Skip to main content

Ad network that delivers ads to the LLM's response

Project description

Adstract AI Python SDK

CI PyPI

Ad network SDK that enhances LLM prompts with integrated advertisements.

Install

python -m pip install adstractai

Quickstart

from adstractai import Adstract

client = Adstract(api_key="sk_test_1234567890")

enhanced_prompt = client.request_ad_enhancement(
    prompt="How do I improve analytics in my LLM app?",
    conversation={
        "conversation_id": "conv-1",
        "session_id": "sess-1",
        "message_id": "msg-1",
    },
    user_agent=(
        "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 "
        "(KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
    ),
    x_forwarded_for="192.168.1.1",
)

print(enhanced_prompt)  # Enhanced prompt with integrated ads
client.close()

Authentication

Pass an API key when initializing the client or set ADSTRACT_API_KEY.

export ADSTRACT_API_KEY="sk_test_1234567890"
from adstractai import Adstract

client = Adstract()

Required Parameters

All ad enhancement methods require both user_agent and x_forwarded_for parameters. Missing either parameter will raise a MissingParameterError:

from adstractai import Adstract
from adstractai.errors import MissingParameterError

client = Adstract(api_key="sk_test_1234567890")

try:
    # This will raise MissingParameterError
    client.request_ad_enhancement(
        prompt="Test prompt",
        conversation={"conversation_id": "c", "session_id": "s", "message_id": "m"},
        user_agent="",  # Empty user_agent
        x_forwarded_for="192.168.1.1",
    )
except MissingParameterError as e:
    print(f"Error: {e}")

Available Methods

  • request_ad_enhancement() - Returns enhanced prompt, raises exception on failure
  • request_ad_enhancement_or_default() - Returns enhanced prompt or original prompt on failure
  • request_ad_enhancement_async() - Async version that returns enhanced prompt
  • request_ad_enhancement_or_default_async() - Async version with fallback behavior

Advanced usage

from adstractai import Adstract

client = Adstract(api_key="sk_test_1234567890", retries=2)

enhanced_prompt = client.request_ad_enhancement(
    prompt="Need performance tips",
    conversation={
        "conversation_id": "conv-42",
        "session_id": "sess-42",
        "message_id": "msg-42",
    },
    user_agent=(
        "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 "
        "(KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
    ),
    x_forwarded_for="203.0.113.1",
    constraints={
        "max_ads": 2,
        "safe_mode": "standard",
    },
)

# For fallback behavior that returns original prompt on failure
safe_prompt = client.request_ad_enhancement_or_default(
    prompt="Need performance tips",
    conversation={
        "conversation_id": "conv-42",
        "session_id": "sess-42", 
        "message_id": "msg-42",
    },
    user_agent=(
        "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 "
        "(KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
    ),
    x_forwarded_for="203.0.113.1",
)

print(enhanced_prompt)
client.close()

Async usage

import asyncio

from adstractai import Adstract


async def main() -> None:
    client = Adstract(api_key="sk_test_1234567890")
    
    enhanced_prompt = await client.request_ad_enhancement_async(
        prompt="Need performance tips",
        conversation={
            "conversation_id": "conv-99",
            "session_id": "sess-99",
            "message_id": "msg-99",
        },
        user_agent=(
            "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 "
            "(KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
        ),
        x_forwarded_for="192.0.2.1",
    )
    
    # For fallback behavior in async
    safe_prompt = await client.request_ad_enhancement_or_default_async(
        prompt="Need performance tips",
        conversation={
            "conversation_id": "conv-99",
            "session_id": "sess-99",
            "message_id": "msg-99",
        },
        user_agent=(
            "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 "
            "(KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
        ),
        x_forwarded_for="192.0.2.1",
    )
    
    print(enhanced_prompt)
    await client.aclose()


asyncio.run(main())

Development setup

python -m venv .venv
source .venv/bin/activate
python -m pip install -e ".[dev]"
pre-commit install

Scripts

ruff format .
ruff check .
pyright
pytest
python -m build

Release

  1. Bump the version in pyproject.toml.
  2. Update CHANGELOG.md.
  3. Commit the changes.
  4. Tag the release: git tag vX.Y.Z.
  5. Push commits and tags: git push && git push --tags.

Publishing to PyPI happens automatically via GitHub Actions using trusted publishing.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

adstractai-0.0.10.tar.gz (22.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

adstractai-0.0.10-py3-none-any.whl (20.3 kB view details)

Uploaded Python 3

File details

Details for the file adstractai-0.0.10.tar.gz.

File metadata

  • Download URL: adstractai-0.0.10.tar.gz
  • Upload date:
  • Size: 22.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for adstractai-0.0.10.tar.gz
Algorithm Hash digest
SHA256 fa2f3a121cee0f1e6ba3c028437eab14c3fe6a539b191cb2e20e6423f0e2c787
MD5 ae8626df4631e1eb3516da9cb0a755cd
BLAKE2b-256 bc6fabcf761a27a4bfce75fc25e8e9910652fd438ed00a6a98cc8a23725d301b

See more details on using hashes here.

Provenance

The following attestation bundles were made for adstractai-0.0.10.tar.gz:

Publisher: publish.yml on Adstract-AI/adstract-library

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file adstractai-0.0.10-py3-none-any.whl.

File metadata

  • Download URL: adstractai-0.0.10-py3-none-any.whl
  • Upload date:
  • Size: 20.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for adstractai-0.0.10-py3-none-any.whl
Algorithm Hash digest
SHA256 cbf04f4c94af7d94b36fa37e4e841793356a1322a5c19754aec7bdbd9417f33b
MD5 7fe0e6d23e627c9af77de48bb7d37104
BLAKE2b-256 f76e65b43e070c106c12f80e8c3152ceb719acc23d945ff1c4b9febf447fd603

See more details on using hashes here.

Provenance

The following attestation bundles were made for adstractai-0.0.10-py3-none-any.whl:

Publisher: publish.yml on Adstract-AI/adstract-library

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page