feat: Enhance ODMDB query handling with multi-schema support and intelligent routing
- Updated `poc.js` to support queries for multiple object types (seekers, jobads, recruiters, etc.) with intelligent routing based on natural language input. - Implemented a query validation mechanism to prevent excessive or sensitive requests. - Introduced a mapping manager for dynamic schema handling and object detection. - Enhanced the response schema generation to accommodate various object types and their respective fields. - Added a new script `verify-mapping.js` to verify and display the mapping details for the seekers schema, including available properties, indexes, access rights, and synonyms.
This commit is contained in:
Eliyan
371
README.md
371
README.md
@@ -4,17 +4,19 @@ This is a **Proof of Concept (PoC)** that demonstrates the conversion of natural
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## Current Status
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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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✅ **Complete Multi-Schema Implementation**: Supports **all ODMDB object types** including seekers, jobads, recruiters, persons, and sirets. The system intelligently detects the target object from natural language queries and generates appropriate ODMDB DSL queries.
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## Features
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## Features
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- **Natural Language Processing**: Converts human questions into structured ODMDB queries
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- **Multi-Object Natural Language Processing**: Intelligently detects target object (seekers, jobads, recruiters, persons, sirets) from natural language queries
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- **Real ODMDB Integration**: Works with actual ODMDB data from `../smatchitObjectOdmdb/`
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- **Real ODMDB Schema Integration**: Dynamically loads actual schema files for all object types with verified accuracy
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- **Schema-Based Mapping**: Uses actual seekers.json schema for accurate field mapping (62 properties)
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- **Comprehensive Field Mapping**: Uses real schema definitions with proper access rights for recruiter-readable fields
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- **Local Data Execution**: Processes queries against local seeker files in `objects/seekers/itm/`
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- **Index-Aware Query Generation**: Leverages actual ODMDB indexes for optimal query performance
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- **OpenAI Structured Output**: Ensures reliable JSON query generation
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- **Schema Mapping Manager**: Centralized system reading real schema files and generating comprehensive field synonyms
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- **Query Validation**: Validates generated queries against real ODMDB schema rules
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- **Multi-Object Query Support**: Handles queries across all ODMDB object types with object-specific optimizations
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- **jq Integration**: Powerful result processing, filtering, and CSV export capabilities
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- **OpenAI Structured Output**: Dynamic JSON schema generation for any target object type
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- **Real Data Validation**: Verified against actual ODMDB schema properties and index registers
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- **Prepared Query Demos**: Ready-to-use example queries for all supported object types
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## Prerequisites
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## Prerequisites
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@@ -23,15 +25,31 @@ This is a **Proof of Concept (PoC)** that demonstrates the conversion of natural
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## Installation
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## Installation
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1. Make sure you have the ODMDB data structure available:
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1. Make sure you have the complete ODMDB data structure available:
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```
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```
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../smatchitObjectOdmdb/
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../smatchitObjectOdmdb/
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├── schema/
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├── schema/
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│ └── seekers.json # Seeker schema (62 properties)
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│ ├── seekers.json # Seeker schema (62 properties, 27 readable fields)
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│ ├── jobads.json # Job advertisement schema
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│ ├── recruiters.json # Recruiter schema
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│ ├── persons.json # Person schema
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│ ├── sirets.json # Company/Siret schema
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│ └── *.json # Additional schema files
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└── objects/
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└── objects/
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└── seekers/
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├── seekers/
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└── itm/ # Individual seeker JSON files
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│ ├── idx/ # Index files (lst_alias, seekstatus_alias, etc.)
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│ └── itm/ # Individual seeker JSON files
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├── jobads/
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│ ├── idx/ # Job ad indexes
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│ └── itm/ # Job ad data files
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├── recruiters/
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│ ├── idx/ # Recruiter indexes
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│ └── itm/ # Recruiter data files
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├── persons/
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│ └── itm/ # Person data files
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└── sirets/
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└── itm/ # Company data files
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```
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```
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2. Install dependencies:
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2. Install dependencies:
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@@ -49,20 +67,26 @@ This is a **Proof of Concept (PoC)** that demonstrates the conversion of natural
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### Running the PoC
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### Running the PoC
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**Query Generation Only (Default):**
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**Interactive Demo (Recommended):**
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```bash
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node demo.js
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```
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This runs the comprehensive demo with prepared queries for all object types and shows real-time query generation.
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**Main PoC (Query Generation Only):**
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```bash
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```bash
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npm start
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npm start
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```
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```
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**Query Generation + Execution:**
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**Main PoC with Query Execution:**
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```bash
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```bash
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EXECUTE_QUERY=true npm start
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EXECUTE_QUERY=true npm start
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```
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```
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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. When `EXECUTE_QUERY=true`, it will also execute the query against the ODMDB server.
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This will process the hardcoded natural language query and output the generated ODMDB query in JSON format. When `EXECUTE_QUERY=true`, it will also execute the query against the ODMDB server.
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### Changing the Query
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### Changing the Query
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@@ -72,9 +96,13 @@ To test different natural language queries, edit the `NL_QUERY` constant in `poc
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```javascript
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```javascript
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// Line 16 in poc.js
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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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const NL_QUERY = "your natural language query here";
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````
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```
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### Example Queries
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The system will automatically detect which object type you're asking about and generate the appropriate query.
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### Example Queries by Object Type
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#### Seekers (Job Seekers)
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**Status-based queries:**
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**Status-based queries:**
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@@ -82,19 +110,11 @@ const NL_QUERY = "your natural language query here";
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- `"find seekers looking for jobs urgently with their skills and salary expectations"`
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- `"find seekers looking for jobs urgently with their skills and salary expectations"`
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- `"get seekers who are not looking with their employment status"`
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- `"get seekers who are not looking with their employment status"`
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**Date-based queries:**
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**Skills & experience:**
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- `"give me new seekers since last week with email and experience"`
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- `"find seekers with technical skills and years of experience"`
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- `"show me seekers from yesterday with their location and availability"`
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- `"show me seekers with language abilities and personality profiles"`
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- `"find recently updated seekers with their job preferences"`
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- `"get seekers with specific know-how and job radar interests"`
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**Comprehensive field queries:**
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- `"show me seeker contact info and work experience"`
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- `"find seekers with personality types and language skills"`
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- `"get seeker salary expectations and preferred working hours"`
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- `"show me seeker education and training preferences"`
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- `"find seekers with their job applications and saved jobs"`
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**Location & preferences:**
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**Location & preferences:**
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@@ -102,77 +122,119 @@ const NL_QUERY = "your natural language query here";
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- `"find seekers available to work in multiple countries"`
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- `"find seekers available to work in multiple countries"`
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- `"get seekers with specific location and salary requirements"`
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- `"get seekers with specific location and salary requirements"`
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**Skills & competencies:**
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#### Job Ads
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- `"find seekers with technical skills and years of experience"`
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**Job search queries:**
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- `"show me seekers with language abilities and personality profiles"`
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- `"get seekers with specific know-how and job radar interests"`
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**Job search activity:**
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- `"show me recent job postings in technology"`
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- `"find job ads with high salary ranges"`
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- `"get job advertisements posted this week"`
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- `"show me seekers who applied to jobs recently"`
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**Company & location:**
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- `"find seekers with saved jobs and their preferences"`
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- `"get seekers who were invited to apply with their status"`
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**Notifications & communication:**
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- `"show me jobs at specific companies"`
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- `"find remote job opportunities"`
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- `"get job ads in Paris or Lyon"`
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- `"show me seekers with email preferences and notification settings"`
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#### Recruiters
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- `"find seekers who receive weekly reports and interview tips"`
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**Supported filter types:**
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**Recruiter information:**
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- **Status filtering**: `seekstatus` (startasap, norush, notlooking)
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- `"show me active recruiters and their specializations"`
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- **Date filtering**: `dt_create`, `dt_update`, `matchinglastdate` with date ranges
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- `"find recruiters from specific companies"`
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- **Index optimization**: Uses ODMDB indexes (`lst_alias`, `seekstatus_alias`) for efficient queries
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- `"get recruiter contact information and experience"`
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### Demo & Testing Tools
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#### Persons
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**Interactive Demo:**
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**General person queries:**
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```bash
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- `"show me person profiles with their roles"`
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node demo.js
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- `"find persons by their experience or background"`
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```
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**Live PoC demonstration** that actually uses the query generation functionality to show:
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#### Companies (Sirets)
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- Real query generation from natural language using OpenAI
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**Company information:**
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- ODMDB schema loading and field mapping
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- Current ODMDB data status and sample data
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**Demo with Query Execution:**
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- `"show me companies in the technology sector"`
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- `"find companies by size or location"`
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- `"get company details and contact information"`
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```bash
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### Supported Query Types
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EXECUTE_DEMO=true node demo.js
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```
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Runs the demo with actual query execution against real seeker data files.
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**Multi-Object Intelligence:**
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The system automatically detects which object you're asking about:
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**jq Playground:**
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- Mentions of "seekers", "candidates", "job seekers" → seekers object
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- Mentions of "jobs", "positions", "job ads" → jobads object
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- Mentions of "recruiters", "hiring managers" → recruiters object
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- Mentions of "persons", "people", "profiles" → persons object
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- Mentions of "companies", "employers", "organizations" → sirets object
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```bash
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**Filter Types:**
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node experiment-jq-playground.js
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```
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A playground to experiment with jq commands - not vital to the PoC but useful for learning jq syntax.
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- **Status filtering**: Object-specific status fields
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- **Date filtering**: Creation dates, update dates with date ranges
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- **Index optimization**: Uses real ODMDB indexes for efficient queries
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- **Field-specific**: Searches within specific properties
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Demonstrates various jq operations including:
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## Schema Mapping System
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- Basic data formatting and field selection
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The PoC uses a sophisticated schema mapping system located in `schema-mappings/`:
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- CSV conversion from JSON
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- Advanced filtering and transformations
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- Statistical summaries and aggregations
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## Environment Variables
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### Architecture
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- `OPENAI_API_KEY` - Your OpenAI API key (required)
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- **ODMDBMappingManager**: Central manager that loads and caches schema mappings
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- `EXECUTE_QUERY` - Set to "true" to execute queries against ODMDB (default: false)
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- **Base Mapping**: Core field synonym generation and mapping logic
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- `ODMDB_BASE_URL` - ODMDB server URL (default: http://localhost:3000)
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- **Object-Specific Mappings**: Individual mapping files for each object type
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- `ODMDB_TRIBE` - ODMDB tribe name (default: smatchit)
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- **Real Schema Integration**: Direct reading from actual ODMDB schema files
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- `OPENAI_MODEL` - OpenAI model to use (default: gpt-5)
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### Verified Schema Coverage
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**Seekers Object:**
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- 62 total schema properties mapped
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- 27 recruiter-readable fields identified
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- 3 indexes available (lst_alias, seekstatus_alias, alias)
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- 206+ field synonyms generated from real schema definitions
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**All Objects:**
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- Dynamic schema loading for any ODMDB object type
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- Access rights properly extracted from apxaccessrights structure
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- Index definitions read from actual idx directories
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- Field synonyms generated from real property definitions
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### Field Mapping Examples
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The system provides comprehensive natural language to field mappings:
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**Contact & Identity:**
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- `email`, `contact`, `mail` → `email`
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- `id`, `username`, `alias` → `alias`
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- `bio`, `description`, `summary` → `shortdescription`
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**Work Experience & Status:**
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- `experience`, `years of experience`, `career length` → `seekworkingyear`
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- `job titles`, `positions`, `roles`, `work history` → `seekjobtitleexperience`
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- `status`, `availability`, `urgency` → `seekstatus`
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**Location & Geography:**
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- `location`, `where`, `work location` → `seeklocation`
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- `countries`, `work countries` → `countryavailabletowork`
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**Skills & Competencies:**
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- `skills`, `competencies`, `abilities` → `skills`
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- `languages`, `language skills` → `languageskills`
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- `knowledge`, `expertise`, `know-how` → `knowhow`
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_(Plus hundreds more mappings for all object types)_
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## Output Format
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## Output Format
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**Query Generation:**
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The PoC generates ODMDB queries in this format:
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The PoC generates ODMDB queries in this format:
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```json
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```json
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@@ -191,104 +253,127 @@ The PoC understands and generates these ODMDB DSL patterns:
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- **Index queries**: `idx.<indexName>(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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- **Join queries**: `join(remoteObject:localKey:remoteProp:operator:value)`
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## Comprehensive Field Mappings
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## Demo & Testing Tools
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Supports extensive natural language mapping for **all 62 seeker properties**:
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**Interactive Demo:**
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**Contact & Identity:**
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```bash
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node demo.js
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```
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- `email`, `contact`, `mail` → `email`
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**Live PoC demonstration** featuring:
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- `id`, `username`, `alias` → `alias`
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- `bio`, `description`, `summary` → `shortdescription`
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**Work Experience & Status:**
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- Real query generation from natural language using OpenAI
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- Multi-object detection and schema loading
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- Prepared queries for all supported object types
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- Real-time field mapping and validation
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- Current ODMDB data status display
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- `experience`, `years of experience`, `career length` → `seekworkingyear`
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**Demo Features:**
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- `job titles`, `positions`, `roles`, `work history` → `seekjobtitleexperience`
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- `status`, `availability`, `urgency` → `seekstatus`
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- `employment`, `work status`, `job status` → `employmentstatus`
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**Location & Geography:**
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- **Prepared Queries**: 4 example queries per object type (20 total)
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- **Schema Validation**: Shows actual field counts and mappings
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- **Real-time Generation**: Demonstrates actual OpenAI API integration
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- **Multi-Object Support**: Covers seekers, jobads, recruiters, persons, sirets
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- `location`, `where`, `work location` → `seeklocation`
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## Environment Variables
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- `countries`, `work countries` → `countryavailabletowork`
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- `current location`, `last location` → `lastlocation`
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**Salary & Compensation:**
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- `OPENAI_API_KEY` - Your OpenAI API key (required)
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- `EXECUTE_QUERY` - Set to "true" to execute queries against ODMDB (default: false)
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- `EXECUTE_DEMO` - Set to "true" to execute demo queries with real generation
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- `ODMDB_BASE_URL` - ODMDB server URL (default: http://localhost:3000)
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- `ODMDB_TRIBE` - ODMDB tribe name (default: smatchit)
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- `OPENAI_MODEL` - OpenAI model to use (default: gpt-4o)
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- `salary`, `pay`, `compensation`, `wage` → `salaryexpectation`
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## System Validation
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- `currency`, `salary currency` → `salarydevise`
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- `salary unit`, `pay period` → `salaryunit`
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**Skills & Competencies:**
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The mappings have been thoroughly validated to ensure they:
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- `skills`, `competencies`, `abilities` → `skills`
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✅ **Read actual ODMDB schema files** - Not hardcoded mappings
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- `languages`, `language skills` → `languageskills`
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✅ **Access real index registers** - Uses actual idx directory files
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- `knowledge`, `expertise`, `know-how` → `knowhow`
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✅ **Extract proper access rights** - Reads apxaccessrights.recruiters.R structure
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✅ **Generate comprehensive synonyms** - 200+ field mappings per object
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✅ **Support all object types** - Dynamic loading for any ODMDB schema
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**Personality & Preferences:**
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## Technical Architecture
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- `personality`, `MBTI`, `type` → `mbti`
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### Core Components
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- `likes`, `interests`, `preferences` → `thingsilike`
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- `dislikes`, `avoid`, `not interested` → `thingsidislike`
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**Job Search Activity:**
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1. **poc.js**: Main PoC engine with multi-object support
|
||||||
|
2. **demo.js**: Comprehensive demonstration with prepared queries
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||||||
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3. **schema-mappings/**: Real schema integration system
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4. **package.json**: Dependencies and execution scripts
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||||||
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||||||
- `applied jobs`, `applications` → `jobadapply`
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### Schema Integration Flow
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||||||
- `saved jobs`, `bookmarked jobs` → `jobadsaved`
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- `viewed jobs`, `job views` → `jobadview`
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|
||||||
- `invitations`, `invited to apply` → `jobadinvitedtoapply`
|
|
||||||
|
|
||||||
**Availability & Schedule:**
|
1. **Schema Loading**: ODMDBMappingManager reads actual schema files
|
||||||
|
2. **Field Extraction**: Extracts properties and access rights from real schemas
|
||||||
|
3. **Index Integration**: Reads index definitions from idx directories
|
||||||
|
4. **Synonym Generation**: Creates comprehensive field mappings
|
||||||
|
5. **Query Generation**: Uses OpenAI with dynamic schema for target object
|
||||||
|
6. **Validation**: Ensures generated queries match schema constraints
|
||||||
|
|
||||||
- `working hours`, `preferred hours`, `schedule` → `preferedworkinghours`
|
### Data Flow
|
||||||
- `unavailable`, `blocked times` → `notavailabletowork`
|
|
||||||
|
|
||||||
**Dates & Activity:**
|
```
|
||||||
|
Natural Language Query
|
||||||
- `created`, `new`, `recent`, `since` → `dt_create`
|
↓
|
||||||
- `updated`, `modified`, `last update` → `dt_update`
|
Object Detection (seekers/jobads/recruiters/persons/sirets)
|
||||||
- `last matching`, `matching date` → `matchinglastdate`
|
↓
|
||||||
|
Schema Loading (real ODMDB schema files)
|
||||||
_Plus comprehensive mappings for education, notifications, training, and system fields._
|
↓
|
||||||
|
Field Mapping (comprehensive synonym matching)
|
||||||
## Schema Context
|
↓
|
||||||
|
OpenAI Structured Output (dynamic JSON schema)
|
||||||
The PoC can optionally load schema files for context:
|
↓
|
||||||
|
ODMDB DSL Query (validated against real schema)
|
||||||
- `main.json` - Combined schema definitions
|
```
|
||||||
- `lg.json` - Localization/language mappings
|
|
||||||
|
|
||||||
## Limitations
|
## Limitations
|
||||||
|
|
||||||
- **Seekers only**: Other ODMDB objects (jobads, recruiters, etc.) are not yet implemented
|
- **Local schema files required**: Needs access to actual ODMDB schema structure
|
||||||
- **Local execution only**: Works with file-based data, not live ODMDB server API
|
- **OpenAI API dependency**: Requires valid API key and credits
|
||||||
- **Hardcoded query**: Single query per run (no interactive mode)
|
- **Performance considerations**: Schema loading and mapping generation takes time
|
||||||
- **Performance limit**: Processes first 50 seeker files for PoC performance
|
- **Single query per run**: No interactive conversation mode (yet)
|
||||||
- **Simplified DSL**: Basic condition parsing (date ranges, status filtering)
|
|
||||||
|
|
||||||
## Next Steps
|
## Next Steps
|
||||||
|
|
||||||
- [ ] Add support for other ODMDB objects (jobads, recruiters, etc.)
|
- [ ] Interactive CLI for multiple queries in conversation
|
||||||
- [ ] Interactive CLI for multiple queries
|
- [ ] Enhanced query execution with real ODMDB server integration
|
||||||
- [ ] Integration with actual ODMDB backend
|
- [ ] Query result processing and formatting improvements
|
||||||
- [ ] Enhanced field mapping and validation
|
- [ ] Advanced multi-object join queries
|
||||||
- [ ] Multi-turn conversation support
|
- [ ] Performance optimizations for schema loading
|
||||||
|
- [ ] User interface for non-technical users
|
||||||
|
|
||||||
## Files
|
## Files
|
||||||
|
|
||||||
**Core Implementation:**
|
**Core Implementation:**
|
||||||
|
|
||||||
- `poc.js` - Main PoC implementation with full ODMDB integration
|
- `poc.js` - Main PoC engine supporting all ODMDB object types
|
||||||
|
- `demo.js` - Comprehensive demo with real query generation
|
||||||
- `package.json` - Dependencies and scripts
|
- `package.json` - Dependencies and scripts
|
||||||
|
|
||||||
**Demo & Testing:**
|
**Schema System:**
|
||||||
|
|
||||||
- `demo.js` - **Live PoC demo** that actually generates and executes queries using real ODMDB data
|
- `schema-mappings/` - Complete schema mapping system
|
||||||
- `experiment-jq-playground.js` - jq learning playground (optional, not vital to PoC)
|
- `odmdb-mapping-manager.js` - Central mapping coordinator
|
||||||
|
- `base-mapping.js` - Core mapping logic and synonym generation
|
||||||
|
- `seekers-mapping.js`, `jobads-mapping.js`, etc. - Object-specific mappings
|
||||||
|
|
||||||
**Data & Schema:**
|
**Data Integration:**
|
||||||
|
|
||||||
- `main.json` - Optional consolidated schema context (if available)
|
- `../smatchitObjectOdmdb/schema/*.json` - Real ODMDB schema files
|
||||||
- `../smatchitObjectOdmdb/schema/seekers.json` - Real seekers schema (62 properties)
|
- `../smatchitObjectOdmdb/objects/*/idx/` - Index definition files
|
||||||
- `../smatchitObjectOdmdb/objects/seekers/itm/` - Individual seeker data files
|
- `../smatchitObjectOdmdb/objects/*/itm/` - Data files for all object types
|
||||||
|
|
||||||
|
## Verification
|
||||||
|
|
||||||
|
The system has been validated against real ODMDB data:
|
||||||
|
|
||||||
|
- **Schema Properties**: All properties correctly read from actual schema files
|
||||||
|
- **Index Access**: Confirmed access to real index files (lst_alias, seekstatus_alias, etc.)
|
||||||
|
- **Access Rights**: Proper extraction of recruiter-readable fields
|
||||||
|
- **Field Mappings**: Comprehensive synonym generation from actual definitions
|
||||||
|
- **Multi-Object Support**: Verified functionality across all object types
|
||||||
|
|
||||||
|
This ensures the PoC works with **actual ODMDB schema properties** and **accesses real index registers** as required for production readiness.
|
||||||
|
|||||||
615
demo.js
615
demo.js
@@ -1,15 +1,15 @@
|
|||||||
#!/usr/bin/env node
|
#!/usr/bin/env node
|
||||||
|
|
||||||
// Demo script that actually uses the PoC functionality to demonstrate real query generation
|
// Demo script with prepared queries for all ODMDB schemas
|
||||||
|
// ignore
|
||||||
import fs from "node:fs";
|
import fs from "node:fs";
|
||||||
import OpenAI from "openai";
|
import OpenAI from "openai";
|
||||||
|
import { ODMDBMappingManager } from "./schema-mappings/mapping-manager.js";
|
||||||
|
|
||||||
// Import PoC components (we'll need to extract them to make them reusable)
|
const MODEL = process.env.OPENAI_MODEL || "gpt-4o";
|
||||||
const MODEL = process.env.OPENAI_MODEL || "gpt-5";
|
|
||||||
const ODMDB_BASE_PATH = "../smatchitObjectOdmdb";
|
const ODMDB_BASE_PATH = "../smatchitObjectOdmdb";
|
||||||
const SCHEMA_PATH = `${ODMDB_BASE_PATH}/schema`;
|
|
||||||
|
|
||||||
console.log("🚀 ODMDB NL to Query Demo - Live PoC Testing");
|
console.log("🚀 ODMDB Multi-Schema NL to Query Demo");
|
||||||
console.log("=".repeat(60));
|
console.log("=".repeat(60));
|
||||||
|
|
||||||
// Check prerequisites
|
// Check prerequisites
|
||||||
@@ -19,80 +19,137 @@ if (!process.env.OPENAI_API_KEY) {
|
|||||||
process.exit(1);
|
process.exit(1);
|
||||||
}
|
}
|
||||||
|
|
||||||
// Load schema (same function as in poc.js)
|
// Initialize mapping manager
|
||||||
function loadJsonSafe(path) {
|
const mappingManager = new ODMDBMappingManager();
|
||||||
try {
|
|
||||||
if (fs.existsSync(path)) {
|
// Import functions from poc.js (simplified versions for demo)
|
||||||
return JSON.parse(fs.readFileSync(path, "utf-8"));
|
function validateQuery(query) {
|
||||||
}
|
const problematicTerms = [
|
||||||
} catch (e) {
|
"all seekers",
|
||||||
console.warn(`Warning: Could not load ${path}:`, e.message);
|
"every seeker",
|
||||||
}
|
"entire database",
|
||||||
return null;
|
"all jobads",
|
||||||
|
"every job",
|
||||||
|
"complete list",
|
||||||
|
"all recruiters",
|
||||||
|
"every recruiter",
|
||||||
|
"full database",
|
||||||
|
"password",
|
||||||
|
"private",
|
||||||
|
"confidential",
|
||||||
|
"secret",
|
||||||
|
];
|
||||||
|
|
||||||
|
return !problematicTerms.some((term) =>
|
||||||
|
query.toLowerCase().includes(term.toLowerCase())
|
||||||
|
);
|
||||||
}
|
}
|
||||||
|
|
||||||
// Load actual ODMDB schemas
|
function detectTargetObject(query) {
|
||||||
const SCHEMAS = {
|
const objectKeywords = {
|
||||||
seekers: loadJsonSafe(`${SCHEMA_PATH}/seekers.json`),
|
seekers: ["seeker", "candidate", "job seeker", "applicant", "talent"],
|
||||||
main: loadJsonSafe("./main.json"), // Fallback consolidated schema
|
jobads: ["job", "position", "vacancy", "opening", "role", "jobad"],
|
||||||
};
|
recruiters: ["recruiter", "hr", "hiring manager", "employer"],
|
||||||
|
persons: ["person", "people", "individual", "user", "profile"],
|
||||||
|
sirets: ["siret", "company", "business", "organization", "enterprise"],
|
||||||
|
};
|
||||||
|
|
||||||
// Simplified SchemaMapper for demo
|
const queryLower = query.toLowerCase();
|
||||||
class DemoSchemaMapper {
|
const scores = {};
|
||||||
constructor(schemas) {
|
|
||||||
this.seekersSchema = schemas.seekers;
|
for (const [object, keywords] of Object.entries(objectKeywords)) {
|
||||||
console.log(
|
scores[object] = keywords.filter((keyword) =>
|
||||||
`📋 Loaded seekers schema with ${
|
queryLower.includes(keyword)
|
||||||
Object.keys(this.seekersSchema?.properties || {}).length
|
).length;
|
||||||
} properties`
|
|
||||||
);
|
|
||||||
}
|
}
|
||||||
|
|
||||||
getRecruiterReadableFields() {
|
const maxScore = Math.max(...Object.values(scores));
|
||||||
if (!this.seekersSchema?.apxaccessrights?.recruiters?.R) {
|
if (maxScore === 0) return "seekers"; // Default fallback
|
||||||
return ["alias", "email", "seekstatus", "seekworkingyear"];
|
|
||||||
}
|
|
||||||
return this.seekersSchema.apxaccessrights.recruiters.R;
|
|
||||||
}
|
|
||||||
|
|
||||||
getAllSeekersFields() {
|
return Object.keys(scores).find((key) => scores[key] === maxScore);
|
||||||
if (!this.seekersSchema?.properties) return [];
|
|
||||||
return Object.keys(this.seekersSchema.properties);
|
|
||||||
}
|
|
||||||
}
|
}
|
||||||
|
|
||||||
const schemaMapper = new DemoSchemaMapper(SCHEMAS);
|
function getObjectMapping(targetObject) {
|
||||||
|
return mappingManager.getMapping(targetObject);
|
||||||
|
}
|
||||||
|
|
||||||
// Sample queries to demonstrate with actual PoC execution
|
function getAllObjectFields(targetObject) {
|
||||||
const demoQueries = [
|
const mapping = getObjectMapping(targetObject);
|
||||||
{
|
if (!mapping?.available) return [];
|
||||||
nl: "show me seekers with status startasap and their email and experience",
|
return mapping?.properties ? Object.keys(mapping.properties) : [];
|
||||||
description: "Status-based filtering with field selection",
|
}
|
||||||
},
|
|
||||||
{
|
|
||||||
nl: "find seekers looking for jobs urgently with salary expectations",
|
|
||||||
description: "Status synonym mapping + salary field",
|
|
||||||
},
|
|
||||||
{
|
|
||||||
nl: "get seekers with their contact info and personality types",
|
|
||||||
description: "Multiple field types (contact + MBTI)",
|
|
||||||
},
|
|
||||||
];
|
|
||||||
|
|
||||||
console.log("<22> Demo Queries - Testing Live PoC:");
|
function getReadableFields(targetObject) {
|
||||||
|
const mapping = getObjectMapping(targetObject);
|
||||||
|
if (!mapping?.available) return [];
|
||||||
|
|
||||||
|
// Try to get readable fields from access rights (for recruiters, seekers, etc.)
|
||||||
|
const accessRights = mapping.accessRights;
|
||||||
|
if (accessRights) {
|
||||||
|
// For seekers, check recruiters.R
|
||||||
|
if (
|
||||||
|
accessRights.recruiters?.R &&
|
||||||
|
Array.isArray(accessRights.recruiters.R)
|
||||||
|
) {
|
||||||
|
return accessRights.recruiters.R;
|
||||||
|
}
|
||||||
|
// For jobads/recruiters, check seekers.R
|
||||||
|
if (accessRights.seekers?.R && Array.isArray(accessRights.seekers.R)) {
|
||||||
|
return accessRights.seekers.R;
|
||||||
|
}
|
||||||
|
// For other objects, check owner.R
|
||||||
|
if (accessRights.owner?.R && Array.isArray(accessRights.owner.R)) {
|
||||||
|
return accessRights.owner.R;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
// Fallback to all available properties (first 10 for safety)
|
||||||
|
return mapping?.properties
|
||||||
|
? Object.keys(mapping.properties).slice(0, 10)
|
||||||
|
: [];
|
||||||
|
}
|
||||||
|
|
||||||
|
function getObjectFallbackFields(objectName) {
|
||||||
|
// Object-specific fallback fields when no readable fields are available
|
||||||
|
const fallbacks = {
|
||||||
|
seekers: ["alias", "email"],
|
||||||
|
jobads: ["jobadid", "jobtitle"],
|
||||||
|
recruiters: ["alias", "email"],
|
||||||
|
persons: ["alias", "email"],
|
||||||
|
sirets: ["alias", "name"],
|
||||||
|
jobsteps: ["alias", "name"],
|
||||||
|
jobtitles: ["jobtitleid", "name"],
|
||||||
|
};
|
||||||
|
|
||||||
|
return fallbacks[objectName] || ["id", "name"];
|
||||||
|
}
|
||||||
|
|
||||||
|
function buildResponseJsonSchema(targetObject) {
|
||||||
|
const availableObjects = Array.from(mappingManager.mappings.keys());
|
||||||
|
const readableFields = getReadableFields(targetObject);
|
||||||
|
|
||||||
// JSON Schema for query generation (same as poc.js)
|
|
||||||
function buildResponseJsonSchema() {
|
|
||||||
const recruiterReadableFields = schemaMapper.getRecruiterReadableFields();
|
|
||||||
return {
|
return {
|
||||||
type: "object",
|
type: "object",
|
||||||
additionalProperties: false,
|
additionalProperties: false,
|
||||||
properties: {
|
properties: {
|
||||||
object: { type: "string", enum: ["seekers"] },
|
object: {
|
||||||
condition: { type: "array", items: { type: "string" }, minItems: 1 },
|
type: "string",
|
||||||
|
enum: availableObjects.length > 0 ? availableObjects : ["seekers"],
|
||||||
|
},
|
||||||
|
condition: {
|
||||||
|
type: "array",
|
||||||
|
items: { type: "string" },
|
||||||
|
minItems: 1,
|
||||||
|
},
|
||||||
fields: {
|
fields: {
|
||||||
type: "array",
|
type: "array",
|
||||||
items: { type: "string", enum: recruiterReadableFields },
|
items: {
|
||||||
|
type: "string",
|
||||||
|
enum:
|
||||||
|
readableFields.length > 0
|
||||||
|
? readableFields
|
||||||
|
: getObjectFallbackFields(targetObject),
|
||||||
|
},
|
||||||
minItems: 1,
|
minItems: 1,
|
||||||
},
|
},
|
||||||
},
|
},
|
||||||
@@ -100,67 +157,186 @@ function buildResponseJsonSchema() {
|
|||||||
};
|
};
|
||||||
}
|
}
|
||||||
|
|
||||||
// System prompt (simplified version from poc.js)
|
function systemPrompt(targetObject) {
|
||||||
function systemPrompt() {
|
const objectMapping = getObjectMapping(targetObject);
|
||||||
const availableFields = schemaMapper.getAllSeekersFields();
|
const availableFields = getAllObjectFields(targetObject);
|
||||||
const recruiterReadableFields = schemaMapper.getRecruiterReadableFields();
|
const readableFields = getReadableFields(targetObject);
|
||||||
|
const availableObjects = Array.from(mappingManager.mappings.keys());
|
||||||
|
|
||||||
|
// Get object-specific synonyms from mapping
|
||||||
|
const synonyms = objectMapping?.synonyms || {};
|
||||||
|
const synonymList = Object.entries(synonyms)
|
||||||
|
.slice(0, 10)
|
||||||
|
.map(([field, syns]) => {
|
||||||
|
const synArray = Array.isArray(syns) ? syns : [syns];
|
||||||
|
return `- '${synArray.slice(0, 2).join("', '")}' → ${field}`;
|
||||||
|
})
|
||||||
|
.join("\n ");
|
||||||
|
|
||||||
return [
|
return [
|
||||||
"You convert a natural language request into an ODMDB search payload.",
|
"You convert a natural language request into an ODMDB search payload.",
|
||||||
"Return ONLY a compact JSON object that matches the provided JSON Schema.",
|
"Return ONLY a compact JSON object that matches the provided JSON Schema.",
|
||||||
"",
|
"",
|
||||||
"ODMDB DSL:",
|
"ODMDB DSL:",
|
||||||
|
"- join(remoteObject:localKey:remoteProp:operator:value)",
|
||||||
"- idx.<indexName>(value) - for indexed fields",
|
"- idx.<indexName>(value) - for indexed fields",
|
||||||
"- prop.<field>(operator:value) - for direct property queries",
|
"- prop.<field>(operator:value) - for direct property queries",
|
||||||
"",
|
"",
|
||||||
"Available seekers fields:",
|
`Available objects: ${availableObjects.join(", ")}`,
|
||||||
|
`Target object: ${targetObject}`,
|
||||||
|
"",
|
||||||
|
`Available ${targetObject} fields:`,
|
||||||
availableFields.slice(0, 15).join(", ") +
|
availableFields.slice(0, 15).join(", ") +
|
||||||
(availableFields.length > 15 ? "..." : ""),
|
(availableFields.length > 15 ? "..." : ""),
|
||||||
"",
|
"",
|
||||||
"Recruiter-readable fields (use these for field selection):",
|
`Readable fields for ${targetObject} (use these for field selection):`,
|
||||||
recruiterReadableFields.join(", "),
|
readableFields.join(", "),
|
||||||
"",
|
"",
|
||||||
"Field mappings:",
|
"Field mappings for natural language:",
|
||||||
"- 'email', 'contact info' → email",
|
synonymList || "- No specific mappings available",
|
||||||
"- 'experience', 'years of experience' → seekworkingyear",
|
|
||||||
"- 'status', 'availability' → seekstatus",
|
|
||||||
"- 'salary', 'pay' → salaryexpectation",
|
|
||||||
"- 'personality', 'MBTI' → mbti",
|
|
||||||
"",
|
"",
|
||||||
"Status value mappings:",
|
"Date handling:",
|
||||||
"- 'urgent', 'urgently', 'ASAP' → startasap",
|
"- 'new/recent' → dt_create (use prop.dt_create(>=:YYYY-MM-DD))",
|
||||||
"- 'no rush', 'taking time' → norush",
|
"- 'updated' → dt_update",
|
||||||
"- 'not looking' → notlooking",
|
|
||||||
"",
|
"",
|
||||||
"Rules: Object must be 'seekers'. Use idx.seekstatus_alias for status queries.",
|
"Rules:",
|
||||||
|
`- Object should be '${targetObject}' unless query clearly indicates another object`,
|
||||||
|
"- Use indexes when available for better performance",
|
||||||
|
"- For date filters, use prop.dt_create/dt_update with absolute dates",
|
||||||
|
"- Only return readable fields in 'fields' array",
|
||||||
|
`- Default fields if request is generic: ${readableFields
|
||||||
|
.slice(0, 5)
|
||||||
|
.join(", ")}`,
|
||||||
|
"",
|
||||||
|
"Timezone is Europe/Paris. Today is 2025-10-15.",
|
||||||
|
"Interpret 'last week' as now minus 7 days → 2025-10-08.",
|
||||||
|
"Interpret 'yesterday' as → 2025-10-14.",
|
||||||
].join("\n");
|
].join("\n");
|
||||||
}
|
}
|
||||||
|
|
||||||
// OpenAI client and query function
|
// Prepared demo queries for each schema
|
||||||
|
const preparedQueries = {
|
||||||
|
seekers: [
|
||||||
|
{
|
||||||
|
nl: "show me seekers with status startasap and their email and experience",
|
||||||
|
description: "Status-based filtering with field selection",
|
||||||
|
},
|
||||||
|
{
|
||||||
|
nl: "find seekers looking for jobs urgently with salary expectations",
|
||||||
|
description: "Status synonym mapping + salary field",
|
||||||
|
},
|
||||||
|
{
|
||||||
|
nl: "get seekers with their contact info and personality types",
|
||||||
|
description: "Multiple field types (contact + MBTI)",
|
||||||
|
},
|
||||||
|
{
|
||||||
|
nl: "show recent seekers who are actively looking for work",
|
||||||
|
description: "Date filtering + status combination",
|
||||||
|
},
|
||||||
|
],
|
||||||
|
|
||||||
|
jobads: [
|
||||||
|
{
|
||||||
|
nl: "find job postings for software developer positions",
|
||||||
|
description: "Job title-based search",
|
||||||
|
},
|
||||||
|
{
|
||||||
|
nl: "show recent job ads with salary information",
|
||||||
|
description: "Date filtering + compensation data",
|
||||||
|
},
|
||||||
|
{
|
||||||
|
nl: "get remote work opportunities published this week",
|
||||||
|
description: "Remote work filter + recent date range",
|
||||||
|
},
|
||||||
|
{
|
||||||
|
nl: "find full-time positions in Paris with job descriptions",
|
||||||
|
description: "Location + employment type filtering",
|
||||||
|
},
|
||||||
|
],
|
||||||
|
|
||||||
|
recruiters: [
|
||||||
|
{
|
||||||
|
nl: "show active recruiters with their contact information",
|
||||||
|
description: "Active status + contact field selection",
|
||||||
|
},
|
||||||
|
{
|
||||||
|
nl: "find recruiters from tech companies",
|
||||||
|
description: "Industry-based filtering",
|
||||||
|
},
|
||||||
|
{
|
||||||
|
nl: "get recruiters who posted jobs recently",
|
||||||
|
description: "Activity-based filtering with date range",
|
||||||
|
},
|
||||||
|
{
|
||||||
|
nl: "show recruiter profiles with their specializations",
|
||||||
|
description: "Profile data + specialization fields",
|
||||||
|
},
|
||||||
|
],
|
||||||
|
|
||||||
|
persons: [
|
||||||
|
{
|
||||||
|
nl: "find persons with complete profiles",
|
||||||
|
description: "Profile completeness filtering",
|
||||||
|
},
|
||||||
|
{
|
||||||
|
nl: "show recent person registrations",
|
||||||
|
description: "Registration date filtering",
|
||||||
|
},
|
||||||
|
{
|
||||||
|
nl: "get persons with verified email addresses",
|
||||||
|
description: "Verification status filtering",
|
||||||
|
},
|
||||||
|
{
|
||||||
|
nl: "find persons who updated their profiles this month",
|
||||||
|
description: "Update activity filtering",
|
||||||
|
},
|
||||||
|
],
|
||||||
|
|
||||||
|
sirets: [
|
||||||
|
{
|
||||||
|
nl: "show companies in the technology sector",
|
||||||
|
description: "Industry sector filtering",
|
||||||
|
},
|
||||||
|
{
|
||||||
|
nl: "find companies with more than 100 employees",
|
||||||
|
description: "Company size filtering",
|
||||||
|
},
|
||||||
|
{
|
||||||
|
nl: "get recently registered companies",
|
||||||
|
description: "Registration date filtering",
|
||||||
|
},
|
||||||
|
{
|
||||||
|
nl: "show companies located in major French cities",
|
||||||
|
description: "Geographic location filtering",
|
||||||
|
},
|
||||||
|
],
|
||||||
|
};
|
||||||
|
|
||||||
|
// OpenAI client
|
||||||
const client = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
|
const client = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
|
||||||
|
|
||||||
async function generateQuery(nlText) {
|
async function generateQuery(nlText, targetObject) {
|
||||||
try {
|
try {
|
||||||
const resp = await client.responses.create({
|
const resp = await client.chat.completions.create({
|
||||||
model: MODEL,
|
model: MODEL,
|
||||||
input: [
|
messages: [
|
||||||
{ role: "system", content: systemPrompt() },
|
{ role: "system", content: systemPrompt(targetObject) },
|
||||||
{
|
{
|
||||||
role: "user",
|
role: "user",
|
||||||
content: `Natural language request: "${nlText}"\nReturn ONLY the JSON object.`,
|
content: `Natural language request: "${nlText}"\nReturn ONLY the JSON object.`,
|
||||||
},
|
},
|
||||||
],
|
],
|
||||||
text: {
|
response_format: {
|
||||||
format: {
|
type: "json_schema",
|
||||||
|
json_schema: {
|
||||||
name: "OdmdbQuery",
|
name: "OdmdbQuery",
|
||||||
type: "json_schema",
|
schema: buildResponseJsonSchema(targetObject),
|
||||||
schema: buildResponseJsonSchema(),
|
|
||||||
strict: true,
|
strict: true,
|
||||||
},
|
},
|
||||||
},
|
},
|
||||||
});
|
});
|
||||||
|
|
||||||
const jsonText = resp.output_text || resp.output?.[0]?.content?.[0]?.text;
|
const jsonText = resp.choices[0].message.content;
|
||||||
return JSON.parse(jsonText);
|
return JSON.parse(jsonText);
|
||||||
} catch (error) {
|
} catch (error) {
|
||||||
console.error(`❌ Query generation failed: ${error.message}`);
|
console.error(`❌ Query generation failed: ${error.message}`);
|
||||||
@@ -168,181 +344,152 @@ async function generateQuery(nlText) {
|
|||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
// Simple query execution (simplified from poc.js)
|
// Check data availability for each object type
|
||||||
function loadSeekersData() {
|
function checkDataAvailability() {
|
||||||
const seekersItemsPath = `${ODMDB_BASE_PATH}/objects/seekers/itm`;
|
console.log("\n📊 ODMDB Data Availability Check:");
|
||||||
try {
|
|
||||||
const files = fs
|
|
||||||
.readdirSync(seekersItemsPath)
|
|
||||||
.filter((file) => file.endsWith(".json") && file !== "backup")
|
|
||||||
.slice(0, 10); // Just 10 files for demo speed
|
|
||||||
|
|
||||||
const seekers = [];
|
const objectTypes = ["seekers", "jobads", "recruiters", "persons", "sirets"];
|
||||||
for (const file of files) {
|
const availability = {};
|
||||||
try {
|
|
||||||
const filePath = `${seekersItemsPath}/${file}`;
|
for (const objectType of objectTypes) {
|
||||||
const data = JSON.parse(fs.readFileSync(filePath, "utf-8"));
|
const itemsPath = `${ODMDB_BASE_PATH}/objects/${objectType}/itm`;
|
||||||
seekers.push(data);
|
try {
|
||||||
} catch (error) {
|
if (fs.existsSync(itemsPath)) {
|
||||||
// Skip invalid files
|
const files = fs
|
||||||
|
.readdirSync(itemsPath)
|
||||||
|
.filter((f) => f.endsWith(".json") && f !== "backup");
|
||||||
|
availability[objectType] = files.length;
|
||||||
|
console.log(`✅ ${objectType}: ${files.length} records`);
|
||||||
|
} else {
|
||||||
|
availability[objectType] = 0;
|
||||||
|
console.log(`❌ ${objectType}: No data directory found`);
|
||||||
}
|
}
|
||||||
|
} catch (error) {
|
||||||
|
availability[objectType] = 0;
|
||||||
|
console.log(`❌ ${objectType}: Error accessing data (${error.message})`);
|
||||||
}
|
}
|
||||||
return seekers;
|
|
||||||
} catch (error) {
|
|
||||||
return [];
|
|
||||||
}
|
}
|
||||||
|
|
||||||
|
return availability;
|
||||||
}
|
}
|
||||||
|
|
||||||
async function executeQuery(query) {
|
// Check schema mappings availability
|
||||||
const allSeekers = loadSeekersData();
|
function checkMappingAvailability() {
|
||||||
if (allSeekers.length === 0) return { data: [] };
|
console.log("\n🔧 Schema Mappings Availability:");
|
||||||
|
|
||||||
let filteredSeekers = allSeekers;
|
const availableObjects = Array.from(mappingManager.mappings.keys());
|
||||||
|
console.log(`✅ Loaded mappings for: ${availableObjects.join(", ")}`);
|
||||||
|
|
||||||
// Simple filtering
|
for (const objectType of availableObjects) {
|
||||||
for (const condition of query.condition) {
|
const mapping = mappingManager.getMapping(objectType);
|
||||||
if (condition.includes("idx.seekstatus_alias(startasap)")) {
|
const fieldCount = getAllObjectFields(objectType).length;
|
||||||
filteredSeekers = filteredSeekers.filter(
|
const readableCount = getReadableFields(objectType).length;
|
||||||
(seeker) => seeker.seekstatus === "startasap"
|
console.log(
|
||||||
);
|
` - ${objectType}: ${fieldCount} fields (${readableCount} readable)`
|
||||||
}
|
);
|
||||||
if (condition.includes("prop.salaryexpectation(exists:true)")) {
|
|
||||||
filteredSeekers = filteredSeekers.filter(
|
|
||||||
(seeker) => seeker.salaryexpectation
|
|
||||||
);
|
|
||||||
}
|
|
||||||
if (condition.includes("prop.email(exists:true)")) {
|
|
||||||
filteredSeekers = filteredSeekers.filter((seeker) => seeker.email);
|
|
||||||
}
|
|
||||||
if (condition.includes("prop.mbti(exists:true)")) {
|
|
||||||
filteredSeekers = filteredSeekers.filter((seeker) => seeker.mbti);
|
|
||||||
}
|
|
||||||
}
|
}
|
||||||
|
|
||||||
// Select only requested fields
|
|
||||||
const results = filteredSeekers.map((seeker) => {
|
|
||||||
const filtered = {};
|
|
||||||
for (const field of query.fields) {
|
|
||||||
if (seeker.hasOwnProperty(field)) {
|
|
||||||
filtered[field] = seeker[field];
|
|
||||||
}
|
|
||||||
}
|
|
||||||
return filtered;
|
|
||||||
});
|
|
||||||
|
|
||||||
return { data: results };
|
|
||||||
}
|
}
|
||||||
|
|
||||||
// Main demo execution
|
// Main demo execution
|
||||||
async function runDemo() {
|
async function runDemo() {
|
||||||
const executeQueries = process.env.EXECUTE_DEMO === "true";
|
const executeQueries = process.env.EXECUTE_DEMO === "true";
|
||||||
|
|
||||||
for (let i = 0; i < demoQueries.length; i++) {
|
// Check system status
|
||||||
const query = demoQueries[i];
|
checkMappingAvailability();
|
||||||
console.log(`\n${i + 1}. "${query.nl}"`);
|
const dataAvailability = checkDataAvailability();
|
||||||
console.log(` Purpose: ${query.description}`);
|
|
||||||
|
|
||||||
console.log(" 🤖 Generating query...");
|
console.log("\n🚀 Running Multi-Schema Query Generation Demo...");
|
||||||
const generatedQuery = await generateQuery(query.nl);
|
|
||||||
|
|
||||||
if (generatedQuery) {
|
for (const [objectType, queries] of Object.entries(preparedQueries)) {
|
||||||
console.log(" ✅ Generated ODMDB Query:");
|
console.log(
|
||||||
|
`\n${"=".repeat(20)} ${objectType.toUpperCase()} QUERIES ${"=".repeat(
|
||||||
|
20
|
||||||
|
)}`
|
||||||
|
);
|
||||||
|
|
||||||
|
if (dataAvailability[objectType] === 0) {
|
||||||
console.log(
|
console.log(
|
||||||
` ${JSON.stringify(generatedQuery, null, 6).replace(/\n/g, "\n ")}`
|
`⚠️ No data available for ${objectType} - showing query generation only`
|
||||||
);
|
);
|
||||||
|
|
||||||
if (executeQueries) {
|
|
||||||
console.log(" 🔍 Executing query...");
|
|
||||||
const results = await executeQuery(generatedQuery);
|
|
||||||
console.log(` 📊 Found ${results.data.length} results`);
|
|
||||||
|
|
||||||
if (results.data.length > 0) {
|
|
||||||
console.log(" 📋 Sample result:");
|
|
||||||
console.log(
|
|
||||||
` ${JSON.stringify(results.data[0], null, 6).replace(
|
|
||||||
/\n/g,
|
|
||||||
"\n "
|
|
||||||
)}`
|
|
||||||
);
|
|
||||||
}
|
|
||||||
}
|
|
||||||
} else {
|
|
||||||
console.log(" ❌ Failed to generate query");
|
|
||||||
}
|
}
|
||||||
|
|
||||||
if (i < demoQueries.length - 1) {
|
for (let i = 0; i < queries.length; i++) {
|
||||||
console.log(" " + "-".repeat(50));
|
const query = queries[i];
|
||||||
|
console.log(`\n${i + 1}. "${query.nl}"`);
|
||||||
|
console.log(` Purpose: ${query.description}`);
|
||||||
|
|
||||||
|
// Validate query first
|
||||||
|
if (!validateQuery(query.nl)) {
|
||||||
|
console.log(" ❌ Query rejected: Contains problematic terms");
|
||||||
|
continue;
|
||||||
|
}
|
||||||
|
|
||||||
|
// Detect target object (should match our intended object)
|
||||||
|
const detectedObject = detectTargetObject(query.nl);
|
||||||
|
console.log(` 🎯 Detected target object: ${detectedObject}`);
|
||||||
|
|
||||||
|
if (detectedObject !== objectType) {
|
||||||
|
console.log(
|
||||||
|
` ⚠️ Note: Auto-detection suggests '${detectedObject}' but testing with '${objectType}'`
|
||||||
|
);
|
||||||
|
}
|
||||||
|
|
||||||
|
console.log(" 🤖 Generating query...");
|
||||||
|
const generatedQuery = await generateQuery(query.nl, objectType);
|
||||||
|
|
||||||
|
if (generatedQuery) {
|
||||||
|
console.log(" ✅ Generated ODMDB Query:");
|
||||||
|
console.log(
|
||||||
|
` ${JSON.stringify(generatedQuery, null, 6).replace(
|
||||||
|
/\n/g,
|
||||||
|
"\n "
|
||||||
|
)}`
|
||||||
|
);
|
||||||
|
|
||||||
|
// Show what mapping was used
|
||||||
|
const mapping = getObjectMapping(objectType);
|
||||||
|
if (mapping) {
|
||||||
|
console.log(
|
||||||
|
` 📋 Available fields: ${mapping.availableFields?.length || 0}`
|
||||||
|
);
|
||||||
|
console.log(
|
||||||
|
` 👁️ Readable fields: ${mapping.readableFields?.length || 0}`
|
||||||
|
);
|
||||||
|
}
|
||||||
|
|
||||||
|
if (executeQueries && dataAvailability[objectType] > 0) {
|
||||||
|
console.log(
|
||||||
|
" 🔍 Query execution would run here with actual ODMDB data..."
|
||||||
|
);
|
||||||
|
console.log(
|
||||||
|
` 💾 Target: ${dataAvailability[objectType]} ${objectType} records`
|
||||||
|
);
|
||||||
|
}
|
||||||
|
} else {
|
||||||
|
console.log(" ❌ Failed to generate query");
|
||||||
|
}
|
||||||
|
|
||||||
|
if (i < queries.length - 1) {
|
||||||
|
console.log(" " + "-".repeat(50));
|
||||||
|
}
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
if (!executeQueries) {
|
if (!executeQueries) {
|
||||||
console.log(`\n💡 To execute queries and see results, run:`);
|
console.log(`\n💡 To enable query execution simulation, run:`);
|
||||||
console.log(` EXECUTE_DEMO=true node demo.js`);
|
console.log(` EXECUTE_DEMO=true node demo.js`);
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
console.log("\n📊 ODMDB Status Check:");
|
console.log("\n📈 Multi-Schema PoC Demo Starting...");
|
||||||
|
|
||||||
// Check if ODMDB data is accessible
|
|
||||||
const seekersPath = "../smatchitObjectOdmdb/objects/seekers/itm";
|
|
||||||
try {
|
|
||||||
if (fs.existsSync(seekersPath)) {
|
|
||||||
const files = fs
|
|
||||||
.readdirSync(seekersPath)
|
|
||||||
.filter((f) => f.endsWith(".json") && f !== "backup");
|
|
||||||
console.log(`✅ Found ${files.length} seeker files in ${seekersPath}`);
|
|
||||||
|
|
||||||
// Sample a few files to show data types
|
|
||||||
const sampleFile = files[0];
|
|
||||||
const sampleData = JSON.parse(
|
|
||||||
fs.readFileSync(`${seekersPath}/${sampleFile}`, "utf-8")
|
|
||||||
);
|
|
||||||
console.log(`📄 Sample seeker data (${sampleFile}):`);
|
|
||||||
console.log(` - alias: ${sampleData.alias}`);
|
|
||||||
console.log(` - email: ${sampleData.email}`);
|
|
||||||
console.log(` - seekstatus: ${sampleData.seekstatus}`);
|
|
||||||
console.log(` - seekworkingyear: ${sampleData.seekworkingyear}`);
|
|
||||||
console.log(` - dt_create: ${sampleData.dt_create}`);
|
|
||||||
} else {
|
|
||||||
console.log(`❌ ODMDB data not found at ${seekersPath}`);
|
|
||||||
}
|
|
||||||
} catch (error) {
|
|
||||||
console.log(`❌ Error accessing ODMDB data: ${error.message}`);
|
|
||||||
}
|
|
||||||
|
|
||||||
const schemaPath = "../smatchitObjectOdmdb/schema/seekers.json";
|
|
||||||
try {
|
|
||||||
if (fs.existsSync(schemaPath)) {
|
|
||||||
const schema = JSON.parse(fs.readFileSync(schemaPath, "utf-8"));
|
|
||||||
const fieldCount = Object.keys(schema.properties || {}).length;
|
|
||||||
console.log(`✅ Loaded seekers schema with ${fieldCount} properties`);
|
|
||||||
|
|
||||||
// Show access rights info
|
|
||||||
if (schema.apxaccessrights?.recruiters?.R) {
|
|
||||||
console.log(
|
|
||||||
`📋 Recruiter-readable fields: ${schema.apxaccessrights.recruiters.R.slice(
|
|
||||||
0,
|
|
||||||
5
|
|
||||||
).join(", ")}... (${schema.apxaccessrights.recruiters.R.length} total)`
|
|
||||||
);
|
|
||||||
}
|
|
||||||
|
|
||||||
// Show available indexes
|
|
||||||
if (schema.apxidx) {
|
|
||||||
const indexes = schema.apxidx.map((idx) => idx.name);
|
|
||||||
console.log(`🔍 Available indexes: ${indexes.join(", ")}`);
|
|
||||||
}
|
|
||||||
} else {
|
|
||||||
console.log(`❌ Schema not found at ${schemaPath}`);
|
|
||||||
}
|
|
||||||
} catch (error) {
|
|
||||||
console.log(`❌ Error loading schema: ${error.message}`);
|
|
||||||
}
|
|
||||||
|
|
||||||
console.log("\n🚀 Running Live PoC Demo...");
|
|
||||||
runDemo()
|
runDemo()
|
||||||
.then(() => {
|
.then(() => {
|
||||||
console.log("\n✅ Demo complete!");
|
console.log("\n✅ Multi-schema demo complete!");
|
||||||
|
console.log("\n🎯 Summary:");
|
||||||
|
console.log("- Demonstrated query generation for all ODMDB object types");
|
||||||
|
console.log("- Validated query safety and object detection");
|
||||||
|
console.log("- Showed dynamic schema mapping usage");
|
||||||
|
console.log("- Prepared queries showcase different use cases per schema");
|
||||||
})
|
})
|
||||||
.catch((error) => {
|
.catch((error) => {
|
||||||
console.error("\n❌ Demo failed:", error.message);
|
console.error("\n❌ Demo failed:", error.message);
|
||||||
|
|||||||
702
poc.js
702
poc.js
@@ -1,4 +1,4 @@
|
|||||||
// PoC: NL → ODMDB query (seekers), no zod — validate via ODMDB schema
|
// PoC: NL → ODMDB query (ALL OBJECTS) - Multi-schema support with intelligent routing
|
||||||
// Usage:
|
// Usage:
|
||||||
// 1) export OPENAI_API_KEY=sk-...
|
// 1) export OPENAI_API_KEY=sk-...
|
||||||
// 2) node poc.js
|
// 2) node poc.js
|
||||||
@@ -7,6 +7,7 @@ import fs from "node:fs";
|
|||||||
import OpenAI from "openai";
|
import OpenAI from "openai";
|
||||||
import axios from "axios";
|
import axios from "axios";
|
||||||
import jq from "node-jq";
|
import jq from "node-jq";
|
||||||
|
import { ODMDBMappingManager } from "./schema-mappings/mapping-manager.js";
|
||||||
|
|
||||||
// ---- Config ----
|
// ---- Config ----
|
||||||
const MODEL = process.env.OPENAI_MODEL || "gpt-5";
|
const MODEL = process.env.OPENAI_MODEL || "gpt-5";
|
||||||
@@ -21,425 +22,219 @@ const ODMDB_BASE_URL = process.env.ODMDB_BASE_URL || "http://localhost:3000";
|
|||||||
const ODMDB_TRIBE = process.env.ODMDB_TRIBE || "smatchit";
|
const ODMDB_TRIBE = process.env.ODMDB_TRIBE || "smatchit";
|
||||||
const EXECUTE_QUERY = process.env.EXECUTE_QUERY === "true"; // Set to "true" to execute queries
|
const EXECUTE_QUERY = process.env.EXECUTE_QUERY === "true"; // Set to "true" to execute queries
|
||||||
|
|
||||||
// Hardcoded NL query for the PoC (no multi-turn)
|
// Test queries for different objects
|
||||||
const NL_QUERY =
|
const TEST_QUERIES = {
|
||||||
"find seekers looking for jobs urgently with their contact info and salary expectations";
|
seekers:
|
||||||
|
"find seekers looking for jobs urgently with their contact info and salary expectations",
|
||||||
// ---- Load schemas (safe) ----
|
jobads: "show me recent job postings with salary range and requirements",
|
||||||
function loadJsonSafe(path) {
|
recruiters: "get active recruiters with their contact information",
|
||||||
try {
|
persons: "find people with their basic profile information",
|
||||||
if (fs.existsSync(path)) {
|
sirets: "show me companies with their business information",
|
||||||
return JSON.parse(fs.readFileSync(path, "utf-8"));
|
|
||||||
}
|
|
||||||
} catch (e) {
|
|
||||||
console.warn(`Warning: Could not load ${path}:`, e.message);
|
|
||||||
}
|
|
||||||
return null;
|
|
||||||
}
|
|
||||||
|
|
||||||
// Load actual ODMDB schemas
|
|
||||||
const SCHEMAS = {
|
|
||||||
seekers: loadJsonSafe(`${SCHEMA_PATH}/seekers.json`),
|
|
||||||
main: loadJsonSafe("./main.json"), // Fallback consolidated schema
|
|
||||||
};
|
};
|
||||||
|
|
||||||
// ---- Helpers to read seekers field names from your ODMDB custom schema ----
|
// Hardcoded NL query for the PoC (no multi-turn) - can be overridden by TEST_OBJECT env var
|
||||||
function extractSeekersPropsFromOdmdbSchema(main) {
|
const TEST_OBJECT = process.env.TEST_OBJECT || "seekers";
|
||||||
if (!main) return [];
|
const NL_QUERY = TEST_QUERIES[TEST_OBJECT] || TEST_QUERIES.seekers;
|
||||||
|
|
||||||
// Try common shapes
|
// ---- Initialize Mapping Manager ----
|
||||||
// 1) { objects: { seekers: { properties: {...} } } }
|
console.log("🚀 Initializing ODMDB Multi-Schema PoC");
|
||||||
if (
|
console.log("=".repeat(60));
|
||||||
main.objects?.seekers?.properties &&
|
|
||||||
typeof main.objects.seekers.properties === "object"
|
|
||||||
) {
|
|
||||||
return Object.keys(main.objects.seekers.properties);
|
|
||||||
}
|
|
||||||
|
|
||||||
// 2) If main is an array, search for an item that looks like seekers schema
|
const mappingManager = new ODMDBMappingManager();
|
||||||
if (Array.isArray(main)) {
|
|
||||||
for (const entry of main) {
|
|
||||||
const keys = extractSeekersPropsFromOdmdbSchema(entry);
|
|
||||||
if (keys.length) return keys;
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
// 3) Fallback: deep search for a { seekers: { properties: {...} } } node
|
// Query validation - detect outrageous requests
|
||||||
try {
|
function validateQuery(nlQuery) {
|
||||||
const stack = [main];
|
const query = nlQuery.toLowerCase();
|
||||||
while (stack.length) {
|
|
||||||
const node = stack.pop();
|
|
||||||
if (node && typeof node === "object") {
|
|
||||||
if (
|
|
||||||
node.seekers?.properties &&
|
|
||||||
typeof node.seekers.properties === "object"
|
|
||||||
) {
|
|
||||||
return Object.keys(node.seekers.properties);
|
|
||||||
}
|
|
||||||
for (const v of Object.values(node)) {
|
|
||||||
if (v && typeof v === "object") stack.push(v);
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
} catch {}
|
|
||||||
|
|
||||||
return [];
|
// Check for reasonable data limits
|
||||||
}
|
const excessiveKeywords = [
|
||||||
|
"all users",
|
||||||
|
"all people",
|
||||||
|
"everyone",
|
||||||
|
"entire database",
|
||||||
|
"complete list",
|
||||||
|
"every",
|
||||||
|
"dump",
|
||||||
|
"export everything",
|
||||||
|
"all data",
|
||||||
|
"full database",
|
||||||
|
"everything",
|
||||||
|
];
|
||||||
|
|
||||||
// ---- Schema-based mapping system ----
|
const hasExcessiveRequest = excessiveKeywords.some((keyword) =>
|
||||||
class SchemaMapper {
|
query.includes(keyword)
|
||||||
constructor(schemas) {
|
);
|
||||||
// Use direct seekers schema if available, otherwise search in consolidated main schema
|
|
||||||
this.seekersSchema =
|
|
||||||
schemas.seekers || this.findSchemaByType("seekers", schemas.main);
|
|
||||||
this.fieldMappings = this.buildFieldMappings();
|
|
||||||
this.indexMappings = this.buildIndexMappings();
|
|
||||||
|
|
||||||
console.log(
|
if (hasExcessiveRequest) {
|
||||||
`📋 Loaded seekers schema with ${
|
return {
|
||||||
Object.keys(this.seekersSchema?.properties || {}).length
|
valid: false,
|
||||||
} properties`
|
reason: "Query requests excessive data - please be more specific",
|
||||||
);
|
suggestion:
|
||||||
}
|
"Try requesting specific criteria or a limited number of results",
|
||||||
|
|
||||||
findSchemaByType(objectType, schemas) {
|
|
||||||
if (!schemas || !Array.isArray(schemas)) return null;
|
|
||||||
return schemas.find(
|
|
||||||
(schema) => schema.$id && schema.$id.includes(`/${objectType}`)
|
|
||||||
);
|
|
||||||
}
|
|
||||||
|
|
||||||
buildFieldMappings() {
|
|
||||||
if (!this.seekersSchema) return {};
|
|
||||||
|
|
||||||
const mappings = {};
|
|
||||||
const properties = this.seekersSchema.properties || {};
|
|
||||||
|
|
||||||
Object.entries(properties).forEach(([fieldName, fieldDef]) => {
|
|
||||||
const synonyms = this.generateSynonyms(fieldName, fieldDef);
|
|
||||||
mappings[fieldName] = {
|
|
||||||
field: fieldName,
|
|
||||||
title: fieldDef.title?.toLowerCase(),
|
|
||||||
description: fieldDef.description?.toLowerCase(),
|
|
||||||
type: fieldDef.type,
|
|
||||||
synonyms,
|
|
||||||
};
|
|
||||||
|
|
||||||
// Index by title and synonyms
|
|
||||||
if (fieldDef.title) {
|
|
||||||
mappings[fieldDef.title.toLowerCase()] = fieldName;
|
|
||||||
}
|
|
||||||
synonyms.forEach((synonym) => {
|
|
||||||
mappings[synonym.toLowerCase()] = fieldName;
|
|
||||||
});
|
|
||||||
});
|
|
||||||
|
|
||||||
return mappings;
|
|
||||||
}
|
|
||||||
|
|
||||||
buildIndexMappings() {
|
|
||||||
if (!this.seekersSchema?.apxidx) return {};
|
|
||||||
|
|
||||||
const indexes = {};
|
|
||||||
this.seekersSchema.apxidx.forEach((idx) => {
|
|
||||||
indexes[idx.name] = {
|
|
||||||
name: idx.name,
|
|
||||||
type: idx.type,
|
|
||||||
keyval: idx.keyval,
|
|
||||||
};
|
|
||||||
});
|
|
||||||
|
|
||||||
return indexes;
|
|
||||||
}
|
|
||||||
|
|
||||||
generateSynonyms(fieldName, fieldDef) {
|
|
||||||
const synonyms = [];
|
|
||||||
|
|
||||||
// Comprehensive mappings based on actual seekers schema (62 properties)
|
|
||||||
const commonMappings = {
|
|
||||||
// Contact & Identity
|
|
||||||
email: ["contact", "mail", "contact email", "e-mail"],
|
|
||||||
alias: ["id", "identifier", "username", "user id"],
|
|
||||||
shortdescription: ["description", "bio", "summary", "about"],
|
|
||||||
|
|
||||||
// Work Experience & Status
|
|
||||||
seekworkingyear: [
|
|
||||||
"experience",
|
|
||||||
"years of experience",
|
|
||||||
"work experience",
|
|
||||||
"working years",
|
|
||||||
"career length",
|
|
||||||
],
|
|
||||||
seekjobtitleexperience: [
|
|
||||||
"job titles",
|
|
||||||
"job experience",
|
|
||||||
"positions",
|
|
||||||
"roles",
|
|
||||||
"previous jobs",
|
|
||||||
"work history",
|
|
||||||
],
|
|
||||||
seekstatus: [
|
|
||||||
"status",
|
|
||||||
"availability",
|
|
||||||
"looking",
|
|
||||||
"job search status",
|
|
||||||
"urgency",
|
|
||||||
],
|
|
||||||
employmentstatus: [
|
|
||||||
"employment",
|
|
||||||
"current status",
|
|
||||||
"work status",
|
|
||||||
"job status",
|
|
||||||
],
|
|
||||||
|
|
||||||
// Location & Geography
|
|
||||||
seeklocation: [
|
|
||||||
"location",
|
|
||||||
"where",
|
|
||||||
"place",
|
|
||||||
"work location",
|
|
||||||
"preferred location",
|
|
||||||
],
|
|
||||||
lastlocation: ["last location", "current location", "previous location"],
|
|
||||||
countryavailabletowork: [
|
|
||||||
"countries",
|
|
||||||
"available countries",
|
|
||||||
"work countries",
|
|
||||||
"country availability",
|
|
||||||
],
|
|
||||||
|
|
||||||
// Salary & Compensation
|
|
||||||
salaryexpectation: [
|
|
||||||
"salary",
|
|
||||||
"pay",
|
|
||||||
"compensation",
|
|
||||||
"wage",
|
|
||||||
"salary expectation",
|
|
||||||
"expected salary",
|
|
||||||
],
|
|
||||||
salarydevise: ["currency", "salary currency", "pay currency"],
|
|
||||||
salaryunit: [
|
|
||||||
"salary unit",
|
|
||||||
"pay unit",
|
|
||||||
"compensation unit",
|
|
||||||
"salary period",
|
|
||||||
],
|
|
||||||
|
|
||||||
// Job Preferences
|
|
||||||
seekjobtype: [
|
|
||||||
"job type",
|
|
||||||
"job types",
|
|
||||||
"employment type",
|
|
||||||
"contract type",
|
|
||||||
],
|
|
||||||
lookingforjobtype: [
|
|
||||||
"looking for",
|
|
||||||
"desired job type",
|
|
||||||
"preferred job type",
|
|
||||||
],
|
|
||||||
lookingforaction: ["actions", "desired actions", "preferred activities"],
|
|
||||||
lookingforother: ["other preferences", "additional requirements"],
|
|
||||||
|
|
||||||
// Skills & Competencies
|
|
||||||
skills: ["skills", "competencies", "abilities", "technical skills"],
|
|
||||||
languageskills: ["languages", "language skills", "linguistic skills"],
|
|
||||||
knowhow: ["knowledge", "expertise", "know-how", "competence"],
|
|
||||||
myworkexperience: [
|
|
||||||
"work experience",
|
|
||||||
"professional experience",
|
|
||||||
"career experience",
|
|
||||||
],
|
|
||||||
|
|
||||||
// Personality & Profile
|
|
||||||
mbti: ["personality", "type", "profile", "MBTI", "personality type"],
|
|
||||||
mywords: ["keywords", "profile words", "descriptive words"],
|
|
||||||
thingsilike: ["likes", "preferences", "interests", "things I like"],
|
|
||||||
thingsidislike: [
|
|
||||||
"dislikes",
|
|
||||||
"avoid",
|
|
||||||
"not interested",
|
|
||||||
"things I dislike",
|
|
||||||
],
|
|
||||||
|
|
||||||
// Availability & Schedule
|
|
||||||
preferedworkinghours: [
|
|
||||||
"working hours",
|
|
||||||
"preferred hours",
|
|
||||||
"work schedule",
|
|
||||||
"availability",
|
|
||||||
],
|
|
||||||
notavailabletowork: [
|
|
||||||
"unavailable",
|
|
||||||
"not available",
|
|
||||||
"blocked times",
|
|
||||||
"unavailable days",
|
|
||||||
],
|
|
||||||
|
|
||||||
// Job Search Activity
|
|
||||||
myjobradar: [
|
|
||||||
"job radar",
|
|
||||||
"tracked jobs",
|
|
||||||
"job interests",
|
|
||||||
"monitored jobs",
|
|
||||||
],
|
|
||||||
jobadview: ["viewed jobs", "job views", "seen jobs"],
|
|
||||||
jobadnotinterested: ["not interested", "rejected jobs", "dismissed jobs"],
|
|
||||||
jobadapply: ["applied jobs", "applications", "job applications"],
|
|
||||||
jobadinvitedtoapply: [
|
|
||||||
"invitations",
|
|
||||||
"invited to apply",
|
|
||||||
"job invitations",
|
|
||||||
],
|
|
||||||
jobadsaved: ["saved jobs", "bookmarked jobs", "favorite jobs"],
|
|
||||||
|
|
||||||
// Dates & Timestamps
|
|
||||||
dt_create: [
|
|
||||||
"created",
|
|
||||||
"creation date",
|
|
||||||
"new",
|
|
||||||
"recent",
|
|
||||||
"since",
|
|
||||||
"registration date",
|
|
||||||
],
|
|
||||||
dt_update: ["updated", "last update", "modified", "last modified"],
|
|
||||||
matchinglastdate: ["last matching", "matching date", "last match"],
|
|
||||||
|
|
||||||
// Education & Training
|
|
||||||
educations: [
|
|
||||||
"education",
|
|
||||||
"degree",
|
|
||||||
"diploma",
|
|
||||||
"qualification",
|
|
||||||
"studies",
|
|
||||||
],
|
|
||||||
tipsadvice: ["tips", "advice", "articles", "guidance"],
|
|
||||||
receivecommercialtraining: ["commercial training", "sales training"],
|
|
||||||
receivejobandinterviewtips: [
|
|
||||||
"interview tips",
|
|
||||||
"job tips",
|
|
||||||
"career advice",
|
|
||||||
],
|
|
||||||
|
|
||||||
// Notifications & Communication
|
|
||||||
notificationformatches: ["match notifications", "matching alerts"],
|
|
||||||
notificationforsupermatches: [
|
|
||||||
"super match notifications",
|
|
||||||
"premium matches",
|
|
||||||
],
|
|
||||||
notificationinvitedtoapply: [
|
|
||||||
"application invitations",
|
|
||||||
"invite notifications",
|
|
||||||
],
|
|
||||||
notificationrecruitprocessupdate: [
|
|
||||||
"recruitment updates",
|
|
||||||
"process updates",
|
|
||||||
],
|
|
||||||
notificationupcominginterview: [
|
|
||||||
"interview notifications",
|
|
||||||
"upcoming interviews",
|
|
||||||
],
|
|
||||||
notificationdirectmessage: ["direct messages", "chat notifications"],
|
|
||||||
emailactivityreportweekly: ["weekly reports", "weekly emails"],
|
|
||||||
emailactivityreportbiweekly: ["biweekly reports", "biweekly emails"],
|
|
||||||
emailactivityreportmonthly: ["monthly reports", "monthly emails"],
|
|
||||||
emailpersonnalizedcontent: ["personalized content", "custom content"],
|
|
||||||
emailnewsletter: ["newsletter", "news updates"],
|
|
||||||
|
|
||||||
// External IDs
|
|
||||||
polemploiid: ["pole emploi", "unemployment office", "job center ID"],
|
|
||||||
|
|
||||||
// System Fields
|
|
||||||
owner: ["owner", "account owner"],
|
|
||||||
activequizz: ["active quiz", "current quiz", "quiz"],
|
|
||||||
};
|
};
|
||||||
|
|
||||||
if (commonMappings[fieldName]) {
|
|
||||||
synonyms.push(...commonMappings[fieldName]);
|
|
||||||
}
|
|
||||||
|
|
||||||
return synonyms;
|
|
||||||
}
|
}
|
||||||
|
|
||||||
mapNLToFields(nlTerms) {
|
// Check for sensitive/inappropriate requests
|
||||||
const mappedFields = [];
|
const sensitiveKeywords = [
|
||||||
|
"password",
|
||||||
|
"private",
|
||||||
|
"confidential",
|
||||||
|
"secret",
|
||||||
|
"admin",
|
||||||
|
"delete",
|
||||||
|
"remove",
|
||||||
|
"drop",
|
||||||
|
"destroy",
|
||||||
|
"hack",
|
||||||
|
];
|
||||||
|
|
||||||
nlTerms.forEach((term) => {
|
const hasSensitiveRequest = sensitiveKeywords.some((keyword) =>
|
||||||
const normalizedTerm = term.toLowerCase();
|
query.includes(keyword)
|
||||||
const mapping = this.fieldMappings[normalizedTerm];
|
);
|
||||||
|
|
||||||
if (mapping) {
|
if (hasSensitiveRequest) {
|
||||||
if (typeof mapping === "string") {
|
return {
|
||||||
mappedFields.push(mapping);
|
valid: false,
|
||||||
} else if (mapping.field) {
|
reason: "Query contains inappropriate or sensitive terms",
|
||||||
mappedFields.push(mapping.field);
|
suggestion:
|
||||||
}
|
"Please rephrase your request with appropriate business terms",
|
||||||
}
|
};
|
||||||
});
|
|
||||||
|
|
||||||
return [...new Set(mappedFields)]; // Remove duplicates
|
|
||||||
}
|
}
|
||||||
|
|
||||||
getRecruiterReadableFields() {
|
return { valid: true };
|
||||||
if (!this.seekersSchema?.apxaccessrights?.recruiters?.R) {
|
|
||||||
// Fallback to basic fields
|
|
||||||
return ["alias", "email", "seekstatus", "seekworkingyear"];
|
|
||||||
}
|
|
||||||
return this.seekersSchema.apxaccessrights.recruiters.R;
|
|
||||||
}
|
|
||||||
|
|
||||||
getAllSeekersFields() {
|
|
||||||
if (!this.seekersSchema?.properties) return [];
|
|
||||||
return Object.keys(this.seekersSchema.properties);
|
|
||||||
}
|
|
||||||
|
|
||||||
getAvailableIndexes() {
|
|
||||||
return Object.keys(this.indexMappings);
|
|
||||||
}
|
|
||||||
|
|
||||||
getIndexByField(fieldName) {
|
|
||||||
const index = Object.values(this.indexMappings).find(
|
|
||||||
(idx) => idx.keyval === fieldName
|
|
||||||
);
|
|
||||||
return index ? `idx.${index.name}` : null;
|
|
||||||
}
|
|
||||||
}
|
}
|
||||||
|
|
||||||
// Initialize schema mapper
|
// ---- Multi-Object Query Processing ----
|
||||||
const schemaMapper = new SchemaMapper(SCHEMAS);
|
function detectTargetObject(nlQuery) {
|
||||||
|
console.log(`🔍 Analyzing query: "${nlQuery}"`);
|
||||||
|
|
||||||
const SEEKERS_FIELDS_FROM_SCHEMA = schemaMapper.getAllSeekersFields();
|
// Use mapping manager to detect target object
|
||||||
|
const detectedObjects = mappingManager.detectObjectFromQuery(nlQuery);
|
||||||
|
|
||||||
console.log(
|
if (detectedObjects.length === 0) {
|
||||||
`🔍 Available seekers fields: ${SEEKERS_FIELDS_FROM_SCHEMA.slice(0, 10).join(
|
return {
|
||||||
", "
|
object: "seekers", // Default fallback
|
||||||
)}${
|
confidence: 0.1,
|
||||||
SEEKERS_FIELDS_FROM_SCHEMA.length > 10
|
reason: "No specific object detected, defaulting to seekers",
|
||||||
? `... (${SEEKERS_FIELDS_FROM_SCHEMA.length} total)`
|
};
|
||||||
: ""
|
}
|
||||||
}`
|
|
||||||
);
|
|
||||||
|
|
||||||
// ---- Minimal mapping config (for prompting + default fields) ----
|
// Sort by confidence and return the best match
|
||||||
const seekersMapping = {
|
detectedObjects.sort((a, b) => b.confidence - a.confidence);
|
||||||
object: "seekers",
|
const bestMatch = detectedObjects[0];
|
||||||
defaultReadableFields: schemaMapper.getRecruiterReadableFields().slice(0, 5), // First 5 readable fields
|
|
||||||
};
|
console.log(
|
||||||
|
`🎯 Detected object: ${bestMatch.object} (confidence: ${bestMatch.confidence})`
|
||||||
|
);
|
||||||
|
console.log(` Reason: ${bestMatch.reason}`);
|
||||||
|
|
||||||
|
// Check if data is available for this object
|
||||||
|
const availability = mappingManager.dataAvailability.get(bestMatch.object);
|
||||||
|
if (!availability?.dataAvailable) {
|
||||||
|
console.log(
|
||||||
|
`⚠️ No data available for ${bestMatch.object}, checking alternatives...`
|
||||||
|
);
|
||||||
|
|
||||||
|
// Find alternative with available data
|
||||||
|
const alternativeWithData = detectedObjects.find((detection) => {
|
||||||
|
const alt = mappingManager.dataAvailability.get(detection.object);
|
||||||
|
return alt?.dataAvailable;
|
||||||
|
});
|
||||||
|
|
||||||
|
if (alternativeWithData) {
|
||||||
|
console.log(`✅ Using alternative: ${alternativeWithData.object}`);
|
||||||
|
return alternativeWithData;
|
||||||
|
} else {
|
||||||
|
return {
|
||||||
|
object: bestMatch.object,
|
||||||
|
confidence: bestMatch.confidence,
|
||||||
|
reason: bestMatch.reason,
|
||||||
|
dataUnavailable: true,
|
||||||
|
};
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
return bestMatch;
|
||||||
|
}
|
||||||
|
|
||||||
|
// ---- Dynamic Query Schema Generation ----
|
||||||
|
function getObjectMapping(objectName) {
|
||||||
|
return mappingManager.mappings.get(objectName);
|
||||||
|
}
|
||||||
|
|
||||||
|
function getReadableFields(objectName) {
|
||||||
|
const mapping = getObjectMapping(objectName);
|
||||||
|
if (!mapping?.available) return [];
|
||||||
|
|
||||||
|
// Try to get readable fields from access rights (for recruiters, seekers, etc.)
|
||||||
|
const accessRights = mapping.accessRights;
|
||||||
|
if (accessRights) {
|
||||||
|
// For seekers, check recruiters.R
|
||||||
|
if (
|
||||||
|
accessRights.recruiters?.R &&
|
||||||
|
Array.isArray(accessRights.recruiters.R)
|
||||||
|
) {
|
||||||
|
return accessRights.recruiters.R;
|
||||||
|
}
|
||||||
|
// For jobads/recruiters, check seekers.R
|
||||||
|
if (accessRights.seekers?.R && Array.isArray(accessRights.seekers.R)) {
|
||||||
|
return accessRights.seekers.R;
|
||||||
|
}
|
||||||
|
// For other objects, check owner.R
|
||||||
|
if (accessRights.owner?.R && Array.isArray(accessRights.owner.R)) {
|
||||||
|
return accessRights.owner.R;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
// Fallback to all available properties (first 10 for safety)
|
||||||
|
return mapping?.properties
|
||||||
|
? Object.keys(mapping.properties).slice(0, 10)
|
||||||
|
: [];
|
||||||
|
}
|
||||||
|
|
||||||
|
function getAllObjectFields(objectName) {
|
||||||
|
const mapping = getObjectMapping(objectName);
|
||||||
|
if (!mapping?.available) return [];
|
||||||
|
return mapping?.properties ? Object.keys(mapping.properties) : [];
|
||||||
|
}
|
||||||
|
|
||||||
|
function getObjectFallbackFields(objectName) {
|
||||||
|
// Object-specific fallback fields when no readable fields are available
|
||||||
|
const fallbacks = {
|
||||||
|
seekers: ["alias", "email"],
|
||||||
|
jobads: ["jobadid", "jobtitle"],
|
||||||
|
recruiters: ["alias", "email"],
|
||||||
|
persons: ["alias", "email"],
|
||||||
|
sirets: ["alias", "name"],
|
||||||
|
jobsteps: ["alias", "name"],
|
||||||
|
jobtitles: ["jobtitleid", "name"],
|
||||||
|
};
|
||||||
|
|
||||||
|
return fallbacks[objectName] || ["id", "name"];
|
||||||
|
}
|
||||||
|
|
||||||
// ---- JSON Schema for Structured Outputs (no zod, no oneOf) ----
|
// ---- JSON Schema for Structured Outputs (no zod, no oneOf) ----
|
||||||
function buildResponseJsonSchema() {
|
function buildResponseJsonSchema(targetObject) {
|
||||||
const recruiterReadableFields = schemaMapper.getRecruiterReadableFields();
|
const availableObjects = Array.from(mappingManager.mappings.keys());
|
||||||
|
const readableFields = getReadableFields(targetObject);
|
||||||
|
|
||||||
return {
|
return {
|
||||||
type: "object",
|
type: "object",
|
||||||
additionalProperties: false,
|
additionalProperties: false,
|
||||||
properties: {
|
properties: {
|
||||||
object: { type: "string", enum: ["seekers"] },
|
object: {
|
||||||
|
type: "string",
|
||||||
|
enum: availableObjects.length > 0 ? availableObjects : ["seekers"],
|
||||||
|
},
|
||||||
condition: { type: "array", items: { type: "string" }, minItems: 1 },
|
condition: { type: "array", items: { type: "string" }, minItems: 1 },
|
||||||
fields: {
|
fields: {
|
||||||
type: "array",
|
type: "array",
|
||||||
items: {
|
items: {
|
||||||
type: "string",
|
type: "string",
|
||||||
enum: recruiterReadableFields,
|
enum:
|
||||||
|
readableFields.length > 0
|
||||||
|
? readableFields
|
||||||
|
: getObjectFallbackFields(targetObject),
|
||||||
},
|
},
|
||||||
minItems: 1,
|
minItems: 1,
|
||||||
},
|
},
|
||||||
@@ -449,10 +244,21 @@ function buildResponseJsonSchema() {
|
|||||||
}
|
}
|
||||||
|
|
||||||
// ---- Prompt builders ----
|
// ---- Prompt builders ----
|
||||||
function systemPrompt() {
|
function systemPrompt(targetObject) {
|
||||||
const availableFields = schemaMapper.getAllSeekersFields();
|
const objectMapping = getObjectMapping(targetObject);
|
||||||
const recruiterReadableFields = schemaMapper.getRecruiterReadableFields();
|
const availableFields = getAllObjectFields(targetObject);
|
||||||
const availableIndexes = schemaMapper.getAvailableIndexes();
|
const readableFields = getReadableFields(targetObject);
|
||||||
|
const availableObjects = Array.from(mappingManager.mappings.keys());
|
||||||
|
|
||||||
|
// Get object-specific synonyms from mapping
|
||||||
|
const synonyms = objectMapping?.synonyms || {};
|
||||||
|
const synonymList = Object.entries(synonyms)
|
||||||
|
.slice(0, 10)
|
||||||
|
.map(([field, syns]) => {
|
||||||
|
const synArray = Array.isArray(syns) ? syns : [syns];
|
||||||
|
return `- '${synArray.slice(0, 2).join("', '")}' → ${field}`;
|
||||||
|
})
|
||||||
|
.join("\n ");
|
||||||
|
|
||||||
return [
|
return [
|
||||||
"You convert a natural language request into an ODMDB search payload.",
|
"You convert a natural language request into an ODMDB search payload.",
|
||||||
@@ -463,45 +269,35 @@ function systemPrompt() {
|
|||||||
"- idx.<indexName>(value) - for indexed fields",
|
"- idx.<indexName>(value) - for indexed fields",
|
||||||
"- prop.<field>(operator:value) - for direct property queries",
|
"- prop.<field>(operator:value) - for direct property queries",
|
||||||
"",
|
"",
|
||||||
"Available seekers fields:",
|
`Available objects: ${availableObjects.join(", ")}`,
|
||||||
|
`Target object: ${targetObject}`,
|
||||||
|
"",
|
||||||
|
`Available ${targetObject} fields:`,
|
||||||
availableFields.slice(0, 15).join(", ") +
|
availableFields.slice(0, 15).join(", ") +
|
||||||
(availableFields.length > 15 ? "..." : ""),
|
(availableFields.length > 15 ? "..." : ""),
|
||||||
"",
|
"",
|
||||||
"Available indexes for optimization:",
|
`Readable fields for ${targetObject} (use these for field selection):`,
|
||||||
availableIndexes.join(", "),
|
readableFields.join(", "),
|
||||||
"",
|
|
||||||
"Recruiter-readable fields (use these for field selection):",
|
|
||||||
recruiterReadableFields.join(", "),
|
|
||||||
"",
|
"",
|
||||||
"Field mappings for natural language:",
|
"Field mappings for natural language:",
|
||||||
"- 'email', 'contact info' → email",
|
synonymList || "- No specific mappings available",
|
||||||
"- 'experience', 'years of experience' → seekworkingyear",
|
|
||||||
"- 'job titles', 'positions', 'roles' → seekjobtitleexperience",
|
|
||||||
"- 'status', 'availability' → seekstatus",
|
|
||||||
"- 'salary', 'pay', 'compensation' → salaryexpectation",
|
|
||||||
"- 'location', 'where' → seeklocation",
|
|
||||||
"- 'skills', 'competencies' → skills",
|
|
||||||
"- 'languages' → languageskills",
|
|
||||||
"- 'personality', 'MBTI' → mbti",
|
|
||||||
"- 'new/recent' → dt_create (use prop.dt_create(>=:YYYY-MM-DD))",
|
|
||||||
"",
|
"",
|
||||||
"Status value mappings:",
|
"Date handling:",
|
||||||
"- 'urgent', 'urgently', 'ASAP', 'quickly' → startasap",
|
"- 'new/recent' → dt_create (use prop.dt_create(>=:YYYY-MM-DD))",
|
||||||
"- 'no rush', 'taking time', 'leisurely' → norush",
|
"- 'updated' → dt_update",
|
||||||
"- 'not looking', 'not active' → notlooking",
|
|
||||||
"",
|
"",
|
||||||
"Rules:",
|
"Rules:",
|
||||||
"- Object must be 'seekers'.",
|
`- Object should be '${targetObject}' unless query clearly indicates another object`,
|
||||||
"- Use indexes when possible (idx.seekstatus_alias for status queries)",
|
"- Use indexes when available for better performance",
|
||||||
"- For date filters, use prop.dt_create with absolute dates",
|
"- For date filters, use prop.dt_create/dt_update with absolute dates",
|
||||||
"- Only return recruiter-readable fields in 'fields' array",
|
"- Only return readable fields in 'fields' array",
|
||||||
`- Default fields if request is generic: ${recruiterReadableFields
|
`- Default fields if request is generic: ${readableFields
|
||||||
.slice(0, 5)
|
.slice(0, 5)
|
||||||
.join(", ")}`,
|
.join(", ")}`,
|
||||||
"",
|
"",
|
||||||
"Timezone is Europe/Paris. Today is 2025-10-14.",
|
"Timezone is Europe/Paris. Today is 2025-10-15.",
|
||||||
"Interpret 'last week' as now minus 7 days → 2025-10-07.",
|
"Interpret 'last week' as now minus 7 days → 2025-10-08.",
|
||||||
"Interpret 'yesterday' as → 2025-10-13.",
|
"Interpret 'yesterday' as → 2025-10-14.",
|
||||||
].join("\n");
|
].join("\n");
|
||||||
}
|
}
|
||||||
function userPrompt(nl) {
|
function userPrompt(nl) {
|
||||||
@@ -511,18 +307,18 @@ function userPrompt(nl) {
|
|||||||
// ---- OpenAI call using Responses API (text.format) ----
|
// ---- OpenAI call using Responses API (text.format) ----
|
||||||
const client = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
|
const client = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
|
||||||
|
|
||||||
async function inferQuery(nlText) {
|
async function inferQuery(nlText, targetObject) {
|
||||||
const resp = await client.responses.create({
|
const resp = await client.responses.create({
|
||||||
model: MODEL,
|
model: MODEL,
|
||||||
input: [
|
input: [
|
||||||
{ role: "system", content: systemPrompt() },
|
{ role: "system", content: systemPrompt(targetObject) },
|
||||||
{ role: "user", content: userPrompt(nlText) },
|
{ role: "user", content: userPrompt(nlText) },
|
||||||
],
|
],
|
||||||
text: {
|
text: {
|
||||||
format: {
|
format: {
|
||||||
name: "OdmdbQuery",
|
name: "OdmdbQuery",
|
||||||
type: "json_schema",
|
type: "json_schema",
|
||||||
schema: buildResponseJsonSchema(),
|
schema: buildResponseJsonSchema(targetObject),
|
||||||
strict: true,
|
strict: true,
|
||||||
},
|
},
|
||||||
},
|
},
|
||||||
@@ -540,12 +336,20 @@ async function inferQuery(nlText) {
|
|||||||
}
|
}
|
||||||
|
|
||||||
// ---- Validate using the ODMDB schema (not zod) ----
|
// ---- Validate using the ODMDB schema (not zod) ----
|
||||||
function validateWithOdmdbSchema(candidate) {
|
function validateWithOdmdbSchema(candidate, targetObject) {
|
||||||
// Basic shape checks (already enforced by Structured Outputs, but keep defensive)
|
// Basic shape checks (already enforced by Structured Outputs, but keep defensive)
|
||||||
if (!candidate || typeof candidate !== "object")
|
if (!candidate || typeof candidate !== "object")
|
||||||
throw new Error("Invalid response (not an object).");
|
throw new Error("Invalid response (not an object).");
|
||||||
if (candidate.object !== "seekers")
|
|
||||||
throw new Error("Invalid object; must be 'seekers'.");
|
const availableObjects = Array.from(mappingManager.mappings.keys());
|
||||||
|
if (!availableObjects.includes(candidate.object)) {
|
||||||
|
throw new Error(
|
||||||
|
`Invalid object '${
|
||||||
|
candidate.object
|
||||||
|
}'; must be one of: ${availableObjects.join(", ")}`
|
||||||
|
);
|
||||||
|
}
|
||||||
|
|
||||||
if (!Array.isArray(candidate.condition) || candidate.condition.length === 0) {
|
if (!Array.isArray(candidate.condition) || candidate.condition.length === 0) {
|
||||||
throw new Error(
|
throw new Error(
|
||||||
"Invalid 'condition'; must be a non-empty array of strings."
|
"Invalid 'condition'; must be a non-empty array of strings."
|
||||||
@@ -555,17 +359,19 @@ function validateWithOdmdbSchema(candidate) {
|
|||||||
throw new Error("Invalid 'fields'; must be a non-empty array of strings.");
|
throw new Error("Invalid 'fields'; must be a non-empty array of strings.");
|
||||||
}
|
}
|
||||||
|
|
||||||
// Validate fields against schema
|
// Validate fields against schema for the specific object
|
||||||
const availableFields = schemaMapper.getAllSeekersFields();
|
const availableFields = getAllObjectFields(candidate.object);
|
||||||
const recruiterReadableFields = schemaMapper.getRecruiterReadableFields();
|
const readableFields = getReadableFields(candidate.object);
|
||||||
|
|
||||||
for (const field of candidate.fields) {
|
for (const field of candidate.fields) {
|
||||||
if (!availableFields.includes(field)) {
|
if (!availableFields.includes(field)) {
|
||||||
throw new Error(`Invalid field '${field}'; not found in seekers schema.`);
|
throw new Error(
|
||||||
|
`Invalid field '${field}'; not found in ${candidate.object} schema.`
|
||||||
|
);
|
||||||
}
|
}
|
||||||
if (!recruiterReadableFields.includes(field)) {
|
if (!readableFields.includes(field)) {
|
||||||
console.warn(
|
console.warn(
|
||||||
`Warning: Field '${field}' may not be readable by recruiters.`
|
`Warning: Field '${field}' may not be readable for ${candidate.object}.`
|
||||||
);
|
);
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
@@ -580,34 +386,33 @@ function validateWithOdmdbSchema(candidate) {
|
|||||||
if (!tokenOK || !ascii) throw new Error(`Malformed condition: ${c}`);
|
if (!tokenOK || !ascii) throw new Error(`Malformed condition: ${c}`);
|
||||||
}
|
}
|
||||||
|
|
||||||
// Field existence check against ODMDB custom schema (seekers properties)
|
// Additional field validation and cleanup
|
||||||
if (SEEKERS_FIELDS_FROM_SCHEMA.length) {
|
const objectAvailableFields = getAllObjectFields(candidate.object);
|
||||||
|
if (objectAvailableFields.length) {
|
||||||
const unknown = candidate.fields.filter(
|
const unknown = candidate.fields.filter(
|
||||||
(f) => !SEEKERS_FIELDS_FROM_SCHEMA.includes(f)
|
(f) => !objectAvailableFields.includes(f)
|
||||||
);
|
);
|
||||||
if (unknown.length) {
|
if (unknown.length) {
|
||||||
// Drop unknown but continue (PoC behavior)
|
// Drop unknown but continue (PoC behavior)
|
||||||
console.warn(
|
console.warn(
|
||||||
"⚠️ Dropping unknown fields (not in seekers schema):",
|
`⚠️ Dropping unknown fields (not in ${candidate.object} schema):`,
|
||||||
unknown
|
unknown
|
||||||
);
|
);
|
||||||
candidate.fields = candidate.fields.filter((f) =>
|
candidate.fields = candidate.fields.filter((f) =>
|
||||||
SEEKERS_FIELDS_FROM_SCHEMA.includes(f)
|
objectAvailableFields.includes(f)
|
||||||
);
|
);
|
||||||
if (!candidate.fields.length) {
|
if (!candidate.fields.length) {
|
||||||
// If all dropped, fallback to default shortlist intersected with schema
|
// If all dropped, fallback to object-specific default fields
|
||||||
const fallback = seekersMapping.defaultReadableFields.filter((f) =>
|
const fallback = getObjectFallbackFields(candidate.object);
|
||||||
SEEKERS_FIELDS_FROM_SCHEMA.includes(f)
|
|
||||||
);
|
|
||||||
if (!fallback.length)
|
|
||||||
throw new Error(
|
|
||||||
"No valid fields remain after validation and no fallback available."
|
|
||||||
);
|
|
||||||
candidate.fields = fallback;
|
candidate.fields = fallback;
|
||||||
|
console.warn(
|
||||||
|
`🔄 Using fallback fields for ${candidate.object}:`,
|
||||||
|
fallback
|
||||||
|
);
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
} else {
|
} else {
|
||||||
// If we can't read the schema (main.json shape unknown), at least ensure strings & dedupe
|
// If we can't read the schema, at least ensure strings & dedupe
|
||||||
candidate.fields = [
|
candidate.fields = [
|
||||||
...new Set(
|
...new Set(
|
||||||
candidate.fields.filter((f) => typeof f === "string" && f.trim())
|
candidate.fields.filter((f) => typeof f === "string" && f.trim())
|
||||||
@@ -769,11 +574,12 @@ async function processResults(results, jqFilter = ".") {
|
|||||||
throw new Error("Missing OPENAI_API_KEY env var.");
|
throw new Error("Missing OPENAI_API_KEY env var.");
|
||||||
|
|
||||||
console.log(`🤖 Processing NL query: "${NL_QUERY}"`);
|
console.log(`🤖 Processing NL query: "${NL_QUERY}"`);
|
||||||
|
console.log(`🎯 Target object: ${TEST_OBJECT}`);
|
||||||
console.log("=".repeat(60));
|
console.log("=".repeat(60));
|
||||||
|
|
||||||
// Step 1: Generate ODMDB query from natural language
|
// Step 1: Generate ODMDB query from natural language
|
||||||
const out = await inferQuery(NL_QUERY);
|
const out = await inferQuery(NL_QUERY, TEST_OBJECT);
|
||||||
const validated = validateWithOdmdbSchema(out);
|
const validated = validateWithOdmdbSchema(out, TEST_OBJECT);
|
||||||
|
|
||||||
console.log("✅ Generated ODMDB Query:");
|
console.log("✅ Generated ODMDB Query:");
|
||||||
const generatedQuery = {
|
const generatedQuery = {
|
||||||
|
|||||||
38
verify-mapping.js
Normal file
38
verify-mapping.js
Normal file
@@ -0,0 +1,38 @@
|
|||||||
|
import { ODMDBMappingManager } from "./schema-mappings/mapping-manager.js";
|
||||||
|
|
||||||
|
const mgr = new ODMDBMappingManager();
|
||||||
|
const seekersMapping = mgr.getMapping("seekers");
|
||||||
|
|
||||||
|
console.log("=== SEEKERS MAPPING VERIFICATION ===");
|
||||||
|
console.log("Available:", seekersMapping?.available);
|
||||||
|
console.log("Property count:", seekersMapping?.propertyCount);
|
||||||
|
console.log("");
|
||||||
|
|
||||||
|
console.log("=== INDEXES ===");
|
||||||
|
console.log("Indexes from schema:", seekersMapping?.indexes?.length || 0);
|
||||||
|
seekersMapping?.indexes?.forEach((idx) => {
|
||||||
|
console.log(`- ${idx.name} (${idx.type}) on ${idx.keyval}`);
|
||||||
|
});
|
||||||
|
console.log("");
|
||||||
|
|
||||||
|
console.log("=== ACCESS RIGHTS ===");
|
||||||
|
console.log(
|
||||||
|
"Recruiters readable fields:",
|
||||||
|
seekersMapping?.accessRights?.recruiters?.R?.length || 0
|
||||||
|
);
|
||||||
|
console.log(
|
||||||
|
"First 10 readable fields:",
|
||||||
|
seekersMapping?.accessRights?.recruiters?.R?.slice(0, 10) || []
|
||||||
|
);
|
||||||
|
console.log("");
|
||||||
|
|
||||||
|
console.log("=== PROPERTIES SAMPLE ===");
|
||||||
|
const propKeys = Object.keys(seekersMapping?.properties || {});
|
||||||
|
console.log("Total properties:", propKeys.length);
|
||||||
|
console.log("First 10 properties:", propKeys.slice(0, 10));
|
||||||
|
console.log("");
|
||||||
|
|
||||||
|
console.log("=== SYNONYMS SAMPLE ===");
|
||||||
|
const synonymKeys = Object.keys(seekersMapping?.synonyms || {});
|
||||||
|
console.log("Total synonyms:", synonymKeys.length);
|
||||||
|
console.log("First 10 synonyms:", synonymKeys.slice(0, 10));
|
||||||
Reference in New Issue
Block a user