Native answers still need an adapter
JevLLM does not pretend Jev generates a free-form investment report. It calls a contract builder and normalizer, and the caller retains responsibility for abstention.
Inspect the supporting source ↗An educational AI hedge-fund prototype with an optional Jev adapter for structured judgments in fund decision workflows.
Converts strategy questions to System One requests and normalizes native answers to the project’s result format.
Allows Jev or other model backends to be used in the same research workflow.
The author describes an educational research prototype that currently does not execute trades. It is not an official Jev adapter, a zero-hallucination system, or evidence of profitability. This site has not backtested it.
Study how a hedge-fund research workflow can swap a chat provider for native typed decisions.
Material analysed:
JevLLM does not pretend Jev generates a free-form investment report. It calls a contract builder and normalizer, and the caller retains responsibility for abstention.
Inspect the supporting source ↗cache_key hashes the agent, built Jev request and contract version. This avoids identifying an answer only by visible prompt text when question semantics change.
Inspect the supporting source ↗Use it to compare decision backends in a research pipeline, not as evidence that typed output makes a strategy profitable or a trade safe.
Read JevLLM.cache_key and complete together. Check the README's explicit note that the system does not actually make trades against any trading claim.