Prompt Library

Manage, version, optimize, and deploy prompts independently of your code—enabling instant updates and rollbacks without application redeploys.

Introduction

Prompt Library is the single place to write, store, version, test, and optimize your prompts before deploying them to production. Instead of hard-coding prompt strings into your application, you author them in FastRouter, manage them as versioned records, and reference them by ID in your API calls. When you ship a change, you publish a new version — no code deploy required.

This page covers what Prompt Library does, how it works, and how to call a stored prompt from the API.

Why use it

Prompts change far more often than application code. Keeping them in Prompt Library gives you:

• A versioned history of every prompt, with notes on what changed in each version.

• Safe rollouts — mark exactly one version as Production and have all live requests use it, then roll back instantly by promoting an older version.

• Optional optimization — refine a system prompt with GEPA and save the result as a new version, without overwriting your original.

• Decoupled deployments — update the prompt your app runs without redeploying the app, since requests reference the prompt by ID.

How it works

The lifecycle is: author a prompt in the Prompt Library, optionally optimize it, save changes as a new version, then reference it by ID from your application.

Prompt Library flow: Prompt Library → (optional) Prompt Optimization → New Version → Your App

1. Create version — Write and store a prompt in the Prompt Library.

2. Optimize (optional) — Run GEPA to refine the system prompt.

3. Save optimized prompt — The refined prompt is saved as a new version.

4. Call by ID — Your application references the prompt by its ID in API calls.

Creating a prompt

From Prompts → Prompt Library, click Create Prompt and fill in:

• Prompt Name — A human-readable name (e.g. Health Assistant Prompt).

• Tags — Up to five comma-separated tags for organization (e.g. health).

• Prompt — The system prompt text. Use {{curly braces}} to insert variables that you fill in at call time.

• What changed in this version? — A short changelog note (e.g. Initial draft). This is required and builds your version history.

• Set as "Production" — When checked, this version is used for all live requests that reference the prompt by ID.

New Prompt form with name, tags, prompt body, version note, and Set as Production toggle

Saving creates v1 of the prompt and assigns a permanent prompt ID (e.g. pmpt_3c743f7f9f9e467eae6525f00e6e0650). The ID never changes across versions — it's the stable handle your application uses.

Prompt Details showing v1 as the only version, marked Latest

Versioning

Each prompt keeps an ordered list of versions in the left panel of Prompt Details. Click Add New to create a new version, or generate one through optimization. Every version records its author, timestamp, and change note. The most recent version is tagged Latest; the version you promote is served as Production.

Optimizing a prompt (optional)

Click Optimize on any prompt to run GEPA based Prompt Optimizations against the current version. GEPA refines the system prompt and saves the result as a new version tagged Optimized, leaving your original untouched so you can compare or revert.

Prompt Details showing v2 (Latest, Optimized) alongside v1, with the expanded optimized prompt text

The optimized version is annotated with the optimizer job that produced it (e.g. Optimized via optimizer job opt_094b50e343624dad99d127f4d57b28d7), so you can trace any version back to its source. Use Compare to view the diff between two versions before promoting one to Production.

Compare Prompt Versions showing the differences between two prompt versions

Calling a prompt by ID

Reference a stored prompt by passing its prompt_id to the chat completions endpoint. When you do this without pinning a version, FastRouter serves the version currently marked Production — so promoting a new Production version changes what your app runs, with no code change on your side.

The API Usage tab on the Prompt Details page generates a ready-to-run snippet for the selected prompt:

API Usage tab that shows the configuration to be used in your requests

curl -X POST "https://api.fastrouter.ai/api/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer API-KEY" \
  -d '{
    "model": "openai/gpt-4.1",
    "prompt_id": "pmpt_dde193a153a14fbf9829dd9499bf828b",
    "variables": {},
    "messages": [
      { "role": "user", "content": "hi" }
    ]
  }'

Request parameters

Parameter	Required	Description
model	Yes	The model to route the request to (e.g. openai/gpt-4.1).
prompt_id	Yes	The stored prompt's ID. Resolves to the Production version.
variables	No	Key–value map filling any {{variables}} declared in the prompt. Defaults to {}.
messages	Yes	The conversation turns. The stored prompt is applied as the system prompt; messages carries the user/assistant turns.

Working with variables

If your prompt contains placeholders such as {{patient_age}} or {{topic}}, supply their values in variables:

{
  "model": "openai/gpt-4.1",
  "prompt_id": "pmpt_dde193a153a14fbf9829dd9499bf828b",
  "variables": {
    "topic": "ibuprofen dosing"
  },
  "messages": [
    { "role": "user", "content": "Is this safe with my blood pressure medication?" }
  ]
}

FastRouter substitutes the values into the stored prompt before sending the request to the model. Detected variables for a prompt are listed at the bottom of the Prompt tab.

Promoting and rolling back

To change what production traffic uses, open the target version and set it as Production (or check Set as "Production" when saving a new version). Because your application references the prompt only by prompt_id, the switch takes effect immediately for all live requests, and you can revert by promoting a previous version the same way.