"""
Mock LLM server for UI e2e tests.
Responds to OpenAI-format endpoints with canned responses.
"""

import os
import time
import json
import uuid

import uvicorn
from fastapi import FastAPI, Request
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import StreamingResponse


app = FastAPI(title="Mock LLM Server")
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_methods=["*"],
    allow_headers=["*"],
)


@app.get("/health")
async def health():
    return {"status": "ok"}


@app.get("/v1/models")
@app.get("/models")
async def list_models():
    return {
        "object": "list",
        "data": [
            {"id": "fake-gpt-4", "object": "model", "owned_by": "mock"},
            {"id": "fake-claude", "object": "model", "owned_by": "mock"},
        ],
    }


@app.post("/v1/chat/completions")
@app.post("/chat/completions")
async def chat_completions(request: Request):
    body = await request.json()
    model = body.get("model", "mock-model")
    stream = body.get("stream", False)

    response_id = f"chatcmpl-{uuid.uuid4().hex[:12]}"
    created = int(time.time())

    if stream:

        async def stream_generator():
            chunk = {
                "id": response_id,
                "object": "chat.completion.chunk",
                "created": created,
                "model": model,
                "choices": [
                    {
                        "index": 0,
                        "delta": {
                            "role": "assistant",
                            "content": "This is a mock response.",
                        },
                        "finish_reason": None,
                    }
                ],
            }
            yield f"data: {json.dumps(chunk)}\n\n"

            done_chunk = {
                "id": response_id,
                "object": "chat.completion.chunk",
                "created": created,
                "model": model,
                "choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}],
            }
            yield f"data: {json.dumps(done_chunk)}\n\n"
            yield "data: [DONE]\n\n"

        return StreamingResponse(stream_generator(), media_type="text/event-stream")

    return {
        "id": response_id,
        "object": "chat.completion",
        "created": created,
        "model": model,
        "choices": [
            {
                "index": 0,
                "message": {"role": "assistant", "content": "This is a mock response."},
                "finish_reason": "stop",
            }
        ],
        "usage": {"prompt_tokens": 10, "completion_tokens": 8, "total_tokens": 18},
    }


@app.post("/v1/embeddings")
@app.post("/embeddings")
async def embeddings(request: Request):
    body = await request.json()
    inputs = body.get("input", [""])
    if isinstance(inputs, str):
        inputs = [inputs]
    return {
        "object": "list",
        "data": [
            {"object": "embedding", "index": i, "embedding": [0.0] * 1536}
            for i in range(len(inputs))
        ],
        "model": body.get("model", "mock-embedding"),
        "usage": {"prompt_tokens": 5, "total_tokens": 5},
    }


if __name__ == "__main__":
    # The port is overridable so two checkouts can run the harness at the same
    # time; the default keeps every existing caller (run_e2e.sh, the CircleCI
    # job, the e2e chart's sidecar) working untouched.
    #
    # The HOST is deliberately NOT configurable. Binding loopback is what makes
    # this reachable at 127.0.0.1:8090 from inside the proxy's own pod, which is
    # the contract the deployed config.yml and the e2e values file are written
    # against.
    uvicorn.run(app, host="127.0.0.1", port=int(os.environ.get("MOCK_LLM_PORT", "8090")))