antarraksha-langchain 0.1.4

Antarraksha AI Agent Enforcement SDK for LangChain

antarraksha-langchain

Antarraksha AI Agent Enforcement SDK for LangChain.

Installation

pip install antarraksha-langchain

Quick Start

Attach Antarraksha as a callback handler on your LLM. Registration happens automatically on first use — no login, no API key, no signup required.

from antarraksha_langchain import AntarrakshaCallbackHandler
from langchain_anthropic import ChatAnthropic

handler = AntarrakshaCallbackHandler(agent_id="my-langchain-agent")

llm = ChatAnthropic(model="claude-sonnet-4-5", callbacks=[handler])
print(llm.invoke("Hello").content)

Run your agent normally — every LLM call, tool call, and chain call is now enforced against Antarraksha policy.

Tool Wrapping (optional)

Wrap individual LangChain tools for inline enforcement:

from langchain_community.tools import ShellTool
from antarraksha_langchain import AntarrakshaSafeTool, AntarrakshaClient

client = AntarrakshaClient(agent_id="my-langchain-agent")
client.register()

safe_shell = AntarrakshaSafeTool(wrapped_tool=ShellTool(), antarraksha_client=client)
safe_shell.run("ls")

Parameters

Parameter	Default	Description
agent_id	None	Unique identifier for your agent. Triggers auto-registration on first use.
base_url	"https://antarraksha.ai"	Antarraksha endpoint. Override for self-hosted / dev.
passport_id	None	Optional pre-issued passport ID (e.g. ANTK-PASS-xxx).
sdk_key	None	Optional pre-issued SDK key. If omitted and agent_id is set, the SDK auto-registers and obtains one.
fail_closed	True	If True, deny on enforcement-server unreachable. Set False for fail-open during early integration.
block_on_deny	True	If True, raise PermissionError when Antarraksha returns DENY.

Enforcement Behavior

• on_llm_start fires before every LLM call. DENY raises PermissionError.
• on_tool_start fires before every tool invocation. DENY raises PermissionError.
• on_chain_start fires for every chain run (informational; no enforcement halt).
• Every call is logged and visible at https://antarraksha.ai/registry.

Corporate Network Note

If you're behind a corporate TLS-inspection proxy and see SSLCertVerificationError, install:

pip install pip-system-certs

This makes Python trust your Windows / macOS system certificate store.