Specification: Gemini CLI Parity

Overview

Achieve full functional and behavioral parity between the Gemini CLI integration (gemini_cli_adapter.py, cli_tool_bridge.py) and the direct Gemini API implementation (ai_client.py). This ensures that users leveraging the Gemini CLI as a headless backend provider experience the same level of capability, reliability, and observability as direct API users.

Functional Requirements

Token Estimation Parity: Implement accurate token counting for both input and output in the Gemini CLI adapter to match the precision of the direct API.
Safety Settings Parity: Enable full configuration and enforcement of Gemini safety filters when using the CLI provider.
Tool Calling Parity: Synchronize tool definition mapping, call handling, and response processing between the CLI bridge and the direct SDK.
System Instructions Parity: Ensure system prompts and instructions are consistently passed and handled across both providers.
Bridge Robustness: Enhance the cli_tool_bridge.py and adapter to improve latency, error handling (retries), and detailed subprocess observability.

Non-Functional Requirements

Observability: Detailed logging of CLI subprocess interactions for debugging.
Performance: Minimize the overhead introduced by the bridge mechanism.
Maintainability: Ensure that future changes to ai_client.py can be easily mirrored in the CLI adapter.

Acceptance Criteria

Token counts for identical prompts match within a 5% margin between CLI and Direct API.
Safety settings configured in the GUI are correctly applied to CLI sessions.
Tool calls from the CLI are successfully executed and returned via the bridge without loss of context.
System instructions are correctly utilized by the model when using the CLI.
Automated tests verify that responses and tool execution flows are identical for both providers.

Out of Scope

Performance optimizations for the gemini CLI binary itself.
Support for non-Gemini CLI providers in this track.

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