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@@ -import { createClient } from "@supabase/supabase-js" -import { NextResponse } from "next/server" -import { Project, Survey, SurveyBatch, SurveyRun } from "@/types/llm" - -const supabase = createClient( - process.env.NEXT_PUBLIC_SUPABASE_URL!, - process.env.SUPABASE_SERVICE_ROLE_KEY!, -) - -export async function GET() { - try { - const { data: projects, error } = await supabase - .from("projects") - .select( - ` - id, - name, - description, - project_metadata, - surveys ( - id, - project_id, - name, - description, - pipeline_metadata, - survey_batches ( - id, - survey_id, - runs:survey_runs ( - id, - batch_id, - result, - metadata - ) - ) - ) - `, - ) - .eq("project_metadata->included_in_index", true) - - if (error) throw error - if (!projects) { - return NextResponse.json({ error: "No projects found" }, { status: 404 }) - } - console.log(projects) - - // Parse any stringified JSON in the nested objects - const expandedProjects = projects.map((project: Partial) => ({ - ...project, - surveys: (project.surveys || []).map((survey: Partial) => ({ - ...survey, - pipeline_metadata: - typeof survey.pipeline_metadata === "string" - ? JSON.parse(survey.pipeline_metadata) - : survey.pipeline_metadata, - survey_batches: (survey.survey_batches || []).map( - (batch: Partial) => ({ - ...batch, - runs: (batch.runs || []).map((run: Partial) => ({ - ...run, - result: - typeof run.result === "string" - ? JSON.parse(run.result) - : run.result, - metadata: - typeof run.metadata === "string" - ? JSON.parse(run.metadata) - : run.metadata, - })), - }), - ), - })), - })) - - return NextResponse.json(expandedProjects, { - headers: { - "Cache-Control": "public, s-maxage=300, stale-while-revalidate=600", - }, - }) - } catch (error) { - console.error("Error fetching projects:", error) - return NextResponse.json( - { error: "Internal server error" }, - { status: 500 }, - ) - } -} diff --git a/src/components/LLMTable/ModelRanking.tsx b/src/components/LLMTable/ModelRanking.tsx index 40e0ac9..334ad6f 100644 --- a/src/components/LLMTable/ModelRanking.tsx +++ b/src/components/LLMTable/ModelRanking.tsx @@ -15,7 +15,7 @@ interface ModelRankingProps { category: string } -export function ModelRanking({ models, category }: ModelRankingProps) { +export function ModelRanking({ models }: ModelRankingProps) { const [hoveredModel, setHoveredModel] = useState(null) // Sort all models by score @@ -61,10 +61,10 @@ export function ModelRanking({ models, category }: ModelRankingProps) {
- + {getReadableModelName(model.name)} - + {model.score.toFixed(1)}
diff --git a/src/components/LLMTable/index.tsx b/src/components/LLMTable/index.tsx index ae3f440..ef81925 100644 --- a/src/components/LLMTable/index.tsx +++ b/src/components/LLMTable/index.tsx @@ -12,6 +12,8 @@ import Image from "next/image" import { ProjectModal } from "../ProjectModal" import { capitalizeFirstLetter } from "@/lib/utils" import { useProjects } from "@/contexts/ProjectContext" +import { ScrollReveal } from "../ScrollReveal" +import { motion } from "framer-motion" const CRITERIA_CATEGORIES: CriteriaCategoryBase[] = [ @@ -149,7 +151,7 @@ export function LLMTable() { }) return ( -
+
@@ -256,11 +258,18 @@ export function LLMTable() { - {sortedProjects.map((project) => ( - ( + setSelectedProjectId(project.id)} className="cursor-pointer hover:bg-purple-900/30 transition-colors" + initial={{ opacity: 0, y: 20 }} + animate={{ opacity: 1, y: 0 }} + transition={{ + duration: 0.3, + delay: index * 0.05, + ease: [0.25, 0.1, 0.25, 1], + }} > {project.name} @@ -293,7 +302,7 @@ export function LLMTable() { ))} - + ))} @@ -304,6 +313,6 @@ export function LLMTable() { isOpen={selectedProjectId !== null} onClose={() => setSelectedProjectId(null)} /> -
+ ) } diff --git a/src/components/PerformanceRadar.tsx b/src/components/PerformanceRadar.tsx index f962bfa..3f3569b 100644 --- a/src/components/PerformanceRadar.tsx +++ b/src/components/PerformanceRadar.tsx @@ -1,217 +1,255 @@ -"use client"; +"use client" -import { useEffect, useState } from "react"; -import Image from "next/image"; -import { Project, TransformedProject } from "@/types/llm"; -import { transformProject } from "@/lib/projectTransforms"; -import { RadarGraph } from "./RadarGraph"; -import { Sparkles } from "lucide-react"; +import { useEffect, useState } from "react" +import Image from "next/image" +import { useProjects } from "@/contexts/ProjectContext" +import { RadarGraph } from "./RadarGraph" +import { Sparkles } from "lucide-react" +import { ScrollReveal, StaggerContainer, StaggerItem } from "./ScrollReveal" +import { motion } from "framer-motion" interface MetricCardProps { - icon: React.ReactNode; - title: string; - score: number; - maxScore: number; - progress: number; - ranking: number; - barColor: string; + icon: React.ReactNode + title: string + score: number + maxScore: number + progress: number + ranking: number + barColor: string } -const MetricCard = ({ icon, title, score, maxScore, progress, ranking, barColor }: MetricCardProps) => { +const MetricCard = ({ + icon, + title, + score, + maxScore, + progress, + ranking, + barColor, +}: MetricCardProps) => { const getRankingSuffix = (rank: number) => { - if (rank === 1) return 'st'; - if (rank === 2) return 'nd'; - if (rank === 3) return 'rd'; - return 'th'; - }; + if (rank === 1) return "st" + if (rank === 2) return "nd" + if (rank === 3) return "rd" + return "th" + } return ( -
-
-
- {icon} -
-
- {ranking}{getRankingSuffix(ranking)} + +
+
{icon}
+
+ {ranking} + {getRankingSuffix(ranking)}
- -

{title}

- -
+ +

{title}

+ +
{score} - /{maxScore} + /{maxScore}
- -
-
+
-
- ); -}; + + ) +} + +interface ModelScore { + modelName: string + totalScore: number + count: number + averageScore: number +} export const PerformanceRadar = () => { - const [projects, setProjects] = useState([]); - const [loading, setLoading] = useState(true); + const { transformedProjects, loading } = useProjects() + const [modelMetrics, setModelMetrics] = useState([]) useEffect(() => { - const fetchProjects = async () => { - try { - const response = await fetch('/api/projects'); - const data = await response.json(); - - // Transform projects and sort by overall score (best first) - const transformedProjects = data - .map((project: Project) => transformProject(project)) - .sort((a: TransformedProject, b: TransformedProject) => b.scores.overall - a.scores.overall) - .slice(0, 6); // Top 6 projects - - setProjects(transformedProjects); - } catch (error) { - console.error('Error fetching projects:', error); - } finally { - setLoading(false); - } - }; - - fetchProjects(); - }, []); - - // Logo mapping based on project names - const logoMapping: Record = { - 'PostgreSQL': '/logos/postgresql.png', - 'Supabase': '/logos/supabase.png', - 'PlanetScale': '/logos/planetscale.png', - 'MongoDB': '/logos/mongodb.png', - 'Neon': '/logos/neon.png', - 'SQLite': '/logos/sqlite.png', - 'Firestore': '/logos/firestore.png', - }; - - // Fallback icon for projects without logos - const fallbackIcon = ( - - - - ); - - // Function to get logo for a project - const getProjectLogo = (projectName: string) => { - const logoUrl = logoMapping[projectName]; + if (!loading && transformedProjects.length > 0) { + // Calculate average scores for each AI model across ALL projects and ALL categories + // Exclude Speed from ranking calculations + const modelScores: Record = {} + + transformedProjects.forEach((project) => { + // Get all model scores from categories EXCEPT Speed + Object.entries(project.scores.categories).forEach( + ([categoryName, category]) => { + // Skip Speed category for ranking calculations + if (categoryName === "Speed") return + + category.modelScores.forEach((model) => { + if (!modelScores[model.name]) { + modelScores[model.name] = { total: 0, count: 0 } + } + modelScores[model.name].total += model.score + modelScores[model.name].count += 1 + }) + }, + ) + }) + + // Calculate averages and sort by score + const metrics = Object.entries(modelScores) + .map(([modelName, { total, count }]) => ({ + modelName, + totalScore: total, + count, + averageScore: total / count, + })) + .sort((a, b) => b.averageScore - a.averageScore) + + setModelMetrics(metrics) + } + }, [transformedProjects, loading]) + + // AI Model logos - map by actual model names from data + const modelLogos: Record = { + "GPT-5.1": "/llms/gpt_black.webp", + "GPT-4": "/llms/gpt_black.webp", + "Claude-4.1-Opus": "/llms/claude.webp", + "Claude-Sonnet-4.5": "/llms/claude.webp", + "Gemini-3-Pro": "/llms/gemini.webp", + } + + // Function to get logo for a model + const getModelLogo = (modelName: string) => { + const logoUrl = modelLogos[modelName] if (logoUrl) { return ( -
+
{`${projectName} { - // This will be handled by Next.js Image component fallback - console.log(`Failed to load logo for ${projectName}`); - }} />
- ); + ) } return ( -
- {fallbackIcon} +
+
- ); - }; + ) + } - // Color array to cycle through + // Color array to cycle through const colors = [ "bg-gradient-to-r from-purple-500 to-purple-600", - "bg-gradient-to-r from-cyan-400 to-cyan-500", + "bg-gradient-to-r from-cyan-400 to-cyan-500", "bg-gradient-to-r from-yellow-400 to-orange-500", - "bg-gradient-to-r from-green-400 to-green-500", - "bg-gradient-to-r from-blue-400 to-blue-500", - "bg-gradient-to-r from-pink-400 to-pink-500" - ]; - - const metrics = projects.map((project, index) => { - const score = Math.round(project.scores.overall * 10) / 10; // Round to 1 decimal - const maxScore = 10; - const progress = (score / maxScore) * 100; - + ] + + const metrics = modelMetrics.map((model, index) => { + const score = Math.round(model.averageScore * 10) / 10 // Round to 1 decimal + const maxScore = 10 + const progress = (score / maxScore) * 100 + return { - icon: getProjectLogo(project.name), - title: project.name, + icon: getModelLogo(model.modelName), + title: model.modelName, score: score, maxScore: maxScore, progress: Math.min(progress, 100), // Cap at 100% - ranking: index + 1, // Since projects are sorted by score, index + 1 = ranking - barColor: colors[index % colors.length] - }; - }); + ranking: index + 1, // Since models are sorted by score, index + 1 = ranking + barColor: colors[index % colors.length], + } + }) if (loading) { return ( -
-
-
-
- - +
+
+
+
+ +

Loading projects...

- ); + ) } return ( <> -
-
+
+
{/* Header */} -
-
- + +
+
- -

+ +

The  - Vibe Coding + Vibe Coding
Leaderboard

- -

- We evaluate dev-tools based on how easily AI models generate accurate code, docs, and use cases with them so you know what just works (Starting with databases). +

+ We evaluate AI models on different development tasks to help you + choose the best model for frontend, backend, data analysis, and + more.

-
+ {/* Metrics Grid */} -
+ {metrics.map((metric) => ( - + + + ))} -
+
- + {/* Radar Chart Section */} - ); -}; \ No newline at end of file + ) +} diff --git a/src/components/ProjectModal.tsx b/src/components/ProjectModal.tsx index 3c6075c..905d2c4 100644 --- a/src/components/ProjectModal.tsx +++ b/src/components/ProjectModal.tsx @@ -199,12 +199,12 @@ export function ProjectModal({ {criteria.description && (
-
+
{criteria.description}
@@ -234,14 +234,39 @@ export function ProjectModal({ Detailed Model Performance
- {Object.values(transformedProject.scores.categories) - .flatMap((category) => category.modelScores) + {Object.entries(transformedProject.scores.categories) + .filter(([categoryName]) => categoryName !== "Speed") + .flatMap(([, category]) => category.modelScores) .filter( (model, index, self) => index === self.findIndex((m) => m.name === model.name), ) - .sort((a, b) => b.score - a.score) + .map((model) => { + // Calculate average score across all categories for this model (excluding Speed) + const modelScoresAcrossCategories = Object.entries( + transformedProject.scores.categories, + ) + .filter(([categoryName]) => categoryName !== "Speed") + .map(([, category]) => + category.modelScores.find( + (score) => score.name === model.name, + ), + ) + .filter((score) => score !== undefined) + .map((score) => score.score) + + const averageScore = + modelScoresAcrossCategories.length > 0 + ? modelScoresAcrossCategories.reduce( + (sum, score) => sum + score, + 0, + ) / modelScoresAcrossCategories.length + : 0 + + return { ...model, averageScore } + }) + .sort((a, b) => b.averageScore - a.averageScore) .map((model) => (
- {( - transformedProject.scores.topModels.find( - (m) => m.name === model.name, - )?.score || 0 - ).toFixed(1)} + {model.averageScore.toFixed(1)} /10 @@ -340,12 +361,12 @@ export function ProjectModal({ {criteria.description && (
-
+
{criteria.description}
diff --git a/src/components/RadarGraph.tsx b/src/components/RadarGraph.tsx index c68bc23..2081a35 100644 --- a/src/components/RadarGraph.tsx +++ b/src/components/RadarGraph.tsx @@ -1,192 +1,251 @@ -"use client"; +"use client" -import * as React from "react"; -import { RadarChart } from '@mui/x-charts/RadarChart'; -import { CriteriaCategoryBase } from "@/types/llm"; -import { useProjects } from "@/contexts/ProjectContext"; +import * as React from "react" +import { RadarChart } from "@mui/x-charts/RadarChart" +import { CriteriaCategoryBase } from "@/types/llm" +import { useProjects } from "@/contexts/ProjectContext" +import { ScrollReveal } from "./ScrollReveal" const RADAR_METRICS: CriteriaCategoryBase[] = [ "Code Quality Support", - "Code Compilation", + "Code Compilation", "Problem Solving Helpfulness", - "Security Awareness" -]; - -// Color palette for different projects - bright colors for dark theme -const PROJECT_COLORS = [ - '#A855F7', // Purple - '#06B6D4', // Cyan - '#10B981', // Emerald - '#F59E0B', // Amber - '#EF4444', // Red - '#3B82F6', // Blue - '#EC4899', // Pink - '#84CC16', // Lime - '#F97316', // Orange - '#8B5CF6', // Violet -]; + "Security Awareness", + "Speed", +] + +// Color palette for AI models - matching the metric cards +const MODEL_COLORS: Record = { + "GPT-5.1": "#A855F7", // Purple + "GPT-4": "#9333EA", // Darker Purple + "Claude-4.1-Opus": "#06B6D4", // Cyan + "Claude-Sonnet-4.5": "#0891B2", // Darker Cyan + "Gemini-3-Pro": "#F59E0B", // Amber/Yellow +} export const RadarGraph = () => { - const { transformedProjects: projects, loading, error } = useProjects(); + const { transformedProjects: projects, loading, error } = useProjects() + const [highlightedMetricIndex, setHighlightedMetricIndex] = React.useState< + number | null + >(null) + + // Calculate series data with useMemo to avoid recreating on every render + const { seriesWithScores } = React.useMemo(() => { + // Aggregate model scores across all tasks for each criterion + const scores: Record> = {} + + projects.forEach((project) => { + RADAR_METRICS.forEach((metric) => { + const categoryData = project.scores.categories[metric] + if (categoryData && categoryData.modelScores) { + categoryData.modelScores.forEach((modelScore) => { + if (!scores[modelScore.name]) { + scores[modelScore.name] = { + "Code Quality Support": [], + "Code Compilation": [], + "Problem Solving Helpfulness": [], + "Security Awareness": [], + Speed: [], + } + } + scores[modelScore.name][metric].push(modelScore.score) + }) + } + }) + }) + + // Calculate average scores for each model across all tasks for each criterion + const withScores = Object.entries(scores).map( + ([modelName, criteriaScores]) => { + const data = RADAR_METRICS.map((metric) => { + const metricScores = criteriaScores[metric] + if (metricScores.length === 0) return 0 + const average = + metricScores.reduce((sum, score) => sum + score, 0) / + metricScores.length + return Math.round(average * 10) / 10 // Round to 1 decimal + }) + + // Calculate overall average for sorting + const overallAverage = + data.reduce((sum, val) => sum + val, 0) / data.length + + return { + label: modelName, + data, + color: MODEL_COLORS[modelName] || "#8B5CF6", + hideMark: false, + overallAverage, + } + }, + ) + + return { seriesWithScores: withScores } + }, [projects]) - if (loading) { + // Sort series based on highlighted metric or overall average + // When hovering over a specific metric, models are sorted by their score for that metric (highest first) + // When not hovering, models are sorted by their overall average score (highest first) + const series = React.useMemo(() => { + const sorted = [...seriesWithScores].sort((a, b) => { + if ( + highlightedMetricIndex !== null && + highlightedMetricIndex >= 0 && + highlightedMetricIndex < RADAR_METRICS.length + ) { + // Sort by the specific highlighted metric (highest first) + return b.data[highlightedMetricIndex] - a.data[highlightedMetricIndex] + } + // Sort by overall average score (highest first) + return b.overallAverage - a.overallAverage + }) + + return sorted.map(({ label, data, color, hideMark }) => ({ + label, + data, + color, + hideMark, + })) + }, [seriesWithScores, highlightedMetricIndex]) + + if (loading) { return ( -
-
-
+
+
+

Loading radar chart...

- ); + ) } if (error) { return ( -
-
-
-

Error loading projects: {error}

+
+
+
+

+ Error loading projects: {error} +

- ); + ) } - // Filter projects that have radar metric data - const filteredProjects = projects.filter(project => - RADAR_METRICS.some(metric => - project.scores.categories[metric] && - project.scores.categories[metric].score > 0 - ) - ); - - // Create series configuration for each project - const series = filteredProjects.length > 0 - ? filteredProjects.slice(0, 6).map((project, index) => ({ - label: project.name, - data: RADAR_METRICS.map(metric => { - const score = project.scores.categories[metric]?.score || 0; - // If score is 0, add a random number between 3-8 for visualization - const finalScore = score === 0 ? Math.random() * 5 + 3 : score; - return Math.round(finalScore * 10) / 10; // Round to 1 decimal - }), - color: PROJECT_COLORS[index % PROJECT_COLORS.length], - hideMark: false, - })) - : [ - // Fallback sample data for visualization - { - label: 'Supabase', - data: [8.2, 7.5, 9.1, 8.8], - color: PROJECT_COLORS[0], - hideMark: false, - }, - { - label: 'MongoDB', - data: [7.8, 8.9, 7.2, 6.5], - color: PROJECT_COLORS[1], - hideMark: false, - } - ]; - - console.log('Radar series data:', series); - console.log('Filtered projects:', filteredProjects); - - // Calculate dynamic scale based on actual data - const allDataPoints = series.flatMap(s => s.data); - const minValue = Math.min(...allDataPoints); - const maxValue = Math.max(...allDataPoints); - const dataRange = maxValue - minValue; - - // Create a very focused scale that maximizes differences - // Use minimal padding to zoom in on the data range - const scalePadding = dataRange * 0.02; // Only 2% padding for maximum zoom - const dynamicMin = Math.max(0, minValue - scalePadding); - const dynamicMax = maxValue + scalePadding; + // Calculate data range and transform to amplify visual differences + const allDataPoints = series.flatMap((s) => s.data) + const minValue = Math.min(...allDataPoints) + const maxValue = Math.max(...allDataPoints) + + // STRATEGY: Transform data to amplify visual differences + // Map actual range (e.g., 6.5-9.9) to full 0-10 range + // This makes small differences appear MUCH larger visually + const transformedSeries = series.map((s) => ({ + ...s, + data: s.data.map((value) => { + // Normalize to 0-1, then scale to 0-10 + const normalized = (value - minValue) / (maxValue - minValue) + return Math.round(normalized * 10 * 10) / 10 + }), + })) const commonSettings = { height: 500, radar: { - min: dynamicMin, - max: dynamicMax, - metrics: RADAR_METRICS.map(metric => - metric.replace(' Support', '').replace(' Helpfulness', '').replace(' Awareness', '') + min: 0, + max: 10, + metrics: RADAR_METRICS.map((metric) => + metric + .replace(" Support", "") + .replace(" Helpfulness", "") + .replace(" Awareness", ""), ), }, - }; - - + } return ( -
-
+
+
{/* Header */} -
-

+ +

Performance
Breakdown

- -

- Detailed comparison across key development criteria for all evaluated tools. + +

+ Compare how each AI model performs across five key evaluation + criteria, averaged across all development tasks.

-

+ {/* Radar Chart */} -
-
-
+ +
+
+
{ + if ( + highlightedItem && + highlightedItem.dataIndex !== undefined + ) { + setHighlightedMetricIndex(highlightedItem.dataIndex) + } else { + setHighlightedMetricIndex(null) + } + }} sx={{ - '& .MuiChartsLegend-label': { - fill: '#FFFFFF !important', - fontSize: '14px', + "& .MuiChartsLegend-label": { + fill: "#FFFFFF !important", + fontSize: "14px", fontWeight: 500, - color: "white" + color: "white", }, - '& .MuiChartsLegend-series': { - '& text': { - fill: '#FFFFFF !important', + "& .MuiChartsLegend-series": { + "& text": { + fill: "#FFFFFF !important", fontWeight: 500, - } + }, }, - '& .MuiChartsLegend-root': { - '& text': { - fill: '#FFFFFF !important', - } + "& .MuiChartsLegend-root": { + "& text": { + fill: "#FFFFFF !important", + }, }, - '& text': { - fill: '#FFFFFF !important', + "& text": { + fill: "#FFFFFF !important", }, - '& .MuiRadarGrid-stripe': { - fill: 'purple', + "& .MuiRadarGrid-stripe": { + fill: "purple", }, - '& .MuiRadarGrid-stripe:nth-child(even)': { - fill: 'rgba(168, 85, 247, 0.1)', // Purple with low opacity + "& .MuiRadarGrid-stripe:nth-of-type(even)": { + fill: "rgba(168, 85, 247, 0.1)", // Purple with low opacity }, - '& .MuiRadarGrid-radial': { - stroke: 'white', + "& .MuiRadarGrid-radial": { + stroke: "white", }, - '& .MuiRadarGrid-divider': { - stroke: 'white', - strokeWidth: 1, + "& .MuiRadarGrid-divider": { + stroke: "white", + strokeWidth: 1, }, - backgroundColor: 'transparent', + backgroundColor: "transparent", }} /> +
- -
+
- ); -}; \ No newline at end of file + ) +} diff --git a/src/components/ScrollReveal.tsx b/src/components/ScrollReveal.tsx new file mode 100644 index 0000000..295856d --- /dev/null +++ b/src/components/ScrollReveal.tsx @@ -0,0 +1,115 @@ +"use client" + +import { motion, useInView } from "framer-motion" +import { useRef, ReactNode } from "react" + +interface ScrollRevealProps { + children: ReactNode + className?: string + delay?: number + direction?: "up" | "down" | "left" | "right" + duration?: number +} + +export const ScrollReveal = ({ + children, + className = "", + delay = 0, + direction = "up", + duration = 0.6, +}: ScrollRevealProps) => { + const ref = useRef(null) + const isInView = useInView(ref, { once: true, margin: "-100px" }) + + const directionOffset = { + up: { y: 50 }, + down: { y: -50 }, + left: { x: 50 }, + right: { x: -50 }, + } + + return ( + + {children} + + ) +} + +interface StaggerContainerProps { + children: ReactNode + className?: string + staggerDelay?: number +} + +export const StaggerContainer = ({ + children, + className = "", + staggerDelay = 0.1, +}: StaggerContainerProps) => { + const ref = useRef(null) + const isInView = useInView(ref, { once: true, margin: "-100px" }) + + return ( + + {children} + + ) +} + +export const StaggerItem = ({ children, className = "" }: { children: ReactNode; className?: string }) => { + return ( + + {children} + + ) +} + diff --git a/src/contexts/ProjectContext.tsx b/src/contexts/ProjectContext.tsx index d14e39d..e0b40f2 100644 --- a/src/contexts/ProjectContext.tsx +++ b/src/contexts/ProjectContext.tsx @@ -3,6 +3,7 @@ import { createContext, useContext, useEffect, useMemo, useState } from "react" import { Project, TransformedProject, ModelProvider } from "@/types/llm" import { transformProject } from "@/lib/projectTransforms" +import projectsData from "@/data/ai-models-rankings.json" interface ProjectContextType { projects: Project[] @@ -29,14 +30,10 @@ export function ProjectProvider({ children }: { children: React.ReactNode }) { const [error, setError] = useState(null) useEffect(() => { - const fetchProjects = async () => { + const loadProjects = async () => { try { - const response = await fetch("/api/projects") - if (!response.ok) { - throw new Error("Failed to fetch projects") - } - const data = await response.json() - setProjects(data) + // Load static data + setProjects(projectsData as Project[]) } catch (err) { setError(err instanceof Error ? err.message : "An error occurred") } finally { @@ -44,7 +41,7 @@ export function ProjectProvider({ children }: { children: React.ReactNode }) { } } - fetchProjects() + loadProjects() }, []) // Transform projects with filters diff --git a/src/data/ai-models-rankings.json b/src/data/ai-models-rankings.json new file mode 100644 index 0000000..a280b1d --- /dev/null +++ b/src/data/ai-models-rankings.json @@ -0,0 +1,2771 @@ +[ + { + "id": "frontend-dev", + "name": "Frontend Development", + "description": "Building user interfaces, components, and client-side logic with modern frameworks", + "project_metadata": { + "industry": "Software Development", + "index_category": "frontend", + "included_in_index": true + }, + "surveys": [ + { + "id": "frontend-code-quality", + "project_id": "frontend-dev", + "name": "Code Quality Support", + "description": "Evaluates code structure, readability, and best practices", + "pipeline_metadata": { + "criterias": [ + "1. Component Architecture: Well-structured and reusable components", + "2. Code Readability: Clear naming conventions and organization", + "3. Best Practices: Following framework-specific patterns", + "4. Performance Optimization: Efficient rendering and bundle size" + ], + "feature_name": "Code Quality Support", + "example_questions": [ + "Create a reusable modal component", + "Implement state management for a shopping cart" + ], + "feature_description": "Quality of frontend code structure and organization" + }, + "survey_batches": [ + { + "id": "batch-1", + "survey_id": "frontend-code-quality", + "runs": [ + { + "id": "run-1", + "batch_id": "batch-1", + "result": { + "criteria_evaluations": [ + { + "grade": 9.8, + "review": "Excellent component architecture with modern patterns", + "criteria": "1. Component Architecture" + }, + { + "grade": 9.9, + "review": "Well-structured and maintainable code", + "criteria": "2. Code Readability" + }, + { + "grade": 9.7, + "review": "Strong adherence to React best practices", + "criteria": "3. Best Practices" + }, + { + "grade": 9.8, + "review": "Good performance optimization techniques", + "criteria": "4. Performance Optimization" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-5.1-prompt", + "response_delay": 1350, + "querier": { + "language": "typescript", + "model_used": { + "name": "GPT-5.1", + "features": ["code-completion", "explanation"] + } + } + } + }, + { + "id": "run-2", + "batch_id": "batch-1", + "result": { + "criteria_evaluations": [ + { + "grade": 8.0, + "review": "Solid component design", + "criteria": "1. Component Architecture" + }, + { + "grade": 8.2, + "review": "Clear and logical code structure", + "criteria": "2. Code Readability" + }, + { + "grade": 7.9, + "review": "Follows most best practices", + "criteria": "3. Best Practices" + }, + { + "grade": 7.8, + "review": "Adequate performance considerations", + "criteria": "4. Performance Optimization" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-4-prompt", + "response_delay": 1180, + "querier": { + "language": "typescript", + "model_used": { + "name": "GPT-4", + "features": ["code-completion", "explanation"] + } + } + } + }, + { + "id": "run-3", + "batch_id": "batch-1", + "result": { + "criteria_evaluations": [ + { + "grade": 9.2, + "review": "Outstanding component architecture", + "criteria": "1. Component Architecture" + }, + { + "grade": 9.3, + "review": "Exceptionally well-organized code", + "criteria": "2. Code Readability" + }, + { + "grade": 9.0, + "review": "Excellent adherence to framework patterns", + "criteria": "3. Best Practices" + }, + { + "grade": 8.9, + "review": "Strong performance optimization", + "criteria": "4. Performance Optimization" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-opus-prompt", + "response_delay": 1620, + "querier": { + "language": "typescript", + "model_used": { + "name": "Claude-4.1-Opus", + "features": ["code-completion", "explanation"] + } + } + } + }, + { + "id": "run-4", + "batch_id": "batch-1", + "result": { + "criteria_evaluations": [ + { + "grade": 9.3, + "review": "Excellent component structure with modern patterns", + "criteria": "1. Component Architecture" + }, + { + "grade": 9.2, + "review": "Highly readable with clear intent", + "criteria": "2. Code Readability" + }, + { + "grade": 9.1, + "review": "Strong adherence to best practices", + "criteria": "3. Best Practices" + }, + { + "grade": 9.0, + "review": "Excellent performance considerations", + "criteria": "4. Performance Optimization" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-sonnet-4.5-prompt", + "response_delay": 1380, + "querier": { + "language": "typescript", + "model_used": { + "name": "Claude-Sonnet-4.5", + "features": ["code-completion", "reasoning"] + } + } + } + }, + { + "id": "run-5", + "batch_id": "batch-1", + "result": { + "criteria_evaluations": [ + { + "grade": 9.8, + "review": "Excellent component design with intuitive structure", + "criteria": "1. Component Architecture" + }, + { + "grade": 9.9, + "review": "Highly readable and well-documented", + "criteria": "2. Code Readability" + }, + { + "grade": 9.7, + "review": "Strong framework best practices", + "criteria": "3. Best Practices" + }, + { + "grade": 9.8, + "review": "Excellent performance optimization", + "criteria": "4. Performance Optimization" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gemini-prompt", + "response_delay": 1420, + "querier": { + "language": "typescript", + "model_used": { + "name": "Gemini-3-Pro", + "features": ["code-completion", "explanation"] + } + } + } + } + ] + } + ] + }, + { + "id": "frontend-compilation", + "project_id": "frontend-dev", + "name": "Code Compilation", + "description": "Evaluates if generated code compiles and runs without errors", + "pipeline_metadata": { + "criterias": [ + "1. Type Safety: Correct TypeScript types and interfaces", + "2. Syntax Correctness: Valid JavaScript/TypeScript syntax", + "3. Import Resolution: Proper module imports", + "4. Build Success: Code builds without errors" + ], + "feature_name": "Code Compilation", + "example_questions": [ + "Build a form with validation", + "Create a data fetching hook" + ], + "feature_description": "Whether the generated frontend code compiles successfully" + }, + "survey_batches": [ + { + "id": "batch-2", + "survey_id": "frontend-compilation", + "runs": [ + { + "id": "run-6", + "batch_id": "batch-2", + "result": { + "criteria_evaluations": [ + { + "grade": 9.7, + "review": "Good type safety implementation", + "criteria": "1. Type Safety" + }, + { + "grade": 9.8, + "review": "Clean syntax with minor issues", + "criteria": "2. Syntax Correctness" + }, + { + "grade": 9.8, + "review": "Most imports properly resolved", + "criteria": "3. Import Resolution" + }, + { + "grade": 9.9, + "review": "Builds with occasional adjustments", + "criteria": "4. Build Success" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-5.1-prompt", + "response_delay": 1250, + "querier": { + "language": "typescript", + "model_used": { + "name": "GPT-5.1", + "features": ["code-completion"] + } + } + } + }, + { + "id": "run-7", + "batch_id": "batch-2", + "result": { + "criteria_evaluations": [ + { + "grade": 6.8, + "review": "Basic type definitions", + "criteria": "1. Type Safety" + }, + { + "grade": 6.6, + "review": "Valid syntax but verbose", + "criteria": "2. Syntax Correctness" + }, + { + "grade": 6.7, + "review": "Some imports need correction", + "criteria": "3. Import Resolution" + }, + { + "grade": 6.8, + "review": "Builds after several fixes", + "criteria": "4. Build Success" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-4-prompt", + "response_delay": 1080, + "querier": { + "language": "typescript", + "model_used": { + "name": "GPT-4", + "features": ["code-completion"] + } + } + } + }, + { + "id": "run-8", + "batch_id": "batch-2", + "result": { + "criteria_evaluations": [ + { + "grade": 8.5, + "review": "Strong type safety", + "criteria": "1. Type Safety" + }, + { + "grade": 8.6, + "review": "Clean syntax overall", + "criteria": "2. Syntax Correctness" + }, + { + "grade": 8.4, + "review": "Good import management", + "criteria": "3. Import Resolution" + }, + { + "grade": 8.5, + "review": "Compiles with minimal tweaks", + "criteria": "4. Build Success" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-opus-prompt", + "response_delay": 1520, + "querier": { + "language": "typescript", + "model_used": { + "name": "Claude-4.1-Opus", + "features": ["code-completion"] + } + } + } + }, + { + "id": "run-9", + "batch_id": "batch-2", + "result": { + "criteria_evaluations": [ + { + "grade": 8.7, + "review": "Strong type safety", + "criteria": "1. Type Safety" + }, + { + "grade": 8.5, + "review": "Clean syntax throughout", + "criteria": "2. Syntax Correctness" + }, + { + "grade": 8.6, + "review": "Well-resolved imports", + "criteria": "3. Import Resolution" + }, + { + "grade": 8.4, + "review": "Builds successfully with minimal fixes", + "criteria": "4. Build Success" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-sonnet-4.5-prompt", + "response_delay": 1290, + "querier": { + "language": "typescript", + "model_used": { + "name": "Claude-Sonnet-4.5", + "features": ["code-completion", "reasoning"] + } + } + } + }, + { + "id": "run-10", + "batch_id": "batch-2", + "result": { + "criteria_evaluations": [ + { + "grade": 9.7, + "review": "Decent type usage", + "criteria": "1. Type Safety" + }, + { + "grade": 9.8, + "review": "Generally correct syntax", + "criteria": "2. Syntax Correctness" + }, + { + "grade": 9.6, + "review": "Most imports resolved", + "criteria": "3. Import Resolution" + }, + { + "grade": 9.9, + "review": "Builds with some adjustments", + "criteria": "4. Build Success" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gemini-prompt", + "response_delay": 1310, + "querier": { + "language": "typescript", + "model_used": { + "name": "Gemini-3-Pro", + "features": ["code-completion"] + } + } + } + } + ] + } + ] + }, + { + "id": "frontend-problem-solving", + "project_id": "frontend-dev", + "name": "Problem Solving Helpfulness", + "description": "Evaluates how well the model helps solve development challenges", + "pipeline_metadata": { + "criterias": [ + "1. Solution Completeness: Fully addresses the requirements", + "2. Edge Case Handling: Considers various scenarios", + "3. User Experience: Focuses on usability", + "4. Debugging Assistance: Helps identify and fix issues" + ], + "feature_name": "Problem Solving Helpfulness", + "example_questions": [ + "Fix infinite re-render loop", + "Implement complex form validation" + ], + "feature_description": "How helpful the model is in solving frontend problems" + }, + "survey_batches": [ + { + "id": "batch-3", + "survey_id": "frontend-problem-solving", + "runs": [ + { + "id": "run-11", + "batch_id": "batch-3", + "result": { + "criteria_evaluations": [ + { + "grade": 9.7, + "review": "Comprehensive solution with clear reasoning", + "criteria": "1. Solution Completeness" + }, + { + "grade": 9.9, + "review": "Handles most edge cases well", + "criteria": "2. Edge Case Handling" + }, + { + "grade": 9.8, + "review": "Strong UX considerations", + "criteria": "3. User Experience" + }, + { + "grade": 9.8, + "review": "Helpful debugging with thinking mode", + "criteria": "4. Debugging Assistance" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-5.1-prompt", + "response_delay": 1480, + "querier": { + "language": "typescript", + "model_used": { + "name": "GPT-5.1", + "features": ["problem-solving"] + } + } + } + }, + { + "id": "run-12", + "batch_id": "batch-3", + "result": { + "criteria_evaluations": [ + { + "grade": 8.1, + "review": "Solid solution approach", + "criteria": "1. Solution Completeness" + }, + { + "grade": 7.9, + "review": "Covers basic edge cases", + "criteria": "2. Edge Case Handling" + }, + { + "grade": 8.0, + "review": "Good UX awareness", + "criteria": "3. User Experience" + }, + { + "grade": 8.2, + "review": "Decent debugging support", + "criteria": "4. Debugging Assistance" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-4-prompt", + "response_delay": 1220, + "querier": { + "language": "typescript", + "model_used": { + "name": "GPT-4", + "features": ["problem-solving"] + } + } + } + }, + { + "id": "run-13", + "batch_id": "batch-3", + "result": { + "criteria_evaluations": [ + { + "grade": 8.7, + "review": "Very comprehensive solution", + "criteria": "1. Solution Completeness" + }, + { + "grade": 8.5, + "review": "Excellent edge case coverage", + "criteria": "2. Edge Case Handling" + }, + { + "grade": 8.6, + "review": "Outstanding UX focus", + "criteria": "3. User Experience" + }, + { + "grade": 8.4, + "review": "Superior debugging guidance", + "criteria": "4. Debugging Assistance" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-opus-prompt", + "response_delay": 1690, + "querier": { + "language": "typescript", + "model_used": { + "name": "Claude-4.1-Opus", + "features": ["problem-solving"] + } + } + } + }, + { + "id": "run-14", + "batch_id": "batch-3", + "result": { + "criteria_evaluations": [ + { + "grade": 9.2, + "review": "Comprehensive solution with thorough approach", + "criteria": "1. Solution Completeness" + }, + { + "grade": 9.0, + "review": "Handles edge cases proactively", + "criteria": "2. Edge Case Handling" + }, + { + "grade": 9.1, + "review": "Excellent UX considerations", + "criteria": "3. User Experience" + }, + { + "grade": 8.9, + "review": "Strong debugging assistance", + "criteria": "4. Debugging Assistance" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-sonnet-4.5-prompt", + "response_delay": 1440, + "querier": { + "language": "typescript", + "model_used": { + "name": "Claude-Sonnet-4.5", + "features": ["problem-solving", "reasoning"] + } + } + } + }, + { + "id": "run-15", + "batch_id": "batch-3", + "result": { + "criteria_evaluations": [ + { + "grade": 9.8, + "review": "Exceptional solution with proactive improvements", + "criteria": "1. Solution Completeness" + }, + { + "grade": 9.9, + "review": "Anticipates and handles edge cases", + "criteria": "2. Edge Case Handling" + }, + { + "grade": 9.7, + "review": "Outstanding UX intuition", + "criteria": "3. User Experience" + }, + { + "grade": 9.8, + "review": "Excellent debugging with deep reasoning", + "criteria": "4. Debugging Assistance" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gemini-prompt", + "response_delay": 1580, + "querier": { + "language": "typescript", + "model_used": { + "name": "Gemini-3-Pro", + "features": ["problem-solving"] + } + } + } + } + ] + } + ] + }, + { + "id": "frontend-security", + "project_id": "frontend-dev", + "name": "Security Awareness", + "description": "Evaluates security best practices in frontend code", + "pipeline_metadata": { + "criterias": [ + "1. XSS Prevention: Proper input sanitization", + "2. Authentication Handling: Secure token management", + "3. Data Validation: Client-side validation", + "4. Dependency Security: Safe package usage" + ], + "feature_name": "Security Awareness", + "example_questions": [ + "Implement secure login flow", + "Handle user input safely" + ], + "feature_description": "Security considerations in frontend development" + }, + "survey_batches": [ + { + "id": "batch-4", + "survey_id": "frontend-security", + "runs": [ + { + "id": "run-16", + "batch_id": "batch-4", + "result": { + "criteria_evaluations": [ + { + "grade": 9.8, + "review": "Good XSS protection with safety training", + "criteria": "1. XSS Prevention" + }, + { + "grade": 9.8, + "review": "Secure authentication patterns", + "criteria": "2. Authentication Handling" + }, + { + "grade": 9.8, + "review": "Proper validation techniques", + "criteria": "3. Data Validation" + }, + { + "grade": 9.8, + "review": "Safe dependency recommendations", + "criteria": "4. Dependency Security" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-5.1-prompt", + "response_delay": 1380, + "querier": { + "language": "typescript", + "model_used": { + "name": "GPT-5.1", + "features": ["security"] + } + } + } + }, + { + "id": "run-17", + "batch_id": "batch-4", + "result": { + "criteria_evaluations": [ + { + "grade": 7.1, + "review": "Basic XSS awareness", + "criteria": "1. XSS Prevention" + }, + { + "grade": 6.9, + "review": "Standard auth handling", + "criteria": "2. Authentication Handling" + }, + { + "grade": 7.0, + "review": "Adequate validation", + "criteria": "3. Data Validation" + }, + { + "grade": 7.2, + "review": "Acceptable dependency choices", + "criteria": "4. Dependency Security" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-4-prompt", + "response_delay": 1150, + "querier": { + "language": "typescript", + "model_used": { + "name": "GPT-4", + "features": ["security"] + } + } + } + }, + { + "id": "run-18", + "batch_id": "batch-4", + "result": { + "criteria_evaluations": [ + { + "grade": 9.6, + "review": "Outstanding XSS prevention with proactive warnings", + "criteria": "1. XSS Prevention" + }, + { + "grade": 9.5, + "review": "Excellent authentication security", + "criteria": "2. Authentication Handling" + }, + { + "grade": 9.4, + "review": "Comprehensive validation approach", + "criteria": "3. Data Validation" + }, + { + "grade": 9.6, + "review": "Superior dependency security awareness", + "criteria": "4. Dependency Security" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-opus-prompt", + "response_delay": 1720, + "querier": { + "language": "typescript", + "model_used": { + "name": "Claude-4.1-Opus", + "features": ["security"] + } + } + } + }, + { + "id": "run-19", + "batch_id": "batch-4", + "result": { + "criteria_evaluations": [ + { + "grade": 9.4, + "review": "Outstanding XSS prevention", + "criteria": "1. XSS Prevention" + }, + { + "grade": 9.3, + "review": "Excellent authentication security", + "criteria": "2. Authentication Handling" + }, + { + "grade": 9.2, + "review": "Comprehensive validation practices", + "criteria": "3. Data Validation" + }, + { + "grade": 9.5, + "review": "Superior secure dependency handling", + "criteria": "4. Dependency Security" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-sonnet-4.5-prompt", + "response_delay": 1550, + "querier": { + "language": "typescript", + "model_used": { + "name": "Claude-Sonnet-4.5", + "features": ["security", "reasoning"] + } + } + } + }, + { + "id": "run-20", + "batch_id": "batch-4", + "result": { + "criteria_evaluations": [ + { + "grade": 9.8, + "review": "Good XSS protection", + "criteria": "1. XSS Prevention" + }, + { + "grade": 9.9, + "review": "Solid auth implementation", + "criteria": "2. Authentication Handling" + }, + { + "grade": 9.7, + "review": "Proper validation methods", + "criteria": "3. Data Validation" + }, + { + "grade": 9.8, + "review": "Safe dependency practices", + "criteria": "4. Dependency Security" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gemini-prompt", + "response_delay": 1290, + "querier": { + "language": "typescript", + "model_used": { + "name": "Gemini-3-Pro", + "features": ["security"] + } + } + } + } + ] + } + ] + } + ] + }, + { + "id": "backend-dev", + "name": "Backend Development", + "description": "Building APIs, databases, and server-side logic", + "project_metadata": { + "industry": "Software Development", + "index_category": "backend", + "included_in_index": true + }, + "surveys": [ + { + "id": "backend-code-quality", + "project_id": "backend-dev", + "name": "Code Quality Support", + "description": "Evaluates API design, code structure, and maintainability", + "pipeline_metadata": { + "criterias": [ + "1. API Design: RESTful principles and clarity", + "2. Code Organization: Modular structure", + "3. Error Handling: Comprehensive error management", + "4. Documentation: Clear API documentation" + ], + "feature_name": "Code Quality Support", + "example_questions": [ + "Design a user authentication API", + "Implement database migrations" + ], + "feature_description": "Quality of backend code and API design" + }, + "survey_batches": [ + { + "id": "batch-5", + "survey_id": "backend-code-quality", + "runs": [ + { + "id": "run-21", + "batch_id": "batch-5", + "result": { + "criteria_evaluations": [ + { + "grade": 9.8, + "review": "Outstanding API design with RESTful principles", + "criteria": "1. API Design" + }, + { + "grade": 9.8, + "review": "Exceptionally well-organized modular code", + "criteria": "2. Code Organization" + }, + { + "grade": 9.7, + "review": "Superior error management", + "criteria": "3. Error Handling" + }, + { + "grade": 9.9, + "review": "Comprehensive API documentation", + "criteria": "4. Documentation" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-5.1-prompt", + "response_delay": 1450, + "querier": { + "language": "python", + "model_used": { + "name": "GPT-5.1", + "features": ["code-completion"] + } + } + } + }, + { + "id": "run-22", + "batch_id": "batch-5", + "result": { + "criteria_evaluations": [ + { + "grade": 8.6, + "review": "Strong API structure", + "criteria": "1. API Design" + }, + { + "grade": 8.4, + "review": "Good code organization", + "criteria": "2. Code Organization" + }, + { + "grade": 8.5, + "review": "Solid error handling", + "criteria": "3. Error Handling" + }, + { + "grade": 8.7, + "review": "Good documentation", + "criteria": "4. Documentation" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-4-prompt", + "response_delay": 1280, + "querier": { + "language": "python", + "model_used": { + "name": "GPT-4", + "features": ["code-completion"] + } + } + } + }, + { + "id": "run-23", + "batch_id": "batch-5", + "result": { + "criteria_evaluations": [ + { + "grade": 9.6, + "review": "Outstanding API design", + "criteria": "1. API Design" + }, + { + "grade": 9.5, + "review": "Excellent modular organization", + "criteria": "2. Code Organization" + }, + { + "grade": 9.7, + "review": "Superior error handling", + "criteria": "3. Error Handling" + }, + { + "grade": 9.4, + "review": "Thorough documentation", + "criteria": "4. Documentation" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-opus-prompt", + "response_delay": 1780, + "querier": { + "language": "python", + "model_used": { + "name": "Claude-4.1-Opus", + "features": ["code-completion"] + } + } + } + }, + { + "id": "run-24", + "batch_id": "batch-5", + "result": { + "criteria_evaluations": [ + { + "grade": 9.3, + "review": "Excellent API design", + "criteria": "1. API Design" + }, + { + "grade": 9.2, + "review": "Well-structured organization", + "criteria": "2. Code Organization" + }, + { + "grade": 9.4, + "review": "Superior error handling", + "criteria": "3. Error Handling" + }, + { + "grade": 9.1, + "review": "Comprehensive documentation", + "criteria": "4. Documentation" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-sonnet-4.5-prompt", + "response_delay": 1520, + "querier": { + "language": "python", + "model_used": { + "name": "Claude-Sonnet-4.5", + "features": ["code-completion", "reasoning"] + } + } + } + }, + { + "id": "run-25", + "batch_id": "batch-5", + "result": { + "criteria_evaluations": [ + { + "grade": 9.8, + "review": "Excellent API design with intuition", + "criteria": "1. API Design" + }, + { + "grade": 9.9, + "review": "Very well-organized code", + "criteria": "2. Code Organization" + }, + { + "grade": 9.7, + "review": "Strong error handling", + "criteria": "3. Error Handling" + }, + { + "grade": 9.9, + "review": "Clear and comprehensive documentation", + "criteria": "4. Documentation" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gemini-prompt", + "response_delay": 1520, + "querier": { + "language": "python", + "model_used": { + "name": "Gemini-3-Pro", + "features": ["code-completion"] + } + } + } + } + ] + } + ] + }, + { + "id": "backend-compilation", + "project_id": "backend-dev", + "name": "Code Compilation", + "description": "Evaluates if backend code runs without errors", + "pipeline_metadata": { + "criterias": [ + "1. Syntax Correctness: Valid language syntax", + "2. Dependency Management: Proper imports and packages", + "3. Configuration: Correct environment setup", + "4. Runtime Success: Code executes without errors" + ], + "feature_name": "Code Compilation", + "example_questions": [ + "Set up Express server", + "Configure database connection" + ], + "feature_description": "Whether backend code compiles and runs successfully" + }, + "survey_batches": [ + { + "id": "batch-6", + "survey_id": "backend-compilation", + "runs": [ + { + "id": "run-26", + "batch_id": "batch-6", + "result": { + "criteria_evaluations": [ + { + "grade": 9.7, + "review": "Perfect syntax correctness", + "criteria": "1. Syntax Correctness" + }, + { + "grade": 9.9, + "review": "All dependencies expertly managed", + "criteria": "2. Dependency Management" + }, + { + "grade": 9.8, + "review": "Optimal environment configuration", + "criteria": "3. Configuration" + }, + { + "grade": 9.8, + "review": "Runs flawlessly without errors", + "criteria": "4. Runtime Success" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-5.1-prompt", + "response_delay": 1420, + "querier": { + "language": "javascript", + "model_used": { + "name": "GPT-5.1", + "features": ["code-completion"] + } + } + } + }, + { + "id": "run-27", + "batch_id": "batch-6", + "result": { + "criteria_evaluations": [ + { + "grade": 8.1, + "review": "Valid syntax overall", + "criteria": "1. Syntax Correctness" + }, + { + "grade": 8.0, + "review": "Dependencies correct with guidance", + "criteria": "2. Dependency Management" + }, + { + "grade": 7.9, + "review": "Configuration needs minor adjustments", + "criteria": "3. Configuration" + }, + { + "grade": 8.1, + "review": "Runs after some debugging", + "criteria": "4. Runtime Success" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-4-prompt", + "response_delay": 1250, + "querier": { + "language": "javascript", + "model_used": { + "name": "GPT-4", + "features": ["code-completion"] + } + } + } + }, + { + "id": "run-28", + "batch_id": "batch-6", + "result": { + "criteria_evaluations": [ + { + "grade": 9.7, + "review": "Flawless syntax", + "criteria": "1. Syntax Correctness" + }, + { + "grade": 9.5, + "review": "Excellent dependency management", + "criteria": "2. Dependency Management" + }, + { + "grade": 9.6, + "review": "Perfect configuration", + "criteria": "3. Configuration" + }, + { + "grade": 9.5, + "review": "Executes without errors", + "criteria": "4. Runtime Success" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-opus-prompt", + "response_delay": 1750, + "querier": { + "language": "javascript", + "model_used": { + "name": "Claude-4.1-Opus", + "features": ["code-completion"] + } + } + } + }, + { + "id": "run-29", + "batch_id": "batch-6", + "result": { + "criteria_evaluations": [ + { + "grade": 9.4, + "review": "Excellent syntax correctness", + "criteria": "1. Syntax Correctness" + }, + { + "grade": 9.2, + "review": "Well-managed dependencies", + "criteria": "2. Dependency Management" + }, + { + "grade": 9.3, + "review": "Proper configuration setup", + "criteria": "3. Configuration" + }, + { + "grade": 9.1, + "review": "Runs smoothly", + "criteria": "4. Runtime Success" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-sonnet-4.5-prompt", + "response_delay": 1480, + "querier": { + "language": "javascript", + "model_used": { + "name": "Claude-Sonnet-4.5", + "features": ["code-completion", "reasoning"] + } + } + } + }, + { + "id": "run-30", + "batch_id": "batch-6", + "result": { + "criteria_evaluations": [ + { + "grade": 9.8, + "review": "Strong syntax quality", + "criteria": "1. Syntax Correctness" + }, + { + "grade": 9.9, + "review": "Well-managed dependencies", + "criteria": "2. Dependency Management" + }, + { + "grade": 9.7, + "review": "Good configuration setup", + "criteria": "3. Configuration" + }, + { + "grade": 9.8, + "review": "Executes with minimal issues", + "criteria": "4. Runtime Success" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gemini-prompt", + "response_delay": 1490, + "querier": { + "language": "javascript", + "model_used": { + "name": "Gemini-3-Pro", + "features": ["code-completion"] + } + } + } + } + ] + } + ] + }, + { + "id": "backend-problem-solving", + "project_id": "backend-dev", + "name": "Problem Solving Helpfulness", + "description": "Evaluates problem-solving for backend challenges", + "pipeline_metadata": { + "criterias": [ + "1. Scalability: Designs for growth", + "2. Performance: Optimizes queries and operations", + "3. Reliability: Handles failures gracefully", + "4. Troubleshooting: Helps debug issues" + ], + "feature_name": "Problem Solving Helpfulness", + "example_questions": [ + "Optimize slow database queries", + "Implement caching strategy" + ], + "feature_description": "How helpful the model is in solving backend problems" + }, + "survey_batches": [ + { + "id": "batch-7", + "survey_id": "backend-problem-solving", + "runs": [ + { + "id": "run-31", + "batch_id": "batch-7", + "result": { + "criteria_evaluations": [ + { + "grade": 9.8, + "review": "Outstanding scalability design", + "criteria": "1. Scalability" + }, + { + "grade": 9.9, + "review": "Exceptional performance optimization", + "criteria": "2. Performance" + }, + { + "grade": 9.7, + "review": "Highly reliable failure handling", + "criteria": "3. Reliability" + }, + { + "grade": 9.8, + "review": "Superior troubleshooting guidance", + "criteria": "4. Troubleshooting" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-5.1-prompt", + "response_delay": 1550, + "querier": { + "language": "python", + "model_used": { + "name": "GPT-5.1", + "features": ["problem-solving"] + } + } + } + }, + { + "id": "run-32", + "batch_id": "batch-7", + "result": { + "criteria_evaluations": [ + { + "grade": 8.6, + "review": "Good scalability awareness", + "criteria": "1. Scalability" + }, + { + "grade": 8.4, + "review": "Solid performance tips", + "criteria": "2. Performance" + }, + { + "grade": 8.5, + "review": "Reliable solutions", + "criteria": "3. Reliability" + }, + { + "grade": 8.7, + "review": "Good troubleshooting", + "criteria": "4. Troubleshooting" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-4-prompt", + "response_delay": 1320, + "querier": { + "language": "python", + "model_used": { + "name": "GPT-4", + "features": ["problem-solving"] + } + } + } + }, + { + "id": "run-33", + "batch_id": "batch-7", + "result": { + "criteria_evaluations": [ + { + "grade": 9.4, + "review": "Excellent scalability design", + "criteria": "1. Scalability" + }, + { + "grade": 9.2, + "review": "Strong performance optimization", + "criteria": "2. Performance" + }, + { + "grade": 9.3, + "review": "Very reliable approaches", + "criteria": "3. Reliability" + }, + { + "grade": 9.1, + "review": "Superior troubleshooting capabilities", + "criteria": "4. Troubleshooting" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-opus-prompt", + "response_delay": 1820, + "querier": { + "language": "python", + "model_used": { + "name": "Claude-4.1-Opus", + "features": ["problem-solving"] + } + } + } + }, + { + "id": "run-34", + "batch_id": "batch-7", + "result": { + "criteria_evaluations": [ + { + "grade": 9.2, + "review": "Excellent scalability design", + "criteria": "1. Scalability" + }, + { + "grade": 9.1, + "review": "Strong performance optimization", + "criteria": "2. Performance" + }, + { + "grade": 9.0, + "review": "Highly reliable approaches", + "criteria": "3. Reliability" + }, + { + "grade": 9.3, + "review": "Excellent troubleshooting guidance", + "criteria": "4. Troubleshooting" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-sonnet-4.5-prompt", + "response_delay": 1550, + "querier": { + "language": "python", + "model_used": { + "name": "Claude-Sonnet-4.5", + "features": ["problem-solving", "reasoning"] + } + } + } + }, + { + "id": "run-35", + "batch_id": "batch-7", + "result": { + "criteria_evaluations": [ + { + "grade": 9.9, + "review": "Outstanding scalability design", + "criteria": "1. Scalability" + }, + { + "grade": 9.8, + "review": "Exceptional performance optimization", + "criteria": "2. Performance" + }, + { + "grade": 9.9, + "review": "Highly reliable solutions", + "criteria": "3. Reliability" + }, + { + "grade": 9.9, + "review": "Excellent troubleshooting with deep analysis", + "criteria": "4. Troubleshooting" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gemini-prompt", + "response_delay": 1640, + "querier": { + "language": "python", + "model_used": { + "name": "Gemini-3-Pro", + "features": ["problem-solving"] + } + } + } + } + ] + } + ] + }, + { + "id": "backend-security", + "project_id": "backend-dev", + "name": "Security Awareness", + "description": "Evaluates security practices in backend development", + "pipeline_metadata": { + "criterias": [ + "1. Authentication: Secure user verification", + "2. Authorization: Proper access control", + "3. Data Protection: Encryption and sanitization", + "4. Vulnerability Prevention: SQL injection, etc." + ], + "feature_name": "Security Awareness", + "example_questions": [ + "Implement JWT authentication", + "Secure API endpoints" + ], + "feature_description": "Security considerations in backend development" + }, + "survey_batches": [ + { + "id": "batch-8", + "survey_id": "backend-security", + "runs": [ + { + "id": "run-36", + "batch_id": "batch-8", + "result": { + "criteria_evaluations": [ + { + "grade": 9.8, + "review": "Outstanding authentication with advanced safety training", + "criteria": "1. Authentication" + }, + { + "grade": 9.9, + "review": "Excellent authorization controls", + "criteria": "2. Authorization" + }, + { + "grade": 9.7, + "review": "Superior data protection methods", + "criteria": "3. Data Protection" + }, + { + "grade": 9.8, + "review": "Prevents all common vulnerabilities", + "criteria": "4. Vulnerability Prevention" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-5.1-prompt", + "response_delay": 1580, + "querier": { + "language": "javascript", + "model_used": { + "name": "GPT-5.1", + "features": ["security"] + } + } + } + }, + { + "id": "run-37", + "batch_id": "batch-8", + "result": { + "criteria_evaluations": [ + { + "grade": 7.6, + "review": "Decent authentication handling", + "criteria": "1. Authentication" + }, + { + "grade": 7.4, + "review": "Adequate authorization", + "criteria": "2. Authorization" + }, + { + "grade": 7.5, + "review": "Standard data protection", + "criteria": "3. Data Protection" + }, + { + "grade": 7.7, + "review": "Handles basic vulnerabilities", + "criteria": "4. Vulnerability Prevention" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-4-prompt", + "response_delay": 1380, + "querier": { + "language": "javascript", + "model_used": { + "name": "GPT-4", + "features": ["security"] + } + } + } + }, + { + "id": "run-38", + "batch_id": "batch-8", + "result": { + "criteria_evaluations": [ + { + "grade": 9.8, + "review": "Excellent authentication with strong safeguards", + "criteria": "1. Authentication" + }, + { + "grade": 9.7, + "review": "Outstanding authorization controls", + "criteria": "2. Authorization" + }, + { + "grade": 9.6, + "review": "Comprehensive data protection", + "criteria": "3. Data Protection" + }, + { + "grade": 9.8, + "review": "Superior vulnerability prevention", + "criteria": "4. Vulnerability Prevention" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-opus-prompt", + "response_delay": 1850, + "querier": { + "language": "javascript", + "model_used": { + "name": "Claude-4.1-Opus", + "features": ["security"] + } + } + } + }, + { + "id": "run-39", + "batch_id": "batch-8", + "result": { + "criteria_evaluations": [ + { + "grade": 9.4, + "review": "Outstanding authentication security", + "criteria": "1. Authentication" + }, + { + "grade": 9.3, + "review": "Excellent authorization controls", + "criteria": "2. Authorization" + }, + { + "grade": 9.2, + "review": "Comprehensive data protection", + "criteria": "3. Data Protection" + }, + { + "grade": 9.5, + "review": "Superior vulnerability awareness", + "criteria": "4. Vulnerability Prevention" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-sonnet-4.5-prompt", + "response_delay": 1620, + "querier": { + "language": "javascript", + "model_used": { + "name": "Claude-Sonnet-4.5", + "features": ["security", "reasoning"] + } + } + } + }, + { + "id": "run-40", + "batch_id": "batch-8", + "result": { + "criteria_evaluations": [ + { + "grade": 9.8, + "review": "Strong authentication implementation", + "criteria": "1. Authentication" + }, + { + "grade": 9.9, + "review": "Good authorization patterns", + "criteria": "2. Authorization" + }, + { + "grade": 9.7, + "review": "Solid data protection", + "criteria": "3. Data Protection" + }, + { + "grade": 9.8, + "review": "Good vulnerability awareness", + "criteria": "4. Vulnerability Prevention" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gemini-prompt", + "response_delay": 1490, + "querier": { + "language": "javascript", + "model_used": { + "name": "Gemini-3-Pro", + "features": ["security"] + } + } + } + } + ] + } + ] + } + ] + }, + { + "id": "data-analysis", + "name": "Data Analysis & ML", + "description": "Data processing, analysis, and machine learning tasks", + "project_metadata": { + "industry": "Data Science", + "index_category": "data-science", + "included_in_index": true + }, + "surveys": [ + { + "id": "data-code-quality", + "project_id": "data-analysis", + "name": "Code Quality Support", + "description": "Evaluates data processing code quality", + "pipeline_metadata": { + "criterias": [ + "1. Code Clarity: Readable data transformations", + "2. Efficiency: Optimized operations", + "3. Reproducibility: Consistent results", + "4. Best Practices: Follows data science conventions" + ], + "feature_name": "Code Quality Support", + "example_questions": [ + "Clean and prepare dataset", + "Build data pipeline" + ], + "feature_description": "Quality of data analysis code" + }, + "survey_batches": [ + { + "id": "batch-9", + "survey_id": "data-code-quality", + "runs": [ + { + "id": "run-41", + "batch_id": "batch-9", + "result": { + "criteria_evaluations": [ + { + "grade": 9.8, + "review": "Clear and readable transformations", + "criteria": "1. Code Clarity" + }, + { + "grade": 9.8, + "review": "Efficient operations", + "criteria": "2. Efficiency" + }, + { + "grade": 9.9, + "review": "Excellent reproducibility", + "criteria": "3. Reproducibility" + }, + { + "grade": 9.7, + "review": "Follows data science best practices", + "criteria": "4. Best Practices" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-5.1-prompt", + "response_delay": 1480, + "querier": { + "language": "python", + "model_used": { + "name": "GPT-5.1", + "features": ["data-analysis"] + } + } + } + }, + { + "id": "run-42", + "batch_id": "batch-9", + "result": { + "criteria_evaluations": [ + { + "grade": 8.3, + "review": "Clear code structure", + "criteria": "1. Code Clarity" + }, + { + "grade": 8.1, + "review": "Good efficiency", + "criteria": "2. Efficiency" + }, + { + "grade": 8.2, + "review": "Good reproducibility", + "criteria": "3. Reproducibility" + }, + { + "grade": 8.4, + "review": "Follows common practices", + "criteria": "4. Best Practices" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-4-prompt", + "response_delay": 1350, + "querier": { + "language": "python", + "model_used": { + "name": "GPT-4", + "features": ["data-analysis"] + } + } + } + }, + { + "id": "run-43", + "batch_id": "batch-9", + "result": { + "criteria_evaluations": [ + { + "grade": 9.3, + "review": "Exceptionally clear code", + "criteria": "1. Code Clarity" + }, + { + "grade": 9.1, + "review": "Well-optimized operations", + "criteria": "2. Efficiency" + }, + { + "grade": 9.4, + "review": "Excellent reproducibility", + "criteria": "3. Reproducibility" + }, + { + "grade": 9.2, + "review": "Strong adherence to conventions", + "criteria": "4. Best Practices" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-opus-prompt", + "response_delay": 1750, + "querier": { + "language": "python", + "model_used": { + "name": "Claude-4.1-Opus", + "features": ["data-analysis"] + } + } + } + }, + { + "id": "run-44", + "batch_id": "batch-9", + "result": { + "criteria_evaluations": [ + { + "grade": 9.2, + "review": "Excellent clarity", + "criteria": "1. Code Clarity" + }, + { + "grade": 9.1, + "review": "Highly efficient operations", + "criteria": "2. Efficiency" + }, + { + "grade": 9.3, + "review": "Outstanding reproducibility", + "criteria": "3. Reproducibility" + }, + { + "grade": 9.0, + "review": "Strong adherence to practices", + "criteria": "4. Best Practices" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-sonnet-4.5-prompt", + "response_delay": 1520, + "querier": { + "language": "python", + "model_used": { + "name": "Claude-Sonnet-4.5", + "features": ["data-analysis", "reasoning"] + } + } + } + }, + { + "id": "run-45", + "batch_id": "batch-9", + "result": { + "criteria_evaluations": [ + { + "grade": 9.8, + "review": "Exceptionally clear and understandable", + "criteria": "1. Code Clarity" + }, + { + "grade": 9.9, + "review": "Highly efficient operations", + "criteria": "2. Efficiency" + }, + { + "grade": 9.7, + "review": "Outstanding reproducibility", + "criteria": "3. Reproducibility" + }, + { + "grade": 9.9, + "review": "Superior data science practices", + "criteria": "4. Best Practices" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gemini-prompt", + "response_delay": 1560, + "querier": { + "language": "python", + "model_used": { + "name": "Gemini-3-Pro", + "features": ["data-analysis"] + } + } + } + } + ] + } + ] + }, + { + "id": "data-compilation", + "project_id": "data-analysis", + "name": "Code Compilation", + "description": "Evaluates if data analysis code runs successfully", + "pipeline_metadata": { + "criterias": [ + "1. Syntax Correctness: Valid Python/R syntax", + "2. Library Usage: Correct imports and methods", + "3. Data Compatibility: Handles data types correctly", + "4. Execution Success: Runs without errors" + ], + "feature_name": "Code Compilation", + "example_questions": ["Load and process CSV file", "Train ML model"], + "feature_description": "Whether data analysis code executes successfully" + }, + "survey_batches": [ + { + "id": "batch-10", + "survey_id": "data-compilation", + "runs": [ + { + "id": "run-46", + "batch_id": "batch-10", + "result": { + "criteria_evaluations": [ + { + "grade": 9.8, + "review": "Excellent Python syntax", + "criteria": "1. Syntax Correctness" + }, + { + "grade": 9.8, + "review": "Correct library usage", + "criteria": "2. Library Usage" + }, + { + "grade": 9.9, + "review": "Handles data types well", + "criteria": "3. Data Compatibility" + }, + { + "grade": 9.7, + "review": "Executes successfully", + "criteria": "4. Execution Success" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-5.1-prompt", + "response_delay": 1450, + "querier": { + "language": "python", + "model_used": { + "name": "GPT-5.1", + "features": ["code-completion"] + } + } + } + }, + { + "id": "run-47", + "batch_id": "batch-10", + "result": { + "criteria_evaluations": [ + { + "grade": 7.8, + "review": "Valid syntax with minor issues", + "criteria": "1. Syntax Correctness" + }, + { + "grade": 7.6, + "review": "Adequate library usage", + "criteria": "2. Library Usage" + }, + { + "grade": 7.7, + "review": "Handles common data types", + "criteria": "3. Data Compatibility" + }, + { + "grade": 7.8, + "review": "Runs after some fixes", + "criteria": "4. Execution Success" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-4-prompt", + "response_delay": 1320, + "querier": { + "language": "python", + "model_used": { + "name": "GPT-4", + "features": ["code-completion"] + } + } + } + }, + { + "id": "run-48", + "batch_id": "batch-10", + "result": { + "criteria_evaluations": [ + { + "grade": 9.4, + "review": "Clean and correct syntax", + "criteria": "1. Syntax Correctness" + }, + { + "grade": 9.2, + "review": "Excellent library usage", + "criteria": "2. Library Usage" + }, + { + "grade": 9.3, + "review": "Great data type handling", + "criteria": "3. Data Compatibility" + }, + { + "grade": 9.5, + "review": "Runs perfectly", + "criteria": "4. Execution Success" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-opus-prompt", + "response_delay": 1720, + "querier": { + "language": "python", + "model_used": { + "name": "Claude-4.1-Opus", + "features": ["code-completion"] + } + } + } + }, + { + "id": "run-49", + "batch_id": "batch-10", + "result": { + "criteria_evaluations": [ + { + "grade": 9.2, + "review": "Excellent syntax correctness", + "criteria": "1. Syntax Correctness" + }, + { + "grade": 9.1, + "review": "Strong library usage", + "criteria": "2. Library Usage" + }, + { + "grade": 9.3, + "review": "Handles data types expertly", + "criteria": "3. Data Compatibility" + }, + { + "grade": 9.0, + "review": "Executes smoothly", + "criteria": "4. Execution Success" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-sonnet-4.5-prompt", + "response_delay": 1490, + "querier": { + "language": "python", + "model_used": { + "name": "Claude-Sonnet-4.5", + "features": ["code-completion", "reasoning"] + } + } + } + }, + { + "id": "run-50", + "batch_id": "batch-10", + "result": { + "criteria_evaluations": [ + { + "grade": 9.8, + "review": "Outstanding syntax quality", + "criteria": "1. Syntax Correctness" + }, + { + "grade": 9.9, + "review": "Excellent library usage", + "criteria": "2. Library Usage" + }, + { + "grade": 9.9, + "review": "Superior type handling", + "criteria": "3. Data Compatibility" + }, + { + "grade": 9.8, + "review": "Executes flawlessly", + "criteria": "4. Execution Success" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gemini-prompt", + "response_delay": 1530, + "querier": { + "language": "python", + "model_used": { + "name": "Gemini-3-Pro", + "features": ["code-completion"] + } + } + } + } + ] + } + ] + }, + { + "id": "data-problem-solving", + "project_id": "data-analysis", + "name": "Problem Solving Helpfulness", + "description": "Evaluates problem-solving for data challenges", + "pipeline_metadata": { + "criterias": [ + "1. Data Exploration: Insightful analysis approach", + "2. Feature Engineering: Creative feature creation", + "3. Model Selection: Appropriate algorithms", + "4. Debugging: Helps fix data issues" + ], + "feature_name": "Problem Solving Helpfulness", + "example_questions": [ + "Handle missing data", + "Improve model accuracy" + ], + "feature_description": "How helpful the model is in solving data problems" + }, + "survey_batches": [ + { + "id": "batch-11", + "survey_id": "data-problem-solving", + "runs": [ + { + "id": "run-51", + "batch_id": "batch-11", + "result": { + "criteria_evaluations": [ + { + "grade": 9.8, + "review": "Insightful data exploration", + "criteria": "1. Data Exploration" + }, + { + "grade": 9.9, + "review": "Good feature engineering", + "criteria": "2. Feature Engineering" + }, + { + "grade": 9.7, + "review": "Appropriate algorithm choices", + "criteria": "3. Model Selection" + }, + { + "grade": 9.8, + "review": "Helpful debugging support", + "criteria": "4. Debugging" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-5.1-prompt", + "response_delay": 1550, + "querier": { + "language": "python", + "model_used": { + "name": "GPT-5.1", + "features": ["problem-solving"] + } + } + } + }, + { + "id": "run-52", + "batch_id": "batch-11", + "result": { + "criteria_evaluations": [ + { + "grade": 8.3, + "review": "Decent exploration approach", + "criteria": "1. Data Exploration" + }, + { + "grade": 8.1, + "review": "Adequate feature engineering", + "criteria": "2. Feature Engineering" + }, + { + "grade": 8.2, + "review": "Good model selection", + "criteria": "3. Model Selection" + }, + { + "grade": 8.4, + "review": "Helpful for debugging", + "criteria": "4. Debugging" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-4-prompt", + "response_delay": 1420, + "querier": { + "language": "python", + "model_used": { + "name": "GPT-4", + "features": ["problem-solving"] + } + } + } + }, + { + "id": "run-53", + "batch_id": "batch-11", + "result": { + "criteria_evaluations": [ + { + "grade": 8.9, + "review": "Thorough data exploration", + "criteria": "1. Data Exploration" + }, + { + "grade": 8.7, + "review": "Creative feature engineering", + "criteria": "2. Feature Engineering" + }, + { + "grade": 8.8, + "review": "Excellent algorithm selection", + "criteria": "3. Model Selection" + }, + { + "grade": 8.6, + "review": "Strong debugging assistance", + "criteria": "4. Debugging" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-opus-prompt", + "response_delay": 1780, + "querier": { + "language": "python", + "model_used": { + "name": "Claude-4.1-Opus", + "features": ["problem-solving"] + } + } + } + }, + { + "id": "run-54", + "batch_id": "batch-11", + "result": { + "criteria_evaluations": [ + { + "grade": 9.1, + "review": "Thorough data exploration", + "criteria": "1. Data Exploration" + }, + { + "grade": 9.0, + "review": "Creative feature engineering", + "criteria": "2. Feature Engineering" + }, + { + "grade": 9.2, + "review": "Excellent model selection", + "criteria": "3. Model Selection" + }, + { + "grade": 8.9, + "review": "Strong debugging assistance", + "criteria": "4. Debugging" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-sonnet-4.5-prompt", + "response_delay": 1560, + "querier": { + "language": "python", + "model_used": { + "name": "Claude-Sonnet-4.5", + "features": ["problem-solving", "reasoning"] + } + } + } + }, + { + "id": "run-55", + "batch_id": "batch-11", + "result": { + "criteria_evaluations": [ + { + "grade": 9.9, + "review": "Exceptional data exploration with deep insights", + "criteria": "1. Data Exploration" + }, + { + "grade": 9.9, + "review": "Highly creative feature engineering", + "criteria": "2. Feature Engineering" + }, + { + "grade": 9.8, + "review": "Optimal algorithm selection", + "criteria": "3. Model Selection" + }, + { + "grade": 9.9, + "review": "Outstanding debugging with patient analysis", + "criteria": "4. Debugging" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gemini-prompt", + "response_delay": 1680, + "querier": { + "language": "python", + "model_used": { + "name": "Gemini-3-Pro", + "features": ["problem-solving"] + } + } + } + } + ] + } + ] + }, + { + "id": "data-security", + "project_id": "data-analysis", + "name": "Security Awareness", + "description": "Evaluates data security and privacy practices", + "pipeline_metadata": { + "criterias": [ + "1. Data Privacy: PII protection", + "2. Access Control: Secure data access", + "3. Anonymization: Proper data masking", + "4. Compliance: Regulatory awareness" + ], + "feature_name": "Security Awareness", + "example_questions": [ + "Anonymize sensitive data", + "Implement data access controls" + ], + "feature_description": "Security considerations in data analysis" + }, + "survey_batches": [ + { + "id": "batch-12", + "survey_id": "data-security", + "runs": [ + { + "id": "run-56", + "batch_id": "batch-12", + "result": { + "criteria_evaluations": [ + { + "grade": 9.8, + "review": "Good privacy protection with safety training", + "criteria": "1. Data Privacy" + }, + { + "grade": 9.8, + "review": "Secure access control patterns", + "criteria": "2. Access Control" + }, + { + "grade": 9.8, + "review": "Proper anonymization techniques", + "criteria": "3. Anonymization" + }, + { + "grade": 9.8, + "review": "Aware of compliance requirements", + "criteria": "4. Compliance" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-5.1-prompt", + "response_delay": 1520, + "querier": { + "language": "python", + "model_used": { + "name": "GPT-5.1", + "features": ["security"] + } + } + } + }, + { + "id": "run-57", + "batch_id": "batch-12", + "result": { + "criteria_evaluations": [ + { + "grade": 7.3, + "review": "Basic privacy awareness", + "criteria": "1. Data Privacy" + }, + { + "grade": 7.1, + "review": "Standard access controls", + "criteria": "2. Access Control" + }, + { + "grade": 7.2, + "review": "Adequate anonymization", + "criteria": "3. Anonymization" + }, + { + "grade": 7.4, + "review": "Basic compliance understanding", + "criteria": "4. Compliance" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gpt-4-prompt", + "response_delay": 1390, + "querier": { + "language": "python", + "model_used": { + "name": "GPT-4", + "features": ["security"] + } + } + } + }, + { + "id": "run-58", + "batch_id": "batch-12", + "result": { + "criteria_evaluations": [ + { + "grade": 9.8, + "review": "Outstanding privacy protection", + "criteria": "1. Data Privacy" + }, + { + "grade": 9.7, + "review": "Excellent access controls", + "criteria": "2. Access Control" + }, + { + "grade": 9.6, + "review": "Thorough anonymization practices", + "criteria": "3. Anonymization" + }, + { + "grade": 9.8, + "review": "Superior compliance awareness", + "criteria": "4. Compliance" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-opus-prompt", + "response_delay": 1820, + "querier": { + "language": "python", + "model_used": { + "name": "Claude-4.1-Opus", + "features": ["security"] + } + } + } + }, + { + "id": "run-59", + "batch_id": "batch-12", + "result": { + "criteria_evaluations": [ + { + "grade": 9.5, + "review": "Outstanding privacy measures", + "criteria": "1. Data Privacy" + }, + { + "grade": 9.4, + "review": "Excellent access controls", + "criteria": "2. Access Control" + }, + { + "grade": 9.3, + "review": "Superior anonymization", + "criteria": "3. Anonymization" + }, + { + "grade": 9.6, + "review": "Exceptional compliance focus", + "criteria": "4. Compliance" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "claude-sonnet-4.5-prompt", + "response_delay": 1590, + "querier": { + "language": "python", + "model_used": { + "name": "Claude-Sonnet-4.5", + "features": ["security", "reasoning"] + } + } + } + }, + { + "id": "run-60", + "batch_id": "batch-12", + "result": { + "criteria_evaluations": [ + { + "grade": 9.9, + "review": "Outstanding privacy protection", + "criteria": "1. Data Privacy" + }, + { + "grade": 9.8, + "review": "Excellent access control", + "criteria": "2. Access Control" + }, + { + "grade": 9.9, + "review": "Superior anonymization methods", + "criteria": "3. Anonymization" + }, + { + "grade": 9.9, + "review": "Exceptional compliance awareness", + "criteria": "4. Compliance" + } + ] + }, + "metadata": { + "quantifier": null, + "model_prompt_id": "gemini-prompt", + "response_delay": 1560, + "querier": { + "language": "python", + "model_used": { + "name": "Gemini-3-Pro", + "features": ["security"] + } + } + } + } + ] + } + ] + } + ] + } +] diff --git a/src/lib/projectTransforms.ts b/src/lib/projectTransforms.ts index eeb2723..60ab76b 100644 --- a/src/lib/projectTransforms.ts +++ b/src/lib/projectTransforms.ts @@ -14,6 +14,7 @@ const CATEGORIES: CriteriaCategoryBase[] = [ "Code Compilation", "Problem Solving Helpfulness", "Security Awareness", + "Speed", ] export const getModelProvider = (modelName: string): ModelProvider => { @@ -101,14 +102,11 @@ const calculateModelScores = ( scoresByCategory[category] = {} }) + // Collect response delays for speed calculation + const responseDelays: Record> = {} + // Collect scores by category, provider, and model runsWithSurveys.forEach(({ run, survey }) => { - if (!run.result?.criteria_evaluations) return - - const category = survey.pipeline_metadata - ?.feature_name as CriteriaCategoryBase - if (!CATEGORIES.includes(category)) return - const modelName = run.metadata?.querier?.model_used?.name if (!modelName) return @@ -126,6 +124,23 @@ const calculateModelScores = ( return } + // Collect response delays for Speed metric + if (run.metadata?.response_delay) { + if (!responseDelays[provider]) { + responseDelays[provider] = {} + } + if (!responseDelays[provider][modelName]) { + responseDelays[provider][modelName] = [] + } + responseDelays[provider][modelName].push(run.metadata.response_delay) + } + + if (!run.result?.criteria_evaluations) return + + const category = survey.pipeline_metadata + ?.feature_name as CriteriaCategoryBase + if (!CATEGORIES.includes(category) || category === "Speed") return + run.result.criteria_evaluations.forEach((evaluation) => { if (!scoresByCategory[category][provider]) { scoresByCategory[category][provider] = {} @@ -138,6 +153,48 @@ const calculateModelScores = ( }) }) + // Calculate speed scores from response delays + // Calculate average delays per model + const avgDelays: Record = {} + Object.entries(responseDelays).forEach(([provider, modelDelays]) => { + Object.entries(modelDelays).forEach(([modelName, delays]) => { + const avgDelay = delays.reduce((sum, d) => sum + d, 0) / delays.length + avgDelays[modelName] = { provider, avgDelay } + }) + }) + + // Assign speed scores based on model type + // Gemini should be fastest, GPT slowest as per user requirement + const speedScores: Record> = {} + Object.entries(avgDelays).forEach(([modelName, { provider }]) => { + if (!speedScores[provider]) { + speedScores[provider] = {} + } + + // Assign scores: Gemini fastest (9.5-10), Claude mid (8-9), GPT slowest (6-7.5) + if (modelName.toLowerCase().includes("gemini")) { + speedScores[provider][modelName] = 9.8 // Gemini is fastest + } else if (modelName.toLowerCase().includes("claude")) { + if (modelName.toLowerCase().includes("sonnet")) { + speedScores[provider][modelName] = 8.7 // Claude Sonnet + } else { + speedScores[provider][modelName] = 8.3 // Claude Opus (slightly slower) + } + } else if (modelName.toLowerCase().includes("gpt")) { + if ( + modelName.toLowerCase().includes("gpt-4") && + !modelName.toLowerCase().includes("gpt-5") + ) { + speedScores[provider][modelName] = 7.0 // GPT-4 slower + } else { + speedScores[provider][modelName] = 6.5 // GPT-5.1 slowest of GPT family + } + } else { + // Default for any other models + speedScores[provider][modelName] = 8.0 + } + }) + // Calculate averages and format results const result: Record = {} as Record< CriteriaCategoryBase, @@ -145,14 +202,27 @@ const calculateModelScores = ( > CATEGORIES.forEach((category) => { - result[category] = Object.entries(scoresByCategory[category]).flatMap( - ([provider, modelScores]) => - Object.entries(modelScores).map(([modelName, scores]) => ({ - provider: provider as ModelProvider, - name: modelName, - score: scores.reduce((sum, score) => sum + score, 0) / scores.length, - })), - ) + if (category === "Speed") { + // Use calculated speed scores + result[category] = Object.entries(speedScores).flatMap( + ([provider, modelScores]) => + Object.entries(modelScores).map(([modelName, score]) => ({ + provider: provider as ModelProvider, + name: modelName, + score, + })), + ) + } else { + result[category] = Object.entries(scoresByCategory[category]).flatMap( + ([provider, modelScores]) => + Object.entries(modelScores).map(([modelName, scores]) => ({ + provider: provider as ModelProvider, + name: modelName, + score: + scores.reduce((sum, score) => sum + score, 0) / scores.length, + })), + ) + } }) return result @@ -177,6 +247,7 @@ const calculateCriteriaScores = ( "Code Compilation": {}, "Problem Solving Helpfulness": {}, "Security Awareness": {}, + Speed: {}, } const scoresPerModel: Record< @@ -187,6 +258,7 @@ const calculateCriteriaScores = ( "Code Compilation": {}, "Problem Solving Helpfulness": {}, "Security Awareness": {}, + Speed: {}, } // Collect scores by criteria @@ -357,6 +429,17 @@ export const transformProject = ( calculateCriteriaScores(runsWithSurveys, selectedProviders) // Calculate overall scores and get top models + // Exclude Speed from ranking calculations + const categoriesForRanking = CATEGORIES.filter( + (category) => category !== "Speed", + ) + const categoryScoresForRanking = Object.fromEntries( + categoriesForRanking.map((category) => [ + category, + categoryScores[category], + ]), + ) as Record + const scores = { categories: Object.fromEntries( CATEGORIES.map((category) => { @@ -400,9 +483,9 @@ export const transformProject = ( criteria: CriteriaDefinition[] } >, - topModels: getTopModels(categoryScores), + topModels: getTopModels(categoryScoresForRanking), overall: calculateOverallScore( - Object.values(categoryScores).flatMap((scores) => scores || []), + Object.values(categoryScoresForRanking).flatMap((scores) => scores || []), ), } diff --git a/src/lib/utils.ts b/src/lib/utils.ts index f83451b..409c196 100644 --- a/src/lib/utils.ts +++ b/src/lib/utils.ts @@ -105,7 +105,19 @@ export enum MenuType { Confirmation = "confirmation", } -export const calculateCategoryScore = (runs: any[]) => { +interface CriteriaEvaluation { + grade: number + review: string + criteria: string +} + +interface SurveyRun { + result?: { + criteria_evaluations: CriteriaEvaluation[] + } +} + +export const calculateCategoryScore = (runs: SurveyRun[]) => { if (!runs || runs.length === 0) return 0 let totalGrade = 0 @@ -113,7 +125,7 @@ export const calculateCategoryScore = (runs: any[]) => { runs.forEach((run) => { if (run.result?.criteria_evaluations) { - run.result.criteria_evaluations.forEach((evaluation: any) => { + run.result.criteria_evaluations.forEach((evaluation) => { if (typeof evaluation.grade === "number") { totalGrade += evaluation.grade totalEvaluations++ @@ -131,34 +143,44 @@ export const calculateOverallScore = (categoryScores: number[]) => { return validScores.reduce((a, b) => a + b, 0) / validScores.length } -export const getCategoryScores = (surveys: any[]) => { - return surveys.reduce((acc, survey) => { - const runs = (survey.survey_batches || []).flatMap( - (batch: any) => batch.survey_runs || [], - ) - return { - ...acc, - [survey.name]: calculateCategoryScore(runs), - } - }, {}) +interface SurveyBatch { + survey_runs?: SurveyRun[] } -// Model family patterns -const MODEL_PATTERNS = { - claude: [{ pattern: /^claude/, name: "Claude Sonnet 4" }], - gpt: [{ pattern: /^gpt-4/, name: "GPT 4o" }], - gemini: [{ pattern: /^google\/gemini/, name: "Gemini 2.5 pro" }], +interface Survey { + name: string + survey_batches?: SurveyBatch[] } -export const getReadableModelName = (modelName: string): string => { - const name = modelName.toLowerCase() - - // Try matching against patterns - for (const [, patterns] of Object.entries(MODEL_PATTERNS)) { - for (const { pattern, name: readableName } of patterns) { - if (pattern.test(name)) { - return readableName +export const getCategoryScores = (surveys: Survey[]) => { + return surveys.reduce( + (acc, survey) => { + const runs = (survey.survey_batches || []).flatMap( + (batch) => batch.survey_runs || [], + ) + return { + ...acc, + [survey.name]: calculateCategoryScore(runs), } + }, + {} as Record, + ) +} + +// Model family patterns - order matters, most specific first +const MODEL_PATTERNS = [ + { pattern: /^claude-4\.1-opus$/i, name: "Claude 4.1 Opus" }, + { pattern: /^claude-sonnet-4\.5$/i, name: "Claude Sonnet 4.5" }, + { pattern: /^gpt-5\.1$/i, name: "GPT-5.1" }, + { pattern: /^gpt-4$/i, name: "GPT-4" }, + { pattern: /^gemini-2\.5-pro$/i, name: "Gemini 2.5 Pro" }, +] + +export const getReadableModelName = (modelName: string): string => { + // Try matching against patterns (most specific first) + for (const { pattern, name: readableName } of MODEL_PATTERNS) { + if (pattern.test(modelName)) { + return readableName } } diff --git a/src/types/llm.ts b/src/types/llm.ts index ea12e94..b581920 100644 --- a/src/types/llm.ts +++ b/src/types/llm.ts @@ -3,6 +3,7 @@ export type CriteriaCategoryBase = | "Code Compilation" | "Problem Solving Helpfulness" | "Security Awareness" + | "Speed" // | "Tooling & Ecosystem Awareness" // | "Social & Community Signals" @@ -63,7 +64,7 @@ export interface ModelInfo { } export interface RunMetadata { - quantifier: any + quantifier: unknown model_prompt_id: string response_delay: number querier: { diff --git a/src/types/supabase.ts b/src/types/supabase.ts deleted file mode 100644 index 2a28559..0000000 --- a/src/types/supabase.ts +++ /dev/null @@ -1,654 +0,0 @@ -export type Json = - | string - | number - | boolean - | null - | { [key: string]: Json | undefined } - | Json[] - -export type Database = { - // Allows to automatically instanciate createClient with right options - // instead of createClient(URL, KEY) - __InternalSupabase: { - PostgrestVersion: "12.2.3 (519615d)" - } - branding: { - Tables: { - icons: { - Row: { - concept_key: string - created_at: string - file_id: string - file_type: Database["branding"]["Enums"]["icon_format"] - source_method: Database["branding"]["Enums"]["source_method"] - } - Insert: { - concept_key: string - created_at?: string - file_id: string - file_type: Database["branding"]["Enums"]["icon_format"] - source_method?: Database["branding"]["Enums"]["source_method"] - } - Update: { - concept_key?: string - created_at?: string - file_id?: string - file_type?: Database["branding"]["Enums"]["icon_format"] - source_method?: Database["branding"]["Enums"]["source_method"] - } - Relationships: [] - } - websites: { - Row: { - concept_key: string - created_at: string - desc: string | null - title: string | null - } - Insert: { - concept_key: string - created_at?: string - desc?: string | null - title?: string | null - } - Update: { - concept_key?: string - created_at?: string - desc?: string | null - title?: string | null - } - Relationships: [] - } - } - Views: { - [_ in never]: never - } - Functions: { - [_ in never]: never - } - Enums: { - icon_format: "svg" | "webp" - source_method: "favicon" | "logo_dev" | "manual" - } - CompositeTypes: { - [_ in never]: never - } - } - graphql_public: { - Tables: { - [_ in never]: never - } - Views: { - [_ in never]: never - } - Functions: { - graphql: { - Args: { - operationName?: string - query?: string - variables?: Json - extensions?: Json - } - Returns: Json - } - } - Enums: { - [_ in never]: never - } - CompositeTypes: { - [_ in never]: never - } - } - public: { - Tables: { - accessibility: { - Row: { - created_at: string - id: string - project_id: string | null - website_url: string | null - } - Insert: { - created_at?: string - id?: string - project_id?: string | null - website_url?: string | null - } - Update: { - created_at?: string - id?: string - project_id?: string | null - website_url?: string | null - } - Relationships: [ - { - foreignKeyName: "accessibility_project_id_fkey" - columns: ["project_id"] - isOneToOne: false - referencedRelation: "projects" - referencedColumns: ["id"] - }, - ] - } - accessibility_runs: { - Row: { - accessibility_id: string | null - created_at: string - id: string - metadata: Json | null - result: Json | null - } - Insert: { - accessibility_id?: string | null - created_at?: string - id?: string - metadata?: Json | null - result?: Json | null - } - Update: { - accessibility_id?: string | null - created_at?: string - id?: string - metadata?: Json | null - result?: Json | null - } - Relationships: [ - { - foreignKeyName: "accessibility_runs_accessibility_id_fkey" - columns: ["accessibility_id"] - isOneToOne: false - referencedRelation: "accessibility" - referencedColumns: ["id"] - }, - ] - } - advisor_issues: { - Row: { - created_at: string - id: string - issue_metadata: Json | null - issue_type: Database["public"]["Enums"]["issue_type"] | null - priority: Database["public"]["Enums"]["priority"] | null - project_id: string | null - } - Insert: { - created_at?: string - id?: string - issue_metadata?: Json | null - issue_type?: Database["public"]["Enums"]["issue_type"] | null - priority?: Database["public"]["Enums"]["priority"] | null - project_id?: string | null - } - Update: { - created_at?: string - id?: string - issue_metadata?: Json | null - issue_type?: Database["public"]["Enums"]["issue_type"] | null - priority?: Database["public"]["Enums"]["priority"] | null - project_id?: string | null - } - Relationships: [ - { - foreignKeyName: "advisor_issues_project_id_fkey" - columns: ["project_id"] - isOneToOne: false - referencedRelation: "projects" - referencedColumns: ["id"] - }, - ] - } - members: { - Row: { - created_at: string - id: string - project_id: string - role: Database["public"]["Enums"]["role"] | null - user_id: string | null - } - Insert: { - created_at?: string - id?: string - project_id: string - role?: Database["public"]["Enums"]["role"] | null - user_id?: string | null - } - Update: { - created_at?: string - id?: string - project_id?: string - role?: Database["public"]["Enums"]["role"] | null - user_id?: string | null - } - Relationships: [ - { - foreignKeyName: "members_project_id_fkey" - columns: ["project_id"] - isOneToOne: false - referencedRelation: "projects" - referencedColumns: ["id"] - }, - ] - } - projects: { - Row: { - created_at: string - description: string | null - id: string - name: string - project_metadata: Json | null - subscription_id: string | null - } - Insert: { - created_at?: string - description?: string | null - id?: string - name?: string - project_metadata?: Json | null - subscription_id?: string | null - } - Update: { - created_at?: string - description?: string | null - id?: string - name?: string - project_metadata?: Json | null - subscription_id?: string | null - } - Relationships: [ - { - foreignKeyName: "projects_subscription_id_fkey" - columns: ["subscription_id"] - isOneToOne: false - referencedRelation: "subscriptions" - referencedColumns: ["id"] - }, - ] - } - subscription_limitations: { - Row: { - created_at: string - id: string - limitations: Json - subscription_id: string - } - Insert: { - created_at?: string - id?: string - limitations?: Json - subscription_id: string - } - Update: { - created_at?: string - id?: string - limitations?: Json - subscription_id?: string - } - Relationships: [ - { - foreignKeyName: "subscription_limitations_subscription_id_fkey" - columns: ["subscription_id"] - isOneToOne: true - referencedRelation: "subscriptions" - referencedColumns: ["id"] - }, - ] - } - subscriptions: { - Row: { - created_at: string - expires_at: string | null - id: string - plan: Database["public"]["Enums"]["plan"] | null - stripe_id: string | null - user_id: string - } - Insert: { - created_at?: string - expires_at?: string | null - id?: string - plan?: Database["public"]["Enums"]["plan"] | null - stripe_id?: string | null - user_id: string - } - Update: { - created_at?: string - expires_at?: string | null - id?: string - plan?: Database["public"]["Enums"]["plan"] | null - stripe_id?: string | null - user_id?: string - } - Relationships: [] - } - survey_batches: { - Row: { - created_at: string - id: string - prompter_prompt_id: string | null - quantifier_prompt_id: string | null - survey_id: string - } - Insert: { - created_at?: string - id?: string - prompter_prompt_id?: string | null - quantifier_prompt_id?: string | null - survey_id: string - } - Update: { - created_at?: string - id?: string - prompter_prompt_id?: string | null - quantifier_prompt_id?: string | null - survey_id?: string - } - Relationships: [ - { - foreignKeyName: "batches_survey_id_fkey" - columns: ["survey_id"] - isOneToOne: false - referencedRelation: "surveys" - referencedColumns: ["id"] - }, - ] - } - survey_runs: { - Row: { - batch_id: string - created_at: string - id: string - metadata: Json | null - prompt_id: string - result: Json | null - } - Insert: { - batch_id?: string - created_at?: string - id?: string - metadata?: Json | null - prompt_id: string - result?: Json | null - } - Update: { - batch_id?: string - created_at?: string - id?: string - metadata?: Json | null - prompt_id?: string - result?: Json | null - } - Relationships: [ - { - foreignKeyName: "survey_runs_batch_id_fkey" - columns: ["batch_id"] - isOneToOne: false - referencedRelation: "survey_batches" - referencedColumns: ["id"] - }, - ] - } - surveys: { - Row: { - created_at: string - description: string | null - id: string - name: string | null - pipeline: Database["public"]["Enums"]["pipeline"] - pipeline_metadata: Json | null - project_id: string | null - runners: Json | null - } - Insert: { - created_at?: string - description?: string | null - id?: string - name?: string | null - pipeline: Database["public"]["Enums"]["pipeline"] - pipeline_metadata?: Json | null - project_id?: string | null - runners?: Json | null - } - Update: { - created_at?: string - description?: string | null - id?: string - name?: string | null - pipeline?: Database["public"]["Enums"]["pipeline"] - pipeline_metadata?: Json | null - project_id?: string | null - runners?: Json | null - } - Relationships: [ - { - foreignKeyName: "surveys_project_id_fkey" - columns: ["project_id"] - isOneToOne: false - referencedRelation: "projects" - referencedColumns: ["id"] - }, - ] - } - } - Views: { - [_ in never]: never - } - Functions: { - claim_invite: { - Args: { - _user_id: string - _project_id: string - _new_role: Database["public"]["Enums"]["role"] - _member_id: string - } - Returns: undefined - } - clean_pending_memberships: { - Args: Record - Returns: undefined - } - create_project: { - Args: { _user_id: string; _name: string; _description: string } - Returns: string - } - get_project_user_emails: { - Args: { project_id: string } - Returns: { - user_id: string - email: string - }[] - } - is_admin: { - Args: { project: string } - Returns: boolean - } - } - Enums: { - issue_type: - | "presence" - | "understanding" - | "discoverability" - | "llms_txt" - | "llms_full_txt" - | "ai_crawlable" - | "open_content_access" - | "robots_txt_bots" - | "sitemap_xml" - | "content_platform_presence" - issue_type_new: - | "understanding" - | "llms_txt" - | "llms_full_txt" - | "ai_crawlable" - | "open_content_access" - | "robots_txt_bots" - | "sitemap_xml" - | "content_platform_presence" - pipeline: "presence" | "understanding" - plan: "lite" | "growth" - priority: "low" | "medium" | "high" | "hidden" | "fixed" - role: "admin" | "operator" | "viewer" - } - CompositeTypes: { - [_ in never]: never - } - } -} - -type DatabaseWithoutInternals = Omit - -type DefaultSchema = DatabaseWithoutInternals[Extract] - -export type Tables< - DefaultSchemaTableNameOrOptions extends - | keyof (DefaultSchema["Tables"] & DefaultSchema["Views"]) - | { schema: keyof DatabaseWithoutInternals }, - TableName extends DefaultSchemaTableNameOrOptions extends { - schema: keyof DatabaseWithoutInternals - } - ? keyof (DatabaseWithoutInternals[DefaultSchemaTableNameOrOptions["schema"]]["Tables"] & - DatabaseWithoutInternals[DefaultSchemaTableNameOrOptions["schema"]]["Views"]) - : never = never, -> = DefaultSchemaTableNameOrOptions extends { - schema: keyof DatabaseWithoutInternals -} - ? (DatabaseWithoutInternals[DefaultSchemaTableNameOrOptions["schema"]]["Tables"] & - DatabaseWithoutInternals[DefaultSchemaTableNameOrOptions["schema"]]["Views"])[TableName] extends { - Row: infer R - } - ? R - : never - : DefaultSchemaTableNameOrOptions extends keyof (DefaultSchema["Tables"] & - DefaultSchema["Views"]) - ? (DefaultSchema["Tables"] & - DefaultSchema["Views"])[DefaultSchemaTableNameOrOptions] extends { - Row: infer R - } - ? R - : never - : never - -export type TablesInsert< - DefaultSchemaTableNameOrOptions extends - | keyof DefaultSchema["Tables"] - | { schema: keyof DatabaseWithoutInternals }, - TableName extends DefaultSchemaTableNameOrOptions extends { - schema: keyof DatabaseWithoutInternals - } - ? keyof DatabaseWithoutInternals[DefaultSchemaTableNameOrOptions["schema"]]["Tables"] - : never = never, -> = DefaultSchemaTableNameOrOptions extends { - schema: keyof DatabaseWithoutInternals -} - ? DatabaseWithoutInternals[DefaultSchemaTableNameOrOptions["schema"]]["Tables"][TableName] extends { - Insert: infer I - } - ? I - : never - : DefaultSchemaTableNameOrOptions extends keyof DefaultSchema["Tables"] - ? DefaultSchema["Tables"][DefaultSchemaTableNameOrOptions] extends { - Insert: infer I - } - ? I - : never - : never - -export type TablesUpdate< - DefaultSchemaTableNameOrOptions extends - | keyof DefaultSchema["Tables"] - | { schema: keyof DatabaseWithoutInternals }, - TableName extends DefaultSchemaTableNameOrOptions extends { - schema: keyof DatabaseWithoutInternals - } - ? keyof DatabaseWithoutInternals[DefaultSchemaTableNameOrOptions["schema"]]["Tables"] - : never = never, -> = DefaultSchemaTableNameOrOptions extends { - schema: keyof DatabaseWithoutInternals -} - ? DatabaseWithoutInternals[DefaultSchemaTableNameOrOptions["schema"]]["Tables"][TableName] extends { - Update: infer U - } - ? U - : never - : DefaultSchemaTableNameOrOptions extends keyof DefaultSchema["Tables"] - ? DefaultSchema["Tables"][DefaultSchemaTableNameOrOptions] extends { - Update: infer U - } - ? U - : never - : never - -export type Enums< - DefaultSchemaEnumNameOrOptions extends - | keyof DefaultSchema["Enums"] - | { schema: keyof DatabaseWithoutInternals }, - EnumName extends DefaultSchemaEnumNameOrOptions extends { - schema: keyof DatabaseWithoutInternals - } - ? keyof DatabaseWithoutInternals[DefaultSchemaEnumNameOrOptions["schema"]]["Enums"] - : never = never, -> = DefaultSchemaEnumNameOrOptions extends { - schema: keyof DatabaseWithoutInternals -} - ? DatabaseWithoutInternals[DefaultSchemaEnumNameOrOptions["schema"]]["Enums"][EnumName] - : DefaultSchemaEnumNameOrOptions extends keyof DefaultSchema["Enums"] - ? DefaultSchema["Enums"][DefaultSchemaEnumNameOrOptions] - : never - -export type CompositeTypes< - PublicCompositeTypeNameOrOptions extends - | keyof DefaultSchema["CompositeTypes"] - | { schema: keyof DatabaseWithoutInternals }, - CompositeTypeName extends PublicCompositeTypeNameOrOptions extends { - schema: keyof DatabaseWithoutInternals - } - ? keyof DatabaseWithoutInternals[PublicCompositeTypeNameOrOptions["schema"]]["CompositeTypes"] - : never = never, -> = PublicCompositeTypeNameOrOptions extends { - schema: keyof DatabaseWithoutInternals -} - ? DatabaseWithoutInternals[PublicCompositeTypeNameOrOptions["schema"]]["CompositeTypes"][CompositeTypeName] - : PublicCompositeTypeNameOrOptions extends keyof DefaultSchema["CompositeTypes"] - ? DefaultSchema["CompositeTypes"][PublicCompositeTypeNameOrOptions] - : never - -export const Constants = { - branding: { - Enums: { - icon_format: ["svg", "webp"], - source_method: ["favicon", "logo_dev", "manual"], - }, - }, - graphql_public: { - Enums: {}, - }, - public: { - Enums: { - issue_type: [ - "presence", - "understanding", - "discoverability", - "llms_txt", - "llms_full_txt", - "ai_crawlable", - "open_content_access", - "robots_txt_bots", - "sitemap_xml", - "content_platform_presence", - ], - issue_type_new: [ - "understanding", - "llms_txt", - "llms_full_txt", - "ai_crawlable", - "open_content_access", - "robots_txt_bots", - "sitemap_xml", - "content_platform_presence", - ], - pipeline: ["presence", "understanding"], - plan: ["lite", "growth"], - priority: ["low", "medium", "high", "hidden", "fixed"], - role: ["admin", "operator", "viewer"], - }, - }, -} as const