151 lines
8 KiB
Markdown
151 lines
8 KiB
Markdown
# 05 — Data Pipeline
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> **Purpose:** Condensed reference for LLMs working on the vocabulary data pipeline. Covers the flow, what exists, and what is still unwritten. Full detail: `documentation/DATA_PIPELINE.md`, `documentation/pipeline/design-doc.md`, `documentation/pipeline/roadmap.md`.
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> **Last updated:** 2026-08-01
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> **Depends on:** 00-project-overview.md, 02-data-model.md
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---
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## Read this first
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The pipeline was **completely rewritten**. The old Kaikki/local-LLM architecture — six stages, `pipeline.db`, `stage-1-extract/`, `stage-3-enrich/`, multi-model CEFR voters, llama.cpp — is **gone from the codebase**. Any reference you see to those stages, directories, or the voter strategy is historical (`documentation/archive/`), not something you can call or modify.
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The current pipeline is Gemini-only, and most of it **is not written yet**. Do not assume a module exists because a doc names it.
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---
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## Pipeline Overview
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```
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source-data/{lang}/{pos} frequency wordlists, one word per line, UTF-8
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↓
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Gemini API batches of 20 words, one language at a time
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↓
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validation per entry; rejects go to a log, never to the DB
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↓
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db/staging.db SQLite staging (words, senses, translations)
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↓
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import script SQLite → PostgreSQL via Drizzle, transaction per batch
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↓
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PostgreSQL dev (:5432), then production
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```
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Each language is processed independently so that definitions and examples are written **in that language**. Only translations cross language boundaries.
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The app always reads PostgreSQL. SQLite is a staging file only, so re-runs and prompt tweaks never touch a real database.
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**Current state:** Phases 1–2 complete (schema, wordlists, databases, prompt). Phase 3 in progress — validation module, pipeline script, and first real run are all still to be written. Phases 4–7 not started.
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---
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## What exists in `data-pipeline/`
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| Path | State |
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| --------------------------- | ------------------------------------------------------------------ |
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| `source-data/{lang}/{pos}/` | ✅ Noun lists for `de`, `en`, `es`, `fr`, `it` |
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| `prompt` | ✅ Gemini system prompt — a plain UTF-8 text file, not a TS module |
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| `db/schema.sql` | ✅ SQLite staging schema |
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| `db/staging.db` | ✅ Tables created, **0 rows**, gitignored |
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| `pipeline.ts` | 🚧 Design pseudocode in comments only — no executable code |
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| validation module | ❌ Not written (rules in design-doc §6.4) |
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| SQLite → PostgreSQL import | ❌ Not written |
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| `kaikki-source-files/` | ⚠️ Leftover JSONL dumps; nothing reads them |
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| `worddata/english/nouns/` | ⚠️ Empty leftover output dir from the old per-word-JSON design |
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Directory names use the codes from `packages/shared/src/constants.ts` (`de/noun`, not `german/nouns`) so no mapping layer is needed.
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`data-pipeline/vitest.config.ts` looks for `tests/**/*.test.ts`; that directory does not exist yet.
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---
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## Gemini output contract
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The model returns a JSON array, one object per input word, in input order — no markdown fences, comments, or trailing commas.
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<!-- prettier-ignore -->
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```json
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[
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{
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"headword": "Haus",
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"language": "de",
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"pos": "noun",
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"senses": [
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{
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"sense_index": 0,
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"difficulty": "easy",
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"definitions": ["Ein Gebäude zum Wohnen."],
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"examples": ["Sie kauften ein Haus in der Stadt."],
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"translations": [
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{ "target_language": "en", "word": "house", "gender": null, "difficulty": "easy" },
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{ "target_language": "es", "word": "casa", "gender": "feminine", "difficulty": "easy" }
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]
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}
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]
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}
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]
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```
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Prompt rules that the output depends on:
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- Definitions and examples in the **source** language, not English.
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- Gender required for `de` (masculine/feminine/neuter) and `it`/`es`/`fr` (masculine/feminine); always `null` for `en`.
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- German nouns capitalized; Romance-language nouns lowercase unless proper nouns.
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- Base dictionary form, no articles or determiners.
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- 1–3 senses per word, most words 1; no rare, archaic, or technical senses.
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- Max 2 translations per target language per sense, only genuine synonyms or difficulty variants.
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- A translation's difficulty is never lower than its sense's difficulty.
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- A word that is not a valid noun in that language returns `"senses": []`.
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⚠️ The checked-in `prompt` file still has hardcoded English leftovers (rules 2, 3, and 31 say `"en"` / "English noun" while the header says Spanish) and its target-language list disagrees with its own header. It is also pinned to one sample batch rather than templated. Fix when implementing `pipeline.ts`.
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---
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## Validation rules (design-doc §6.4)
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Run per entry before anything is written to SQLite. Invalid entries go to a rejection log for review, not to the database. Target reject rate: under 10%.
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- `headword` non-empty; `language` in the 5 supported codes; `pos` in the 4 supported values
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- at least one sense; each sense has ≥1 definition, ≥1 example, ≥1 translation
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- `sense_index` a non-negative integer, starting at 0 and increasing by 1
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- `difficulty` in `easy | medium | hard` on both senses and translations
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- `target_language` supported and never equal to the word's own language
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- `gender` valid for the target language (see above); `null` for English
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- no duplicate (headword, language, pos, sense_index)
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---
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## Constants
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| Constant | Values | Source |
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| ---------- | ------------------------------------- | -------------------------- |
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| Languages | `en`, `it`, `de`, `es`, `fr` | `SUPPORTED_LANGUAGE_CODES` |
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| POS | `noun`, `verb`, `adjective`, `adverb` | `SUPPORTED_POS` |
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| Difficulty | `easy`, `medium`, `hard` | `DIFFICULTY_LEVELS` |
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| Gender | `masculine`, `feminine`, `neuter` | `NOUN_GENDERS` |
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All live in `packages/shared/src/constants.ts` and are CHECK-constrained in the PostgreSQL schema. Adding a value means updating the constant **and** a Drizzle migration before re-running the pipeline.
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CEFR levels still exist as a constant and as columns on the old `vocabulary_entries` tables, but the new pipeline does not produce them — it produces the three-level difficulty directly. The prompt calibrates difficulty against CEFR bands internally (easy ≈ A1/A2, medium ≈ B1/B2, hard ≈ C1/C2) but is explicitly told not to emit CEFR levels.
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---
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## Running it
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```bash
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docker compose up -d pipeline-database # dedicated PostgreSQL on :5433
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pnpm --filter @lila/pipeline pipeline:run # tsx --env-file .env pipeline.ts (currently a no-op)
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pnpm --filter @lila/pipeline test
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```
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Env vars come from the repo-root `.env`: `GEMINI_API_KEY`, `PIPELINE_POSTGRES_USER`, `PIPELINE_POSTGRES_PASSWORD`, `PIPELINE_POSTGRES_DB`, `PIPELINE_DATABASE_URL`. The pipeline database is deliberately separate from the app database (`:5432`).
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Implementation notes from the roadmap: `better-sqlite3` for staging (synchronous), `crypto.randomUUID()` for ids, `JSON.stringify` for the definitions/examples arrays (SQLite has no array type — the import script parses them back into PostgreSQL `text[]`), batches of 20 with a 1s sleep between calls.
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---
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## Current Blockers
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1. **Validation module and `pipeline.ts` are unwritten** — this is Phase 3, the active work.
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2. **Prompt is not templated** — source language, POS, target languages, and the word batch are hardcoded for one sample run.
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3. **No import script** — nothing moves staging rows into PostgreSQL yet (Phase 4).
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4. **App still reads the old schema** — `termModel.ts` queries `vocabulary_entries`/`entry_translations`. Until Phase 5 rewrites it, pipeline output is invisible to the app.
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