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Running
File size: 9,459 Bytes
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"use client";
import q3Results from "../../results/qwen3.json"
import q3_30B_A3B_Results from "../../results/qwen3-30B-A3-results.json"
// import mockResults from "../../qwen3-final-results.json"
import { useMemo, useState, useEffect, useRef } from "react";
import { Card } from "@/components/ui/card";
import ForceDirectedGraph from "@/components/force-directed-graph";
import RunsList from "@/components/runs-list";
import {
Select,
SelectContent,
SelectItem,
SelectTrigger,
SelectValue
} from "@/components/ui/select";
import { Run as ForceGraphRun } from "@/components/reasoning-trace";
import { Badge } from "@/components/ui/badge";
import { Button } from "@/components/ui/button";
import { UploadIcon } from "lucide-react";
const defaultModels = {
"Qwen3-14B": q3Results,
"Qwen3-30B-A3B": q3_30B_A3B_Results,
}
// Use the type expected by RunsList
interface Run {
start_article: string;
destination_article: string;
steps: string[];
result: string;
}
// Interface for model statistics
interface ModelStats {
winPercentage: number;
avgSteps: number;
stdDevSteps: number;
totalRuns: number;
wins: number;
medianSteps: number;
minSteps: number;
maxSteps: number;
}
export default function ViewerTab({
handleTryRun,
}: {
handleTryRun: (startArticle: string, destinationArticle: string) => void;
}) {
const [selectedRun, setSelectedRun] = useState<number | null>(null);
const [runs, setRuns] = useState<Run[]>([]);
const [selectedModel, setSelectedModel] = useState<string>("Qwen3-14B");
const [modelStats, setModelStats] = useState<ModelStats | null>(null);
const [models, setModels] = useState(defaultModels);
const fileInputRef = useRef<HTMLInputElement>(null);
useEffect(() => {
// Convert the model data to the format expected by RunsList
const convertedRuns = models[selectedModel]?.runs?.map((run: {
start_article: string;
destination_article: string;
steps: { type: string; article: string }[];
result: string;
}) => ({
start_article: run.start_article,
destination_article: run.destination_article,
steps: run.steps.map((step: { article: string }) => step.article),
result: run.result
})) || [];
setRuns(convertedRuns);
// Calculate model statistics
const winRuns = convertedRuns.filter(run => run.result === "win");
const totalRuns = convertedRuns.length;
const wins = winRuns.length;
const winPercentage = totalRuns > 0 ? (wins / totalRuns) * 100 : 0;
// Calculate steps statistics for winning runs
const stepCounts = winRuns.map(run => run.steps.length);
const avgSteps = stepCounts.length > 0
? stepCounts.reduce((sum, count) => sum + count, 0) / stepCounts.length
: 0;
// Calculate standard deviation
const variance = stepCounts.length > 0
? stepCounts.reduce((sum, count) => sum + Math.pow(count - avgSteps, 2), 0) / stepCounts.length
: 0;
const stdDevSteps = Math.sqrt(variance);
// Calculate median, min, max steps
const sortedSteps = [...stepCounts].sort((a, b) => a - b);
const medianSteps = stepCounts.length > 0
? stepCounts.length % 2 === 0
? (sortedSteps[stepCounts.length / 2 - 1] + sortedSteps[stepCounts.length / 2]) / 2
: sortedSteps[Math.floor(stepCounts.length / 2)]
: 0;
const minSteps = stepCounts.length > 0 ? Math.min(...stepCounts) : 0;
const maxSteps = stepCounts.length > 0 ? Math.max(...stepCounts) : 0;
setModelStats({
winPercentage,
avgSteps,
stdDevSteps,
totalRuns,
wins,
medianSteps,
minSteps,
maxSteps
});
}, [selectedModel, models]);
const handleRunSelect = (runId: number) => {
setSelectedRun(runId);
};
const filterRuns = useMemo(() => {
return runs.filter(run => run.result === "win");
}, [runs]);
// Convert the runs to the format expected by ForceDirectedGraph
const forceGraphRuns = useMemo(() => {
return filterRuns.map((run): ForceGraphRun => ({
start_article: run.start_article,
destination_article: run.destination_article,
steps: run.steps.map(article => ({ type: "move", article }))
}));
}, [filterRuns]);
const handleFileUpload = (event: React.ChangeEvent<HTMLInputElement>) => {
const file = event.target.files?.[0];
if (!file) return;
const reader = new FileReader();
reader.onload = (e) => {
try {
const jsonData = JSON.parse(e.target?.result as string);
// Validate the JSON structure has the required fields
if (!jsonData.runs || !Array.isArray(jsonData.runs)) {
alert("Invalid JSON format. File must contain a 'runs' array.");
return;
}
// Create a filename-based model name, removing extension and path
const fileName = file.name.replace(/\.[^/.]+$/, "");
const modelName = `Custom: ${fileName}`;
// Add the new model to the models object
setModels(prev => ({
...prev,
[modelName]: jsonData
}));
// Select the newly added model
setSelectedModel(modelName);
} catch (error) {
alert(`Error parsing JSON file: ${error.message}`);
}
};
reader.readAsText(file);
// Reset the file input
if (fileInputRef.current) {
fileInputRef.current.value = '';
}
};
const handleUploadClick = () => {
fileInputRef.current?.click();
};
return (
<div className="grid grid-cols-1 md:grid-cols-12 gap-4 h-[calc(100vh-200px)] max-h-[calc(100vh-200px)] overflow-hidden p-2">
<Card className="p-3 col-span-12 row-start-1">
<div className="flex flex-col sm:flex-row items-start sm:items-center gap-3">
<div className="flex-shrink-0">
<Select value={selectedModel} onValueChange={setSelectedModel}>
<SelectTrigger className="w-[180px]">
<SelectValue placeholder="Select model" />
</SelectTrigger>
<SelectContent>
{Object.keys(models).map((modelName) => (
<SelectItem key={modelName} value={modelName}>
{modelName}
</SelectItem>
))}
</SelectContent>
</Select>
</div>
<Button
variant="outline"
size="sm"
className="flex items-center gap-1"
onClick={handleUploadClick}
>
<UploadIcon size={14} />
<span>Upload JSON</span>
<input
type="file"
ref={fileInputRef}
accept=".json"
className="hidden"
onChange={handleFileUpload}
/>
</Button>
{modelStats && (
<div className="flex flex-wrap gap-1.5 items-center">
<Badge variant="outline" className="px-2 py-0.5 flex gap-1 items-center">
<span className="text-xs font-medium">Success:</span>
<span className="text-xs font-semibold">{modelStats.winPercentage.toFixed(1)}%</span>
<span className="text-xs text-muted-foreground">({modelStats.wins}/{modelStats.totalRuns})</span>
</Badge>
<Badge variant="outline" className="px-2 py-0.5 flex gap-1 items-center">
<span className="text-xs font-medium">Mean:</span>
<span className="text-xs font-semibold">{modelStats.avgSteps.toFixed(1)}</span>
<span className="text-xs text-muted-foreground">±{modelStats.stdDevSteps.toFixed(1)}</span>
</Badge>
<Badge variant="outline" className="px-2 py-0.5 flex gap-1 items-center">
<span className="text-xs font-medium">Median:</span>
<span className="text-xs font-semibold">{modelStats.medianSteps.toFixed(1)}</span>
</Badge>
<Badge variant="outline" className="px-2 py-0.5 flex gap-1 items-center">
<span className="text-xs font-medium">Min:</span>
<span className="text-xs font-semibold">{modelStats.minSteps}</span>
</Badge>
<Badge variant="outline" className="px-2 py-0.5 flex gap-1 items-center">
<span className="text-xs font-medium">Max:</span>
<span className="text-xs font-semibold">{modelStats.maxSteps}</span>
</Badge>
</div>
)}
</div>
</Card>
<div className="md:col-span-3 flex flex-col max-h-full overflow-hidden">
<div className="bg-card rounded-lg p-3 border flex-grow overflow-hidden flex flex-col">
<h3 className="text-sm font-medium mb-2 text-muted-foreground flex-shrink-0">
Runs
</h3>
<div className="flex-grow overflow-hidden">
<RunsList
runs={filterRuns}
onSelectRun={handleRunSelect}
selectedRunId={selectedRun}
onTryRun={handleTryRun}
/>
</div>
</div>
</div>
<div className="md:col-span-9 max-h-full overflow-hidden">
<Card className="w-full h-full flex items-center justify-center p-0 m-0 overflow-hidden">
<ForceDirectedGraph runs={forceGraphRuns} runId={selectedRun} />
</Card>
</div>
</div>
);
}
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