Sync ollama docs from 8f45236d on 2026-03-12

This commit is contained in:
The Librarian
2026-03-12 04:00:04 +00:00
parent 6bfb23ec9f
commit 1c2aec910d
15 changed files with 324 additions and 190 deletions
+51 -16
View File
@@ -4,7 +4,7 @@ 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 `glm-4.7`, `qwen3-coder`, `gpt-oss`.
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)
@@ -32,13 +32,57 @@ irm https://claude.ai/install.ps1 | iex
ollama launch claude
```
To configure without launching:
### Run directly with a model
```shell
ollama launch claude --config
ollama launch claude --model kimi-k2.5:cloud
```
### Manual setup
## Recommended Models
- `kimi-k2.5:cloud`
- `glm-5:cloud`
- `minimax-m2.5: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).
## 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
```
## Manual setup
Claude Code connects to Ollama using the Anthropic-compatible API.
@@ -53,23 +97,14 @@ export ANTHROPIC_BASE_URL=http://localhost:11434
2. Run Claude Code with an Ollama model:
```shell
claude --model gpt-oss:20b
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 qwen3-coder
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.
## Recommended Models
- `qwen3-coder`
- `glm-4.7`
- `gpt-oss:20b`
- `gpt-oss:120b`
Cloud models are also available at [ollama.com/search?c=cloud](https://ollama.com/search?c=cloud).
+1
View File
@@ -13,6 +13,7 @@ Coding assistants that can read, modify, and execute code in your projects.
- [OpenCode](/integrations/opencode)
- [Droid](/integrations/droid)
- [Goose](/integrations/goose)
- [Pi](/integrations/pi)
## Assistants
+48 -30
View File
@@ -4,47 +4,65 @@ 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.
## Install
Install [OpenClaw](https://openclaw.ai/)
```bash
npm install -g openclaw@latest
```
Then run the onboarding wizard:
```bash
openclaw onboard --install-daemon
```
<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>
## Usage with Ollama
### Quick setup
## 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, and sets your model as the primary
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>
This configures OpenClaw to use Ollama and starts the gateway.
If the gateway is already running, no changes need to be made as the gateway will auto-reload the changes.
## Configure without launching
To change the model without starting the gateway and TUI:
To configure without launching:
```shell
```bash
ollama launch openclaw --config
```
## Recommended Models
To use a specific model directly:
- `qwen3-coder`
- `glm-4.7`
- `gpt-oss:20b`
- `gpt-oss:120b`
```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
- `minimax-m2.5:cloud` — Fast, efficient coding and real-world productivity
- `glm-5:cloud` — Reasoning and code generation
**Local models:**
- `glm-4.7-flash` — Reasoning and code generation locally (~25 GB VRAM)
More models at [ollama.com/search](https://ollama.com/search?c=cloud).
## 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
```
Cloud models are also available at [ollama.com/search?c=cloud](https://ollama.com/search?c=cloud).
+57
View File
@@ -0,0 +1,57 @@
---
title: Pi
---
Pi is a minimal AI agent toolkit with plugin support.
## 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
```
To configure without launching:
```shell
ollama launch pi --config
```
### 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"
}
```