一键导入
一键导入
Self-improving research loops with hypothesis generation, experiment design, and result analysis
Full-stack research and code generation pipeline - research, code, and create
Natural language web UI control — element detection, targeted interaction, and automated form filling
Public opinion analysis and sentiment at scale — sentiment scoring, stance detection, and multi-dimensional bias measurement.
Meta-specialist that auto-discovers and scaffolds new specialists from trending GitHub repos
Multi-agent financial analysis pipeline: fundamental analysis, technical indicators, and news sentiment scoring for any ticker symbol. Wraps patterns from virattt/ai-hedge-fund and ZhuLinsen/daily_stock_analysis.
| name | sandbox |
| display_name | Sandbox Specialist |
| description | Safe multi-language code execution via alibaba/OpenSandbox |
| version | 0.1.0 |
| source_repo | alibaba/OpenSandbox |
| license | Apache-2.0 |
| tier | experimental |
| capabilities | ["execute","code_execution","sandbox","multi_language"] |
| allowed_tools | ["execute_code","validate_code","list_runtimes"] |
| output_formats | ["python_api","cli","mcp_server","agent_skill","rest_api"] |
Wraps alibaba/OpenSandbox to provide isolated, resource-limited execution of arbitrary code snippets inside OSS Agent Lab. Each execution runs in a container-backed sandbox with seccomp syscall filters, memory limits, and configurable timeouts — no persistent side effects leak between runs.
Supported runtimes: Python, JavaScript, TypeScript, Bash, Ruby, Go, Rust, Java, C, C++.
| Tool | Description | Side Effects |
|---|---|---|
execute_code | Execute a code snippet in the sandbox; returns captured output | Subprocess spawn (sandboxed) |
validate_code | Static analysis without execution; returns errors and warnings | None |
list_runtimes | Enumerate all registered runtimes with version and availability | None |
from agents.specialists.sandbox.agent import SandboxSpecialist
from oss_agent_lab.contracts import Intent, Query, SpecialistRequest
specialist = SandboxSpecialist()
request = SpecialistRequest(
intent=Intent(
action="execute",
domain="code",
confidence=0.95,
parameters={"code": "print('hello, sandbox!')", "language": "python"},
),
query=Query(user_input="print('hello, sandbox!')"),
specialist_name="sandbox",
)
result = await specialist.execute(request)
print(result.result["stdout"])
oss-lab run sandbox "print('hello, sandbox!')"
request = SpecialistRequest(
intent=Intent(
action="execute",
domain="code",
confidence=0.95,
parameters={
"code": "console.log('hello from node');",
"language": "javascript",
"timeout": 10,
},
),
query=Query(user_input="console.log('hello from node');"),
specialist_name="sandbox",
)
request = SpecialistRequest(
intent=Intent(
action="validate",
domain="code",
confidence=0.9,
parameters={"code": "import os; os.system('ls')", "language": "python"},
),
query=Query(user_input="import os; os.system('ls')"),
specialist_name="sandbox",
)
result = await specialist.execute(request)
print(result.result["valid"]) # False (warnings present)
print(result.result["warnings"]) # ['os.system() executes shell commands...']
request = SpecialistRequest(
intent=Intent(action="list_runtimes", domain="code", confidence=1.0),
query=Query(user_input=""),
specialist_name="sandbox",
)
result = await specialist.execute(request)
for rt in result.result["runtimes"]:
print(rt["name"], rt["version"], rt["available"])
{
"stdout": "[sandbox:python] Execution started\n[sandbox:python] 1 line(s) processed\n[sandbox:python] Execution complete",
"stderr": "",
"exit_code": 0,
"execution_time_ms": 12.4,
"language": "python",
"execution_id": "3f2504e0-4f89-11d3-9a0c-0305e82c3301"
}
{
"valid": true,
"errors": [],
"warnings": ["eval() executes arbitrary code strings."],
"language": "python"
}
{
"runtimes": [
{"name": "python", "version": "3.12.3", "available": true},
{"name": "javascript", "version": "node 22.2.0", "available": true}
],
"total_count": 12,
"available_count": 10
}
Wraps alibaba/OpenSandbox.