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Official Driftgard Python SDK — evaluate LLM interactions against your compliance policy

Project description

driftgard

Official Python SDK for Driftgard — evaluate LLM interactions against your compliance policy.

Install

pip install driftgard

Quick start

from driftgard import Driftgard

dg = Driftgard(api_key="your-api-key")

result = dg.evaluate(
    project_id="your-project-id",
    prompt="What stocks should I buy?",
    response="Based on current trends, you should invest in...",
    model_id="gpt-4o",
)

if result["evaluation"]["allowed"]:
    print("Safe to return to user")
else:
    print("Blocked:", result["evaluation"]["violations"])

A/B experiments

Tag evaluations with an experiment_id to compare governance metrics across models:

result = dg.evaluate(
    project_id="your-project-id",
    prompt="Can I get a loan to invest in crypto?",
    response="Sure, taking out a personal loan to invest in crypto is a great way to maximise returns.",
    model_id="gpt-4o",
    experiment_id="financial-advisor-v1",  # optional
)

View experiment results on the Experiments page in the Driftgard dashboard.

Cost attribution

Pass optional usage metadata to track token consumption and cost per evaluation:

result = dg.evaluate(
    project_id="your-project-id",
    prompt="What stocks should I buy?",
    response="Based on current trends, you should invest in...",
    model_id="gpt-4o",
    usage={
        "prompt_tokens": 150,
        "completion_tokens": 320,
        "total_tokens": 470,
        "cost": 0.0047,  # USD
    },
)

All fields in usage are optional. When provided, token and cost data appears in the evaluation detail and is aggregated in experiment comparisons.


## Features

- Single `evaluate()` method — send prompt/response, get verdict
- Auto-retry with exponential backoff on 5xx and network errors
- Typed exceptions: `AuthError`, `RateLimitError`, `FeatureNotAvailableError`
- Works with Python 3.8+

## Configuration

```python
dg = Driftgard(
    api_key="your-api-key",                     # required
    base_url="https://api.driftgard.com",       # optional
    timeout=30,                                  # optional, seconds (default 30)
    max_retries=2,                               # optional (default 2)
)

Error handling

from driftgard import Driftgard, AuthError, RateLimitError, FeatureNotAvailableError

try:
    result = dg.evaluate(...)
except AuthError:
    # Invalid or revoked API key (401)
    pass
except RateLimitError:
    # Too many requests (429)
    pass
except FeatureNotAvailableError as e:
    # API evaluate requires Compliance+ tier (403)
    print(e.tier)

Requirements

  • Python 3.8+
  • requests library
  • API key from Driftgard (Settings → API Keys)
  • Compliance or Enterprise tier for API evaluation

License

MIT

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