061 Architecture 37005839

Tunacode Architecture Documentation

Overview

Tunacode is a TUI (Terminal User Interface) code agent built with a layered, component-based architecture. The system is designed with clear separation of concerns between the presentation layer (UI), the core agent logic, tool capabilities, and configuration management.

File: <repo_root>/src

Version: 0.1.20

Python Version: 3.11-3.13

1. Architectural Pattern

The project follows a pragmatic layered architecture with strong component-based design principles:

┌─────────────────────────────────────────────────────────────┐
│                     Presentation Layer                       │
│                    (src/tunacode/ui/)                        │
│  Built with Textual framework - handles user interaction     │
└─────────────────────────────────────────────────────────────┘
                              ↓
┌─────────────────────────────────────────────────────────────┐
│                      Application Layer                       │
│                   (src/tunacode/core/)                       │
│  Agent orchestration, request processing, state management   │
└─────────────────────────────────────────────────────────────┘
                              ↓
┌─────────────────────────────────────────────────────────────┐
│                       Domain Layer                           │
│                    (src/tunacode/tools/)                     │
│  Tool functions - bash, grep, read_file, etc.               │
└─────────────────────────────────────────────────────────────┘
                              ↓
┌─────────────────────────────────────────────────────────────┐
│                   Infrastructure Layer                       │
│  (src/tunacode/configuration/, indexing/, lsp/, utils/)      │
│  Configuration, indexing, LSP integration, utilities        │
└─────────────────────────────────────────────────────────────┘

Key Architectural Principles

1. UI/Core Decoupling: The core agent logic is completely independent of the Textual UI, enabling headless execution and testing
2. Callback-based Communication: Layers communicate through callbacks rather than direct dependencies
3. Centralized State Management: A StateManager holds all session state, avoiding scattered state management
4. Modular Tool System: Tools are self-contained functions with clear interfaces
5. Composable System Prompts: Prompts are composed from smaller sections for maintainability

2. Component Relationships

Major Components

┌──────────────────────────────────────────────────────────────────┐
│                         UI Layer                                 │
│  ┌──────────────┐  ┌──────────────┐  ┌──────────────┐          │
│  │  TextualApp  │  │   Screens    │  │  Renderers   │          │
│  │  (app.py)    │  │ (setup,      │  │  (tools,     │          │
│  │              │  │  picker)     │  │   panels)    │          │
│  └──────────────┘  └──────────────┘  └──────────────┘          │
└──────────────────────────────────────────────────────────────────┘
         │                      │                      │
         │ requests             │ renders             │ callbacks
         ▼                      ▼                      ▼
┌──────────────────────────────────────────────────────────────────┐
│                        Core Layer                                │
│  ┌──────────────┐  ┌──────────────┐  ┌──────────────┐          │
│  │   Agent      │  │ Request      │  │  State       │          │
│  │  Config      │  │Orchestrator  │  │  Manager     │          │
│  └──────────────┘  └──────────────┘  └──────────────┘          │
└──────────────────────────────────────────────────────────────────┘
         │                      │                      │
         │ configures           │ orchestrates        │ manages
         ▼                      ▼                      ▼
┌──────────────────────────────────────────────────────────────────┐
│                       Tools Layer                                │
│  ┌──────────────┐  ┌──────────────┐  ┌──────────────┐          │
│  │    Bash      │  │    Grep      │  │  Read File   │          │
│  │   Tool       │  │    Tool      │  │    Tool      │          │
│  └──────────────┘  └──────────────┘  └──────────────┘          │
│  ┌──────────────┐  ┌──────────────┐  ┌──────────────┐          │
│  │    Glob      │  │    Tool      │  │   Decorators │          │
│  │   Tool       │  │  Utilities   │  │              │          │
│  └──────────────┘  └──────────────┘  └──────────────┘          │
└──────────────────────────────────────────────────────────────────┘
         │                      │                      │
         │ reads                │ uses                │ provides
         ▼                      ▼                      ▼
┌──────────────────────────────────────────────────────────────────┐
│                   Configuration Layer                            │
│  ┌──────────────┐  ┌──────────────┐  ┌──────────────┐          │
│  │   Models     │  │   Defaults   │  │   Settings   │          │
│  │  Registry    │  │              │  │              │          │
│  └──────────────┘  └──────────────┘  └──────────────┘          │
└──────────────────────────────────────────────────────────────────┘

Dependency Graph

                    ┌─────────────┐
                    │    UI       │
                    └──────┬──────┘
                           │
          ┌────────────────┼────────────────┐
          ▼                ▼                ▼
    ┌───────────┐    ┌───────────┐    ┌───────────┐
    │   Core    │───▶│   Tools   │    │    LSP    │
    └─────┬─────┘    └─────┬─────┘    └───────────┘
          │                │
          └────────┬───────┘
                   ▼
            ┌──────────────┐
            │Configuration │
            └──────────────┘

Note: Dependency direction is one-way here:

• core imports tool functions for orchestration
• tools do not import from core

3. Data Flow

Complete Request Lifecycle

USER INPUT
    │
    ▼
┌───────────────────────────────────────────────────────────────┐
│ 1. INPUT CAPTURE (UI Layer)                                   │
│    - User types in Editor widget (ui/app.py)                 │
│    - EditorSubmitRequested message posted                     │
│    - Message placed on request_queue                          │
└───────────────────────────────────────────────────────────────┘
    │
    ▼
┌───────────────────────────────────────────────────────────────┐
│ 2. REQUEST PROCESSING (Core Layer)                            │
│    - _request_worker dequeues from request_queue              │
│    - Calls process_request() (core/agents/main.py)           │
│    - RequestOrchestrator instantiated                          │
│    - Agent created/retrieved from cache                       │
└───────────────────────────────────────────────────────────────┘
    │
    ▼
┌───────────────────────────────────────────────────────────────┐
│ 3. AGENT EXECUTION (Core Layer)                               │
│    - System prompt composed from sections                     │
│    - Agent.iter() loop begins                                 │
│    - Model request sent to LLM API                            │
│    - Response streamed back                                   │
└───────────────────────────────────────────────────────────────┘
    │
    ▼
┌───────────────────────────────────────────────────────────────┐
│ 4. TOOL SELECTION (Core Layer)                                │
│    - Node processor inspects response                         │
│    - Tool calls extracted from structured output              │
│    - tool_callback invoked (ui/repl_support.py)              │
└───────────────────────────────────────────────────────────────┘
    │
    ▼
┌───────────────────────────────────────────────────────────────┐
│ 5. TOOL DISPATCH (Core Layer)                                 │
│    - Tool calls registered and batched                        │
│    - Parallel execution scheduled                             │
└───────────────────────────────────────────────────────────────┘
    │
    ▼
┌───────────────────────────────────────────────────────────────┐
│ 6. TOOL EXECUTION (Tools Layer)                               │
│    - Tool function executed (e.g., bash, grep)                │
│    - Return value captured                                    │
│    - Results recorded in the run message history              │
└───────────────────────────────────────────────────────────────┘
    │
    ▼
┌───────────────────────────────────────────────────────────────┐
│ 7. RESPONSE RENDERING (UI Layer)                              │
│    - streaming_callback updates streaming_output              │
│    - tool_result_callback creates Panel for results           │
│    - Final response written to RichLog                        │
│    - Token usage and cost calculated                          │
└───────────────────────────────────────────────────────────────┘
    │
    ▼
STATE UPDATE
    │
    ▼
┌───────────────────────────────────────────────────────────────┐
│ 8. STATE MANAGEMENT (Core Layer)                              │
│    - SessionState messages synced from agent_run history       │
│    - Token usage updated                                      │
│    - Context window managed via compaction                    │
└───────────────────────────────────────────────────────────────┘

Callback Communication Flow

┌─────────────────┐                    ┌─────────────────┐
│      UI         │                    │      Core       │
│  (TextualApp)   │                    │ (Orchestrator)  │
└────────┬────────┘                    └────────┬────────┘
         │                                     │
         │  streaming_callback(text)           │
         │  tool_callback(tool_name)           │
         │  tool_result_callback(result)       │
         │  tool_start_callback()              │
         │------------------------------------>│
         │                                     │
         │                                     │  Execute tool
         │                                     │  Stream response
         │                                     │
         │  Update UI widgets                  │
         │  Show confirmation dialog           │
         │  Render tool output                 │
         │<-------------------------------------│
         │                                     │

4. Design Patterns

1. Factory & Singleton Pattern

Location: src/tunacode/core/agents/agent_components/agent_config.py

def get_or_create_agent(model: ModelName, state_manager: StateManager) -> PydanticAgent:
    # Factory: Creates agent instances
    # Singleton: Caches agents per model
    if model not in _agent_cache:
        agent = Agent(
            model=model_instance,
            system_prompt=system_prompt,
            tools=tools_list,
        )
        _agent_cache[model] = agent
    return _agent_cache[model]

Purpose: Avoid expensive re-initialization of agents while allowing dynamic creation.

2. Strategy Pattern

Location: src/tunacode/tools/grep.py

def grep(..., search_type: Literal["smart", "ripgrep", "python", "hybrid"] = "smart"):
    # Dynamically selects search algorithm based on context
    if search_type == "smart":
        # Choose best algorithm automatically
    elif search_type == "ripgrep":
        # Use ripgrep
    elif search_type == "python":
        # Use pure Python

Purpose: Allow runtime selection of search algorithms based on file count and context.

3. Decorator Pattern

Location: src/tunacode/tools/decorators.py

@file_tool
def read_file(file_path: str) -> str:
    # Decorator adds error handling and LSP diagnostics
    ...

@base_tool
def bash(command: str) -> str:
    # Decorator adds error handling and retry logic
    ...

Purpose: Add cross-cutting concerns (error handling, retries) without cluttering tool logic.

4. Observer Pattern

Location: Throughout UI/Core communication

# Core notifies UI of state changes
async def process_request(
    streaming_callback: Callable[[str], None],
    tool_callback: Callable[[ToolCall], None],
    tool_result_callback: Callable[[ToolResult], None],
    ...
):
    # Core (Subject) notifies UI (Observer) via callbacks
    await streaming_callback(token)
    await tool_callback(tool_call)
    await tool_result_callback(result)

Purpose: Enable UI to react to core events without tight coupling.

5. Composite Pattern

Location: src/tunacode/core/agents/delegation_tools.py

# A tool that is itself an agent
def research_codebase(query: str) -> str:
    # Main agent delegates to specialized research agent
    research_agent = get_or_create_agent(model, ...)
    return await research_agent.run(query)

Purpose: Enable hierarchical agent organization where agents can delegate to specialized sub-agents.

6. State Management Pattern

Location: src/tunacode/core/state.py

class StateManager:
    def __init__(self):
        self.session = SessionState(
            messages=[],
            model=None,
            token_usage=TokenUsage(),
            ...
        )

# Centralized state store passed to all components
state_manager = StateManager()
app = TextualReplApp(state_manager=state_manager)

Purpose: Single source of truth for application state, avoiding scattered state management.

5. Module Dependencies

Dependency Hierarchy

Level 0 (Foundation):
├── constants
├── types
└── exceptions

Level 1 (Utilities):
├── configuration
│   ├── models (model registry, pricing)
│   ├── defaults (default config)
│   └── settings (API keys, user config)
├── utils
│   ├── config
│   ├── messaging
│   ├── parsing
│   └── system
├── lsp
├── prompting
│   └── sections
└── indexing

Level 2 (Core Logic):
├── core
│   ├── agents (agent orchestration)
│   ├── background (async task management)
│   ├── logging
│   ├── setup
│   └── token_usage
└── tools
    ├── grep_components
    ├── prompts
    └── utils

Level 3 (Application):
├── ui
│   ├── screens (setup, picker, confirm)
│   ├── renderers (tools, panels)
│   ├── components
│   ├── widgets
│   └── styles
└── services (currently empty)

Import Flow Analysis

Tightly Coupled:

• core -> tools (one-way orchestration dependency)
  • core imports tool functions for agent configuration and dispatch

Loosely Coupled:

• configuration - Standalone, only depends on foundation types
• constants, types, exceptions - No internal dependencies
• indexing, lsp, prompting - Limited, specific dependencies

Highly Coupled to UI:

• ui depends on nearly all modules (core, tools, configuration, indexing, lsp)

External Dependencies

6. Key Architectural Decisions

Decision 1: UI/Core Decoupling

Rationale: Enable headless execution, simplify testing, support future UI implementations

Implementation:

• Callback-based communication
• StateManager as shared state object
• Core logic has no Textual dependencies

Files:

• <repo_root>/src/tunacode/ui/app.py
• <repo_root>/src/tunacode/core/agents/main.py

Decision 2: Modular System Prompts

Rationale: Make prompts maintainable, composable, and customizable per agent type

Implementation:

• Prompts composed from sections in src/tunacode/core/prompting/sections/
• SectionLoader and compose_prompt for assembly
• Different agents use different prompt combinations

Files:

• <repo_root>/src/tunacode/core/prompting/
• <repo_root>/src/tunacode/prompts/sections/

Decision 3: Agent as Iterator

Rationale: Provide clean, pull-based model for consuming agent execution steps

Implementation:

• Agent execution exposed as async iterator
• UI consumes steps as they arrive
• Avoids callback hell

Files:

• <repo_root>/src/tunacode/core/agents/main.py

Decision 4: Centralized State Management

Rationale: Single source of truth, explicit state changes, easier debugging

Implementation:

• SessionState dataclass holds all session data
• StateManager provides access and updates
• State passed to key components

Files:

• <repo_root>/src/tunacode/core/state.py

7. Separation of Concerns

UI Layer (src/tunacode/ui/)

Responsibility: Presentation and user interaction

Key Files:

• app.py - Main Textual application
• screens/ - Setup, picker, and confirmation screens
• renderers/ - Tool output rendering
• components/ - Reusable UI components
• widgets/ - Custom widgets

Does NOT:

• Execute tool logic
• Make agent decisions
• Manage business logic

Core Layer (src/tunacode/core/)

Responsibility: Agent orchestration and business logic

Key Files:

• agents/main.py - Request processing entry point
• agents/agent_config.py - Agent factory
• agents/agent_components/node_processor.py - Response processing
• state.py - State management
• prompting/ - Prompt composition

Does NOT:

• Render UI
• Execute file operations directly
• Handle Textual framework details

Tools Layer (src/tunacode/tools/)

Responsibility: Agent capabilities and system interactions

Key Files:

• bash.py - Shell command execution
• grep.py - Code search
• read_file.py - File reading

Does NOT:

• Orchestrate agent flow
• Render output
• Manage UI state

Configuration Layer (src/tunacode/configuration/)

Responsibility: Settings and model data

Key Files:

• models.py - Model registry
• defaults.py - Default configuration
• settings.py - User settings

Does NOT:

• Execute logic
• Manage state
• Interact with UI

8. Anti-Patterns and Technical Debt

Circular Dependency: Core ↔ Tools

Issue:

• core imports tool functions
• Some tools import from core

Impact:

• Difficult to test in isolation
• Complex initialization order
• Harder to reason about

Potential Solutions:

1. Extract shared interfaces to a separate module
2. Use dependency injection
3. Move shared functionality to a utilities module

Current Locations

Core → Tools:

• <repo_root>/src/tunacode/core/agents/agent_components/agent_config.py

Tools → Core:

• <repo_root>/src/tunacode/tools/todo.py

9. Extension Points

Adding a New Tool

1. Create tool function in <repo_root>/src/tunacode/tools/
2. Decorate with @file_tool or @base_tool
3. Add to tools list in agent_config.py
4. Optionally create custom renderer in ui/renderers/tools/

Adding a New Agent Type

1. Create prompt sections in <repo_root>/src/tunacode/prompts/sections/
2. Compose prompt using compose_prompt()
3. Configure tools for agent type
4. Add agent factory logic

Adding a New UI Screen

1. Create screen class in <repo_root>/src/tunacode/ui/screens/
2. Integrate with TextualReplApp
3. Add navigation logic

10. Testing Strategy

Current Test Coverage

Located in <repo_root>/tests/:

• Tool decorator tests
• Tool conformance tests
• Compaction tests
• Tool retry logic tests

Testing Challenges

1. Circular Dependency: Makes unit testing difficult
2. Async Code: Requires pytest-asyncio
3. UI Code: Textual framework requires specialized testing

Recommended Testing Approach

1. Unit Tests: Test tools in isolation
2. Integration Tests: Test core orchestration with mock tools
3. E2E Tests: Test full request flow with real tools
4. UI Tests: Use textual-dev for screen testing

11. Performance Considerations

Token Management

• Context window managed via prune_old_tool_outputs()
• Token usage tracked per request and session
• Cost calculation based on model pricing

Caching

• Agent instances cached per model
• Code index cached
• Model registry lazy-loaded

Async Operations

• All I/O operations are async
• Background tasks for long-running operations
• Non-blocking UI updates

13. Security Considerations

Tool Safety

• Tool definitions enforce validation and limits
• Bash commands validated before execution
• File operations enforce size and path checks

Input Validation

• Pydantic models for all inputs
• Path sanitization for file operations
• Shell command validation

Dependency Security

• defusedxml for secure XML parsing
• Bandit security scanning configured
• Regular dependency updates

Conclusion

Tunacode demonstrates a well-structured, modular architecture with clear separation of concerns. The primary architectural strength is the UI/Core decoupling, enabling multiple UI implementations and headless operation. Core-to-tools dependencies are now one-way, keeping the tool layer isolated from core internals.

The callback-based communication pattern, centralized state management, and composable system prompts all contribute to a maintainable and extensible codebase.

Generated: 2026-01-04 Analysis Tool: Gemini MCP (gemini-2.5-pro) Codebase Version: 0.1.20