package executor

import (
	"context"
	"encoding/json"
	"errors"
	"fmt"

	"github.com/thepeterstone/claudomator/internal/llm"
)

// agentToolDefs returns the four agent back-channel tools as OpenAI
// function-calling definitions, for runners that talk to an OpenAI-compatible
// endpoint (LocalRunner). They mirror the MCP tools the container runners expose.
func agentToolDefs() []llm.Tool {
	strProp := func(desc string) map[string]any {
		return map[string]any{"type": "string", "description": desc}
	}
	return []llm.Tool{
		{Type: "function", Function: llm.ToolFunction{
			Name:        "ask_user",
			Description: "Ask the user a question when you genuinely need a decision to proceed. The task pauses until the user answers; do not call other tools after this.",
			Parameters: map[string]any{
				"type": "object",
				"properties": map[string]any{
					"question": strProp("the question to ask, phrased as a real question"),
					"options":  map[string]any{"type": "array", "items": map[string]any{"type": "string"}, "description": "optional suggested answer choices"},
				},
				"required": []string{"question"},
			},
		}},
		{Type: "function", Function: llm.ToolFunction{
			Name:        "report_summary",
			Description: "Record a concise 2-5 sentence summary of what you accomplished. Call this before finishing.",
			Parameters: map[string]any{
				"type":       "object",
				"properties": map[string]any{"summary": strProp("the summary text")},
				"required":   []string{"summary"},
			},
		}},
		{Type: "function", Function: llm.ToolFunction{
			Name:        "spawn_subtask",
			Description: "Create a child task to be executed separately. Use this to break large work into focused pieces.",
			Parameters: map[string]any{
				"type": "object",
				"properties": map[string]any{
					"name":           strProp("short descriptive name for the subtask"),
					"instructions":   strProp("complete instructions for the subtask agent"),
					"model":          strProp("optional model override"),
					"max_budget_usd": map[string]any{"type": "number", "description": "optional budget cap in USD"},
				},
				"required": []string{"name", "instructions"},
			},
		}},
		{Type: "function", Function: llm.ToolFunction{
			Name:        "record_progress",
			Description: "Record a short progress note that appears in the task timeline.",
			Parameters: map[string]any{
				"type":       "object",
				"properties": map[string]any{"message": strProp("a short progress note")},
				"required":   []string{"message"},
			},
		}},
	}
}

// dispatchAgentTool invokes one model-requested tool against the AgentChannel.
// It returns the text to feed back to the model as the tool result, and a
// blocked flag set when ask_user could not be answered in-session (the run must
// stop and the task block).
func dispatchAgentTool(ctx context.Context, ch AgentChannel, name, argsJSON string) (result string, blocked bool, err error) {
	switch name {
	case "ask_user":
		var a struct {
			Question string   `json:"question"`
			Options  []string `json:"options"`
		}
		_ = json.Unmarshal([]byte(argsJSON), &a)
		q := map[string]any{"text": a.Question}
		if len(a.Options) > 0 {
			q["options"] = a.Options
		}
		payload, _ := json.Marshal(q)
		ans, askErr := ch.AskUser(ctx, string(payload))
		if errors.Is(askErr, ErrAgentBlocked) {
			return "", true, nil
		}
		if askErr != nil {
			return "", false, askErr
		}
		return ans, false, nil

	case "report_summary":
		var a struct {
			Summary string `json:"summary"`
		}
		_ = json.Unmarshal([]byte(argsJSON), &a)
		if rsErr := ch.ReportSummary(ctx, a.Summary); rsErr != nil {
			return "", false, rsErr
		}
		return "Summary recorded.", false, nil

	case "spawn_subtask":
		var a struct {
			Name         string  `json:"name"`
			Instructions string  `json:"instructions"`
			Model        string  `json:"model"`
			MaxBudgetUSD float64 `json:"max_budget_usd"`
		}
		_ = json.Unmarshal([]byte(argsJSON), &a)
		id, ssErr := ch.SpawnSubtask(ctx, SubtaskSpec{
			Name:         a.Name,
			Instructions: a.Instructions,
			Model:        a.Model,
			MaxBudgetUSD: a.MaxBudgetUSD,
		})
		if ssErr != nil {
			return "", false, ssErr
		}
		return "Created subtask " + id, false, nil

	case "record_progress":
		var a struct {
			Message string `json:"message"`
		}
		_ = json.Unmarshal([]byte(argsJSON), &a)
		if rpErr := ch.RecordProgress(ctx, a.Message); rpErr != nil {
			return "", false, rpErr
		}
		return "Noted.", false, nil

	default:
		return "", false, fmt.Errorf("unknown tool %q", name)
	}
}