Prompt Store

Manage and version system prompts centrally.

How It Works

Prompt Stored

ID: code-reviewer

"You are a {{tone}} reviewer"

API References It

system: quilrai-prompt-store-code-reviewer

vars: {tone: "formal"}

QuilrAI Resolves

"You are a formal reviewer"

Sent to LLM ✓

QuilrAI

1. Create - Store a prompt with a unique ID (e.g., code-reviewer)
2. Reference - Use it as the system message content: quilrai-prompt-store-code-reviewer
3. Gateway Resolves - The gateway resolves the prompt and sends the full text to the LLM

Template Variables

Prompts support {{variable}} placeholders. Pass variable values via the X-Prompt-Variables header.

Prompt template:

You are a {{tone}} code reviewer for {{language}}.

X-Prompt-Variables header:

{"tone": "formal", "language": "Python"}

Resolved prompt sent to LLM:

You are a formal code reviewer for Python.

Enforce System Prompts

Require System From Store locks system prompts to the Prompt Store so application code can't inject ad-hoc system instructions.

Mode	Behavior
Enabled	Every system message must be a Prompt Store reference (e.g. quilrai-prompt-store-<id>, or multiple refs separated by whitespace). Requests with freeform system text, mixed text + ref, or no system message at all are rejected with a 400 error.
Disabled (default)	Both stored and freeform system prompts are accepted.

This applies uniformly across Chat Completions, Anthropic Messages (both the top-level system field and any system-role messages), Vertex/Gemini, and the OpenAI Responses API. Useful when you want prompt changes to go through a review/versioning workflow in the Prompt Store rather than through code deploys.

Code Examples

OpenAI

from openai import OpenAI

client = OpenAI(
    base_url='https://guardrails-usa-2.quilr.ai/openai_compatible/',
    api_key='sk-quilr-xxx'
)

response = client.chat.completions.create(
    model='gpt-4o-mini',
    messages=[
        {'role': 'system', 'content': 'quilrai-prompt-store-code-reviewer'},
        {'role': 'user', 'content': 'Review this code'}
    ],
    extra_headers={
        'X-Prompt-Variables': '{"quilrai-prompt-store-code-reviewer": {"tone": "formal", "language": "Python"}}'
    }
)

Anthropic

import anthropic

client = anthropic.Anthropic(
    base_url='https://guardrails-usa-2.quilr.ai/anthropic_messages/',
    api_key='sk-quilr-xxx'
)

message = client.messages.create(
    model='claude-sonnet-4-20250514',
    max_tokens=1024,
    system='quilrai-prompt-store-code-reviewer',
    messages=[
        {'role': 'user', 'content': 'Review this code'}
    ],
    extra_headers={
        'X-Prompt-Variables': '{"quilrai-prompt-store-code-reviewer": {"tone": "formal", "language": "Python"}}'
    }
)