veldrixai 1.0.2

Runtime trust infrastructure for AI applications — five-pillar evaluation via a single decorator

VeldrixAI Python SDK

Runtime trust infrastructure for AI applications. Add one decorator to any LLM call — every prompt and response is automatically evaluated across five trust pillars and logged to your VeldrixAI dashboard.

Install

pip install veldrixai

With provider extras:

pip install veldrixai[openai]       # OpenAI SDK support
pip install veldrixai[anthropic]    # Anthropic SDK support
pip install veldrixai[langchain]    # LangChain support
pip install veldrixai[all]          # All providers

Quickstart

from veldrixai import Veldrix
from litellm   import completion

veldrix = Veldrix(api_key="vx-live-...")

@veldrix.guard
def chat(messages):
    return completion(model="openai/gpt-4o", messages=messages)

response = chat([{"role": "user", "content": "Hello"}])
print(response.choices[0].message.content)   # unchanged
print(response.trust.verdict)                # ALLOW
print(response.trust.overall)                # 0.94

What gets evaluated automatically

Pillar	What it checks
Safety	Toxicity, harmful content
Hallucination	Factual accuracy and grounding
Bias & Fairness	Demographic bias, stereotyping
Prompt Security	Jailbreaks, prompt injection
Compliance / PII	GDPR, HIPAA, PII exposure

Every result is logged to your dashboard at https://app.veldrixai.ca automatically.

Works with any LLM framework

• OpenAI SDK, Azure OpenAI
• Anthropic (Claude)
• Google Gemini / Vertex AI
• AWS Bedrock
• Cohere, Mistral, Groq, Together AI, Fireworks AI
• DeepSeek, Qwen, Zhipu AI, Moonshot AI
• LiteLLM, LangChain, LlamaIndex
• Ollama, vLLM, LocalAI
• Any function that returns a string or chat completion object

Sync evaluation (scripts, Jupyter, Django)

trust = veldrix.evaluate_sync(
    prompt="What is the capital of France?",
    response="Paris is the capital of France.",
)
print(trust.verdict, trust.overall)

Async evaluation

trust = await veldrix.evaluate(
    prompt="What is the capital of France?",
    response="Paris is the capital of France.",
)

Block harmful responses automatically

from veldrixai import GuardConfig, VeldrixBlockError

@veldrix.guard(config=GuardConfig(block_on_verdict=["BLOCK"]))
def chat(messages):
    return completion(model="openai/gpt-4o", messages=messages)

try:
    response = chat(messages)
except VeldrixBlockError as e:
    return "I can't help with that."

Async decorator

@veldrix.guard
async def chat(messages):
    return await async_openai_client.chat.completions.create(...)

response = await chat(messages)
print(response.trust.verdict)

Global HTTP intercept (zero code changes)

from veldrixai import Veldrix
from veldrixai.http_interceptor import enable_global_intercept

veldrix = Veldrix(api_key="vx-live-...")
enable_global_intercept(veldrix)

# Use ANY AI SDK as normal — all calls are monitored automatically

FastAPI middleware

from veldrixai.middleware import VeldrixMiddleware

app.add_middleware(VeldrixMiddleware, api_key="vx-live-...")

Flask

from veldrixai.middleware import init_flask

init_flask(app, api_key="vx-live-...")

Requirements

• Python 3.10+
• httpx >= 0.27
• pydantic >= 2.0

Links

• Dashboard: https://app.veldrixai.ca
• Docs: https://docs.veldrixai.ca
• Changelog: CHANGELOG.md
• API Reference: https://docs.veldrixai.ca/api