        elif sys.platform == "darwin":
+            # macOS: Use ~/Library/Application Support
+            base_path = os.path.expanduser("~/Library/Application Support")
+        else:
+            # Linux and other Unix-like: Use ~/.local/share
+            base_path = os.path.expanduser("~/.local/share")
+
+        app_name = "crewai/credentials"
+        storage_path = Path(base_path) / app_name
+
+        storage_path.mkdir(parents=True, exist_ok=True)
+
+        return storage_path
+
+    def save_secure_file(self, filename: str, content: bytes) -> None:
+        """
+        Save the content to a secure file.
+
+        :param filename: The name of the file.
+        :param content: The content to save.
+        """
+        storage_path = self.get_secure_storage_path()
+        file_path = storage_path / filename
+
+        with open(file_path, "wb") as f:
+            f.write(content)
+
+        # Set appropriate permissions (read/write for owner only)
+        os.chmod(file_path, 0o600)
+
+    def read_secure_file(self, filename: str) -> Optional[bytes]:
+        """
+        Read the content of a secure file.
+
+        :param filename: The name of the file.
+        :return: The content of the file if it exists, otherwise None.
+        """
+        storage_path = self.get_secure_storage_path()
+        file_path = storage_path / filename
+
+        if not file_path.exists():
+            return None
+
+        with open(file_path, "rb") as f:
+            return f.read()
+
+    def delete_secure_file(self, filename: str) -> None:
+        """
+        Delete the secure file.
+
+        :param filename: The name of the file.
+        """
+        storage_path = self.get_secure_storage_path()
+        file_path = storage_path / filename
+        if file_path.exists():
+            file_path.unlink(missing_ok=True)

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]>=0.165.1,<1.0.0"
+    "crewai[tools]>=0.177.0,<1.0.0"
 ]
 
 [project.scripts]

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]>=0.165.1,<1.0.0",
+    "crewai[tools]>=0.177.0,<1.0.0",
 ]
 
 [project.scripts]

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]>=0.165.1"
+    "crewai[tools]>=0.177.0"
 ]
 
 [tool.crewai]

src/crewai/crew.py

@@ -59,7 +59,7 @@ from crewai.utilities import I18N, FileHandler, Logger, RPMController
 from crewai.utilities.constants import NOT_SPECIFIED, TRAINING_DATA_FILE
 from crewai.utilities.evaluators.crew_evaluator_handler import CrewEvaluator
 from crewai.utilities.evaluators.task_evaluator import TaskEvaluator
-from crewai.utilities.events.crew_events import (
+from crewai.events.types.crew_events import (
     CrewKickoffCompletedEvent,
     CrewKickoffFailedEvent,
     CrewKickoffStartedEvent,
@@ -70,14 +70,14 @@ from crewai.utilities.events.crew_events import (
     CrewTrainFailedEvent,
     CrewTrainStartedEvent,
 )
-from crewai.utilities.events.crewai_event_bus import crewai_event_bus
-from crewai.utilities.events.event_listener import EventListener
-from crewai.utilities.events.listeners.tracing.trace_listener import (
+from crewai.events.event_bus import crewai_event_bus
+from crewai.events.event_listener import EventListener
+from crewai.events.listeners.tracing.trace_listener import (
     TraceCollectionListener,
 )
 
 
-from crewai.utilities.events.listeners.tracing.utils import (
+from crewai.events.listeners.tracing.utils import (
     is_tracing_enabled,
 )
 from crewai.utilities.formatter import (
@@ -559,9 +559,10 @@ class Crew(FlowTrackable, BaseModel):
         CrewTrainingHandler(filename).initialize_file()
 
     def train(
-        self, n_iterations: int, filename: str, inputs: Optional[Dict[str, Any]] = {}
+        self, n_iterations: int, filename: str, inputs: Optional[Dict[str, Any]] = None
     ) -> None:
         """Trains the crew for a given number of iterations."""
+        inputs = inputs or {}
         try:
             crewai_event_bus.emit(
                 self,
@@ -702,8 +703,11 @@ class Crew(FlowTrackable, BaseModel):
         self._task_output_handler.reset()
         return results
 
-    async def kickoff_async(self, inputs: Optional[Dict[str, Any]] = {}) -> CrewOutput:
+    async def kickoff_async(
+        self, inputs: Optional[Dict[str, Any]] = None
+    ) -> CrewOutput:
         """Asynchronous kickoff method to start the crew execution."""
+        inputs = inputs or {}
         return await asyncio.to_thread(self.kickoff, inputs)
 
     async def kickoff_for_each_async(self, inputs: List[Dict]) -> List[CrewOutput]:

src/crewai/events/__init__.py

@@ -0,0 +1,56 @@
+"""CrewAI events system for monitoring and extending agent behavior.
+
+This module provides the event infrastructure that allows users to:
+- Monitor agent, task, and crew execution
+- Track memory operations and performance
+- Build custom logging and analytics
+- Extend CrewAI with custom event handlers
+"""
+
+from crewai.events.base_event_listener import BaseEventListener
+from crewai.events.event_bus import crewai_event_bus
+
+from crewai.events.types.memory_events import (
+    MemoryQueryCompletedEvent,
+    MemorySaveCompletedEvent,
+    MemorySaveStartedEvent,
+    MemoryQueryStartedEvent,
+    MemoryRetrievalCompletedEvent,
+    MemorySaveFailedEvent,
+    MemoryQueryFailedEvent,
+)
+
+from crewai.events.types.knowledge_events import (
+    KnowledgeRetrievalStartedEvent,
+    KnowledgeRetrievalCompletedEvent,
+)
+
+from crewai.events.types.crew_events import (
+    CrewKickoffStartedEvent,
+    CrewKickoffCompletedEvent,
+)
+from crewai.events.types.agent_events import (
+    AgentExecutionCompletedEvent,
+)
+
+from crewai.events.types.llm_events import (
+    LLMStreamChunkEvent,
+)
+
+__all__ = [
+    "BaseEventListener",
+    "crewai_event_bus",
+    "MemoryQueryCompletedEvent",
+    "MemorySaveCompletedEvent",
+    "MemorySaveStartedEvent",
+    "MemoryQueryStartedEvent",
+    "MemoryRetrievalCompletedEvent",
+    "MemorySaveFailedEvent",
+    "MemoryQueryFailedEvent",
+    "KnowledgeRetrievalStartedEvent",
+    "KnowledgeRetrievalCompletedEvent",
+    "CrewKickoffStartedEvent",
+    "CrewKickoffCompletedEvent",
+    "AgentExecutionCompletedEvent",
+    "LLMStreamChunkEvent",
+]

src/crewai/events/base_event_listener.py

@@ -0,0 +1,15 @@
+from abc import ABC, abstractmethod
+
+from crewai.events.event_bus import CrewAIEventsBus, crewai_event_bus
+
+
+class BaseEventListener(ABC):
+    verbose: bool = False
+
+    def __init__(self):
+        super().__init__()
+        self.setup_listeners(crewai_event_bus)
+
+    @abstractmethod
+    def setup_listeners(self, crewai_event_bus: CrewAIEventsBus):
+        pass

src/crewai/events/base_events.py

@@ -11,7 +11,9 @@ class BaseEvent(BaseModel):
     timestamp: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
     type: str
     source_fingerprint: Optional[str] = None  # UUID string of the source entity
-    source_type: Optional[str] = None  # "agent", "task", "crew", "memory", "entity_memory", "short_term_memory", "long_term_memory", "external_memory"
+    source_type: Optional[str] = (
+        None  # "agent", "task", "crew", "memory", "entity_memory", "short_term_memory", "long_term_memory", "external_memory"
+    )
     fingerprint_metadata: Optional[Dict[str, Any]] = None  # Any relevant metadata
 
     def to_json(self, exclude: set[str] | None = None):
@@ -25,3 +27,20 @@ class BaseEvent(BaseModel):
             dict: A JSON-serializable dictionary.
         """
         return to_serializable(self, exclude=exclude)
+
+    def _set_task_params(self, data: Dict[str, Any]):
+        if "from_task" in data and (task := data["from_task"]):
+            self.task_id = task.id
+            self.task_name = task.name or task.description
+            self.from_task = None
+
+    def _set_agent_params(self, data: Dict[str, Any]):
+        task = data.get("from_task", None)
+        agent = task.agent if task else data.get("from_agent", None)
+
+        if not agent:
+            return
+
+        self.agent_id = agent.id
+        self.agent_role = agent.role
+        self.from_agent = None

src/crewai/events/event_bus.py

@@ -0,0 +1,117 @@
+from __future__ import annotations
+
+import threading
+from contextlib import contextmanager
+from typing import Any, Callable, Dict, List, Type, TypeVar, cast
+
+from blinker import Signal
+
+from crewai.events.base_events import BaseEvent
+from crewai.events.event_types import EventTypes
+
+EventT = TypeVar("EventT", bound=BaseEvent)
+
+
+class CrewAIEventsBus:
+    """
+    A singleton event bus that uses blinker signals for event handling.
+    Allows both internal (Flow/Crew) and external event handling.
+    """
+
+    _instance = None
+    _lock = threading.Lock()
+
+    def __new__(cls):
+        if cls._instance is None:
+            with cls._lock:
+                if cls._instance is None:  # prevent race condition
+                    cls._instance = super(CrewAIEventsBus, cls).__new__(cls)
+                    cls._instance._initialize()
+        return cls._instance
+
+    def _initialize(self) -> None:
+        """Initialize the event bus internal state"""
+        self._signal = Signal("crewai_event_bus")
+        self._handlers: Dict[Type[BaseEvent], List[Callable]] = {}
+
+    def on(
+        self, event_type: Type[EventT]
+    ) -> Callable[[Callable[[Any, EventT], None]], Callable[[Any, EventT], None]]:
+        """
+        Decorator to register an event handler for a specific event type.
+
+        Usage:
+            @crewai_event_bus.on(AgentExecutionCompletedEvent)
+            def on_agent_execution_completed(
+                source: Any, event: AgentExecutionCompletedEvent
+            ):
+                print(f"👍 Agent '{event.agent}' completed task")
+                print(f"   Output: {event.output}")
+        """
+
+        def decorator(
+            handler: Callable[[Any, EventT], None],
+        ) -> Callable[[Any, EventT], None]:
+            if event_type not in self._handlers:
+                self._handlers[event_type] = []
+            self._handlers[event_type].append(
+                cast(Callable[[Any, EventT], None], handler)
+            )
+            return handler
+
+        return decorator
+
+    def emit(self, source: Any, event: BaseEvent) -> None:
+        """
+        Emit an event to all registered handlers
+
+        Args:
+            source: The object emitting the event
+            event: The event instance to emit
+        """
+        for event_type, handlers in self._handlers.items():
+            if isinstance(event, event_type):
+                for handler in handlers:
+                    try:
+                        handler(source, event)
+                    except Exception as e:
+                        print(
+                            f"[EventBus Error] Handler '{handler.__name__}' failed for event '{event_type.__name__}': {e}"
+                        )
+
+        self._signal.send(source, event=event)
+
+    def register_handler(
+        self, event_type: Type[EventTypes], handler: Callable[[Any, EventTypes], None]
+    ) -> None:
+        """Register an event handler for a specific event type"""
+        if event_type not in self._handlers:
+            self._handlers[event_type] = []
+        self._handlers[event_type].append(
+            cast(Callable[[Any, EventTypes], None], handler)
+        )
+
+    @contextmanager
+    def scoped_handlers(self):
+        """
+        Context manager for temporary event handling scope.
+        Useful for testing or temporary event handling.
+
+        Usage:
+            with crewai_event_bus.scoped_handlers():
+                @crewai_event_bus.on(CrewKickoffStarted)
+                def temp_handler(source, event):
+                    print("Temporary handler")
+                # Do stuff...
+            # Handlers are cleared after the context
+        """
+        previous_handlers = self._handlers.copy()
+        self._handlers.clear()
+        try:
+            yield
+        finally:
+            self._handlers = previous_handlers
+
+
+# Global instance
+crewai_event_bus = CrewAIEventsBus()

src/crewai/events/event_listener.py

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 from io import StringIO
 from typing import Any, Dict
 
@@ -7,8 +9,8 @@ from crewai.task import Task
 from crewai.telemetry.telemetry import Telemetry
 from crewai.utilities import Logger
 from crewai.utilities.constants import EMITTER_COLOR
-from crewai.utilities.events.base_event_listener import BaseEventListener
-from crewai.utilities.events.knowledge_events import (
+from crewai.events.base_event_listener import BaseEventListener
+from crewai.events.types.knowledge_events import (
     KnowledgeQueryCompletedEvent,
     KnowledgeQueryFailedEvent,
     KnowledgeQueryStartedEvent,
@@ -16,28 +18,30 @@ from crewai.utilities.events.knowledge_events import (
     KnowledgeRetrievalStartedEvent,
     KnowledgeSearchQueryFailedEvent,
 )
-from crewai.utilities.events.llm_events import (
+from crewai.events.types.llm_events import (
     LLMCallCompletedEvent,
     LLMCallFailedEvent,
     LLMCallStartedEvent,
     LLMStreamChunkEvent,
 )
-from crewai.utilities.events.llm_guardrail_events import (
+from crewai.events.types.llm_guardrail_events import (
     LLMGuardrailStartedEvent,
     LLMGuardrailCompletedEvent,
 )
-from crewai.utilities.events.utils.console_formatter import ConsoleFormatter
+from crewai.events.utils.console_formatter import ConsoleFormatter
 
-from .agent_events import (
+from crewai.events.types.agent_events import (
     AgentExecutionCompletedEvent,
     AgentExecutionStartedEvent,
-    AgentLogsStartedEvent,
-    AgentLogsExecutionEvent,
     LiteAgentExecutionCompletedEvent,
     LiteAgentExecutionErrorEvent,
     LiteAgentExecutionStartedEvent,
 )
-from .crew_events import (
+from crewai.events.types.logging_events import (
+    AgentLogsStartedEvent,
+    AgentLogsExecutionEvent,
+)
+from crewai.events.types.crew_events import (
     CrewKickoffCompletedEvent,
     CrewKickoffFailedEvent,
     CrewKickoffStartedEvent,
@@ -49,7 +53,7 @@ from .crew_events import (
     CrewTrainFailedEvent,
     CrewTrainStartedEvent,
 )
-from .flow_events import (
+from .types.flow_events import (
     FlowCreatedEvent,
     FlowFinishedEvent,
     FlowStartedEvent,
@@ -57,13 +61,13 @@ from .flow_events import (
     MethodExecutionFinishedEvent,
     MethodExecutionStartedEvent,
 )
-from .task_events import TaskCompletedEvent, TaskFailedEvent, TaskStartedEvent
-from .tool_usage_events import (
+from .types.task_events import TaskCompletedEvent, TaskFailedEvent, TaskStartedEvent
+from .types.tool_usage_events import (
     ToolUsageErrorEvent,
     ToolUsageFinishedEvent,
     ToolUsageStartedEvent,
 )
-from .reasoning_events import (
+from .types.reasoning_events import (
     AgentReasoningStartedEvent,
     AgentReasoningCompletedEvent,
     AgentReasoningFailedEvent,
@@ -162,7 +166,7 @@ class EventListener(BaseEventListener):
             span = self._telemetry.task_started(crew=source.agent.crew, task=source)
             self.execution_spans[source] = span
             # Pass both task ID and task name (if set)
-            task_name = source.name if hasattr(source, 'name') and source.name else None
+            task_name = source.name if hasattr(source, "name") and source.name else None
             self.formatter.create_task_branch(
                 self.formatter.current_crew_tree, source.id, task_name
             )
@@ -176,13 +180,13 @@ class EventListener(BaseEventListener):
             self.execution_spans[source] = None
 
             # Pass task name if it exists
-            task_name = source.name if hasattr(source, 'name') and source.name else None
+            task_name = source.name if hasattr(source, "name") and source.name else None
             self.formatter.update_task_status(
                 self.formatter.current_crew_tree,
                 source.id,
                 source.agent.role,
                 "completed",
-                task_name
+                task_name,
             )
 
         @crewai_event_bus.on(TaskFailedEvent)
@@ -194,13 +198,13 @@ class EventListener(BaseEventListener):
                 self.execution_spans[source] = None
 
             # Pass task name if it exists
-            task_name = source.name if hasattr(source, 'name') and source.name else None
+            task_name = source.name if hasattr(source, "name") and source.name else None
             self.formatter.update_task_status(
                 self.formatter.current_crew_tree,
                 source.id,
                 source.agent.role,
                 "failed",
-                task_name
+                task_name,
             )
 
         # ----------- AGENT EVENTS -----------

src/crewai/events/event_types.py

@@ -1,12 +1,12 @@
 from typing import Union
 
-from .agent_events import (
+from crewai.events.types.agent_events import (
     AgentExecutionCompletedEvent,
     AgentExecutionErrorEvent,
     AgentExecutionStartedEvent,
     LiteAgentExecutionCompletedEvent,
 )
-from .crew_events import (
+from .types.crew_events import (
     CrewKickoffCompletedEvent,
     CrewKickoffFailedEvent,
     CrewKickoffStartedEvent,
@@ -17,39 +17,39 @@ from .crew_events import (
     CrewTrainFailedEvent,
     CrewTrainStartedEvent,
 )
-from .flow_events import (
+from .types.flow_events import (
     FlowFinishedEvent,
     FlowStartedEvent,
     MethodExecutionFailedEvent,
     MethodExecutionFinishedEvent,
     MethodExecutionStartedEvent,
 )
-from .llm_events import (
+from .types.llm_events import (
     LLMCallCompletedEvent,
     LLMCallFailedEvent,
     LLMCallStartedEvent,
     LLMStreamChunkEvent,
 )
-from .llm_guardrail_events import (
+from .types.llm_guardrail_events import (
     LLMGuardrailCompletedEvent,
     LLMGuardrailStartedEvent,
 )
-from .task_events import (
+from .types.task_events import (
     TaskCompletedEvent,
     TaskFailedEvent,
     TaskStartedEvent,
 )
-from .tool_usage_events import (
+from .types.tool_usage_events import (
     ToolUsageErrorEvent,
     ToolUsageFinishedEvent,
     ToolUsageStartedEvent,
 )
-from .reasoning_events import (
+from .types.reasoning_events import (
     AgentReasoningStartedEvent,
     AgentReasoningCompletedEvent,
     AgentReasoningFailedEvent,
 )
-from .knowledge_events import (
+from .types.knowledge_events import (
     KnowledgeRetrievalStartedEvent,
     KnowledgeRetrievalCompletedEvent,
     KnowledgeQueryStartedEvent,
@@ -58,7 +58,7 @@ from .knowledge_events import (
     KnowledgeSearchQueryFailedEvent,
 )
 
-from .memory_events import (
+from .types.memory_events import (
     MemorySaveStartedEvent,
     MemorySaveCompletedEvent,
     MemorySaveFailedEvent,

src/crewai/events/listeners/__init__.py

@@ -0,0 +1,5 @@
+"""Event listener implementations for CrewAI.
+
+This module contains various event listener implementations
+for handling memory, tracing, and other event-driven functionality.
+"""

src/crewai/events/listeners/memory_listener.py

@@ -1,5 +1,5 @@
-from crewai.utilities.events.base_event_listener import BaseEventListener
-from crewai.utilities.events.memory_events import (
+from crewai.events.base_event_listener import BaseEventListener
+from crewai.events.types.memory_events import (
     MemoryRetrievalCompletedEvent,
     MemoryRetrievalStartedEvent,
     MemoryQueryFailedEvent,
@@ -9,8 +9,8 @@ from crewai.utilities.events.memory_events import (
     MemorySaveFailedEvent,
 )
 
-class MemoryListener(BaseEventListener):
 
+class MemoryListener(BaseEventListener):
     def __init__(self, formatter):
         super().__init__()
         self.formatter = formatter
@@ -19,9 +19,7 @@ class MemoryListener(BaseEventListener):
 
     def setup_listeners(self, crewai_event_bus):
         @crewai_event_bus.on(MemoryRetrievalStartedEvent)
-        def on_memory_retrieval_started(
-            source, event: MemoryRetrievalStartedEvent
-        ):
+        def on_memory_retrieval_started(source, event: MemoryRetrievalStartedEvent):
             if self.memory_retrieval_in_progress:
                 return
 
@@ -33,9 +31,7 @@ class MemoryListener(BaseEventListener):
             )
 
         @crewai_event_bus.on(MemoryRetrievalCompletedEvent)
-        def on_memory_retrieval_completed(
-            source, event: MemoryRetrievalCompletedEvent
-        ):
+        def on_memory_retrieval_completed(source, event: MemoryRetrievalCompletedEvent):
             if not self.memory_retrieval_in_progress:
                 return
 
@@ -44,7 +40,7 @@ class MemoryListener(BaseEventListener):
                 self.formatter.current_agent_branch,
                 self.formatter.current_crew_tree,
                 event.memory_content,
-                event.retrieval_time_ms
+                event.retrieval_time_ms,
             )
 
         @crewai_event_bus.on(MemoryQueryCompletedEvent)
@@ -107,4 +103,4 @@ class MemoryListener(BaseEventListener):
                 event.error,
                 event.source_type,
                 self.formatter.current_crew_tree,
-            )
+            )

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

@@ -11,7 +11,7 @@ from crewai.cli.plus_api import PlusAPI
 from rich.console import Console
 from rich.panel import Panel
 
-from crewai.utilities.events.listeners.tracing.types import TraceEvent
+from crewai.events.listeners.tracing.types import TraceEvent
 from logging import getLogger
 
 logger = getLogger(__name__)
@@ -41,18 +41,21 @@ class TraceBatchManager:
     """Single responsibility: Manage batches and event buffering"""
 
     is_current_batch_ephemeral: bool = False
+    trace_batch_id: Optional[str] = None
+    current_batch: Optional[TraceBatch] = None
+    event_buffer: List[TraceEvent] = []
+    execution_start_times: Dict[str, datetime] = {}
+    batch_owner_type: Optional[str] = None
+    batch_owner_id: Optional[str] = None
 
     def __init__(self):
         try:
-            self.plus_api = PlusAPI(api_key=get_auth_token())
+            self.plus_api = PlusAPI(
+                api_key=get_auth_token(),
+            )
         except AuthError:
             self.plus_api = PlusAPI(api_key="")
 
-        self.trace_batch_id: Optional[str] = None  # Backend ID
-        self.current_batch: Optional[TraceBatch] = None
-        self.event_buffer: List[TraceEvent] = []
-        self.execution_start_times: Dict[str, datetime] = {}
-
     def initialize_batch(
         self,
         user_context: Dict[str, str],
@@ -113,7 +116,13 @@ class TraceBatchManager:
                 else self.plus_api.initialize_trace_batch(payload)
             )
 
-            if response.status_code == 201 or response.status_code == 200:
+            if response is None:
+                logger.warning(
+                    "Trace batch initialization failed gracefully. Continuing without tracing."
+                )
+                return
+
+            if response.status_code in [201, 200]:
                 response_data = response.json()
                 self.trace_batch_id = (
                     response_data["trace_id"]
@@ -128,21 +137,23 @@ class TraceBatchManager:
                 )
                 console.print(panel)
             else:
-                logger.error(
-                    f"❌ Failed to initialize trace batch: {response.status_code} - {response.text}"
+                logger.warning(
+                    f"Trace batch initialization returned status {response.status_code}. Continuing without tracing."
                 )
 
         except Exception as e:
-            logger.error(f"❌ Error initializing trace batch: {str(e)}")
+            logger.warning(
+                f"Error initializing trace batch: {str(e)}. Continuing without tracing."
+            )
 
     def add_event(self, trace_event: TraceEvent):
         """Add event to buffer"""
         self.event_buffer.append(trace_event)
 
-    def _send_events_to_backend(self):
-        """Send buffered events to backend"""
+    def _send_events_to_backend(self) -> int:
+        """Send buffered events to backend with graceful failure handling"""
         if not self.plus_api or not self.trace_batch_id or not self.event_buffer:
-            return
+            return 500
 
         try:
             payload = {
@@ -154,38 +165,48 @@ class TraceBatchManager:
                 },
             }
 
-            if not self.trace_batch_id:
-                raise Exception("❌ Trace batch ID not found")
-
             response = (
                 self.plus_api.send_ephemeral_trace_events(self.trace_batch_id, payload)
                 if self.is_current_batch_ephemeral
                 else self.plus_api.send_trace_events(self.trace_batch_id, payload)
             )
 
-            if response.status_code == 200 or response.status_code == 201:
+            if response is None:
+                logger.warning("Failed to send trace events. Events will be lost.")
+                return 500
+
+            if response.status_code in [200, 201]:
                 self.event_buffer.clear()
+                return 200
             else:
-                logger.error(
-                    f"❌ Failed to send events: {response.status_code} - {response.text}"
+                logger.warning(
+                    f"Failed to send events: {response.status_code}. Events will be lost."
                 )
+                return 500
 
         except Exception as e:
-            logger.error(f"❌ Error sending events to backend: {str(e)}")
+            logger.warning(
+                f"Error sending events to backend: {str(e)}. Events will be lost."
+            )
+            return 500
 
     def finalize_batch(self) -> Optional[TraceBatch]:
         """Finalize batch and return it for sending"""
         if not self.current_batch:
             return None
 
+        self.current_batch.events = self.event_buffer.copy()
         if self.event_buffer:
-            self._send_events_to_backend()
+            events_sent_to_backend_status = self._send_events_to_backend()
+            if events_sent_to_backend_status == 500:
+                return None
         self._finalize_backend_batch()
 
-        self.current_batch.events = self.event_buffer.copy()
-
         finalized_batch = self.current_batch
 
+        self.batch_owner_type = None
+        self.batch_owner_id = None
+
         self.current_batch = None
         self.event_buffer.clear()
         self.trace_batch_id = None

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

@@ -3,8 +3,8 @@ import uuid
 
 from typing import Dict, Any, Optional
 
-from crewai.utilities.events.base_event_listener import BaseEventListener
-from crewai.utilities.events.agent_events import (
+from crewai.events.base_event_listener import BaseEventListener
+from crewai.events.types.agent_events import (
     AgentExecutionCompletedEvent,
     AgentExecutionStartedEvent,
     LiteAgentExecutionStartedEvent,
@@ -12,34 +12,34 @@ from crewai.utilities.events.agent_events import (
     LiteAgentExecutionErrorEvent,
     AgentExecutionErrorEvent,
 )
-from crewai.utilities.events.listeners.tracing.types import TraceEvent
-from crewai.utilities.events.reasoning_events import (
+from crewai.events.listeners.tracing.types import TraceEvent
+from crewai.events.types.reasoning_events import (
     AgentReasoningStartedEvent,
     AgentReasoningCompletedEvent,
     AgentReasoningFailedEvent,
 )
-from crewai.utilities.events.crew_events import (
+from crewai.events.types.crew_events import (
     CrewKickoffCompletedEvent,
     CrewKickoffFailedEvent,
     CrewKickoffStartedEvent,
 )
-from crewai.utilities.events.task_events import (
+from crewai.events.types.task_events import (
     TaskCompletedEvent,
     TaskFailedEvent,
     TaskStartedEvent,
 )
-from crewai.utilities.events.tool_usage_events import (
+from crewai.events.types.tool_usage_events import (
     ToolUsageErrorEvent,
     ToolUsageFinishedEvent,
     ToolUsageStartedEvent,
 )
-from crewai.utilities.events.llm_events import (
+from crewai.events.types.llm_events import (
     LLMCallCompletedEvent,
     LLMCallFailedEvent,
     LLMCallStartedEvent,
 )
 
-from crewai.utilities.events.flow_events import (
+from crewai.events.types.flow_events import (
     FlowCreatedEvent,
     FlowStartedEvent,
     FlowFinishedEvent,
@@ -48,7 +48,7 @@ from crewai.utilities.events.flow_events import (
     MethodExecutionFailedEvent,
     FlowPlotEvent,
 )
-from crewai.utilities.events.llm_guardrail_events import (
+from crewai.events.types.llm_guardrail_events import (
     LLMGuardrailStartedEvent,
     LLMGuardrailCompletedEvent,
 )
@@ -57,7 +57,7 @@ from crewai.utilities.serialization import to_serializable
 
 from .trace_batch_manager import TraceBatchManager
 
-from crewai.utilities.events.memory_events import (
+from crewai.events.types.memory_events import (
     MemoryQueryStartedEvent,
     MemoryQueryCompletedEvent,
     MemoryQueryFailedEvent,
@@ -75,10 +75,18 @@ class TraceCollectionListener(BaseEventListener):
     Trace collection listener that orchestrates trace collection
     """
 
-    complex_events = ["task_started", "llm_call_started", "llm_call_completed"]
+    complex_events = [
+        "task_started",
+        "task_completed",
+        "llm_call_started",
+        "llm_call_completed",
+        "agent_execution_started",
+        "agent_execution_completed",
+    ]
 
     _instance = None
     _initialized = False
+    _listeners_setup = False
 
     def __new__(cls, batch_manager=None):
         if cls._instance is None:
@@ -116,10 +124,15 @@ class TraceCollectionListener(BaseEventListener):
     def setup_listeners(self, crewai_event_bus):
         """Setup event listeners - delegates to specific handlers"""
 
+        if self._listeners_setup:
+            return
+
         self._register_flow_event_handlers(crewai_event_bus)
         self._register_context_event_handlers(crewai_event_bus)
         self._register_action_event_handlers(crewai_event_bus)
 
+        self._listeners_setup = True
+
     def _register_flow_event_handlers(self, event_bus):
         """Register handlers for flow events"""
 
@@ -148,7 +161,8 @@ class TraceCollectionListener(BaseEventListener):
         @event_bus.on(FlowFinishedEvent)
         def on_flow_finished(source, event):
             self._handle_trace_event("flow_finished", source, event)
-            self.batch_manager.finalize_batch()
+            if self.batch_manager.batch_owner_type == "flow":
+                self.batch_manager.finalize_batch()
 
         @event_bus.on(FlowPlotEvent)
         def on_flow_plot(source, event):
@@ -166,7 +180,8 @@ class TraceCollectionListener(BaseEventListener):
         @event_bus.on(CrewKickoffCompletedEvent)
         def on_crew_completed(source, event):
             self._handle_trace_event("crew_kickoff_completed", source, event)
-            self.batch_manager.finalize_batch()
+            if self.batch_manager.batch_owner_type == "crew":
+                self.batch_manager.finalize_batch()
 
         @event_bus.on(CrewKickoffFailedEvent)
         def on_crew_failed(source, event):
@@ -218,7 +233,7 @@ class TraceCollectionListener(BaseEventListener):
             self._handle_trace_event("llm_guardrail_completed", source, event)
 
     def _register_action_event_handlers(self, event_bus):
-        """Register handlers for action events (LLM calls, tool usage, memory)"""
+        """Register handlers for action events (LLM calls, tool usage)"""
 
         @event_bus.on(LLMCallStartedEvent)
         def on_llm_call_started(source, event):
@@ -289,6 +304,9 @@ class TraceCollectionListener(BaseEventListener):
             "crewai_version": get_crewai_version(),
         }
 
+        self.batch_manager.batch_owner_type = "crew"
+        self.batch_manager.batch_owner_id = getattr(source, "id", str(uuid.uuid4()))
+
         self._initialize_batch(user_context, execution_metadata)
 
     def _initialize_flow_batch(self, source: Any, event: Any):
@@ -301,6 +319,9 @@ class TraceCollectionListener(BaseEventListener):
             "execution_type": "flow",
         }
 
+        self.batch_manager.batch_owner_type = "flow"
+        self.batch_manager.batch_owner_id = getattr(source, "id", str(uuid.uuid4()))
+
         self._initialize_batch(user_context, execution_metadata)
 
     def _initialize_batch(
@@ -358,12 +379,44 @@ class TraceCollectionListener(BaseEventListener):
             return {
                 "task_description": event.task.description,
                 "expected_output": event.task.expected_output,
-                "task_name": event.task.name,
+                "task_name": event.task.name or event.task.description,
                 "context": event.context,
-                "agent": source.agent.role,
+                "agent_role": source.agent.role,
+                "task_id": str(event.task.id),
+            }
+        elif event_type == "task_completed":
+            return {
+                "task_description": event.task.description if event.task else None,
+                "task_name": event.task.name or event.task.description
+                if event.task
+                else None,
+                "task_id": str(event.task.id) if event.task else None,
+                "output_raw": event.output.raw if event.output else None,
+                "output_format": str(event.output.output_format)
+                if event.output
+                else None,
+                "agent_role": event.output.agent if event.output else None,
+            }
+        elif event_type == "agent_execution_started":
+            return {
+                "agent_role": event.agent.role,
+                "agent_goal": event.agent.goal,
+                "agent_backstory": event.agent.backstory,
+            }
+        elif event_type == "agent_execution_completed":
+            return {
+                "agent_role": event.agent.role,
+                "agent_goal": event.agent.goal,
+                "agent_backstory": event.agent.backstory,
             }
         elif event_type == "llm_call_started":
-            return self._safe_serialize_to_dict(event)
+            event_data = self._safe_serialize_to_dict(event)
+            event_data["task_name"] = (
+                event.task_name or event.task_description
+                if hasattr(event, "task_name") and event.task_name
+                else None
+            )
+            return event_data
         elif event_type == "llm_call_completed":
             return self._safe_serialize_to_dict(event)
         else:

src/crewai/events/types/__init__.py

@@ -0,0 +1,5 @@
+"""Event type definitions for CrewAI.
+
+This module contains all event types used throughout the CrewAI system
+for monitoring and extending agent, crew, task, and tool execution.
+"""

src/crewai/events/types/agent_events.py

@@ -1,13 +1,15 @@
-from typing import TYPE_CHECKING, Any, Dict, List, Optional, Sequence, Union
+"""Agent-related events moved to break circular dependencies."""
+
+from __future__ import annotations
+
+from typing import Any, Dict, List, Optional, Sequence, Union
+
+from pydantic import model_validator
 
 from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.tools.base_tool import BaseTool
 from crewai.tools.structured_tool import CrewStructuredTool
-
-from .base_events import BaseEvent
-
-if TYPE_CHECKING:
-    from crewai.agents.agent_builder.base_agent import BaseAgent
+from crewai.events.base_events import BaseEvent
 
 
 class AgentExecutionStartedEvent(BaseEvent):
@@ -21,9 +23,9 @@ class AgentExecutionStartedEvent(BaseEvent):
 
     model_config = {"arbitrary_types_allowed": True}
 
-    def __init__(self, **data):
-        super().__init__(**data)
-        # Set fingerprint data from the agent
+    @model_validator(mode="after")
+    def set_fingerprint_data(self):
+        """Set fingerprint data from the agent if available."""
         if hasattr(self.agent, "fingerprint") and self.agent.fingerprint:
             self.source_fingerprint = self.agent.fingerprint.uuid_str
             self.source_type = "agent"
@@ -32,6 +34,7 @@ class AgentExecutionStartedEvent(BaseEvent):
                 and self.agent.fingerprint.metadata
             ):
                 self.fingerprint_metadata = self.agent.fingerprint.metadata
+        return self
 
 
 class AgentExecutionCompletedEvent(BaseEvent):
@@ -42,9 +45,11 @@ class AgentExecutionCompletedEvent(BaseEvent):
     output: str
     type: str = "agent_execution_completed"
 
-    def __init__(self, **data):
-        super().__init__(**data)
-        # Set fingerprint data from the agent
+    model_config = {"arbitrary_types_allowed": True}
+
+    @model_validator(mode="after")
+    def set_fingerprint_data(self):
+        """Set fingerprint data from the agent if available."""
         if hasattr(self.agent, "fingerprint") and self.agent.fingerprint:
             self.source_fingerprint = self.agent.fingerprint.uuid_str
             self.source_type = "agent"
@@ -53,6 +58,7 @@ class AgentExecutionCompletedEvent(BaseEvent):
                 and self.agent.fingerprint.metadata
             ):
                 self.fingerprint_metadata = self.agent.fingerprint.metadata
+        return self
 
 
 class AgentExecutionErrorEvent(BaseEvent):
@@ -63,9 +69,11 @@ class AgentExecutionErrorEvent(BaseEvent):
     error: str
     type: str = "agent_execution_error"
 
-    def __init__(self, **data):
-        super().__init__(**data)
-        # Set fingerprint data from the agent
+    model_config = {"arbitrary_types_allowed": True}
+
+    @model_validator(mode="after")
+    def set_fingerprint_data(self):
+        """Set fingerprint data from the agent if available."""
         if hasattr(self.agent, "fingerprint") and self.agent.fingerprint:
             self.source_fingerprint = self.agent.fingerprint.uuid_str
             self.source_type = "agent"
@@ -74,6 +82,7 @@ class AgentExecutionErrorEvent(BaseEvent):
                 and self.agent.fingerprint.metadata
             ):
                 self.fingerprint_metadata = self.agent.fingerprint.metadata
+        return self
 
 
 # New event classes for LiteAgent
@@ -104,26 +113,6 @@ class LiteAgentExecutionErrorEvent(BaseEvent):
     type: str = "lite_agent_execution_error"
 
 
-# New logging events
-class AgentLogsStartedEvent(BaseEvent):
-    """Event emitted when agent logs should be shown at start"""
-
-    agent_role: str
-    task_description: Optional[str] = None
-    verbose: bool = False
-    type: str = "agent_logs_started"
-
-
-class AgentLogsExecutionEvent(BaseEvent):
-    """Event emitted when agent logs should be shown during execution"""
-
-    agent_role: str
-    formatted_answer: Any
-    verbose: bool = False
-    type: str = "agent_logs_execution"
-
-    model_config = {"arbitrary_types_allowed": True}
-
 # Agent Eval events
 class AgentEvaluationStartedEvent(BaseEvent):
     agent_id: str
@@ -132,6 +121,7 @@ class AgentEvaluationStartedEvent(BaseEvent):
     iteration: int
     type: str = "agent_evaluation_started"
 
+
 class AgentEvaluationCompletedEvent(BaseEvent):
     agent_id: str
     agent_role: str
@@ -141,6 +131,7 @@ class AgentEvaluationCompletedEvent(BaseEvent):
     score: Any
     type: str = "agent_evaluation_completed"
 
+
 class AgentEvaluationFailedEvent(BaseEvent):
     agent_id: str
     agent_role: str

src/crewai/events/types/crew_events.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any, Dict, Optional, Union
 
-from crewai.utilities.events.base_events import BaseEvent
+from crewai.events.base_events import BaseEvent
 
 if TYPE_CHECKING:
     from crewai.crew import Crew

src/crewai/events/types/flow_events.py

@@ -2,7 +2,7 @@ from typing import Any, Dict, Optional, Union
 
 from pydantic import BaseModel, ConfigDict
 
-from .base_events import BaseEvent
+from crewai.events.base_events import BaseEvent
 
 
 class FlowEvent(BaseEvent):

src/crewai/events/types/knowledge_events.py

@@ -1,10 +1,6 @@
-from typing import TYPE_CHECKING, Any
+from crewai.events.base_events import BaseEvent
 
 from crewai.agents.agent_builder.base_agent import BaseAgent
-from crewai.utilities.events.base_events import BaseEvent
-
-if TYPE_CHECKING:
-    from crewai.agents.agent_builder.base_agent import BaseAgent
 
 
 class KnowledgeRetrievalStartedEvent(BaseEvent):
@@ -20,7 +16,7 @@ class KnowledgeRetrievalCompletedEvent(BaseEvent):
     query: str
     type: str = "knowledge_search_query_completed"
     agent: BaseAgent
-    retrieved_knowledge: Any
+    retrieved_knowledge: str
 
 
 class KnowledgeQueryStartedEvent(BaseEvent):

src/crewai/events/types/llm_events.py

@@ -3,7 +3,7 @@ from typing import Any, Dict, List, Optional, Union
 
 from pydantic import BaseModel
 
-from crewai.utilities.events.base_events import BaseEvent
+from crewai.events.base_events import BaseEvent
 
 
 class LLMEventBase(BaseEvent):
@@ -13,26 +13,14 @@ class LLMEventBase(BaseEvent):
     agent_id: Optional[str] = None
     agent_role: Optional[str] = None
 
+    from_task: Optional[Any] = None
+    from_agent: Optional[Any] = None
+
     def __init__(self, **data):
         super().__init__(**data)
         self._set_agent_params(data)
         self._set_task_params(data)
 
-    def _set_agent_params(self, data: Dict[str, Any]):
-        task = data.get("from_task", None)
-        agent = task.agent if task else data.get("from_agent", None)
-
-        if not agent:
-            return
-
-        self.agent_id = agent.id
-        self.agent_role = agent.role
-
-    def _set_task_params(self, data: Dict[str, Any]):
-        if "from_task" in data and (task := data["from_task"]):
-            self.task_id = task.id
-            self.task_name = task.name
-
 
 class LLMCallType(Enum):
     """Type of LLM call being made"""

src/crewai/events/types/llm_guardrail_events.py

@@ -1,7 +1,7 @@
 from inspect import getsource
 from typing import Any, Callable, Optional, Union
 
-from crewai.utilities.events.base_events import BaseEvent
+from crewai.events.base_events import BaseEvent
 
 
 class LLMGuardrailStartedEvent(BaseEvent):

src/crewai/events/types/logging_events.py

@@ -0,0 +1,25 @@
+"""Agent logging events that don't reference BaseAgent to avoid circular imports."""
+
+from typing import Any, Optional
+
+from crewai.events.base_events import BaseEvent
+
+
+class AgentLogsStartedEvent(BaseEvent):
+    """Event emitted when agent logs should be shown at start"""
+
+    agent_role: str
+    task_description: Optional[str] = None
+    verbose: bool = False
+    type: str = "agent_logs_started"
+
+
+class AgentLogsExecutionEvent(BaseEvent):
+    """Event emitted when agent logs should be shown during execution"""
+
+    agent_role: str
+    formatted_answer: Any
+    verbose: bool = False
+    type: str = "agent_logs_execution"
+
+    model_config = {"arbitrary_types_allowed": True}

src/crewai/events/types/memory_events.py

@@ -1,9 +1,26 @@
 from typing import Any, Dict, Optional
 
-from crewai.utilities.events.base_events import BaseEvent
+from crewai.events.base_events import BaseEvent
 
 
-class MemoryQueryStartedEvent(BaseEvent):
+class MemoryBaseEvent(BaseEvent):
+    """Base event for memory operations"""
+
+    type: str
+    task_id: Optional[str] = None
+    task_name: Optional[str] = None
+    from_task: Optional[Any] = None
+    from_agent: Optional[Any] = None
+    agent_role: Optional[str] = None
+    agent_id: Optional[str] = None
+
+    def __init__(self, **data):
+        super().__init__(**data)
+        self._set_agent_params(data)
+        self._set_task_params(data)
+
+
+class MemoryQueryStartedEvent(MemoryBaseEvent):
     """Event emitted when a memory query is started"""
 
     type: str = "memory_query_started"
@@ -12,7 +29,7 @@ class MemoryQueryStartedEvent(BaseEvent):
     score_threshold: Optional[float] = None
 
 
-class MemoryQueryCompletedEvent(BaseEvent):
+class MemoryQueryCompletedEvent(MemoryBaseEvent):
     """Event emitted when a memory query is completed successfully"""
 
     type: str = "memory_query_completed"
@@ -23,7 +40,7 @@ class MemoryQueryCompletedEvent(BaseEvent):
     query_time_ms: float
 
 
-class MemoryQueryFailedEvent(BaseEvent):
+class MemoryQueryFailedEvent(MemoryBaseEvent):
     """Event emitted when a memory query fails"""
 
     type: str = "memory_query_failed"
@@ -33,7 +50,7 @@ class MemoryQueryFailedEvent(BaseEvent):
     error: str
 
 
-class MemorySaveStartedEvent(BaseEvent):
+class MemorySaveStartedEvent(MemoryBaseEvent):
     """Event emitted when a memory save operation is started"""
 
     type: str = "memory_save_started"
@@ -42,7 +59,7 @@ class MemorySaveStartedEvent(BaseEvent):
     agent_role: Optional[str] = None
 
 
-class MemorySaveCompletedEvent(BaseEvent):
+class MemorySaveCompletedEvent(MemoryBaseEvent):
     """Event emitted when a memory save operation is completed successfully"""
 
     type: str = "memory_save_completed"
@@ -52,7 +69,7 @@ class MemorySaveCompletedEvent(BaseEvent):
     save_time_ms: float
 
 
-class MemorySaveFailedEvent(BaseEvent):
+class MemorySaveFailedEvent(MemoryBaseEvent):
     """Event emitted when a memory save operation fails"""
 
     type: str = "memory_save_failed"
@@ -62,14 +79,14 @@ class MemorySaveFailedEvent(BaseEvent):
     error: str
 
 
-class MemoryRetrievalStartedEvent(BaseEvent):
+class MemoryRetrievalStartedEvent(MemoryBaseEvent):
     """Event emitted when memory retrieval for a task prompt starts"""
 
     type: str = "memory_retrieval_started"
     task_id: Optional[str] = None
 
 
-class MemoryRetrievalCompletedEvent(BaseEvent):
+class MemoryRetrievalCompletedEvent(MemoryBaseEvent):
     """Event emitted when memory retrieval for a task prompt completes successfully"""
 
     type: str = "memory_retrieval_completed"

src/crewai/events/types/reasoning_events.py

@@ -0,0 +1,47 @@
+from crewai.events.base_events import BaseEvent
+from typing import Any, Optional
+
+
+class ReasoningEvent(BaseEvent):
+    """Base event for reasoning events."""
+
+    type: str
+    attempt: int = 1
+    agent_role: str
+    task_id: str
+    task_name: Optional[str] = None
+    from_task: Optional[Any] = None
+    agent_id: Optional[str] = None
+    from_agent: Optional[Any] = None
+
+    def __init__(self, **data):
+        super().__init__(**data)
+        self._set_task_params(data)
+        self._set_agent_params(data)
+
+
+class AgentReasoningStartedEvent(ReasoningEvent):
+    """Event emitted when an agent starts reasoning about a task."""
+
+    type: str = "agent_reasoning_started"
+    agent_role: str
+    task_id: str
+
+
+class AgentReasoningCompletedEvent(ReasoningEvent):
+    """Event emitted when an agent finishes its reasoning process."""
+
+    type: str = "agent_reasoning_completed"
+    agent_role: str
+    task_id: str
+    plan: str
+    ready: bool
+
+
+class AgentReasoningFailedEvent(ReasoningEvent):
+    """Event emitted when the reasoning process fails."""
+
+    type: str = "agent_reasoning_failed"
+    agent_role: str
+    task_id: str
+    error: str

src/crewai/events/types/task_events.py

@@ -1,7 +1,7 @@
 from typing import Any, Optional
 
 from crewai.tasks.task_output import TaskOutput
-from crewai.utilities.events.base_events import BaseEvent
+from crewai.events.base_events import BaseEvent
 
 
 class TaskStartedEvent(BaseEvent):

src/crewai/events/types/tool_usage_events.py

@@ -1,7 +1,7 @@
 from datetime import datetime
 from typing import Any, Callable, Dict, Optional
 
-from .base_events import BaseEvent
+from crewai.events.base_events import BaseEvent
 
 
 class ToolUsageEvent(BaseEvent):
@@ -9,17 +9,24 @@ class ToolUsageEvent(BaseEvent):
 
     agent_key: Optional[str] = None
     agent_role: Optional[str] = None
+    agent_id: Optional[str] = None
     tool_name: str
     tool_args: Dict[str, Any] | str
     tool_class: Optional[str] = None
     run_attempts: int | None = None
     delegations: int | None = None
     agent: Optional[Any] = None
+    task_name: Optional[str] = None
+    task_id: Optional[str] = None
+    from_task: Optional[Any] = None
+    from_agent: Optional[Any] = None
 
     model_config = {"arbitrary_types_allowed": True}
 
     def __init__(self, **data):
         super().__init__(**data)
+        self._set_agent_params(data)
+        self._set_task_params(data)
         # Set fingerprint data from the agent
         if self.agent and hasattr(self.agent, "fingerprint") and self.agent.fingerprint:
             self.source_fingerprint = self.agent.fingerprint.uuid_str

src/crewai/events/utils/console_formatter.py

@@ -227,7 +227,7 @@ class ConsoleFormatter:
             return None
 
         task_content = Text()
-        
+
         # Display task name if available, otherwise just the ID
         if task_name:
             task_content.append("📋 Task: ", style="yellow bold")
@@ -235,7 +235,7 @@ class ConsoleFormatter:
             task_content.append(f" (ID: {task_id})", style="yellow dim")
         else:
             task_content.append(f"📋 Task: {task_id}", style="yellow bold")
-            
+
         task_content.append("\nStatus: ", style="white")
         task_content.append("Executing Task...", style="yellow dim")
 

src/crewai/experimental/evaluation/agent_evaluator.py

@@ -1,28 +1,42 @@
 import threading
-from typing import Any
+from typing import Any, Optional
 
-from crewai.experimental.evaluation.base_evaluator import AgentEvaluationResult, AggregationStrategy
+from crewai.experimental.evaluation.base_evaluator import (
+    AgentEvaluationResult,
+    AggregationStrategy,
+)
 from crewai.agent import Agent
 from crewai.task import Task
 from crewai.experimental.evaluation.evaluation_display import EvaluationDisplayFormatter
-from crewai.utilities.events.agent_events import AgentEvaluationStartedEvent, AgentEvaluationCompletedEvent, AgentEvaluationFailedEvent
+from crewai.events.types.agent_events import (
+    AgentEvaluationStartedEvent,
+    AgentEvaluationCompletedEvent,
+    AgentEvaluationFailedEvent,
+)
 from crewai.experimental.evaluation import BaseEvaluator, create_evaluation_callbacks
 from collections.abc import Sequence
-from crewai.utilities.events.crewai_event_bus import crewai_event_bus
-from crewai.utilities.events.utils.console_formatter import ConsoleFormatter
-from crewai.utilities.events.task_events import TaskCompletedEvent
-from crewai.utilities.events.agent_events import LiteAgentExecutionCompletedEvent
-from crewai.experimental.evaluation.base_evaluator import AgentAggregatedEvaluationResult, EvaluationScore, MetricCategory
+from crewai.events.event_bus import crewai_event_bus
+from crewai.events.utils.console_formatter import ConsoleFormatter
+from crewai.events.types.task_events import TaskCompletedEvent
+from crewai.events.types.agent_events import LiteAgentExecutionCompletedEvent
+from crewai.experimental.evaluation.base_evaluator import (
+    AgentAggregatedEvaluationResult,
+    EvaluationScore,
+    MetricCategory,
+)
+
 
 class ExecutionState:
+    current_agent_id: Optional[str] = None
+    current_task_id: Optional[str] = None
+
     def __init__(self):
         self.traces = {}
-        self.current_agent_id: str | None = None
-        self.current_task_id: str | None = None
         self.iteration = 1
         self.iterations_results = {}
         self.agent_evaluators = {}
 
+
 class AgentEvaluator:
     def __init__(
         self,
@@ -45,27 +59,45 @@ class AgentEvaluator:
 
     @property
     def _execution_state(self) -> ExecutionState:
-        if not hasattr(self._thread_local, 'execution_state'):
+        if not hasattr(self._thread_local, "execution_state"):
             self._thread_local.execution_state = ExecutionState()
         return self._thread_local.execution_state
 
     def _subscribe_to_events(self) -> None:
         from typing import cast
-        crewai_event_bus.register_handler(TaskCompletedEvent, cast(Any, self._handle_task_completed))
-        crewai_event_bus.register_handler(LiteAgentExecutionCompletedEvent, cast(Any, self._handle_lite_agent_completed))
+
+        crewai_event_bus.register_handler(
+            TaskCompletedEvent, cast(Any, self._handle_task_completed)
+        )
+        crewai_event_bus.register_handler(
+            LiteAgentExecutionCompletedEvent,
+            cast(Any, self._handle_lite_agent_completed),
+        )
 
     def _handle_task_completed(self, source: Any, event: TaskCompletedEvent) -> None:
         assert event.task is not None
         agent = event.task.agent
-        if agent and str(getattr(agent, 'id', 'unknown')) in self._execution_state.agent_evaluators:
-            self.emit_evaluation_started_event(agent_role=agent.role, agent_id=str(agent.id), task_id=str(event.task.id))
+        if (
+            agent
+            and str(getattr(agent, "id", "unknown"))
+            in self._execution_state.agent_evaluators
+        ):
+            self.emit_evaluation_started_event(
+                agent_role=agent.role,
+                agent_id=str(agent.id),
+                task_id=str(event.task.id),
+            )
 
             state = ExecutionState()
             state.current_agent_id = str(agent.id)
             state.current_task_id = str(event.task.id)
 
-            assert state.current_agent_id is not None and state.current_task_id is not None
-            trace = self.callback.get_trace(state.current_agent_id, state.current_task_id)
+            assert (
+                state.current_agent_id is not None and state.current_task_id is not None
+            )
+            trace = self.callback.get_trace(
+                state.current_agent_id, state.current_task_id
+            )
 
             if not trace:
                 return
@@ -75,19 +107,28 @@ class AgentEvaluator:
                 task=event.task,
                 execution_trace=trace,
                 final_output=event.output,
-                state=state
+                state=state,
             )
 
             current_iteration = self._execution_state.iteration
             if current_iteration not in self._execution_state.iterations_results:
                 self._execution_state.iterations_results[current_iteration] = {}
 
-            if agent.role not in self._execution_state.iterations_results[current_iteration]:
-                self._execution_state.iterations_results[current_iteration][agent.role] = []
+            if (
+                agent.role
+                not in self._execution_state.iterations_results[current_iteration]
+            ):
+                self._execution_state.iterations_results[current_iteration][
+                    agent.role
+                ] = []
 
-            self._execution_state.iterations_results[current_iteration][agent.role].append(result)
+            self._execution_state.iterations_results[current_iteration][
+                agent.role
+            ].append(result)
 
-    def _handle_lite_agent_completed(self, source: object, event: LiteAgentExecutionCompletedEvent) -> None:
+    def _handle_lite_agent_completed(
+        self, source: object, event: LiteAgentExecutionCompletedEvent
+    ) -> None:
         agent_info = event.agent_info
         agent_id = str(agent_info["id"])
 
@@ -105,8 +146,12 @@ class AgentEvaluator:
             if not target_agent:
                 return
 
-            assert state.current_agent_id is not None and state.current_task_id is not None
-            trace = self.callback.get_trace(state.current_agent_id, state.current_task_id)
+            assert (
+                state.current_agent_id is not None and state.current_task_id is not None
+            )
+            trace = self.callback.get_trace(
+                state.current_agent_id, state.current_task_id
+            )
 
             if not trace:
                 return
@@ -115,7 +160,7 @@ class AgentEvaluator:
                 agent=target_agent,
                 execution_trace=trace,
                 final_output=event.output,
-                state=state
+                state=state,
             )
 
             current_iteration = self._execution_state.iteration
@@ -123,10 +168,17 @@ class AgentEvaluator:
                 self._execution_state.iterations_results[current_iteration] = {}
 
             agent_role = target_agent.role
-            if agent_role not in self._execution_state.iterations_results[current_iteration]:
-                self._execution_state.iterations_results[current_iteration][agent_role] = []
+            if (
+                agent_role
+                not in self._execution_state.iterations_results[current_iteration]
+            ):
+                self._execution_state.iterations_results[current_iteration][
+                    agent_role
+                ] = []
 
-            self._execution_state.iterations_results[current_iteration][agent_role].append(result)
+            self._execution_state.iterations_results[current_iteration][
+                agent_role
+            ].append(result)
 
     def set_iteration(self, iteration: int) -> None:
         self._execution_state.iteration = iteration
@@ -135,14 +187,26 @@ class AgentEvaluator:
         self._execution_state.iterations_results = {}
 
     def get_evaluation_results(self) -> dict[str, list[AgentEvaluationResult]]:
-        if self._execution_state.iterations_results and self._execution_state.iteration in self._execution_state.iterations_results:
-            return self._execution_state.iterations_results[self._execution_state.iteration]
+        if (
+            self._execution_state.iterations_results
+            and self._execution_state.iteration
+            in self._execution_state.iterations_results
+        ):
+            return self._execution_state.iterations_results[
+                self._execution_state.iteration
+            ]
         return {}
 
     def display_results_with_iterations(self) -> None:
-        self.display_formatter.display_summary_results(self._execution_state.iterations_results)
+        self.display_formatter.display_summary_results(
+            self._execution_state.iterations_results
+        )
 
-    def get_agent_evaluation(self, strategy: AggregationStrategy = AggregationStrategy.SIMPLE_AVERAGE, include_evaluation_feedback: bool = True) -> dict[str, AgentAggregatedEvaluationResult]:
+    def get_agent_evaluation(
+        self,
+        strategy: AggregationStrategy = AggregationStrategy.SIMPLE_AVERAGE,
+        include_evaluation_feedback: bool = True,
+    ) -> dict[str, AgentAggregatedEvaluationResult]:
         agent_results = {}
         with crewai_event_bus.scoped_handlers():
             task_results = self.get_evaluation_results()
@@ -156,13 +220,16 @@ class AgentEvaluator:
                     agent_id=agent_id,
                     agent_role=agent_role,
                     results=results,
-                    strategy=strategy
+                    strategy=strategy,
                 )
 
                 agent_results[agent_role] = aggregated_result
 
-
-            if self._execution_state.iterations_results and self._execution_state.iteration == max(self._execution_state.iterations_results.keys(), default=0):
+            if (
+                self._execution_state.iterations_results
+                and self._execution_state.iteration
+                == max(self._execution_state.iterations_results.keys(), default=0)
+            ):
                 self.display_results_with_iterations()
 
             if include_evaluation_feedback:
@@ -171,7 +238,9 @@ class AgentEvaluator:
         return agent_results
 
     def display_evaluation_with_feedback(self) -> None:
-        self.display_formatter.display_evaluation_with_feedback(self._execution_state.iterations_results)
+        self.display_formatter.display_evaluation_with_feedback(
+            self._execution_state.iterations_results
+        )
 
     def evaluate(
         self,
@@ -183,46 +252,91 @@ class AgentEvaluator:
     ) -> AgentEvaluationResult:
         result = AgentEvaluationResult(
             agent_id=state.current_agent_id or str(agent.id),
-            task_id=state.current_task_id or (str(task.id) if task else "unknown_task")
+            task_id=state.current_task_id or (str(task.id) if task else "unknown_task"),
         )
 
         assert self.evaluators is not None
         task_id = str(task.id) if task else None
         for evaluator in self.evaluators:
             try:
-                self.emit_evaluation_started_event(agent_role=agent.role, agent_id=str(agent.id), task_id=task_id)
+                self.emit_evaluation_started_event(
+                    agent_role=agent.role, agent_id=str(agent.id), task_id=task_id
+                )
                 score = evaluator.evaluate(
                     agent=agent,
                     task=task,
                     execution_trace=execution_trace,
-                    final_output=final_output
+                    final_output=final_output,
                 )
                 result.metrics[evaluator.metric_category] = score
-                self.emit_evaluation_completed_event(agent_role=agent.role, agent_id=str(agent.id), task_id=task_id, metric_category=evaluator.metric_category, score=score)
+                self.emit_evaluation_completed_event(
+                    agent_role=agent.role,
+                    agent_id=str(agent.id),
+                    task_id=task_id,
+                    metric_category=evaluator.metric_category,
+                    score=score,
+                )
             except Exception as e:
-                self.emit_evaluation_failed_event(agent_role=agent.role, agent_id=str(agent.id), task_id=task_id, error=str(e))
-                self.console_formatter.print(f"Error in {evaluator.metric_category.value} evaluator: {str(e)}")
+                self.emit_evaluation_failed_event(
+                    agent_role=agent.role,
+                    agent_id=str(agent.id),
+                    task_id=task_id,
+                    error=str(e),
+                )
+                self.console_formatter.print(
+                    f"Error in {evaluator.metric_category.value} evaluator: {str(e)}"
+                )
 
         return result
 
-    def emit_evaluation_started_event(self, agent_role: str, agent_id: str, task_id: str | None = None):
+    def emit_evaluation_started_event(
+        self, agent_role: str, agent_id: str, task_id: str | None = None
+    ):
         crewai_event_bus.emit(
             self,
-            AgentEvaluationStartedEvent(agent_role=agent_role, agent_id=agent_id, task_id=task_id, iteration=self._execution_state.iteration)
+            AgentEvaluationStartedEvent(
+                agent_role=agent_role,
+                agent_id=agent_id,
+                task_id=task_id,
+                iteration=self._execution_state.iteration,
+            ),
         )
 
-    def emit_evaluation_completed_event(self, agent_role: str, agent_id: str, task_id: str | None = None, metric_category: MetricCategory | None = None, score: EvaluationScore | None = None):
+    def emit_evaluation_completed_event(
+        self,
+        agent_role: str,
+        agent_id: str,
+        task_id: str | None = None,
+        metric_category: MetricCategory | None = None,
+        score: EvaluationScore | None = None,
+    ):
         crewai_event_bus.emit(
             self,
-            AgentEvaluationCompletedEvent(agent_role=agent_role, agent_id=agent_id, task_id=task_id, iteration=self._execution_state.iteration, metric_category=metric_category, score=score)
+            AgentEvaluationCompletedEvent(
+                agent_role=agent_role,
+                agent_id=agent_id,
+                task_id=task_id,
+                iteration=self._execution_state.iteration,
+                metric_category=metric_category,
+                score=score,
+            ),
         )
 
-    def emit_evaluation_failed_event(self, agent_role: str, agent_id: str, error: str, task_id: str | None = None):
+    def emit_evaluation_failed_event(
+        self, agent_role: str, agent_id: str, error: str, task_id: str | None = None
+    ):
         crewai_event_bus.emit(
             self,
-            AgentEvaluationFailedEvent(agent_role=agent_role, agent_id=agent_id, task_id=task_id, iteration=self._execution_state.iteration, error=error)
+            AgentEvaluationFailedEvent(
+                agent_role=agent_role,
+                agent_id=agent_id,
+                task_id=task_id,
+                iteration=self._execution_state.iteration,
+                error=error,
+            ),
         )
 
+
 def create_default_evaluator(agents: list[Agent], llm: None = None):
     from crewai.experimental.evaluation import (
         GoalAlignmentEvaluator,
@@ -230,7 +344,7 @@ def create_default_evaluator(agents: list[Agent], llm: None = None):
         ToolSelectionEvaluator,
         ParameterExtractionEvaluator,
         ToolInvocationEvaluator,
-        ReasoningEfficiencyEvaluator
+        ReasoningEfficiencyEvaluator,
     )
 
     evaluators = [

src/crewai/experimental/evaluation/evaluation_display.py

@@ -3,18 +3,28 @@ from typing import Dict, Any, List
 from rich.table import Table
 from rich.box import HEAVY_EDGE, ROUNDED
 from collections.abc import Sequence
-from crewai.experimental.evaluation.base_evaluator import AgentAggregatedEvaluationResult, AggregationStrategy, AgentEvaluationResult, MetricCategory
+from crewai.experimental.evaluation.base_evaluator import (
+    AgentAggregatedEvaluationResult,
+    AggregationStrategy,
+    AgentEvaluationResult,
+    MetricCategory,
+)
 from crewai.experimental.evaluation import EvaluationScore
-from crewai.utilities.events.utils.console_formatter import ConsoleFormatter
+from crewai.events.utils.console_formatter import ConsoleFormatter
 from crewai.utilities.llm_utils import create_llm
 
+
 class EvaluationDisplayFormatter:
     def __init__(self):
         self.console_formatter = ConsoleFormatter()
 
-    def display_evaluation_with_feedback(self, iterations_results: Dict[int, Dict[str, List[Any]]]):
+    def display_evaluation_with_feedback(
+        self, iterations_results: Dict[int, Dict[str, List[Any]]]
+    ):
         if not iterations_results:
-            self.console_formatter.print("[yellow]No evaluation results to display[/yellow]")
+            self.console_formatter.print(
+                "[yellow]No evaluation results to display[/yellow]"
+            )
             return
 
         all_agent_roles: set[str] = set()
@@ -22,7 +32,9 @@ class EvaluationDisplayFormatter:
             all_agent_roles.update(iter_results.keys())
 
         for agent_role in sorted(all_agent_roles):
-            self.console_formatter.print(f"\n[bold cyan]Agent: {agent_role}[/bold cyan]")
+            self.console_formatter.print(
+                f"\n[bold cyan]Agent: {agent_role}[/bold cyan]"
+            )
 
             for iter_num, results in sorted(iterations_results.items()):
                 if agent_role not in results or not results[agent_role]:
@@ -62,9 +74,7 @@ class EvaluationDisplayFormatter:
 
                         table.add_section()
                         table.add_row(
-                            metric.title(),
-                            score_text,
-                            evaluation_score.feedback or ""
+                            metric.title(), score_text, evaluation_score.feedback or ""
                         )
 
                 if aggregated_result.overall_score is not None:
@@ -82,19 +92,26 @@ class EvaluationDisplayFormatter:
                     table.add_row(
                         "Overall Score",
                         f"[{overall_color}]{overall_score:.1f}[/]",
-                        "Overall agent evaluation score"
+                        "Overall agent evaluation score",
                     )
 
                 self.console_formatter.print(table)
 
-    def display_summary_results(self, iterations_results: Dict[int, Dict[str, List[AgentAggregatedEvaluationResult]]]):
+    def display_summary_results(
+        self,
+        iterations_results: Dict[int, Dict[str, List[AgentAggregatedEvaluationResult]]],
+    ):
         if not iterations_results:
-            self.console_formatter.print("[yellow]No evaluation results to display[/yellow]")
+            self.console_formatter.print(
+                "[yellow]No evaluation results to display[/yellow]"
+            )
             return
 
         self.console_formatter.print("\n")
 
-        table = Table(title="Agent Performance Scores \n (1-10 Higher is better)", box=HEAVY_EDGE)
+        table = Table(
+            title="Agent Performance Scores \n (1-10 Higher is better)", box=HEAVY_EDGE
+        )
 
         table.add_column("Agent/Metric", style="cyan")
 
@@ -123,11 +140,14 @@ class EvaluationDisplayFormatter:
                     agent_id=agent_id,
                     agent_role=agent_role,
                     results=agent_results,
-                    strategy=AggregationStrategy.SIMPLE_AVERAGE
+                    strategy=AggregationStrategy.SIMPLE_AVERAGE,
                 )
 
-                valid_scores = [score.score for score in aggregated_result.metrics.values()
-                               if score.score is not None]
+                valid_scores = [
+                    score.score
+                    for score in aggregated_result.metrics.values()
+                    if score.score is not None
+                ]
                 if valid_scores:
                     avg_score = sum(valid_scores) / len(valid_scores)
                     agent_scores_by_iteration[iter_num] = avg_score
@@ -137,7 +157,9 @@ class EvaluationDisplayFormatter:
             if not agent_scores_by_iteration:
                 continue
 
-            avg_across_iterations = sum(agent_scores_by_iteration.values()) / len(agent_scores_by_iteration)
+            avg_across_iterations = sum(agent_scores_by_iteration.values()) / len(
+                agent_scores_by_iteration
+            )
 
             row = [f"[bold]{agent_role}[/bold]"]
 
@@ -178,9 +200,13 @@ class EvaluationDisplayFormatter:
                 row = [f"  - {metric.title()}"]
 
                 for iter_num in sorted(iterations_results.keys()):
-                    if (iter_num in agent_metrics_by_iteration and
-                            metric in agent_metrics_by_iteration[iter_num]):
-                        metric_score = agent_metrics_by_iteration[iter_num][metric].score
+                    if (
+                        iter_num in agent_metrics_by_iteration
+                        and metric in agent_metrics_by_iteration[iter_num]
+                    ):
+                        metric_score = agent_metrics_by_iteration[iter_num][
+                            metric
+                        ].score
                         if metric_score is not None:
                             metric_scores.append(metric_score)
                             if metric_score >= 8.0:
@@ -225,7 +251,9 @@ class EvaluationDisplayFormatter:
         results: Sequence[AgentEvaluationResult],
         strategy: AggregationStrategy = AggregationStrategy.SIMPLE_AVERAGE,
     ) -> AgentAggregatedEvaluationResult:
-        metrics_by_category: dict[MetricCategory, list[EvaluationScore]] = defaultdict(list)
+        metrics_by_category: dict[MetricCategory, list[EvaluationScore]] = defaultdict(
+            list
+        )
 
         for result in results:
             for metric_name, evaluation_score in result.metrics.items():
@@ -246,19 +274,20 @@ class EvaluationDisplayFormatter:
                         metric=category.title(),
                         feedbacks=feedbacks,
                         scores=[s.score for s in scores],
-                        strategy=strategy
+                        strategy=strategy,
                     )
                 else:
                     feedback_summary = feedbacks[0]
 
             aggregated_metrics[category] = EvaluationScore(
-                score=avg_score,
-                feedback=feedback_summary
+                score=avg_score, feedback=feedback_summary
             )
 
         overall_score = None
         if aggregated_metrics:
-            valid_scores = [m.score for m in aggregated_metrics.values() if m.score is not None]
+            valid_scores = [
+                m.score for m in aggregated_metrics.values() if m.score is not None
+            ]
             if valid_scores:
                 overall_score = sum(valid_scores) / len(valid_scores)
 
@@ -268,7 +297,7 @@ class EvaluationDisplayFormatter:
             metrics=aggregated_metrics,
             overall_score=overall_score,
             task_count=len(results),
-            aggregation_strategy=strategy
+            aggregation_strategy=strategy,
         )
 
     def _summarize_feedbacks(
@@ -277,10 +306,12 @@ class EvaluationDisplayFormatter:
         metric: str,
         feedbacks: List[str],
         scores: List[float | None],
-        strategy: AggregationStrategy
+        strategy: AggregationStrategy,
     ) -> str:
         if len(feedbacks) <= 2 and all(len(fb) < 200 for fb in feedbacks):
-            return "\n\n".join([f"Feedback {i+1}: {fb}" for i, fb in enumerate(feedbacks)])
+            return "\n\n".join(
+                [f"Feedback {i+1}: {fb}" for i, fb in enumerate(feedbacks)]
+            )
 
         try:
             llm = create_llm()
@@ -290,20 +321,26 @@ class EvaluationDisplayFormatter:
                 if len(feedback) > 500:
                     feedback = feedback[:500] + "..."
                 score_text = f"{score:.1f}" if score is not None else "N/A"
-                formatted_feedbacks.append(f"Feedback #{i+1} (Score: {score_text}):\n{feedback}")
+                formatted_feedbacks.append(
+                    f"Feedback #{i+1} (Score: {score_text}):\n{feedback}"
+                )
 
             all_feedbacks = "\n\n" + "\n\n---\n\n".join(formatted_feedbacks)
 
             strategy_guidance = ""
             if strategy == AggregationStrategy.BEST_PERFORMANCE:
-                strategy_guidance = "Focus on the highest-scoring aspects and strengths demonstrated."
+                strategy_guidance = (
+                    "Focus on the highest-scoring aspects and strengths demonstrated."
+                )
             elif strategy == AggregationStrategy.WORST_PERFORMANCE:
                 strategy_guidance = "Focus on areas that need improvement and common issues across tasks."
             else:
                 strategy_guidance = "Provide a balanced analysis of strengths and weaknesses across all tasks."
 
             prompt = [
-                {"role": "system", "content": f"""You are an expert evaluator creating a comprehensive summary of agent performance feedback.
+                {
+                    "role": "system",
+                    "content": f"""You are an expert evaluator creating a comprehensive summary of agent performance feedback.
                 Your job is to synthesize multiple feedback points about the same metric across different tasks.
 
                 Create a concise, insightful summary that captures the key patterns and themes from all feedback.
@@ -315,14 +352,18 @@ class EvaluationDisplayFormatter:
                 3. Highlighting patterns across tasks
                 4. 150-250 words in length
 
-                The summary should be directly usable as final feedback for the agent's performance on this metric."""},
-                {"role": "user", "content": f"""I need a synthesized summary of the following feedback for:
+                The summary should be directly usable as final feedback for the agent's performance on this metric.""",
+                },
+                {
+                    "role": "user",
+                    "content": f"""I need a synthesized summary of the following feedback for:
 
                 Agent Role: {agent_role}
                 Metric: {metric.title()}
 
                 {all_feedbacks}
-                """}
+                """,
+                },
             ]
             assert llm is not None
             response = llm.call(prompt)
@@ -330,4 +371,6 @@ class EvaluationDisplayFormatter:
             return response
 
         except Exception:
-            return "Synthesized from multiple tasks: " + "\n\n".join([f"- {fb[:500]}..." for fb in feedbacks])
+            return "Synthesized from multiple tasks: " + "\n\n".join(
+                [f"- {fb[:500]}..." for fb in feedbacks]
+            )

src/crewai/experimental/evaluation/evaluation_listener.py

@@ -5,25 +5,23 @@ from collections.abc import Sequence
 
 from crewai.agent import Agent
 from crewai.task import Task
-from crewai.utilities.events.base_event_listener import BaseEventListener
-from crewai.utilities.events.crewai_event_bus import CrewAIEventsBus
-from crewai.utilities.events.agent_events import (
+from crewai.events.base_event_listener import BaseEventListener
+from crewai.events.event_bus import CrewAIEventsBus
+from crewai.events.types.agent_events import (
     AgentExecutionStartedEvent,
     AgentExecutionCompletedEvent,
     LiteAgentExecutionStartedEvent,
-    LiteAgentExecutionCompletedEvent
+    LiteAgentExecutionCompletedEvent,
 )
-from crewai.utilities.events.tool_usage_events import (
+from crewai.events.types.tool_usage_events import (
     ToolUsageFinishedEvent,
     ToolUsageErrorEvent,
     ToolExecutionErrorEvent,
     ToolSelectionErrorEvent,
-    ToolValidateInputErrorEvent
-)
-from crewai.utilities.events.llm_events import (
-    LLMCallStartedEvent,
-    LLMCallCompletedEvent
+    ToolValidateInputErrorEvent,
 )
+from crewai.events.types.llm_events import LLMCallStartedEvent, LLMCallCompletedEvent
+
 
 class EvaluationTraceCallback(BaseEventListener):
     """Event listener for collecting execution traces for evaluation.
@@ -68,27 +66,49 @@ class EvaluationTraceCallback(BaseEventListener):
 
         @event_bus.on(ToolUsageFinishedEvent)
         def on_tool_completed(source, event: ToolUsageFinishedEvent):
-            self.on_tool_use(event.tool_name, event.tool_args, event.output, success=True)
+            self.on_tool_use(
+                event.tool_name, event.tool_args, event.output, success=True
+            )
 
         @event_bus.on(ToolUsageErrorEvent)
         def on_tool_usage_error(source, event: ToolUsageErrorEvent):
-            self.on_tool_use(event.tool_name, event.tool_args, event.error,
-                           success=False, error_type="usage_error")
+            self.on_tool_use(
+                event.tool_name,
+                event.tool_args,
+                event.error,
+                success=False,
+                error_type="usage_error",
+            )
 
         @event_bus.on(ToolExecutionErrorEvent)
         def on_tool_execution_error(source, event: ToolExecutionErrorEvent):
-            self.on_tool_use(event.tool_name, event.tool_args, event.error,
-                           success=False, error_type="execution_error")
+            self.on_tool_use(
+                event.tool_name,
+                event.tool_args,
+                event.error,
+                success=False,
+                error_type="execution_error",
+            )
 
         @event_bus.on(ToolSelectionErrorEvent)
         def on_tool_selection_error(source, event: ToolSelectionErrorEvent):
-            self.on_tool_use(event.tool_name, event.tool_args, event.error,
-                           success=False, error_type="selection_error")
+            self.on_tool_use(
+                event.tool_name,
+                event.tool_args,
+                event.error,
+                success=False,
+                error_type="selection_error",
+            )
 
         @event_bus.on(ToolValidateInputErrorEvent)
         def on_tool_validate_input_error(source, event: ToolValidateInputErrorEvent):
-            self.on_tool_use(event.tool_name, event.tool_args, event.error,
-                           success=False, error_type="validation_error")
+            self.on_tool_use(
+                event.tool_name,
+                event.tool_args,
+                event.error,
+                success=False,
+                error_type="validation_error",
+            )
 
         @event_bus.on(LLMCallStartedEvent)
         def on_llm_call_started(source, event: LLMCallStartedEvent):
@@ -99,7 +119,7 @@ class EvaluationTraceCallback(BaseEventListener):
             self.on_llm_call_end(event.messages, event.response)
 
     def on_lite_agent_start(self, agent_info: dict[str, Any]):
-        self.current_agent_id = agent_info['id']
+        self.current_agent_id = agent_info["id"]
         self.current_task_id = "lite_task"
 
         trace_key = f"{self.current_agent_id}_{self.current_task_id}"
@@ -110,7 +130,7 @@ class EvaluationTraceCallback(BaseEventListener):
             tool_uses=[],
             llm_calls=[],
             start_time=datetime.now(),
-            final_output=None
+            final_output=None,
         )
 
     def _init_trace(self, trace_key: str, **kwargs: Any):
@@ -128,7 +148,7 @@ class EvaluationTraceCallback(BaseEventListener):
             tool_uses=[],
             llm_calls=[],
             start_time=datetime.now(),
-            final_output=None
+            final_output=None,
         )
 
     def on_agent_finish(self, agent: Agent, task: Task, output: Any):
@@ -151,8 +171,14 @@ class EvaluationTraceCallback(BaseEventListener):
 
         self._reset_current()
 
-    def on_tool_use(self, tool_name: str, tool_args: dict[str, Any] | str, result: Any,
-                   success: bool = True, error_type: str | None = None):
+    def on_tool_use(
+        self,
+        tool_name: str,
+        tool_args: dict[str, Any] | str,
+        result: Any,
+        success: bool = True,
+        error_type: str | None = None,
+    ):
         if not self.current_agent_id or not self.current_task_id:
             return
 
@@ -163,7 +189,7 @@ class EvaluationTraceCallback(BaseEventListener):
                 "args": tool_args,
                 "result": result,
                 "success": success,
-                "timestamp": datetime.now()
+                "timestamp": datetime.now(),
             }
 
             # Add error information if applicable
@@ -173,7 +199,11 @@ class EvaluationTraceCallback(BaseEventListener):
 
             self.traces[trace_key]["tool_uses"].append(tool_use)
 
-    def on_llm_call_start(self, messages: str | Sequence[dict[str, Any]] | None, tools: Sequence[dict[str, Any]] | None = None):
+    def on_llm_call_start(
+        self,
+        messages: str | Sequence[dict[str, Any]] | None,
+        tools: Sequence[dict[str, Any]] | None = None,
+    ):
         if not self.current_agent_id or not self.current_task_id:
             return
 
@@ -186,10 +216,12 @@ class EvaluationTraceCallback(BaseEventListener):
             "tools": tools,
             "start_time": datetime.now(),
             "response": None,
-            "end_time": None
+            "end_time": None,
         }
 
-    def on_llm_call_end(self, messages: str | list[dict[str, Any]] | None, response: Any):
+    def on_llm_call_end(
+        self, messages: str | list[dict[str, Any]] | None, response: Any
+    ):
         if not self.current_agent_id or not self.current_task_id:
             return
 
@@ -213,7 +245,7 @@ class EvaluationTraceCallback(BaseEventListener):
             "response": response,
             "start_time": start_time,
             "end_time": current_time,
-            "total_tokens": total_tokens
+            "total_tokens": total_tokens,
         }
 
         self.traces[trace_key]["llm_calls"].append(llm_call)
@@ -227,7 +259,7 @@ class EvaluationTraceCallback(BaseEventListener):
 
 
 def create_evaluation_callbacks() -> EvaluationTraceCallback:
-    from crewai.utilities.events.crewai_event_bus import crewai_event_bus
+    from crewai.events.event_bus import crewai_event_bus
 
     callback = EvaluationTraceCallback()
     callback.setup_listeners(crewai_event_bus)

src/crewai/flow/flow.py

@@ -25,8 +25,8 @@ from crewai.flow.flow_visualizer import plot_flow
 from crewai.flow.persistence.base import FlowPersistence
 from crewai.flow.types import FlowExecutionData
 from crewai.flow.utils import get_possible_return_constants
-from crewai.utilities.events.crewai_event_bus import crewai_event_bus
-from crewai.utilities.events.flow_events import (
+from crewai.events.event_bus import crewai_event_bus
+from crewai.events.types.flow_events import (
     FlowCreatedEvent,
     FlowFinishedEvent,
     FlowPlotEvent,
@@ -35,10 +35,10 @@ from crewai.utilities.events.flow_events import (
     MethodExecutionFinishedEvent,
     MethodExecutionStartedEvent,
 )
-from crewai.utilities.events.listeners.tracing.trace_listener import (
+from crewai.events.listeners.tracing.trace_listener import (
     TraceCollectionListener,
 )
-from crewai.utilities.events.listeners.tracing.utils import (
+from crewai.events.listeners.tracing.utils import (
     is_tracing_enabled,
 )
 from crewai.utilities.printer import Printer
@@ -474,6 +474,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
         self._method_outputs: List[Any] = []  # List to store all method outputs
         self._completed_methods: Set[str] = set()  # Track completed methods for reload
         self._persistence: Optional[FlowPersistence] = persistence
+        self._is_execution_resuming: bool = False
 
         # Initialize state with initial values
         self._state = self._create_initial_state()
@@ -829,6 +830,9 @@ class Flow(Generic[T], metaclass=FlowMeta):
                 # Clear completed methods and outputs for a fresh start
                 self._completed_methods.clear()
                 self._method_outputs.clear()
+            else:
+                # We're restoring from persistence, set the flag
+                self._is_execution_resuming = True
 
             if inputs:
                 # Override the id in the state if it exists in inputs
@@ -880,6 +884,9 @@ class Flow(Generic[T], metaclass=FlowMeta):
             ]
             await asyncio.gather(*tasks)
 
+            # Clear the resumption flag after initial execution completes
+            self._is_execution_resuming = False
+
             final_output = self._method_outputs[-1] if self._method_outputs else None
 
             crewai_event_bus.emit(
@@ -916,19 +923,23 @@ class Flow(Generic[T], metaclass=FlowMeta):
         - Automatically injects crewai_trigger_payload if available in flow inputs
         """
         if start_method_name in self._completed_methods:
-            last_output = self._method_outputs[-1] if self._method_outputs else None
-            await self._execute_listeners(start_method_name, last_output)
-            return
+            if self._is_execution_resuming:
+                # During resumption, skip execution but continue listeners
+                last_output = self._method_outputs[-1] if self._method_outputs else None
+                await self._execute_listeners(start_method_name, last_output)
+                return
+            # For cyclic flows, clear from completed to allow re-execution
+            self._completed_methods.discard(start_method_name)
 
         method = self._methods[start_method_name]
         enhanced_method = self._inject_trigger_payload_for_start_method(method)
 
-        result = await self._execute_method(
-            start_method_name, enhanced_method
-        )
+        result = await self._execute_method(start_method_name, enhanced_method)
         await self._execute_listeners(start_method_name, result)
 
-    def _inject_trigger_payload_for_start_method(self, original_method: Callable) -> Callable:
+    def _inject_trigger_payload_for_start_method(
+        self, original_method: Callable
+    ) -> Callable:
         def prepare_kwargs(*args, **kwargs):
             inputs = baggage.get_baggage("flow_inputs") or {}
             trigger_payload = inputs.get("crewai_trigger_payload")
@@ -941,15 +952,17 @@ class Flow(Generic[T], metaclass=FlowMeta):
             elif trigger_payload is not None:
                 self._log_flow_event(
                     f"Trigger payload available but {original_method.__name__} doesn't accept crewai_trigger_payload parameter",
-                    color="yellow"
+                    color="yellow",
                 )
             return args, kwargs
 
         if asyncio.iscoroutinefunction(original_method):
+
             async def enhanced_method(*args, **kwargs):
                 args, kwargs = prepare_kwargs(*args, **kwargs)
                 return await original_method(*args, **kwargs)
         else:
+
             def enhanced_method(*args, **kwargs):
                 args, kwargs = prepare_kwargs(*args, **kwargs)
                 return original_method(*args, **kwargs)
@@ -1050,11 +1063,15 @@ class Flow(Generic[T], metaclass=FlowMeta):
             for router_name in routers_triggered:
                 await self._execute_single_listener(router_name, result)
                 # After executing router, the router's result is the path
-                router_result = self._method_outputs[-1]
+                router_result = (
+                    self._method_outputs[-1] if self._method_outputs else None
+                )
                 if router_result:  # Only add non-None results
                     router_results.append(router_result)
                 current_trigger = (
-                    router_result  # Update for next iteration of router chain
+                    str(router_result)
+                    if router_result is not None
+                    else ""  # Update for next iteration of router chain
                 )
 
         # Now execute normal listeners for all router results and the original trigger
@@ -1072,6 +1089,24 @@ class Flow(Generic[T], metaclass=FlowMeta):
                     ]
                     await asyncio.gather(*tasks)
 
+                if current_trigger in router_results:
+                    # Find start methods triggered by this router result
+                    for method_name in self._start_methods:
+                        # Check if this start method is triggered by the current trigger
+                        if method_name in self._listeners:
+                            condition_type, trigger_methods = self._listeners[
+                                method_name
+                            ]
+                            if current_trigger in trigger_methods:
+                                # Only execute if this is a cycle (method was already completed)
+                                if method_name in self._completed_methods:
+                                    # For router-triggered start methods in cycles, temporarily clear resumption flag
+                                    # to allow cyclic execution
+                                    was_resuming = self._is_execution_resuming
+                                    self._is_execution_resuming = False
+                                    await self._execute_start_method(method_name)
+                                    self._is_execution_resuming = was_resuming
+
     def _find_triggered_methods(
         self, trigger_method: str, router_only: bool
     ) -> List[str]:
@@ -1109,6 +1144,9 @@ class Flow(Generic[T], metaclass=FlowMeta):
             if router_only != is_router:
                 continue
 
+            if not router_only and listener_name in self._start_methods:
+                continue
+
             if condition_type == "OR":
                 # If the trigger_method matches any in methods, run this
                 if trigger_method in methods:
@@ -1158,10 +1196,13 @@ class Flow(Generic[T], metaclass=FlowMeta):
         Catches and logs any exceptions during execution, preventing
         individual listener failures from breaking the entire flow.
         """
-        # TODO: greyson fix
-        # if listener_name in self._completed_methods:
-        #     await self._execute_listeners(listener_name, None)
-        #     return
+        if listener_name in self._completed_methods:
+            if self._is_execution_resuming:
+                # During resumption, skip execution but continue listeners
+                await self._execute_listeners(listener_name, None)
+                return
+            # For cyclic flows, clear from completed to allow re-execution
+            self._completed_methods.discard(listener_name)
 
         try:
             method = self._methods[listener_name]

src/crewai/knowledge/storage/knowledge_storage.py

@@ -1,6 +1,4 @@
-import contextlib
 import hashlib
-import io
 import logging
 import os
 import shutil
@@ -20,23 +18,7 @@ from crewai.utilities.constants import KNOWLEDGE_DIRECTORY
 from crewai.utilities.logger import Logger
 from crewai.utilities.paths import db_storage_path
 from crewai.utilities.chromadb import create_persistent_client
-
-
-@contextlib.contextmanager
-def suppress_logging(
-    logger_name="chromadb.segment.impl.vector.local_persistent_hnsw",
-    level=logging.ERROR,
-):
-    logger = logging.getLogger(logger_name)
-    original_level = logger.getEffectiveLevel()
-    logger.setLevel(level)
-    with (
-        contextlib.redirect_stdout(io.StringIO()),
-        contextlib.redirect_stderr(io.StringIO()),
-        contextlib.suppress(UserWarning),
-    ):
-        yield
-    logger.setLevel(original_level)
+from crewai.utilities.logger_utils import suppress_logging
 
 
 class KnowledgeStorage(BaseKnowledgeStorage):
@@ -64,7 +46,9 @@ class KnowledgeStorage(BaseKnowledgeStorage):
         filter: Optional[dict] = None,
         score_threshold: float = 0.35,
     ) -> List[Dict[str, Any]]:
-        with suppress_logging():
+        with suppress_logging(
+            "chromadb.segment.impl.vector.local_persistent_hnsw", logging.ERROR
+        ):
             if self.collection:
                 fetched = self.collection.query(
                     query_texts=query,

src/crewai/lite_agent.py

@@ -62,19 +62,14 @@ from crewai.utilities.agent_utils import (
     render_text_description_and_args,
 )
 from crewai.utilities.converter import generate_model_description
-from crewai.utilities.events.agent_events import (
-    AgentLogsExecutionEvent,
+from crewai.events.types.logging_events import AgentLogsExecutionEvent
+from crewai.events.types.agent_events import (
     LiteAgentExecutionCompletedEvent,
     LiteAgentExecutionErrorEvent,
     LiteAgentExecutionStartedEvent,
 )
-from crewai.utilities.events.crewai_event_bus import crewai_event_bus
-from crewai.utilities.events.llm_events import (
-    LLMCallCompletedEvent,
-    LLMCallFailedEvent,
-    LLMCallStartedEvent,
-    LLMCallType,
-)
+from crewai.events.event_bus import crewai_event_bus
+
 from crewai.utilities.llm_utils import create_llm
 from crewai.utilities.printer import Printer
 from crewai.utilities.token_counter_callback import TokenCalcHandler
@@ -519,19 +514,6 @@ class LiteAgent(FlowTrackable, BaseModel):
 
                 enforce_rpm_limit(self.request_within_rpm_limit)
 
-                llm = cast(LLM, self.llm)
-                model = llm.model if hasattr(llm, "model") else "unknown"
-                crewai_event_bus.emit(
-                    self,
-                    event=LLMCallStartedEvent(
-                        messages=self._messages,
-                        tools=None,
-                        callbacks=self._callbacks,
-                        from_agent=self,
-                        model=model,
-                    ),
-                )
-
                 try:
                     answer = get_llm_response(
                         llm=cast(LLM, self.llm),
@@ -541,23 +523,7 @@ class LiteAgent(FlowTrackable, BaseModel):
                         from_agent=self,
                     )
 
-                    # Emit LLM call completed event
-                    crewai_event_bus.emit(
-                        self,
-                        event=LLMCallCompletedEvent(
-                            messages=self._messages,
-                            response=answer,
-                            call_type=LLMCallType.LLM_CALL,
-                            from_agent=self,
-                            model=model,
-                        ),
-                    )
                 except Exception as e:
-                    # Emit LLM call failed event
-                    crewai_event_bus.emit(
-                        self,
-                        event=LLMCallFailedEvent(error=str(e), from_agent=self),
-                    )
                     raise e
 
                 formatted_answer = process_llm_response(answer, self.use_stop_words)

src/crewai/llm.py

@@ -23,14 +23,14 @@ from dotenv import load_dotenv
 from litellm.types.utils import ChatCompletionDeltaToolCall
 from pydantic import BaseModel, Field
 
-from crewai.utilities.events.llm_events import (
+from crewai.events.types.llm_events import (
     LLMCallCompletedEvent,
     LLMCallFailedEvent,
     LLMCallStartedEvent,
     LLMCallType,
     LLMStreamChunkEvent,
 )
-from crewai.utilities.events.tool_usage_events import (
+from crewai.events.types.tool_usage_events import (
     ToolUsageStartedEvent,
     ToolUsageFinishedEvent,
     ToolUsageErrorEvent,
@@ -52,7 +52,7 @@ import io
 from typing import TextIO
 
 from crewai.llms.base_llm import BaseLLM
-from crewai.utilities.events import crewai_event_bus
+from crewai.events.event_bus import crewai_event_bus
 from crewai.utilities.exceptions.context_window_exceeding_exception import (
     LLMContextLengthExceededException,
 )
@@ -311,7 +311,7 @@ class LLM(BaseLLM):
         api_base: Optional[str] = None,
         api_version: Optional[str] = None,
         api_key: Optional[str] = None,
-        callbacks: List[Any] = [],
+        callbacks: List[Any] | None = None,
         reasoning_effort: Optional[Literal["none", "low", "medium", "high"]] = None,
         stream: bool = False,
         **kwargs,
@@ -351,7 +351,7 @@ class LLM(BaseLLM):
         else:
             self.stop = stop
 
-        self.set_callbacks(callbacks)
+        self.set_callbacks(callbacks or [])
         self.set_env_callbacks()
 
     def _is_anthropic_model(self, model: str) -> bool:
@@ -851,7 +851,9 @@ class LLM(BaseLLM):
             return tool_calls
 
         # --- 7) Handle tool calls if present
-        tool_result = self._handle_tool_call(tool_calls, available_functions)
+        tool_result = self._handle_tool_call(
+            tool_calls, available_functions, from_task, from_agent
+        )
         if tool_result is not None:
             return tool_result
         # --- 8) If tool call handling didn't return a result, emit completion event and return text response
@@ -868,6 +870,8 @@ class LLM(BaseLLM):
         self,
         tool_calls: List[Any],
         available_functions: Optional[Dict[str, Any]] = None,
+        from_task: Optional[Any] = None,
+        from_agent: Optional[Any] = None,
     ) -> Optional[str]:
         """Handle a tool call from the LLM.
 
@@ -902,6 +906,8 @@ class LLM(BaseLLM):
                     event=ToolUsageStartedEvent(
                         tool_name=function_name,
                         tool_args=function_args,
+                        from_agent=from_agent,
+                        from_task=from_task,
                     ),
                 )
 
@@ -914,12 +920,17 @@ class LLM(BaseLLM):
                         tool_args=function_args,
                         started_at=started_at,
                         finished_at=datetime.now(),
+                        from_task=from_task,
+                        from_agent=from_agent,
                     ),
                 )
 
                 # --- 3.3) Emit success event
                 self._handle_emit_call_events(
-                    response=result, call_type=LLMCallType.TOOL_CALL
+                    response=result,
+                    call_type=LLMCallType.TOOL_CALL,
+                    from_task=from_task,
+                    from_agent=from_agent,
                 )
                 return result
             except Exception as e:
@@ -939,6 +950,8 @@ class LLM(BaseLLM):
                         tool_name=function_name,
                         tool_args=function_args,
                         error=f"Tool execution error: {str(e)}",
+                        from_task=from_task,
+                        from_agent=from_agent,
                     ),
                 )
         return None
@@ -1139,7 +1152,11 @@ class LLM(BaseLLM):
 
         # TODO: Remove this code after merging PR https://github.com/BerriAI/litellm/pull/10917
         # Ollama doesn't supports last message to be 'assistant'
-        if "ollama" in self.model.lower() and messages and messages[-1]["role"] == "assistant":
+        if (
+            "ollama" in self.model.lower()
+            and messages
+            and messages[-1]["role"] == "assistant"
+        ):
             return messages + [{"role": "user", "content": ""}]
 
         # Handle Anthropic models

src/crewai/memory/contextual/contextual_memory.py

@@ -1,4 +1,4 @@
-from typing import Optional
+from typing import Optional, TYPE_CHECKING
 
 from crewai.memory import (
     EntityMemory,
@@ -7,6 +7,10 @@ from crewai.memory import (
     ShortTermMemory,
 )
 
+if TYPE_CHECKING:
+    from crewai.agent import Agent
+    from crewai.task import Task
+
 
 class ContextualMemory:
     def __init__(
@@ -15,11 +19,28 @@ class ContextualMemory:
         ltm: LongTermMemory,
         em: EntityMemory,
         exm: ExternalMemory,
+        agent: Optional["Agent"] = None,
+        task: Optional["Task"] = None,
     ):
         self.stm = stm
         self.ltm = ltm
         self.em = em
         self.exm = exm
+        self.agent = agent
+        self.task = task
+
+        if self.stm is not None:
+            self.stm.agent = self.agent
+            self.stm.task = self.task
+        if self.ltm is not None:
+            self.ltm.agent = self.agent
+            self.ltm.task = self.task
+        if self.em is not None:
+            self.em.agent = self.agent
+            self.em.task = self.task
+        if self.exm is not None:
+            self.exm.agent = self.agent
+            self.exm.task = self.task
 
     def build_context_for_task(self, task, context) -> str:
         """
@@ -49,10 +70,7 @@ class ContextualMemory:
 
         stm_results = self.stm.search(query)
         formatted_results = "\n".join(
-            [
-                f"- {result['context']}"
-                for result in stm_results
-            ]
+            [f"- {result['context']}" for result in stm_results]
         )
         return f"Recent Insights:\n{formatted_results}" if stm_results else ""
 
@@ -89,10 +107,7 @@ class ContextualMemory:
 
         em_results = self.em.search(query)
         formatted_results = "\n".join(
-            [
-                f"- {result['context']}"
-                for result in em_results
-            ]  # type: ignore #  Invalid index type "str" for "str"; expected type "SupportsIndex | slice"
+            [f"- {result['context']}" for result in em_results]  # type: ignore #  Invalid index type "str" for "str"; expected type "SupportsIndex | slice"
         )
         return f"Entities:\n{formatted_results}" if em_results else ""
 

src/crewai/memory/entity/entity_memory.py

@@ -1,4 +1,4 @@
-from typing import Optional
+from typing import Any
 import time
 
 from pydantic import PrivateAttr
@@ -6,8 +6,8 @@ from pydantic import PrivateAttr
 from crewai.memory.entity.entity_memory_item import EntityMemoryItem
 from crewai.memory.memory import Memory
 from crewai.memory.storage.rag_storage import RAGStorage
-from crewai.utilities.events.crewai_event_bus import crewai_event_bus
-from crewai.utilities.events.memory_events import (
+from crewai.events.event_bus import crewai_event_bus
+from crewai.events.types.memory_events import (
     MemoryQueryStartedEvent,
     MemoryQueryCompletedEvent,
     MemoryQueryFailedEvent,
@@ -24,7 +24,7 @@ class EntityMemory(Memory):
     Inherits from the Memory class.
     """
 
-    _memory_provider: Optional[str] = PrivateAttr()
+    _memory_provider: str | None = PrivateAttr()
 
     def __init__(self, crew=None, embedder_config=None, storage=None, path=None):
         memory_provider = embedder_config.get("provider") if embedder_config else None
@@ -35,7 +35,7 @@ class EntityMemory(Memory):
                 raise ImportError(
                     "Mem0 is not installed. Please install it with `pip install mem0ai`."
                 )
-            config = embedder_config.get("config")
+            config = embedder_config.get("config") if embedder_config else None
             storage = Mem0Storage(type="short_term", crew=crew, config=config)
         else:
             storage = (
@@ -53,47 +53,99 @@ class EntityMemory(Memory):
         super().__init__(storage=storage)
         self._memory_provider = memory_provider
 
-    def save(self, item: EntityMemoryItem) -> None:  # type: ignore # BUG?: Signature of "save" incompatible with supertype "Memory"
-        """Saves an entity item into the SQLite storage."""
+    def save(
+        self,
+        value: EntityMemoryItem | list[EntityMemoryItem],
+        metadata: dict[str, Any] | None = None,
+    ) -> None:
+        """Saves one or more entity items into the SQLite storage.
+
+        Args:
+            value: Single EntityMemoryItem or list of EntityMemoryItems to save.
+            metadata: Optional metadata dict (included for supertype compatibility but not used).
+
+        Notes:
+            The metadata parameter is included to satisfy the supertype signature but is not
+            used - entity metadata is extracted from the EntityMemoryItem objects themselves.
+        """
+
+        if not value:
+            return
+
+        items = value if isinstance(value, list) else [value]
+        is_batch = len(items) > 1
+
+        metadata = {"entity_count": len(items)} if is_batch else items[0].metadata
         crewai_event_bus.emit(
             self,
             event=MemorySaveStartedEvent(
-                metadata=item.metadata,
+                metadata=metadata,
                 source_type="entity_memory",
+                from_agent=self.agent,
+                from_task=self.task,
             ),
         )
 
         start_time = time.time()
+        saved_count = 0
+        errors = []
+
         try:
-            if self._memory_provider == "mem0":
-                data = f"""
-                Remember details about the following entity:
-                Name: {item.name}
-                Type: {item.type}
-                Entity Description: {item.description}
-                """
+            for item in items:
+                try:
+                    if self._memory_provider == "mem0":
+                        data = f"""
+                        Remember details about the following entity:
+                        Name: {item.name}
+                        Type: {item.type}
+                        Entity Description: {item.description}
+                        """
+                    else:
+                        data = f"{item.name}({item.type}): {item.description}"
+
+                    super().save(data, item.metadata)
+                    saved_count += 1
+                except Exception as e:
+                    errors.append(f"{item.name}: {str(e)}")
+
+            if is_batch:
+                emit_value = f"Saved {saved_count} entities"
+                metadata = {"entity_count": saved_count, "errors": errors}
             else:
-                data = f"{item.name}({item.type}): {item.description}"
+                emit_value = f"{items[0].name}({items[0].type}): {items[0].description}"
+                metadata = items[0].metadata
 
-            super().save(data, item.metadata)
-
-            # Emit memory save completed event
             crewai_event_bus.emit(
                 self,
                 event=MemorySaveCompletedEvent(
-                    value=data,
-                    metadata=item.metadata,
+                    value=emit_value,
+                    metadata=metadata,
                     save_time_ms=(time.time() - start_time) * 1000,
                     source_type="entity_memory",
+                    from_agent=self.agent,
+                    from_task=self.task,
                 ),
             )
+
+            if errors:
+                raise Exception(
+                    f"Partial save: {len(errors)} failed out of {len(items)}"
+                )
+
         except Exception as e:
+            fail_metadata = (
+                {"entity_count": len(items), "saved": saved_count}
+                if is_batch
+                else items[0].metadata
+            )
             crewai_event_bus.emit(
                 self,
                 event=MemorySaveFailedEvent(
-                    metadata=item.metadata,
+                    metadata=fail_metadata,
                     error=str(e),
                     source_type="entity_memory",
+                    from_agent=self.agent,
+                    from_task=self.task,
                 ),
             )
             raise
@@ -111,6 +163,8 @@ class EntityMemory(Memory):
                 limit=limit,
                 score_threshold=score_threshold,
                 source_type="entity_memory",
+                from_agent=self.agent,
+                from_task=self.task,
             ),
         )
 
@@ -129,6 +183,8 @@ class EntityMemory(Memory):
                     score_threshold=score_threshold,
                     query_time_ms=(time.time() - start_time) * 1000,
                     source_type="entity_memory",
+                    from_agent=self.agent,
+                    from_task=self.task,
                 ),
             )
 

src/crewai/memory/external/external_memory.py

@@ -4,8 +4,8 @@ import time
 from crewai.memory.external.external_memory_item import ExternalMemoryItem
 from crewai.memory.memory import Memory
 from crewai.memory.storage.interface import Storage
-from crewai.utilities.events.crewai_event_bus import crewai_event_bus
-from crewai.utilities.events.memory_events import (
+from crewai.events.event_bus import crewai_event_bus
+from crewai.events.types.memory_events import (
     MemoryQueryStartedEvent,
     MemoryQueryCompletedEvent,
     MemoryQueryFailedEvent,
@@ -53,7 +53,6 @@ class ExternalMemory(Memory):
         self,
         value: Any,
         metadata: Optional[Dict[str, Any]] = None,
-        agent: Optional[str] = None,
     ) -> None:
         """Saves a value into the external storage."""
         crewai_event_bus.emit(
@@ -61,24 +60,30 @@ class ExternalMemory(Memory):
             event=MemorySaveStartedEvent(
                 value=value,
                 metadata=metadata,
-                agent_role=agent,
                 source_type="external_memory",
+                from_agent=self.agent,
+                from_task=self.task,
             ),
         )
 
         start_time = time.time()
         try:
-            item = ExternalMemoryItem(value=value, metadata=metadata, agent=agent)
-            super().save(value=item.value, metadata=item.metadata, agent=item.agent)
+            item = ExternalMemoryItem(
+                value=value,
+                metadata=metadata,
+                agent=self.agent.role if self.agent else None,
+            )
+            super().save(value=item.value, metadata=item.metadata)
 
             crewai_event_bus.emit(
                 self,
                 event=MemorySaveCompletedEvent(
                     value=value,
                     metadata=metadata,
-                    agent_role=agent,
                     save_time_ms=(time.time() - start_time) * 1000,
                     source_type="external_memory",
+                    from_agent=self.agent,
+                    from_task=self.task,
                 ),
             )
         except Exception as e:
@@ -87,9 +92,10 @@ class ExternalMemory(Memory):
                 event=MemorySaveFailedEvent(
                     value=value,
                     metadata=metadata,
-                    agent_role=agent,
                     error=str(e),
                     source_type="external_memory",
+                    from_agent=self.agent,
+                    from_task=self.task,
                 ),
             )
             raise
@@ -107,6 +113,8 @@ class ExternalMemory(Memory):
                 limit=limit,
                 score_threshold=score_threshold,
                 source_type="external_memory",
+                from_agent=self.agent,
+                from_task=self.task,
             ),
         )
 
@@ -125,6 +133,8 @@ class ExternalMemory(Memory):
                     score_threshold=score_threshold,
                     query_time_ms=(time.time() - start_time) * 1000,
                     source_type="external_memory",
+                    from_agent=self.agent,
+                    from_task=self.task,
                 ),
             )
 

src/crewai/memory/long_term/long_term_memory.py

@@ -3,8 +3,8 @@ import time
 
 from crewai.memory.long_term.long_term_memory_item import LongTermMemoryItem
 from crewai.memory.memory import Memory
-from crewai.utilities.events.crewai_event_bus import crewai_event_bus
-from crewai.utilities.events.memory_events import (
+from crewai.events.event_bus import crewai_event_bus
+from crewai.events.types.memory_events import (
     MemoryQueryStartedEvent,
     MemoryQueryCompletedEvent,
     MemoryQueryFailedEvent,
@@ -37,13 +37,17 @@ class LongTermMemory(Memory):
                 metadata=item.metadata,
                 agent_role=item.agent,
                 source_type="long_term_memory",
+                from_agent=self.agent,
+                from_task=self.task,
             ),
         )
 
         start_time = time.time()
         try:
             metadata = item.metadata
-            metadata.update({"agent": item.agent, "expected_output": item.expected_output})
+            metadata.update(
+                {"agent": item.agent, "expected_output": item.expected_output}
+            )
             self.storage.save(  # type: ignore # BUG?: Unexpected keyword argument "task_description","score","datetime" for "save" of "Storage"
                 task_description=item.task,
                 score=metadata["quality"],
@@ -59,6 +63,8 @@ class LongTermMemory(Memory):
                     agent_role=item.agent,
                     save_time_ms=(time.time() - start_time) * 1000,
                     source_type="long_term_memory",
+                    from_agent=self.agent,
+                    from_task=self.task,
                 ),
             )
         except Exception as e:
@@ -74,13 +80,19 @@ class LongTermMemory(Memory):
             )
             raise
 
-    def search(self, task: str, latest_n: int = 3) -> List[Dict[str, Any]]:  # type: ignore # signature of "search" incompatible with supertype "Memory"
+    def search(  # type: ignore # signature of "search" incompatible with supertype "Memory"
+        self,
+        task: str,
+        latest_n: int = 3,
+    ) -> List[Dict[str, Any]]:  # type: ignore # signature of "search" incompatible with supertype "Memory"
         crewai_event_bus.emit(
             self,
             event=MemoryQueryStartedEvent(
                 query=task,
                 limit=latest_n,
                 source_type="long_term_memory",
+                from_agent=self.agent,
+                from_task=self.task,
             ),
         )
 
@@ -96,6 +108,8 @@ class LongTermMemory(Memory):
                     limit=latest_n,
                     query_time_ms=(time.time() - start_time) * 1000,
                     source_type="long_term_memory",
+                    from_agent=self.agent,
+                    from_task=self.task,
                 ),
             )