| import { randomUUID } from "node:crypto"; |
| import { BigQuery } from "@google-cloud/bigquery"; |
| import type { SupplyChainTool, ToolCategory } from "@/lib/tool-types"; |
| import { categories } from "@/lib/tool-types"; |
|
|
| type NewTool = Omit< |
| SupplyChainTool, |
| "id" | "slug" | "createdAt" | "averageRating" | "ratingCount" |
| >; |
|
|
| type DemoState = { |
| tools: SupplyChainTool[]; |
| ratings: Map<string, number>; |
| ratingSums: Map<string, number>; |
| }; |
|
|
| declare global { |
| var __chainkitDemoState: DemoState | undefined; |
| } |
|
|
| const demoTools: SupplyChainTool[] = [ |
| { |
| id: "intelligent-supply-chain", |
| slug: "intelligent-supply-chain-management", |
| name: "Intelligent Supply Chain Management", |
| summary: |
| "Azure ML accelerator using deep-learning forecasts and distributed computing to simulate inventory optimization.", |
| category: "Planning", |
| repoUrl: "https://github.com/MSUSAzureAccelerators/Intelligent-Supply-Chain-Management", |
| websiteUrl: "", |
| submittedBy: "Chainkit demo", |
| createdAt: "2026-11-06T10:00:00.000Z", |
| averageRating: 0, |
| ratingCount: 0, |
| }, |
| { |
| id: "scimai-gym", |
| slug: "scimai-gym", |
| name: "SCIMAI Gym", |
| summary: |
| "Python environment for supply-chain inventory management experiments with deep reinforcement learning.", |
| category: "Planning", |
| repoUrl: "https://github.com/frenkowski/SCIMAI-Gym", |
| websiteUrl: "", |
| submittedBy: "Chainkit demo", |
| createdAt: "2026-11-06T10:00:00.000Z", |
| averageRating: 0, |
| ratingCount: 0, |
| }, |
| { |
| id: "product-demand-forecasting", |
| slug: "product-demand-forecasting-ml", |
| name: "Product Demand Forecasting with ML", |
| summary: |
| "Machine-learning project exploring product demand forecasting for supply-chain planning.", |
| category: "Planning", |
| repoUrl: "https://github.com/trydoff/Product-Demand-Forecasting-Using-ML", |
| websiteUrl: "", |
| submittedBy: "Chainkit demo", |
| createdAt: "2026-11-06T10:00:00.000Z", |
| averageRating: 0, |
| ratingCount: 0, |
| }, |
| { |
| id: "timefold-solver", |
| slug: "timefold-solver", |
| name: "Timefold Solver", |
| summary: |
| "Open-source AI solver for vehicle routing, task assignment, and other operational planning problems.", |
| category: "Logistics", |
| repoUrl: "https://github.com/TimefoldAI/timefold-solver", |
| websiteUrl: "", |
| submittedBy: "Chainkit demo", |
| createdAt: "2026-11-06T10:00:00.000Z", |
| averageRating: 0, |
| ratingCount: 0, |
| }, |
| { |
| id: "late-delivery-prediction", |
| slug: "supply-chain-late-delivery-prediction", |
| name: "Late Delivery Prediction", |
| summary: |
| "Industrial ML pipeline for shipment-delay prediction with model comparisons and a Streamlit batch app.", |
| category: "Visibility", |
| repoUrl: "https://github.com/workkrishnpatel/supply-chain-late-delivery-prediction", |
| websiteUrl: "", |
| submittedBy: "Chainkit demo", |
| createdAt: "2026-11-06T10:00:00.000Z", |
| averageRating: 0, |
| ratingCount: 0, |
| }, |
| { |
| id: "ai-warehouse-slotting", |
| slug: "ai-warehouse-slotting", |
| name: "AI Warehouse Slotting", |
| summary: |
| "Warehouse-management prototype integrating ML demand forecasting and dynamic slotting optimization.", |
| category: "Warehousing", |
| repoUrl: "https://github.com/ArwaElsayed5/Graduation-Project", |
| websiteUrl: "", |
| submittedBy: "Chainkit demo", |
| createdAt: "2026-11-06T10:00:00.000Z", |
| averageRating: 0, |
| ratingCount: 0, |
| }, |
| { |
| id: "fraudlens-ai", |
| slug: "fraudlens-ai", |
| name: "FraudLens AI", |
| summary: |
| "Procurement audit prototype that applies anomaly detection and NLP to flag suspicious bid and vendor patterns.", |
| category: "Procurement", |
| repoUrl: "https://github.com/thenishantraj/fraudlens-ai", |
| websiteUrl: "", |
| submittedBy: "Chainkit demo", |
| createdAt: "2026-11-06T10:00:00.000Z", |
| averageRating: 0, |
| ratingCount: 0, |
| }, |
| ]; |
|
|
| function getDemoState(): DemoState { |
| globalThis.__chainkitDemoState ??= { |
| tools: demoTools.map((tool) => ({ ...tool })), |
| ratings: new Map(), |
| ratingSums: new Map(), |
| }; |
| return globalThis.__chainkitDemoState; |
| } |
|
|
| function getBigQueryConfig() { |
| const projectId = process.env.BIGQUERY_PROJECT_ID; |
| const dataset = process.env.BIGQUERY_DATASET; |
| if (!projectId && !dataset) return undefined; |
| if (!projectId || !dataset) { |
| throw new Error( |
| "Set both BIGQUERY_PROJECT_ID and BIGQUERY_DATASET to enable BigQuery.", |
| ); |
| } |
| if (!/^[a-z][a-z0-9-]{4,28}[a-z0-9]$/.test(projectId)) { |
| throw new Error("BIGQUERY_PROJECT_ID is not a valid Google Cloud project ID."); |
| } |
| if (!/^[A-Za-z0-9_]{1,1024}$/.test(dataset)) { |
| throw new Error("BIGQUERY_DATASET contains unsupported characters."); |
| } |
| return { projectId, dataset }; |
| } |
|
|
| let bigQueryClient: BigQuery | undefined; |
|
|
| function getBigQuery() { |
| const config = getBigQueryConfig(); |
| if (!config) return undefined; |
| bigQueryClient ??= new BigQuery({ projectId: config.projectId }); |
| return { client: bigQueryClient, ...config }; |
| } |
|
|
| function toolTable(projectId: string, dataset: string) { |
| return `\`${projectId}.${dataset}.tools\``; |
| } |
|
|
| function ratingTable(projectId: string, dataset: string) { |
| return `\`${projectId}.${dataset}.tool_ratings\``; |
| } |
|
|
| function isToolCategory(value: string): value is ToolCategory { |
| return categories.some((item) => item === value); |
| } |
|
|
| function mapBigQueryRow(row: Record<string, unknown>): SupplyChainTool { |
| const category = String(row.category); |
| if (!isToolCategory(category)) { |
| throw new Error(`BigQuery returned an unsupported category: ${category}`); |
| } |
| return { |
| id: String(row.id), |
| slug: String(row.slug), |
| name: String(row.name), |
| summary: String(row.summary), |
| category, |
| repoUrl: String(row.repoUrl), |
| websiteUrl: String(row.websiteUrl ?? ""), |
| submittedBy: String(row.submittedBy), |
| createdAt: new Date(String(row.createdAt)).toISOString(), |
| averageRating: Number(row.averageRating ?? 0), |
| ratingCount: Number(row.ratingCount ?? 0), |
| }; |
| } |
|
|
| function buildToolQuery( |
| projectId: string, |
| dataset: string, |
| where = "", |
| order = "", |
| ) { |
| return ` |
| SELECT |
| t.tool_id AS id, |
| t.slug, |
| t.name, |
| t.summary, |
| t.category, |
| t.repo_url AS repoUrl, |
| t.website_url AS websiteUrl, |
| t.submitted_by AS submittedBy, |
| t.created_at AS createdAt, |
| COALESCE(AVG(r.rating), 0) AS averageRating, |
| COUNT(r.rating) AS ratingCount |
| FROM ${toolTable(projectId, dataset)} AS t |
| LEFT JOIN ${ratingTable(projectId, dataset)} AS r |
| ON t.tool_id = r.tool_id |
| ${where} |
| GROUP BY |
| t.tool_id, t.slug, t.name, t.summary, t.category, t.repo_url, |
| t.website_url, t.submitted_by, t.created_at |
| ${order} |
| `; |
| } |
|
|
| export async function getTools(): Promise<SupplyChainTool[]> { |
| const bigQuery = getBigQuery(); |
| if (!bigQuery) return getDemoState().tools; |
|
|
| const [rows] = await bigQuery.client.query({ |
| query: buildToolQuery( |
| bigQuery.projectId, |
| bigQuery.dataset, |
| "", |
| "ORDER BY t.created_at DESC", |
| ), |
| }); |
| return rows.map(mapBigQueryRow); |
| } |
|
|
| export async function getToolBySlug(slug: string) { |
| const bigQuery = getBigQuery(); |
| if (!bigQuery) { |
| return getDemoState().tools.find((tool) => tool.slug === slug); |
| } |
| const [rows] = await bigQuery.client.query({ |
| query: `${buildToolQuery( |
| bigQuery.projectId, |
| bigQuery.dataset, |
| "WHERE t.slug = @slug", |
| )} LIMIT 1`, |
| params: { slug }, |
| }); |
| return rows[0] ? mapBigQueryRow(rows[0]) : undefined; |
| } |
|
|
| async function getToolById(toolId: string) { |
| const bigQuery = getBigQuery(); |
| if (!bigQuery) { |
| return getDemoState().tools.find((tool) => tool.id === toolId); |
| } |
| const [rows] = await bigQuery.client.query({ |
| query: `${buildToolQuery( |
| bigQuery.projectId, |
| bigQuery.dataset, |
| "WHERE t.tool_id = @toolId", |
| )} LIMIT 1`, |
| params: { toolId }, |
| }); |
| return rows[0] ? mapBigQueryRow(rows[0]) : undefined; |
| } |
|
|
| export async function submitTool(input: NewTool) { |
| const createdAt = new Date().toISOString(); |
| const id = randomUUID(); |
| const slugBase = |
| input.name |
| .toLowerCase() |
| .normalize("NFKD") |
| .replace(/[\u0300-\u036f]/g, "") |
| .replace(/[^a-z0-9]+/g, "-") |
| .replace(/^-|-$/g, "") |
| .slice(0, 48) || "supply-chain-tool"; |
| const tool: SupplyChainTool = { |
| ...input, |
| id, |
| slug: `${slugBase}-${id.slice(0, 8)}`, |
| createdAt, |
| averageRating: 0, |
| ratingCount: 0, |
| }; |
| const bigQuery = getBigQuery(); |
|
|
| if (!bigQuery) { |
| getDemoState().tools.unshift(tool); |
| return tool; |
| } |
|
|
| await bigQuery.client.query({ |
| query: ` |
| INSERT INTO ${toolTable(bigQuery.projectId, bigQuery.dataset)} |
| (tool_id, slug, name, summary, category, repo_url, website_url, submitted_by, created_at) |
| VALUES |
| (@id, @slug, @name, @summary, @category, @repoUrl, @websiteUrl, @submittedBy, TIMESTAMP(@createdAt)) |
| `, |
| params: { |
| id: tool.id, |
| slug: tool.slug, |
| name: tool.name, |
| summary: tool.summary, |
| category: tool.category, |
| repoUrl: tool.repoUrl, |
| websiteUrl: tool.websiteUrl, |
| submittedBy: tool.submittedBy, |
| createdAt: tool.createdAt, |
| }, |
| }); |
| return tool; |
| } |
|
|
| export async function rateTool(toolId: string, voterId: string, rating: number) { |
| const bigQuery = getBigQuery(); |
| if (!bigQuery) { |
| const state = getDemoState(); |
| const tool = state.tools.find((candidate) => candidate.id === toolId); |
| if (!tool) return undefined; |
|
|
| const key = `${toolId}:${voterId}`; |
| const previousRating = state.ratings.get(key); |
| const total = state.ratingSums.get(toolId) ?? tool.averageRating * tool.ratingCount; |
| const nextCount = tool.ratingCount + (previousRating === undefined ? 1 : 0); |
| const nextTotal = total - (previousRating ?? 0) + rating; |
| state.ratings.set(key, rating); |
| state.ratingSums.set(toolId, nextTotal); |
| tool.averageRating = nextTotal / nextCount; |
| tool.ratingCount = nextCount; |
| return tool; |
| } |
|
|
| const tool = await getToolById(toolId); |
| if (!tool) return undefined; |
|
|
| await bigQuery.client.query({ |
| query: ` |
| MERGE ${ratingTable(bigQuery.projectId, bigQuery.dataset)} AS target |
| USING (SELECT @toolId AS tool_id, @voterId AS voter_id, @rating AS rating) AS source |
| ON target.tool_id = source.tool_id AND target.voter_id = source.voter_id |
| WHEN MATCHED THEN |
| UPDATE SET rating = source.rating, updated_at = CURRENT_TIMESTAMP() |
| WHEN NOT MATCHED THEN |
| INSERT (tool_id, voter_id, rating, created_at, updated_at) |
| VALUES (source.tool_id, source.voter_id, source.rating, CURRENT_TIMESTAMP(), CURRENT_TIMESTAMP()) |
| `, |
| params: { toolId, voterId, rating }, |
| }); |
| return getToolById(toolId); |
| } |
|
|
