"""hb_swarm_ - Credential-free swarm coordination plans."""

from __future__ import annotations

from typing import Any

from homebase.modules import ModuleBase, ToolDefinition


class SwarmModule(ModuleBase):
    """Plan swarm patterns without launching model calls."""

    def __init__(self, config: dict[str, Any]):
        super().__init__(config)
        self.backend = config.get("backend", "ollama")
        self.endpoint = config.get("endpoint", "http://localhost:11434")
        self.model = config.get("model", "qwen2.5:7b")

    def get_tools(self) -> list[ToolDefinition]:
        return [
            ToolDefinition(
                name="hb_swarm_parallel",
                description="Split task into chunks and process in parallel",
                input_schema={
                    "type": "object",
                    "properties": {
                        "task": {"type": "string"},
                        "chunks": {"type": "array", "items": {"type": "string"}},
                        "workers": {"type": "integer", "default": 3},
                    },
                    "required": ["task", "chunks"],
                },
                handler=self._parallel,
            ),
            ToolDefinition(
                name="hb_swarm_consensus",
                description="Get majority vote from multiple independent agents",
                input_schema={
                    "type": "object",
                    "properties": {
                        "question": {"type": "string"},
                        "voters": {"type": "integer", "default": 3},
                    },
                    "required": ["question"],
                },
                handler=self._consensus,
            ),
            ToolDefinition(
                name="hb_swarm_hierarchy",
                description="Boss-worker delegation pattern",
                input_schema={
                    "type": "object",
                    "properties": {
                        "task": {"type": "string"},
                        "subtasks": {"type": "array", "items": {"type": "string"}},
                    },
                    "required": ["task"],
                },
                handler=self._hierarchy,
            ),
            ToolDefinition(
                name="hb_swarm_stigmergy",
                description="Indirect coordination via shared state (blackboard pattern)",
                input_schema={
                    "type": "object",
                    "properties": {
                        "task": {"type": "string"},
                        "iterations": {"type": "integer", "default": 3},
                    },
                    "required": ["task"],
                },
                handler=self._stigmergy,
            ),
        ]

    async def _parallel(self, **kwargs) -> dict[str, Any]:
        chunks = [str(chunk) for chunk in kwargs.get("chunks", [])]
        workers = max(1, int(kwargs.get("workers", 3)))
        assignments = [
            {"worker": f"worker-{index % workers + 1}", "chunk_index": index, "chunk": chunk}
            for index, chunk in enumerate(chunks)
        ]
        return {
            "status": "planned",
            "pattern": "parallel",
            "backend": self.backend,
            "model": self.model,
            "task": kwargs.get("task"),
            "workers": workers,
            "chunk_count": len(chunks),
            "assignments": assignments,
        }

    async def _consensus(self, **kwargs) -> dict[str, Any]:
        voters = max(1, int(kwargs.get("voters", 3)))
        return {
            "status": "planned",
            "pattern": "consensus",
            "backend": self.backend,
            "model": self.model,
            "question": kwargs.get("question"),
            "voters": voters,
            "quorum": voters // 2 + 1,
            "rounds": ["independent_answer", "compare_answers", "majority_or_escalate"],
        }

    async def _hierarchy(self, **kwargs) -> dict[str, Any]:
        subtasks = kwargs.get("subtasks") or _derive_subtasks(str(kwargs.get("task", "")))
        return {
            "status": "planned",
            "pattern": "hierarchy",
            "backend": self.backend,
            "model": self.model,
            "task": kwargs.get("task"),
            "boss": {"role": "planner-reviewer", "responsibilities": ["split", "assign", "integrate"]},
            "workers": [{"worker": f"worker-{idx + 1}", "subtask": str(subtask)} for idx, subtask in enumerate(subtasks)],
        }

    async def _stigmergy(self, **kwargs) -> dict[str, Any]:
        iterations = max(1, int(kwargs.get("iterations", 3)))
        return {
            "status": "planned",
            "pattern": "stigmergy",
            "backend": self.backend,
            "model": self.model,
            "task": kwargs.get("task"),
            "blackboard_keys": ["current_state", "open_questions", "candidate_patches", "review_notes"],
            "iterations": [
                {"iteration": idx + 1, "action": "read shared state, contribute delta, update blackboard"}
                for idx in range(iterations)
            ],
        }


def _derive_subtasks(task: str) -> list[str]:
    parts = [part.strip(" .") for part in task.replace("\n", ". ").split(".") if part.strip()]
    return parts[:5] or [task or "Define task"]


def create_module(config: dict[str, Any]) -> SwarmModule:
    return SwarmModule(config)