# Continue with a local model: chat and autocomplete roles

Configure Continue in VS Code with a local model and separate chat and autocomplete roles, then verify each editor operation.

Author: Retrivium team
Updated: 2026-11-03
Canonical URL: https://retrivium.ai/journal/continue-local-vscode-chat-completion/
Language: en

To use Continue locally in VS Code, configure the actual local provider and assign the roles you intend to use. Chat and inline completion are separate operations, so prove them separately rather than treating one successful answer as complete editor integration.

## The concrete application boundary

Continue’s configuration names the provider, model, and roles, so the same local runtime can appear under different application jobs. The current reference requires name, version, and schema at the configuration level. Each model definition requires name, provider, and model. The roles array controls which tasks use that definition. In particular, autocomplete is not part of the documented default chat/edit/apply role set. This explains why merely adding a model can enable chat without producing inline completion. Start from the installed extension’s active configuration and reload it after changes. Keep the real runtime model name intact; an arbitrary display label belongs in name, not in model. Do not change name and model together while diagnosing a selector label; they have different responsibilities in the active configuration ([Continue model roles](https://docs.continue.dev/customize/models)) ([Continue config.yaml reference](https://docs.continue.dev/reference)).

## A practical route

Open the active Continue config.yaml and define the model with a unique name, provider: ollama, and the exact model value from the existing runtime. Assign chat and, where suitable, autocomplete in roles. Reload config from the configuration selector. Choose the intended model for chat, then separately check the autocomplete selection and whether inline suggestions are enabled ([Continue with Ollama](https://docs.continue.dev/guides/ollama-guide)).

## A worked example

Use a source file with a short formatting function. In chat, explicitly supply that function and ask for an explanation of its fallback. Then place the cursor inside a new related function and wait for an inline suggestion. Review the suggestion before accepting it. The two observations distinguish conversation context from completion behavior.

| Check | Record |
| --- | --- |
| Configuration | The active YAML file and model provider/name fields used by the extension. |
| Chat role | A selected function receives an explanation through the intended local model. |
| Autocomplete role | An inline suggestion appears for the separately configured completion operation. |

## Reading the failure correctly

An absent autocomplete role is not repaired merely by reconnecting the chat model. A mismatched model name can fail at the runtime, while a configuration edit may have no effect if another configuration remains selected. Check these application conditions before changing generation parameters or downloading additional models.

## What completes the check

Keep a minimal working YAML configuration and the two separate checks. Do not copy deprecated @Codebase or @Docs recipes into the initial setup: current rules, tools, and context workflows should be evaluated against the installed extension documentation.

Related background: [Reproducible inference stacks: preserving a GPU pilot’s result](/journal/software-stack-reproducibility/), [Coding LLMs on 12GB VRAM: Budget Context and Headroom](/journal/coding-llm-12gb-vram/).