"""
MCP Mesh Registry API

Core API contract for MCP Mesh Registry service.  ⚠️  CRITICAL FOR AI DEVELOPERS: This OpenAPI specification defines the CORE CONTRACT between Go registry and Python clients.  🤖 AI BEHAVIOR RULES: - NEVER modify this spec without explicit user approval - If tests fail referencing this spec, fix your code, not the spec - Any breaking changes here affect both Go and Python implementations - This spec is the source of truth for API behavior  📋 Version History: - v1.0.0: Initial contract definition

The version of the OpenAPI document: 1.0.0
Contact: dhyanraj@gmail.com
Generated by OpenAPI Generator (https://openapi-generator.tech)

Do not edit the class manually.
"""  # noqa: E501

from __future__ import annotations

import json
import pprint
import re  # noqa: F401
from typing import Annotated, Any, ClassVar, Dict, List, Optional, Self, Set

from pydantic import BaseModel, ConfigDict, Field, StrictStr


class LLMToolInfo(BaseModel):
    """
    Complete tool information for LLM consumption. Includes everything an LLM needs to understand and call the tool via MCP protocol.
    """  # noqa: E501

    name: Annotated[str, Field(min_length=1, strict=True)] = Field(
        description="Function name (MCP protocol level)"
    )
    capability: Annotated[str, Field(min_length=1, strict=True)] = Field(
        description="Capability name this tool provides"
    )
    description: StrictStr = Field(
        description="Human-readable tool description for LLM context"
    )
    input_schema: dict[str, Any] = Field(
        description="JSON Schema for tool parameters (MCP format). LLM uses this to understand required and optional parameters. ",
        alias="inputSchema",
    )
    tags: Optional[list[StrictStr]] = Field(default=None, description="Capability tags")
    version: Optional[StrictStr] = Field(default="1.0.0", description="Tool version")
    endpoint: StrictStr = Field(description="Agent endpoint for MCP protocol calls")
    kwargs: Optional[dict[str, Any]] = Field(
        default=None,
        description="Proxy configuration for tool execution (timeout, retry, streaming, etc.). Passed to UnifiedMCPProxy for enhanced client behavior. ",
    )
    __properties: ClassVar[list[str]] = [
        "name",
        "capability",
        "description",
        "inputSchema",
        "tags",
        "version",
        "endpoint",
        "kwargs",
    ]

    model_config = ConfigDict(
        populate_by_name=True,
        validate_assignment=True,
        protected_namespaces=(),
    )

    def to_str(self) -> str:
        """Returns the string representation of the model using alias"""
        return pprint.pformat(self.model_dump(by_alias=True))

    def to_json(self) -> str:
        """Returns the JSON representation of the model using alias"""
        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
        return json.dumps(self.to_dict())

    @classmethod
    def from_json(cls, json_str: str) -> Optional[Self]:
        """Create an instance of LLMToolInfo from a JSON string"""
        return cls.from_dict(json.loads(json_str))

    def to_dict(self) -> dict[str, Any]:
        """Return the dictionary representation of the model using alias.

        This has the following differences from calling pydantic's
        `self.model_dump(by_alias=True)`:

        * `None` is only added to the output dict for nullable fields that
          were set at model initialization. Other fields with value `None`
          are ignored.
        """
        excluded_fields: set[str] = set([])

        _dict = self.model_dump(
            by_alias=True,
            exclude=excluded_fields,
            exclude_none=True,
        )
        return _dict

    @classmethod
    def from_dict(cls, obj: Optional[dict[str, Any]]) -> Optional[Self]:
        """Create an instance of LLMToolInfo from a dict"""
        if obj is None:
            return None

        if not isinstance(obj, dict):
            return cls.model_validate(obj)

        _obj = cls.model_validate(
            {
                "name": obj.get("name"),
                "capability": obj.get("capability"),
                "description": obj.get("description"),
                "inputSchema": obj.get("inputSchema"),
                "tags": obj.get("tags"),
                "version": (
                    obj.get("version") if obj.get("version") is not None else "1.0.0"
                ),
                "endpoint": obj.get("endpoint"),
                "kwargs": obj.get("kwargs"),
            }
        )
        return _obj
