sleigh-sdk 0.1.19

Python SDK for Sleigh runtime server.

Sleigh Python SDK

Python SDK for the Sleigh runtime server.

Two client variants are included:

• LangChain Tool variant: one-call as_langchain_tool() (returns StructuredTool)
• MCP variant: expose runtime APIs as MCP tools over stdio

---

1. Install

pip install sleigh-sdk

Optional extras:

pip install "sleigh-sdk[langchain]"
pip install "sleigh-sdk[mcp]"

---

2. Base Python Client

from sleigh_sdk import SleighClient

client = SleighClient(base_url="http://127.0.0.1:10122")
session_token = client.create_session_token()["session_token"]
created = client.create_sandbox(session_token=session_token, image="python:3.11-slim")
sandbox_id = created["sandbox_id"]

---

3. Ordered Workflow (AI Coding)

Run multiple steps in one request and stop early on failure/timeout:

sandbox_id = created["sandbox_id"]
result = client.run_workflow(
    session_token=session_token,
    steps=[
        {"action": "exec_command", "sandbox_id": sandbox_id, "command": "echo hello", "wait": True, "wait_timeout_seconds": 10},
        {"action": "create_snapshot", "sandbox_id": sandbox_id},
        {"action": "exec_command", "sandbox_id": sandbox_id, "command": "uname -a", "wait": True},
    ],
)
print(result["stopped_early"], result["steps"])

Note: in SDK validation, every workflow step must include sandbox_id.

---

3.1 Exec Completion Webhook Subscription

Subscribe a callback for a specific exec task:

sub = client.subscribe_exec_webhook(
    session_token=session_token,
    sandbox_id=sandbox_id,
    exec_id="exec_xxx",
    webhook_url="https://your-domain/webhook/notify/evt_xxx",
)
print(sub)

Server sends a signed POST when exec reaches terminal state.

---

4. Sandbox Read API (AI Coding)

read_result = client.read_sandbox(
    session_token=session_token,
    sandbox_id=sandbox_id,
    command="rg",
    args=["TODO", "/workspace"],
    timeout_seconds=10,
    max_output_bytes=65536,
    max_lines=200,
)
print(read_result)

---

5. Mount + Environment Copy

List available mount workspace directories first:

dirs = client.list_mount_workspaces(session_token=session_token)
print(dirs["items"])

Mount is now server-enforced read-only:

mount_result = client.mount_path(
    session_token=session_token,
    sandbox_id=sandbox_id,
    workspace_path="/project-a",
    container_path="/workspace",
)
print(mount_result)

List available environment directories first:

env_dirs = client.list_environment_workspaces(session_token=session_token)
print(env_dirs["items"])

Copy one allowlisted environment directory into sandbox filesystem (non-mount path, via docker cp):

copy_result = client.copy_environment(
    session_token=session_token,
    sandbox_id=sandbox_id,
    environment_path="/env-a",
    sandbox_path="/app",
)
print(copy_result)

---

6. Code Write API (Sandbox Semantic)

code_write targets:

• POST /sandboxes/{id}/ops/code/write
• validates sandbox auth and targets file inside sandbox filesystem
• sandbox_path is required and must be an absolute file path in sandbox
• service exports target file directory to host temp workspace, applies edit, and syncs back
• quality checks: run pre-commit when config exists; otherwise auto-detect language for fallback checks
• write_mode=context_edit is default for partial edits; pass raw snippets with old_text, new_text, and optional before_context/after_context/occurrence
• write_mode=replace_file is supported for full overwrite by raw source content
• For agent friendliness, LangChain tool also supports explicit actions: code_write_context_edit and code_write_replace_file

result = client.code_write(
    session_token=session_token,
    sandbox_id=sandbox_id,
    sandbox_path="/app/calculator.py",
    write_mode="context_edit",
    before_context="    def multiply(self, a, b):\n        return a * b\n\n",
    old_text="    def multiply(self, a, b):\n        return a * b\n",
    new_text="    def multiply(self, a, b):\n        return a * b\n\n    def sqrt(self, a):\n        if a < 0:\n            raise ValueError('Cannot sqrt negative number!')\n        return a ** 0.5\n",
)

# Full overwrite mode (raw source content)
rewrite_result = client.code_write(
    session_token=session_token,
    sandbox_id=sandbox_id,
    sandbox_path="/app/calculator.py",
    write_mode="replace_file",
    content="print('hello from overwrite mode')\n",
)

---

7. Low-Memory Guard (Create + Expand)

When host available memory ratio:

• < 10%: create/expand is blocked
• >= 10% and < 15%: create requires confirm_low_memory=True; expand proceeds with warning in response reason

created = client.create_sandbox(
    session_token=session_token,
    image="python:3.11-slim",
    confirm_low_memory=True,
    request_timeout_seconds=180,
)

---

8. More Examples

• LangChain integration: ../README_langchain.md
• MCP integration: ../README_mcp.md

9. Session Exec History

list_session_exec_tasks accepts optional session_id. If omitted, SDK uses session_token as session_id automatically:

history = client.list_session_exec_tasks(
    session_token=session_token,
    limit=20,
)
print(history)