Prompt Versioning

Ship prompt changes safely with saved versions, promotion, rollback, and release notes.

PromptRails provides immutable versioning for prompts, similar to agent versioning. Every change to a prompt's template, model assignment, or parameters creates a new version that can be tested independently before being promoted to production.

PromptRails Studio showing the prompt Version Control panel with saved prompt versions — Prompt version history is managed from the same Studio version control rail. Review the current prompt snapshot, saved versions, field-level change counts, restore actions, and comparison controls before promoting a prompt.

How It Works

Each prompt has one or more versions. A version captures:

System prompt text
User prompt template
Primary and fallback LLM model assignments
Temperature, max tokens, and top_p parameters
Input and output schemas
Cache timeout
Configuration object
Version message (release notes)

Exactly one version per prompt is marked as is_current. This is the version used when an agent references the prompt without specifying a particular version.

Technical detailsVersion field reference

Version Fields

Field	Type	Description
`id`	KSUID	Unique version identifier
`prompt_id`	KSUID	Parent prompt ID
`version`	string	Version label (e.g., `v1`, `v2`)
`system_prompt`	string	System instructions for the LLM
`user_prompt`	string	User message template (Jinja2)
`llm_model_id`	KSUID	Primary LLM model
`fallback_llm_model_id`	KSUID	Fallback LLM model
`temperature`	float	Sampling temperature (0.0 - 1.0)
`max_tokens`	integer	Maximum response tokens
`top_p`	float	Nucleus sampling parameter
`input_schema`	JSON	Input validation schema
`output_schema`	JSON	Output structure schema
`cache_timeout`	integer	Response cache TTL in seconds (0 = disabled)
`config`	JSON	Additional configuration
`is_current`	boolean	Whether this is the active version
`message`	string	Version message / release notes
`created_at`	timestamp	Creation timestamp

Creating a Version

Create prompt versions from Studio when you are editing copy, model choice, or schema with teammates. Use SDK calls when prompt versioning is part of a release workflow.

Technical detailsCreate, promote, and roll back prompt versions with SDKs

version = client.prompts.create_version(
    prompt_id="your-prompt-id",
    system_prompt="You are a concise technical writer.",
    user_prompt="Summarize the following text in {{ max_sentences }} sentences:\n\n{{ text }}",
    temperature=0.5,
    max_tokens=256,
    input_schema={
        "type": "object",
        "properties": {
            "text": {"type": "string"},
            "max_sentences": {"type": "integer", "default": 3}
        },
        "required": ["text"]
    },
    message="Reduced temperature for more consistent summaries"
)

Promoting a Version

Promotion sets a version as the current active version. The previously current version is automatically demoted.

client.prompts.promote_version(
    prompt_id="your-prompt-id",
    version_id="version-id-to-promote"
)

After promotion:

All agents referencing this prompt (via their current agent version) will use the newly promoted prompt version
Previous executions retain their original prompt version in the trace for reproducibility

Viewing Version History

versions = client.prompts.list_versions(prompt_id="your-prompt-id")
 
for v in versions["data"]:
    current_marker = " *" if v["is_current"] else ""
    print(f"{v['version']}{current_marker} | {v['message']} | {v['created_at']}")

Rolling Back

Rolling back is simply promoting a previous version:

# Find the version you want to restore
versions = client.prompts.list_versions(prompt_id="your-prompt-id")
target = versions["data"][1]  # previous version
 
# Promote it
client.prompts.promote_version(
    prompt_id="your-prompt-id",
    version_id=target["id"]
)

Since versions are immutable, rollback is instant and safe. The "rolled back from" version remains in history and can be re-promoted later.

Version Messages

Always include a descriptive message when creating a version. This serves as release notes and makes the version history meaningful:

# Good version messages
"Initial prompt for customer support agent"
"Reduced temperature from 0.9 to 0.5 for more consistent output"
"Added fallback model (Claude) for reliability"
"Updated system prompt to handle refund requests"
"Switched to GPT-4o for improved accuracy on complex queries"

Best Practices

One change per version -- Make focused changes so you can isolate the impact of each modification
Test before promoting -- Execute the prompt version directly to verify behavior before making it current
Document changes -- Use version messages to explain what changed and why
Coordinate with agent versions -- When creating a new agent version, explicitly link it to the desired prompt versions to avoid unintended changes
Use cache timeouts -- For deterministic prompts (translation, classification), enable caching to reduce LLM costs and latency