diff --git a/docs/how-to/langfuse-observability.mdx b/docs/how-to/langfuse-observability.mdx
new file mode 100644
index 0000000000..c0feb6d872
--- /dev/null
+++ 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.
+
+
+
+_[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)
diff --git a/docs/how-to/portkey-observability-and-guardrails.mdx b/docs/how-to/portkey-observability-and-guardrails.mdx
deleted file mode 100644
index f4f7a696e1..0000000000
--- a/docs/how-to/portkey-observability-and-guardrails.mdx
+++ /dev/null
@@ -1,211 +0,0 @@
-# Portkey Integration with CrewAI
-
-
-
-[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.
-
-
- 
-
-
-
-### 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
-
-
-
-### 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.
-
-
- Traces
- 
-
-
-
- Logs
- 
-
-
-### 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)
-
-
-
-
-
-
-
-
-
diff --git a/docs/how-to/portkey-observability.mdx b/docs/how-to/portkey-observability.mdx
index 4002323a54..d071b49fc1 100644
--- 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
---
diff --git a/docs/mint.json b/docs/mint.json
index a49f609462..fb0dcfdf51 100644
--- 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"
]
},
{
diff --git a/pyproject.toml b/pyproject.toml
index 37ecf0cad9..c17d5fedbc 100644
--- 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"
]
diff --git a/src/crewai/__init__.py b/src/crewai/__init__.py
index 7264c1d5cd..662af25635 100644
--- a/src/crewai/__init__.py
+++ b/src/crewai/__init__.py
@@ -14,7 +14,7 @@
category=UserWarning,
module="pydantic.main",
)
-__version__ = "0.100.1"
+__version__ = "0.102.0"
__all__ = [
"Agent",
"Crew",
diff --git a/src/crewai/cli/templates/crew/main.py b/src/crewai/cli/templates/crew/main.py
index 104f146c0b..d9fe85d428 100644
--- 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)
diff --git a/src/crewai/cli/templates/crew/pyproject.toml b/src/crewai/cli/templates/crew/pyproject.toml
index 167ce267ed..a7d9c14252 100644
--- 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]
diff --git a/src/crewai/cli/templates/flow/pyproject.toml b/src/crewai/cli/templates/flow/pyproject.toml
index 2db6014a8b..63635bb9a7 100644
--- 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]
diff --git a/src/crewai/cli/templates/tool/pyproject.toml b/src/crewai/cli/templates/tool/pyproject.toml
index 39f983f6a1..2606f6ddb8 100644
--- 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]
diff --git a/src/crewai/flow/flow.py b/src/crewai/flow/flow.py
index 382a792e5d..f1242a2bf8 100644
--- 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 @@ def __new__(mcs, name, bases, dct):
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 StateWithId(state_type, FlowState): # type: ignore
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 @@ def kickoff(self, inputs: Optional[Dict[str, Any]] = None) -> Any:
event=FlowStartedEvent(
type="flow_started",
flow_name=self.__class__.__name__,
+ inputs=inputs,
),
)
self._log_flow_event(
@@ -803,6 +807,18 @@ async def _execute_start_method(self, start_method_name: str) -> None:
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 @@ async def _execute_method(
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 @@ async def _execute_single_listener(self, listener_name: str, result: Any) -> Non
"""
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 @@ async def _execute_single_listener(self, listener_name: str, result: Any) -> Non
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)
diff --git a/src/crewai/flow/flow_events.py b/src/crewai/flow/flow_events.py
index 068005ebef..c8f9e96948 100644
--- 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 @@ def __post_init__(self):
@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
diff --git a/tests/flow_test.py b/tests/flow_test.py
index 44ea1d15db..d036f7987b 100644
--- 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 log_final_step(self):
# 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)
diff --git a/uv.lock b/uv.lock
index 3784605379..d02181f54a 100644
--- a/uv.lock
+++ b/uv.lock
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version = "2.4.1"
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name = "attrs"
version = "24.2.0"
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name = "autoflake"
version = "2.3.1"
@@ -595,14 +565,14 @@ wheels = [
[[package]]
name = "click"
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+version = "8.1.8"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "colorama", marker = "platform_system == 'Windows'" },
]
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+sdist = { url = "https://files.pythonhosted.org/packages/b9/2e/0090cbf739cee7d23781ad4b89a9894a41538e4fcf4c31dcdd705b78eb8b/click-8.1.8.tar.gz", hash = "sha256:ed53c9d8990d83c2a27deae68e4ee337473f6330c040a31d4225c9574d16096a", size = 226593 }
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@@ -649,7 +619,7 @@ wheels = [
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name = "crewai"
-version = "0.100.1"
+version = "0.102.0"
source = { editable = "." }
dependencies = [
{ name = "appdirs" },
@@ -733,7 +703,7 @@ requires-dist = [
{ name = "blinker", specifier = ">=1.9.0" },
{ name = "chromadb", specifier = ">=0.5.23" },
{ name = "click", specifier = ">=8.1.7" },
- { name = "crewai-tools", marker = "extra == 'tools'", specifier = ">=0.32.1" },
+ { name = "crewai-tools", marker = "extra == 'tools'", specifier = ">=0.36.0" },
{ name = "docling", marker = "extra == 'docling'", specifier = ">=2.12.0" },
{ name = "fastembed", marker = "extra == 'fastembed'", specifier = ">=0.4.1" },
{ name = "instructor", specifier = ">=1.3.3" },
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[[package]]
name = "crewai-tools"
-version = "0.32.1"
+version = "0.36.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
- { name = "beautifulsoup4" },
{ name = "chromadb" },
+ { name = "click" },
{ name = "crewai" },
{ name = "docker" },
- { name = "docx2txt" },
{ name = "embedchain" },
{ name = "lancedb" },
- { name = "linkup-sdk" },
{ name = "openai" },
- { name = "patronus" },
{ name = "pydantic" },
{ name = "pyright" },
{ name = "pytube" },
{ name = "requests" },
- { name = "scrapegraph-py" },
- { name = "selenium" },
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