from typing import Literal

from pydantic import BaseModel, Field


class SourceReference(BaseModel):
    """Reference to a source artifact chunk used in RAG response."""

    artifact_file: str = Field(..., description="Path to the YAML artifact file")
    source_file: str = Field(..., description="Path to the source code file")
    chunk_type: str = Field(..., description="Type of chunk (factual_summary, interpretive_summary, method, invariants)")
    relevance_score: float = Field(..., description="Similarity score from FAISS search")


class ChatRequest(BaseModel):
    """Request model for the /chat endpoint."""

    message: str = Field(..., description="The user's message")
    conversation_id: str | None = Field(
        default=None, description="Optional conversation ID for continuity"
    )


class ChatResponse(BaseModel):
    """Response model for the /chat endpoint."""

    conversation_id: str = Field(..., description="Conversation ID (generated if not provided)")
    response: str = Field(..., description="The LLM's response")
    mode: Literal["local", "remote", "openai", "asksage"] = Field(..., description="Which adapter was used")
    intent: Literal["codebase", "general", "clarification"] = Field(
        default="general", description="Classified intent of the user message"
    )
    sources: list[SourceReference] = Field(default_factory=list, description="Source artifact references used in response")


class HealthResponse(BaseModel):
    """Response model for the /health endpoint."""

    status: str = Field(default="ok")
    faiss_loaded: bool = Field(default=False, description="Whether FAISS index is loaded")
    index_size: int = Field(default=0, description="Number of chunks in FAISS index")


class ErrorResponse(BaseModel):
    """Standard error response model."""

    detail: str = Field(..., description="Error description")


# --- SSE Streaming Event Models ---


class StreamChunkEvent(BaseModel):
    """SSE event for content chunks during streaming."""

    type: Literal["chunk"] = "chunk"
    content: str = Field(..., description="Content chunk from the LLM")
    conversation_id: str = Field(..., description="Conversation ID")


class StreamDoneEvent(BaseModel):
    """SSE event signaling completion of streaming."""

    type: Literal["done"] = "done"
    conversation_id: str = Field(..., description="Conversation ID")
    mode: Literal["local", "remote", "openai", "asksage"] = Field(..., description="Which adapter was used")
    intent: Literal["codebase", "general", "clarification"] = Field(
        default="general", description="Classified intent of the user message"
    )
    sources: list[SourceReference] = Field(default_factory=list, description="Source artifact references used in response")


class IndexResponse(BaseModel):
    """Response model for the /index endpoint."""

    status: str = Field(..., description="Indexing status")
    chunks_indexed: int = Field(default=0, description="Number of chunks indexed")
    artifacts_processed: int = Field(default=0, description="Number of YAML files processed")


class StreamErrorEvent(BaseModel):
    """SSE event for errors during streaming."""

    type: Literal["error"] = "error"
    message: str = Field(..., description="Error message")
    code: int = Field(default=500, description="HTTP status code")