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@@ -1199,8 +1199,8 @@ within your user's home folder.
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Environment variables are a common way to configure applications, especially for
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sensitive information like API keys or for settings that might change between
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environments. For authentication setup, see the
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[Authentication documentation](./authentication.md) which covers all available
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authentication methods.
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[Authentication documentation](../get-started/authentication.md) which covers
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all available authentication methods.
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The CLI automatically loads environment variables from an `.env` file. The
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loading order is:
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@@ -1219,7 +1219,8 @@ the `advanced.excludedEnvVars` setting in your `settings.json` file.
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- **`GEMINI_API_KEY`**:
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- Your API key for the Gemini API.
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- One of several available [authentication methods](./authentication.md).
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- One of several available
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[authentication methods](../get-started/authentication.md).
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- Set this in your shell profile (e.g., `~/.bashrc`, `~/.zshrc`) or an `.env`
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file.
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- **`GEMINI_MODEL`**:
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@@ -1565,15 +1566,16 @@ conventions and context.
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about the active instructional context.
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- **Importing content:** You can modularize your context files by importing
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other Markdown files using the `@path/to/file.md` syntax. For more details,
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see the [Memory Import Processor documentation](../core/memport.md).
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see the [Memory Import Processor documentation](../reference/memport.md).
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- **Commands for memory management:**
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- Use `/memory refresh` to force a re-scan and reload of all context files
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from all configured locations. This updates the AI's instructional context.
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- Use `/memory show` to display the combined instructional context currently
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loaded, allowing you to verify the hierarchy and content being used by the
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AI.
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- See the [Commands documentation](../cli/commands.md#memory) for full details
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on the `/memory` command and its sub-commands (`show` and `refresh`).
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- See the [Commands documentation](../reference/commands.md#memory) for full
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details on the `/memory` command and its sub-commands (`show` and
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`refresh`).
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By understanding and utilizing these configuration layers and the hierarchical
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nature of context files, you can effectively manage the AI's memory and tailor
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