ollama source for Momentry Core verification

2026-05-22 17:19:10 +08:00
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--- a/docs/integrations/claude-code.mdx
+++ b/docs/integrations/claude-code.mdx
@@ -0,0 +1,136 @@
+---
+title: Claude Code
+---
+
+Claude Code is Anthropic's agentic coding tool that can read, modify, and execute code in your working directory. 
+
+Open models can be used with Claude Code through Ollama's Anthropic-compatible API, enabling you to use models such as `qwen3.5`, `glm-5:cloud`, `kimi-k2.5:cloud`.
+
+![Claude Code with Ollama](https://files.ollama.com/claude-code.png)
+
+## Install
+
+Install [Claude Code](https://code.claude.com/docs/en/overview):
+
+<CodeGroup>
+
+```shell macOS / Linux
+curl -fsSL https://claude.ai/install.sh | bash
+```
+
+```powershell Windows
+irm https://claude.ai/install.ps1 | iex
+```
+
+</CodeGroup>
+
+## Usage with Ollama
+
+### Quick setup
+
+```shell
+ollama launch claude
+```
+
+### Run directly with a model
+```shell
+ollama launch claude --model kimi-k2.5:cloud
+```
+
+## Recommended Models
+
+- `kimi-k2.5:cloud`
+- `glm-5:cloud`
+- `minimax-m2.7:cloud`
+- `qwen3.5:cloud`
+- `glm-4.7-flash`
+- `qwen3.5`
+
+Cloud models are also available at [ollama.com/search?c=cloud](https://ollama.com/search?c=cloud).
+
+## Non-interactive (headless) mode
+
+Run Claude Code without interaction for use in Docker, CI/CD, or scripts:
+
+```shell
+ollama launch claude --model kimi-k2.5:cloud --yes -- -p "how does this repository work?"
+```
+
+The `--yes` flag auto-pulls the model, skips selectors, and requires `--model` to be specified. Arguments after `--` are passed directly to Claude Code.
+
+## Web search
+
+Claude Code can search the web through Ollama's web search API. See the [web search documentation](/capabilities/web-search) for setup and usage.
+
+## Scheduled Tasks with `/loop`
+
+The `/loop` command runs a prompt or slash command on a recurring schedule inside Claude Code. This is useful for automating repetitive tasks like checking PRs, running research, or setting reminders.
+
+```
+/loop <interval> <prompt or /command>
+```
+
+### Examples
+
+**Check in on your PRs**
+
+```
+/loop 30m Check my open PRs and summarize their status
+```
+
+**Automate research tasks**
+
+```
+/loop 1h Research the latest AI news and summarize key developments
+```
+
+**Automate bug reporting and triaging**
+
+```
+/loop 15m Check for new GitHub issues and triage by priority
+```
+
+**Set reminders**
+
+```
+/loop 1h Remind me to review the deploy status
+```
+
+## Telegram
+
+Chat with Claude Code from Telegram by connecting a bot to your session. Install the [Telegram plugin](https://github.com/anthropics/claude-plugins-official), create a bot via [@BotFather](https://t.me/BotFather), then launch with the channel flag:
+
+```shell
+ollama launch claude -- --channels plugin:telegram@claude-plugins-official
+```
+
+Claude Code will prompt for permission on most actions. To allow the bot to work autonomously, configure [permission rules](https://code.claude.com/docs/en/permissions) or pass `--dangerously-skip-permissions` in isolated environments.
+
+See the [plugin README](https://github.com/anthropics/claude-plugins-official/tree/main/external_plugins/telegram) for full setup instructions including pairing and access control.
+
+## Manual setup
+
+Claude Code connects to Ollama using the Anthropic-compatible API.
+
+1. Set the environment variables:
+
+```shell
+export ANTHROPIC_AUTH_TOKEN=ollama
+export ANTHROPIC_API_KEY=""
+export ANTHROPIC_BASE_URL=http://localhost:11434
+```
+
+2. Run Claude Code with an Ollama model:
+
+```shell
+claude --model qwen3.5
+```
+
+Or run with environment variables inline:
+
+```shell
+ANTHROPIC_AUTH_TOKEN=ollama ANTHROPIC_BASE_URL=http://localhost:11434 ANTHROPIC_API_KEY="" claude --model glm-5:cloud
+```
+
+**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.
+
--- a/docs/integrations/claude-desktop.mdx
+++ b/docs/integrations/claude-desktop.mdx
@@ -0,0 +1,13 @@
+---
+title: Claude Desktop
+---
+
+Claude Desktop is no longer supported by `ollama launch`.
+
+Existing installations can be restored to the usual Claude profile:
+
+```shell
+ollama launch claude-desktop --restore
+```
+
+Use [Claude Code](/integrations/claude-code) for Anthropic-compatible coding workflows with Ollama.
--- a/docs/integrations/cline.mdx
+++ b/docs/integrations/cline.mdx
@@ -0,0 +1,38 @@
+---
+title: Cline
+---
+
+## Install
+
+Install [Cline](https://docs.cline.bot/getting-started/installing-cline) in your IDE.
+
+
+## Usage with Ollama
+
+1. Open Cline settings > `API Configuration` and set `API Provider` to `Ollama`
+2. Select a model under `Model` or type one (e.g. `qwen3`)
+3. Update the context window to at least 32K tokens under `Context Window`
+
+<Note>Coding tools require 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>
+
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/cline-settings.png" 
+    alt="Cline settings configuration showing API Provider set to Ollama"
+    width="50%"
+  />
+</div>
+
+
+    
+## Connecting to ollama.com
+1. Create an [API key](https://ollama.com/settings/keys) from ollama.com
+2. Click on `Use custom base URL` and set it to `https://ollama.com`
+3. Enter your **Ollama API Key**
+4. Select a model from the list
+
+
+### Recommended Models
+
+- `qwen3-coder:480b` 
+- `deepseek-v3.1:671b`
--- a/docs/integrations/codex-app.mdx
+++ b/docs/integrations/codex-app.mdx
@@ -0,0 +1,82 @@
+---
+title: Codex App
+---
+
+Codex App is OpenAI's desktop coding agent for macOS and Windows. Ollama configures the app to use Ollama's OpenAI-compatible endpoint, so Codex can work with local models and Ollama Cloud models in the desktop app.
+
+<img
+  src="/images/codex-app-home.png"
+  alt="Codex App with Ollama selected"
+  style={{ borderRadius: "12px" }}
+/>
+
+## Install
+
+Install the [Codex App](https://developers.openai.com/codex/quickstart/) for macOS or Windows.
+
+<Note>Codex App support is available in Ollama v0.24.0 and newer.</Note>
+
+
+## Quick setup
+
+```shell
+ollama launch codex-app
+```
+
+Once Codex App opens, start a task or open a repository as usual.
+
+## Built-in browser
+
+Codex App can open local servers and sites in its built-in browser. Annotate directly on the page to request changes.
+
+<img
+  src="/images/codex-app-annotate.png"
+  alt="Codex App browser annotations"
+  style={{ borderRadius: "12px" }}
+/>
+
+## Review mode
+
+Use review mode to inspect code changes, leave comments, and iterate on fixes without leaving the app.
+
+<img
+  src="/images/codex-app-review.png"
+  alt="Codex App review comments"
+  style={{ borderRadius: "12px" }}
+/>
+
+### Run directly with a model
+
+```shell
+ollama launch codex-app --model kimi-k2.6:cloud
+```
+
+Use a local model by passing its model name:
+
+```shell
+ollama launch codex-app --model gemma4:31b
+```
+
+Running `ollama launch codex-app` is persistent and will have your model selected next time you open Codex.
+
+
+### Restore Codex App
+
+To switch Codex App back to the profile you were using before `ollama launch codex-app`, run:
+
+```shell
+ollama launch codex-app --restore
+```
+
+Ollama restores Codex App's settings and configs. If Codex App is open, Ollama asks before restarting it.
+
+
+The Codex CLI profile managed by `ollama launch codex` is left separate from the Codex App profile.
+
+Before overwriting Codex App config files, Ollama Launch saves backups under `~/.ollama/backup/codex-app/`. On Windows, `~` resolves to your user profile directory.
+
+## Troubleshooting
+
+If Codex App does not open after setup, open Codex manually once and run `ollama launch codex-app` again.
+
+If Codex App is already running and does not switch models, allow Ollama to restart it when prompted, or quit Codex App and run `ollama launch codex-app` again.
--- a/docs/integrations/codex.mdx
+++ b/docs/integrations/codex.mdx
@@ -0,0 +1,76 @@
+---
+title: Codex CLI
+---
+
+
+## Install
+
+Install the [Codex CLI](https://developers.openai.com/codex/cli/). For the desktop app, see [Codex App](/integrations/codex-app).
+
+```
+npm install -g @openai/codex
+```
+
+## Usage with Ollama
+
+<Note>Codex requires a larger context window. It is recommended to use a context window of at least 64k tokens.</Note>
+
+### Quick setup
+
+```
+ollama launch codex
+```
+
+When launched through `ollama launch codex`, Ollama refreshes the model catalog
+and passes it to Codex for that session.
+
+To configure without launching:
+
+```shell
+ollama launch codex --config
+```
+
+### Manual setup
+
+To use `codex` with Ollama, use the `--oss` flag:
+
+```
+codex --oss
+```
+
+To use a specific model, pass the `-m` flag:
+
+```
+codex --oss -m gpt-oss:120b
+```
+
+To use a cloud model:
+
+```
+codex --oss -m gpt-oss:120b-cloud
+```
+
+### Profile-based setup
+
+For a persistent configuration, add an Ollama provider and profiles to `~/.codex/config.toml`:
+
+```toml
+[model_providers.ollama-launch]
+name = "Ollama"
+base_url = "http://localhost:11434/v1"
+
+[profiles.ollama-launch]
+model = "gpt-oss:120b"
+model_provider = "ollama-launch"
+
+[profiles.ollama-cloud]
+model = "gpt-oss:120b-cloud"
+model_provider = "ollama-launch"
+```
+
+Then run:
+
+```
+codex --profile ollama-launch
+codex --profile ollama-cloud
+```
--- a/docs/integrations/copilot-cli.mdx
+++ b/docs/integrations/copilot-cli.mdx
@@ -0,0 +1,93 @@
+---
+title: Copilot CLI
+---
+
+GitHub Copilot CLI is GitHub's AI coding agent for the terminal. It can understand your codebase, make edits, run commands, and help you build software faster.
+
+Open models can be used with Copilot CLI through Ollama, enabling you to use models such as `qwen3.5`, `glm-5.1:cloud`, `kimi-k2.5:cloud`.
+
+## Install
+
+Install [Copilot CLI](https://github.com/features/copilot/cli/):
+
+<CodeGroup>
+
+```shell macOS / Linux (Homebrew)
+brew install copilot-cli
+```
+
+```shell npm (all platforms)
+npm install -g @github/copilot
+```
+
+```shell macOS / Linux (script)
+curl -fsSL https://gh.io/copilot-install | bash
+```
+
+```powershell Windows (WinGet)
+winget install GitHub.Copilot
+```
+
+</CodeGroup>
+
+## Usage with Ollama
+
+### Quick setup
+
+```shell
+ollama launch copilot
+```
+
+### Run directly with a model
+
+```shell
+ollama launch copilot --model kimi-k2.5:cloud
+```
+
+## Recommended Models
+
+- `kimi-k2.5:cloud`
+- `glm-5:cloud`
+- `minimax-m2.7:cloud`
+- `qwen3.5:cloud`
+- `glm-4.7-flash`
+- `qwen3.5`
+
+Cloud models are also available at [ollama.com/search?c=cloud](https://ollama.com/search?c=cloud).
+
+## Non-interactive (headless) mode
+
+Run Copilot CLI without interaction for use in Docker, CI/CD, or scripts:
+
+```shell
+ollama launch copilot --model kimi-k2.5:cloud --yes -- -p "how does this repository work?"
+```
+
+The `--yes` flag auto-pulls the model, skips selectors, and requires `--model` to be specified. Arguments after `--` are passed directly to Copilot CLI.
+
+## Manual setup
+
+Copilot CLI connects to Ollama using the OpenAI-compatible API via environment variables.
+
+1. Set the environment variables:
+
+```shell
+export COPILOT_PROVIDER_BASE_URL=http://localhost:11434/v1
+export COPILOT_PROVIDER_API_KEY=
+export COPILOT_PROVIDER_WIRE_API=responses
+export COPILOT_MODEL=qwen3.5
+```
+
+1. Run Copilot CLI:
+
+```shell
+copilot
+```
+
+Or run with environment variables inline:
+
+```shell
+COPILOT_PROVIDER_BASE_URL=http://localhost:11434/v1 COPILOT_PROVIDER_API_KEY= COPILOT_PROVIDER_WIRE_API=responses COPILOT_MODEL=glm-5:cloud copilot
+```
+
+**Note:** Copilot 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.
--- a/docs/integrations/droid.mdx
+++ b/docs/integrations/droid.mdx
@@ -0,0 +1,90 @@
+---
+title: Droid
+---
+
+
+## Install
+
+Install the [Droid CLI](https://factory.ai/):
+
+```bash
+curl -fsSL https://app.factory.ai/cli | sh
+```
+
+<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>
+
+## Usage with Ollama
+
+### Quick setup
+
+```bash
+ollama launch droid
+```
+
+To configure without launching:
+
+```shell
+ollama launch droid --config
+```
+
+### Manual setup
+
+Add a local configuration block to `~/.factory/config.json`:
+
+```json
+{
+  "custom_models": [
+    {
+      "model_display_name": "qwen3-coder [Ollama]",
+      "model": "qwen3-coder",
+      "base_url": "http://localhost:11434/v1/",
+      "api_key": "not-needed",
+      "provider": "generic-chat-completion-api",
+      "max_tokens": 32000 
+    }
+  ]
+}
+```
+
+
+## Cloud Models
+`qwen3-coder:480b-cloud` is the recommended model for use with Droid.
+
+Add the cloud configuration block to `~/.factory/config.json`:
+
+```json
+{
+  "custom_models": [
+    {
+      "model_display_name": "qwen3-coder [Ollama Cloud]",
+      "model": "qwen3-coder:480b-cloud",
+      "base_url": "http://localhost:11434/v1/",
+      "api_key": "not-needed",
+      "provider": "generic-chat-completion-api",
+      "max_tokens": 128000
+    }
+  ]
+}
+```
+
+## Connecting to ollama.com
+
+1. Create an [API key](https://ollama.com/settings/keys) from ollama.com and export it as `OLLAMA_API_KEY`.
+2. Add the cloud configuration block to `~/.factory/config.json`:
+
+   ```json
+   {
+     "custom_models": [
+       {
+         "model_display_name": "qwen3-coder [Ollama Cloud]",
+         "model": "qwen3-coder:480b",
+         "base_url": "https://ollama.com/v1/",
+         "api_key": "OLLAMA_API_KEY",
+         "provider": "generic-chat-completion-api",
+         "max_tokens": 128000
+       }
+     ]
+   }
+   ```
+
+Run `droid` in a new terminal to load the new settings.
--- a/docs/integrations/goose.mdx
+++ b/docs/integrations/goose.mdx
@@ -0,0 +1,49 @@
+---
+title: Goose
+---
+
+## Goose Desktop
+
+Install [Goose](https://block.github.io/goose/docs/getting-started/installation/) Desktop.
+
+### Usage with Ollama
+1. In Goose, open **Settings** → **Configure Provider**.  
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/goose-settings.png" 
+    alt="Goose settings Panel"
+    width="75%"
+  />
+</div>
+2. Find **Ollama**, click **Configure** 
+3. Confirm **API Host** is `http://localhost:11434` and click Submit
+
+
+### Connecting to ollama.com
+
+1. Create an [API key](https://ollama.com/settings/keys) on ollama.com and save it in your `.env` 
+2. In Goose, set **API Host** to `https://ollama.com`
+
+
+## Goose CLI
+
+Install [Goose](https://block.github.io/goose/docs/getting-started/installation/) CLI
+
+### Usage with Ollama
+1. Run `goose configure`
+2. Select **Configure Providers** and select **Ollama**
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/goose-cli.png" 
+    alt="Goose CLI"
+    width="50%"
+  />
+</div>
+3. Enter model name (e.g `qwen3`)
+
+### Connecting to ollama.com
+
+1. Create an [API key](https://ollama.com/settings/keys) on ollama.com and save it in your `.env` 
+2. Run `goose configure`
+3. Select **Configure Providers** and select **Ollama**
+4. Update **OLLAMA_HOST** to `https://ollama.com`
--- a/docs/integrations/hermes.mdx
+++ b/docs/integrations/hermes.mdx
@@ -0,0 +1,119 @@
+---
+title: Hermes Agent
+---
+
+Hermes Agent is a self-improving AI agent built by Nous Research. It features automatic skill creation, cross-session memory, and 70+ skills that it ships with by default. 
+
+![Hermes Agent with Ollama](/images/hermes.png)
+
+## Quick start
+
+```bash
+ollama launch hermes
+```
+
+Ollama handles everything automatically:
+
+1. **Install** — If Hermes isn't installed, Ollama prompts to install it via the Nous Research install script
+2. **Model** — Pick a model from the selector (local or cloud)
+3. **Onboarding** — Ollama configures the Ollama provider, points Hermes at `http://127.0.0.1:11434/v1`, and sets your model as the primary
+4. **Gateway** — Optionally connects a messaging platform (Telegram, Discord, Slack, WhatsApp, Signal, Email) and launches the Hermes chat
+
+<Note>Hermes on Windows requires WSL2. Install it with `wsl --install` and re-run from inside the WSL shell.</Note>
+
+## Recommended models
+
+**Cloud models**:
+
+- `kimi-k2.5:cloud` — Multimodal reasoning with subagents
+- `glm-5.1:cloud` — Reasoning and code generation
+- `qwen3.5:cloud` — Reasoning, coding, and agentic tool use with vision
+- `minimax-m2.7:cloud` — Fast, efficient coding and real-world productivity
+
+**Local models:**
+
+- `gemma4` — Reasoning and code generation locally (~16 GB VRAM)
+- `qwen3.6` — Reasoning, coding, and visual understanding locally (~24 GB VRAM)
+
+More models at [ollama.com/search](https://ollama.com/search?c=cloud).
+
+## Connect messaging apps
+
+Link Telegram, Discord, Slack, WhatsApp, Signal, or Email to chat with your models from anywhere:
+
+```bash
+hermes gateway setup
+```
+
+## Reconfigure
+
+Re-run the full setup wizard at any time:
+
+```bash
+hermes setup
+```
+
+## Manual setup
+
+If you'd rather drive Hermes's own wizard instead of `ollama launch hermes`, install it directly:
+
+```bash
+curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash
+```
+
+Hermes launches the setup wizard automatically. Choose **Quick setup**:
+
+```
+How would you like to set up Hermes?
+
+ →  Quick setup — provider, model & messaging (recommended)
+    Full setup — configure everything
+```
+
+### Connect to Ollama
+
+1. Select **More providers...**
+2. Select **Custom endpoint (enter URL manually)**
+3. Set the API base URL to the Ollama OpenAI-compatible endpoint:
+
+   ```
+   API base URL [e.g. https://api.example.com/v1]: http://127.0.0.1:11434/v1
+   ```
+
+4. Leave the API key blank (not required for local Ollama):
+
+   ```
+   API key [optional]:
+   ```
+
+5. Hermes auto-detects downloaded models, confirm the one you want:
+
+   ```
+   Verified endpoint via http://127.0.0.1:11434/v1/models (1 model(s) visible)
+     Detected model: kimi-k2.5:cloud
+     Use this model? [Y/n]:
+   ```
+
+6. Leave context length blank to auto-detect:
+
+   ```
+   Context length in tokens [leave blank for auto-detect]:
+   ```
+
+### Connect messaging
+
+Optionally connect a messaging platform during setup:
+
+```
+Connect a messaging platform? (Telegram, Discord, etc.)
+
+ →  Set up messaging now (recommended)
+    Skip — set up later with 'hermes setup gateway'
+```
+
+### Launch
+
+```
+Launch hermes chat now? [Y/n]: Y
+```
+
--- a/docs/integrations/index.mdx
+++ b/docs/integrations/index.mdx
@@ -0,0 +1,55 @@
+---
+title: Overview
+---
+
+Ollama integrates with a wide range of tools.
+
+## Coding Agents
+
+Coding assistants that can read, modify, and execute code in your projects.
+
+- [Claude Code](/integrations/claude-code)
+- [Codex App](/integrations/codex-app)
+- [Codex CLI](/integrations/codex)
+- [Copilot CLI](/integrations/copilot-cli)
+- [OpenCode](/integrations/opencode)
+- [Droid](/integrations/droid)
+- [Goose](/integrations/goose)
+- [Pi](/integrations/pi)
+- [Pool](/integrations/pool)
+
+## Assistants
+
+AI assistants that help with everyday tasks.
+
+- [OpenClaw](/integrations/openclaw)
+- [Hermes Agent](/integrations/hermes)
+
+## IDEs & Editors
+
+Native integrations for popular development environments.
+
+- [VS Code](/integrations/vscode)
+- [Cline](/integrations/cline)
+- [Roo Code](/integrations/roo-code)
+- [JetBrains](/integrations/jetbrains)
+- [Xcode](/integrations/xcode)
+- [Zed](/integrations/zed)
+
+## Chat & RAG
+
+Chat interfaces and retrieval-augmented generation platforms.
+
+- [Onyx](/integrations/onyx)
+
+## Automation
+
+Workflow automation platforms with AI integration.
+
+- [n8n](/integrations/n8n)
+
+## Notebooks
+
+Interactive computing environments with AI capabilities.
+
+- [marimo](/integrations/marimo)
--- a/docs/integrations/jetbrains.mdx
+++ b/docs/integrations/jetbrains.mdx
@@ -0,0 +1,47 @@
+---
+title: JetBrains
+---
+
+<Note>This example uses **IntelliJ**; same steps apply to other JetBrains IDEs (e.g., PyCharm).</Note>
+
+## Install
+
+Install [IntelliJ](https://www.jetbrains.com/idea/).
+
+## Usage with Ollama
+
+<Note>
+  To use **Ollama**,  you will need a [JetBrains AI Subscription](https://www.jetbrains.com/ai-ides/buy/?section=personal&billing=yearly).
+</Note>
+
+1. In Intellij, click the **chat icon** located in the right sidebar
+
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/intellij-chat-sidebar.png" 
+    alt="Intellij Sidebar Chat"
+    width="50%"
+  />
+</div>
+
+2. Select the **current model** in the sidebar, then click **Set up Local Models**
+
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/intellij-current-model.png" 
+    alt="Intellij model bottom right corner"
+    width="50%"
+  />
+</div>
+
+3. Under **Third Party AI Providers**, choose **Ollama**  
+4. Confirm the **Host URL** is `http://localhost:11434`, then click **Ok**  
+5. Once connected, select a model under **Local models by Ollama**
+
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/intellij-local-models.png" 
+    alt="Zed star icon in bottom right corner"
+    width="50%"
+  />
+</div>
--- a/docs/integrations/marimo.mdx
+++ b/docs/integrations/marimo.mdx
@@ -0,0 +1,73 @@
+---
+title: marimo
+---
+
+## Install
+
+Install [marimo](https://marimo.io). You can use `pip` or `uv` for this. You 
+can also use `uv` to create a sandboxed environment for marimo by running:
+
+```
+uvx marimo edit --sandbox notebook.py
+```
+
+## Usage with Ollama
+
+1. In marimo, go to the user settings and go to the AI tab. From here
+you can find and configure Ollama as an AI provider. For local use you
+would typically point the base url to `http://localhost:11434/v1`.
+
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/marimo-settings.png" 
+    alt="Ollama settings in marimo"
+    width="50%"
+  />
+</div>
+
+2. Once the AI provider is set up, you can turn on/off specific AI models you'd like to access. 
+
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/marimo-models.png" 
+    alt="Selecting an Ollama model"
+    width="50%"
+  />
+</div>
+
+3. You can also add a model to the list of available models by scrolling to the bottom and using the UI there. 
+
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/marimo-add-model.png" 
+    alt="Adding a new Ollama model"
+    width="50%"
+  />
+</div>
+
+4. Once configured, you can now use Ollama for AI chats in marimo.
+
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/marimo-chat.png" 
+    alt="Configure code completion"
+    width="50%"
+  />
+</div>
+
+4. Alternatively, you can now use Ollama for **inline code completion** in marimo. This can be configured in the "AI Features" tab. 
+
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/marimo-code-completion.png" 
+    alt="Configure code completion"
+    width="50%"
+  />
+</div>
+
+
+## Connecting to ollama.com
+
+1. Sign in to ollama cloud via `ollama signin` 
+2. In the ollama model settings add a model that ollama hosts, like `gpt-oss:120b`.
+3. You can now refer to this model in marimo!
--- a/docs/integrations/n8n.mdx
+++ b/docs/integrations/n8n.mdx
@@ -0,0 +1,68 @@
+---
+title: n8n
+---
+
+## Install
+
+Install [n8n](https://docs.n8n.io/choose-n8n/).
+
+## Using Ollama Locally
+
+1. In the top right corner, click the dropdown and select **Create Credential**
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/n8n-credential-creation.png" 
+    alt="Create a n8n Credential"
+    width="75%"
+  />
+</div>
+
+2. Under **Add new credential** select **Ollama**
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/n8n-ollama-form.png" 
+    alt="Select Ollama under Credential"
+    width="75%"
+  />
+</div>
+3. Confirm Base URL is set to `http://localhost:11434` if running locally or `http://host.docker.internal:11434` if running through docker and click **Save**
+
+<Note> 
+In environments that don't use Docker Desktop (ie, Linux server installations), `host.docker.internal` is not automatically added. 
+
+Run n8n in docker with `--add-host=host.docker.internal:host-gateway` 
+
+or add the following to a docker compose file:
+
+```yaml
+extra_hosts:
+  - "host.docker.internal:host-gateway"
+```
+</Note>
+
+You should see a `Connection tested successfully` message.
+
+4. When creating a new workflow, select **Add a first step** and select an **Ollama node** 
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/n8n-chat-node.png" 
+    alt="Add a first step with Ollama node"
+    width="75%"
+  />
+</div>
+5. Select your model of choice (e.g. `qwen3-coder`) 
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/n8n-models.png" 
+    alt="Set up Ollama credentials"
+    width="75%"
+  />
+</div>
+
+## Connecting to ollama.com
+1. Create an [API key](https://ollama.com/settings/keys) on **ollama.com**.  
+2. In n8n, click **Create Credential** and select **Ollama**
+4. Set the **API URL** to `https://ollama.com`
+5. Enter your **API Key** and click **Save**
+
+
--- a/docs/integrations/nemoclaw.mdx
+++ b/docs/integrations/nemoclaw.mdx
@@ -0,0 +1,67 @@
+---
+title: NemoClaw
+---
+
+NemoClaw is NVIDIA's open source security stack for [OpenClaw](/integrations/openclaw). It wraps OpenClaw with the NVIDIA OpenShell runtime to provide kernel-level sandboxing, network policy controls, and audit trails for AI agents. 
+
+## Quick start
+
+Pull a model:
+
+```bash
+ollama pull nemotron-3-nano:30b
+```
+
+Run the installer:
+
+```bash
+curl -fsSL https://www.nvidia.com/nemoclaw.sh | \
+  NEMOCLAW_NON_INTERACTIVE=1 \
+  NEMOCLAW_PROVIDER=ollama \
+  NEMOCLAW_MODEL=nemotron-3-nano:30b \
+  bash
+```
+
+Connect to your sandbox:
+
+```bash
+nemoclaw my-assistant connect
+```
+
+Open the TUI:
+
+```bash
+openclaw tui
+```
+
+<Note>Ollama support in NemoClaw is still experimental.</Note>
+
+## Platform support
+
+| Platform | Runtime | Status |
+|----------|---------|--------|
+| Linux (Ubuntu 22.04+) | Docker | Primary |
+| macOS (Apple Silicon) | Colima or Docker Desktop | Supported |
+| Windows | WSL2 with Docker Desktop | Supported |
+
+CMD and PowerShell are not supported on Windows — WSL2 is required.
+
+<Note>Ollama must be installed and running before the installer runs. When running inside WSL2 or a container, ensure Ollama is reachable from the sandbox (e.g. `OLLAMA_HOST=0.0.0.0`).</Note>
+
+## System requirements
+
+- CPU: 4 vCPU minimum
+- RAM: 8 GB minimum (16 GB recommended)
+- Disk: 20 GB free (40 GB recommended for local models)
+- Node.js 20+ and npm 10+
+- Container runtime (Docker preferred)
+
+## Recommended models
+
+- `nemotron-3-super:cloud` — Strong reasoning and coding
+- `qwen3.5:cloud` — 397B; reasoning and code generation
+- `nemotron-3-nano:30b` — Recommended local model; fits in 24 GB VRAM
+- `qwen3.5:27b` — Fast local reasoning (~18 GB VRAM)
+- `glm-4.7-flash` — Reasoning and code generation (~25 GB VRAM)
+
+More models at [ollama.com/search](https://ollama.com/search).
--- a/docs/integrations/onyx.mdx
+++ b/docs/integrations/onyx.mdx
@@ -0,0 +1,63 @@
+---
+title: Onyx
+---
+
+## Overview
+[Onyx](http://onyx.app/) is a self-hostable Chat UI that integrates with all Ollama models. Features include:
+- Creating custom Agents
+- Web search
+- Deep Research
+- RAG over uploaded documents and connected apps
+- Connectors to applications like Google Drive, Email, Slack, etc.
+- MCP and OpenAPI Actions support
+- Image generation
+- User/Groups management, RBAC, SSO, etc.
+
+Onyx can be deployed for single users or large organizations.
+
+## Install Onyx
+
+Deploy Onyx with the [quickstart guide](https://docs.onyx.app/deployment/getting_started/quickstart).
+
+<Info>
+Resourcing/scaling docs [here](https://docs.onyx.app/deployment/getting_started/resourcing).
+</Info>
+
+## Usage with Ollama 
+
+1. Login to your Onyx deployment (create an account first).
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/onyx-login.png" 
+    alt="Onyx Login Page"
+    width="75%"
+  />
+</div>
+2. In the set-up process select `Ollama` as the LLM provider.
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/onyx-ollama-llm.png" 
+    alt="Onyx Set Up Form"
+    width="75%"
+  />
+</div>
+3. Provide your **Ollama API URL** and select your models.
+<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>
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/onyx-ollama-form.png" 
+    alt="Selecting Ollama Models"
+    width="75%"
+  />
+</div>
+
+You can also easily connect up Onyx Cloud with the `Ollama Cloud` tab of the setup.
+
+## Send your first query
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/onyx-query.png" 
+    alt="Onyx Query Example"
+    width="75%"
+  />
+</div>
--- a/docs/integrations/openclaw.mdx
+++ b/docs/integrations/openclaw.mdx
@@ -0,0 +1,95 @@
+---
+title: OpenClaw
+---
+
+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.
+
+## Quick start
+
+```bash
+ollama launch openclaw
+```
+
+Ollama handles everything automatically:
+
+1. **Install** — If OpenClaw isn't installed, Ollama prompts to install it via npm
+2. **Security** — On the first launch, a security notice explains the risks of tool access
+3. **Model** — Pick a model from the selector (local or cloud)
+4. **Onboarding** — Ollama configures the provider, installs the gateway daemon, sets your model as the primary, and enables OpenClaw's bundled Ollama web search
+5. **Gateway** — Starts in the background and opens the OpenClaw TUI
+
+<Note>OpenClaw requires a larger context window. It is recommended to use a context window of at least 64k tokens if using local models. See [Context length](/context-length) for more information.</Note>
+
+<Note>Previously known as Clawdbot. `ollama launch clawdbot` still works as an alias.</Note>
+
+## Web search and fetch
+
+OpenClaw ships with a bundled Ollama `web_search` provider that lets local or cloud-backed Ollama setups search the web through the configured Ollama host.
+
+```bash
+ollama launch openclaw
+```
+
+Ollama web search is enabled automatically when launching OpenClaw through Ollama. To configure it manually:
+
+```bash
+openclaw configure --section web
+```
+
+<Note>Ollama web search for local models requires `ollama signin`.</Note>
+
+## Configure without launching
+
+To change the model without starting the gateway and TUI:
+
+```bash
+ollama launch openclaw --config
+```
+
+To use a specific model directly:
+
+```bash
+ollama launch openclaw --model kimi-k2.5:cloud
+```
+
+If the gateway is already running, it restarts automatically to pick up the new model.
+
+## Recommended models
+
+**Cloud models**:
+
+- `kimi-k2.5:cloud` — Multimodal reasoning with subagents
+- `qwen3.5:cloud` — Reasoning, coding, and agentic tool use with vision
+- `glm-5.1:cloud` — Reasoning and code generation
+- `minimax-m2.7:cloud` — Fast, efficient coding and real-world productivity
+
+**Local models:**
+
+- `gemma4` — Reasoning and code generation locally (~16 GB VRAM)
+- `qwen3.5` — Reasoning, coding, and visual understanding locally (~11 GB VRAM)
+
+More models at [ollama.com/search](https://ollama.com/search?c=cloud).
+
+## Non-interactive (headless) mode
+
+Run OpenClaw without interaction for use in Docker, CI/CD, or scripts:
+
+```bash
+ollama launch openclaw --model kimi-k2.5:cloud --yes
+```
+
+The `--yes` flag auto-pulls the model, skips selectors, and requires `--model` to be specified.
+
+## Connect messaging apps
+
+```bash
+openclaw configure --section channels
+```
+
+Link WhatsApp, Telegram, Slack, Discord, or iMessage to chat with your local models from anywhere.
+
+## Stopping the gateway
+
+```bash
+openclaw gateway stop
+```
--- a/docs/integrations/opencode.mdx
+++ b/docs/integrations/opencode.mdx
@@ -0,0 +1,31 @@
+---
+title: OpenCode
+---
+
+OpenCode is an open-source AI coding assistant that runs in your terminal.
+
+## Install
+
+Install the [OpenCode CLI](https://opencode.ai):
+
+```bash
+curl -fsSL https://opencode.ai/install | bash
+```
+
+<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>
+
+## Usage with Ollama
+
+### Quick setup
+
+```bash
+ollama launch opencode
+```
+
+To configure without launching:
+
+```shell
+ollama launch opencode --config
+```
+
+<Note>`ollama launch opencode` passes its configuration to OpenCode inline via the `OPENCODE_CONFIG_CONTENT` environment variable. OpenCode deep-merges its config sources on startup, so anything you declare in `~/.config/opencode/opencode.json` is still respected and available inside OpenCode. Models declared only in `opencode.json` won't appear in `ollama launch`'s model-selection menu.</Note>
--- a/docs/integrations/pi.mdx
+++ b/docs/integrations/pi.mdx
@@ -0,0 +1,109 @@
+---
+title: Pi
+---
+
+Pi is a minimal and extensible coding agent.
+
+## Install
+
+Install [Pi](https://github.com/badlogic/pi-mono):
+
+```bash
+npm install -g @mariozechner/pi-coding-agent
+```
+
+## Usage with Ollama
+
+### Quick setup
+
+```bash
+ollama launch pi
+```
+
+This installs Pi, configures Ollama as a provider including web tools, and drops you into an interactive session.
+
+To configure without launching:
+
+```shell
+ollama launch pi --config
+```
+
+### Run directly with a model
+
+```shell
+ollama launch pi --model qwen3.5:cloud
+```
+
+Cloud models are also available at [ollama.com](https://ollama.com/search?c=cloud).
+
+## Extensions 
+
+Pi ships with four core tools: `read`, `write`, `edit`, and `bash`. All other capabilities are added through its extension system.
+
+On-demand capability packages invoked via `/skill:name` commands.  
+
+Install from npm or git:
+
+```bash
+pi install npm:@foo/some-tools
+pi install git:github.com/user/repo@v1
+```
+
+See all packages at [pi.dev](https://pi.dev/packages) 
+
+### Web search
+
+Pi can use web search and fetch tools via the `@ollama/pi-web-search` package.
+
+When launching Pi through Ollama, package install/update is managed automatically.
+To install manually:
+
+```bash
+pi install npm:@ollama/pi-web-search
+```
+
+### Autoresearch with `pi-autoresearch`
+
+[pi-autoresearch](https://github.com/davebcn87/pi-autoresearch) brings autonomous experiment loops to Pi. Inspired by Karpathy's autoresearch, it turns any measurable metric into an optimization target: test speed, bundle size, build time, model training loss, Lighthouse scores.
+
+```bash
+pi install https://github.com/davebcn87/pi-autoresearch
+```
+
+Tell Pi what to optimize. It runs experiments, benchmarks each one, keeps improvements, reverts regressions, and repeats — all autonomously. A built-in dashboard tracks every run with confidence scoring to distinguish real gains from benchmark noise.
+
+```bash
+/autoresearch optimize unit test runtime
+```
+
+Each kept experiment is automatically committed. Each failed one is reverted. When you're done, Pi can group improvements into independent branches for clean review and merge.
+
+## Manual setup
+
+Add a configuration block to `~/.pi/agent/models.json`:
+
+```json
+{
+  "providers": {
+    "ollama": {
+      "baseUrl": "http://localhost:11434/v1",
+      "api": "openai-completions",
+      "apiKey": "ollama",
+      "models": [
+        {
+          "id": "qwen3-coder"
+        }
+      ]
+    }
+  }
+}
+```
+
+Update `~/.pi/agent/settings.json` to set the default provider:
+
+```json
+{
+  "defaultProvider": "ollama",
+  "defaultModel": "qwen3-coder"
+}
+```
--- a/docs/integrations/pool.mdx
+++ b/docs/integrations/pool.mdx
@@ -0,0 +1,54 @@
+---
+title: Pool
+---
+
+Pool is Poolside's software agent for the terminal, built for enterprise development workflows.
+
+## Install
+
+Install [Pool](https://github.com/poolsideai/pool):
+
+## Usage with Ollama
+
+### Quick setup
+
+```shell
+ollama launch pool
+```
+
+### Run directly with a model
+
+```shell
+ollama launch pool --model kimi-k2.6:cloud
+```
+
+### Pass arguments through to Pool
+
+Arguments after `--` are passed directly to Pool:
+
+```shell
+ollama launch pool -- --help
+```
+
+## Manual setup
+
+Pool connects to Ollama using the OpenAI-compatible API via environment variables.
+
+1. Set the environment variables:
+
+```shell
+export POOLSIDE_STANDALONE_BASE_URL=http://localhost:11434/v1
+export POOLSIDE_API_KEY=ollama
+```
+
+2. Run Pool with an Ollama model:
+
+```shell
+pool -m kimi-k2.6:cloud
+```
+
+Or run with environment variables inline:
+
+```shell
+POOLSIDE_STANDALONE_BASE_URL=http://localhost:11434/v1 POOLSIDE_API_KEY=ollama pool -m kimi-k2.6:cloud
+```
--- a/docs/integrations/roo-code.mdx
+++ b/docs/integrations/roo-code.mdx
@@ -0,0 +1,30 @@
+---
+title: Roo Code
+---
+
+
+## Install
+
+Install [Roo Code](https://marketplace.visualstudio.com/items?itemName=RooVeterinaryInc.roo-cline) from the VS Code Marketplace.
+
+## Usage with Ollama
+
+1. Open Roo Code in VS Code and click the **gear icon** on the top right corner of the Roo Code window to open **Provider Settings**
+2. Set `API Provider` to `Ollama`
+3. (Optional) Update `Base URL` if your Ollama instance is running remotely. The default is `http://localhost:11434`
+4. Enter a valid `Model ID` (for example `qwen3` or `qwen3-coder:480b-cloud`)
+5. Adjust the `Context Window` to at least 32K tokens for coding tasks
+
+<Note>Coding tools require 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>
+
+## Connecting to ollama.com
+
+1. Create an [API key](https://ollama.com/settings/keys) from ollama.com
+2. Enable `Use custom base URL` and set it to `https://ollama.com`
+3. Enter your **Ollama API Key**
+4. Select a model from the list
+
+### Recommended Models
+
+- `qwen3-coder:480b`
+- `deepseek-v3.1:671b`
--- a/docs/integrations/vscode.mdx
+++ b/docs/integrations/vscode.mdx
@@ -0,0 +1,85 @@
+---
+title: VS Code
+---
+
+VS Code includes built-in AI chat through GitHub Copilot Chat. Ollama models can be used directly in the Copilot Chat model picker.
+
+
+![VS Code with Ollama](/images/vscode.png)
+
+
+## Prerequisites
+
+- Ollama v0.18.3+
+- [VS Code 1.113+](https://code.visualstudio.com/download)
+- [GitHub Copilot Chat extension 0.41.0+](https://marketplace.visualstudio.com/items?itemName=GitHub.copilot-chat)
+
+<Note> VS Code requires you to be logged in to use its model selector, even for custom models. This doesn't require a paid GitHub Copilot account; GitHub Copilot Free will enable model selection for custom models.</Note>
+
+## Quick setup
+
+```shell
+ollama launch vscode
+```
+
+Recommended models will be shown after running the command. See the latest models at [ollama.com](https://ollama.com/search?c=tools).
+
+Make sure **Local** is selected at the bottom of the Copilot Chat panel to use your Ollama models.
+<div style={{ display: "flex", justifyContent: "center" }}>
+  <img
+    src="/images/local.png"
+    alt="Ollama Local Models"
+    width="60%"
+    style={{ borderRadius: "4px", marginTop: "10px", marginBottom: "10px" }}
+  />
+</div>
+
+
+## Run directly with a model
+
+```shell
+ollama launch vscode --model qwen3.5:cloud
+```
+Cloud models are also available at [ollama.com](https://ollama.com/search?c=cloud).
+
+## Manual setup
+
+To configure Ollama manually without `ollama launch`:
+
+1. Open the **Copilot Chat** side bar from the top right corner
+   <div style={{ display: "flex", justifyContent: "center" }}>
+     <img
+       src="/images/vscode-sidebar.png"
+       alt="VS Code chat Sidebar"
+       width="75%"
+       style={{ borderRadius: "4px" }}
+     />
+   </div>
+2. Click the **settings gear icon** (<Icon icon="gear" />) to bring up the Language Models window
+   <div style={{ display: "flex", justifyContent: "center" }}>
+     <img
+       src="/images/vscode-other-models.png"
+       alt="VS Code model picker"
+       width="75%"
+       style={{ borderRadius: "4px" }}
+     />
+   </div>
+3. Click **Add Models** and select **Ollama** to load all your Ollama models into VS Code
+   <div style={{ display: "flex", justifyContent: "center" }}>
+     <img
+       src="/images/vscode-add-ollama.png"
+       alt="VS Code model options dropdown to add ollama models"
+       width="75%"
+       style={{ borderRadius: "4px" }}
+     />
+   </div>
+
+4. Click the **Unhide** button in the model picker to show your Ollama models  
+   <div style={{ display: "flex", justifyContent: "center" }}>
+     <img
+       src="/images/vscode-unhide.png"
+       alt="VS Code unhide models button"
+       width="75%"
+       style={{ borderRadius: "4px" }}
+     />
+   </div>
--- a/docs/integrations/xcode.mdx
+++ b/docs/integrations/xcode.mdx
@@ -0,0 +1,45 @@
+---
+title: Xcode 
+---
+
+## Install
+
+Install [XCode](https://developer.apple.com/xcode/)
+
+
+## Usage with Ollama 
+<Note> Ensure Apple Intelligence is setup and the latest XCode version is v26.0 </Note>
+
+1. Click **XCode** in top left corner > **Settings** 
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/xcode-intelligence-window.png" 
+    alt="Xcode Intelligence window"
+    width="50%"
+  />
+</div>
+
+2. Select **Locally Hosted**, enter port **11434** and click **Add**
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/xcode-locally-hosted.png" 
+    alt="Xcode settings"
+    width="50%"
+  />
+</div>
+
+3. Select the **star icon** on the top left corner and click the **dropdown**
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/xcode-chat-icon.png" 
+    alt="Xcode settings"
+    width="50%"
+  />
+</div>
+4. Click **My Account** and select your desired model
+
+
+## Connecting to ollama.com directly
+1. Create an [API key](https://ollama.com/settings/keys) from ollama.com 
+2. Select **Internet Hosted** and enter URL as `https://ollama.com`  
+3. Enter your **Ollama API Key** and click **Add** 
--- a/docs/integrations/zed.mdx
+++ b/docs/integrations/zed.mdx
@@ -0,0 +1,38 @@
+---
+title: Zed
+---
+
+## Install
+
+Install [Zed](https://zed.dev/download).
+
+## Usage with Ollama
+
+1. In Zed, click the **star icon** in the bottom-right corner, then select **Configure**.
+
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/zed-settings.png" 
+    alt="Zed star icon in bottom right corner"
+    width="50%"
+  />
+</div>
+
+2. Under **LLM Providers**, choose **Ollama**
+3. Confirm the **Host URL** is `http://localhost:11434`, then click **Connect**
+4. Once connected, select a model under **Ollama**
+
+<div style={{ display: 'flex', justifyContent: 'center' }}>
+  <img 
+    src="/images/zed-ollama-dropdown.png" 
+    alt="Zed star icon in bottom right corner"
+    width="50%"
+  />
+</div>
+
+## Connecting to ollama.com
+1. Create an [API key](https://ollama.com/settings/keys) on **ollama.com**
+2. In Zed, open the **star icon** → **Configure**
+3. Under **LLM Providers**, select **Ollama**
+4. Set the **API URL** to `https://ollama.com`
+