| Variable | Default Value | Description + Effect + Scenario |
| OLLAMA_HOST | "[color=var(--fgColor-accent, var(--color-accent-fg))]The hyperlink login is visible." | Configures the host and scheme for the Ollama server. Effect: Determines the URL used for connecting to the Ollama server. Scenario: Useful when deploying Ollama in a distributed environment or when you need to expose the service on a specific network interface. |
| OLLAMA_ORIGINS | [localhost, 127.0.0.1, 0.0.0.0] + app://, file://, tauri:// | Configures allowed origins for CORS. Effect: Controls which origins are allowed to make requests to the Ollama server. Scenario: Critical when integrating Ollama with web applications to prevent unauthorized access from different domains. |
| OLLAMA_MODELS | $HOME/.ollama/models | Sets the path to the models directory. Effect: Determines where model files are stored and loaded from. Scenario: Useful for managing disk space on different drives or setting up shared model repositories in multi-user environments. |
| OLLAMA_KEEP_ALIVE | 5 minutes | Sets how long models stay loaded in memory. Effect: Controls the duration models remain in memory after use. Scenario: Longer durations improve response times for frequent queries but increase memory usage. Shorter durations free up resources but may increase initial response times. |
| OLLAMA_DEBUG | false | Enables additional debug information. Effect: Increases verbosity of logging and debugging output. Scenario: Invaluable for troubleshooting issues or understanding the system's behavior during development or deployment. |
| OLLAMA_FLASH_ATTENTION | false | Enables experimental flash attention feature. Effect: Activates an experimental optimization for attention mechanisms. Scenario: Can potentially improve performance on compatible hardware but may introduce instability. |
| OLLAMA_NOHISTORY | false | Disables readline history. Effect: Prevents command history from being saved. Scenario: Useful in security-sensitive environments where command history should not be persisted. |
| OLLAMA_NOPRUNE | false | Disables pruning of model blobs on startup. Effect: Keeps all model blobs, potentially increasing disk usage. Scenario: Helpful when you need to maintain all model versions for compatibility or rollback purposes. |
| OLLAMA_SCHED_SPREAD | false | Allows scheduling models across all GPUs. Effect: Enables multi-GPU usage for model inference. Scenario: Beneficial in high-performance computing environments with multiple GPUs to maximize hardware utilization. |
| OLLAMA_INTEL_GPU | false | Enables experimental Intel GPU detection. Effect: Allows usage of Intel GPUs for model inference. Scenario: Useful for organizations leveraging Intel GPU hardware for AI workloads. |
| OLLAMA_LLM_LIBRARY | "" (auto-detect) | Sets the LLM library to use. Effect: Overrides automatic detection of LLM library. Scenario: Useful when you need to force a specific library version or implementation for compatibility or performance reasons. |
| OLLAMA_TMPDIR | System default temp directory | Sets the location for temporary files. Effect: Determines where temporary files are stored. Scenario: Important for managing I/O performance or when system temp directory has limited space. |
| CUDA_VISIBLE_DEVICES | All available | Sets which NVIDIA devices are visible. Effect: Controls which NVIDIA GPUs can be used. Scenario: Critical for managing GPU allocation in multi-user or multi-process environments. |
| HIP_VISIBLE_DEVICES | All available | Sets which AMD devices are visible. Effect: Controls which AMD GPUs can be used. Scenario: Similar to CUDA_VISIBLE_DEVICES but for AMD hardware. |
| OLLAMA_RUNNERS_DIR | System-dependent | Sets the location for runners. Effect: Determines where runner executables are located. Scenario: Important for custom deployments or when runners need to be isolated from the main application. |
| OLLAMA_NUM_PARALLEL | 0 (unlimited) | Sets the number of parallel model requests. Effect: Controls concurrency of model inference. Scenario: Critical for managing system load and ensuring responsiveness in high-traffic environments. |
| OLLAMA_MAX_LOADED_MODELS | 0 (unlimited) | Sets the maximum number of loaded models. Effect: Limits the number of models that can be simultaneously loaded. Scenario: Helps manage memory usage in environments with limited resources or many different models. |
| OLLAMA_MAX_QUEUE | 512 | Sets the maximum number of queued requests. Effect: Limits the size of the request queue. Scenario: Prevents system overload during traffic spikes and ensures timely processing of requests. |
| OLLAMA_MAX_VRAM | 0 (unlimited) | Sets a maximum VRAM override in bytes. Effect: Limits the amount of VRAM that can be used. Scenario: Useful in shared GPU environments to prevent a single process from monopolizing GPU memory. |
Posted on 2025-2-5 21:14:04
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Landlord|
Posted on 2025-2-5 21:22:49
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