from __future__ import annotations

import asyncio
import json
import logging
from collections import defaultdict
from typing import Any, AsyncIterator

from app.clients.hana_client import hana_client
from app.clients.openai_compat import openai_chat_completion
from app.config import settings
from app.services.session_store import ComparisonResult, session_store

LOG = logging.getLogger(__name__)

PROVIDER_STAGGER_SECONDS = 0.1
_provider_semaphores: dict[str, asyncio.Semaphore] = defaultdict(lambda: asyncio.Semaphore(1))


async def _query_neon(
    query: str,
    model_id: str,
    persona_name: str,
    system_prompt: str | None,
    has_persona: bool = True,
    history: list[tuple[str, str]] | None = None,
) -> dict[str, Any]:
    try:
        if settings._neon_security_direct_vllm_enabled(model_id):
            builtin = hana_client.get_persona_system_prompt(model_id, persona_name)
            parts: list[str] = []
            if system_prompt and has_persona:
                parts.append(system_prompt)
            if builtin:
                parts.append("[Neon persona base from HANA]\n" + builtin)
            combined = "\n\n".join(parts) if parts else ""
            messages: list[dict[str, str]] = []
            if combined:
                messages.append({"role": "system", "content": combined})
            messages.append({"role": "user", "content": query})
            base = f"{settings.neon_security_vllm_base_url.rstrip('/')}/v1"
            result = await openai_chat_completion(
                base_url=base,
                api_key=settings.hana_password_klatchat,
                model=model_id,
                messages=messages,
            )
            return {
                "provider": "neon",
                "model_id": model_id,
                "model_name": model_id.split("/")[-1].split("@")[0] if "/" in model_id else model_id,
                "persona_name": persona_name,
                "response": result["response"],
                "elapsed_seconds": result["elapsed_seconds"],
                "is_neon": True,
                "params": "24B (quantized)",
                "has_persona": has_persona,
            }

        result = await hana_client.get_inference(
            query=query,
            model_id=model_id,
            persona_name=persona_name,
            system_prompt=system_prompt,
            history=history,
        )
        return {
            "provider": "neon",
            "model_id": model_id,
            "model_name": model_id.split("/")[-1].split("@")[0] if "/" in model_id else model_id,
            "persona_name": persona_name,
            "response": result["response"],
            "elapsed_seconds": result["elapsed_seconds"],
            "is_neon": True,
            "params": "24B (quantized)",
            "has_persona": has_persona,
        }
    except Exception as exc:
        LOG.exception("Neon inference failed for %s: %s", model_id, exc)
        return {
            "provider": "neon",
            "model_id": model_id,
            "model_name": model_id,
            "persona_name": persona_name,
            "response": f"[Error]: {exc}",
            "elapsed_seconds": 0,
            "is_neon": True,
            "error": True,
            "params": "24B (quantized)",
            "has_persona": has_persona,
        }


async def _query_comparison(
    query: str,
    provider_id: str,
    provider_name: str,
    base_url: str,
    api_key: str,
    model_id: str,
    model_name: str,
    system_prompt: str | None,
    params: str = "",
    has_persona: bool = True,
) -> dict[str, Any]:
    sem = _provider_semaphores[provider_id]
    async with sem:
        messages: list[dict[str, str]] = []
        if system_prompt and has_persona:
            messages.append({"role": "system", "content": system_prompt})
        messages.append({"role": "user", "content": query})

        result = await openai_chat_completion(
            base_url=base_url,
            api_key=api_key,
            model=model_id,
            messages=messages,
        )
        await asyncio.sleep(PROVIDER_STAGGER_SECONDS)
    return {
        "provider": provider_id,
        "provider_name": provider_name,
        "model_id": model_id,
        "model_name": model_name,
        "response": result["response"],
        "elapsed_seconds": result["elapsed_seconds"],
        "is_neon": False,
        "error": result.get("error", False),
        "params": params,
        "has_persona": has_persona,
    }


def _resolve_comparison_models(selected_ids: list[str]) -> list[dict[str, Any]]:
    """Map selected comparison model IDs to their provider config."""
    resolved = []
    for provider in settings.comparison_providers:
        for model in provider["models"]:
            if model["id"] in selected_ids:
                resolved.append({
                    "provider_id": provider["id"],
                    "provider_name": provider["name"],
                    "base_url": model.get("base_url", provider["base_url"]),
                    "api_key": model.get("api_key", provider["api_key"]),
                    "model_id": model["id"],
                    "model_name": model["name"],
                    "params": model.get("params", ""),
                })
    return resolved


async def stream_comparison(
    query: str,
    neon_selections: list[dict[str, str]],
    comparison_model_ids: list[str],
    session_id: str | None = None,
    persona_target: str = "neon-only",
) -> AsyncIterator[str]:
    """Yield SSE events as each model response completes."""
    comparison_models = _resolve_comparison_models(comparison_model_ids)

    for gi, neon_sel in enumerate(neon_selections):
        system_prompt = neon_sel.get("system_prompt")
        neon_gets_persona = persona_target in ("all", "neon-only")
        comp_gets_persona = persona_target == "all"

        group_meta = {
            "neon_model_id": neon_sel["model_id"],
            "neon_persona": neon_sel["persona_name"],
            "system_prompt": system_prompt or "",
            "query": query,
            "group_index": gi,
            "persona_target": persona_target,
        }
        yield f"event: group_start\ndata: {json.dumps(group_meta)}\n\n"

        session_responses: list[dict[str, Any]] = []
        pending: set[asyncio.Task] = set()

        neon_task = asyncio.create_task(_query_neon(
            query=query,
            model_id=neon_sel["model_id"],
            persona_name=neon_sel["persona_name"],
            system_prompt=system_prompt if neon_gets_persona else None,
            has_persona=neon_gets_persona,
        ))
        neon_task.set_name("neon")
        pending.add(neon_task)

        for cm in comparison_models:
            t = asyncio.create_task(_query_comparison(
                query=query,
                provider_id=cm["provider_id"],
                provider_name=cm["provider_name"],
                base_url=cm["base_url"],
                api_key=cm["api_key"],
                model_id=cm["model_id"],
                model_name=cm["model_name"],
                system_prompt=system_prompt,
                params=cm.get("params", ""),
                has_persona=comp_gets_persona,
            ))
            t.set_name(cm["model_id"])
            pending.add(t)

        while pending:
            done, pending = await asyncio.wait(pending, return_when=asyncio.FIRST_COMPLETED)
            for task in done:
                try:
                    result = task.result()
                except Exception as exc:
                    result = {
                        "provider": "unknown",
                        "model_id": task.get_name(),
                        "model_name": task.get_name(),
                        "response": f"[Error]: {exc}",
                        "elapsed_seconds": 0,
                        "is_neon": False,
                        "error": True,
                    }
                result["group_index"] = gi
                session_responses.append(result)
                yield f"event: response\ndata: {json.dumps(result)}\n\n"

        if session_id:
            resp_map = {}
            timing_map = {}
            for r in session_responses:
                key = f"{r.get('provider_name', r['provider'])} / {r['model_name']}"
                if r.get("is_neon"):
                    key = f"Neon / {r['model_name']} ({r.get('persona_name', '')})"
                resp_map[key] = r["response"]
                timing_map[key] = r["elapsed_seconds"]
            session_store.add_result(session_id, ComparisonResult(
                query=query,
                neon_model_id=neon_sel["model_id"],
                neon_persona=neon_sel["persona_name"],
                responses=resp_map,
                timings=timing_map,
            ))

    yield "event: done\ndata: {}\n\n"


async def _run_single_group(
    query: str,
    neon_sel: dict[str, str],
    comparison_models: list[dict[str, Any]],
    persona_target: str = "neon-only",
) -> dict[str, Any]:
    """Run one Neon model + all comparison models for a single query."""
    system_prompt = neon_sel.get("system_prompt")
    neon_gets_persona = persona_target in ("all", "neon-only")
    comp_gets_persona = persona_target == "all"
    tasks = []

    tasks.append(_query_neon(
        query=query,
        model_id=neon_sel["model_id"],
        persona_name=neon_sel["persona_name"],
        system_prompt=system_prompt if neon_gets_persona else None,
        has_persona=neon_gets_persona,
    ))

    for cm in comparison_models:
        tasks.append(_query_comparison(
            query=query,
            provider_id=cm["provider_id"],
            provider_name=cm["provider_name"],
            base_url=cm["base_url"],
            api_key=cm["api_key"],
            model_id=cm["model_id"],
            model_name=cm["model_name"],
            system_prompt=system_prompt,
            params=cm.get("params", ""),
            has_persona=comp_gets_persona,
        ))

    results = await asyncio.gather(*tasks, return_exceptions=True)
    responses: list[dict[str, Any]] = []
    for r in results:
        if isinstance(r, Exception):
            responses.append({
                "provider": "unknown",
                "model_id": "unknown",
                "model_name": "unknown",
                "response": f"[Error]: {r}",
                "elapsed_seconds": 0,
                "is_neon": False,
                "error": True,
            })
        else:
            responses.append(r)

    return {
        "neon_model_id": neon_sel["model_id"],
        "neon_persona": neon_sel["persona_name"],
        "query": query,
        "responses": responses,
    }


async def run_comparison(
    query: str,
    neon_selections: list[dict[str, str]],
    comparison_model_ids: list[str],
    session_id: str | None = None,
    persona_target: str = "neon-only",
) -> list[dict[str, Any]]:
    """Non-streaming version. Neon groups run in parallel; semaphores handle rate limiting."""
    comparison_models = _resolve_comparison_models(comparison_model_ids)

    group_tasks = [
        _run_single_group(query, neon_sel, comparison_models, persona_target=persona_target)
        for neon_sel in neon_selections
    ]
    groups = await asyncio.gather(*group_tasks)
    groups = list(groups)

    if session_id:
        for group in groups:
            resp_map = {}
            timing_map = {}
            for r in group["responses"]:
                key = f"{r.get('provider_name', r['provider'])} / {r['model_name']}"
                if r.get("is_neon"):
                    key = f"Neon / {r['model_name']} ({r['persona_name']})"
                resp_map[key] = r["response"]
                timing_map[key] = r["elapsed_seconds"]
            session_store.add_result(session_id, ComparisonResult(
                query=query,
                neon_model_id=group["neon_model_id"],
                neon_persona=group["neon_persona"],
                responses=resp_map,
                timings=timing_map,
            ))

    return groups


async def run_csv_comparison(
    questions: list[str],
    neon_selections: list[dict[str, str]],
    comparison_model_ids: list[str],
    persona_target: str = "neon-only",
) -> list[list[dict[str, Any]]]:
    """Run comparison for a batch of questions. Returns list of group-lists."""
    all_results = []
    for q in questions:
        groups = await run_comparison(
            query=q,
            neon_selections=neon_selections,
            comparison_model_ids=comparison_model_ids,
            persona_target=persona_target,
        )
        all_results.append(groups)
    return all_results