[INIT] innitial Poc of the concept for ql creation fron NL
This commit is contained in:
Eliyan
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node_modules/
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dist/
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.env
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.vscode/
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package-lock.json
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README.md
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README.md
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# ODMDB Natural Language Query PoC
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This is a **Proof of Concept (PoC)** that demonstrates the conversion of natural language queries into ODMDB search queries using OpenAI's structured output API.
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## Current Status
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⚠️ **Partial Implementation**: Currently only the **seekers** object mapping is implemented. This PoC focuses on demonstrating the natural language to DSL query conversion for seeker-related searches.
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## Features
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- Converts natural language requests into ODMDB DSL queries
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- Handles temporal queries ("new seekers since last week")
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- Maps human-readable field names to schema fields
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- Validates output using Zod schema validation
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- Uses OpenAI's structured output for reliable JSON generation
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## Prerequisites
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- Node.js (v16 or higher)
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- OpenAI API key
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## Installation
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1. Install dependencies:
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```bash
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npm install
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```
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2. Set your OpenAI API key:
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```bash
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export OPENAI_API_KEY=sk-your-api-key-here
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```
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## Usage
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### Running the PoC
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```bash
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npm start
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```
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This will process the hardcoded natural language query and output the generated ODMDB query in JSON format.
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### Changing the Query
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To test different natural language queries, edit the `NL_QUERY` constant in `poc.js`:
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```javascript
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// Line 16 in poc.js
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const NL_QUERY = "your natural language query here";
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```
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### Example Queries
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- `"give me new seekers since last week with email and experience"`
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- `"find recent seekers with job titles and salary expectations"`
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- `"show me seekers from yesterday with their skills"`
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## Output Format
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The PoC generates ODMDB queries in this format:
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```json
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{
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"object": "seekers",
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"condition": [
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"prop.dt_create(>=:2025-10-06)"
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],
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"fields": [
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"alias",
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"email",
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"seekworkingyear"
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]
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}
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```
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## ODMDB DSL Support
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The PoC understands and generates these ODMDB DSL patterns:
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- **Property queries**: `prop.<field>(operator:value)`
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- **Index queries**: `idx.<indexName>(value)`
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- **Join queries**: `join(remoteObject:localKey:remoteProp:operator:value)`
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## Field Mappings
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Currently supports mapping for seekers object:
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- `email` → `email`
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- `experience` → `seekworkingyear`
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- `job titles` → `seekjobtitleexperience`
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- `status` → `seekstatus`
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## Schema Context
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The PoC can optionally load schema files for context:
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- `main.json` - Combined schema definitions
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- `lg.json` - Localization/language mappings
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## Limitations
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- **Seekers only**: Other ODMDB objects (jobads, recruiters, etc.) are not yet implemented
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- **No execution**: Only generates queries, doesn't execute them against ODMDB
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- **Hardcoded query**: Single query per run (no interactive mode)
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- **Basic validation**: Limited DSL syntax validation
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## Next Steps
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- [ ] Add support for other ODMDB objects (jobads, recruiters, etc.)
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- [ ] Interactive CLI for multiple queries
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- [ ] Integration with actual ODMDB backend
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- [ ] Enhanced field mapping and validation
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- [ ] Multi-turn conversation support
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## Files
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- `poc.js` - Main PoC implementation
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- `package.json` - Dependencies and scripts
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- `main.json` - Optional schema context (if available)
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- `lg.json` - Optional localization context (if available)
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281
lg.json
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lg.json
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[
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{
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"comment": "lg/hobbies_fr.json"
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},
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{
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"Lecture": [
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"Roman",
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"Science-fiction",
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"Policier",
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"Biographie",
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"Essai",
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"Poésie",
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"Magazine",
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"Bandes dessinées"
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],
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"Jardinage": [
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"Potager",
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"Fleurs",
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"Aménagement paysager",
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"Bonsaï",
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"Jardinage urbain",
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"Jardins d'intérieur"
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],
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"Cuisine": [
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"Pâtisserie",
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"Cuisine internationale",
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"Cuisine végétarienne",
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"Cuisine fusion",
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"Cuisine moléculaire",
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"Cuisine de rue",
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"Confitures et conserves"
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],
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"Photographie": [
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"Paysages",
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"Portraits",
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"Macro",
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"Photographie de rue",
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"Photographie animalière",
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"Photographie de mode",
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"Photographie de mariage"
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],
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"Peinture": [
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"Acrylique",
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"Huile",
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"Aquarelle",
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"Pastel",
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"Peinture sur verre",
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"Peinture sur toile",
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"Peinture abstraite"
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],
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"Randonnée": [
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"Randonnée en montagne",
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"Randonnée pédestre",
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"Randonnée en forêt",
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"Randonnée côtière",
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"Randonnée en groupe",
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"Randonnée nocturne"
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],
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"Musique": [
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"Jouer d'un instrument",
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"Chant",
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"Composition",
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"Musique classique",
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"Musique rock",
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"Musique jazz",
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"Musique électronique"
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],
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"Danse": [
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"Salsa",
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"Bachata",
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"Tango",
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"Hip-hop",
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"Danse contemporaine",
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"Danse de salon",
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"Danse orientale"
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],
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"Écriture": [
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"Roman",
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"Nouvelle",
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"Poésie",
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"Scénario",
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"Blog",
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"Journal intime",
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"Lettres"
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],
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"Bricolage": [
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"Menuiserie",
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"Électricité",
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"Plomberie",
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"Décoration",
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"Peinture",
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"Couture",
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"Restauration de meubles"
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],
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"Jeux de société": [
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"Jeu de cartes",
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"Jeu de plateau",
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"Jeu de rôle",
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"Jeu de stratégie",
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"Jeu de dés",
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"Jeu de société coopératif",
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"Jeu de société d'ambiance"
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],
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"Sports": [
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"Football",
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"Basketball",
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"Tennis",
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"Natation",
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"Course à pied",
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"Yoga",
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"Cyclisme"
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],
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"Voyages": [
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"Voyages en Europe",
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"Voyages en Asie",
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"Voyages en Amérique",
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"Voyages en Afrique",
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"Voyages en Océanie",
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"Voyages d'aventure",
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"Voyages culturels"
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],
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"Collection de timbres": [
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"Timbres classiques",
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"Timbres thématiques",
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"Timbres rares",
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"Timbres du monde",
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"Timbres oblitérés",
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"Timbres neufs",
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"Timbres anciens"
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],
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"Couture": [
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"Vêtements",
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"Accessoires",
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"Patchwork",
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"Couture pour enfants",
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"Broderie",
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"Travail du cuir",
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"Customisation"
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],
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"Tricot": [
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"Écharpes",
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"Pulls",
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"Chaussettes",
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"Bonnet",
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"Gants",
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"Couvertures",
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"Peluches"
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],
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"Modélisme": [
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"Modélisme ferroviaire",
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"Modélisme naval",
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"Modélisme aérien",
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"Modélisme automobile",
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"Modélisme architectural",
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"Modélisme spatial",
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"Modélisme militaire"
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],
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"Jeu d'échecs": [
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"Parties classiques",
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"Parties rapides",
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"Variantes",
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"Études",
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"Problèmes d'échecs",
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"Compétitions",
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"Analyse de parties"
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],
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"Sculpture": [
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"Argile",
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"Pierre",
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"Bois",
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"Métal",
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"Verre",
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"Céramique",
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"Sculpture sur glace"
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],
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"Camping": [
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"Camping en tente",
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"Camping-car",
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"Randonnée avec camping",
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"Feu de camp",
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"Cuisine en plein air",
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"Observation des étoiles",
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"Activités de plein air"
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]
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},
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{
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"comment": "lg/persons_fr.json"
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},
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{
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"title": "Une Personne au niveau d'une tribut avec des informations personnelles",
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"description": "Un alias peut se stocker comme un objet Person avec des informations supplémentaires permettant de qualifier son profil",
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"properties": {
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"alias": {
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"title": "Une identité numérique d'apxtri"
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},
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"owner": {
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"title": "Le propriétaire de cet objet (celui qui posséde la clé)"
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},
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"dt_create": {
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"title": "Date de creation"
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},
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"dt_update": {
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"title": "Date de mise à jour"
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},
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"dt_lastlogin": {
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"title": "Date de derniere authentification"
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},
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"dt_delete": {
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"title": "Date de fermeture du compte"
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},
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"will": {
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"title": "Nom du script à lancer lors d'une fermeture de compte"
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},
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"recoveryauth": {
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"title": "Information pour recuperer ses codes d'accès",
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"description": "Cette objet garde votre identité numérique, en vue d'une demande de recuperation par email.",
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"properties": {
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"email": {
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"title": "email de recuperation"
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},
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"privatekey": {
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"title": "La cle privée associé à l'alias"
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},
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"passphrase": {
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"title": "La passphrase eventuelle"
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}
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}
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},
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"firstname": {
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"title": "Votre prenom",
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"description": "Ce prénom s'affichera pour les memebres de smatchit"
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},
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"lastname": {
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"title": "Votre nom de famille",
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"description": "Ce nom s'affichera pour les membres de smatchit"
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},
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"termandcondition": {
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"title": "J'accepte les conditions d'utilisation de smatchit",
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"description": "Conditions générales d'utilisation et de ventes de Smatchit"
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},
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"truthfullinformation": {
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"title": "I certify all my information",
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"description": "I certify all my information is truthful"
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},
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"contactfromschool": {
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"title": "J'accepte de recevoir des offres de formations de nos partenaires",
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"description": "Nous pouvons vous recommander des formations coorespondant à votre profil"
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},
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"dt_birth": {
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"title": "Votre date anniversaire",
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"description": "Date de naissance"
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},
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"pronom": {
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"title": "Pronom",
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"description": "La façon dont on doit s'adresser à votre personne"
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},
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"emailcom": {
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"title": "L'email de communication",
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"description": "Cet email sera utilisé pour communiqué avec les membres de smatchot"
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},
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"hobbies": {
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"title": "Mes hobbies"
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},
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"biography": {
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"title": "Quelques mots sur moi",
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"description": "Ce texte sera partagé pour tous les membres de smatchit, recruteur et chercheur d'emploi"
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},
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"mbti": {
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"title": "Mon profil mbti en tant que personne"
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},
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"imgavatar": {
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"title": "Une image public qui me represente",
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"description": "Image qui en dit long sur ma personnalité, attention elle est public"
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},
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"profils": {
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"title": "Liste de mes profils",
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"description": "Chaque profils donne des droits particulier à chaque personne sur les objet de smatchit"
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}
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}
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}
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]
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13
package.json
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package.json
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{
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"name": "nl2odmdb-poc",
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"version": "0.1.0",
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"type": "module",
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"private": true,
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"scripts": {
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"start": "node poc.js"
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},
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"dependencies": {
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"openai": "^4.60.0",
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"zod": "^3.23.8"
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}
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}
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159
poc.js
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poc.js
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// PoC: NL → ODMDB query (seekers)
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// Usage:
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// 1) export OPENAI_API_KEY=sk-...
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// 2) node poc.js
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import fs from "node:fs";
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import OpenAI from "openai";
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import { z } from "zod";
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// ---- Config ----
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const MODEL = process.env.OPENAI_MODEL || "gpt-5";
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const MAIN_SCHEMA_PATH = "./main.json"; // optional context; safe if missing
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const LG_SCHEMA_PATH = "./lg.json"; // optional context; safe if missing
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// Hardcoded NL query for the PoC (no multi-turn)
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const NL_QUERY =
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"give me new seekers since last week with email and experience";
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// ---- Load schemas if present (not required for output) ----
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function loadJsonSafe(path) {
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try {
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if (fs.existsSync(path)) {
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return JSON.parse(fs.readFileSync(path, "utf-8"));
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}
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} catch {}
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return null;
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}
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const SCHEMAS = {
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main: loadJsonSafe(MAIN_SCHEMA_PATH),
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lg: loadJsonSafe(LG_SCHEMA_PATH),
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};
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// ---- Seekers mapping (from our agreement) ----
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const seekersMapping = {
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object: "seekers",
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readableFieldsForRecruiters: [
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"alias",
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"email",
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"seekstatus",
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"seekworkingyear",
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"seekjobtitleexperience",
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],
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};
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// ---- Output contract (strict) ----
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const OdmdbQueryZ = z.object({
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object: z.literal("seekers"),
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condition: z.array(z.string()),
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fields: z.array(z.string()), // always an array
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});
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// JSON Schema for Structured Output
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const RESPONSE_JSON_SCHEMA = {
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type: "object",
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additionalProperties: false,
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properties: {
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object: { type: "string", enum: ["seekers"] },
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condition: { type: "array", items: { type: "string" } },
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fields: { type: "array", items: { type: "string" }, minItems: 1 },
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},
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required: ["object", "condition", "fields"],
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};
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// ---- Prompt builders ----
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||||
function systemPrompt() {
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return [
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"You convert a natural language request into an ODMDB search payload.",
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||||
"Return ONLY a compact JSON object that matches the provided JSON Schema. The 'fields' property MUST be an array of strings.",
|
||||
"",
|
||||
"ODMDB DSL:",
|
||||
"- join(remoteObject:localKey:remoteProp:operator:value)",
|
||||
"- idx.<indexName>(value)",
|
||||
"- prop.<field>(operator:value) with dates or scalars.",
|
||||
"",
|
||||
"Rules:",
|
||||
"- Object must be 'seekers'.",
|
||||
"- For 'new'/'recent' recency, map to prop.dt_create with a resolved absolute date.",
|
||||
"- For 'experience', map to seekworkingyear.",
|
||||
"- Prefer recruiter-readable fields if a small set is requested. If the request is generic, return this default shortlist:",
|
||||
seekersMapping.readableFieldsForRecruiters.join(", "),
|
||||
"",
|
||||
"Timezone is Europe/Paris. Today is 2025-10-13.",
|
||||
"Interpret 'last week' as now minus 7 days → 2025-10-06.",
|
||||
"",
|
||||
"Schemas (context only, may be null):",
|
||||
JSON.stringify(SCHEMAS, null, 2),
|
||||
].join("\n");
|
||||
}
|
||||
function userPrompt(nl) {
|
||||
return `Natural language request: "${nl}"\nReturn ONLY the JSON object.`;
|
||||
}
|
||||
|
||||
// ---- OpenAI call using Responses API (text.format) ----
|
||||
const client = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
|
||||
|
||||
async function inferQuery(nlText) {
|
||||
const resp = await client.responses.create({
|
||||
model: MODEL,
|
||||
input: [
|
||||
{ role: "system", content: systemPrompt() },
|
||||
{ role: "user", content: userPrompt(nlText) },
|
||||
],
|
||||
text: {
|
||||
// <= new location for structured output format
|
||||
format: {
|
||||
name: "OdmdbQuery",
|
||||
type: "json_schema",
|
||||
schema: RESPONSE_JSON_SCHEMA,
|
||||
strict: true,
|
||||
},
|
||||
},
|
||||
});
|
||||
|
||||
const jsonText =
|
||||
resp.output_text ||
|
||||
resp.output?.[0]?.content?.[0]?.text ||
|
||||
(() => {
|
||||
throw new Error("Empty model output");
|
||||
})();
|
||||
|
||||
const parsed = JSON.parse(jsonText);
|
||||
const validated = OdmdbQueryZ.parse(parsed);
|
||||
|
||||
// Light safety check on DSL tokens
|
||||
const allowed = ["join(", "idx.", "prop."];
|
||||
for (const c of validated.condition) {
|
||||
const ok = allowed.some((t) => c.includes(t));
|
||||
const ascii = /^[\x09\x0A\x0D\x20-\x7E()_:\[\].,=><!'"-]+$/.test(c);
|
||||
if (!ok || !ascii) throw new Error(`Malformed condition: ${c}`);
|
||||
}
|
||||
return validated;
|
||||
}
|
||||
|
||||
// ---- Run PoC (print only the created query; do not execute) ----
|
||||
(async () => {
|
||||
try {
|
||||
if (!process.env.OPENAI_API_KEY) {
|
||||
throw new Error("Missing OPENAI_API_KEY env var.");
|
||||
}
|
||||
|
||||
const out = await inferQuery(NL_QUERY);
|
||||
|
||||
// Just output the created query (no execution)
|
||||
console.log(
|
||||
JSON.stringify(
|
||||
{
|
||||
object: out.object,
|
||||
condition: out.condition,
|
||||
fields: out.fields,
|
||||
},
|
||||
null,
|
||||
2
|
||||
)
|
||||
);
|
||||
} catch (e) {
|
||||
console.error("PoC failed:", e.message || e);
|
||||
process.exit(1);
|
||||
}
|
||||
})();
|
||||
Reference in New Issue
Block a user