backend/llm/workflow.py

from __future__ import annotations

from dataclasses import dataclass, field
from typing import Any, Dict, Optional

from backend.llm.gateway import ModelGateway


@dataclass
class WorkflowState:
    prompt: str
    session_id: Optional[str] = None
    project_id: Optional[str] = None
    intent: str = "general"
    response: str = ""
    provider: Optional[str] = None
    model: Optional[str] = None
    metadata: Dict[str, Any] = field(default_factory=dict)


class WorkflowEngine:
    """
    Application workflow boundary.

    The workflow does not import provider implementations directly.
    All model execution goes through ModelGateway.
    """

    def __init__(
        self,
        gateway: Optional[ModelGateway] = None,
        **gateway_kwargs: Any,
    ) -> None:
        self.gateway = gateway or ModelGateway(**gateway_kwargs)

    async def run(
        self,
        prompt: str,
        intent: str = "general",
        **kwargs: Any,
    ) -> WorkflowState:
        if not isinstance(prompt, str) or not prompt.strip():
            raise ValueError("prompt must be a non-empty string")

        state = WorkflowState(
            prompt=prompt,
            intent=intent or "general",
        )

        result = await self.gateway.complete(
            prompt=prompt,
            intent=state.intent,
            **kwargs,
        )

        if isinstance(result, str):
            state.response = result
        elif isinstance(result, dict):
            state.response = str(
                result.get("text")
                or result.get("content")
                or result.get("response")
                or ""
            )
            state.provider = result.get("provider")
            state.model = result.get("model")
            state.metadata.update(result)
        else:
            state.response = str(result)

        return state