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EnhancementResult

EnhancementResult is the primary output object returned by ad-enhancement calls. It carries both success and fallback outcomes in a single, consistent shape.

Class purpose​

This class exists to make application handling deterministic:

  • your pipeline always receives a prompt to continue execution;
  • success and failure state are explicit via success and error;
  • conversation metadata is always preserved on the result; and
  • backend response payload is available when present.

Class shape​

from adstractai import Adstract
from adstractai.models import AdRequestConfiguration

client = Adstract(api_key="your-api-key")

result = client.request_ad_or_default(
    prompt="Explain SOC 2 for startups.",
    config=AdRequestConfiguration(
        session_id="sess-100",
        user_agent="Mozilla/5.0 (X11; Linux x86_64)",
        x_forwarded_for="203.0.113.10",
    ),
)

Field reference​

  • prompt

    • Type: str
    • Meaning: Final prompt your application should use in the LLM call.
    • Behavior:
      • Enhanced prompt when ad enhancement succeeds.
      • Original prompt when fallback is used.

  • conversation

    • Type: Conversation
    • Meaning: Resolved conversation context for tracking and reporting continuity.

  • ad_response

    • Type: AdResponse | None
    • Meaning: Parsed backend response when available.
    • Behavior:
      • Can be None in error/fallback scenarios.

  • success

    • Type: bool
    • Meaning: Outcome flag for enhancement operation.
    • Behavior:
      • True when enhancement succeeded.
      • False when fallback path was used.

  • error

    • Type: Exception | None
    • Meaning: Captured failure context.
    • Behavior:
      • Populated when enhancement fails.
      • None on successful enhancement.

Handling pattern​

if result.success:
    prompt_for_model = result.prompt
else:
    print(result.error)
    prompt_for_model = result.prompt

Next steps​