Prompt Registry examples

This page offers examples for the Prompt Registry operations.

register_prompt()

API reference: mlflow.genai.register_prompt

prompt = mlflow.genai.register_prompt(
    name="mycatalog.myschema.summarization",
    template="""Summarize the following text in {{num_sentences}} sentences:

Text: {{content}}

Focus on: {{focus_areas}}""",
    commit_message="Added focus areas parameter",
    tags={
        "tested_with": "gpt-4",
        "avg_latency_ms": "1200",
        "team": "content",
        "project": "summarization-v2"
    }
)

load_prompt()

API reference: mlflow.genai.load_prompt

The following example loads a specific version using URI format

# Load specific version using URI format
v2 = mlflow.genai.load_prompt(name_or_uri="prompts:/mycatalog.myschema.qa_prompt/2")

# Load specific version using name + version parameter
v3 = mlflow.genai.load_prompt(name_or_uri="mycatalog.myschema.qa_prompt", version=3)

# Load with allow_missing flag (returns None if not found)
optional_prompt = mlflow.genai.load_prompt(
    name_or_uri="mycatalog.myschema.qa_prompt",
    version=3,
    allow_missing=True
)

# Use the prompt
if optional_prompt is not None:
    response = llm.invoke(optional_prompt.format(
        question="What is MLflow?",
        context="MLflow is an open source platform..."
    ))

The following example loads by alias using URI format

# Load by alias using URI
prod = mlflow.genai.load_prompt(name_or_uri="prompts:/mycatalog.myschema.qa_prompt@production")

# Load with allow_missing flag (returns None if not found)
optional_prompt = mlflow.genai.load_prompt(
    name_or_uri="mycatalog.myschema.qa_prompt",
    version=3,
    allow_missing=True
)

# Use the prompt
if optional_prompt is not None:
    response = llm.invoke(optional_prompt.format(
        question="What is MLflow?",
        context="MLflow is an open source platform..."
    ))

search_prompts()

API Reference: mlflow.genai.search_prompts

Unity Catalog Requirements

For Unity Catalog prompt registries, you must specify both catalog and schema:

# REQUIRED format - list all prompts in a catalog.schema
results = mlflow.genai.search_prompts("catalog = 'mycatalog' AND schema = 'myschema'")

# This is the ONLY supported filter format
results = mlflow.genai.search_prompts("catalog = 'rohit' AND schema = 'default'")

Limitations

The following filters are NOT supported in Unity Catalog:

• Name patterns: name LIKE '%pattern%'
• Tag filtering: tags.field = 'value'
• Exact name matching: name = 'specific.name'
• Combined filters beyond catalog + schema

To find specific prompts, use the returned list and filter programmatically:

# Get all prompts in schema
all_prompts = mlflow.genai.search_prompts("catalog = 'mycatalog' AND schema = 'myschema'")

# Filter programmatically
customer_prompts = [p for p in all_prompts if 'customer' in p.name.lower()]
tagged_prompts = [p for p in all_prompts if p.tags.get('team') == 'support']

set_prompt_alias()

API Reference: mlflow.genai.set_prompt_alias

# Promote version 3 to production
mlflow.genai.set_prompt_alias(
    name="mycatalog.myschema.chat_assistant",
    alias="production",
    version=3
)

# Set up staging for testing
mlflow.genai.set_prompt_alias(
    name="mycatalog.myschema.chat_assistant",
    alias="staging",
    version=4
)

delete_prompt() and delete_prompt_version()

delete_prompt_version()

API Reference: MlflowClient.delete_prompt_version

Deletes a specific version of a prompt:

from mlflow import MlflowClient

client = MlflowClient()

# Delete specific versions first (required for Unity Catalog)
client.delete_prompt_version("mycatalog.myschema.chat_assistant", "1")
client.delete_prompt_version("mycatalog.myschema.chat_assistant", "2")
client.delete_prompt_version("mycatalog.myschema.chat_assistant", "3")

# Then delete the entire prompt
client.delete_prompt("mycatalog.myschema.chat_assistant")

# For convenience with Unity Catalog, you can also search and delete all versions:
search_response = client.search_prompt_versions("mycatalog.myschema.chat_assistant")
for version in search_response.prompt_versions:
    client.delete_prompt_version("mycatalog.myschema.chat_assistant", str(version.version))

client.delete_prompt("mycatalog.myschema.chat_assistant")

delete_prompt()

After you delete the prompt version, you can delete the prompt.

API Reference: MlflowClient.delete_prompt

from mlflow import MlflowClient

client = MlflowClient()

# Delete specific versions first (required for Unity Catalog)
client.delete_prompt_version("mycatalog.myschema.chat_assistant", "1")
client.delete_prompt_version("mycatalog.myschema.chat_assistant", "2")
client.delete_prompt_version("mycatalog.myschema.chat_assistant", "3")

# Then delete the entire prompt
client.delete_prompt("mycatalog.myschema.chat_assistant")

# For convenience with Unity Catalog, you can also search and delete all versions:
search_response = client.search_prompt_versions("mycatalog.myschema.chat_assistant")
for version in search_response.prompt_versions:
    client.delete_prompt_version("mycatalog.myschema.chat_assistant", str(version.version))

client.delete_prompt("mycatalog.myschema.chat_assistant")