import asyncio

from fastapi.testclient import TestClient

import app.dependencies as deps
from app.main import app
from app.providers.llm.base import sse_delta, LLMProvider
from app.pipeline.sentence_chunker import SentenceChunker

client = TestClient(app)


def test_sentence_chunker_incremental():
    ch = SentenceChunker()
    emitted = []
    for tok in ["Hallo", " Anna", ". ", "Wie", " geht", " es", "? ", "Tschuess"]:
        emitted += ch.feed(tok)
    assert emitted == ["Hallo Anna.", "Wie geht es?"]
    assert ch.flush() == "Tschuess"
    assert SentenceChunker().feed("Eins. Zwei! Drei? Vier") == ["Eins.", "Zwei!", "Drei?"]


def test_sentence_chunker_keeps_ordinals_and_abbreviations():
    # "1." (Ziffer+Punkt) darf KEINE Satzgrenze sein.
    ch = SentenceChunker()
    assert ch.feed("Am 1. Mai ist frei. ") == ["Am 1. Mai ist frei."]
    # Abkuerzung "z. B." darf den Satz nicht zerschneiden.
    ch2 = SentenceChunker()
    assert ch2.feed("Obst, z. B. Äpfel und Birnen. ") == ["Obst, z. B. Äpfel und Birnen."]


def test_sse_delta_parsing():
    assert sse_delta('data: {"choices":[{"delta":{"content":"Hal"}}]}') == "Hal"
    assert sse_delta("data: [DONE]") is None
    assert sse_delta("") is None
    assert sse_delta(": keep-alive") is None
    assert sse_delta('data: {"choices":[{"delta":{}}]}') is None
    assert sse_delta("data: nicht-json") is None


def test_base_stream_default_yields_full_completion():
    class P(LLMProvider):
        async def complete(self, text, history=None, session_id=None):
            return "ganze Antwort"

    async def run():
        return [delta async for delta in P().stream("x")]

    assert asyncio.run(run()) == ["ganze Antwort"]


def _install_streaming(monkeypatch, tokens):
    class StreamLLM:
        async def complete(self, text, history=None, session_id=None):
            return "".join(tokens)

        async def stream(self, text, history=None, session_id=None):
            for tok in tokens:
                yield tok

    class StubTTS:
        async def synthesize(self, text, voice=None, audio_format="pcm"):
            return b"AUD"

    monkeypatch.setitem(deps.LLM_REGISTRY, "stream", lambda s: StreamLLM())
    monkeypatch.setitem(deps.TTS_REGISTRY, "stub", lambda s: StubTTS())
    return {"llm_provider": "stream", "tts_provider": "stub", "output_endpoint": "loopback"}


def test_ws_stream_emits_token_events(monkeypatch):
    base = _install_streaming(monkeypatch, ["Gu", "ten ", "Tag"])
    with client.websocket_connect("/ws/chat") as ws:
        ws.send_json({"text": "Hallo", "stream": True, **base})
        assert ws.receive_json()["type"] == "ack"

        tokens = []
        event = ws.receive_json()
        while event["type"] == "token":
            tokens.append(event["text"])
            event = ws.receive_json()

        assert tokens == ["Gu", "ten ", "Tag"]
        assert event["type"] == "semantic" and event["text"] == "Guten Tag"
        assert ws.receive_bytes() == b"AUD"
        assert ws.receive_json()["type"] == "done"


def test_ws_without_stream_flag_has_no_tokens(monkeypatch):
    base = _install_streaming(monkeypatch, ["a", "b"])
    with client.websocket_connect("/ws/chat") as ws:
        ws.send_json({"text": "Hallo", **base})  # kein stream-Flag
        assert ws.receive_json()["type"] == "ack"
        assert ws.receive_json()["type"] == "semantic"  # direkt, keine token-Events


def test_ws_stream_fallback_for_nonstreaming_llm(monkeypatch):
    class OnlyComplete:
        async def complete(self, text, history=None, session_id=None):
            return "komplett"

    class StubTTS:
        async def synthesize(self, text, voice=None, audio_format="pcm"):
            return b"X"

    monkeypatch.setitem(deps.LLM_REGISTRY, "oc", lambda s: OnlyComplete())
    monkeypatch.setitem(deps.TTS_REGISTRY, "stub", lambda s: StubTTS())
    base = {"llm_provider": "oc", "tts_provider": "stub", "output_endpoint": "loopback"}

    with client.websocket_connect("/ws/chat") as ws:
        ws.send_json({"text": "x", "stream": True, **base})
        assert ws.receive_json()["type"] == "ack"
        token = ws.receive_json()
        assert token["type"] == "token" and token["text"] == "komplett"
        assert ws.receive_json()["type"] == "semantic"


def test_ws_audio_stream_sends_chunks_per_sentence(monkeypatch):
    tts_calls = []

    class StreamLLM:
        async def complete(self, text, history=None, session_id=None):
            return "Satz eins. Satz zwei."

        async def stream(self, text, history=None, session_id=None):
            for tok in ["Satz ", "eins. ", "Satz ", "zwei."]:
                yield tok

    class CountTTS:
        async def synthesize(self, text, voice=None, audio_format="pcm"):
            tts_calls.append(text)
            return b"A" * len(tts_calls)

    monkeypatch.setitem(deps.LLM_REGISTRY, "stream", lambda s: StreamLLM())
    monkeypatch.setitem(deps.TTS_REGISTRY, "cnt", lambda s: CountTTS())
    base = {"llm_provider": "stream", "tts_provider": "cnt", "output_endpoint": "loopback"}

    with client.websocket_connect("/ws/chat") as ws:
        ws.send_json({"text": "x", "audio_stream": True, **base})
        assert ws.receive_json()["type"] == "ack"

        audio_events = 0
        event = ws.receive_json()
        while event["type"] != "semantic":
            assert event["type"] == "audio"
            assert ws.receive_bytes()  # binärer Audio-Chunk folgt
            audio_events += 1
            event = ws.receive_json()

        assert audio_events == 2  # zwei Sätze -> zwei Chunks
        # Kein finales Vollaudio mehr -> direkt done.
        assert ws.receive_json()["type"] == "done"

    assert len(tts_calls) == 2  # TTS pro Satz