SneakyCode/app/models/config.py

"""Pydantic configuration models mapping to config/config.yaml."""

import os
from pathlib import Path
from typing import Any

import yaml
from pydantic import BaseModel, Field, model_validator


class LLMConfig(BaseModel):
    """LLM backend configuration."""

    model: str = Field(description="Model name to use")
    endpoint: str = Field(description="Base URL of the LLM API")
    api_path: str = Field(default="/v1/chat/completions", description="API endpoint path")
    temperature: float = Field(default=0.1, description="Sampling temperature")
    max_tokens: int = Field(default=4096, description="Maximum tokens in LLM response")
    timeout: int = Field(default=120, description="Request timeout in seconds")
    max_retries: int = Field(default=3, description="Max retry attempts on transient errors")
    retry_backoff_base: float = Field(default=1.0, description="Base seconds for exponential backoff")
    retry_backoff_max: float = Field(default=30.0, description="Maximum backoff seconds")
    thinking: bool = Field(
        default=True,
        description="Enable model thinking/reasoning mode (disable to reduce reasoning-only loops)",
    )
    extra_body: dict[str, Any] = Field(
        default_factory=dict,
        description="Extra parameters merged into the API request body (model-specific)",
    )


class AgentConfig(BaseModel):
    """Agent loop configuration."""

    max_iterations: int = Field(default=25, description="Maximum tool-call loop iterations")
    max_conversation_tokens: int = Field(
        default=32000, description="Token budget for conversation history"
    )
    workspace_root: Path = Field(
        default=Path("."), description="Root directory for file operations"
    )
    truncation_keep_recent: int = Field(
        default=10, description="Number of recent messages to preserve during truncation"
    )
    truncation_threshold: float = Field(
        default=0.85, description="Token budget fraction that triggers truncation"
    )


class PermissionsConfig(BaseModel):
    """Tool permission tiers."""

    auto_approve: list[str] = Field(default_factory=list, description="Auto-approved tools")
    prompt_user: list[str] = Field(default_factory=list, description="Tools requiring confirmation")
    deny: list[str] = Field(default_factory=list, description="Tools that are blocked entirely")


class ShellToolConfig(BaseModel):
    """Shell tool restrictions."""

    allowed_commands: list[str] = Field(default_factory=list, description="Allowed shell commands")
    denied_commands: list[str] = Field(default_factory=list, description="Blocked shell commands")
    max_output_bytes: int = Field(default=65536, description="Max output capture size in bytes")


class FilesystemToolConfig(BaseModel):
    """Filesystem tool limits."""

    max_file_size_bytes: int = Field(default=1_048_576, description="Max file size for read/write")
    binary_detection: bool = Field(default=True, description="Detect and reject binary files")


class ToolsConfig(BaseModel):
    """Aggregate tool configuration."""

    shell: ShellToolConfig = Field(default_factory=ShellToolConfig)
    filesystem: FilesystemToolConfig = Field(default_factory=FilesystemToolConfig)


class SessionConfig(BaseModel):
    """Session persistence configuration."""

    session_dir: Path = Field(
        default=Path(".sneakycode/sessions"), description="Directory for session files"
    )
    auto_save: bool = Field(default=True, description="Auto-save session after each turn")
    max_session_age_hours: int = Field(
        default=72, description="Max age in hours before session files are cleaned up"
    )
    offer_resume: bool = Field(default=True, description="Offer to resume previous sessions on startup")


class DisplayConfig(BaseModel):
    """Terminal display preferences."""

    show_tool_calls: bool = Field(default=True, description="Show tool call details in output")
    show_token_usage: bool = Field(default=True, description="Show token usage stats")
    stream_output: bool = Field(default=True, description="Stream LLM output to terminal")


class SkillsConfig(BaseModel):
    """Skills system configuration."""

    enabled: bool = Field(default=True, description="Enable skills system")
    directories: list[Path] = Field(
        default_factory=lambda: [Path(".sneakycode/skills")],
        description="Directories to scan for skill markdown files",
    )


class DebugConfig(BaseModel):
    """Debug logging configuration."""

    enabled: bool = Field(default=False, description="Enable debug logging")
    log_dir: Path = Field(default=Path(".sneakycode/logs"), description="Debug log directory")
    max_files: int = Field(default=10, description="Max debug log files to retain")


class AppConfig(BaseModel):
    """Top-level application configuration composing all sub-configs."""

    llm: LLMConfig
    agent: AgentConfig = Field(default_factory=AgentConfig)
    permissions: PermissionsConfig = Field(default_factory=PermissionsConfig)
    tools: ToolsConfig = Field(default_factory=ToolsConfig)
    display: DisplayConfig = Field(default_factory=DisplayConfig)
    session: SessionConfig = Field(default_factory=SessionConfig)
    debug: DebugConfig = Field(default_factory=DebugConfig)
    skills: SkillsConfig = Field(default_factory=SkillsConfig)

    @model_validator(mode="after")
    def resolve_workspace_root(self) -> "AppConfig":
        """Resolve workspace_root to an absolute path."""
        self.agent.workspace_root = self.agent.workspace_root.resolve()
        return self


# Default config file location relative to project root
_DEFAULT_CONFIG_PATH = Path("config/config.yaml")


def load_config(config_path: Path | None = None) -> AppConfig:
    """Load and validate application config from YAML.

    Resolution order:
    1. Explicit config_path argument
    2. SNEAKYCODE_CONFIG environment variable
    3. config/config.yaml (default)

    Args:
        config_path: Optional explicit path to config file.

    Returns:
        Validated AppConfig instance.

    Raises:
        FileNotFoundError: If the resolved config file does not exist.
        ValueError: If the config file is invalid YAML or fails validation.
    """
    if config_path is None:
        env_path = os.environ.get("SNEAKYCODE_CONFIG")
        if env_path:
            config_path = Path(env_path)
        else:
            config_path = _DEFAULT_CONFIG_PATH

    config_path = config_path.resolve()

    if not config_path.exists():
        raise FileNotFoundError(f"Config file not found: {config_path}")

    with open(config_path) as f:
        raw = yaml.safe_load(f)

    if not isinstance(raw, dict):
        raise ValueError(f"Config file must contain a YAML mapping, got {type(raw).__name__}")

    return AppConfig(**raw)