Python

Two settings change: the base URL and the API key. Everything else in your code stays the same. Each example reads VULNETIX_API_KEY and VULNETIX_ORG_ID from the environment.

The CLI prints the OpenAI, Anthropic, LangChain and LlamaIndex examples with your UUID and an allowed model filled in:

vulnetix ai-firewall snippet --lang python --sdk openai --provider openai
vulnetix ai-firewall snippet --lang python --sdk anthropic
vulnetix ai-firewall snippet --lang python --sdk langchain --output-file llm.py

openai-python 1.x reads OPENAI_BASE_URL, and langchain-openai and LlamaIndex read OPENAI_API_BASE, so vulnetix ai-firewall install shell alone routes them. Setting the base URL in code, as below, keeps the routing explicit.

OpenAI SDK

pip install openai

import os
from openai import OpenAI

client = OpenAI(
    base_url=f"https://guardrails.vulnetix.com/openai/{os.environ['VULNETIX_ORG_ID']}/v1",
    api_key=os.environ["VULNETIX_API_KEY"],  # the Vulnetix key, not an OpenAI key
)

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Hello"}],
)
print(response.choices[0].message.content)

For another chat provider change the slug and the model name, for example /groq/<uuid>/v1 with llama-3.3-70b-versatile, or /openrouter/<uuid>/v1 with openai/gpt-4o-mini. client.responses.create(...) works against openai only.

Streaming:

stream = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Hello"}],
    stream=True,
)
for chunk in stream:
    if chunk.choices and chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

A refusal is a 403, raised as openai.PermissionDeniedError:

import openai

try:
    client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[{"role": "user", "content": "Hello"}],
    )
except openai.PermissionDeniedError as e:
    err = e.response.json().get("error", {})
    print(err.get("code"), err.get("blocked_by"))  # e.g. request_blocked, "No connection strings"
    raise

Anthropic SDK

The base URL stops at the UUID: the SDK adds /v1.

pip install anthropic

import os
from anthropic import Anthropic

client = Anthropic(
    base_url=f"https://guardrails.vulnetix.com/anthropic/{os.environ['VULNETIX_ORG_ID']}",  # no /v1
    auth_token=os.environ["VULNETIX_API_KEY"],
)

message = client.messages.create(
    model="claude-sonnet-4-5",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello"}],
)
print(message.content[0].text)

auth_token sends Authorization: Bearer; api_key sends x-api-key. The gateway accepts both. The CLI snippet uses auth_token.

with client.messages.stream(
    model="claude-sonnet-4-5",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello"}],
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

Refusals raise anthropic.PermissionDeniedError; e.response.json()["error"] carries code, blocked_by and violations.

LangChain

pip install langchain-openai

import os
from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    base_url=f"https://guardrails.vulnetix.com/openai/{os.environ['VULNETIX_ORG_ID']}/v1",
    api_key=os.environ["VULNETIX_API_KEY"],
    model="gpt-4o-mini",
)
print(llm.invoke("Hello").content)

llm.stream("Hello") streams. Refusals surface as openai.PermissionDeniedError from inside the chain. The gateway names this client langchain when its user agent says so.

LlamaIndex

pip install llama-index-llms-openai

import os
from llama_index.core import Settings
from llama_index.llms.openai import OpenAI

llm = OpenAI(
    api_base=f"https://guardrails.vulnetix.com/openai/{os.environ['VULNETIX_ORG_ID']}/v1",
    api_key=os.environ["VULNETIX_API_KEY"],
    model="gpt-4o-mini",
)
Settings.llm = llm  # query engines and agents now use the gateway
print(llm.complete("Hello"))

Pydantic AI

pip install pydantic-ai

import os
from pydantic_ai import Agent
from pydantic_ai.models.openai import OpenAIChatModel
from pydantic_ai.providers.openai import OpenAIProvider

model = OpenAIChatModel(
    "gpt-4o-mini",
    provider=OpenAIProvider(
        base_url=f"https://guardrails.vulnetix.com/openai/{os.environ['VULNETIX_ORG_ID']}/v1",
        api_key=os.environ["VULNETIX_API_KEY"],
    ),
)
agent = Agent(model, system_prompt="Be concise.")
print(agent.run_sync("Hello").output)

A refusal raises pydantic_ai.exceptions.ModelHTTPError with status_code == 403; e.body is the parsed error body when it is JSON.

Codes to handle

code	Meaning
request_blocked	A content guardrail matched. blocked_by names it.
tool_denied, mcp_denied, skill_denied, client_denied	A capability rule refused the request
held_for_review	A capability nobody has reviewed is held
provider_denied, model_denied, model_not_allowed	Provider or model policy
provider_key_missing	No key in the vault for this provider

All codes and statuses: Errors.