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add SHELL tool

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Ishaan Jaffer 2026-02-12 10:01:02 -08:00
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commit b71cc9cc20
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58
docs/my-website/docs/response_api.md
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@ -1093,6 +1093,64 @@ curl -X POST "http://localhost:4000/v1/responses" \
}'
```
## Shell tool
The **Shell tool** lets the model run commands in a hosted container or local runtime (OpenAI Responses API). You pass `tools=[{"type": "shell", "environment": {...}}]`; the `environment` object configures the runtime (e.g. `type: "container_auto"` for auto-provisioned containers). See [OpenAI Shell tool guide](https://developers.openai.com/api/docs/guides/tools-shell) for full options.
Supported when using the `openai` or `azure` provider with a model that supports the Shell tool.
### Python SDK
```python showLineNumbers title="Shell tool with LiteLLM Python SDK"
import litellm
response = litellm.responses(
model="openai/gpt-4o",
input="List files in /mnt/data and run python --version.",
tools=[{"type": "shell", "environment": {"type": "container_auto"}}],
tool_choice="auto",
max_output_tokens=1024,
)
```
### LiteLLM Proxy (AI Gateway)
Use the OpenAI SDK with your proxy as `base_url`, or call the proxy with curl. The proxy forwards `tools` (including `type: "shell"`) to the provider.
**OpenAI Python SDK (proxy as base_url):**
```python showLineNumbers title="Shell tool via LiteLLM Proxy"
from openai import OpenAI
client = OpenAI(
base_url="http://localhost:4000",
api_key="your-proxy-api-key",
)
response = client.responses.create(
model="openai/gpt-4o",
input="List files in /mnt/data.",
tools=[{"type": "shell", "environment": {"type": "container_auto"}}],
tool_choice="auto",
max_output_tokens=1024,
)
```
**curl:**
```bash title="Shell tool via curl to LiteLLM Proxy"
curl -X POST "http://localhost:4000/v1/responses" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer your-proxy-api-key" \
-d '{
"model": "openai/gpt-4o",
"input": "List files in /mnt/data.",
"tools": [{"type": "shell", "environment": {"type": "container_auto"}}],
"tool_choice": "auto",
"max_output_tokens": 1024
}'
```
## Session Management
LiteLLM Proxy supports session management for all supported models. This allows you to store and fetch conversation history (state) in LiteLLM Proxy.

15
litellm/types/llms/openai.py
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@ -1058,7 +1058,20 @@ class ComputerToolParam(TypedDict, total=False):
type: Required[Union[Literal["computer_use_preview"], str]]
ALL_RESPONSES_API_TOOL_PARAMS = Union[ToolParam, ComputerToolParam]
class ShellToolParam(TypedDict, total=False):
"""
Shell tool for Responses API: run commands in hosted containers or local runtime.
See https://developers.openai.com/api/docs/guides/tools-shell.
"""
type: str
"""The type of tool. Use ``\"shell\"``."""
environment: Dict[str, Any]
"""Environment config: ``type`` (e.g. ``\"container_auto\"``, ``\"container_reference\"``, ``\"local\"``), optional ``container_id``, ``network_policy``, ``domain_secrets``, ``skills``."""
ALL_RESPONSES_API_TOOL_PARAMS = Union[ToolParam, ComputerToolParam, ShellToolParam]
class PromptObject(TypedDict, total=False):