Local classification in OpenClaw with Ollama and Tev1

说明与用途

通过 Ollama 将本地 Tev1 模型集成到 OpenClaw，实现代理本地化结构化决策，无需外部 API。

问题

Integrating local Tev1 models via Ollama into OpenClaw’s Decision provider for structured agent outputs.

结果

The adapter validates answer types, question IDs, distribution keys, labels, numerical ranges and usage counters, limits bodies to 1 MiB, preserves caller cancellation and monotonic deadlines, and accepts only HTTP loopback origins.

工作流

• 1. Clone the openclaw-ollama-decision repo. 2. Run npm test ollama pull tev1:0.8b and npm run smoke to validate the 0.8B model. 3. For the 4B model run ollama pull tev1:4b and npm run smoke -- --model tev1:4b --timeout-ms 120000. 4. Install the plugin via the README instructions. 5. In the target agent’s Decision picker select ollama-decision/tev1:0.8b or ollama-decision/tev1:4b. 6. Keep the chat‑model unchanged. 7. Verify integration with the desired OpenClaw version (e.g., 2026.9.8).

证据

OpenClaw’s developers added native support for a separate Decision model role. Our plugin connects local Tev1 models running in Ollama to that existing infrastructure.

来源

A real captured OpenClaw call with tev1:0.8b returned support, an escalation probability of about 0.8888, and an impact score of about 1.9096 on a zero-based 0–2 rubric.

来源

Requirements: Node.js 22+, an OpenClaw version exposing Decision provider contract v1 and registerDecisionProvider, and local Ollama with /v1/systemone.

来源

The adapter validates answer types, question IDs, distribution keys, labels, numerical ranges and usage counters.

来源