Python SDK for dataset generation on LightningRod platform ⚡
Project description
Lightning Rod Python SDK
Foresight returns a calibrated probability for any question about the future through an OpenAI-compatible API.
Trusted for high-stakes predictions by Numinous, Shore Capital Partners, Awardable, ERIS Marketplace, and others. Foresight processes billions of tokens and serves 100k+ inference requests every day.
Documentation · Get an API key · Research paper
⚡ Better AI Predictions
Foresight is served behind an OpenAI-compatible endpoint, so any OpenAI client works — just point base_url at Lightning Rod.
from openai import OpenAI
client = OpenAI(
api_key="your-api-key",
base_url="https://api.lightningrod.ai/v1/openai",
)
completion = client.chat.completions.create(
model="foresight-v4",
messages=[
{"role": "user", "content": "Will the Fed cut rates at its next meeting?"},
],
extra_body={"research": True}, # Auto research the most relevant prediction context
)
print(completion.choices[0].message.content)
See the forecasting guides for how to write good forecasting prompts.
Prefer an SDK helper?
lr.predict() wraps the same API and parses the structured answer for you:
pip install lightningrod-ai
import lightningrod as lr
client = lr.LightningRod(api_key="your-api-key")
result = client.predict(
"Will the Fed cut interest rates in 2026?",
answer_type="binary",
research=True,
)
print(result.binary.probability)
🏗️ Train an expert on your domain
Need a model tuned to your domain? Our platform turns raw sources into labeled datasets and fine-tuned models. Read the Future-as-Label paper or view public models and datasets on Hugging Face.
📚 Learn more
- Documentation & API reference — quickstart, guides, recipes, and the REST API reference
- Enterprise examples — forecasting, dataset generation, training, and evaluation
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