fix: Fix code execution and multimodal tool handling in Agent class

Co-Authored-By: Joe Moura <joao@crewai.com>
fix: Fix multimodal and code execution tool handling
2026-01-08 15:48:29 +00:00 · 2025-02-14 21:25:17 +00:00 · 2025-02-14 21:20:46 +00:00 · 2025-02-14 21:16:57 +00:00 · 2025-02-14 21:13:46 +00:00 · 2025-02-14 21:13:06 +00:00
20 changed files with 759 additions and 715 deletions
--- a/docs/concepts/memory.mdx
+++ b/docs/concepts/memory.mdx
@@ -282,6 +282,19 @@ my_crew = Crew(

 ### Using Google AI embeddings

+#### Prerequisites
+Before using Google AI embeddings, ensure you have:
+- Access to the Gemini API
+- The necessary API keys and permissions
+
+You will need to update your *pyproject.toml* dependencies:
+```YAML
+dependencies = [
+    "google-generativeai>=0.8.4", #main version in January/2025 - crewai v.0.100.0 and crewai-tools 0.33.0
+    "crewai[tools]>=0.100.0,<1.0.0"
+]
+```
+
 ```python Code
 from crewai import Crew, Agent, Task, Process

@@ -434,6 +447,38 @@ my_crew = Crew(
 )
 ```

+### Using Amazon Bedrock embeddings
+
+```python Code
+# Note: Ensure you have installed `boto3` for Bedrock embeddings to work.
+
+import os
+import boto3
+from crewai import Crew, Agent, Task, Process
+
+boto3_session = boto3.Session(
+    region_name=os.environ.get("AWS_REGION_NAME"),
+    aws_access_key_id=os.environ.get("AWS_ACCESS_KEY_ID"),
+    aws_secret_access_key=os.environ.get("AWS_SECRET_ACCESS_KEY")
+)
+
+my_crew = Crew(
+    agents=[...],
+    tasks=[...],
+    process=Process.sequential,
+    memory=True,
+    embedder={
+    "provider": "bedrock",
+        "config":{
+            "session": boto3_session,
+            "model": "amazon.titan-embed-text-v2:0",
+            "vector_dimension": 1024
+        }
+    }
+    verbose=True
+)
+```
+
 ### Adding Custom Embedding Function

 ```python Code
--- a/docs/how-to/langfuse-observability.mdx
+++ b/docs/how-to/langfuse-observability.mdx
@@ -0,0 +1,98 @@
+---
+title: Agent Monitoring with Langfuse
+description: Learn how to integrate Langfuse with CrewAI via OpenTelemetry using OpenLit
+icon: magnifying-glass-chart
+---
+
+# Integrate Langfuse with CrewAI
+
+This notebook demonstrates how to integrate **Langfuse** with **CrewAI** using OpenTelemetry via the **OpenLit** SDK. By the end of this notebook, you will be able to trace your CrewAI applications with Langfuse for improved observability and debugging.
+
+> **What is Langfuse?** [Langfuse](https://langfuse.com) is an open-source LLM engineering platform. It provides tracing and monitoring capabilities for LLM applications, helping developers debug, analyze, and optimize their AI systems. Langfuse integrates with various tools and frameworks via native integrations, OpenTelemetry, and APIs/SDKs.
+
+## Get Started
+
+We'll walk through a simple example of using CrewAI and integrating it with Langfuse via OpenTelemetry using OpenLit.
+
+### Step 1: Install Dependencies
+
+
+```python
+%pip install langfuse openlit crewai crewai_tools
+```
+
+### Step 2: Set Up Environment Variables
+
+Set your Langfuse API keys and configure OpenTelemetry export settings to send traces to Langfuse. Please refer to the [Langfuse OpenTelemetry Docs](https://langfuse.com/docs/opentelemetry/get-started) for more information on the Langfuse OpenTelemetry endpoint `/api/public/otel` and authentication.
+
+
+```python
+import os
+import base64
+
+LANGFUSE_PUBLIC_KEY="pk-lf-..."
+LANGFUSE_SECRET_KEY="sk-lf-..."
+LANGFUSE_AUTH=base64.b64encode(f"{LANGFUSE_PUBLIC_KEY}:{LANGFUSE_SECRET_KEY}".encode()).decode()
+
+os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"] = "https://cloud.langfuse.com/api/public/otel" # EU data region
+# os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"] = "https://us.cloud.langfuse.com/api/public/otel" # US data region
+os.environ["OTEL_EXPORTER_OTLP_HEADERS"] = f"Authorization=Basic {LANGFUSE_AUTH}"
+
+# your openai key
+os.environ["OPENAI_API_KEY"] = "sk-..."
+```
+
+### Step 3: Initialize OpenLit
+
+Initialize the OpenLit OpenTelemetry instrumentation SDK to start capturing OpenTelemetry traces.
+
+
+```python
+import openlit
+
+openlit.init()
+```
+
+### Step 4: Create a Simple CrewAI Application
+
+We'll create a simple CrewAI application where multiple agents collaborate to answer a user's question.
+
+
+```python
+from crewai import Agent, Task, Crew
+
+from crewai_tools import (
+    WebsiteSearchTool
+)
+
+web_rag_tool = WebsiteSearchTool()
+
+writer = Agent(
+        role="Writer",
+        goal="You make math engaging and understandable for young children through poetry",
+        backstory="You're an expert in writing haikus but you know nothing of math.",
+        tools=[web_rag_tool],  
+    )
+
+task = Task(description=("What is {multiplication}?"),
+            expected_output=("Compose a haiku that includes the answer."),
+            agent=writer)
+
+crew = Crew(
+  agents=[writer],
+  tasks=[task],
+  share_crew=False
+)
+```
+
+### Step 5: See Traces in Langfuse
+
+After running the agent, you can view the traces generated by your CrewAI application in [Langfuse](https://cloud.langfuse.com). You should see detailed steps of the LLM interactions, which can help you debug and optimize your AI agent.
+
+![CrewAI example trace in Langfuse](https://langfuse.com/images/cookbook/integration_crewai/crewai-example-trace.png)
+
+_[Public example trace in Langfuse](https://cloud.langfuse.com/project/cloramnkj0002jz088vzn1ja4/traces/e2cf380ffc8d47d28da98f136140642b?timestamp=2025-02-05T15%3A12%3A02.717Z&observation=3b32338ee6a5d9af)_
+
+## References
+
+- [Langfuse OpenTelemetry Docs](https://langfuse.com/docs/opentelemetry/get-started)
--- a/docs/how-to/portkey-observability-and-guardrails.mdx
+++ b/docs/how-to/portkey-observability-and-guardrails.mdx
@@ -1,211 +0,0 @@
-# Portkey Integration with CrewAI
-<img src="https://raw.githubusercontent.com/siddharthsambharia-portkey/Portkey-Product-Images/main/Portkey-CrewAI.png" alt="Portkey CrewAI Header Image" width="70%" />
-
-
-[Portkey](https://portkey.ai/?utm_source=crewai&utm_medium=crewai&utm_campaign=crewai) is a 2-line upgrade to make your CrewAI agents reliable, cost-efficient, and fast.
-
-Portkey adds 4 core production capabilities to any CrewAI agent:
-1. Routing to **200+ LLMs**
-2. Making each LLM call more robust
-3. Full-stack tracing & cost, performance analytics
-4. Real-time guardrails to enforce behavior
-
-
-
-
-
-## Getting Started
-
-1. **Install Required Packages:**
-
-```bash
-pip install -qU crewai portkey-ai
-```
-
-2. **Configure the LLM Client:**
-
-To build CrewAI Agents with Portkey, you'll need two keys:
- **Portkey API Key**: Sign up on the [Portkey app](https://app.portkey.ai/?utm_source=crewai&utm_medium=crewai&utm_campaign=crewai) and copy your API key
- **Virtual Key**: Virtual Keys securely manage your LLM API keys in one place. Store your LLM provider API keys securely in Portkey's vault
-
-```python
-from crewai import LLM
-from portkey_ai import createHeaders, PORTKEY_GATEWAY_URL
-
-gpt_llm = LLM(
-    model="gpt-4",
-    base_url=PORTKEY_GATEWAY_URL,
-    api_key="dummy", # We are using Virtual key
-    extra_headers=createHeaders(
-        api_key="YOUR_PORTKEY_API_KEY",
-        virtual_key="YOUR_VIRTUAL_KEY", # Enter your Virtual key from Portkey
-    )
-)
-```
-
-3. **Create and Run Your First Agent:**
-
-```python
-from crewai import Agent, Task, Crew
-
-# Define your agents with roles and goals
-coder = Agent(
-    role='Software developer',
-    goal='Write clear, concise code on demand',
-    backstory='An expert coder with a keen eye for software trends.',
-    llm=gpt_llm
-)
-
-# Create tasks for your agents
-task1 = Task(
-    description="Define the HTML for making a simple website with heading- Hello World! Portkey is working!",
-    expected_output="A clear and concise HTML code",
-    agent=coder
-)
-
-# Instantiate your crew
-crew = Crew(
-    agents=[coder],
-    tasks=[task1],
-)
-
-result = crew.kickoff()
-print(result)
-```
-
-
-## Key Features
-
-| Feature | Description |
-|---------|-------------|
-| 🌐 Multi-LLM Support | Access OpenAI, Anthropic, Gemini, Azure, and 250+ providers through a unified interface |
-| 🛡️ Production Reliability | Implement retries, timeouts, load balancing, and fallbacks |
-| 📊 Advanced Observability | Track 40+ metrics including costs, tokens, latency, and custom metadata |
-| 🔍 Comprehensive Logging | Debug with detailed execution traces and function call logs |
-| 🚧 Security Controls | Set budget limits and implement role-based access control |
-| 🔄 Performance Analytics | Capture and analyze feedback for continuous improvement |
-| 💾 Intelligent Caching | Reduce costs and latency with semantic or simple caching |
-
-
-## Production Features with Portkey Configs
-
-All features mentioned below are through Portkey's Config system. Portkey's Config system allows you to define routing strategies using simple JSON objects in your LLM API calls. You can create and manage Configs directly in your code or through the Portkey Dashboard. Each Config has a unique ID for easy reference.
-
-<Frame>
-    <img src="https://raw.githubusercontent.com/Portkey-AI/docs-core/refs/heads/main/images/libraries/libraries-3.avif"/>
-</Frame>
-
-
-### 1. Use 250+ LLMs
-Access various LLMs like Anthropic, Gemini, Mistral, Azure OpenAI, and more with minimal code changes. Switch between providers or use them together seamlessly. [Learn more about Universal API](https://portkey.ai/docs/product/ai-gateway/universal-api)
-
-
-Easily switch between different LLM providers:
-
-```python
-# Anthropic Configuration
-anthropic_llm = LLM(
-    model="claude-3-5-sonnet-latest",
-    base_url=PORTKEY_GATEWAY_URL,
-    api_key="dummy",
-    extra_headers=createHeaders(
-        api_key="YOUR_PORTKEY_API_KEY",
-        virtual_key="YOUR_ANTHROPIC_VIRTUAL_KEY", #You don't need provider when using Virtual keys
-        trace_id="anthropic_agent"
-    )
-)
-
-# Azure OpenAI Configuration
-azure_llm = LLM(
-    model="gpt-4",
-    base_url=PORTKEY_GATEWAY_URL,
-    api_key="dummy",
-    extra_headers=createHeaders(
-        api_key="YOUR_PORTKEY_API_KEY",
-        virtual_key="YOUR_AZURE_VIRTUAL_KEY", #You don't need provider when using Virtual keys
-        trace_id="azure_agent"
-    )
-)
-```
-
-
-### 2. Caching
-Improve response times and reduce costs with two powerful caching modes:
- **Simple Cache**: Perfect for exact matches
- **Semantic Cache**: Matches responses for requests that are semantically similar
-[Learn more about Caching](https://portkey.ai/docs/product/ai-gateway/cache-simple-and-semantic)
-
-```py
-config = {
-    "cache": {
-        "mode": "semantic",  # or "simple" for exact matching
-    }
-}
-```
-
-### 3. Production Reliability
-Portkey provides comprehensive reliability features:
- **Automatic Retries**: Handle temporary failures gracefully
- **Request Timeouts**: Prevent hanging operations
- **Conditional Routing**: Route requests based on specific conditions
- **Fallbacks**: Set up automatic provider failovers
- **Load Balancing**: Distribute requests efficiently
-
-[Learn more about Reliability Features](https://portkey.ai/docs/product/ai-gateway/)
-
-
-
-### 4. Metrics
-
-Agent runs are complex. Portkey automatically logs **40+ comprehensive metrics** for your AI agents, including cost, tokens used, latency, etc. Whether you need a broad overview or granular insights into your agent runs, Portkey's customizable filters provide the metrics you need.
-
-
- Cost per agent interaction
- Response times and latency
- Token usage and efficiency
- Success/failure rates
- Cache hit rates
-
-<img src="https://github.com/siddharthsambharia-portkey/Portkey-Product-Images/blob/main/Portkey-Dashboard.png?raw=true" width="70%" alt="Portkey Dashboard" />
-
-### 5. Detailed Logging
-Logs are essential for understanding agent behavior, diagnosing issues, and improving performance. They provide a detailed record of agent activities and tool use, which is crucial for debugging and optimizing processes.
-
-
-Access a dedicated section to view records of agent executions, including parameters, outcomes, function calls, and errors. Filter logs based on multiple parameters such as trace ID, model, tokens used, and metadata.
-
-<details>
-  <summary><b>Traces</b></summary>
-  <img src="https://raw.githubusercontent.com/siddharthsambharia-portkey/Portkey-Product-Images/main/Portkey-Traces.png" alt="Portkey Traces" width="70%" />
-</details>
-
-<details>
-  <summary><b>Logs</b></summary>
-  <img src="https://raw.githubusercontent.com/siddharthsambharia-portkey/Portkey-Product-Images/main/Portkey-Logs.png" alt="Portkey Logs" width="70%" />
-</details>
-
-### 6. Enterprise Security Features
- Set budget limit and rate limts per Virtual Key (disposable API keys)
- Implement role-based access control
- Track system changes with audit logs
- Configure data retention policies
-
-
-
-For detailed information on creating and managing Configs, visit the [Portkey documentation](https://docs.portkey.ai/product/ai-gateway/configs).
-
-## Resources
-
- [📘 Portkey Documentation](https://docs.portkey.ai)
- [📊 Portkey Dashboard](https://app.portkey.ai/?utm_source=crewai&utm_medium=crewai&utm_campaign=crewai)
- [🐦 Twitter](https://twitter.com/portkeyai)
- [💬 Discord Community](https://discord.gg/DD7vgKK299)
-
-
-
-
-
-
-
-
-
--- a/docs/how-to/portkey-observability.mdx
+++ b/docs/how-to/portkey-observability.mdx
@@ -1,5 +1,5 @@
 ---
-title: Portkey Observability and Guardrails
+title: Agent Monitoring with Portkey
 description: How to use Portkey with CrewAI
 icon: key
 ---
--- a/docs/mint.json
+++ b/docs/mint.json
@@ -103,7 +103,8 @@
        "how-to/langtrace-observability",
        "how-to/mlflow-observability",
        "how-to/openlit-observability",
-        "how-to/portkey-observability"
+        "how-to/portkey-observability",
+        "how-to/langfuse-observability"
      ]
    },
    {
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "crewai"
-version = "0.100.1"
+version = "0.102.0"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
 requires-python = ">=3.10,<3.13"
@@ -45,7 +45,7 @@ Documentation = "https://docs.crewai.com"
 Repository = "https://github.com/crewAIInc/crewAI"

 [project.optional-dependencies]
-tools = ["crewai-tools>=0.32.1"]
+tools = ["crewai-tools>=0.36.0"]
 embeddings = [
    "tiktoken~=0.7.0"
 ]
--- a/src/crewai/init.py
+++ b/src/crewai/init.py
@@ -14,7 +14,7 @@ warnings.filterwarnings(
    category=UserWarning,
    module="pydantic.main",
 )
-__version__ = "0.100.1"
+__version__ = "0.102.0"
 __all__ = [
    "Agent",
    "Crew",
--- a/src/crewai/agent.py
+++ b/src/crewai/agent.py
@@ -135,6 +135,19 @@ class Agent(BaseAgent):
        if self.allow_code_execution:
            self._validate_docker_installation()

+        # If this is a manager agent, ensure it only has delegation tools
+        if self.role == "Manager" and self.allow_delegation and self.crew:
+            try:
+                self.tools = self.get_delegation_tools(self.crew.agents)
+                self._logger.log(
+                    "info",
+                    f"Manager agent has delegation tools: {[tool.name for tool in self.tools]}",
+                    color="blue",
+                )
+            except Exception as e:
+                self._logger.log("error", f"Failed to set delegation tools: {str(e)}", color="red")
+                raise ValueError(f"Failed to set delegation tools: {str(e)}")
+
        return self

    def _setup_agent_executor(self):
@@ -325,21 +338,33 @@ class Agent(BaseAgent):
        return tools

    def get_multimodal_tools(self) -> Sequence[BaseTool]:
-        from crewai.tools.agent_tools.add_image_tool import AddImageTool
+        """Get multimodal tools for the agent.
+        
+        Returns:
+            List[BaseTool]: List containing the AddImageTool if agent is multimodal
+        """
+        if self.multimodal:
+            from crewai.tools.agent_tools.add_image_tool import AddImageTool
+            return [AddImageTool()]
+        return []

-        return [AddImageTool()]
-
-    def get_code_execution_tools(self):
-        try:
-            from crewai_tools import CodeInterpreterTool  # type: ignore
-
-            # Set the unsafe_mode based on the code_execution_mode attribute
-            unsafe_mode = self.code_execution_mode == "unsafe"
-            return [CodeInterpreterTool(unsafe_mode=unsafe_mode)]
-        except ModuleNotFoundError:
-            self._logger.log(
-                "info", "Coding tools not available. Install crewai_tools. "
-            )
+    def get_code_execution_tools(self) -> Sequence[BaseTool]:
+        """Get code execution tools for the agent.
+        
+        Returns:
+            List[BaseTool]: List containing the CodeInterpreterTool if code execution is allowed
+        """
+        if self.allow_code_execution:
+            try:
+                from crewai_tools import CodeInterpreterTool  # type: ignore
+                # Set the unsafe_mode based on the code_execution_mode attribute
+                unsafe_mode = self.code_execution_mode == "unsafe"
+                return [CodeInterpreterTool(unsafe_mode=unsafe_mode)]
+            except ModuleNotFoundError:
+                self._logger.log(
+                    "warning", "Coding tools not available. Install crewai_tools.", color="yellow"
+                )
+        return []

    def get_output_converter(self, llm, text, model, instructions):
        return Converter(llm=llm, text=text, model=model, instructions=instructions)
--- a/src/crewai/cli/templates/crew/main.py
+++ b/src/crewai/cli/templates/crew/main.py
@@ -56,7 +56,8 @@ def test():
    Test the crew execution and returns the results.
    """
    inputs = {
-        "topic": "AI LLMs"
+        "topic": "AI LLMs",
+        "current_year": str(datetime.now().year)
    }
    try:
        {{crew_name}}().crew().test(n_iterations=int(sys.argv[1]), openai_model_name=sys.argv[2], inputs=inputs)
--- a/src/crewai/cli/templates/crew/pyproject.toml
+++ b/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,<3.13"
 dependencies = [
-    "crewai[tools]>=0.100.1,<1.0.0"
+    "crewai[tools]>=0.102.0,<1.0.0"
 ]

 [project.scripts]
--- a/src/crewai/cli/templates/flow/pyproject.toml
+++ b/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,<3.13"
 dependencies = [
-    "crewai[tools]>=0.100.1,<1.0.0",
+    "crewai[tools]>=0.102.0,<1.0.0",
 ]

 [project.scripts]
--- a/src/crewai/cli/templates/tool/pyproject.toml
+++ b/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,<3.13"
 dependencies = [
-    "crewai[tools]>=0.100.1"
+    "crewai[tools]>=0.102.0"
 ]

 [tool.crewai]
--- a/src/crewai/crew.py
+++ b/src/crewai/crew.py
@@ -36,7 +36,11 @@ from crewai.task import Task
 from crewai.tasks.conditional_task import ConditionalTask
 from crewai.tasks.task_output import TaskOutput
 from crewai.telemetry import Telemetry
-from crewai.tools.agent_tools.agent_tools import AgentTools
+from crewai.tools.agent_tools.agent_tools import (
+    ASK_QUESTION_TOOL,
+    DELEGATE_WORK_TOOL,
+    AgentTools,
+)
 from crewai.tools.base_tool import Tool
 from crewai.types.usage_metrics import UsageMetrics
 from crewai.utilities import I18N, FileHandler, Logger, RPMController
@@ -314,14 +318,16 @@ class Crew(BaseModel):
                    {},
                )

-            if (self.manager_agent is not None) and (
-                self.agents.count(self.manager_agent) > 0
-            ):
-                raise PydanticCustomError(
-                    "manager_agent_in_agents",
-                    "Manager agent should not be included in agents list.",
-                    {},
-                )
+            if self.manager_agent is not None:
+                if self.agents.count(self.manager_agent) > 0:
+                    raise PydanticCustomError(
+                        "manager_agent_in_agents",
+                        "Manager agent should not be included in agents list.",
+                        {},
+                    )
+                # Set manager agent's crew and tools
+                self.manager_agent.crew = self
+                self.manager_agent.tools = AgentTools(agents=self.agents).tools()

        return self

@@ -688,29 +694,40 @@ class Crew(BaseModel):
        return self._execute_tasks(self.tasks)

    def _create_manager_agent(self):
+        """Creates and configures the manager agent for hierarchical process."""
        i18n = I18N(prompt_file=self.prompt_file)
        if self.manager_agent is not None:
-            self.manager_agent.allow_delegation = True
            manager = self.manager_agent
-            if manager.tools is not None and len(manager.tools) > 0:
-                self._logger.log(
-                    "warning", "Manager agent should not have tools", color="orange"
-                )
-                manager.tools = []
-                raise Exception("Manager agent should not have tools")
        else:
            self.manager_llm = create_llm(self.manager_llm)
            manager = Agent(
                role=i18n.retrieve("hierarchical_manager_agent", "role"),
                goal=i18n.retrieve("hierarchical_manager_agent", "goal"),
                backstory=i18n.retrieve("hierarchical_manager_agent", "backstory"),
-                tools=AgentTools(agents=self.agents).tools(),
+                tools=[],  # Initialize with no tools
                allow_delegation=True,
                llm=self.manager_llm,
                verbose=self.verbose,
            )
            self.manager_agent = manager
+
+        # Configure manager agent
+        manager.allow_delegation = True
        manager.crew = self
+        try:
+            delegation_tools = AgentTools(agents=self.agents).tools()
+            manager.tools = delegation_tools
+            self._logger.log(
+                "info",
+                f"Manager agent has delegation tools: {[tool.name for tool in manager.tools]}",
+                color="blue",
+            )
+        except Exception as e:
+            self._logger.log("error", f"Failed to set manager tools: {str(e)}", color="red")
+            raise ValueError(f"Failed to set manager tools: {str(e)}")
+
+        return manager
+

    def _execute_tasks(
        self,
@@ -722,7 +739,8 @@ class Crew(BaseModel):

        Args:
            tasks (List[Task]): List of tasks to execute
-            manager (Optional[BaseAgent], optional): Manager agent to use for delegation. Defaults to None.
+            start_index (Optional[int]): Index to start execution from
+            was_replayed (bool): Whether this is a replay execution

        Returns:
            CrewOutput: Final output of the crew
@@ -748,9 +766,59 @@ class Crew(BaseModel):
                    f"No agent available for task: {task.description}. Ensure that either the task has an assigned agent or a manager agent is provided."
                )

-            # Determine which tools to use - task tools take precedence over agent tools
-            tools_for_task = task.tools or agent_to_use.tools or []
-            tools_for_task = self._prepare_tools(agent_to_use, task, tools_for_task)
+            # In hierarchical process, if task has no agent, assign it to the first available agent
+            if self.process == Process.hierarchical and not task.agent and len(self.agents) > 0:
+                task.agent = self.agents[0]
+                self._logger.log(
+                    "debug",
+                    f"Assigning task {task_index} to agent {task.agent.role}",
+                    color="blue",
+                )
+
+            # Track delegation in hierarchical process
+            if (
+                self.process == Process.hierarchical 
+                and task.agent 
+                and task.agent != self.manager_agent 
+                and self.manager_agent
+            ):
+                task.increment_delegations(self.manager_agent.role)
+                task.processed_by_agents.add(self.manager_agent.role)
+                self._logger.log(
+                    "debug",
+                    f"Tracking delegation for task {task_index} from {task.agent.role} to {self.manager_agent.role}",
+                    color="blue",
+                )
+
+            # Determine which tools to use
+            tools_for_task = []
+
+            # Get delegation tools if agent allows delegation or is in sequential process
+            delegation_tools = []
+            if agent_to_use.allow_delegation or (self.process == Process.sequential and len(self.agents) > 1):
+                if self.process == Process.hierarchical:
+                    delegation_tools = self._update_manager_tools(task, [])
+                else:
+                    delegation_tools = self._add_delegation_tools(task, [])
+                if delegation_tools:
+                    tools_for_task.extend(delegation_tools)
+                    self._logger.log(
+                        "debug",
+                        f"Added delegation tools for agent {agent_to_use.role}: {[tool.name for tool in delegation_tools]}",
+                        color="blue",
+                    )
+
+            # Add task tools if present, otherwise use agent tools
+            if task.tools:
+                tools_for_task.extend([
+                    tool for tool in task.tools
+                    if not any(dtool.name == tool.name for dtool in tools_for_task)
+                ])
+            elif agent_to_use.tools:
+                tools_for_task.extend([
+                    tool for tool in agent_to_use.tools
+                    if not any(dtool.name == tool.name for dtool in tools_for_task)
+                ])

            self._log_task_start(task, agent_to_use.role)

@@ -821,74 +889,205 @@ class Crew(BaseModel):
    def _prepare_tools(
        self, agent: BaseAgent, task: Task, tools: List[Tool]
    ) -> List[Tool]:
-        # Add delegation tools if agent allows delegation
+        """Prepare tools for an agent to use in a task.
+        
+        Args:
+            agent: The agent that will use the tools
+            task: The task being executed
+            tools: The initial set of tools
+            
+        Returns:
+            List[Tool]: The final set of tools for the agent to use
+        """
+        # For manager agent, only use delegation tools
+        if agent == self.manager_agent:
+            return self._update_manager_tools(task, [])
+
+        # Get delegation tools first if agent allows delegation
+        delegation_tools = []
        if agent.allow_delegation:
            if self.process == Process.hierarchical:
                if self.manager_agent:
-                    tools = self._update_manager_tools(task, tools)
+                    delegation_tools = self._update_manager_tools(task, [])
                else:
                    raise ValueError(
                        "Manager agent is required for hierarchical process."
                    )
+            else:
+                delegation_tools = self._add_delegation_tools(task, [])

-            elif agent and agent.allow_delegation:
-                tools = self._add_delegation_tools(task, tools)
+        # Start with task tools if present, otherwise use agent tools
+        final_tools = []
+        if task.tools:
+            final_tools.extend(task.tools)
+        elif agent.tools:
+            final_tools.extend(agent.tools)

        # Add code execution tools if agent allows code execution
        if agent.allow_code_execution:
-            tools = self._add_code_execution_tools(agent, tools)
+            code_tools = agent.get_code_execution_tools()
+            if code_tools:
+                final_tools.extend(code_tools)
+                self._logger.log(
+                    "debug",
+                    f"Added code execution tools for agent {agent.role}: {[tool.name for tool in code_tools]}",
+                    color="blue",
+                )

+        # Add multimodal tools if agent supports them
        if agent and agent.multimodal:
-            tools = self._add_multimodal_tools(agent, tools)
+            multimodal_tools = agent.get_multimodal_tools()
+            if multimodal_tools:
+                final_tools.extend(multimodal_tools)
+                self._logger.log(
+                    "debug",
+                    f"Added multimodal tools for agent {agent.role}: {[tool.name for tool in multimodal_tools]}",
+                    color="blue",
+                )

-        return tools
+        # Always add delegation tools if agent allows delegation
+        if delegation_tools:
+            # Add delegation tools to the beginning
+            final_tools = delegation_tools + [
+                tool for tool in final_tools 
+                if not any(dtool.name == tool.name for dtool in delegation_tools)
+            ]
+
+        return final_tools

    def _get_agent_to_use(self, task: Task) -> Optional[BaseAgent]:
+        """Get the agent that should execute the task.
+        
+        In hierarchical process, all tasks are delegated through the manager agent.
+        In sequential process, tasks are executed by their assigned agent.
+        """
        if self.process == Process.hierarchical:
            return self.manager_agent
-        return task.agent
+        
+        # In sequential process, if agent allows delegation and there are other agents,
+        # we track delegation to the first available agent
+        agent_to_use = task.agent
+        if agent_to_use and agent_to_use.allow_delegation and len(self.agents) > 1:
+            for other_agent in self.agents:
+                if other_agent != agent_to_use:
+                    task.increment_delegations(other_agent.role)
+                    agent_to_use = other_agent
+                    break
+        
+        return agent_to_use

    def _merge_tools(
        self, existing_tools: List[Tool], new_tools: List[Tool]
    ) -> List[Tool]:
-        """Merge new tools into existing tools list, avoiding duplicates by tool name."""
+        """Merge new tools into existing tools list, preserving delegation tools."""
        if not new_tools:
            return existing_tools

+        # Keep track of delegation tools
+        delegation_tools = [
+            tool for tool in existing_tools 
+            if tool.name in {DELEGATE_WORK_TOOL, ASK_QUESTION_TOOL}
+        ]
+
        # Create mapping of tool names to new tools
        new_tool_map = {tool.name: tool for tool in new_tools}

        # Remove any existing tools that will be replaced
-        tools = [tool for tool in existing_tools if tool.name not in new_tool_map]
+        tools = [
+            tool for tool in existing_tools 
+            if tool.name not in new_tool_map and tool not in delegation_tools
+        ]

        # Add all new tools
        tools.extend(new_tools)

+        # Add back delegation tools
+        tools.extend(delegation_tools)
+
        return tools

    def _inject_delegation_tools(
        self, tools: List[Tool], task_agent: BaseAgent, agents: List[BaseAgent]
    ):
        delegation_tools = task_agent.get_delegation_tools(agents)
+        if task_agent == self.manager_agent:
+            return delegation_tools
        return self._merge_tools(tools, delegation_tools)

-    def _add_multimodal_tools(self, agent: BaseAgent, tools: List[Tool]):
+    def _add_multimodal_tools(self, agent: BaseAgent, tools: List[Tool]) -> List[Tool]:
+        """Add multimodal tools for an agent.
+        
+        Args:
+            agent: The agent that will use the tools
+            tools: The current set of tools
+            
+        Returns:
+            List[Tool]: The tools with multimodal tools added
+        """
        multimodal_tools = agent.get_multimodal_tools()
-        return self._merge_tools(tools, multimodal_tools)
-
-    def _add_code_execution_tools(self, agent: BaseAgent, tools: List[Tool]):
-        code_tools = agent.get_code_execution_tools()
-        return self._merge_tools(tools, code_tools)
-
-    def _add_delegation_tools(self, task: Task, tools: List[Tool]):
-        agents_for_delegation = [agent for agent in self.agents if agent != task.agent]
-        if len(self.agents) > 1 and len(agents_for_delegation) > 0 and task.agent:
-            if not tools:
-                tools = []
-            tools = self._inject_delegation_tools(
-                tools, task.agent, agents_for_delegation
+        if multimodal_tools:
+            self._logger.log(
+                "debug",
+                f"Adding multimodal tools for agent {agent.role}: {[tool.name for tool in multimodal_tools]}",
+                color="blue",
            )
-        return tools
+            return multimodal_tools
+        return []
+
+    def _add_code_execution_tools(self, agent: BaseAgent, tools: List[Tool]) -> List[Tool]:
+        """Add code execution tools for an agent.
+        
+        Args:
+            agent: The agent that will use the tools
+            tools: The current set of tools
+            
+        Returns:
+            List[Tool]: The tools with code execution tools added
+        """
+        code_tools = agent.get_code_execution_tools()
+        if code_tools:
+            self._logger.log(
+                "debug",
+                f"Adding code execution tools for agent {agent.role}: {[tool.name for tool in code_tools]}",
+                color="blue",
+            )
+            return code_tools
+        return []
+
+    def _add_delegation_tools(self, task: Task, tools: List[Tool]) -> List[Tool]:
+        """Add delegation tools for the task's agent.
+        
+        Args:
+            task: The task being executed
+            tools: The current set of tools
+            
+        Returns:
+            List[Tool]: The tools with delegation tools added
+        """
+        if task.agent and task.agent.allow_delegation:
+            agents_for_delegation = [agent for agent in self.agents if agent != task.agent]
+            if len(agents_for_delegation) > 0:
+                delegation_tools = self._inject_delegation_tools([], task.agent, agents_for_delegation)
+                if delegation_tools:
+                    self._logger.log(
+                        "debug",
+                        f"Adding delegation tools for agent {task.agent.role}: {[tool.name for tool in delegation_tools]}",
+                        color="blue",
+                    )
+                    return delegation_tools
+        elif task.agent and task.agent.crew and task.agent.crew.process == Process.sequential:
+            # In sequential process, if agent has crew but no delegation tools, add them
+            agents_for_delegation = [agent for agent in task.agent.crew.agents if agent != task.agent]
+            if len(agents_for_delegation) > 0:
+                delegation_tools = self._inject_delegation_tools([], task.agent, agents_for_delegation)
+                if delegation_tools:
+                    self._logger.log(
+                        "debug",
+                        f"Adding delegation tools for agent {task.agent.role} in sequential process: {[tool.name for tool in delegation_tools]}",
+                        color="blue",
+                    )
+                    return delegation_tools
+        return []

    def _log_task_start(self, task: Task, role: str = "None"):
        if self.output_log_file:
@@ -899,10 +1098,10 @@ class Crew(BaseModel):
    def _update_manager_tools(self, task: Task, tools: List[Tool]):
        if self.manager_agent:
            if task.agent:
-                tools = self._inject_delegation_tools(tools, task.agent, [task.agent])
+                tools = self._inject_delegation_tools([], task.agent, [task.agent])
            else:
                tools = self._inject_delegation_tools(
-                    tools, self.manager_agent, self.agents
+                    [], self.manager_agent, self.agents
                )
        return tools

--- a/src/crewai/flow/flow.py
+++ b/src/crewai/flow/flow.py
@@ -1,4 +1,5 @@
 import asyncio
+import copy
 import inspect
 import logging
 from typing import (
@@ -394,7 +395,6 @@ class FlowMeta(type):
                or hasattr(attr_value, "__trigger_methods__")
                or hasattr(attr_value, "__is_router__")
            ):
-
                # Register start methods
                if hasattr(attr_value, "__is_start_method__"):
                    start_methods.append(attr_name)
@@ -569,6 +569,9 @@ class Flow(Generic[T], metaclass=FlowMeta):
            f"Initial state must be dict or BaseModel, got {type(self.initial_state)}"
        )

+    def _copy_state(self) -> T:
+        return copy.deepcopy(self._state)
+
    @property
    def state(self) -> T:
        return self._state
@@ -740,6 +743,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
            event=FlowStartedEvent(
                type="flow_started",
                flow_name=self.__class__.__name__,
+                inputs=inputs,
            ),
        )
        self._log_flow_event(
@@ -803,6 +807,18 @@ class Flow(Generic[T], metaclass=FlowMeta):
    async def _execute_method(
        self, method_name: str, method: Callable, *args: Any, **kwargs: Any
    ) -> Any:
+        dumped_params = {f"_{i}": arg for i, arg in enumerate(args)} | (kwargs or {})
+        self.event_emitter.send(
+            self,
+            event=MethodExecutionStartedEvent(
+                type="method_execution_started",
+                method_name=method_name,
+                flow_name=self.__class__.__name__,
+                params=dumped_params,
+                state=self._copy_state(),
+            ),
+        )
+
        result = (
            await method(*args, **kwargs)
            if asyncio.iscoroutinefunction(method)
@@ -812,6 +828,18 @@ class Flow(Generic[T], metaclass=FlowMeta):
        self._method_execution_counts[method_name] = (
            self._method_execution_counts.get(method_name, 0) + 1
        )
+
+        self.event_emitter.send(
+            self,
+            event=MethodExecutionFinishedEvent(
+                type="method_execution_finished",
+                method_name=method_name,
+                flow_name=self.__class__.__name__,
+                state=self._copy_state(),
+                result=result,
+            ),
+        )
+
        return result

    async def _execute_listeners(self, trigger_method: str, result: Any) -> None:
@@ -950,16 +978,6 @@ class Flow(Generic[T], metaclass=FlowMeta):
        """
        try:
            method = self._methods[listener_name]
-
-            self.event_emitter.send(
-                self,
-                event=MethodExecutionStartedEvent(
-                    type="method_execution_started",
-                    method_name=listener_name,
-                    flow_name=self.__class__.__name__,
-                ),
-            )
-
            sig = inspect.signature(method)
            params = list(sig.parameters.values())
            method_params = [p for p in params if p.name != "self"]
@@ -971,15 +989,6 @@ class Flow(Generic[T], metaclass=FlowMeta):
            else:
                listener_result = await self._execute_method(listener_name, method)

-            self.event_emitter.send(
-                self,
-                event=MethodExecutionFinishedEvent(
-                    type="method_execution_finished",
-                    method_name=listener_name,
-                    flow_name=self.__class__.__name__,
-                ),
-            )
-
            # Execute listeners (and possibly routers) of this listener
            await self._execute_listeners(listener_name, listener_result)

--- a/src/crewai/flow/flow_events.py
+++ b/src/crewai/flow/flow_events.py
@@ -1,6 +1,8 @@
 from dataclasses import dataclass, field
 from datetime import datetime
-from typing import Any, Optional
+from typing import Any, Dict, Optional, Union
+
+from pydantic import BaseModel


@dataclass
@@ -15,17 +17,21 @@ class Event:

@dataclass
 class FlowStartedEvent(Event):
-    pass
+    inputs: Optional[Dict[str, Any]] = None


@dataclass
 class MethodExecutionStartedEvent(Event):
    method_name: str
+    state: Union[Dict[str, Any], BaseModel]
+    params: Optional[Dict[str, Any]] = None


@dataclass
 class MethodExecutionFinishedEvent(Event):
    method_name: str
+    state: Union[Dict[str, Any], BaseModel]
+    result: Any = None


@dataclass
--- a/src/crewai/task.py
+++ b/src/crewai/task.py
@@ -358,6 +358,8 @@ class Task(BaseModel):
        self.start_time = datetime.datetime.now()
        self._execution_span = self._telemetry.task_started(crew=agent.crew, task=self)

+        # Track delegation is now handled in _execute_tasks to ensure proper counting
+
        self.prompt_context = context
        tools = tools or self.tools or []

--- a/src/crewai/tools/agent_tools/agent_tools.py
+++ b/src/crewai/tools/agent_tools/agent_tools.py
@@ -1,10 +1,14 @@
 from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.tools.base_tool import BaseTool
-from crewai.utilities import I18N
+from crewai.utilities import I18N, Logger

 from .ask_question_tool import AskQuestionTool
 from .delegate_work_tool import DelegateWorkTool

+# Tool name constants
+DELEGATE_WORK_TOOL = "Delegate Work"
+ASK_QUESTION_TOOL = "Ask Question"
+

 class AgentTools:
    """Manager class for agent-related tools"""
@@ -12,21 +16,28 @@ class AgentTools:
    def __init__(self, agents: list[BaseAgent], i18n: I18N = I18N()):
        self.agents = agents
        self.i18n = i18n
+        self._logger = Logger()

    def tools(self) -> list[BaseTool]:
        """Get all available agent tools"""
        coworkers = ", ".join([f"{agent.role}" for agent in self.agents])

+        self._logger.log(
+            "debug", f"Creating delegation tools for agents: {coworkers}", color="blue"
+        )
+
        delegate_tool = DelegateWorkTool(
            agents=self.agents,
            i18n=self.i18n,
            description=self.i18n.tools("delegate_work").format(coworkers=coworkers),  # type: ignore
+            name=DELEGATE_WORK_TOOL,  # Using constant for consistency
        )

        ask_tool = AskQuestionTool(
            agents=self.agents,
            i18n=self.i18n,
            description=self.i18n.tools("ask_question").format(coworkers=coworkers),  # type: ignore
+            name=ASK_QUESTION_TOOL,  # Using constant for consistency
        )

        return [delegate_tool, ask_tool]
--- a/tests/crew_test.py
+++ b/tests/crew_test.py
@@ -22,6 +22,7 @@ from crewai.task import Task
 from crewai.tasks.conditional_task import ConditionalTask
 from crewai.tasks.output_format import OutputFormat
 from crewai.tasks.task_output import TaskOutput
+from crewai.tools.base_tool import BaseTool
 from crewai.types.usage_metrics import UsageMetrics
 from crewai.utilities import Logger
 from crewai.utilities.rpm_controller import RPMController
@@ -350,6 +351,42 @@ def test_manager_llm_requirement_for_hierarchical_process():
            tasks=[task],
        )

+class TestTool(BaseTool):
+    """Test tool for validation."""
+    name: str = "test_tool"
+    description: str = "A test tool"
+
+    def _run(self, *args, **kwargs):
+        return "test output"
+
+def test_manager_agent_tools_validation():
+    """Test that manager agent only has delegation tools."""
+    task = Task(
+        description="Test task",
+        expected_output="Test output",
+    )
+
+    # Test with manager_agent having non-delegation tools
+    manager = Agent(
+        role="Manager",
+        goal="Manage tasks",
+        backstory="Test manager",
+        tools=[TestTool()],
+    )
+
+    crew = Crew(
+        agents=[researcher, writer],
+        process=Process.hierarchical,
+        manager_agent=manager,
+        tasks=[task],
+    )
+
+    # Verify manager agent has only delegation tools
+    assert crew.manager_agent.tools is not None
+    assert len(crew.manager_agent.tools) == 2
+    tool_names = {tool.name for tool in crew.manager_agent.tools}
+    assert tool_names == {"Delegate Work", "Ask Question"}
+

@pytest.mark.vcr(filter_headers=["authorization"])
 def test_manager_agent_delegating_to_assigned_task_agent():
--- a/tests/flow_test.py
+++ b/tests/flow_test.py
@@ -1,11 +1,18 @@
 """Test Flow creation and execution basic functionality."""

 import asyncio
+from datetime import datetime

 import pytest
 from pydantic import BaseModel

 from crewai.flow.flow import Flow, and_, listen, or_, router, start
+from crewai.flow.flow_events import (
+    FlowFinishedEvent,
+    FlowStartedEvent,
+    MethodExecutionFinishedEvent,
+    MethodExecutionStartedEvent,
+)


 def test_simple_sequential_flow():
@@ -398,3 +405,218 @@ def test_router_with_multiple_conditions():

    # final_step should run after router_and
    assert execution_order.index("log_final_step") > execution_order.index("router_and")
+
+
+def test_unstructured_flow_event_emission():
+    """Test that the correct events are emitted during unstructured flow
+    execution with all fields validated."""
+
+    class PoemFlow(Flow):
+        @start()
+        def prepare_flower(self):
+            self.state["flower"] = "roses"
+            return "foo"
+
+        @start()
+        def prepare_color(self):
+            self.state["color"] = "red"
+            return "bar"
+
+        @listen(prepare_color)
+        def write_first_sentence(self):
+            return f"{self.state['flower']} are {self.state['color']}"
+
+        @listen(write_first_sentence)
+        def finish_poem(self, first_sentence):
+            separator = self.state.get("separator", "\n")
+            return separator.join([first_sentence, "violets are blue"])
+
+        @listen(finish_poem)
+        def save_poem_to_database(self):
+            # A method without args/kwargs to ensure events are sent correctly
+            pass
+
+    event_log = []
+
+    def handle_event(_, event):
+        event_log.append(event)
+
+    flow = PoemFlow()
+    flow.event_emitter.connect(handle_event)
+    flow.kickoff(inputs={"separator": ", "})
+
+    assert isinstance(event_log[0], FlowStartedEvent)
+    assert event_log[0].flow_name == "PoemFlow"
+    assert event_log[0].inputs == {"separator": ", "}
+    assert isinstance(event_log[0].timestamp, datetime)
+
+    # Asserting for concurrent start method executions in a for loop as you
+    # can't guarantee ordering in asynchronous executions
+    for i in range(1, 5):
+        event = event_log[i]
+        assert isinstance(event.state, dict)
+        assert isinstance(event.state["id"], str)
+
+        if event.method_name == "prepare_flower":
+            if isinstance(event, MethodExecutionStartedEvent):
+                assert event.params == {}
+                assert event.state["separator"] == ", "
+            elif isinstance(event, MethodExecutionFinishedEvent):
+                assert event.result == "foo"
+                assert event.state["flower"] == "roses"
+                assert event.state["separator"] == ", "
+            else:
+                assert False, "Unexpected event type for prepare_flower"
+        elif event.method_name == "prepare_color":
+            if isinstance(event, MethodExecutionStartedEvent):
+                assert event.params == {}
+                assert event.state["separator"] == ", "
+            elif isinstance(event, MethodExecutionFinishedEvent):
+                assert event.result == "bar"
+                assert event.state["color"] == "red"
+                assert event.state["separator"] == ", "
+            else:
+                assert False, "Unexpected event type for prepare_color"
+        else:
+            assert False, f"Unexpected method {event.method_name} in prepare events"
+
+    assert isinstance(event_log[5], MethodExecutionStartedEvent)
+    assert event_log[5].method_name == "write_first_sentence"
+    assert event_log[5].params == {}
+    assert isinstance(event_log[5].state, dict)
+    assert event_log[5].state["flower"] == "roses"
+    assert event_log[5].state["color"] == "red"
+    assert event_log[5].state["separator"] == ", "
+
+    assert isinstance(event_log[6], MethodExecutionFinishedEvent)
+    assert event_log[6].method_name == "write_first_sentence"
+    assert event_log[6].result == "roses are red"
+
+    assert isinstance(event_log[7], MethodExecutionStartedEvent)
+    assert event_log[7].method_name == "finish_poem"
+    assert event_log[7].params == {"_0": "roses are red"}
+    assert isinstance(event_log[7].state, dict)
+    assert event_log[7].state["flower"] == "roses"
+    assert event_log[7].state["color"] == "red"
+
+    assert isinstance(event_log[8], MethodExecutionFinishedEvent)
+    assert event_log[8].method_name == "finish_poem"
+    assert event_log[8].result == "roses are red, violets are blue"
+
+    assert isinstance(event_log[9], MethodExecutionStartedEvent)
+    assert event_log[9].method_name == "save_poem_to_database"
+    assert event_log[9].params == {}
+    assert isinstance(event_log[9].state, dict)
+    assert event_log[9].state["flower"] == "roses"
+    assert event_log[9].state["color"] == "red"
+
+    assert isinstance(event_log[10], MethodExecutionFinishedEvent)
+    assert event_log[10].method_name == "save_poem_to_database"
+    assert event_log[10].result is None
+
+    assert isinstance(event_log[11], FlowFinishedEvent)
+    assert event_log[11].flow_name == "PoemFlow"
+    assert event_log[11].result is None
+    assert isinstance(event_log[11].timestamp, datetime)
+
+
+def test_structured_flow_event_emission():
+    """Test that the correct events are emitted during structured flow
+    execution with all fields validated."""
+
+    class OnboardingState(BaseModel):
+        name: str = ""
+        sent: bool = False
+
+    class OnboardingFlow(Flow[OnboardingState]):
+        @start()
+        def user_signs_up(self):
+            self.state.sent = False
+
+        @listen(user_signs_up)
+        def send_welcome_message(self):
+            self.state.sent = True
+            return f"Welcome, {self.state.name}!"
+
+    event_log = []
+
+    def handle_event(_, event):
+        event_log.append(event)
+
+    flow = OnboardingFlow()
+    flow.event_emitter.connect(handle_event)
+    flow.kickoff(inputs={"name": "Anakin"})
+
+    assert isinstance(event_log[0], FlowStartedEvent)
+    assert event_log[0].flow_name == "OnboardingFlow"
+    assert event_log[0].inputs == {"name": "Anakin"}
+    assert isinstance(event_log[0].timestamp, datetime)
+
+    assert isinstance(event_log[1], MethodExecutionStartedEvent)
+    assert event_log[1].method_name == "user_signs_up"
+
+    assert isinstance(event_log[2], MethodExecutionFinishedEvent)
+    assert event_log[2].method_name == "user_signs_up"
+
+    assert isinstance(event_log[3], MethodExecutionStartedEvent)
+    assert event_log[3].method_name == "send_welcome_message"
+    assert event_log[3].params == {}
+    assert getattr(event_log[3].state, "sent") is False
+
+    assert isinstance(event_log[4], MethodExecutionFinishedEvent)
+    assert event_log[4].method_name == "send_welcome_message"
+    assert getattr(event_log[4].state, "sent") is True
+    assert event_log[4].result == "Welcome, Anakin!"
+
+    assert isinstance(event_log[5], FlowFinishedEvent)
+    assert event_log[5].flow_name == "OnboardingFlow"
+    assert event_log[5].result == "Welcome, Anakin!"
+    assert isinstance(event_log[5].timestamp, datetime)
+
+
+def test_stateless_flow_event_emission():
+    """Test that the correct events are emitted stateless during flow execution
+    with all fields validated."""
+
+    class StatelessFlow(Flow):
+        @start()
+        def init(self):
+            pass
+
+        @listen(init)
+        def process(self):
+            return "Deeds will not be less valiant because they are unpraised."
+
+    event_log = []
+
+    def handle_event(_, event):
+        event_log.append(event)
+
+    flow = StatelessFlow()
+    flow.event_emitter.connect(handle_event)
+    flow.kickoff()
+
+    assert isinstance(event_log[0], FlowStartedEvent)
+    assert event_log[0].flow_name == "StatelessFlow"
+    assert event_log[0].inputs is None
+    assert isinstance(event_log[0].timestamp, datetime)
+
+    assert isinstance(event_log[1], MethodExecutionStartedEvent)
+    assert event_log[1].method_name == "init"
+
+    assert isinstance(event_log[2], MethodExecutionFinishedEvent)
+    assert event_log[2].method_name == "init"
+
+    assert isinstance(event_log[3], MethodExecutionStartedEvent)
+    assert event_log[3].method_name == "process"
+
+    assert isinstance(event_log[4], MethodExecutionFinishedEvent)
+    assert event_log[4].method_name == "process"
+
+    assert isinstance(event_log[5], FlowFinishedEvent)
+    assert event_log[5].flow_name == "StatelessFlow"
+    assert (
+        event_log[5].result
+        == "Deeds will not be less valiant because they are unpraised."
+    )
+    assert isinstance(event_log[5].timestamp, datetime)
--- a/uv.lock
+++ b/uv.lock
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Author	SHA1	Message	Date
Devin AI	939e8e6736	fix: Fix code execution and multimodal tool handling in Agent class Co-Authored-By: Joe Moura <joao@crewai.com>	2025-02-14 21:25:17 +00:00
Devin AI	c6153cc1b4	fix: Fix multimodal and code execution tool handling Co-Authored-By: Joe Moura <joao@crewai.com>	2025-02-14 21:20:46 +00:00
Devin AI	4832b35779	fix: Fix code execution and multimodal tool handling Co-Authored-By: Joe Moura <joao@crewai.com>	2025-02-14 21:16:57 +00:00
Devin AI	be9caaf5ee	fix: Fix import sorting with ruff Co-Authored-By: Joe Moura <joao@crewai.com>	2025-02-14 21:13:46 +00:00
Devin AI	c080227751	fix: Fix import sorting and type checking issues Co-Authored-By: Joe Moura <joao@crewai.com>	2025-02-14 21:13:06 +00:00
Devin AI	2fbff69c81	fix: Fix type checking and import issues Co-Authored-By: Joe Moura <joao@crewai.com>	2025-02-14 21:10:53 +00:00
Devin AI	32c1c81978	style: Fix import sorting in agent_tools.py Co-Authored-By: Joe Moura <joao@crewai.com>	2025-02-14 21:06:36 +00:00
Devin AI	c4263bf8e6	fix: Add delegation tracking and improve error handling Co-Authored-By: Joe Moura <joao@crewai.com>	2025-02-14 21:02:24 +00:00
Devin AI	26751bb2cb	fix: Add error handling and consolidate tool assignment logic Co-Authored-By: Joe Moura <joao@crewai.com>	2025-02-14 20:32:16 +00:00
Devin AI	e4282f7c53	fix: Prevent manager agent from having tools assigned (#2131 ) - Add model validation to prevent tool assignment to manager agent - Improve error handling in _create_manager_agent - Add test to verify manager agent tools validation Co-Authored-By: Joe Moura <joao@crewai.com>	2025-02-14 20:25:12 +00:00
luctrate	1b488b6da7	fix: Missing required template variable 'current_year' in description (#2085 )	2025-02-13 10:19:52 -03:00
João Moura	d3b398ed52	preparring new version	2025-02-12 18:16:48 -05:00
Vini Brasil	d52fd09602	Fix linting issues (#2115 )	2025-02-12 15:33:16 -05:00
Vini Brasil	d6800d8957	Ensure `@start` methods emit `MethodExecutionStartedEvent` (#2114 ) Previously, `@start` methods triggered a `FlowStartedEvent` but did not emit a `MethodExecutionStartedEvent`. This was fine for a single entry point but caused ambiguity when multiple `@start` methods existed. This commit (1) emits events for starting points, (2) adds tests ensuring ordering, (3) adds more fields to events.	2025-02-12 14:19:41 -06:00
Tony Kipkemboi	2fd7506ed9	Merge pull request #2109 from tonykipkemboi/main docs: update observability documentation and mint configuration	2025-02-12 11:43:28 -05:00
Tony Kipkemboi	161084aff2	Update observability documentation and mint configuration	2025-02-12 10:17:36 -05:00
Tony Kipkemboi	b145cb3247	Merge pull request #2100 from jannikmaierhoefer/main docs: add Langfuse guide	2025-02-12 10:05:07 -05:00
Jannik Maierhöfer	1adbcf697d	fix openlit typo	2025-02-11 13:11:08 +01:00
Jannik Maierhöfer	e51355200a	docs: add Langfuse guide	2025-02-11 12:52:49 +01:00
Brandon Hancock (bhancock_ai)	47818f4f41	updating bedrock docs (#2088 ) Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>	2025-02-10 12:48:12 -05:00
Brandon Hancock (bhancock_ai)	9b10fd47b0	incorporate Small update in memory.mdx, fixing Google AI parameters #2008 (#2087 )	2025-02-10 12:17:41 -05:00
Brandon Hancock (bhancock_ai)	c408368267	fix linting issues in new tests (#2089 ) Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>	2025-02-10 12:10:53 -05:00