LangChain

pip install faramesh-sdk

from langchain.agents import AgentExecutor, create_openai_tools_agent
from langchain_core.tools import tool

@tool
def lookup_customer(email: str) -> str: ...

@tool
def refund_order(order_id: str, amount: float) -> str: ...

agent = create_openai_tools_agent(model, [lookup_customer, refund_order], prompt)
executor = AgentExecutor(agent=agent, tools=[lookup_customer, refund_order])

from faramesh import GovernedToolSet
from langchain.agents import AgentExecutor, create_openai_tools_agent

governed = GovernedToolSet(
    [lookup_customer, refund_order],
    agent_id="support-bot",
)

agent    = create_openai_tools_agent(model, governed, prompt)
executor = AgentExecutor(agent=agent, tools=governed)

from faramesh import GovernedToolSet

governed = GovernedToolSet([lookup_customer, refund_order], agent_id="support-bot")
chain    = prompt | model.bind_tools(governed) | parser

from faramesh import ToolDeniedException

try:
    response = executor.invoke({"input": "Refund order 42 for $250"})
except ToolDeniedException as denial:
    if denial.code == "POLICY_DEFER":
        store_pending_approval(denial.approval_id)
        return "Refund queued for operator approval."
    raise

import "github.com/faramesh/faramesh-registry/frameworks/langgraph@1.0.0"

agent "support-bot" {
  default deny

  rules {
    permit lookup_customer
    permit refund_order if amount < $100
    defer  refund_order if amount >= $100
  }

  rate_limit "refund_order": 20 per hour

  budget daily {
    max       $1000
    warn_at   0.9
    on_exceed defer
  }
}