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# AworldServer
AworldServer is an execution environment for the Aworld framework that integrates MCP LLM models. It supports distributed deployment and dynamic scaling.
The system features:
- Distributed Architecture: Supports multi-server deployment with load balancing
- Dynamic Scaling: Ability to adjust server capacity based on demand
- LLM Integration: Built-in MCP LLM model support
- Asynchronous Processing: Uses asynchronous programming patterns for improved performance
- Containerized Deployment: Docker containerization support for easy environment management
## 🚀 Quick Start
1. Start services using Docker Compose:
```sh
docker build --build-arg MINIMUM_BUILD=true -f Dockerfile --progress=plain -t aworldserver:main .
docker compose up -d
```
2. Configure the number of server instances:
You can modify the `docker-compose.yaml` file to adjust the number of server instances. The default configuration includes 3 instances:
3. Usage Methods:
a. OpenWebUI Integration:
- Configure external link in OpenWebUI settings
- Add AworldServer endpoints to the configuration
- Set up API key authentication
b. Python Client Usage:
```python
# Initialize AworldTaskClient with server endpoints
AWORLD_TASK_CLIENT = AworldTaskClient(
know_hosts=["localhost:9299", "localhost:9399", "localhost:9499"]
)
async def _run_gaia_task(gaia_question_id: str) -> None:
"""Run a single Gaia task with the given question ID.
Args:
gaia_question_id: The ID of the question to process
"""
global AWORLD_TASK_CLIENT
task_id = str(uuid.uuid4())
# Submit task to Aworld server
await AWORLD_TASK_CLIENT.submit_task(
AworldTask(
task_id=task_id,
agent_id="gaia_agent",
agent_input=gaia_question_id,
session_id="session_id",
user_id="SYSTEM"
)
)
# Get and print task result
task_result = await AWORLD_TASK_CLIENT.get_task_state(task_id=task_id)
print(task_result)
async def _batch_run_gaia_task(start_i: int, end_i: int) -> None:
"""Run multiple Gaia tasks in parallel.
Args:
start_i: Starting question ID
end_i: Ending question ID
"""
tasks = [
_run_gaia_task(str(i))
for i in range(start_i, end_i + 1)
]
await asyncio.gather(*tasks)
if __name__ == '__main__':
# Run batch processing for questions 1-5
asyncio.run(_batch_run_gaia_task(1, 5))
```
c. user curl
```shell
curl http://localhost:9299/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer 0p3n-w3bu!" \
-d '{
"model": "gaia_agent",
"messages": [
{
"role": "user",
"content": [
{
"type": "text",
"text": "5"
}
]
}
]
}'
```
## 🔑 Key Features
- **Distributed Task Processing System**
- Multi-server load balancing
- Round-robin task distribution
- Asynchronous task processing
- **Docker Containerization**
- Multi-instance deployment
- Environment variable configuration
- Auto-restart mechanism
- **API Services**
- FastAPI framework support
- RESTful API design
- Asynchronous request handling
- **Development Tools**
- Debug mode support
- Batch task processing
- Task state tracking
- **Security Features**
- API key authentication
- Session management
- User authentication
## 📦 Installation and Setup
Get started with aworldserver in a few easy steps:
1. **Ensure Python 3.11 is installed.**
2. **Install the required dependencies:**
```sh
pip install -r requirements-minimux.txt
```
3. **Start the aworld server:**
```sh
sh ./start.sh
```
### Custom debug
please run `debug_run.py`
##
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