Code with local models
Flame supports Ollama as a local AI provider, alongside LM Studio and compatible endpoints. The model choice is configured in Flame rather than requiring a separate editor.
Ollama integration
Use local AI models for coding with Ollama and Flame
Ollama gives Flame a local model provider. Flame gives that model a real development environment: project context, Git, terminals, tests, debugging, and an option to use cloud providers for a different task.
The developer problem
Choosing a local model should not mean giving up the development workspace.
Developers use local models for experimentation, model control, predictable local inference, or privacy-sensitive parts of a workflow. But a model endpoint alone does not provide a project browser, Git review, test runner, debugger, or an implementation process.
Flame can connect Ollama as a local provider while retaining those tools around the model. The provider choice is separate from the rest of the workspace, so local and cloud models can coexist according to the task.
A connected workflow
A local-model coding workflow
The tool remains the system you know. Flame provides the local workspace where the work moves forward.
- 01
Connect the local provider
Add Ollama in Flame’s AI settings and choose it where a local model is appropriate for chat, completion, or compatible AI workflows.
- 02
Work with the project context
Use selected files, diffs, terminal output, test results, and browser state as scoped AI context instead of moving code into a separate local-model interface.
- 03
Verify with local development tools
Keep the terminal, tests, debugger, API client, and Git diff in the same workspace as the AI interaction.
- 04
Choose cloud only when it fits
Use a cloud provider or a full coding-agent runtime for another task without rebuilding the projects, branches, or review workflow.
How it works in Flame
Local AI, with precise boundaries
What stays local
When you use a local Ollama model, model inference is handled by that local provider. This does not automatically make every other Flame feature, connected integration, or external service local or private.
Use local models with the actual workspace
AI context can include selected files, diffs, terminal output, test results, and browser state under Flame’s scoped permissions; terminals, Git, tests, and debugging remain local workspace tools.
Mix local and cloud AI deliberately
Flame supports local providers as well as Anthropic, OpenAI, Gemini, OpenRouter, Bedrock, Vertex, and compatible endpoints. Use the provider that suits the job without replacing the workspace.
FAQ
Ollama integration questions
Use Ollama with Flame.
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