from typing import Optional
from pydantic import BaseModel
import warnings

class Config(BaseModel):
    """Root configuration model."""

    # New section (preferred)
    adapters: Optional[dict[str, AdapterConfig]] = None

    # Legacy section (deprecated)
    cli_tools: Optional[dict[str, CLIToolConfig]] = None

    def model_post_init(self, __context):
        """Post-initialization validation."""
        # Ensure at least one section exists
        if self.adapters is None and self.cli_tools is None:
            raise ValueError(
                "Configuration must include either 'adapters' or 'cli_tools' section"
            )

        # Emit deprecation warning for old section
        if self.cli_tools is not None and self.adapters is None:
            warnings.warn(
                "The 'cli_tools' configuration section is deprecated. "
                "Please migrate to 'adapters' section with explicit 'type' field. "
                "See migration guide: docs/migration/cli_tools_to_adapters.md",
                DeprecationWarning,
                stacklevel=2,
            )

from typing import Annotated, Literal, Union
from pydantic import BaseModel, Field

class CLIAdapterConfig(BaseModel):
    """Configuration for CLI-based adapter."""
    type: Literal["cli"] = "cli"
    command: str
    args: list[str]
    timeout: int = 60

class HTTPAdapterConfig(BaseModel):
    """Configuration for HTTP-based adapter."""
    type: Literal["http"] = "http"
    base_url: str
    api_key: Optional[str] = None
    timeout: int = 60
    max_retries: int = 3

# Discriminated union - Pydantic uses 'type' field to determine which model
AdapterConfig = Annotated[
    Union[CLIAdapterConfig, HTTPAdapterConfig],
    Field(discriminator="type")
]

adapters:
  claude:
    type: cli  # Discriminator field
    command: "claude"
    args: ["-p", "{prompt}"]
    timeout: 60

  ollama:
    type: http  # Different type triggers HTTPAdapterConfig
    base_url: "http://localhost:11434"
    timeout: 120

import os
import re
from pydantic import BaseModel, field_validator

class HTTPAdapterConfig(BaseModel):
    """Configuration for HTTP-based adapter."""
    base_url: str
    api_key: Optional[str] = None

    @field_validator("api_key", "base_url")
    @classmethod
    def resolve_env_vars(cls, v: Optional[str], info) -> Optional[str]:
        """Resolve ${ENV_VAR} references in string fields."""
        if v is None:
            return v

        # Pattern: ${VAR_NAME}
        pattern = r"\$\{([^}]+)\}"
        is_api_key = info.field_name == "api_key"

        def replacer(match):
            env_var = match.group(1)
            value = os.getenv(env_var)
            if value is None:
                # For optional fields like api_key, use sentinel
                if is_api_key:
                    return "__MISSING_API_KEY__"
                # For required fields, raise error
                raise ValueError(
                    f"Environment variable '{env_var}' is not set. "
                    f"Required for configuration."
                )
            return value

        result = re.sub(pattern, replacer, v)

        # If api_key has sentinel marker, return None (graceful degradation)
        if is_api_key and "__MISSING_API_KEY__" in result:
            return None

        return result

adapters:
  openrouter:
    type: http
    base_url: "https://openrouter.ai/api/v1"
    api_key: "${OPENROUTER_API_KEY}"  # Resolved from environment

#!/usr/bin/env python3
"""
Migration script: cli_tools → adapters

Migrates config.yaml from legacy cli_tools format to new adapters format
with explicit type fields.

Usage:
    python scripts/migrate_config.py [path/to/config.yaml]
"""

import shutil
import sys
from pathlib import Path
from typing import Any, Dict
import yaml

def migrate_config_dict(config: Dict[str, Any]) -> Dict[str, Any]:
    """
    Migrate config dictionary from cli_tools to adapters format.

    Returns:
        Migrated config with adapters section
    """
    # If already migrated, return as-is
    if "adapters" in config and "cli_tools" not in config:
        print("Info: Config already migrated (has 'adapters' section)")
        return config

    # If no cli_tools, nothing to migrate
    if "cli_tools" not in config:
        print("Warning: No 'cli_tools' section found, nothing to migrate")
        return config

    # Create new config with adapters
    migrated = config.copy()

    # Transform cli_tools → adapters
    adapters = {}
    for name, cli_config in config["cli_tools"].items():
        adapters[name] = {
            "type": "cli",  # Add explicit type discriminator
            "command": cli_config["command"],
            "args": cli_config["args"],
            "timeout": cli_config["timeout"],
        }

    migrated["adapters"] = adapters
    del migrated["cli_tools"]

    print(f"Success: Migrated {len(adapters)} CLI tools to adapters format")
    return migrated

def migrate_config_file(path: str) -> None:
    """
    Migrate config file from cli_tools to adapters format.

    Creates a backup at {path}.bak before modifying.
    """
    config_path = Path(path)

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

    # Create backup BEFORE modifying
    backup_path = Path(f"{path}.bak")
    shutil.copy2(config_path, backup_path)
    print(f"Created backup: {backup_path}")

    # Load config
    with open(config_path, "r") as f:
        config = yaml.safe_load(f)

    # Migrate
    migrated = migrate_config_dict(config)

    # Write migrated config
    with open(config_path, "w") as f:
        yaml.dump(migrated, f, default_flow_style=False, sort_keys=False)

    print(f"Migrated config written to: {config_path}")
    print(f"\nInfo: Review the changes and delete {backup_path} when satisfied.")

def main():
    """Main entry point."""
    config_path = sys.argv[1] if len(sys.argv) > 1 else "config.yaml"

    print(f"Migrating config: {config_path}")
    print("-" * 50)

    try:
        migrate_config_file(config_path)
        print("\nMigration complete!")
        print("\nNext steps:")
        print("1. Review the migrated config.yaml")
        print("2. Test loading: python -c 'from models.config import load_config; load_config()'")
        print("3. Delete backup if satisfied: rm config.yaml.bak")
    except Exception as e:
        print(f"\nError: Migration failed: {e}")
        sys.exit(1)

if __name__ == "__main__":
    main()

import os
import re
from pathlib import Path
from pydantic import BaseModel, field_validator

class DecisionGraphConfig(BaseModel):
    """Configuration for decision graph memory."""
    db_path: str = "decision_graph.db"

    @field_validator("db_path")
    @classmethod
    def resolve_db_path(cls, v: str) -> str:
        """
        Resolve db_path to absolute path relative to project root.

        Processing steps:
        1. Resolve ${ENV_VAR} environment variable references
        2. Convert relative paths to absolute paths relative to project root
        3. Keep absolute paths unchanged
        4. Return normalized absolute path as string

        Examples:
            "decision_graph.db" → "/path/to/project/decision_graph.db"
            "/tmp/foo.db" → "/tmp/foo.db" (unchanged)
            "${DATA_DIR}/graph.db" → "/var/data/graph.db" (if DATA_DIR=/var/data)
        """
        # Step 1: Resolve environment variables
        pattern = r"\$\{([^}]+)\}"

        def replacer(match):
            env_var = match.group(1)
            value = os.getenv(env_var)
            if value is None:
                raise ValueError(
                    f"Environment variable '{env_var}' is not set. "
                    f"Required for db_path configuration."
                )
            return value

        resolved = re.sub(pattern, replacer, v)

        # Step 2: Convert to Path object
        path = Path(resolved)

        # Step 3: If relative, make it relative to project root
        if not path.is_absolute():
            # This file is at: project_root/models/config.py
            # Project root is two levels up from this file
            project_root = Path(__file__).parent.parent
            path = (project_root / path).resolve()

        # Step 4: Return as string (normalized, absolute)
        return str(path)

from pydantic import BaseModel, Field, field_validator

class DecisionGraphConfig(BaseModel):
    """Configuration for decision graph memory."""

    # DEPRECATED field (kept for backward compatibility)
    similarity_threshold: float = Field(
        0.7,
        ge=0.0,
        le=1.0,
        description="DEPRECATED: Use tier_boundaries instead.",
    )

    # NEW field (preferred)
    tier_boundaries: dict[str, float] = Field(
        default_factory=lambda: {"strong": 0.75, "moderate": 0.60},
        description="Similarity score boundaries for tiered injection"
    )

    @field_validator("tier_boundaries")
    @classmethod
    def validate_tier_boundaries(cls, v: dict[str, float]) -> dict[str, float]:
        """Validate tier boundaries: strong > moderate > 0."""
        if not isinstance(v, dict) or "strong" not in v or "moderate" not in v:
            raise ValueError("tier_boundaries must have 'strong' and 'moderate' keys")

        if not (0.0 < v["moderate"] < v["strong"] <= 1.0):
            raise ValueError(
                f"tier_boundaries must satisfy: 0 < moderate ({v['moderate']}) "
                f"< strong ({v['strong']}) <= 1"
            )

        return v

decision_graph:
  # OLD (still works, but deprecated in field description)
  similarity_threshold: 0.7

  # NEW (preferred)
  tier_boundaries:
    strong: 0.75
    moderate: 0.60