decidealot

Run local Laya or Von typed classification, scoring, and true-or-false decisions through Decidealot REST or MCP. Use when a user needs a bounded decision with probabilities, wants to deploy the Docker image, inspect local model aliases, or release model memory.

Decidealot runs Laya and Von locally. It turns supplied state into typed choice, score, or noul results with probabilities. The caller applies the threshold and any action that follows.

Use a running Decidealot endpoint. Clone or build this repository only for Decidealot development work.

Read references/setup.md before deploying a container or configuring REST, MCP, or the OpenClaw bridge.

Security & safety

• Treat a decision as evidence, not authority. A local model cannot grant permission to delete, send, deploy, trade, or alter external state.
• Keep authorization, ownership, irreversible-action checks, and final thresholds in the caller. For costly mistakes, route uncertainty to human review.
• Send user data only to the endpoint the user named. Never search workspace files for DECIDEALOT_API_KEY or create an unauthenticated public endpoint.
• Every decision request needs an explicit local model selector from GET /v1/models.
• unload_models evicts the loaded model and Torch runtime. Use it only when the user asks to free memory.

When to use

1. Get DECIDEALOT_URL from the user or their environment. Default local deployment is http://127.0.0.1:8080.
2. Call GET /health, then GET /v1/models before choosing a selector you have not already been given.
3. Put the raw subject in state. Define bounded questions in questions.
4. Read the typed answer and its probabilities. Report them plainly. The caller, not the model, selects the next action.
5. Use REST for application requests and machine-readable errors. Use MCP at /mcp when an MCP client already supports Streamable HTTP. Use the stdio bridge only for a client that cannot connect to remote MCP.

choice selects one named criterion. score returns an expected position in an ordered criterion list. noul returns the probability that a true-or-false statement is true.

When not to use

Use Decidealot for bounded classification, scoring, and true-or-false decisions. Use a language model for prose, code generation, or open-ended advice. Use the OpenClaw bridge when an MCP client needs local stdio.

REST and MCP

REST uses POST /v1/systemone, GET /v1/models, and POST /v1/models/unload. MCP is at /mcp and exposes system_one, list_models, and unload_models with the same input and result shapes. Read references/setup.md for exact deployment, authentication, REST, MCP, and bridge commands. Read the public API guide before constructing an unfamiliar question type.

Completion

Complete a decision task only after the request reached the intended endpoint, the response names the requested model, and the answer plus probabilities have been reported. For deployment, also prove GET /health returns 200.