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To use a local large language model in a writing workflow, run it through a local model server and connect a compatible writing app to that server’s API. If your editor cannot connect directly, use an intermediary such as Open WebUI. Before sending real drafts, verify which model and other services will receive your prompts and context.
Choose how your writing app will reach the model
There are two practical routes. A direct connection is simplest when your writing app accepts a custom endpoint and supports the model server’s API format. An intermediary such as Open WebUI is useful when the editor lacks that connection option or when you want a separate browser-based interface.
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| Route | What you need | Setup and troubleshooting | Prompt routing |
|---|---|---|---|
| Direct from the writing app | The app must accept a custom endpoint and support the server’s API format. Check the app’s own documentation for its required base URL, authentication, and request format. | Fewer components, but app-specific setup requirements vary. | Requests go to the configured endpoint; check any other services the app uses separately. |
| Through Open WebUI | A running Open WebUI instance and a reachable local provider, such as Ollama or an OpenAI-compatible server. | Adds an intermediary to configure, but gives you a browser-based interface for connected models. | The selected model determines which configured endpoint receives inference requests. Other configured cloud services may also handle data. |
Open WebUI’s provider setup covers local and cloud models, including Ollama and OpenAI-compatible servers. Its provider connection guide explains the connection flow; its OpenAI-compatible provider guide covers that route. Compatibility with a particular editor is not established by those guides, so confirm the editor’s own API requirements.
Connect the writing workflow
1. Start a local model server
Choose a server and make sure the model you want to use is available to it. Ollama documents a local chat API at http://localhost:11434/api/chat once a model has been downloaded. For local inference, its API documentation says not to include an authorization header. See Ollama’s API introduction.
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2. Make sure the server is reachable
The client—your writing app or Open WebUI—must be able to reach the model server. Open WebUI’s connection guide calls for a running instance, administrator access, and a reachable model server. The examples using localhost apply when the client and server can reach each other at that address. If the model server runs on another machine or in a container, the reachable address depends on that environment; there is no single address that applies to every setup.
3. Configure a direct app connection or Open WebUI
- For a direct connection: In the writing app, use its documented custom-endpoint settings. Enter the local server’s endpoint in the format the app requires, and check its authentication and API-format requirements. Do not assume that accepting an OpenAI-style endpoint means the app supports every server or feature.
- For Open WebUI with Ollama: Configure Ollama as the provider using Open WebUI’s documented connection flow. Open WebUI supports Ollama and OpenAI-compatible servers; use its provider documentation for the applicable setup.
- For Open WebUI with LM Studio: Start the local server in LM Studio’s Developer tab first. Open WebUI lists
http://localhost:1234/v1as the LM Studio connection URL. Follow LM Studio’s local API server documentation and Open WebUI’s OpenAI-compatible provider instructions.
4. Test with a short prompt
Select the intended model and send a simple test message. Open WebUI recommends this check after connecting a provider. A response confirms that this route can pass a prompt and return an answer; it does not prove that every feature in a separate writing app is compatible.
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Check where drafts and context will go
“Local model” describes where that model performs inference, not necessarily where every part of the workflow runs. In Open WebUI, the selected endpoint determines where inference happens: choosing a cloud model sends prompts and included context to that provider. Separately configured cloud tools, extraction services, or embedding services may also receive data even when the main model runs locally. Open WebUI discusses provider routing in its connection guide and related service behavior in its direct connections documentation.
- Check the selected model before submitting a draft, notes, or uploaded context.
- Review separately configured tools and services that may process prompts, files, extraction, or embeddings.
- Do not treat a mixed local-and-cloud setup as fully local unless you have checked every relevant route.
Open WebUI also documents a direct-connections feature that sends inference requests from the browser rather than through its backend. Browser CORS policies can prevent some endpoints from working with this mode; see Open WebUI’s direct connections guide. Open WebUI’s API endpoints documentation describes an OpenAI-compatible chat-completions endpoint for models it exposes, including Ollama models. That can help another workflow component call Open WebUI, but it does not establish compatibility with any particular editor.
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What to check when the connection fails
- The app cannot connect: Confirm the model server is running and reachable from the client, and check that you used the endpoint format required by the app.
- The model is unavailable: Confirm it has been downloaded or otherwise made available to the server, then select the intended model in the client.
- A direct app connection is rejected: Check the app’s documentation for its supported API format, base URL, and authentication behavior. Requirements vary by app.
- Browser-based direct connections fail: CORS restrictions may block the endpoint. Try the provider connection route through Open WebUI’s backend if it fits your setup.
- A test works but a writing feature does not: A successful prompt verifies only the tested path. It does not demonstrate that every editor feature or request type is supported.
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