# coding: utf-8

"""
    Mixpeek API

    This is the Mixpeek API, providing access to various endpoints for data processing and retrieval.

    The version of the OpenAPI document: 1.3.0
    Contact: info@mixpeek.com
    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, StrictStr
from typing import Any, ClassVar, Dict, List, Optional
from typing_extensions import Annotated
from typing import Optional, Set
from typing_extensions import Self

class StageParamsRerank(BaseModel):
    """
    Configuration for reranking documents using cross-encoder models.  Reranking refines search results by computing query-document relevance scores using cross-encoder models (e.g., BGE reranker). More accurate than vector similarity but slower, so typically used on top-K results.  Common Pipeline:     feature_filter (retrieve 100) → rerank (refine to 10) → sort_relevance
    """ # noqa: E501
    inference_name: Optional[StrictStr] = Field(default='baai_bge_reranker_v2_m3', description="Reranking inference service name. Must be a reranking service. Use GET /engine/inference to list available rerankers.")
    query: Optional[StrictStr] = Field(default='{{INPUT.query}}', description="Query text to compare against documents. Supports template variables: {{INPUT.query}}, etc.")
    document_field: Optional[StrictStr] = Field(default='content', description="Document field path containing text to rerank against")
    top_k: Optional[Annotated[int, Field(strict=True, ge=1)]] = Field(default=null, description="Number of top documents to keep after reranking. If None, returns all documents in reranked order.")
    score_field: Optional[StrictStr] = Field(default='scores.rerank', description="Document field path to store reranking scores")
    batch_size: Optional[Annotated[int, Field(le=100, strict=True, ge=1)]] = Field(default=32, description="Batch size for reranking inference calls")
    __properties: ClassVar[List[str]] = ["inference_name", "query", "document_field", "top_k", "score_field", "batch_size"]

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

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

        _obj = cls.model_validate({
            "inference_name": obj.get("inference_name") if obj.get("inference_name") is not None else 'baai_bge_reranker_v2_m3',
            "query": obj.get("query") if obj.get("query") is not None else '{{INPUT.query}}',
            "document_field": obj.get("document_field") if obj.get("document_field") is not None else 'content',
            "top_k": obj.get("top_k") if obj.get("top_k") is not None else null,
            "score_field": obj.get("score_field") if obj.get("score_field") is not None else 'scores.rerank',
            "batch_size": obj.get("batch_size") if obj.get("batch_size") is not None else 32
        })
        return _obj


