Implements Phases 1-8 of the TFTSR implementation plan. Rust backend (Tauri 2.x, src-tauri/): - Multi-provider AI: OpenAI-compatible, Anthropic, Gemini, Mistral, Ollama - PII detection engine: 11 regex patterns with overlap resolution - SQLCipher AES-256 encrypted database with 10 versioned migrations - 28 Tauri IPC commands for triage, analysis, document, and system ops - Ollama: hardware probe, model recommendations, pull/delete with events - RCA and blameless post-mortem Markdown document generators - PDF export via printpdf - Audit log: SHA-256 hash of every external data send - Integration stubs for Confluence, ServiceNow, Azure DevOps (v0.2) Frontend (React 18 + TypeScript + Vite, src/): - 9 pages: full triage workflow NewIssue→LogUpload→Triage→Resolution→RCA→Postmortem→History+Settings - 7 components: ChatWindow, TriageProgress, PiiDiffViewer, DocEditor, HardwareReport, ModelSelector, UI primitives - 3 Zustand stores: session, settings (persisted), history - Type-safe tauriCommands.ts matching Rust backend types exactly - 8 IT domain system prompts (Linux, Windows, Network, K8s, DB, Virt, HW, Obs) DevOps: - .woodpecker/test.yml: rustfmt, clippy, cargo test, tsc, vitest on every push - .woodpecker/release.yml: linux/amd64 + linux/arm64 builds, Gogs release upload Verified: - cargo check: zero errors - tsc --noEmit: zero errors - vitest run: 13/13 unit tests passing Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
90 lines
2.6 KiB
JavaScript
90 lines
2.6 KiB
JavaScript
"use strict";Object.defineProperty(exports, "__esModule", {value: true});var _genmapping = require('@jridgewell/gen-mapping');
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var _charcodes = require('./parser/util/charcodes');
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/**
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* Generate a source map indicating that each line maps directly to the original line,
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* with the tokens in their new positions.
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*/
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function computeSourceMap(
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{code: generatedCode, mappings: rawMappings},
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filePath,
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options,
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source,
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tokens,
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) {
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const sourceColumns = computeSourceColumns(source, tokens);
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const map = new (0, _genmapping.GenMapping)({file: options.compiledFilename});
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let tokenIndex = 0;
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// currentMapping is the output source index for the current input token being
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// considered.
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let currentMapping = rawMappings[0];
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while (currentMapping === undefined && tokenIndex < rawMappings.length - 1) {
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tokenIndex++;
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currentMapping = rawMappings[tokenIndex];
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}
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let line = 0;
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let lineStart = 0;
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if (currentMapping !== lineStart) {
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_genmapping.maybeAddSegment.call(void 0, map, line, 0, filePath, line, 0);
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}
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for (let i = 0; i < generatedCode.length; i++) {
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if (i === currentMapping) {
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const genColumn = currentMapping - lineStart;
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const sourceColumn = sourceColumns[tokenIndex];
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_genmapping.maybeAddSegment.call(void 0, map, line, genColumn, filePath, line, sourceColumn);
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while (
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(currentMapping === i || currentMapping === undefined) &&
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tokenIndex < rawMappings.length - 1
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) {
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tokenIndex++;
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currentMapping = rawMappings[tokenIndex];
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}
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}
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if (generatedCode.charCodeAt(i) === _charcodes.charCodes.lineFeed) {
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line++;
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lineStart = i + 1;
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if (currentMapping !== lineStart) {
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_genmapping.maybeAddSegment.call(void 0, map, line, 0, filePath, line, 0);
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}
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}
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}
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const {sourceRoot, sourcesContent, ...sourceMap} = _genmapping.toEncodedMap.call(void 0, map);
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return sourceMap ;
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} exports.default = computeSourceMap;
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/**
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* Create an array mapping each token index to the 0-based column of the start
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* position of the token.
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*/
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function computeSourceColumns(code, tokens) {
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const sourceColumns = new Array(tokens.length);
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let tokenIndex = 0;
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let currentMapping = tokens[tokenIndex].start;
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let lineStart = 0;
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for (let i = 0; i < code.length; i++) {
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if (i === currentMapping) {
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sourceColumns[tokenIndex] = currentMapping - lineStart;
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tokenIndex++;
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currentMapping = tokens[tokenIndex].start;
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}
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if (code.charCodeAt(i) === _charcodes.charCodes.lineFeed) {
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lineStart = i + 1;
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}
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}
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return sourceColumns;
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}
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