Skip to main content
Last updated on
Tags:
Options
Open in ChatGPTAsk ChatGPT about this pageOpen in ClaudeAsk Claude about this page

LangChain SDK (Python)

The OpenBox LangChain SDK connects LangChain agents to OpenBox through LangChain's middleware interface. It governs agent lifecycle hooks, model calls, tool calls, and hook-level operational telemetry while keeping your existing agent logic unchanged.

Published package: openbox-langchain-sdk-python

GuideDescription
Integration WalkthroughEnd-to-end guide for wiring create_openbox_langchain_middleware(), tool classification, DID signing, and telemetry into a LangChain agent
ConfigurationEnvironment variables, middleware options, defaults, and production guidance
Error HandlingRuntime errors, approval outcomes, guardrail failures, and startup validation issues
Event ModelUnderstand agent runs, model calls, tool calls, signals, and how LangChain events appear in OpenBox
Approvals and GuardrailsHow verdicts are enforced and how to test live guardrails correctly
TelemetryHTTP, database, file, and traced-function capture behavior
TroubleshootingDiagnose startup, policy, approvals, telemetry, and UI interpretation issues
What the SDK Does

The SDK's job is to connect a LangChain runtime to OpenBox. Trust policy, approvals, guardrails, dashboards, and operator workflows live on the OpenBox platform, not inside the SDK.

Philosophy​

The integration is intentionally minimal:

  • One standard middleware factory with create_openbox_langchain_middleware()
  • No rewrite of existing model, tool, or prompt logic
  • Automatic governance at LangChain middleware boundaries
  • Automatic telemetry capture through the shared OpenBox OpenTelemetry layer

Recommended Entry Point​

For most services, create middleware and pass it to create_agent():

import os

from langchain.agents import create_agent
from openbox_langchain import create_openbox_langchain_middleware

middleware = create_openbox_langchain_middleware(
    api_url=os.environ["OPENBOX_URL"],
    api_key=os.environ["OPENBOX_API_KEY"],
    agent_did=os.environ["OPENBOX_AGENT_DID"],
    agent_private_key=os.environ["OPENBOX_AGENT_PRIVATE_KEY"],
    agent_name="SupportAgent",
)

agent = create_agent(
    model="openai:gpt-4o",
    tools=[search_web, lookup_customer],
    middleware=[middleware],
)

Newly created OpenBox agents require DID signing by default. Configure agent_did and agent_private_key together unless Require signing is disabled for the registered agent, and store the private key as a per-agent secret.

Public API Summary​

Most integrations only need these exports:

  • create_openbox_langchain_middleware()
  • OpenBoxLangChainMiddleware
  • OpenBoxLangChainMiddlewareOptions
  • GovernanceBlockedError
  • GovernanceHaltError
  • ApprovalRejectedError
  • ApprovalExpiredError
  • GuardrailsValidationError
  • traced()

The package re-exports the shared OpenBox LangGraph governance core types so LangChain and LangGraph integrations behave consistently.

What The SDK Captures​

OpenBox receives:

Agent Boundaries​

  • WorkflowStarted
  • WorkflowCompleted
  • SignalReceived(user_prompt)

Model Boundaries​

  • LLMStarted
  • LLMCompleted

Tool Boundaries​

  • ToolStarted
  • ToolCompleted

Operational Telemetry​

  • HTTP requests
  • SQLAlchemy-backed database activity when an engine is configured
  • file operations when captured by the shared telemetry layer
  • custom traced functions

Supported Runtime Conditions​

RequirementValue
Python>=3.11
LangChain>=0.3.0
LangGraph>=0.2.0
OpenBox LangGraph SDK>=0.2.0
OpenBox Corereachable over HTTPS except localhost development

Next Steps​

  1. Start with the Integration Walkthrough.
  2. Configure production behavior in Configuration.
  3. Read Event Model before writing policy or guardrails.