from __future__ import annotations

import json
from dataclasses import dataclass, field
from typing import Any, Callable, Iterable, Optional

from anthropic import Anthropic

from .config import Config
from .endpoints import V3_REFERENCE
from .tools import ToolDispatcher, tool_schemas


BASE_SYSTEM_PROMPT = """\
You are a careful operations assistant for an IBM Spectrum Scale (GPFS) cluster.

You have a single tool, `gpfs_request`, that calls the cluster's REST API. \
The operator has wired the base URL, credentials and TLS settings for you; \
you only supply the method, path, and (when relevant) query/body.

Operating principles:
1. Read before you write. Inspect with GET requests before proposing any \
mutation. If the operator's question can be answered by reading, don't write.
2. Stay in scope. Only call paths that are relevant to the user's question. \
Don't enumerate the whole cluster when one filesystem is being discussed.
3. Explain what you did. Summarise findings in plain English. Cite the \
endpoint(s) you used. Show raw fields only when they materially answer the \
question or the user asks for them.
4. Be honest about errors. If a call returns a non-2xx, report the status \
and message rather than retrying blindly. Suggest the next diagnostic step.
5. Defer destructive work. For any DELETE or large-scale change, restate \
the plan in a single sentence and wait for the human to confirm before calling \
the tool — the harness will also prompt for confirmation.
6. Never invent endpoints. If you are unsure whether a path exists, try the \
parent collection first (e.g. GET `/filesystems` before guessing a name).
"""


def build_system_prompt(cfg: Config) -> str:
    methods = ", ".join(sorted(cfg.allowed_methods))
    lines = [
        BASE_SYSTEM_PROMPT,
        "\n" + V3_REFERENCE,
        f"\nThis session's allowed HTTP methods: {methods}.",
    ]
    if not cfg.allow_writes:
        lines.append(
            "Writes are disabled. Do not suggest POST/PUT/DELETE; explain what "
            "you would do instead and let the operator run it themselves."
        )
    if cfg.allow_writes and not cfg.allow_destructive:
        lines.append(
            "DELETE is disabled. Stop short of destructive operations and "
            "explain what would be required."
        )
    if cfg.path_allow:
        lines.append(f"Only paths matching {cfg.path_allow.pattern!r} are accessible.")
    if cfg.path_deny:
        lines.append(f"Paths matching {cfg.path_deny.pattern!r} are blocked.")
    if cfg.extra_instructions:
        lines.append("\n[Operator instructions]\n" + cfg.extra_instructions)
    return "\n".join(lines)


ToolEventFn = Callable[[str, dict[str, Any], dict[str, Any]], None]


@dataclass
class AgentState:
    messages: list[dict[str, Any]] = field(default_factory=list)


class Agent:
    def __init__(
        self,
        cfg: Config,
        dispatcher: ToolDispatcher,
        on_tool_event: Optional[ToolEventFn] = None,
    ) -> None:
        self._cfg = cfg
        self._client = Anthropic(api_key=cfg.anthropic_api_key)
        self._dispatcher = dispatcher
        self._tools = tool_schemas(cfg)
        self.system_prompt = build_system_prompt(cfg)
        self._on_tool_event = on_tool_event or (lambda *_args: None)
        self.state = AgentState()

    def reset(self) -> None:
        self.state = AgentState()

    def chat(self, user_message: str, max_steps: int = 12) -> str:
        self.state.messages.append({"role": "user", "content": user_message})

        for _ in range(max_steps):
            response = self._client.messages.create(
                model=self._cfg.model,
                max_tokens=self._cfg.max_tokens,
                system=self.system_prompt,
                tools=self._tools,
                messages=self.state.messages,
            )

            self.state.messages.append(
                {"role": "assistant", "content": [b.model_dump() for b in response.content]}
            )

            if response.stop_reason != "tool_use":
                return _extract_text(response.content)

            tool_results = []
            for block in response.content:
                if block.type != "tool_use":
                    continue
                tool_input = dict(block.input) if isinstance(block.input, dict) else {}
                result = self._dispatcher.dispatch(block.name, tool_input)
                self._on_tool_event(block.name, tool_input, result)
                tool_results.append(
                    {
                        "type": "tool_result",
                        "tool_use_id": block.id,
                        "content": json.dumps(result, default=str),
                        "is_error": "error" in result,
                    }
                )
            self.state.messages.append({"role": "user", "content": tool_results})

        return (
            "[Reached max tool-use iterations without a final answer. "
            "Try restating the question or narrowing the scope.]"
        )


def _extract_text(blocks: Iterable[Any]) -> str:
    parts: list[str] = []
    for block in blocks:
        if getattr(block, "type", None) == "text":
            parts.append(block.text)
    return "\n".join(parts).strip()