> ## Documentation Index > Fetch the complete documentation index at: https://docs.graphify.com/llms.txt > Use this file to discover all available pages before exploring further. # Extract without an IDE > Run code or semantic extraction from a terminal or CI environment. `graphify extract` runs the pipeline without an assistant skill. It is useful for repeatable local scripts and CI jobs. ## Code-only extraction ```bash theme={null} graphify extract . --code-only ``` This needs no model API key. Start here to verify installation and the project scope. ## Semantic extraction Install the extra for your backend, configure its credentials outside the repository, then select it: ```bash theme={null} graphify extract ./docs --backend claude ``` Graphify supports Claude, Gemini, OpenAI, DeepSeek, Kimi, Ollama, Bedrock, Azure, and Claude CLI backends. [Configuration](/reference/configuration) maps backends to their environment variables. Do not assume a model supports every input type. ## Tune resource use ```bash theme={null} graphify extract ./docs --backend ollama --token-budget 4000 --max-concurrency 2 ``` `--max-workers` controls structural extraction parallelism. `--max-concurrency` controls model requests. `--api-timeout` changes the request timeout. Smaller chunks and less concurrency can help a local model fit its available memory. ## CI pattern Install a pinned package version in the CI environment, run extraction from the repository root, and retain the reviewed graph or report as an artifact. Use the same ignore rules and output location on every run. Supply provider credentials through the CI secret store only when semantic extraction is part of the job. No provider key is necessary for `--code-only`. Do not make CI publication of the graph public unless the underlying source can be public too.