tatlock/src/responses/router.py

"""
Responses router.

OpenAI-compatible /v1/responses endpoint with streaming support.
"""

import logging
from fastapi import APIRouter, HTTPException
from sse_starlette.sse import EventSourceResponse

from src.responses import service
from src.responses.schemas import ResponseRequest, Response
from src.core.exceptions import ModelNotFoundError, AppException
from src.core.context import current_user, current_conversation

logger = logging.getLogger(__name__)

router = APIRouter(prefix="/responses", tags=["responses"])


@router.post("", response_model=Response)
async def create_response(
    request: ResponseRequest,
) -> Response | EventSourceResponse:
    """
    Create a response using Responses API format.

    Supports:
    - Reasoning summaries (thinking/reasoning display)
    - Function calling (tool usage)
    - Streaming responses
    - Multi-turn conversations
    - Error handling

    Args:
        request: Response request with model, input, optional reasoning/tools

    Returns:
        Response object or SSE stream

    Example non-streaming request:
        POST /v1/responses
        {
            "model": "lorem-tester",
            "input": [{"role": "user", "content": "Hello"}],
            "reasoning": {"effort": "medium", "summary": "auto"},
            "stream": false
        }

    Example streaming request:
        POST /v1/responses
        {
            "model": "lorem-tester",
            "input": [{"role": "user", "content": "Hello"}],
            "stream": true
        }

    Response format (non-streaming):
        {
            "id": "resp_...",
            "object": "response",
            "created_at": 1733529600,
            "model": "lorem-tester",
            "status": "completed",
            "output": [
                {
                    "type": "reasoning",
                    "id": "rs_...",
                    "summary": ["Analyzing...", "Considering..."]
                },
                {
                    "type": "message",
                    "id": "msg_...",
                    "role": "assistant",
                    "content": [{"type": "output_text", "text": "Lorem ipsum..."}]
                }
            ],
            "usage": {
                "input_tokens": 10,
                "output_tokens": 50,
                "reasoning_tokens": 20,
                "total_tokens": 80
            }
        }

    Streaming format (SSE):
        event: response.reasoning_summary_text.delta
        data: {"delta": "Analyzing..."}

        event: response.output_text.delta
        data: {"delta": "Lorem"}

        event: response.done
        data: {"response": {...}}
    """
    logger.info(f"Response request for model: {request.model}")

    # Set request context (propagates through all async calls)
    user_token = current_user.set(request.user or "jpmschweitzer")
    conv_id = request.metadata.get("conversation_id") if request.metadata else None
    conv_token = current_conversation.set(conv_id)

    try:
        # Check if this is a Tatlock request - use Steward preprocessing (Phase 2)
        model_id = request.model
        if "." in model_id:
            model_id = model_id.split(".", 1)[1]

        use_steward = model_id.lower() == "tatlock"

        if request.stream:
            logger.info("Streaming response requested")
            if use_steward:
                logger.info("Streaming with Steward preprocessing for Tatlock request")
                # Use Steward + Tatlock streaming (Milestone 3.5)
                from src.responses.streaming import StreamingCoordinator
                coordinator = StreamingCoordinator()
                return EventSourceResponse(
                    coordinator.stream_response_with_steward(request)
                )
            else:
                # Regular streaming for non-Tatlock models
                return EventSourceResponse(
                    service.create_response_stream(request)
                )

        # Use appropriate service method
        if use_steward:
            logger.info("Using Steward preprocessing for Tatlock request")
            return await service.create_response_with_steward(request)
        else:
            return await service.create_response(request)

    except ModelNotFoundError as e:
        logger.error(f"Model not found: {e}")
        raise HTTPException(status_code=404, detail=str(e))

    except AppException as e:
        logger.error(f"Application error: {e}")
        raise HTTPException(status_code=e.status_code, detail=e.message)

    except Exception as e:
        logger.error(f"Unexpected error: {e}", exc_info=True)
        raise HTTPException(status_code=500, detail="Internal server error")

    finally:
        # Reset context (important for connection reuse)
        current_user.reset(user_token)
        current_conversation.reset(conv_token)