gemini-cli

Gemini CLI Core

Gemini CLI’s core package (packages/core) is the backend portion of Gemini CLI, handling communication with the Gemini API, managing tools, and processing requests sent from packages/cli. For a general overview of Gemini CLI, see the main documentation page.

Navigating this section

• Core tools API: Information on how tools are defined, registered, and used by the core.
• Memory Import Processor: Documentation for the modular GEMINI.md import feature using @file.md syntax.

Role of the core

While the packages/cli portion of Gemini CLI provides the user interface, packages/core is responsible for:

• Gemini API interaction: Securely communicating with the Google Gemini API, sending user prompts, and receiving model responses.
• Prompt engineering: Constructing effective prompts for the Gemini model, potentially incorporating conversation history, tool definitions, and instructional context from GEMINI.md files.
• Tool management & orchestration:
  • Registering available tools (e.g., file system tools, shell command execution).
  • Interpreting tool use requests from the Gemini model.
  • Executing the requested tools with the provided arguments.
  • Returning tool execution results to the Gemini model for further processing.
• Session and state management: Keeping track of the conversation state, including history and any relevant context required for coherent interactions.
• Configuration: Managing core-specific configurations, such as API key access, model selection, and tool settings.

Security considerations

The core plays a vital role in security:

• API key management: It handles the GEMINI_API_KEY and ensures it’s used securely when communicating with the Gemini API.
• Tool execution: When tools interact with the local system (e.g., run_shell_command), the core (and its underlying tool implementations) must do so with appropriate caution, often involving sandboxing mechanisms to prevent unintended modifications.

Chat history compression

To ensure that long conversations don’t exceed the token limits of the Gemini model, the core includes a chat history compression feature.

When a conversation approaches the token limit for the configured model, the core automatically compresses the conversation history before sending it to the model. This compression is designed to be lossless in terms of the information conveyed, but it reduces the overall number of tokens used.

You can find the token limits for each model in the Google AI documentation.

Model fallback

Gemini CLI includes a model fallback mechanism to ensure that you can continue to use the CLI even if the default “pro” model is rate-limited.

If you are using the default “pro” model and the CLI detects that you are being rate-limited, it automatically switches to the “flash” model for the current session. This allows you to continue working without interruption.

File discovery service

The file discovery service is responsible for finding files in the project that are relevant to the current context. It is used by the @ command and other tools that need to access files.

Memory discovery service

The memory discovery service is responsible for finding and loading the GEMINI.md files that provide context to the model. It searches for these files in a hierarchical manner, starting from the current working directory and moving up to the project root and the user’s home directory. It also searches in subdirectories.

This allows you to have global, project-level, and component-level context files, which are all combined to provide the model with the most relevant information.

You can use the /memory command to show, add, and refresh the content of loaded GEMINI.md files.

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