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Fetch Prompts via SDK/API

This guide shows you how to fetch prompt configurations from variants or environments using the Agenta SDK.

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Fetching a Prompt Configuration​

You can fetch the configurations from a variant reference (app_slug, variant_slug, variant_version) or an environment reference (app_slug, environment_slug). The default behavior when fetching is to fetch the latest configuration from the production environment. If you don't provide a variant_version parameter but only a variant_slug or an environment_slug, the SDK will fetch the latest version of the variant from the specified environment/variant.

tip

Check the reference section for more details on the data format used for prompts.

Default Behavior when fetching​

If you don't provide either variant or environment identifiers, the SDK fetches the latest configuration deployed to the production environment.

config = ag.ConfigManager.get_from_registry(
    app_slug="my-app-slug",
    variant_slug="my-variant-slug",
    variant_version=2  # Optional: fetches latest if not provided
)

print("Fetched configuration from production:")
print(config)

Example Output:

{
  "prompt": {
    "messages": [
      {
        "role": "system",
        "content": "You are an assistant that provides concise answers"
      },
      {
        "role": "user",
        "content": "Explain {{topic}} in simple terms"
      }
    ],
    "llm_config": {
      "model": "gpt-3.5-turbo",
      "top_p": 1.0,
      "max_tokens": 150,
      "temperature": 0.7,
      "presence_penalty": 0.0,
      "frequency_penalty": 0.0
    },
    "template_format": "curly"
  }
}
tip

Agenta provides a helper class PromptTemplate to format the configuration and then use it to generate the prompt.

from openai import OpenAI
from agenta.sdk.types import PromptTemplate

# Fetch configuration
config = ag.ConfigManager.get_from_registry(
    app_slug="my-app-slug"
)

# Format the prompt with variables
prompt = PromptTemplate(**config['prompt']).format(topic="AI")

# Use with OpenAI
client = OpenAI()
response = client.chat.completions.create(
    **prompt.to_openai_kwargs()
)

print(response.choices[0].message.content)

Fetching by Variant Reference​

# Fetch configuration by variant
config = ag.ConfigManager.get_from_registry(
    app_slug="my-app-slug",
    variant_slug="my-variant-slug",
    variant_version=2  # Optional: If not provided, fetches the latest version
)

print("Fetched configuration:")
print(config)

Fetching by Environment Reference​

# Fetch the latest configuration from the staging environment
config = ag.ConfigManager.get_from_registry(
    app_slug="my-app",
    environment_slug="staging",
    environment_version=1  # Optional: If not provided, fetches the latest version
)

print("Fetched configuration from staging:")
print(config)

Response Format​

The API response contains your prompt configuration under params:

{
  "params": {
    "prompt": {
      "messages": [
        {
          "role": "system",
          "content": "You are an assistant that provides concise answers"
        },
        {
          "role": "user",
          "content": "Explain {{topic}} in simple terms"
        }
      ],
      "llm_config": {
        "model": "gpt-3.5-turbo",
        "max_tokens": 150,
        "temperature": 0.7,
        "top_p": 1.0,
        "frequency_penalty": 0.0,
        "presence_penalty": 0.0
      },
      "template_format": "curly"
    }
  },
  "url": "https://cloud.agenta.ai/services/completion",
  "application_ref": {
    "slug": "my-app-slug",
    "version": null,
    "id": "..."
  },
  "variant_ref": {
    "slug": "my-variant-slug",
    "version": 2,
    "id": "..."
  },
  "environment_ref": {
    "slug": "production",
    "version": 1,
    "id": "..."
  }
}
Asynchronous Operations in Python SDK

All SDK methods have async counterparts with an a prefix:

async def async_operations():
    # Fetch configuration asynchronously
    config = await ag.ConfigManager.aget_from_registry(...)