from datetime import datetime
from typing import Any, Dict, List, Optional

from pydantic import Field, field_validator

from mirix.constants import MAX_EMBEDDING_DIM
from mirix.schemas.embedding_config import EmbeddingConfig
from mirix.schemas.mirix_base import MirixBase
from mirix.utils import get_utc_time


class EpisodicEventBase(MirixBase):
    """
    Base schema for episodic memory events containing common fields.
    """

    __id_prefix__ = "ep_mem"
    event_type: str = Field(
        ...,
        description="Type/category of the episodic event (e.g., user_message, inference, system_notification)",
    )
    summary: str = Field(..., description="Short textual summary of the event")
    details: str = Field(..., description="Detailed description or text for the event")
    actor: str = Field(
        ..., description="The actor who generated the event (user or assistant)"
    )


class EpisodicEventForLLM(EpisodicEventBase):
    """
    Schema for creating a new episodic memory record.
    """

    # TODO: make `occurred_at` optional
    occurred_at: str = Field(
        ...,
        description="When the event happened (it should be mentioned in the user's response and it should be in the format of 'YYYY-MM-DD HH:MM:SS')",
    )


class EpisodicEvent(EpisodicEventBase):
    """
    Representation of a single episodic memory event in the system.

    Additional Parameters:
        id (str): Unique identifier for this memory item
        occurred_at (datetime): When the event occurred or was recorded
        created_at (datetime): When the memory record was created in the system
        updated_at (Optional[datetime]): Last update timestamp
    """

    id: Optional[str] = Field(
        None, description="Unique identifier for the episodic event"
    )

    agent_id: Optional[str] = Field(
        None, description="The id of the agent this episodic event belongs to"
    )

    user_id: str = Field(
        ..., description="The id of the user who generated the episodic event"
    )

    occurred_at: datetime = Field(
        default_factory=get_utc_time,
        description="When the event actually happened (recorded or user-labeled).",
    )
    created_at: datetime = Field(
        default_factory=get_utc_time,
        description="Timestamp when this memory record was created",
    )
    updated_at: Optional[datetime] = Field(
        None, description="When this memory record was last updated"
    )
    last_modify: Dict[str, Any] = Field(
        default_factory=lambda: {
            "timestamp": get_utc_time().isoformat(),
            "operation": "created",
        },
        description="Last modification info including timestamp and operation type",
    )
    organization_id: str = Field(
        ..., description="Unique identifier of the organization"
    )
    details_embedding: Optional[List[float]] = Field(
        None, description="The embedding of the event"
    )
    summary_embedding: Optional[List[float]] = Field(
        None, description="The embedding of the summary"
    )
    embedding_config: Optional[EmbeddingConfig] = Field(
        None, description="The embedding configuration used by the event"
    )
    
    # NEW: Filter tags for flexible filtering and categorization
    filter_tags: Optional[Dict[str, Any]] = Field(
        default=None,
        description="Custom filter tags for filtering and categorization",
        examples=[
            {
                "project_id": "proj-abc",
                "session_id": "sess-xyz",
                "tags": ["important", "work"],
                "priority": "high"
            }
        ]
    )

    # need to validate both details_embedding and summary_embedding to ensure they are the same size
    @field_validator("details_embedding", "summary_embedding")
    @classmethod
    def pad_embeddings(cls, embedding: List[float]) -> List[float]:
        """Pad embeddings to `MAX_EMBEDDING_SIZE`. This is necessary to ensure all stored embeddings are the same size."""
        import numpy as np

        if embedding and len(embedding) != MAX_EMBEDDING_DIM:
            np_embedding = np.array(embedding)
            padded_embedding = np.pad(
                np_embedding,
                (0, MAX_EMBEDDING_DIM - np_embedding.shape[0]),
                mode="constant",
            )
            return padded_embedding.tolist()
        return embedding


class EpisodicEventUpdate(MirixBase):
    """
    Schema for updating an existing episodic memory record.

    All fields (except id) are optional so that only provided fields are updated.
    """

    id: str = Field(..., description="Unique ID for this episodic memory record")
    agent_id: Optional[str] = Field(
        None, description="The id of the agent this episodic event belongs to"
    )
    event_type: Optional[str] = Field(None, description="Type/category of the event")
    summary: Optional[str] = Field(
        None, description="Short textual summary of the event"
    )
    details: Optional[str] = Field(
        None, description="Detailed text describing the event"
    )
    organization_id: Optional[str] = Field(
        None, description="Unique identifier of the organization"
    )
    occurred_at: Optional[datetime] = Field(
        None, description="If the event's time is updated"
    )
    updated_at: datetime = Field(
        default_factory=get_utc_time,
        description="Timestamp when this memory record was last updated",
    )
    last_modify: Optional[Dict[str, Any]] = Field(
        None,
        description="Last modification info including timestamp and operation type",
    )
    summary_embedding: Optional[List[float]] = Field(
        None, description="The embedding of the summary"
    )
    details_embedding: Optional[List[float]] = Field(
        None, description="The embedding of the event"
    )
    embedding_config: Optional[EmbeddingConfig] = Field(
        None, description="The embedding configuration used by the event"
    )
    filter_tags: Optional[Dict[str, Any]] = Field(
        None, description="Custom filter tags for filtering and categorization"
    )
