Ollama is automatically detected when running locally at http://127.0.0.1:11434/v1
openclaw can detect presence of ollama if it is visible at this specific localhost address. basically if you have ollama running it will be detected. Meaning I could run openclaw fully locally.
Ollama Ollama is a local LLM runtime that provides an OpenAI-compatible API:
one can set openclaw to work through ollama.
ollama can integrate with OpenClaw, meaning it would run through local models
Setting context length Setting a larger context length will increase the amount of memory required to run a model. Ensure you have enough VRAM available to increase the context length.
This setting is in ollama desktop interface. Does it set it for the terminal too? Or are these two separate instances?
Context length is the maximum number of tokens that the model has access to in memory. The default context length in Ollama is 4096 tokens. Tasks which require large context like web search, agents, and coding tools should be set to at least 64000 tokens.
Default ollama context length is 4k. Recommended minimum for websearch, agents and coding tools (like Claude Code or Open code) is 64k. I've seen 128k recommendations for Claude Code
Note: Claude Code requires a large context window. We recommend at least 64k tokens. See the context length documentation for how to adjust context length in Ollama.
how to set context length in ollama?
Set the environment variables:
where? and in ollama or claude code? this reads like in claude code
Quick setup Copyollama launch claude
Did this using qwen3-code, but then Claude Code just keeps spinning, even with the smallest prompt. Not sure about the cause (first load of model??)
Recommended Models qwen3-coder glm-4.7 gpt-oss:20b gpt-oss:120b
the local models ollama recommends for use in claudecode - qwen3-code - glm-4.7 - gpt-oss:20b - gpt-oss:120b
ollama can also be used with claude code through their endpoint. This allows to use the open Chinese coding models like qwen3
ollama model catalog, to see which ones are popular at the mo
Select a Model: Once connected, you can choose from any of the models you have pulled in Ollama.
connecting to ollama let's me choose the model for text enhancement
Supported Providers Ollama (Free & Local): Run powerful open-source models locally on your machine. This is a great option for privacy and offline use.
Ah, enhancement can be done locally too, by connecting to ollama.
Flow uses a combination of open-source models (i.e. LLAMA 3.1) and proprietary LLM providers (such as OpenAI) to provide its services. Wispr has agreements with all third party generative AI providers to ensure no data is stored or used for model training (zero data retention).
Wispr Flow uses both open (Llama) and closed LLMS, ao OpenAI . Server side though
suggested ollama models for code generation, 4 out of 5 are Chinese, one other from OpenAI
CodeGPT and this blog are run by Judini Inc, a Miami based US corporation
Qwen3-Coder Alibaba's performant long context models for agentic and coding tasks
Another Qwen model, without the focus on visual inputs. Alibaba. Listed in ollama
Qwen3-VL
Qwen models are by Alibaba. The VL versions are for visual inputs to generating code. Listed in ollama
DeepSeek-R1 DeepSeek-R1 i
DeepSeek, Chinese model. Listed in ollama
GLM-4.6 Advanced agentic, reasoning and coding capabilities
GLM is a Chinese model. I don't see it listed in Ollama though.
GPT-OSS OpenAI's open-weight models designed for powerful reasoning, agentic tasks, and versatile developer use cases.
GPT-OSS is by OpenAI. It is available locally in Ollama it seems in various versions.
The AI toolkit adds LLM based options to VSCode. Installed it, as it allows me to access different models via ollama locally.
能力 - 语音转录: 基于whisper模型（可本地，也可用OpenAI Whisper API） - 字幕翻译: 支持ollama 和 LM Studio （其实是基于【兼容OpenAI API】设计的 https://chidiwilliams.github.io/buzz/zh/docs/usage/translations ）
安装与部署: 基于python包 - 对MacOS和Windows均提供了一键安装包 - 对Linux提供了flatpak和snap包
能力: - 语音转录支持本地(WhisperCpp/FasterWhisper) 和在线（B接口/J接口??） - 字幕翻译支持传统引擎和LLM - 传统引擎: DeepL/微软/谷歌 - LLM: Ollama、DeepSeek、硅基流动以及【OpenAI兼容接口】 （配套提供LLM API中转站）
安装部署 - Windows提供一键安装包 - MacOS需要自行基于python搭建，且作者说未验证过 👎 。另外本地 whisper 功能尚不支持macos）
http://192.168.1.100:11434 or the docker host machine IP address, e.g., http://172.17.0.1:11434.For local source code deployment, use http://localhost:11434
docker容器间访问ollama localhost要变 ubuntu获取主机ip命令： hostname -I