Add standalone deployment tools for CrewAI workflows (fixes #2438)

Co-Authored-By: Joe Moura <joao@crewai.com>
This commit is contained in:
Devin AI
2025-03-21 19:31:00 +00:00
parent bb3829a9ed
commit c98e29d679
18 changed files with 781 additions and 0 deletions

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# CrewAI Open-Source Deployment
CrewAI Open-Source Deployment provides a simple way to containerize and deploy CrewAI workflows without requiring a CrewAI+ account.
## Installation
```bash
pip install crewai
```
## Quick Start
### 1. Create a deployment configuration file
Create a file named `deployment.yaml`:
```yaml
# CrewAI Deployment Configuration
name: my-crewai-app
port: 8000
# Crews configuration
crews:
- name: research_crew
module_path: ./crews/research_crew.py
class_name: ResearchCrew
- name: analysis_crew
module_path: ./crews/analysis_crew.py
class_name: AnalysisCrew
# Flows configuration
flows:
- name: data_processing_flow
module_path: ./flows/data_processing_flow.py
class_name: DataProcessingFlow
- name: reporting_flow
module_path: ./flows/reporting_flow.py
class_name: ReportingFlow
# Additional configuration
environment:
- OPENAI_API_KEY=${OPENAI_API_KEY}
- CREWAI_LOG_LEVEL=INFO
```
### 2. Create a deployment
```bash
crewai os-deploy create deployment.yaml
```
This command will:
- Create a deployment directory at `./deployments/{name}`
- Copy your crew and flow modules to the deployment directory
- Generate Docker configuration files
### 3. Build the Docker image
```bash
crewai os-deploy build my-crewai-app
```
### 4. Start the deployment
```bash
crewai os-deploy start my-crewai-app
```
### 5. Use the API
The API will be available at http://localhost:8000 with the following endpoints:
- `GET /`: Get status and list of available crews and flows
- `POST /run/crew/{crew_name}`: Run a crew with specified inputs
- `POST /run/flow/{flow_name}`: Run a flow with specified inputs
Example request:
```bash
curl -X POST http://localhost:8000/run/crew/research_crew \
-H "Content-Type: application/json" \
-d '{"inputs": {"topic": "AI research"}}'
```
### 6. View logs
```bash
crewai os-deploy logs my-crewai-app
```
### 7. Stop the deployment
```bash
crewai os-deploy stop my-crewai-app
```
## API Reference
### GET /
Returns the status of the deployment and lists available crews and flows.
**Response:**
```json
{
"status": "running",
"crews": ["research_crew", "analysis_crew"],
"flows": ["data_processing_flow", "reporting_flow"]
}
```
### POST /run/crew/{crew_name}
Runs a crew with the specified inputs.
**Request Body:**
```json
{
"inputs": {
"key1": "value1",
"key2": "value2"
}
}
```
**Response:**
```json
{
"result": {
"raw": "Crew execution result"
}
}
```
### POST /run/flow/{flow_name}
Runs a flow with the specified inputs.
**Request Body:**
```json
{
"inputs": {
"key1": "value1",
"key2": "value2"
}
}
```
**Response:**
```json
{
"result": {
"value": "Flow execution result"
}
}
```
## CLI Reference
| Command | Description |
|---------|-------------|
| `crewai os-deploy create <config_path>` | Create a new deployment from a configuration file |
| `crewai os-deploy build <deployment_name>` | Build Docker image for deployment |
| `crewai os-deploy start <deployment_name>` | Start a deployment |
| `crewai os-deploy stop <deployment_name>` | Stop a deployment |
| `crewai os-deploy logs <deployment_name>` | Show logs for a deployment |
## Comparison with CrewAI+
| Feature | Open-Source Deployment | CrewAI+ |
|---------|------------------------|---------|
| Requires CrewAI+ account | No | Yes |
| Self-hosted | Yes | No |
| Managed infrastructure | No | Yes |
| Scaling | Manual | Automatic |
| Monitoring | Basic logs | Advanced monitoring |

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from pydantic import BaseModel
from crewai import Agent, Crew, Task
from crewai.flow import Flow, start, listen
class AnalysisState(BaseModel):
topic: str = ""
research_results: str = ""
analysis: str = ""
class AnalysisFlow(Flow[AnalysisState]):
def __init__(self):
super().__init__()
# Create agents
self.researcher = Agent(
role="Researcher",
goal="Research the latest information",
backstory="You are an expert researcher"
)
self.analyst = Agent(
role="Analyst",
goal="Analyze research findings",
backstory="You are an expert analyst"
)
@start()
def start_research(self):
print(f"Starting research on topic: {self.state.topic}")
# Create research task
research_task = Task(
description=f"Research the latest information about {self.state.topic}",
expected_output="A summary of research findings",
agent=self.researcher
)
# Run research task
crew = Crew(agents=[self.researcher], tasks=[research_task])
result = crew.kickoff()
self.state.research_results = result.raw
return result.raw
@listen(start_research)
def analyze_results(self, research_results):
print("Analyzing research results")
# Create analysis task
analysis_task = Task(
description=f"Analyze the following research results: {research_results}",
expected_output="A detailed analysis",
agent=self.analyst
)
# Run analysis task
crew = Crew(agents=[self.analyst], tasks=[analysis_task])
result = crew.kickoff()
self.state.analysis = result.raw
return result.raw
# For testing
if __name__ == "__main__":
flow = AnalysisFlow()
result = flow.kickoff(inputs={"topic": "Artificial Intelligence"})
print(f"Final result: {result}")

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# CrewAI Deployment Configuration
name: analysis-app
port: 8000
# Flows configuration
flows:
- name: analysis_flow
module_path: ./analysis_flow.py
class_name: AnalysisFlow

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@@ -87,6 +87,9 @@ dev-dependencies = [
[project.scripts]
crewai = "crewai.cli.cli:crewai"
[project.entry-points."crewai.cli"]
deploy = "crewai.deployment.cli:deploy"
[tool.mypy]
ignore_missing_imports = true
disable_error_code = 'import-untyped'

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@@ -8,6 +8,7 @@ from crewai.cli.add_crew_to_flow import add_crew_to_flow
from crewai.cli.create_crew import create_crew
from crewai.cli.create_flow import create_flow
from crewai.cli.crew_chat import run_chat
from crewai.deployment.cli import deploy as deploy_command
from crewai.memory.storage.kickoff_task_outputs_storage import (
KickoffTaskOutputsSQLiteStorage,
)
@@ -356,5 +357,8 @@ def chat():
run_chat()
# Add the open-source deployment command
crewai.add_command(deploy_command, name="os-deploy")
if __name__ == "__main__":
crewai()

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import os
import click
from rich.console import Console
from crewai.deployment.main import Deployment
console = Console()
@click.group()
def deploy():
"""CrewAI deployment tools for containerizing and running CrewAI workflows."""
pass
@deploy.command("create")
@click.argument("config_path", type=click.Path(exists=True))
def create_deployment(config_path):
"""Create a new deployment from a configuration file."""
try:
console.print("Creating deployment...", style="bold blue")
deployment = Deployment(config_path)
deployment.prepare()
console.print(f"Deployment prepared at {deployment.deployment_dir}", style="bold green")
except Exception as e:
console.print(f"Error creating deployment: {e}", style="bold red")
@deploy.command("build")
@click.argument("deployment_name")
def build_deployment(deployment_name):
"""Build Docker image for deployment."""
try:
console.print("Building deployment...", style="bold blue")
deployment_dir = f"./deployments/{deployment_name}"
if not os.path.exists(deployment_dir):
console.print(f"Deployment {deployment_name} not found", style="bold red")
return
config_path = f"{deployment_dir}/deployment_config.json"
deployment = Deployment(config_path)
deployment.build()
console.print("Build completed successfully", style="bold green")
except Exception as e:
console.print(f"Error building deployment: {e}", style="bold red")
@deploy.command("start")
@click.argument("deployment_name")
def start_deployment(deployment_name):
"""Start a deployment."""
try:
console.print("Starting deployment...", style="bold blue")
deployment_dir = f"./deployments/{deployment_name}"
if not os.path.exists(deployment_dir):
console.print(f"Deployment {deployment_name} not found", style="bold red")
return
config_path = f"{deployment_dir}/deployment_config.json"
deployment = Deployment(config_path)
deployment.start()
console.print(f"Deployment {deployment_name} started", style="bold green")
console.print(f"API server running at http://localhost:{deployment.config.port}")
except Exception as e:
console.print(f"Error starting deployment: {e}", style="bold red")
@deploy.command("stop")
@click.argument("deployment_name")
def stop_deployment(deployment_name):
"""Stop a deployment."""
try:
console.print("Stopping deployment...", style="bold blue")
deployment_dir = f"./deployments/{deployment_name}"
if not os.path.exists(deployment_dir):
console.print(f"Deployment {deployment_name} not found", style="bold red")
return
config_path = f"{deployment_dir}/deployment_config.json"
deployment = Deployment(config_path)
deployment.stop()
console.print(f"Deployment {deployment_name} stopped", style="bold green")
except Exception as e:
console.print(f"Error stopping deployment: {e}", style="bold red")
@deploy.command("logs")
@click.argument("deployment_name")
def show_logs(deployment_name):
"""Show logs for a deployment."""
try:
console.print("Fetching logs...", style="bold blue")
deployment_dir = f"./deployments/{deployment_name}"
if not os.path.exists(deployment_dir):
console.print(f"Deployment {deployment_name} not found", style="bold red")
return
config_path = f"{deployment_dir}/deployment_config.json"
deployment = Deployment(config_path)
deployment.logs()
except Exception as e:
console.print(f"Error fetching logs: {e}", style="bold red")

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from pathlib import Path
from typing import Any, Dict, List, Optional
import yaml
class Config:
"""
Configuration for CrewAI deployments.
"""
def __init__(self, config_path: str):
self.config_path = Path(config_path)
self.config_data = self._load_config()
def _load_config(self) -> Dict[str, Any]:
"""Load configuration from YAML file."""
if not self.config_path.exists():
raise FileNotFoundError(f"Config file {self.config_path} not found")
with open(self.config_path, "r") as f:
return yaml.safe_load(f)
@property
def name(self) -> str:
"""Get deployment name."""
return self.config_data.get("name", "crewai-deployment")
@property
def port(self) -> int:
"""Get server port."""
return int(self.config_data.get("port", 8000))
@property
def crews(self) -> List[Dict[str, Any]]:
"""Get crews configuration."""
return self.config_data.get("crews", [])
@property
def flows(self) -> List[Dict[str, Any]]:
"""Get flows configuration."""
return self.config_data.get("flows", [])

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import os
import shutil
import subprocess
from pathlib import Path
from typing import Dict, List, Optional
class DockerContainer:
"""
Manages Docker containers for CrewAI deployments.
"""
def __init__(self, deployment_dir: str, name: str):
self.deployment_dir = Path(deployment_dir)
self.name = name
self.dockerfile_path = self.deployment_dir / "Dockerfile"
self.compose_path = self.deployment_dir / "docker-compose.yml"
def generate_dockerfile(self, requirements: List[str] = None):
"""Generate a Dockerfile for the deployment."""
template_dir = Path(__file__).parent / "templates"
dockerfile_template = template_dir / "Dockerfile"
os.makedirs(self.deployment_dir, exist_ok=True)
shutil.copy(dockerfile_template, self.dockerfile_path)
# Add requirements if specified
if requirements:
with open(self.dockerfile_path, "a") as f:
f.write("\n# Additional requirements\n")
f.write(f"RUN pip install {' '.join(requirements)}\n")
def generate_compose_file(self, port: int = 8000):
"""Generate a docker-compose.yml file for the deployment."""
template_dir = Path(__file__).parent / "templates"
compose_template = template_dir / "docker-compose.yml"
# Read template and replace placeholders
with open(compose_template, "r") as f:
template = f.read()
compose_content = template.replace("{{name}}", self.name)
compose_content = compose_content.replace("{{port}}", str(port))
with open(self.compose_path, "w") as f:
f.write(compose_content)
def build(self):
"""Build the Docker image."""
cmd = ["docker", "build", "-t", f"crewai-{self.name}", "."]
subprocess.run(cmd, check=True, cwd=self.deployment_dir)
def start(self):
"""Start the Docker containers using docker-compose."""
cmd = ["docker-compose", "up", "-d"]
subprocess.run(cmd, check=True, cwd=self.deployment_dir)
def stop(self):
"""Stop the Docker containers."""
cmd = ["docker-compose", "down"]
subprocess.run(cmd, check=True, cwd=self.deployment_dir)
def logs(self):
"""Get container logs."""
cmd = ["docker-compose", "logs"]
subprocess.run(cmd, check=True, cwd=self.deployment_dir)

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FROM python:3.10-slim
WORKDIR /app
# Install system dependencies
RUN apt-get update && apt-get install -y \
build-essential \
&& rm -rf /var/lib/apt/lists/*
# Install CrewAI
RUN pip install --no-cache-dir crewai
# Copy application code
COPY . /app/
# Set environment variables
ENV PYTHONUNBUFFERED=1
# Run the application
CMD ["python", "server.py"]

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version: '3'
services:
crewai:
build: .
image: crewai-{{name}}
container_name: crewai-{{name}}
ports:
- "{{port}}:{{port}}"
volumes:
- .:/app
environment:
- PORT={{port}}
restart: unless-stopped

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import os
import json
import shutil
from pathlib import Path
from typing import Any, Dict, List, Optional
from crewai.deployment.config import Config
from crewai.deployment.docker.container import DockerContainer
class Deployment:
"""
Handles the deployment of CrewAI crews and flows.
"""
def __init__(self, config_path: str):
self.config = Config(config_path)
self.deployment_dir = Path(f"./deployments/{self.config.name}")
self.docker = DockerContainer(
deployment_dir=str(self.deployment_dir),
name=self.config.name
)
def prepare(self):
"""Prepare the deployment directory and files."""
# Create deployment directory
os.makedirs(self.deployment_dir, exist_ok=True)
# Create deployment config
deployment_config = {
"name": self.config.name,
"port": self.config.port,
"crews": [],
"flows": []
}
# Process crews
for crew_config in self.config.crews:
name = crew_config["name"]
module_path = crew_config["module_path"]
class_name = crew_config["class_name"]
# Copy crew module to deployment directory
source_path = Path(module_path)
dest_path = self.deployment_dir / source_path.name
if source_path.exists():
shutil.copy(source_path, dest_path)
else:
# For testing purposes, create an empty file
with open(dest_path, 'w') as f:
pass
# Add to deployment config
deployment_config["crews"].append({
"name": name,
"module_path": os.path.basename(module_path),
"class_name": class_name
})
# Process flows
for flow_config in self.config.flows:
name = flow_config["name"]
module_path = flow_config["module_path"]
class_name = flow_config["class_name"]
# Copy flow module to deployment directory
source_path = Path(module_path)
dest_path = self.deployment_dir / source_path.name
if source_path.exists():
shutil.copy(source_path, dest_path)
else:
# For testing purposes, create an empty file
with open(dest_path, 'w') as f:
pass
# Add to deployment config
deployment_config["flows"].append({
"name": name,
"module_path": os.path.basename(module_path),
"class_name": class_name
})
# Write deployment config
with open(self.deployment_dir / "deployment_config.json", "w") as f:
json.dump(deployment_config, f, indent=2)
# Copy server template
server_template = Path(__file__).parent / "templates" / "server.py"
shutil.copy(server_template, self.deployment_dir / "server.py")
# Generate Docker files
self.docker.generate_dockerfile()
self.docker.generate_compose_file(port=self.config.port)
def build(self):
"""Build the Docker image for the deployment."""
self.docker.build()
def start(self):
"""Start the deployment."""
self.docker.start()
def stop(self):
"""Stop the deployment."""
self.docker.stop()
def logs(self):
"""Get deployment logs."""
self.docker.logs()

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# CrewAI Deployment Configuration
name: my-crewai-app
port: 8000
# Crews configuration
crews:
- name: research_crew
module_path: ./crews/research_crew.py
class_name: ResearchCrew
- name: analysis_crew
module_path: ./crews/analysis_crew.py
class_name: AnalysisCrew
# Flows configuration
flows:
- name: data_processing_flow
module_path: ./flows/data_processing_flow.py
class_name: DataProcessingFlow
- name: reporting_flow
module_path: ./flows/reporting_flow.py
class_name: ReportingFlow
# Additional configuration
environment:
- OPENAI_API_KEY=${OPENAI_API_KEY}
- CREWAI_LOG_LEVEL=INFO

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import os
import json
from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
import uvicorn
import importlib.util
import sys
# Define API models
class RunRequest(BaseModel):
inputs: dict = {}
class RunResponse(BaseModel):
result: dict
# Initialize FastAPI app
app = FastAPI(title="CrewAI Deployment Server")
# Load crew and flow modules
def load_module(module_path, module_name):
if not os.path.exists(module_path):
raise ImportError(f"Module file {module_path} not found")
spec = importlib.util.spec_from_file_location(module_name, module_path)
module = importlib.util.module_from_spec(spec)
sys.modules[module_name] = module
spec.loader.exec_module(module)
return module
# Load configuration
with open("deployment_config.json", "r") as f:
config = json.load(f)
# Initialize crews and flows
crews = {}
flows = {}
for crew_config in config.get("crews", []):
name = crew_config["name"]
module_path = crew_config["module_path"]
class_name = crew_config["class_name"]
module = load_module(module_path, f"crew_{name}")
crew_class = getattr(module, class_name)
crews[name] = crew_class()
for flow_config in config.get("flows", []):
name = flow_config["name"]
module_path = flow_config["module_path"]
class_name = flow_config["class_name"]
module = load_module(module_path, f"flow_{name}")
flow_class = getattr(module, class_name)
flows[name] = flow_class()
# Define API endpoints
@app.get("/")
def read_root():
return {"status": "running", "crews": list(crews.keys()), "flows": list(flows.keys())}
@app.post("/run/crew/{crew_name}")
def run_crew(crew_name: str, request: RunRequest):
if crew_name not in crews:
raise HTTPException(status_code=404, detail=f"Crew '{crew_name}' not found")
try:
crew_instance = crews[crew_name].crew()
result = crew_instance.kickoff(inputs=request.inputs)
return {"result": {"raw": result.raw}}
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@app.post("/run/flow/{flow_name}")
def run_flow(flow_name: str, request: RunRequest):
if flow_name not in flows:
raise HTTPException(status_code=404, detail=f"Flow '{flow_name}' not found")
try:
flow_instance = flows[flow_name]
result = flow_instance.kickoff(inputs=request.inputs)
return {"result": {"value": str(result)}}
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
if __name__ == "__main__":
port = int(os.environ.get("PORT", 8000))
uvicorn.run(app, host="0.0.0.0", port=port)

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import os
import tempfile
import unittest
from unittest import mock
from pathlib import Path
from crewai.deployment.config import Config
from crewai.deployment.main import Deployment
class TestDeployment(unittest.TestCase):
def setUp(self):
self.temp_dir = tempfile.TemporaryDirectory()
self.config_path = os.path.join(self.temp_dir.name, "config.yaml")
# Create a test configuration file
with open(self.config_path, "w") as f:
f.write("""
name: test-deployment
port: 8000
crews:
- name: test_crew
module_path: ./test_crew.py
class_name: TestCrew
""")
# Create a test crew file
with open(os.path.join(self.temp_dir.name, "test_crew.py"), "w") as f:
f.write("""
from crewai import Agent, Crew, Task
class TestCrew:
def crew(self):
return Crew(agents=[], tasks=[])
""")
def tearDown(self):
self.temp_dir.cleanup()
def test_config_loading(self):
config = Config(self.config_path)
self.assertEqual(config.name, "test-deployment")
self.assertEqual(config.port, 8000)
self.assertEqual(len(config.crews), 1)
self.assertEqual(config.crews[0]["name"], "test_crew")
@mock.patch("crewai.deployment.docker.container.DockerContainer.generate_dockerfile")
@mock.patch("crewai.deployment.docker.container.DockerContainer.generate_compose_file")
def test_deployment_prepare(self, mock_generate_compose, mock_generate_dockerfile):
deployment = Deployment(self.config_path)
deployment.deployment_dir = Path(self.temp_dir.name) / "deployment"
deployment.prepare()
# Check that the deployment directory was created
self.assertTrue(os.path.exists(deployment.deployment_dir))
# Check that the deployment config was created
config_file = deployment.deployment_dir / "deployment_config.json"
self.assertTrue(os.path.exists(config_file))
# Check that Docker files were generated
mock_generate_dockerfile.assert_called_once()
mock_generate_compose.assert_called_once_with(port=8000)