# coding: utf-8

"""
    Blackman AI API

    A transparent AI API proxy that optimizes token usage to reduce costs.  ## Authentication  Blackman AI supports two authentication methods:  ### 1. API Key (Recommended for integrations)  Use the API key created from your dashboard:  ```bash curl -X POST https://ap.useblackman.ai/v1/completions \\   -H \"Authorization: Bearer sk_your_api_key_here\" \\   -H \"Content-Type: application/json\" \\   -d '{\"provider\": \"OpenAI\", \"model\": \"gpt-4\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}' ```  ### 2. JWT Token (For web UI)  Obtain a JWT token by logging in:  ```bash curl -X POST https://ap.useblackman.ai/v1/auth/login \\   -H \"Content-Type: application/json\" \\   -d '{\"email\": \"user@example.com\", \"password\": \"yourpassword\"}' ```  Then use the token:  ```bash curl -X POST https://ap.useblackman.ai/v1/completions \\   -H \"Authorization: Bearer your_jwt_token\" \\   -H \"Content-Type: application/json\" \\   -d '{...}' ```  ### Provider API Keys (Optional)  You can optionally provide your own LLM provider API key via the `X-Provider-Api-Key` header, or store it in your account settings.  ## Client SDKs  Auto-generated SDKs are available for 10 languages:  - **TypeScript**: [View Docs](/v1/sdks/typescript) - **Python**: [View Docs](/v1/sdks/python) - **Go**: [View Docs](/v1/sdks/go) - **Java**: [View Docs](/v1/sdks/java) - **Ruby**: [View Docs](/v1/sdks/ruby) - **PHP**: [View Docs](/v1/sdks/php) - **C#**: [View Docs](/v1/sdks/csharp) - **Rust**: [View Docs](/v1/sdks/rust) - **Swift**: [View Docs](/v1/sdks/swift) - **Kotlin**: [View Docs](/v1/sdks/kotlin)  All SDKs are generated from this OpenAPI spec using [openapi-generator](https://openapi-generator.tech).  ## Quick Start  ```python # Python example with API key import blackman_client from blackman_client import CompletionRequest  configuration = blackman_client.Configuration(     host=\"http://localhost:8080\",     access_token=\"sk_your_api_key_here\"  # Your Blackman API key )  with blackman_client.ApiClient(configuration) as api_client:     api = blackman_client.CompletionsApi(api_client)     response = api.completions(         CompletionRequest(             provider=\"OpenAI\",             model=\"gpt-4o\",             messages=[{\"role\": \"user\", \"content\": \"Hello!\"}]         )     ) ```

    The version of the OpenAPI document: 0.1.0
    Generated by OpenAPI Generator (https://openapi-generator.tech)

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


from __future__ import annotations
import pprint
import re  # noqa: F401
import json

from pydantic import BaseModel, ConfigDict, Field, StrictBool, StrictFloat, StrictInt
from typing import Any, ClassVar, Dict, List, Union
from typing import Optional, Set
from typing_extensions import Self

class SemanticCacheConfig(BaseModel):
    """
    SemanticCacheConfig
    """ # noqa: E501
    enabled: StrictBool = Field(description="Whether semantic caching is enabled")
    similarity_threshold: Union[StrictFloat, StrictInt] = Field(description="Similarity threshold for cache hits (0.0-1.0)")
    ttl_seconds: StrictInt = Field(description="Time-to-live for cache entries in seconds")
    __properties: ClassVar[List[str]] = ["enabled", "similarity_threshold", "ttl_seconds"]

    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 SemanticCacheConfig 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 SemanticCacheConfig from a dict"""
        if obj is None:
            return None

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

        _obj = cls.model_validate({
            "enabled": obj.get("enabled"),
            "similarity_threshold": obj.get("similarity_threshold"),
            "ttl_seconds": obj.get("ttl_seconds")
        })
        return _obj


