This guide connects a new LLM provider to Harness.
## Overview
An LLM adapter extends `LlmAdapter` and implements `stream()`, translating Harness's provider-neutral request into a provider API call and translating the response back into Harness chunks.
`stream()` receives the exported `GenerateOptions` type. It includes the model, adapter-owned reasoning-effort id, conversation history, system prompt, tool schemas, generation parameters, stop sequences, and abort signal; treat the TypeScript type exported by `@deepseek-ai/dsh-llm` as authoritative. Map supported fields to the provider API. If the provider cannot honor a field, throw `LlmError` with a stable code instead of silently dropping it.
Override `resolveModel(provider, model, signal?)` to return exact provider/model identity plus optional `context` and `reasoning` metadata in one lookup. Reasoning metadata contains ordered opaque ids and display names plus an optional configured default; preserve the adapter's authoritative selectable list, including `off` when its upstream capability API returns it, instead of promoting those values into a core enum. Honor the optional signal for asynchronous lookup so cancellation and disposal reach quiescence. The service validates the aggregate and rejects unsupported explicit efforts before `stream()`; omitting `reasoning` means that model has no selectable reasoning-effort capability.
The first argument lists the model names handled by the adapter. If `cordis.yml` selects `model: model-name-1`, the service routes that request to this adapter.
Adapters throw transport and protocol failures as `LlmError` values with stable codes. The agent loop preserves the error and code for diagnostics and policy; it does not convert an ordinary `Error` automatically. Every provider HTTP request must also merge `attributionHeaders()` and forward `options.signal`.