driftgard

Official Python SDK for DriftGard.

Use it to control what production AI can say and do: evaluate prompts and responses, run OpenAI-compatible gateway calls through DriftGard, validate agent tool calls, and record audit evidence.

Install

pip install driftgard

Requires Python 3.8 or newer.

Quick Start

from driftgard import Driftgard

dg = Driftgard(api_key="dg_...")

result = dg.evaluate(
    project_id="proj_...",
    prompt="What stocks should I buy?",
    response="You should invest everything in...",
    model_id="gpt-4o",
)

if not result["evaluation"]["allowed"]:
    print("Blocked:", result.get("fallback", {}).get("message"))
elif result["evaluation"].get("sanitized"):
    print("Use sanitized response:", result["evaluation"]["sanitized_response"])
else:
    print("Allowed")

Inline Gateway

Use the gateway when DriftGard should sit in the request path, call the provider, enforce policy, and return the final response.

completion = dg.gateway_chat_completions(
    project_id="proj_...",
    model="gpt-4o-mini",
    messages=[
        {"role": "system", "content": "You are a support assistant."},
        {"role": "user", "content": "Summarize the refund process."},
    ],
    driftgard={
        "gateway_mode": "enforce",
        "agent_id": "support-agent",
        "agent_role": "customer_support",
        "session_id": "sess_123",
    },
)

print(completion["choices"][0]["message"]["content"])
print(completion.get("driftgard", {}).get("gateway_decision"))

Streaming is also supported:

stream = dg.stream_gateway_chat_completions(
    project_id="proj_...",
    model="gpt-4o-mini",
    messages=messages,
    driftgard={"gateway_mode": "observe"},
)

Tool Call Validation

Validate agent tool calls against Control Pack tool_rules.

result = dg.evaluate(
    project_id="proj_...",
    eval_mode="tool_call",
    tool_call={
        "tool_name": "transfer_money",
        "parameters": {"amount": 500, "to_account": "acct_123"},
    },
    agent_role="payments_agent",
    model_id="agent-runtime",
)

if not result["evaluation"]["allowed"]:
    raise RuntimeError(result.get("fallback", {}).get("message", "Tool call blocked"))

Local Evaluation

For sensitive environments, the SDK can evaluate locally through DriftGard's WASM evaluator.

dg = Driftgard(
    api_key="dg_...",
    mode="local",
    project_id="proj_...",
)

dg.init()
result = dg.evaluate(prompt=prompt, response=response, model_id="local-model")

Modes:

Mode	Behavior
`remote`	Send prompt/response to DriftGard API
`local`	Evaluate locally; no prompt/response leaves your environment
`local-with-audit`	Evaluate locally and report verdict metadata only

Framework Integrations

Included integrations:

LangChain response guardrail
LangChain tool guard
CrewAI response and tool guardrails
Strands / AWS Agent Core hook
local semantic matching for local mode

Documentation

Requirements

Python 3.8+
DriftGard API key
DriftGard project ID

License

MIT

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