package openai

import (
	"strings"
	"testing"
)

func TestEstimateInputTokens_SmallRequest(t *testing.T) {
	// A small request with a short prompt should be far below 100k threshold.
	estimate := estimateInputTokens("hi", nil, nil, nil)
	if estimate >= 100000 {
		t.Fatalf("small request estimate too large: %d", estimate)
	}
	if estimate <= 0 {
		t.Fatalf("small request estimate should be positive: %d", estimate)
	}
}

func TestEstimateInputTokens_LargePayloadExceedsThreshold(t *testing.T) {
	// 150k characters should produce an estimate above 100k.
	largePayload := make([]byte, 150000)
	for i := range largePayload {
		largePayload[i] = 'x'
	}
	prompt := string(largePayload)
	estimate := estimateInputTokens(prompt, nil, nil, nil)
	// estimate = runes/4 + runes/16, so 150k ASCII characters stay below 100k.
	// We need roughly 320k+ runes to reach the threshold with this formula.
	if estimate >= 100000 {
		t.Fatalf("expected estimate below 100k for 150k chars: %d", estimate)
	}

	// 400k characters should produce above 100k.
	largePayload2 := make([]byte, 400000)
	for i := range largePayload2 {
		largePayload2[i] = 'x'
	}
	prompt2 := string(largePayload2)
	estimate2 := estimateInputTokens(prompt2, nil, nil, nil)
	if estimate2 < 100000 {
		t.Fatalf("expected estimate >= 100k for 400k chars: %d", estimate2)
	}
}

func TestEstimateInputTokens_WithMetadata(t *testing.T) {
	prompt := "test"
	metadata := map[string]string{
		"request_id": "req-001",
		"workspace":  "/home/user/project",
		"custom_key": "custom_value_that_is_quite_long_for_testing",
	}
	estimate := estimateInputTokens(prompt, metadata, nil, nil)
	if estimate <= 0 {
		t.Fatalf("estimate with metadata should be positive: %d", estimate)
	}
}

func TestEstimateInputTokens_WithTools(t *testing.T) {
	prompt := "run the command"
	tools := []any{
		map[string]any{
			"type": "function",
			"function": map[string]any{
				"name": "run_commands",
				"parameters": map[string]any{
					"type": "object",
					"properties": map[string]any{
						"commands": map[string]any{
							"type":  "array",
							"items": map[string]any{"type": "string"},
						},
					},
				},
			},
		},
	}
	estimate := estimateInputTokens(prompt, nil, tools, nil)
	if estimate <= 0 {
		t.Fatalf("estimate with tools should be positive: %d", estimate)
	}
}

func TestToolsSchemaToJSON_FloatLessThanOne(t *testing.T) {
	got := toolsSchemaToJSON(map[string]any{
		"type":     "number",
		"minimum":  0.5,
		"multiple": 0.25,
	})
	if !strings.Contains(got, `"minimum":0.5`) {
		t.Fatalf("expected minimum float to be encoded, got %q", got)
	}
	if !strings.Contains(got, `"multiple":0.25`) {
		t.Fatalf("expected multiple float to be encoded, got %q", got)
	}
}

func TestClassifyContext_Normal(t *testing.T) {
	threshold := 100000
	if classifyContext(1000, threshold) != "normal" {
		t.Fatalf("expected normal for 1000 tokens")
	}
	if classifyContext(99999, threshold) != "normal" {
		t.Fatalf("expected normal for 99999 tokens")
	}
}

func TestClassifyContext_Long(t *testing.T) {
	threshold := 100000
	if classifyContext(100000, threshold) != "long" {
		t.Fatalf("expected long for 100000 tokens")
	}
	if classifyContext(200000, threshold) != "long" {
		t.Fatalf("expected long for 200000 tokens")
	}
}

func TestClassifyContext_AtThreshold(t *testing.T) {
	threshold := 100000
	// At exactly the threshold, should be "long".
	if classifyContext(threshold, threshold) != "long" {
		t.Fatalf("expected long at threshold %d", threshold)
	}
	// Just below, should be "normal".
	if classifyContext(threshold-1, threshold) != "normal" {
		t.Fatalf("expected normal at threshold-1 %d", threshold-1)
	}
}