OpenAI-compatible API
Send forecasting prompts through an API that follows the OpenAI chat.completions style, with a Lightning Rod base URL and a model identifier such as LightningRodLabs/foresight-v4.
Lightning Rod Foresight is a hosted forecasting model API that returns calibrated probability estimates through an OpenAI-compatible interface. It is designed for prediction-market, risk, and event-monitoring workflows.
Lightning Rod Foresight is a hosted forecasting model product that lets users predict events through an OpenAI-compatible API. The homepage positions it as a way to get calibrated probability estimates from AI models built specifically for forecasting rather than general text generation.
The page highlights Foresight v4 and shows a Python example using the OpenAI client, a Lightning Rod API base URL, and a forecasting query about a Federal Reserve rate cut. The product is framed for production workflows where the output of interest is a probability that can be used directly in automated systems or decision support tools.
Send forecasting prompts through an API that follows the OpenAI chat.completions style, with a Lightning Rod base URL and a model identifier such as LightningRodLabs/foresight-v4.
Pass an extra_body research flag to auto-gather relevant context before producing a forecast, which suggests the model can support context-aware prediction workflows.
Request calibrated probabilistic answers through the answer_type option, and receive output that includes a probability value rather than only a narrative response.
Use hosted forecasting models instead of running your own stack, with the product presented as an API service for production workflows.
Apply the same API in forecasting-related systems such as prediction-market bots, agents, risk tools, and event monitors, reducing the need for custom integration patterns.
Build bots that pull live market data, compare contract prices against a calibrated probability, and decide when there is an edge to act on.
Quote both sides of a market around a fair value estimate and re-price as new information arrives.
Add a forecasting tool to an agent so it can predict future events through the same OpenAI-compatible interface used elsewhere in the stack.
Turn news, filings, or other event inputs into probabilities for supply-chain shocks, policy actions, and geopolitics.
Track events on a watchlist and update probabilities as news breaks, using the model as a live event monitor.
Lightning Rod Foresight models are accessed through an OpenAI-compatible API. The page shows a Python example using the OpenAI client with a Lightning Rod base URL and a model named LightningRodLabs/foresight-v4.
The product is designed to return calibrated probabilities for forecasting questions, rather than only free-form text. The page’s example response includes a probability value embedded in the output.
The page highlights forecasting use cases such as prediction-market bots, market making, forecasting agents, risk forecasting, quant signals, and event monitoring.
The source mentions a 'New Foresight v4' release and a comparison between Foresight v3 and v4, but it does not provide setup requirements, team features, or detailed version documentation on the page itself.
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