"""Shared fixtures for integration tests."""

import json
from collections.abc import AsyncIterator
from pathlib import Path
from typing import Any
from unittest.mock import AsyncMock

import pytest

from app.models.config import AgentConfig, AppConfig, DisplayConfig, LLMConfig, PermissionsConfig, SessionConfig
from app.models.message import Message
from app.services.llm import LLMClient


@pytest.fixture
def tmp_workspace(tmp_path: Path) -> Path:
    """Create a temporary workspace directory with a sample file."""
    ws = tmp_path / "workspace"
    ws.mkdir()
    (ws / "hello.txt").write_text("Hello, world!")
    return ws


@pytest.fixture
def test_config(tmp_workspace: Path) -> AppConfig:
    """AppConfig suitable for integration tests."""
    return AppConfig(
        llm=LLMConfig(
            model="test-model",
            endpoint="http://localhost:11434",
            max_retries=2,
            retry_backoff_base=0.01,
            retry_backoff_max=0.02,
        ),
        agent=AgentConfig(
            max_iterations=10,
            max_conversation_tokens=32000,
            workspace_root=tmp_workspace,
            truncation_keep_recent=4,
            truncation_threshold=0.85,
        ),
        permissions=PermissionsConfig(
            auto_approve=["read_file", "list_dir", "grep_files", "find_files", "finish"],
        ),
        display=DisplayConfig(
            show_tool_calls=False,
            show_token_usage=False,
            stream_output=False,
        ),
        session=SessionConfig(
            session_dir=tmp_workspace / ".sneakycode" / "sessions",
        ),
    )


def make_text_chunks(content: str) -> list[dict[str, Any]]:
    """Create SSE chunk dicts for a plain text response."""
    chunks = []
    for char in content:
        chunks.append({
            "choices": [{"delta": {"content": char}, "index": 0}]
        })
    chunks.append({
        "choices": [{"delta": {}, "finish_reason": "stop", "index": 0}],
        "usage": {"prompt_tokens": 10, "completion_tokens": len(content), "total_tokens": 10 + len(content)},
    })
    return chunks


def make_tool_call_chunks(name: str, args: dict[str, Any], tc_id: str = "call_001") -> list[dict[str, Any]]:
    """Create SSE chunk dicts for a tool call response."""
    args_str = json.dumps(args)
    chunks = [
        {
            "choices": [{
                "delta": {
                    "tool_calls": [{
                        "index": 0,
                        "id": tc_id,
                        "function": {"name": name, "arguments": ""},
                    }]
                },
                "index": 0,
            }]
        },
        {
            "choices": [{
                "delta": {
                    "tool_calls": [{
                        "index": 0,
                        "function": {"arguments": args_str},
                    }]
                },
                "index": 0,
            }]
        },
        {
            "choices": [{"delta": {}, "finish_reason": "tool_calls", "index": 0}],
            "usage": {"prompt_tokens": 10, "completion_tokens": 20, "total_tokens": 30},
        },
    ]
    return chunks


class MockLLMClient:
    """LLM client that returns scripted SSE chunk sequences."""

    def __init__(self, responses: list[list[dict[str, Any]]]) -> None:
        self._responses = list(responses)
        self._call_count = 0

    async def stream_chat(
        self,
        messages: list[Message],
        tools: list[dict[str, Any]] | None = None,
    ) -> AsyncIterator[dict]:
        if self._call_count >= len(self._responses):
            raise RuntimeError("MockLLMClient ran out of scripted responses")
        chunks = self._responses[self._call_count]
        self._call_count += 1
        for chunk in chunks:
            yield chunk

    async def stream_chat_with_retry(
        self,
        messages: list[Message],
        tools: list[dict[str, Any]] | None = None,
    ) -> AsyncIterator[dict]:
        async for chunk in self.stream_chat(messages, tools=tools):
            yield chunk

    @property
    def call_count(self) -> int:
        return self._call_count

    async def close(self) -> None:
        pass

    async def __aenter__(self):
        return self

    async def __aexit__(self, *exc):
        pass


@pytest.fixture
def mock_llm_client():
    """Factory fixture for creating MockLLMClient instances."""
    return MockLLMClient