From 434ec07885bf2df9a62ae95e0f617908285d038e Mon Sep 17 00:00:00 2001 From: Replit Agent Date: Wed, 10 Jun 2026 18:53:17 +0000 Subject: [PATCH] Add live progress updates and detailed scan checkpoints to scan results Introduce streaming endpoint for NDJSON scan progress, incorporate scan checkpoints into scan details, and update UI components to display this new information. Replit-Commit-Author: Agent Replit-Commit-Session-Id: 0d01f99a-ea6a-447d-82fd-311715434a39 Replit-Commit-Checkpoint-Type: full_checkpoint Replit-Commit-Event-Id: 2852b526-3bf8-4a93-a62a-a50e26291074 Replit-Commit-Screenshot-Url: https://storage.googleapis.com/screenshot-production-us-central1/e32d2b99-1721-47dd-833c-98b372f48008/0d01f99a-ea6a-447d-82fd-311715434a39/8MCgDZm Replit-Helium-Checkpoint-Created: true --- .agents/memory/MEMORY.md | 1 + .../memory/ndjson-streaming-express-replit.md | 36 ++ .agents/memory/openai-temperature-gpt5.md | 5 +- artifacts/api-server/src/lib/scanEngine.ts | 116 +++++- artifacts/api-server/src/routes/scans.ts | 209 ++++++++--- artifacts/skillguard/public/opengraph.jpg | Bin 18404 -> 82375 bytes .../skillguard/src/components/ui-helpers.tsx | 24 +- artifacts/skillguard/src/lib/streamScan.ts | 119 ++++++ artifacts/skillguard/src/pages/scan-form.tsx | 347 +++++++++++++++--- .../skillguard/src/pages/scan-report.tsx | 74 +++- .../src/generated/api.schemas.ts | 65 ++++ lib/api-spec/openapi.yaml | 36 +- lib/api-zod/src/generated/api.ts | 13 +- lib/api-zod/src/generated/types/index.ts | 5 + .../src/generated/types/scanCheckpoint.ts | 29 ++ .../src/generated/types/scanCheckpointAxis.ts | 18 + .../types/scanCheckpointDetectedBy.ts | 18 + .../generated/types/scanCheckpointSeverity.ts | 21 ++ .../generated/types/scanCheckpointStatus.ts | 17 + lib/api-zod/src/generated/types/scanDetail.ts | 2 + lib/db/src/schema/scans.ts | 19 + 21 files changed, 1064 insertions(+), 110 deletions(-) create mode 100644 .agents/memory/ndjson-streaming-express-replit.md create mode 100644 artifacts/skillguard/src/lib/streamScan.ts create mode 100644 lib/api-zod/src/generated/types/scanCheckpoint.ts create mode 100644 lib/api-zod/src/generated/types/scanCheckpointAxis.ts create mode 100644 lib/api-zod/src/generated/types/scanCheckpointDetectedBy.ts create mode 100644 lib/api-zod/src/generated/types/scanCheckpointSeverity.ts create mode 100644 lib/api-zod/src/generated/types/scanCheckpointStatus.ts diff --git a/.agents/memory/MEMORY.md b/.agents/memory/MEMORY.md index 5793f2b..5968210 100644 --- a/.agents/memory/MEMORY.md +++ b/.agents/memory/MEMORY.md @@ -1,2 +1,3 @@ - [lucide-react icon name collisions](lucide-icon-name-collisions.md) — `Badge`/`Activity` from lucide collide with shadcn/ui Badge and React 19 Activity; import Badge from ui, Activity from lucide. - [OpenAI gpt-5 temperature](openai-temperature-gpt5.md) — gpt-5* reject `temperature != 1`; omit temperature in OpenAI-compatible clients or AI analysis silently fails. +- [NDJSON streaming on Replit](ndjson-streaming-express-replit.md) — use `res.on("close")`+`writableFinished` (NOT `req.on("close")`); persist on disconnect; proxy doesn't buffer; gate fallback to avoid dup rows. diff --git a/.agents/memory/ndjson-streaming-express-replit.md b/.agents/memory/ndjson-streaming-express-replit.md new file mode 100644 index 0000000..aeb823f --- /dev/null +++ b/.agents/memory/ndjson-streaming-express-replit.md @@ -0,0 +1,36 @@ +--- +name: NDJSON streaming under Express behind the Replit proxy +description: Pitfalls for live/streaming HTTP responses (NDJSON/SSE) from an Express API on Replit — client-disconnect detection, persistence, and proxy buffering +--- + +# Streaming responses (NDJSON) from Express on Replit + +For a long-lived POST that streams progress (e.g. `application/x-ndjson` with +`res.flushHeaders()` then line-delimited JSON writes): + +**Detect a real client abort with `res.on("close")` + `res.writableFinished` — never +`req.on("close")`.** +`req.on("close")` fires as soon as the POST *request body* has been fully consumed, +which is normal and happens immediately. Gating writes on that wrongly suppresses the +entire stream. Use the *response* close event, and treat it as an abort only when +`!res.writableFinished`. + +**Persist the result regardless of disconnect.** Run the analysis and the DB write +inside the handler's `try` unconditionally; only guard the `res.write()` calls on +"connection still open". This way a client that disconnects mid-stream still gets its +result persisted (and the client must NOT re-submit on a mid-stream error, or it +creates a duplicate row — see below). + +**The Replit path-proxy does NOT buffer the stream.** Incremental flushes arrive line +by line through `$REPLIT_DEV_DOMAIN`, same as `localhost`. No special proxy header or +chunk-padding needed. + +**Client fetch must be root-relative (`/api/...`), not `import.meta.env.BASE_URL`.** +That matches the generated API client and is what routes correctly through the proxy. + +**Fallback gating to avoid duplicate persists:** a client that streams and also falls +back to a non-streaming POST on error must only fall back when the server never +processed the request (fetch rejected, or `!res.ok` with a 5xx). Once the response +body has started streaming, any read error means the server is already persisting — +falling back then duplicates the record. Distinguish 4xx (show message, no retry) +from transport failures. diff --git a/.agents/memory/openai-temperature-gpt5.md b/.agents/memory/openai-temperature-gpt5.md index 625c1b8..e5da2e5 100644 --- a/.agents/memory/openai-temperature-gpt5.md +++ b/.agents/memory/openai-temperature-gpt5.md @@ -16,6 +16,5 @@ rather than hardcoding a low value for determinism. **Why:** older models accepted `temperature: 0.1` but gpt-5* only accept the default. A hardcoded low temperature breaks every scan against modern models. -**How to apply:** in `artifacts/api-server/src/lib/aiAnalysis.ts` the OpenAI-compatible -path no longer sends `temperature`. If reintroducing sampling controls, gate them per -model or make them optional. +**How to apply:** in the OpenAI-compatible AI-analysis path, do not send `temperature`. +If reintroducing sampling controls, gate them per model or make them optional. diff --git a/artifacts/api-server/src/lib/scanEngine.ts b/artifacts/api-server/src/lib/scanEngine.ts index 377f1e7..92e23a7 100644 --- a/artifacts/api-server/src/lib/scanEngine.ts +++ b/artifacts/api-server/src/lib/scanEngine.ts @@ -15,9 +15,14 @@ import { type Severity, type Axis, } from "./ruleCatalog"; -import type { FindingCounts as DbFindingCounts } from "@workspace/db"; +import type { + FindingCounts as DbFindingCounts, + ScanCheckpoint, +} from "@workspace/db"; import { runAiAnalysis, type AiRuleConfig } from "./aiAnalysis"; +export type { ScanCheckpoint } from "@workspace/db"; + const SEVERITY_WEIGHT: Record = { critical: 50, high: 18, @@ -26,9 +31,18 @@ const SEVERITY_WEIGHT: Record = { info: 0, }; +export type ScanProgressEvent = + | { type: "ai-start" } + | { type: "checkpoint"; checkpoint: ScanCheckpoint }; + +export type ProgressFn = ( + event: ScanProgressEvent, +) => void | Promise; + export type EngineResult = { findings: RawFinding[]; counts: DbFindingCounts; + checkpoints: ScanCheckpoint[]; riskScore: number; verdict: "pass" | "review" | "block"; aiUsed: boolean; @@ -70,29 +84,75 @@ export function computeVerdict( return "pass"; } +function scoreOf(findings: RawFinding[]): number { + return findings.reduce((s, f) => s + SEVERITY_WEIGHT[f.severity], 0); +} + export async function analyzeSkill( files: ParsedFile[], useAi: boolean, + onProgress?: ProgressFn, ): Promise { const dbRules = await db.select().from(rulesTable); const ruleConfig = new Map( - dbRules.map((r) => [r.ruleId, { enabled: r.enabled, severity: r.severity as Severity }]), + dbRules.map((r) => [ + r.ruleId, + { enabled: r.enabled, severity: r.severity as Severity }, + ]), ); const findings: RawFinding[] = []; + const checkpoints: ScanCheckpoint[] = []; + for (const rule of STATIC_RULES) { const cfg = ruleConfig.get(rule.ruleId); - if (cfg && !cfg.enabled) continue; const severity = cfg?.severity ?? rule.defaultSeverity; - for (const file of files) { - findings.push(...runStaticRule(rule, file, severity)); + + if (cfg && !cfg.enabled) { + const checkpoint: ScanCheckpoint = { + id: rule.ruleId, + label: rule.title, + category: rule.category, + axis: rule.axis, + severity, + status: "skipped", + findingCount: 0, + scoreDelta: 0, + detectedBy: "static", + }; + checkpoints.push(checkpoint); + await onProgress?.({ type: "checkpoint", checkpoint }); + continue; } + + const ruleFindings: RawFinding[] = []; + for (const file of files) { + ruleFindings.push(...runStaticRule(rule, file, severity)); + } + findings.push(...ruleFindings); + + const checkpoint: ScanCheckpoint = { + id: rule.ruleId, + label: rule.title, + category: rule.category, + axis: rule.axis, + severity, + status: ruleFindings.length > 0 ? "flagged" : "pass", + findingCount: ruleFindings.length, + scoreDelta: scoreOf(ruleFindings), + detectedBy: "static", + }; + checkpoints.push(checkpoint); + await onProgress?.({ type: "checkpoint", checkpoint }); } let aiUsed = false; let aiError: string | null = null; + let aiFindings: RawFinding[] = []; if (useAi) { + await onProgress?.({ type: "ai-start" }); + const aiRuleIds = new Set(AI_RULES.map((r) => r.ruleId)); const enabledAiRules: AiRuleConfig[] = AI_RULES.filter((rule) => { const cfg = ruleConfig.get(rule.ruleId); @@ -131,14 +191,58 @@ export async function analyzeSkill( aiError = result.error; if (!result.error) { aiUsed = true; + aiFindings = result.findings; findings.push(...result.findings); } } + + for (const rule of AI_RULES) { + const cfg = ruleConfig.get(rule.ruleId); + const severity = cfg?.severity ?? rule.defaultSeverity; + const enabled = cfg ? cfg.enabled : true; + + let status: ScanCheckpoint["status"]; + let findingCount = 0; + let scoreDelta = 0; + + if (!enabled) { + status = "skipped"; + } else if (!aiUsed) { + status = "error"; + } else { + const ruleFindings = aiFindings.filter((f) => f.ruleId === rule.ruleId); + findingCount = ruleFindings.length; + scoreDelta = scoreOf(ruleFindings); + status = findingCount > 0 ? "flagged" : "pass"; + } + + const checkpoint: ScanCheckpoint = { + id: rule.ruleId, + label: rule.title, + category: rule.category, + axis: rule.axis, + severity, + status, + findingCount, + scoreDelta, + detectedBy: "ai", + }; + checkpoints.push(checkpoint); + await onProgress?.({ type: "checkpoint", checkpoint }); + } } const riskScore = computeScore(findings); const counts = computeCounts(findings); const verdict = computeVerdict(findings, riskScore); - return { findings, counts, riskScore, verdict, aiUsed, aiError }; + return { + findings, + counts, + checkpoints, + riskScore, + verdict, + aiUsed, + aiError, + }; } diff --git a/artifacts/api-server/src/routes/scans.ts b/artifacts/api-server/src/routes/scans.ts index 6627569..798a47d 100644 --- a/artifacts/api-server/src/routes/scans.ts +++ b/artifacts/api-server/src/routes/scans.ts @@ -22,12 +22,14 @@ import { parseText, deriveScanName, } from "../lib/skillParser"; -import { analyzeSkill } from "../lib/scanEngine"; -import type { ParsedFile } from "../lib/ruleCatalog"; +import { analyzeSkill, type EngineResult } from "../lib/scanEngine"; +import { STATIC_RULES, AI_RULES, type ParsedFile } from "../lib/ruleCatalog"; import { logger } from "../lib/logger"; const router: IRouter = Router(); +type CreateScanInput = ReturnType; + export function serializeScan(scan: Scan) { return { id: scan.id, @@ -69,32 +71,33 @@ function serializeFinding(f: Finding) { }; } -router.get("/scans", async (_req, res) => { - const rows = await db - .select() - .from(scansTable) - .orderBy(desc(scansTable.createdAt)); - res.json(ListScansResponse.parse(rows.map(serializeScan))); -}); +function serializeScanDetail( + scan: Scan, + files: ScanFile[], + findings: Finding[], +) { + return { + ...serializeScan(scan), + checkpoints: scan.checkpoints ?? [], + files: files.map(serializeFile), + findings: [...findings].sort((a, b) => a.id - b.id).map(serializeFinding), + }; +} -router.post("/scans", async (req, res) => { - const parsed = CreateScanBody.safeParse(req.body); - if (!parsed.success) { - return res - .status(400) - .json({ message: "Ungültige Eingabe", details: parsed.error.issues }); - } - const input = parsed.data; +type ParseResult = + | { ok: true; files: ParsedFile[] } + | { ok: false; status: number; message: string }; - let files: ParsedFile[] = []; +function parseScanInput(input: CreateScanInput): ParseResult { try { + let files: ParsedFile[]; if (input.source === "zip") { if (!input.contentBase64) - return res.status(400).json({ message: "ZIP-Inhalt fehlt." }); + return { ok: false, status: 400, message: "ZIP-Inhalt fehlt." }; files = parseZip(Buffer.from(input.contentBase64, "base64")); } else if (input.source === "file") { if (!input.contentBase64) - return res.status(400).json({ message: "Dateiinhalt fehlt." }); + return { ok: false, status: 400, message: "Dateiinhalt fehlt." }; files = [ parseSingleFile( input.filename ?? "datei", @@ -103,26 +106,33 @@ router.post("/scans", async (req, res) => { ]; } else { if (!input.text || !input.text.trim()) - return res.status(400).json({ message: "Text fehlt." }); + return { ok: false, status: 400, message: "Text fehlt." }; files = [parseText(input.text, input.name ?? "SKILL.md")]; } + if (files.length === 0) + return { + ok: false, + status: 400, + message: "Keine analysierbaren Dateien gefunden.", + }; + return { ok: true, files }; } catch (err) { logger.error({ err }, "Skill-Parsing fehlgeschlagen"); - return res.status(400).json({ + return { + ok: false, + status: 400, message: "Das Skill konnte nicht gelesen werden. Bitte prüfen Sie das Format (gültiges ZIP / Textdatei).", - }); + }; } +} - if (files.length === 0) { - return res - .status(400) - .json({ message: "Keine analysierbaren Dateien gefunden." }); - } - - const name = input.name?.trim() || deriveScanName(files, "Unbenanntes Skill"); - const result = await analyzeSkill(files, input.useAi); - +async function persistScan( + input: CreateScanInput, + name: string, + files: ParsedFile[], + result: EngineResult, +): Promise<{ scan: Scan; files: ScanFile[]; findings: Finding[] }> { const [scan] = await db .insert(scansTable) .values({ @@ -135,6 +145,7 @@ router.post("/scans", async (req, res) => { aiUsed: result.aiUsed, aiError: result.aiError, findingCounts: result.counts, + checkpoints: result.checkpoints, }) .returning(); @@ -176,14 +187,127 @@ router.post("/scans", async (req, res) => { .returning(); } - const payload = { - ...serializeScan(scan), - files: insertedFiles.map(serializeFile), - findings: insertedFindings - .sort((a, b) => a.id - b.id) - .map(serializeFinding), + return { scan, files: insertedFiles, findings: insertedFindings }; +} + +router.get("/scans", async (_req, res) => { + const rows = await db + .select() + .from(scansTable) + .orderBy(desc(scansTable.createdAt)); + res.json(ListScansResponse.parse(rows.map(serializeScan))); +}); + +router.post("/scans", async (req, res) => { + const parsed = CreateScanBody.safeParse(req.body); + if (!parsed.success) { + return res + .status(400) + .json({ message: "Ungültige Eingabe", details: parsed.error.issues }); + } + const input = parsed.data; + + const parseResult = parseScanInput(input); + if (!parseResult.ok) { + return res.status(parseResult.status).json({ message: parseResult.message }); + } + const files = parseResult.files; + + const name = input.name?.trim() || deriveScanName(files, "Unbenanntes Skill"); + const result = await analyzeSkill(files, input.useAi); + const { scan, files: insertedFiles, findings } = await persistScan( + input, + name, + files, + result, + ); + + return res + .status(201) + .json(GetScanResponse.parse(serializeScanDetail(scan, insertedFiles, findings))); +}); + +const STREAM_PACING_MS = 80; +const delay = (ms: number) => new Promise((resolve) => setTimeout(resolve, ms)); + +router.post("/scans/stream", async (req, res) => { + const parsed = CreateScanBody.safeParse(req.body); + if (!parsed.success) { + res + .status(400) + .json({ message: "Ungültige Eingabe", details: parsed.error.issues }); + return; + } + const input = parsed.data; + + const parseResult = parseScanInput(input); + if (!parseResult.ok) { + res.status(parseResult.status).json({ message: parseResult.message }); + return; + } + const files = parseResult.files; + const name = input.name?.trim() || deriveScanName(files, "Unbenanntes Skill"); + + res.status(200); + res.setHeader("Content-Type", "application/x-ndjson; charset=utf-8"); + res.setHeader("Cache-Control", "no-cache, no-transform"); + res.setHeader("X-Accel-Buffering", "no"); + res.setHeader("Connection", "keep-alive"); + res.flushHeaders(); + + // Detect a genuine client disconnect. NOTE: do NOT use req.on("close") here — + // for a POST it fires as soon as the request body is consumed, not on abort. + // res "close" before writableFinished means the client went away. + let aborted = false; + res.on("close", () => { + if (!res.writableFinished) aborted = true; + }); + + const write = (obj: unknown) => { + if (aborted || res.writableEnded) return; + res.write(JSON.stringify(obj) + "\n"); }; - return res.status(201).json(GetScanResponse.parse(payload)); + + write({ + type: "start", + name, + fileCount: files.length, + totalChecks: STATIC_RULES.length + (input.useAi ? AI_RULES.length : 0), + }); + + let cumulative = 0; + try { + const result = await analyzeSkill(files, input.useAi, async (event) => { + if (event.type === "ai-start") { + write({ type: "ai-start" }); + return; + } + cumulative += event.checkpoint.scoreDelta; + write({ + type: "checkpoint", + checkpoint: event.checkpoint, + runningScore: Math.min(100, cumulative), + }); + if (!aborted) await delay(STREAM_PACING_MS); + }); + + const { scan } = await persistScan(input, name, files, result); + + write({ + type: "done", + scanId: scan.id, + riskScore: result.riskScore, + verdict: result.verdict, + findingCounts: result.counts, + aiUsed: result.aiUsed, + aiError: result.aiError, + }); + if (!aborted && !res.writableEnded) res.end(); + } catch (err) { + logger.error({ err }, "Streaming-Scan fehlgeschlagen"); + write({ type: "error", message: "Die Analyse ist fehlgeschlagen." }); + if (!aborted && !res.writableEnded) res.end(); + } }); router.get("/scans/:id", async (req, res) => { @@ -207,12 +331,7 @@ router.get("/scans/:id", async (req, res) => { .where(eq(findingsTable.scanId, scan.id)) .orderBy(findingsTable.id); - const payload = { - ...serializeScan(scan), - files: files.map(serializeFile), - findings: findings.map(serializeFinding), - }; - return res.json(GetScanResponse.parse(payload)); + return res.json(GetScanResponse.parse(serializeScanDetail(scan, files, findings))); }); router.delete("/scans/:id", async (req, res) => { diff --git a/artifacts/skillguard/public/opengraph.jpg b/artifacts/skillguard/public/opengraph.jpg index 01f64318e68c4cd056074cd36b12413a8766b4f3..38feab2cef24bc0fc621492bb2955f9d1814c6cd 100644 GIT binary patch literal 82375 zcmdqJ1ytMJmIoS&7An_|;jBnwfsgC-^L4AP$C_oJ$3wU|= z{-|eEaLfPzM9u&J^pF2YGyMbr)O-K{sAm3=#+(iS5WNQgst5m(_Kz`fGI25aqd5#z ze9zJn065MC00?ve0Ma1<09XHyJXG`_(8hqu0;1@0M18CPb^r?i13(_&05Ah^p%5Q{ z2fzyu`aKJf1YlucVqs!nVPRrnV`JgqKETDje;=2OkO=<)B^ebJB^d<;4IRrv8d@eG z1qA~q1Jh&HC+ttCAA)#5Y&K%U#lb0 zSR|oA%T$lughgC4q|6Ud&C;Se{4@N$Qvljsvsl=uObKFC9{_aJkfEbtqhp|>il7nS zdvu6S!uvwi#5v}3>o5i;X+Rkx-|`U_89BvEHFc(MBh02Q@Qm`6-!lMwbX0v}bYj3W zz*1;v6Coob10&GX-$e7OE}E@<)0%XB_BQC zwxti2+LS-rqZF2-Pc3QnY>@g1(n|i|YIl;Vtn^dTZ!LXUSJ9$=yuL_nmLo^No-3cY z<-!55ZXECfhK)Fw6|T}q1bvup5RbLR>M+dH&5^UoFC$lPdNtwsCI#vLl?gs|?mk;N zeyv&~;3JD!m8jRt&lqmQpieIOs=DeY*e^unM^cWdB~#6T3{6rPa!}M?yLw1-Zs&7G z&1kQ>Hh*O&ney1i!#BF+cJs#~Ycc0Op|B@6da{=lr_}}l4Xjk-a4gXy!vgVy>3+mv zYB?>d@(Z==Lg2J*36dAg^)W#tfFcoqXnX$rrPB@o~d-y5%ogneT0zxfTo z9kCm4u&Aadbd*{3nbu!p9xKUDK;%GIT}{%DhG}_5+nB%-7G`fx7v-uips>k}O2cTo zYQ8py+Dn0OSda(Z3Y(#U@CesTdu`$NJ)#9rHnK;6rBA(j+SZj$43<_1GRy z><%U-he(V&TNEd<4rx};UF^?lm^g(E+&sE$1ry<4C6F8-A3Uzmc-z)rVxOFomsKP0 z%4H8enAl9c>Z{Q%vWhVv&`JITLk`8qy{ZijEx-wV7aIEaDDO9bcVSIa_9yIu;YuPj zA}BAkkt1Ppcf6!rK@mALy}7;GQES6t8nxHe)vFi)eBhJUsBbjByEl`rK2th@m>y)? 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+import { ShieldCheck, ShieldAlert, Shield, AlertTriangle, Info, AlertCircle, AlertOctagon, CheckCircle2, MinusCircle, XCircle } from "lucide-react"; + +export const CHECKPOINT_STATUS_LABELS: Record = { + pass: "Unauffällig", + flagged: "Auffällig", + skipped: "Übersprungen", + error: "Fehler", +}; + +export function CheckpointStatusBadge({ status, className }: { status: string, className?: string }) { + switch (status) { + case "pass": + return Unauffällig; + case "flagged": + return Auffällig; + case "skipped": + return Übersprungen; + case "error": + return Fehler; + default: + return {status}; + } +} export function VerdictBadge({ verdict, className }: { verdict: string, className?: string }) { switch (verdict) { diff --git a/artifacts/skillguard/src/lib/streamScan.ts b/artifacts/skillguard/src/lib/streamScan.ts new file mode 100644 index 0000000..bb40031 --- /dev/null +++ b/artifacts/skillguard/src/lib/streamScan.ts @@ -0,0 +1,119 @@ +import type { + SkillScanInput, + ScanCheckpoint, + FindingCounts, +} from "@workspace/api-client-react"; + +export type ScanStreamEvent = + | { type: "start"; name: string; fileCount: number; totalChecks: number } + | { type: "ai-start" } + | { type: "checkpoint"; checkpoint: ScanCheckpoint; runningScore: number } + | { + type: "done"; + scanId: number; + riskScore: number; + verdict: string; + findingCounts: FindingCounts; + aiUsed: boolean; + aiError: string | null; + } + | { type: "error"; message: string }; + +/** + * Fehler beim Aufruf des Streaming-Endpunkts. `allowFallback` zeigt an, ob ein + * Rückfall auf den nicht-streamenden Endpunkt sinnvoll ist. Bei Client-Fehlern + * (4xx, z. B. ungültige Eingabe) ist das nicht der Fall – die Servermeldung + * soll direkt angezeigt werden, statt dieselbe Anfrage erneut zu senden. + */ +export class ScanStreamError extends Error { + allowFallback: boolean; + constructor(message: string, allowFallback: boolean) { + super(message); + this.name = "ScanStreamError"; + this.allowFallback = allowFallback; + } +} + +/** + * Streamt einen Skill-Scan über NDJSON. Ruft `onEvent` für jedes Ereignis auf, + * sobald es eintrifft (Live-Prüfschritte). Wirft bei Transportfehlern; ein vom + * Server gemeldeter Analysefehler kommt als `{ type: "error" }`-Ereignis an. + * + * Nutzt – wie der generierte API-Client – eine wurzelrelative `/api`-URL, damit + * der Replit-Pfad-Proxy die Anfrage korrekt an den API-Server weiterleitet. + */ +export async function streamScan( + input: SkillScanInput, + onEvent: (event: ScanStreamEvent) => void, + signal?: AbortSignal, +): Promise { + let res: Response; + try { + res = await fetch("/api/scans/stream", { + method: "POST", + headers: { "Content-Type": "application/json" }, + body: JSON.stringify(input), + signal, + }); + } catch (err) { + // Verbindung kam nicht zustande – der Server hat die Anfrage nicht erhalten. + // Rückfall auf den nicht-streamenden Endpunkt ist sicher und sinnvoll. + throw new ScanStreamError( + err instanceof Error ? err.message : "Verbindung zum Server fehlgeschlagen.", + true, + ); + } + + if (!res.ok || !res.body) { + let message = "Live-Analyse nicht verfügbar."; + try { + const body = await res.json(); + if (body && typeof body.message === "string") message = body.message; + } catch { + // ignore – Standardmeldung verwenden + } + // 4xx = Client-/Eingabefehler: Meldung direkt anzeigen, kein erneuter Versuch. + // 5xx oder fehlender Body: Rückfall auf den nicht-streamenden Endpunkt erlauben. + const isClientError = res.status >= 400 && res.status < 500; + throw new ScanStreamError(message, !isClientError); + } + + const reader = res.body.getReader(); + const decoder = new TextDecoder(); + let buffer = ""; + + const emit = (line: string) => { + const trimmed = line.trim(); + if (!trimmed) return; + try { + onEvent(JSON.parse(trimmed) as ScanStreamEvent); + } catch { + // Unvollständige / nicht-JSON Zeile ignorieren + } + }; + + // Ab hier verarbeitet der Server die Anfrage und persistiert das Ergebnis auch + // bei Verbindungsabbruch. Ein Fehler beim Lesen darf daher NICHT zum Rückfall + // führen, sonst entsteht ein doppelter Scan-Eintrag. + try { + for (;;) { + const { value, done } = await reader.read(); + if (done) break; + buffer += decoder.decode(value, { stream: true }); + let newlineIndex: number; + while ((newlineIndex = buffer.indexOf("\n")) >= 0) { + const line = buffer.slice(0, newlineIndex); + buffer = buffer.slice(newlineIndex + 1); + emit(line); + } + } + emit(buffer); + } catch (err) { + throw new ScanStreamError( + err instanceof Error && err.name === "AbortError" + ? "Die Analyse wurde abgebrochen." + : "Die Live-Übertragung wurde unterbrochen. Der Scan läuft möglicherweise im Hintergrund weiter – bitte prüfen Sie den Verlauf.", + false, + ); + } +} diff --git a/artifacts/skillguard/src/pages/scan-form.tsx b/artifacts/skillguard/src/pages/scan-form.tsx index 807bd9b..e08686b 100644 --- a/artifacts/skillguard/src/pages/scan-form.tsx +++ b/artifacts/skillguard/src/pages/scan-form.tsx @@ -1,6 +1,11 @@ -import { useState } from "react"; +import { useMemo, useState } from "react"; import { useLocation } from "wouter"; -import { useCreateScan, SkillScanInputSource } from "@workspace/api-client-react"; +import { + useCreateScan, + SkillScanInputSource, + type SkillScanInput, + type ScanCheckpoint, +} from "@workspace/api-client-react"; import { Card, CardContent, CardDescription, CardHeader, CardTitle, CardFooter } from "@/components/ui/card"; import { Button } from "@/components/ui/button"; import { Input } from "@/components/ui/input"; @@ -8,26 +13,126 @@ import { Label } from "@/components/ui/label"; import { Textarea } from "@/components/ui/textarea"; import { Tabs, TabsContent, TabsList, TabsTrigger } from "@/components/ui/tabs"; import { Switch } from "@/components/ui/switch"; -import { FileUp, FileText, Type, Loader2, ShieldCheck } from "lucide-react"; +import { Progress } from "@/components/ui/progress"; +import { Badge } from "@/components/ui/badge"; +import { CheckpointStatusBadge, AxisBadge } from "@/components/ui-helpers"; +import { + FileUp, + FileText, + Type, + Loader2, + ShieldCheck, + Sparkles, + Activity, + CheckCircle2, +} from "lucide-react"; import { useToast } from "@/hooks/use-toast"; +import { streamScan, ScanStreamError, type ScanStreamEvent } from "@/lib/streamScan"; + +type Phase = "idle" | "scanning" | "done"; + +function scoreColor(score: number): string { + if (score < 30) return "text-emerald-500"; + if (score < 70) return "text-amber-500"; + return "text-rose-500"; +} + +function deltaLabel(checkpoint: ScanCheckpoint): string { + if (checkpoint.status === "skipped") return "übersprungen"; + if (checkpoint.scoreDelta > 0) return `+${checkpoint.scoreDelta} Punkte`; + return "0 Punkte"; +} export default function ScanForm() { const [, setLocation] = useLocation(); const { toast } = useToast(); const createScan = useCreateScan(); - + const [sourceType, setSourceType] = useState("file"); const [name, setName] = useState(""); const [useAi, setUseAi] = useState(false); const [file, setFile] = useState(null); const [text, setText] = useState(""); + const [phase, setPhase] = useState("idle"); + const [steps, setSteps] = useState([]); + const [runningScore, setRunningScore] = useState(0); + const [totalChecks, setTotalChecks] = useState(0); + const [aiActive, setAiActive] = useState(false); + const [finalVerdict, setFinalVerdict] = useState(null); + + const isBusy = phase === "scanning" || phase === "done" || createScan.isPending; + + const groupedSteps = useMemo(() => { + const order: string[] = []; + const groups = new Map(); + for (const step of steps) { + if (!groups.has(step.category)) { + groups.set(step.category, []); + order.push(step.category); + } + groups.get(step.category)!.push(step); + } + return order.map((category) => ({ category, steps: groups.get(category)! })); + }, [steps]); + const handleFileChange = (e: React.ChangeEvent) => { if (e.target.files && e.target.files[0]) { setFile(e.target.files[0]); } }; + const buildInput = async (): Promise => { + let contentBase64: string | undefined = undefined; + let filename: string | undefined = undefined; + + if (file && (sourceType === "file" || sourceType === "zip")) { + const reader = new FileReader(); + const base64Promise = new Promise((resolve, reject) => { + reader.onload = () => { + const result = reader.result as string; + const base64 = result.split(",")[1] || result; + resolve(base64); + }; + reader.onerror = reject; + }); + reader.readAsDataURL(file); + contentBase64 = await base64Promise; + filename = file.name; + } + + return { + name: name || undefined, + source: sourceType, + useAi, + contentBase64, + filename, + text: sourceType === "text" ? text : undefined, + }; + }; + + const finishWithScan = (scanId: number) => { + setPhase("done"); + window.setTimeout(() => { + toast({ title: "Scan abgeschlossen", description: "Der Bericht wird geöffnet." }); + setLocation(`/berichte/${scanId}`); + }, 900); + }; + + const runNonStreaming = async (input: SkillScanInput) => { + try { + const data = await createScan.mutateAsync({ data: input }); + finishWithScan(data.id); + } catch (err) { + setPhase("idle"); + toast({ + title: "Fehler", + description: "Der Scan konnte nicht durchgeführt werden.", + variant: "destructive", + }); + } + }; + const handleSubmit = async (e: React.FormEvent) => { e.preventDefault(); @@ -40,49 +145,193 @@ export default function ScanForm() { return; } + let input: SkillScanInput; try { - let contentBase64: string | undefined = undefined; - let filename: string | undefined = undefined; + input = await buildInput(); + } catch { + toast({ title: "Fehler", description: "Beim Verarbeiten der Datei ist ein Fehler aufgetreten.", variant: "destructive" }); + return; + } - if (file && (sourceType === "file" || sourceType === "zip")) { - const reader = new FileReader(); - const base64Promise = new Promise((resolve, reject) => { - reader.onload = () => { - const result = reader.result as string; - // Strip data URL prefix - const base64 = result.split(',')[1] || result; - resolve(base64); - }; - reader.onerror = reject; - }); - reader.readAsDataURL(file); - contentBase64 = await base64Promise; - filename = file.name; - } + setPhase("scanning"); + setSteps([]); + setRunningScore(0); + setTotalChecks(0); + setAiActive(false); + setFinalVerdict(null); - createScan.mutate({ - data: { - name: name || undefined, - source: sourceType, - useAi, - contentBase64, - filename, - text: sourceType === "text" ? text : undefined - } - }, { - onSuccess: (data) => { - toast({ title: "Scan erfolgreich", description: "Der Skill wurde erfolgreich analysiert." }); - setLocation(`/berichte/${data.id}`); - }, - onError: (err) => { - toast({ title: "Fehler", description: "Der Scan konnte nicht durchgeführt werden.", variant: "destructive" }); + let outcome: "done" | "error" | null = null; + let doneScanId: number | null = null; + let errorMessage = "Die Analyse ist fehlgeschlagen."; + + try { + await streamScan(input, (event: ScanStreamEvent) => { + switch (event.type) { + case "start": + setTotalChecks(event.totalChecks); + break; + case "ai-start": + setAiActive(true); + break; + case "checkpoint": + setSteps((prev) => [...prev, event.checkpoint]); + setRunningScore(event.runningScore); + if (event.checkpoint.detectedBy === "ai") setAiActive(false); + break; + case "done": + outcome = "done"; + doneScanId = event.scanId; + setRunningScore(event.riskScore); + setFinalVerdict(event.verdict); + break; + case "error": + outcome = "error"; + errorMessage = event.message; + break; } }); } catch (err) { - toast({ title: "Fehler", description: "Beim Verarbeiten der Datei ist ein Fehler aufgetreten.", variant: "destructive" }); + // Rückfall nur, wenn der Server die Anfrage nicht verarbeitet hat + // (Verbindung kam nicht zustande oder 5xx). Bei Client-Fehlern (4xx) oder + // einem Abbruch während des Streamings persistiert der Server bereits – + // ein erneuter Versuch würde einen doppelten Eintrag erzeugen. + const canFallback = err instanceof ScanStreamError ? err.allowFallback : true; + if (canFallback) { + await runNonStreaming(input); + return; + } + setPhase("idle"); + toast({ + title: "Fehler", + description: err instanceof Error ? err.message : "Die Analyse ist fehlgeschlagen.", + variant: "destructive", + }); + return; + } + + if (outcome === "done" && doneScanId != null) { + finishWithScan(doneScanId); + } else if (outcome === "error") { + setPhase("idle"); + toast({ title: "Fehler", description: errorMessage, variant: "destructive" }); + } else { + // Stream endete ohne Abschluss-Ereignis: Fallback auf klassischen Scan. + await runNonStreaming(input); } }; + if (phase === "scanning" || phase === "done") { + const completed = steps.length; + const progressPct = totalChecks > 0 ? (completed / totalChecks) * 100 : 0; + return ( +

+
+

+ {phase === "done" ? "Analyse abgeschlossen" : "Analyse läuft"} +

+

+ {phase === "done" + ? "Alle Prüfschritte wurden ausgewertet. Der Bericht wird geöffnet." + : "Verfolgen Sie jeden Prüfschritt und seine Teilbewertung in Echtzeit."} +

+
+ + + +
+ + {phase === "done" ? ( + + ) : ( + + )} + Live-Risiko + +
+ + {runningScore} + + / 100 +
+
+ + +
+
+ Prüfschritte + + {completed}{totalChecks > 0 ? ` / ${totalChecks}` : ""} + +
+ +
+ + {aiActive && ( +
+ + KI-Analyse läuft – semantische Prüfung der Instruktionen... +
+ )} + {finalVerdict && ( +
+ Vorläufiges Ergebnis:{" "} + + {finalVerdict === "pass" + ? "Freigabe" + : finalVerdict === "review" + ? "Manuelle Prüfung" + : "Blockieren"} + +
+ )} + + + +
+ {groupedSteps.map((group) => ( + + + + {group.category} + + + + {group.steps.map((step) => ( +
+
+ + {step.label} + {step.axis && } + + {step.detectedBy === "ai" ? "KI" : "Statisch"} + +
+ 0 ? "text-rose-600 dark:text-rose-400" : "text-muted-foreground" + }`} + > + {deltaLabel(step)} + +
+ ))} + + + ))} + {groupedSteps.length === 0 && ( +
+ + Initialisiere Prüfung... +
+ )} +
+
+ ); + } + return (
@@ -99,9 +348,9 @@ export default function ScanForm() {
- setName(e.target.value)} /> @@ -113,7 +362,7 @@ export default function ScanForm() { ZIP-Archiv Text - +
@@ -126,9 +375,9 @@ export default function ScanForm() { -