Sync ollama docs from f8dc7c9f on 2026-02-12
This commit is contained in:
The Librarian
@@ -2,6 +2,12 @@
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title: Claude Code
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---
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Claude Code is Anthropic's agentic coding tool that can read, modify, and execute code in your working directory.
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Open models can be used with Claude Code through Ollama's Anthropic-compatible API, enabling you to use models such as `glm-4.7`, `qwen3-coder`, `gpt-oss`.
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## Install
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Install [Claude Code](https://code.claude.com/docs/en/overview):
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@@ -20,50 +26,50 @@ irm https://claude.ai/install.ps1 | iex
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## Usage with Ollama
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### Quick setup
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```shell
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ollama launch claude
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```
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To configure without launching:
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```shell
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ollama launch claude --config
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```
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### Manual setup
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Claude Code connects to Ollama using the Anthropic-compatible API.
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1. Set the environment variables:
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```shell
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export ANTHROPIC_AUTH_TOKEN=ollama
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export ANTHROPIC_API_KEY=""
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export ANTHROPIC_BASE_URL=http://localhost:11434
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export ANTHROPIC_API_KEY=ollama
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```
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2. Run Claude Code with an Ollama model:
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```shell
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claude --model qwen3-coder
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claude --model gpt-oss:20b
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```
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Or run with environment variables inline:
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```shell
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ANTHROPIC_BASE_URL=http://localhost:11434 ANTHROPIC_API_KEY=ollama claude --model qwen3-coder
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ANTHROPIC_AUTH_TOKEN=ollama ANTHROPIC_BASE_URL=http://localhost:11434 ANTHROPIC_API_KEY="" claude --model qwen3-coder
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```
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## Connecting to ollama.com
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1. Create an [API key](https://ollama.com/settings/keys) on ollama.com
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2. Set the environment variables:
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```shell
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export ANTHROPIC_BASE_URL=https://ollama.com
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export ANTHROPIC_API_KEY=<your-api-key>
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```
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3. Run Claude Code with a cloud model:
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```shell
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claude --model glm-4.7:cloud
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```
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**Note:** Claude Code requires a large context window. We recommend at least 64k tokens. See the [context length documentation](/context-length) for how to adjust context length in Ollama.
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## Recommended Models
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### Cloud models
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- `glm-4.7:cloud` - High-performance cloud model
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- `minimax-m2.1:cloud` - Fast cloud model
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- `qwen3-coder:480b` - Large coding model
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- `qwen3-coder`
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- `glm-4.7`
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- `gpt-oss:20b`
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- `gpt-oss:120b`
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Cloud models are also available at [ollama.com/search?c=cloud](https://ollama.com/search?c=cloud).
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### Local models
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- `qwen3-coder` - Excellent for coding tasks
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- `gpt-oss:20b` - Strong general-purpose model
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@@ -13,7 +13,21 @@ npm install -g @openai/codex
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## Usage with Ollama
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<Note>Codex requires a larger context window. It is recommended to use a context window of at least 32K tokens.</Note>
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<Note>Codex requires a larger context window. It is recommended to use a context window of at least 64k tokens.</Note>
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### Quick setup
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```
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ollama launch codex
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```
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To configure without launching:
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```shell
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ollama launch codex --config
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```
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### Manual setup
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To use `codex` with Ollama, use the `--oss` flag:
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@@ -11,10 +11,24 @@ Install the [Droid CLI](https://factory.ai/):
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curl -fsSL https://app.factory.ai/cli | sh
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```
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<Note>Droid requires a larger context window. It is recommended to use a context window of at least 32K tokens. See [Context length](/context-length) for more information.</Note>
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<Note>Droid requires a larger context window. It is recommended to use a context window of at least 64k tokens. See [Context length](/context-length) for more information.</Note>
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## Usage with Ollama
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### Quick setup
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```bash
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ollama launch droid
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```
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To configure without launching:
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```shell
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ollama launch droid --config
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```
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### Manual setup
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Add a local configuration block to `~/.factory/config.json`:
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```json
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@@ -73,4 +87,4 @@ Add the cloud configuration block to `~/.factory/config.json`:
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}
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```
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Run `droid` in a new terminal to load the new settings.
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Run `droid` in a new terminal to load the new settings.
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@@ -0,0 +1,50 @@
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---
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title: Overview
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---
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Ollama integrates with a wide range of tools.
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## Coding Agents
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Coding assistants that can read, modify, and execute code in your projects.
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- [Claude Code](/integrations/claude-code)
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- [Codex](/integrations/codex)
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- [OpenCode](/integrations/opencode)
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- [Droid](/integrations/droid)
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- [Goose](/integrations/goose)
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## Assistants
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AI assistants that help with everyday tasks.
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- [OpenClaw](/integrations/openclaw)
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## IDEs & Editors
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Native integrations for popular development environments.
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- [VS Code](/integrations/vscode)
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- [Cline](/integrations/cline)
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- [Roo Code](/integrations/roo-code)
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- [JetBrains](/integrations/jetbrains)
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- [Xcode](/integrations/xcode)
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- [Zed](/integrations/zed)
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## Chat & RAG
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Chat interfaces and retrieval-augmented generation platforms.
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- [Onyx](/integrations/onyx)
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## Automation
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Workflow automation platforms with AI integration.
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- [n8n](/integrations/n8n)
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## Notebooks
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Interactive computing environments with AI capabilities.
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- [marimo](/integrations/marimo)
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---
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title: marimo
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---
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## Install
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Install [marimo](https://marimo.io). You can use `pip` or `uv` for this. You
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can also use `uv` to create a sandboxed environment for marimo by running:
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```
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uvx marimo edit --sandbox notebook.py
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```
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## Usage with Ollama
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1. In marimo, go to the user settings and go to the AI tab. From here
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you can find and configure Ollama as an AI provider. For local use you
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would typically point the base url to `http://localhost:11434/v1`.
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<div style={{ display: 'flex', justifyContent: 'center' }}>
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<img
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src="/images/marimo-settings.png"
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alt="Ollama settings in marimo"
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width="50%"
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/>
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</div>
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2. Once the AI provider is set up, you can turn on/off specific AI models you'd like to access.
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<div style={{ display: 'flex', justifyContent: 'center' }}>
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<img
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src="/images/marimo-models.png"
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alt="Selecting an Ollama model"
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width="50%"
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/>
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</div>
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3. You can also add a model to the list of available models by scrolling to the bottom and using the UI there.
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<div style={{ display: 'flex', justifyContent: 'center' }}>
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<img
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src="/images/marimo-add-model.png"
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alt="Adding a new Ollama model"
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width="50%"
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/>
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</div>
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4. Once configured, you can now use Ollama for AI chats in marimo.
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<div style={{ display: 'flex', justifyContent: 'center' }}>
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<img
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src="/images/marimo-chat.png"
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alt="Configure code completion"
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width="50%"
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/>
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</div>
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4. Alternatively, you can now use Ollama for **inline code completion** in marimo. This can be configured in the "AI Features" tab.
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<div style={{ display: 'flex', justifyContent: 'center' }}>
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<img
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src="/images/marimo-code-completion.png"
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alt="Configure code completion"
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width="50%"
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/>
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</div>
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## Connecting to ollama.com
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1. Sign in to ollama cloud via `ollama signin`
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2. In the ollama model settings add a model that ollama hosts, like `gpt-oss:120b`.
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3. You can now refer to this model in marimo!
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---
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title: Onyx
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---
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## Overview
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[Onyx](http://onyx.app/) is a self-hostable Chat UI that integrates with all Ollama models. Features include:
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- Creating custom Agents
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- Web search
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- Deep Research
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- RAG over uploaded documents and connected apps
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- Connectors to applications like Google Drive, Email, Slack, etc.
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- MCP and OpenAPI Actions support
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- Image generation
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- User/Groups management, RBAC, SSO, etc.
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Onyx can be deployed for single users or large organizations.
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## Install Onyx
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Deploy Onyx with the [quickstart guide](https://docs.onyx.app/deployment/getting_started/quickstart).
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<Info>
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Resourcing/scaling docs [here](https://docs.onyx.app/deployment/getting_started/resourcing).
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</Info>
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## Usage with Ollama
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1. Login to your Onyx deployment (create an account first).
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<div style={{ display: 'flex', justifyContent: 'center' }}>
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<img
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src="/images/onyx-login.png"
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alt="Onyx Login Page"
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width="75%"
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/>
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</div>
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2. In the set-up process select `Ollama` as the LLM provider.
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<div style={{ display: 'flex', justifyContent: 'center' }}>
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<img
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src="/images/onyx-ollama-llm.png"
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alt="Onyx Set Up Form"
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width="75%"
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/>
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</div>
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3. Provide your **Ollama API URL** and select your models.
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<Note>If you're running Onyx in Docker, to access your computer's local network use `http://host.docker.internal` instead of `http://127.0.0.1`.</Note>
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<div style={{ display: 'flex', justifyContent: 'center' }}>
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<img
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src="/images/onyx-ollama-form.png"
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alt="Selecting Ollama Models"
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width="75%"
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/>
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</div>
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You can also easily connect up Onyx Cloud with the `Ollama Cloud` tab of the setup.
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## Send your first query
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<div style={{ display: 'flex', justifyContent: 'center' }}>
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<img
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src="/images/onyx-query.png"
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alt="Onyx Query Example"
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width="75%"
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/>
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</div>
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@@ -0,0 +1,50 @@
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---
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title: OpenClaw
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---
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OpenClaw is a personal AI assistant that runs on your own devices. It bridges messaging services (WhatsApp, Telegram, Slack, Discord, iMessage, and more) to AI coding agents through a centralized gateway.
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## Install
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Install [OpenClaw](https://openclaw.ai/)
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```bash
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npm install -g openclaw@latest
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```
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Then run the onboarding wizard:
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```bash
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openclaw onboard --install-daemon
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```
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<Note>OpenClaw requires a larger context window. It is recommended to use a context window of at least 64k tokens. See [Context length](/context-length) for more information.</Note>
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## Usage with Ollama
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### Quick setup
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```bash
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ollama launch openclaw
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```
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<Note>Previously known as Clawdbot. `ollama launch clawdbot` still works as an alias.</Note>
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This configures OpenClaw to use Ollama and starts the gateway.
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If the gateway is already running, no changes need to be made as the gateway will auto-reload the changes.
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To configure without launching:
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```shell
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ollama launch openclaw --config
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```
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## Recommended Models
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- `qwen3-coder`
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- `glm-4.7`
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- `gpt-oss:20b`
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- `gpt-oss:120b`
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Cloud models are also available at [ollama.com/search?c=cloud](https://ollama.com/search?c=cloud).
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@@ -0,0 +1,106 @@
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---
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title: OpenCode
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---
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OpenCode is an open-source AI coding assistant that runs in your terminal.
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## Install
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Install the [OpenCode CLI](https://opencode.ai):
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```bash
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curl -fsSL https://opencode.ai/install | bash
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```
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<Note>OpenCode requires a larger context window. It is recommended to use a context window of at least 64k tokens. See [Context length](/context-length) for more information.</Note>
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## Usage with Ollama
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### Quick setup
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```bash
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ollama launch opencode
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```
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To configure without launching:
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```shell
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ollama launch opencode --config
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```
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### Manual setup
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Add a configuration block to `~/.config/opencode/opencode.json`:
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```json
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{
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"$schema": "https://opencode.ai/config.json",
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"provider": {
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"ollama": {
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"npm": "@ai-sdk/openai-compatible",
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"name": "Ollama",
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"options": {
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"baseURL": "http://localhost:11434/v1"
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},
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"models": {
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"qwen3-coder": {
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"name": "qwen3-coder"
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}
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}
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}
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}
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}
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```
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## Cloud Models
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`glm-4.7:cloud` is the recommended model for use with OpenCode.
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Add the cloud configuration to `~/.config/opencode/opencode.json`:
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```json
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{
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"$schema": "https://opencode.ai/config.json",
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"provider": {
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"ollama": {
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"npm": "@ai-sdk/openai-compatible",
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"name": "Ollama",
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"options": {
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"baseURL": "http://localhost:11434/v1"
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},
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"models": {
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"glm-4.7:cloud": {
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"name": "glm-4.7:cloud"
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}
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}
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}
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}
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}
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```
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## Connecting to ollama.com
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1. Create an [API key](https://ollama.com/settings/keys) from ollama.com and export it as `OLLAMA_API_KEY`.
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2. Update `~/.config/opencode/opencode.json` to point to ollama.com:
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```json
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{
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"$schema": "https://opencode.ai/config.json",
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"provider": {
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"ollama": {
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"npm": "@ai-sdk/openai-compatible",
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"name": "Ollama Cloud",
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"options": {
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"baseURL": "https://ollama.com/v1"
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},
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"models": {
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"glm-4.7:cloud": {
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"name": "glm-4.7:cloud"
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}
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}
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}
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}
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}
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```
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Run `opencode` in a new terminal to load the new settings.
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Reference in New Issue
Block a user