"""Agent invocation via subprocess with live spinner."""
from __future__ import annotations

import itertools
import logging
import os
import subprocess
import sys
import tempfile
import threading
import time
from pathlib import Path
from typing import Optional

from cross_eval.models import AgentConfig, AgentResult

logger = logging.getLogger(__name__)

# CLI tools that support --system-prompt flag natively
_SYSTEM_PROMPT_AGENTS = ("claude",)
_REASONING_EFFORT_AGENTS = ("codex",)
_NO_CHANGE_ACK_MARKERS = (
    "no changes",
    "no code changes",
    "no file changes",
    "did not make any changes",
    "nothing to change",
    "no modifications were necessary",
    "no update was necessary",
    "already satisfied",
    "no changes needed",
    "no fixes needed",
    "everything is correct",
    "code is correct as-is",
    "already correct",
    "no action required",
    "변경 없음",
    "수정 없음",
    "수정할 필요 없음",
    "변경할 필요 없음",
    "이미 올바름",
    "조치 불필요",
)
_CHANGE_CLAIM_MARKERS = (
    "summary of all changes made",
    "here's a summary of all changes made",
    "here is a summary of all changes",
    "implemented",
    "i implemented",
    "i've implemented",
    "added",
    "i added",
    "i've added",
    "updated",
    "i updated",
    "i've updated",
    "modified",
    "i modified",
    "i've modified",
    "created",
    "i created",
    "i've created",
    "fixed",
    "i fixed",
    "i've fixed",
    "completed the changes",
    "finished the changes",
    "made the following changes",
    "applied the fix",
    "changes have been applied",
    "wrote the code",
    "refactored",
    "i refactored",
    "completed all the changes",
    "finished implementing",
    "all tasks completed",
    "done with the implementation",
    "successfully implemented",
    "completed the implementation",
    "all changes have been made",
    "changes are complete",
    "수정 완료",
    "모든 수정이 완료",
    "변경 요약",
    "변경 파일",
    "신규 생성",
    "기획서 수정",
    "체크리스트 수정",
    "문서를 수정",
    "문서 수정",
)


class AgentInvocationError(RuntimeError):
    """Structured error for agent CLI failures."""

    def __init__(
        self,
        *,
        agent_name: str,
        step_name: str,
        cmd_preview: str,
        raw_error: str,
        failure_type: str,
        suggested_action: str,
    ) -> None:
        self.agent_name = agent_name
        self.step_name = step_name
        self.cmd_preview = cmd_preview
        self.raw_error = raw_error
        self.failure_type = failure_type
        self.suggested_action = suggested_action
        super().__init__(
            f"Agent '{agent_name}' failed (exit code != 0) at step '{step_name}':\n"
            f"  type: {failure_type}\n"
            f"  cmd: {cmd_preview}\n"
            f"  error: {raw_error or '(no output)'}\n"
            f"  action: {suggested_action}"
        )


def _supports_system_prompt_flag(command: str) -> bool:
    """Check if the agent CLI supports --system-prompt flag."""
    return any(name in command for name in _SYSTEM_PROMPT_AGENTS)


def _supports_reasoning_effort(command: str) -> bool:
    """Check if the agent CLI supports reasoning effort overrides."""
    return any(name in command for name in _REASONING_EFFORT_AGENTS)


def _classify_agent_failure(detail: str) -> tuple[str, str]:
    """Classify a failed agent invocation into a user-actionable bucket."""
    normalized = detail.lower()

    auth_markers = (
        "not logged in",
        "please run /login",
        "auth",
        "authentication",
        "invalid api key",
        "api key",
        "unauthorized",
        "forbidden",
    )
    usage_limit_markers = (
        "quota",
        "rate limit",
        "credits",
        "credit balance",
        "budget",
        "insufficient funds",
        "usage limit",
        "token limit",
        "billing",
    )

    if any(marker in normalized for marker in auth_markers):
        return (
            "AUTH",
            "Agent CLI authentication is missing or expired. Re-authenticate the CLI, then rerun.",
        )
    if any(marker in normalized for marker in usage_limit_markers):
        return (
            "USAGE_LIMIT",
            "Agent CLI hit a quota, billing, or token budget limit. Refill or raise the limit, then rerun.",
        )
    if "api error" in normalized:
        return (
            "API_ERROR",
            "Agent CLI returned an API error. Inspect the saved error file for the raw response.",
        )
    return (
        "UNKNOWN",
        "Agent CLI failed for an unknown reason. Inspect the saved error file for details.",
    )


_WRITE_FAILURE_MARKERS = (
    "permission denied",
    "read-only file system",
    "read only file system",
    "operation not permitted",
    "cannot write",
    "failed to write",
    "could not write",
    "unable to write",
    "sandbox",
    "eacces",
    "erofs",
)


def _has_write_failure_indicators(stderr: str) -> bool:
    """Detect stderr patterns indicating the agent could not write files."""
    if not stderr.strip():
        return False
    normalized = stderr.lower()
    return any(marker in normalized for marker in _WRITE_FAILURE_MARKERS)


def _claims_file_changes(output: str) -> bool:
    """Heuristic for agent text that claims code changes were made."""
    normalized = output.lower()
    if not normalized.strip():
        return False
    if any(marker in normalized for marker in _NO_CHANGE_ACK_MARKERS):
        return False
    return any(marker in normalized for marker in _CHANGE_CLAIM_MARKERS)


class _Spinner:
    """Animated spinner for long-running agent calls."""

    FRAMES = "⠋⠙⠹⠸⠼⠴⠦⠧⠇⠏"
    _CLEAR_LINE = "\r" + (" " * 160) + "\r"

    def __init__(self, message: str) -> None:
        self.message = message
        self._running = False
        self._thread: Optional[threading.Thread] = None
        self._start_time = 0.0

    def start(self) -> None:
        self._running = True
        self._start_time = time.monotonic()
        self._thread = threading.Thread(target=self._spin, daemon=True)
        self._thread.start()

    def _spin(self) -> None:
        for frame in itertools.cycle(self.FRAMES):
            if not self._running:
                break
            elapsed = int(time.monotonic() - self._start_time)
            line = f"\r  {frame} {self.message} ({elapsed}s)"
            sys.stderr.write(line)
            sys.stderr.flush()
            time.sleep(0.1)

    def stop(self, final: str) -> None:
        self._running = False
        if self._thread:
            self._thread.join(timeout=1)
        elapsed = round(time.monotonic() - self._start_time, 1)
        sys.stderr.write(self._CLEAR_LINE)
        sys.stderr.write(f"  \u2713 {final} ({elapsed}s)\n")
        sys.stderr.flush()


def _is_print_mode(args: list[str]) -> bool:
    """Check if the agent args include -p / --print flag."""
    return "-p" in args or "--print" in args


def invoke_agent(
    agent: AgentConfig,
    prompt: str,
    step_name: str,
    cwd: Optional[Path] = None,
    env: Optional[dict[str, str]] = None,
    timeout: int | None = None,
    quiet: bool = False,
) -> AgentResult:
    """Invoke an agent CLI with the given prompt.

    Args:
        quiet: If True, suppress spinner (for parallel execution).
    """
    is_claude = "claude" in agent.command
    is_interactive = is_claude and not _is_print_mode(agent.args)

    cmd = [agent.command]
    if agent.reasoning_effort and _supports_reasoning_effort(agent.command):
        cmd.extend(["-c", f'model_reasoning_effort="{agent.reasoning_effort}"'])
    cmd.extend(agent.args)

    # --- Temp files for interactive (non -p) claude ---
    task_file: Optional[Path] = None
    output_file: Optional[Path] = None

    if is_interactive:
        # Write prompt + output instruction to temp task file
        task_fd, task_path = tempfile.mkstemp(suffix=".md", prefix="cross_eval_task_")
        task_file = Path(task_path)
        os.close(task_fd)

        out_fd, out_path = tempfile.mkstemp(suffix=".md", prefix="cross_eval_out_")
        output_file = Path(out_path)
        os.close(out_fd)
        # Clear the output file so we can detect if agent wrote to it
        output_file.write_text("", encoding="utf-8")

        wrapped_prompt = (
            f"{prompt}\n\n"
            f"---\n"
            f"IMPORTANT: Write your COMPLETE response to this file: {output_file}\n"
            f"Do NOT modify any other files in the project."
        )
        task_file.write_text(wrapped_prompt, encoding="utf-8")

        # System prompt via flag
        if agent.system_prompt and _supports_system_prompt_flag(agent.command):
            cmd.extend(["--system-prompt", agent.system_prompt])

        # Positional arg: point claude to the task file
        cmd.append(
            f"Read the task file at {task_file} and follow all instructions in it. "
            f"Write your complete output to {output_file}."
        )
        input_data: str | None = None
    else:
        # Print mode (-p) or non-claude: deliver prompt via stdin
        if agent.system_prompt and _supports_system_prompt_flag(agent.command):
            cmd.extend(["--system-prompt", agent.system_prompt])
            input_data = prompt
        elif agent.system_prompt:
            input_data = (
                f"<system>\n{agent.system_prompt}\n</system>\n\n"
                f"{prompt}"
            )
        else:
            input_data = prompt

    cmd_preview = " ".join(cmd[:6])
    logger.debug("Invoking agent '%s': %s", agent.name, " ".join(cmd[:5]) + " ...")

    spinner: Optional[_Spinner] = None
    if not quiet:
        mode_label = "interactive" if is_interactive else ""
        logger.info("  cmd: %s %s", " ".join(cmd[:6]), f"({mode_label})" if mode_label else "")
        spinner = _Spinner(f"[{step_name}] {agent.name} running...")
        spinner.start()

    try:
        start = time.monotonic()
        result = subprocess.run(
            cmd,
            input=input_data,
            capture_output=True,
            text=True,
            timeout=timeout,
            cwd=cwd,
            env=env,
        )
        duration = time.monotonic() - start
    except subprocess.TimeoutExpired:
        if spinner:
            spinner.stop(f"[{step_name}] TIMEOUT after {timeout}s")
        raise
    except Exception:
        if spinner:
            spinner.stop(f"[{step_name}] ERROR")
        raise
    finally:
        if task_file:
            task_file.unlink(missing_ok=True)

    if result.returncode != 0:
        if spinner:
            spinner.stop(f"[{step_name}] FAILED (exit {result.returncode})")
        if output_file:
            output_file.unlink(missing_ok=True)
        err_detail = result.stderr.strip() or result.stdout.strip()
        if err_detail and len(err_detail) > 500:
            err_detail = err_detail[:500] + "..."
        failure_type, suggested_action = _classify_agent_failure(err_detail or "")
        raise AgentInvocationError(
            agent_name=agent.name,
            step_name=step_name,
            cmd_preview=cmd_preview,
            raw_error=err_detail or "(no output)",
            failure_type=failure_type,
            suggested_action=suggested_action,
        )

    # --- Capture output ---
    if output_file:
        output = output_file.read_text(encoding="utf-8").strip()
        output_file.unlink(missing_ok=True)
        if not output:
            # Fallback to stdout if agent didn't write to the file
            output = result.stdout.strip()
    else:
        output = result.stdout.strip()

    chars = len(output)

    if spinner:
        spinner.stop(f"[{step_name}] done — {chars} chars")

    if not output:
        stderr_info = result.stderr.strip()
        if stderr_info:
            logger.warning(
                "Agent '%s' produced empty output at step '%s'. stderr: %s",
                agent.name, step_name, stderr_info[:500],
            )
        else:
            logger.warning(
                "Agent '%s' produced empty output at step '%s' (no stderr either)",
                agent.name, step_name,
            )

    transcript = _build_transcript(
        command_preview=cmd_preview,
        stdout=result.stdout,
        stderr=result.stderr,
        exit_code=result.returncode,
        duration_seconds=round(duration, 1),
        cwd=str(cwd) if cwd else "",
    )

    return AgentResult(
        output=output,
        exit_code=result.returncode,
        agent_name=agent.name,
        step_name=step_name,
        duration_seconds=round(duration, 1),
        transcript=transcript,
        command_preview=cmd_preview,
    )


def invoke_agent_agentic(
    agent: AgentConfig,
    prompt: str,
    step_name: str,
    worktree_path: Path,
    env: Optional[dict[str, str]] = None,
    timeout: int | None = None,
    quiet: bool = False,
    base_commit: str | None = None,
) -> AgentResult:
    """Invoke an agent in agentic mode using the worktree as the source of truth."""
    from cross_eval.worktree import capture_diff

    # Write prompt to a temp file (outside worktree, won't appear in diffs)
    import tempfile
    task_fd, task_path = tempfile.mkstemp(suffix=".md", prefix="cross_eval_task_")
    task_file = Path(task_path)
    task_file.write_text(prompt, encoding="utf-8")
    os.close(task_fd)

    cmd = [agent.command]
    if agent.reasoning_effort and _supports_reasoning_effort(agent.command):
        cmd.extend(["-c", f'model_reasoning_effort="{agent.reasoning_effort}"'])

    # Strip print-mode flags and stdin sentinels for agentic mode.
    # Agentic runs should operate on the worktree and return a real git diff,
    # not behave as a one-shot text completer.
    args = [a for a in agent.args if a not in {"-", "-p", "--print"}]
    cmd.extend(args)

    # System prompt via flag if supported
    if agent.system_prompt and _supports_system_prompt_flag(agent.command):
        cmd.extend(["--system-prompt", agent.system_prompt])

    # Deliver the prompt differently per agent type
    is_codex = "codex" in agent.command
    input_data: str | None = None
    if is_codex:
        # codex: stdin mode
        cmd.append("-")
        if agent.system_prompt and not _supports_system_prompt_flag(agent.command):
            input_data = f"<system>\n{agent.system_prompt}\n</system>\n\n{prompt}"
        else:
            input_data = prompt
    else:
        # claude: deliver the task through stdin and let the worktree be the
        # canonical place where files are read/written.
        input_data = prompt

    cmd_preview = " ".join(cmd[:6])
    logger.debug(
        "Invoking agent '%s' (agentic) in worktree: %s",
        agent.name, worktree_path,
    )

    spinner: Optional[_Spinner] = None
    if not quiet:
        logger.info("  cmd: %s (agentic)", " ".join(cmd[:6]))
        spinner = _Spinner(f"[{step_name}] {agent.name} (agentic) running...")
        spinner.start()

    try:
        start = time.monotonic()
        result = subprocess.run(
            cmd,
            input=input_data,
            capture_output=True,
            text=True,
            timeout=timeout,
            cwd=worktree_path,
            env=env,
        )
        duration = time.monotonic() - start
    except subprocess.TimeoutExpired:
        if spinner:
            spinner.stop(f"[{step_name}] TIMEOUT after {timeout}s")
        raise
    except Exception:
        if spinner:
            spinner.stop(f"[{step_name}] ERROR")
        raise
    finally:
        # Clean up temp task file (it's in /tmp, not in worktree)
        task_file.unlink(missing_ok=True)

    if result.returncode != 0:
        if spinner:
            spinner.stop(f"[{step_name}] FAILED (exit {result.returncode})")
        err_detail = result.stderr.strip() or result.stdout.strip()
        if err_detail and len(err_detail) > 500:
            err_detail = err_detail[:500] + "..."
        failure_type, suggested_action = _classify_agent_failure(err_detail or "")
        raise AgentInvocationError(
            agent_name=agent.name,
            step_name=step_name,
            cmd_preview=cmd_preview,
            raw_error=err_detail or "(no output)",
            failure_type=failure_type,
            suggested_action=suggested_action,
        )

    # Capture git diff as the output (changes since the base commit)
    diff_output = capture_diff(worktree_path, base_commit=base_commit)

    if not diff_output:
        stdout_excerpt = (result.stdout or "").strip()
        stderr_excerpt = (result.stderr or "").strip()

        # Detect two failure modes:
        # 1. Agent claims changes in stdout but produced no diff
        # 2. Agent stderr contains permission or write-failure indicators
        claims_changes = _claims_file_changes(stdout_excerpt)
        has_write_failure = _has_write_failure_indicators(stderr_excerpt)

        if claims_changes or has_write_failure:
            if spinner:
                spinner.stop(f"[{step_name}] FAILED (empty diff)")
            raw_error = stdout_excerpt or "(stdout empty)"
            if stderr_excerpt:
                raw_error = f"{raw_error}\n\n[stderr]\n{stderr_excerpt}"
            if len(raw_error) > 2000:
                raw_error = raw_error[:2000] + "..."

            if has_write_failure:
                failure_type = "WRITE_FAILURE"
                suggested_action = (
                    "Agent encountered file write errors (permission denied, read-only, "
                    "or sandbox restriction). Check agent permissions and worktree state."
                )
            else:
                failure_type = "EMPTY_DIFF"
                suggested_action = (
                    "Agent reported code changes but produced no git diff. "
                    "Treat this run as failed and require a real worktree diff before continuing."
                )

            raise AgentInvocationError(
                agent_name=agent.name,
                step_name=step_name,
                cmd_preview=cmd_preview,
                raw_error=raw_error,
                failure_type=failure_type,
                suggested_action=suggested_action,
            )

        diff_output = "(no changes)"
        logger.warning(
            "Agent '%s' made no file changes at step '%s'",
            agent.name, step_name,
        )

    chars = len(diff_output)
    if spinner:
        spinner.stop(f"[{step_name}] done — {chars} chars (agentic)")

    transcript = _build_transcript(
        command_preview=cmd_preview,
        stdout=result.stdout,
        stderr=result.stderr,
        exit_code=result.returncode,
        duration_seconds=round(duration, 1),
        cwd=str(worktree_path),
    )

    return AgentResult(
        output=diff_output,
        exit_code=result.returncode,
        agent_name=agent.name,
        step_name=step_name,
        duration_seconds=round(duration, 1),
        transcript=transcript,
        command_preview=cmd_preview,
    )


def _build_transcript(
    *,
    command_preview: str,
    stdout: str,
    stderr: str,
    exit_code: int = 0,
    duration_seconds: float = 0.0,
    cwd: str = "",
) -> str:
    """Build a compact execution transcript for debugging/audit output."""
    sections = [
        "# Agent Execution Transcript",
        "",
        "## Command",
        "```",
        command_preview or "(unknown command)",
        "```",
        "",
    ]
    if cwd:
        sections.extend(["## Working Directory", f"`{cwd}`", ""])
    sections.extend([
        f"## Exit Code: {exit_code}",
        "",
    ])
    if duration_seconds > 0:
        sections.extend([f"## Duration: {duration_seconds}s", ""])
    sections.extend([
        "## Stdout",
        "```",
        (stdout or "(empty)").strip(),
        "```",
        "",
        "## Stderr",
        "```",
        (stderr or "(empty)").strip(),
        "```",
        "",
    ])
    return "\n".join(sections)