# Gemini Agent Specification

**Version**: v1.0.0 | **Status**: Active | **Last Updated**: February 2026

## 1. Overview

The Gemini Agent provides a standardized interface to Google's Gemini models, supporting text generation, multimodal inputs, and advanced platform features via the `google-genai` SDK.

## 2. Architecture

### 2.1 Class Hierarchy

- **`GeminiClient`** (extends `BaseAgent`)
  - **Responsibilities**:
    - SDK Client Initialization.
    - Request validation.
    - Method mapping (generate, stream, embed, files, cache).
  
- **`GeminiCLIWrapper`** (extends `BaseAgent`)
  - **Responsibilities**:
    - CLI subprocess wrapper.
    - Method mapping to `gemini-cli` npm package (`query`, `list_sessions`, `--extensions`, `mcp`, etc.).

### 2.2 Integration

- **`GeminiIntegrationAdapter`** (extends `AgentIntegrationAdapter`)
  - **Responsibilities**:
    - Adapt `adapt_for_ai_code_editing` -> `generate_content`.
    - Adapt `adapt_for_llm` -> `generate_content` (chat).
    - Adapt `adapt_for_code_execution` -> `generate_content` (analysis).

## 3. Interfaces

### 3.1 Primary Methods

- `execute(request: AgentRequest) -> AgentResponse`
- `stream(request: AgentRequest) -> Iterator[str]`
- `list_models()`
- `get_model(name)`
- `count_tokens(content)`
- `embed_content(content)`
- `upload_file(file, mime_type)`
- `list_files()`
- `delete_file(name)`
- `create_cached_content(...)`
- `create_tuned_model(...)`

## 4. Error Handling

- Wraps SDK exceptions in `GeminiError`.
- Logs failures with structured metadata.

## 5. Configuration

- `GEMINI_API_KEY`: Required.
- `GEMINI_MODEL`: Default model (default: `gemini-2.5-flash`).

## Navigation Links

- **Parent**: [Project Overview](../README.md)
- **Module Index**: [All Agents](../../AGENTS.md)
- **Documentation**: [Reference Guides](../../../../docs/README.md)
- **Home**: [Root README](../../../README.md)

## Detailed Architecture and Implementation

### Design Principles

1. **Strict Modularity**: Each component is isolated and communicates via well-defined APIs.
2. **Performance Optimization**: Implementation leverages lazy loading and intelligent caching to minimize resource overhead.
3. **Error Resilience**: Robust exception handling ensures system stability even under unexpected conditions.
4. **Extensibility**: The architecture is designed to accommodate future enhancements without breaking existing contracts.

### Technical Implementation

The codebase utilizes modern Python features (version 3.10+) to provide a clean, type-safe API. Interaction patterns are documented in the corresponding `AGENTS.md` and `SPEC.md` files, ensuring that both human developers and automated agents can effectively utilize these capabilities.
