8839075805
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>
46 lines
1.5 KiB
TypeScript
46 lines
1.5 KiB
TypeScript
/**
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* Create a tokenizer.
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* Tokenizers deal with one type of data (e.g., containers, flow, text).
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* The parser is the object dealing with it all.
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* `initialize` works like other constructs, except that only its `tokenize`
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* function is used, in which case it doesn’t receive an `ok` or `nok`.
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* `from` can be given to set the point before the first character, although
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* when further lines are indented, they must be set with `defineSkip`.
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*
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* @param {ParseContext} parser
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* Parser.
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* @param {InitialConstruct} initialize
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* Construct.
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* @param {Omit<Point, '_bufferIndex' | '_index'> | undefined} [from]
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* Point (optional).
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* @returns {TokenizeContext}
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* Context.
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*/
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export function createTokenizer(parser: ParseContext, initialize: InitialConstruct, from?: Omit<Point, "_bufferIndex" | "_index"> | undefined): TokenizeContext;
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/**
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* Restore the state.
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*/
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export type Restore = () => undefined;
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/**
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* Info.
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*/
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export type Info = {
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/**
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* Restore.
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*/
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restore: Restore;
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/**
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* From.
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*/
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from: number;
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};
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/**
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* Handle a successful run.
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*/
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export type ReturnHandle = (construct: Construct, info: Info) => undefined;
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import type { ParseContext } from 'micromark-util-types';
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import type { InitialConstruct } from 'micromark-util-types';
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import type { Point } from 'micromark-util-types';
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import type { TokenizeContext } from 'micromark-util-types';
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import type { Construct } from 'micromark-util-types';
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//# sourceMappingURL=create-tokenizer.d.ts.map
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