from pydantic import BaseModel, Field
from typing import List, Optional, Dict, Any, Union

class SkillDto(BaseModel):
    id: Optional[int] = None
    name: str

class DomainDto(BaseModel):
    id: Optional[int] = None
    name: str

class CareerDto(BaseModel):
    id: Optional[int] = None
    name: str

class ExperienceDto(BaseModel):
    company: Optional[str] = None
    position: Optional[str] = None
    start_date: Optional[str] = None
    end_date: Optional[str] = None
    description: Optional[str] = None

class EducationDto(BaseModel):
    school: Optional[str] = None
    degree: Optional[str] = None
    start_date: Optional[str] = None
    end_date: Optional[str] = None
    description: Optional[str] = None

class MentorUpsertRequest(BaseModel):
    mentor_id: int
    full_name: Optional[str] = None
    bio: Optional[str] = None
    career: Optional[Union[CareerDto, Dict[str, Any], str]] = None
    skills: Optional[List[Union[SkillDto, Dict[str, Any], str]]] = None
    domains: Optional[List[Union[DomainDto, Dict[str, Any], str]]] = None
    experiences: Optional[List[Union[ExperienceDto, Dict[str, Any]]]] = None
    educations: Optional[List[Union[EducationDto, Dict[str, Any]]]] = None
    rating: Optional[float] = Field(None, ge=0.0, le=5.0)
    total_ratings: Optional[int] = Field(None, ge=0)
    session_count: Optional[int] = Field(None, ge=0)
    career_id: Optional[int] = None
    skill_ids: Optional[List[int]] = None
    domain_ids: Optional[List[int]] = None
    status: Optional[str] = "ACTIVATED"

class MentorUpsertResponse(BaseModel):
    success: bool
    message: str
    mentor_id: int

class RecommendationRequest(BaseModel):
    goals: Optional[str] = None
    skill_ids: Optional[List[int]] = None
    domain_ids: Optional[List[int]] = None
    mentor_domain_ids: Optional[List[int]] = None
    career_id: Optional[int] = None
    career_name: Optional[str] = None
    domain_names: Optional[List[str]] = None
    mentor_domain_names: Optional[List[str]] = None
    skill_names: Optional[List[str]] = None
    top_k: Optional[int] = Field(None, ge=1, le=100)
    final_count: Optional[int] = Field(None, ge=1, le=20)

class RecommendedMentor(BaseModel):
    mentor_id: str
    score: float
    semantic_similarity: float
    reason: str
    metadata: Dict[str, Any]

class RecommendationResponse(BaseModel):
    mentors: List[RecommendedMentor]
    count: int
    query_text: Optional[str] = None

class HealthResponse(BaseModel):
    status: str
    embedding_model: Dict[str, Any]
    pinecone_index: Dict[str, Any]

class BatchUpsertRequest(BaseModel):
    mentors: List[MentorUpsertRequest]

class BatchUpsertResponse(BaseModel):
    success: bool
    message: str
    upserted_count: int
    failed_count: int