| Name | agentsociety-benchmark JSON |
| Version |
0.1.4
JSON |
| download |
| home_page | None |
| Summary | A tool for benchmark your agent design in different scenarios. |
| upload_time | 2025-07-24 00:40:22 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.11 |
| license | Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. "Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. "Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. "You" (or "Your") shall mean an individual or Legal Entity exercising permissions granted by this License. "Source" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files. "Object" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types. "Work" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below). "Derivative Works" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof. "Contribution" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. For the purposes of this definition, "submitted" means any form of electronic, verbal, or written communication sent to the Licensor or its representatives, including but not limited to communication on electronic mailing lists, source code control systems, and issue tracking systems that are managed by, or on behalf of, the Licensor for the purpose of discussing and improving the Work, but excluding communication that is conspicuously marked or otherwise designated in writing by the copyright owner as "Not a Contribution." "Contributor" shall mean Licensor and any individual or Legal Entity on behalf of whom a Contribution has been received by Licensor and subsequently incorporated within the Work. 2. Grant of Copyright License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form. 3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed. 4. Redistribution. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions: (a) You must give any other recipients of the Work or Derivative Works a copy of this License; and (b) You must cause any modified files to carry prominent notices stating that You changed the files; and (c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and (d) If the Work includes a "NOTICE" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. 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You are solely responsible for determining the appropriateness of using or redistributing the Work and assume any risks associated with Your exercise of permissions under this License. 8. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Work (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages. 9. Accepting Warranty or Additional Liability. 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# AgentSociety Benchmark Toolkit
## Tool Objectives
The AgentSociety Benchmark Toolkit is a comprehensive evaluation tool designed for multi-agent systems. This tool aims to help researchers and developers:
- **Standardize Evaluation Process**: Provide a unified evaluation framework to ensure fair comparison between different agent systems
- **Multi-Scenario Testing**: Support agent behavior evaluation in various real-world scenarios
- **Automated Assessment**: Simplify the entire evaluation workflow from data preparation to result analysis
- **Reproducibility**: Ensure reproducibility and verifiability of experimental results
## Supported Benchmarks
### 1. BehaviorModeling
The BehaviorModeling benchmark focuses on evaluating agents' behavior modeling capabilities in complex social scenarios. This benchmark tests how agents:
- Understand and simulate human behavior patterns
- Make reasonable decisions in group environments
- Adapt to different social norms and constraints
### 2. DailyMobility
The DailyMobility benchmark evaluates agents' mobility behavior modeling capabilities in daily life. This benchmark tests how agents:
- Plan reasonable daily activity routes
- Consider correlations between time, location, and activities
- Simulate real-world mobility patterns
### 3. HarricaneMobility
The HarricaneMobility benchmark focuses on evaluating agents' behavior modeling capabilities in emergency situations. This benchmark tests how agents:
- Make emergency decisions during natural disasters
- Simulate crowd evacuation and shelter-seeking behaviors
- Handle uncertainty and resource allocation in emergency situations
## Basic Usage
### Installation
```bash
# Install from source
git clone <repository-url>
cd packages/agentsociety-benchmark
pip install -e .
# Or install via pip (if published)
pip install agentsociety-benchmark
```
### Command Line Interface
#### View Available Tasks
```bash
# List all available benchmark tasks
asbench list-tasks
```
#### Download Datasets
- You need to install git lfc firstly.
```bash
# Clone datasets for specific benchmarks, this will clone the datasets and install dependancies at the same time
asbench clone BehaviorModeling
asbench clone DailyMobility
asbench clone HarricaneMobility
# View installed benchmarks
asbench list-installed
# Force clone datasets for specific benchmarks
asbench clone BehaviorModeling --force
# Only install dependancies for specific benchmarks
asbench clone BehaviorModeling --only-install-deps
```
#### Run Evaluation
```bash
# Run evaluation for specific benchmark
asbench run <TASK-NAME> --config your_config.yaml --agent your_agent.py --mode test/inference
```
#### Independent Result Evaluation
```bash
# Independently evaluate generated result files
asbench evaluate <TASK-NAME> results.json --config your_config.yaml
```
#### Update Benchmarks
```bash
# Update all benchmarks to latest versions
asbench update-benchmarks
```
### Programmatic Usage
The AgentSociety Benchmark also supports programmatic usage through Python code, allowing you to integrate benchmark execution into your applications and scripts.
#### Basic Usage
```python
import asyncio
from agentsociety_benchmark import BenchmarkRunner, run_benchmark, evaluate_results
async def run_my_benchmark():
# Create a BenchmarkRunner instance
runner = BenchmarkRunner(home_dir="./benchmark_data")
# Run a benchmark
result = await runner.run_benchmark(
task_name="BehaviorModeling",
benchmark_config="config.yaml",
agent_config="agent_config.yaml",
mode="test", # Run with evaluation
tenant_id="my_tenant",
exp_id="my_experiment_001"
)
print(f"Benchmark completed! Experiment ID: {result['exp_id']}")
print(f"Results: {result['results']}")
print(f"Evaluation: {result['evaluation']}")
# Run the benchmark
asyncio.run(run_my_benchmark())
```
#### Using Convenience Functions
```python
import asyncio
from agentsociety_benchmark import run_benchmark, evaluate_results, list_available_tasks
async def simple_benchmark():
# List available tasks
tasks = list_available_tasks()
print(f"Available tasks: {tasks}")
# Run benchmark using convenience function
result = await run_benchmark(
task_name="BehaviorModeling",
benchmark_config="config.yaml",
agent_config="agent_config.yaml",
mode="inference" # Run without evaluation
)
# Evaluate results separately if needed
if result['results']:
evaluation = await evaluate_results(
task_name="BehaviorModeling",
results_file="results.pkl",
benchmark_config="config.yaml"
)
print(f"Evaluation result: {evaluation['evaluation_result']}")
asyncio.run(simple_benchmark())
```
#### Advanced Usage
```python
import asyncio
from agentsociety_benchmark import BenchmarkRunner
async def advanced_benchmark():
# Create runner with custom settings
runner = BenchmarkRunner(home_dir="./custom_data")
# Run with advanced configuration
result = await runner.run_benchmark(
task_name="BehaviorModeling",
benchmark_config="my_config.yaml",
agent_config="my_agent.py",
datasets_path="./my_datasets",
mode="test",
tenant_id="advanced_example",
exp_id="advanced_001",
official=True, # Mark as official validation
callback_url="https://my-callback-url.com/webhook"
)
print(f"Advanced benchmark completed: {result}")
asyncio.run(advanced_benchmark())
```
#### Configuration Files
You'll need to create configuration files for your benchmarks:
**Benchmark Configuration (config.yaml):**
```yaml
llm:
- api_key: YOUR-API-KEY
model: gpt-4
provider: openai
semaphore: 200
env:
db:
enabled: true
home_dir: .agentsociety-benchmark/agentsociety_data
```
**Agent Configuration (agent_config.yaml):**
```yaml
agent_class: my_agent.py
number: 1
config:
name: MyAgent
description: A custom agent for testing
```
#### Complete Example
See `examples/programmatic_usage.py` for a complete working example that demonstrates all the features of the programmatic API.
### Storage and Configuration
- **Data Storage**: All benchmark data is stored in the `.agentsociety-benchmark/` directory
- **Configuration Files**: Use YAML format configuration files to define agent parameters and evaluation settings
- **Result Storage**: Evaluation results are saved in JSON format for easy subsequent analysis and comparison
## Configuration Example
```yaml
# config.yaml
llm:
- api_key: YOUR-API-KEY # LLM API key
model: YOUR-MODEL # LLM model
provider: PROVIDER # LLM provider
semaphore: 200 # Semaphore for LLM requests, control the max number of concurrent requests
env:
db:
enabled: true # Whether to enable database
home_dir: .agentsociety-benchmark/agentsociety_data
```
## Requirements
- Python >= 3.11
- agentsociety >= 1.5.0a11
- Other dependencies see `pyproject.toml`
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
Raw data
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"author_email": "Yuwei Yan <yyan791@connect.hkust-gz.edu.cn>",
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"description": "# AgentSociety Benchmark Toolkit\n\n## Tool Objectives\n\nThe AgentSociety Benchmark Toolkit is a comprehensive evaluation tool designed for multi-agent systems. This tool aims to help researchers and developers:\n\n- **Standardize Evaluation Process**: Provide a unified evaluation framework to ensure fair comparison between different agent systems\n- **Multi-Scenario Testing**: Support agent behavior evaluation in various real-world scenarios\n- **Automated Assessment**: Simplify the entire evaluation workflow from data preparation to result analysis\n- **Reproducibility**: Ensure reproducibility and verifiability of experimental results\n\n## Supported Benchmarks\n\n### 1. BehaviorModeling\nThe BehaviorModeling benchmark focuses on evaluating agents' behavior modeling capabilities in complex social scenarios. This benchmark tests how agents:\n- Understand and simulate human behavior patterns\n- Make reasonable decisions in group environments\n- Adapt to different social norms and constraints\n\n### 2. DailyMobility\nThe DailyMobility benchmark evaluates agents' mobility behavior modeling capabilities in daily life. This benchmark tests how agents:\n- Plan reasonable daily activity routes\n- Consider correlations between time, location, and activities\n- Simulate real-world mobility patterns\n\n### 3. HarricaneMobility\nThe HarricaneMobility benchmark focuses on evaluating agents' behavior modeling capabilities in emergency situations. This benchmark tests how agents:\n- Make emergency decisions during natural disasters\n- Simulate crowd evacuation and shelter-seeking behaviors\n- Handle uncertainty and resource allocation in emergency situations\n\n## Basic Usage\n\n### Installation\n\n```bash\n# Install from source\ngit clone <repository-url>\ncd packages/agentsociety-benchmark\npip install -e .\n\n# Or install via pip (if published)\npip install agentsociety-benchmark\n```\n\n### Command Line Interface\n\n#### View Available Tasks\n\n```bash\n# List all available benchmark tasks\nasbench list-tasks\n```\n\n#### Download Datasets\n- You need to install git lfc firstly.\n```bash\n# Clone datasets for specific benchmarks, this will clone the datasets and install dependancies at the same time\nasbench clone BehaviorModeling\nasbench clone DailyMobility\nasbench clone HarricaneMobility\n\n# View installed benchmarks\nasbench list-installed\n\n# Force clone datasets for specific benchmarks\nasbench clone BehaviorModeling --force\n\n# Only install dependancies for specific benchmarks\nasbench clone BehaviorModeling --only-install-deps\n```\n\n#### Run Evaluation\n\n```bash\n# Run evaluation for specific benchmark\nasbench run <TASK-NAME> --config your_config.yaml --agent your_agent.py --mode test/inference\n```\n\n#### Independent Result Evaluation\n\n```bash\n# Independently evaluate generated result files\nasbench evaluate <TASK-NAME> results.json --config your_config.yaml\n```\n\n#### Update Benchmarks\n\n```bash\n# Update all benchmarks to latest versions\nasbench update-benchmarks\n```\n\n### Programmatic Usage\n\nThe AgentSociety Benchmark also supports programmatic usage through Python code, allowing you to integrate benchmark execution into your applications and scripts.\n\n#### Basic Usage\n\n```python\nimport asyncio\nfrom agentsociety_benchmark import BenchmarkRunner, run_benchmark, evaluate_results\n\nasync def run_my_benchmark():\n # Create a BenchmarkRunner instance\n runner = BenchmarkRunner(home_dir=\"./benchmark_data\")\n \n # Run a benchmark\n result = await runner.run_benchmark(\n task_name=\"BehaviorModeling\",\n benchmark_config=\"config.yaml\",\n agent_config=\"agent_config.yaml\",\n mode=\"test\", # Run with evaluation\n tenant_id=\"my_tenant\",\n exp_id=\"my_experiment_001\"\n )\n \n print(f\"Benchmark completed! Experiment ID: {result['exp_id']}\")\n print(f\"Results: {result['results']}\")\n print(f\"Evaluation: {result['evaluation']}\")\n\n# Run the benchmark\nasyncio.run(run_my_benchmark())\n```\n\n#### Using Convenience Functions\n\n```python\nimport asyncio\nfrom agentsociety_benchmark import run_benchmark, evaluate_results, list_available_tasks\n\nasync def simple_benchmark():\n # List available tasks\n tasks = list_available_tasks()\n print(f\"Available tasks: {tasks}\")\n \n # Run benchmark using convenience function\n result = await run_benchmark(\n task_name=\"BehaviorModeling\",\n benchmark_config=\"config.yaml\",\n agent_config=\"agent_config.yaml\",\n mode=\"inference\" # Run without evaluation\n )\n \n # Evaluate results separately if needed\n if result['results']:\n evaluation = await evaluate_results(\n task_name=\"BehaviorModeling\",\n results_file=\"results.pkl\",\n benchmark_config=\"config.yaml\"\n )\n print(f\"Evaluation result: {evaluation['evaluation_result']}\")\n\nasyncio.run(simple_benchmark())\n```\n\n#### Advanced Usage\n\n```python\nimport asyncio\nfrom agentsociety_benchmark import BenchmarkRunner\n\nasync def advanced_benchmark():\n # Create runner with custom settings\n runner = BenchmarkRunner(home_dir=\"./custom_data\")\n \n # Run with advanced configuration\n result = await runner.run_benchmark(\n task_name=\"BehaviorModeling\",\n benchmark_config=\"my_config.yaml\",\n agent_config=\"my_agent.py\",\n datasets_path=\"./my_datasets\",\n mode=\"test\",\n tenant_id=\"advanced_example\",\n exp_id=\"advanced_001\",\n official=True, # Mark as official validation\n callback_url=\"https://my-callback-url.com/webhook\"\n )\n \n print(f\"Advanced benchmark completed: {result}\")\n\nasyncio.run(advanced_benchmark())\n```\n\n#### Configuration Files\n\nYou'll need to create configuration files for your benchmarks:\n\n**Benchmark Configuration (config.yaml):**\n```yaml\nllm:\n- api_key: YOUR-API-KEY\n model: gpt-4\n provider: openai\n semaphore: 200\nenv:\n db:\n enabled: true\n home_dir: .agentsociety-benchmark/agentsociety_data\n```\n\n**Agent Configuration (agent_config.yaml):**\n```yaml\nagent_class: my_agent.py\nnumber: 1\nconfig:\n name: MyAgent\n description: A custom agent for testing\n```\n\n#### Complete Example\n\nSee `examples/programmatic_usage.py` for a complete working example that demonstrates all the features of the programmatic API.\n\n### Storage and Configuration\n\n- **Data Storage**: All benchmark data is stored in the `.agentsociety-benchmark/` directory\n- **Configuration Files**: Use YAML format configuration files to define agent parameters and evaluation settings\n- **Result Storage**: Evaluation results are saved in JSON format for easy subsequent analysis and comparison\n\n## Configuration Example\n\n```yaml\n# config.yaml\nllm:\n- api_key: YOUR-API-KEY # LLM API key\n model: YOUR-MODEL # LLM model\n provider: PROVIDER # LLM provider\n semaphore: 200 # Semaphore for LLM requests, control the max number of concurrent requests\nenv:\n db:\n enabled: true # Whether to enable database\n home_dir: .agentsociety-benchmark/agentsociety_data\n```\n\n## Requirements\n\n- Python >= 3.11\n- agentsociety >= 1.5.0a11\n- Other dependencies see `pyproject.toml`\n\n## License\n\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.",
"bugtrack_url": null,
"license": "Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. \"License\" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. \"Licensor\" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. \"Legal Entity\" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, \"control\" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. \"You\" (or \"Your\") shall mean an individual or Legal Entity exercising permissions granted by this License. \"Source\" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files. \"Object\" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types. \"Work\" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below). \"Derivative Works\" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof. \"Contribution\" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. For the purposes of this definition, \"submitted\" means any form of electronic, verbal, or written communication sent to the Licensor or its representatives, including but not limited to communication on electronic mailing lists, source code control systems, and issue tracking systems that are managed by, or on behalf of, the Licensor for the purpose of discussing and improving the Work, but excluding communication that is conspicuously marked or otherwise designated in writing by the copyright owner as \"Not a Contribution.\" \"Contributor\" shall mean Licensor and any individual or Legal Entity on behalf of whom a Contribution has been received by Licensor and subsequently incorporated within the Work. 2. Grant of Copyright License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form. 3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed. 4. Redistribution. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions: (a) You must give any other recipients of the Work or Derivative Works a copy of this License; and (b) You must cause any modified files to carry prominent notices stating that You changed the files; and (c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and (d) If the Work includes a \"NOTICE\" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License. You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License. 5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. 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