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-0.0.9.tar.gz (10.8 kB view details)

Uploaded Source

Built Distribution

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

adstractai-0.0.9-py3-none-any.whl (10.1 kB view details)

Uploaded Python 3

File details

Details for the file adstractai-0.0.9.tar.gz.

File metadata

  • Download URL: adstractai-0.0.9.tar.gz
  • Upload date:
  • Size: 10.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for adstractai-0.0.9.tar.gz
Algorithm Hash digest
SHA256 abb87b9450402844af5d8215f8f17cc8f0f49c3758165b5f3f28d6b2da3644f7
MD5 a436241b458045eeef1b411628ec3737
BLAKE2b-256 a938fb0b54046673dd42730d38d944db1aec54e404d2cb18febe982981634a37

See more details on using hashes here.

Provenance

The following attestation bundles were made for adstractai-0.0.9.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-0.0.9-py3-none-any.whl.

File metadata

  • Download URL: adstractai-0.0.9-py3-none-any.whl
  • Upload date:
  • Size: 10.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for adstractai-0.0.9-py3-none-any.whl
Algorithm Hash digest
SHA256 9c910e456bf8b66b2bdb84d77fbeebec14f9ea0c8d755a866d77c1f80323af58
MD5 40be87fd19adaa3830e6cfb0a33d239a
BLAKE2b-256 430cd4b7ae07296d4925dcd3ed0756728e5086c48a2d60a0b787d8e0191dd816

See more details on using hashes here.

Provenance

The following attestation bundles were made for adstractai-0.0.9-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