This is a Proof of Concept (PoC) that demonstrates the conversion of natural language queries into ODMDB search queries using OpenAI's structured output API.

Current Status

⚠️ 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.

Features

Natural Language Processing: Converts human questions into structured ODMDB queries
Real ODMDB Integration: Works with actual ODMDB data from ../smatchitObjectOdmdb/
Schema-Based Mapping: Uses actual seekers.json schema for accurate field mapping (62 properties)
Local Data Execution: Processes queries against local seeker files in objects/seekers/itm/
OpenAI Structured Output: Ensures reliable JSON query generation
Query Validation: Validates generated queries against real ODMDB schema rules
jq Integration: Powerful result processing, filtering, and CSV export capabilities

Prerequisites

Node.js (v16 or higher)
OpenAI API key

Installation

Make sure you have the ODMDB data structure available:

../smatchitObjectOdmdb/
├── schema/
│   └── seekers.json       # Seeker schema (62 properties)
└── objects/
    └── seekers/
        └── itm/           # Individual seeker JSON files

Install dependencies:
```
npm install
```

Set your OpenAI API key:

export OPENAI_API_KEY=sk-your-api-key-here

Usage

Running the PoC

Query Generation Only (Default):

npm start

Query Generation + Execution:

EXECUTE_QUERY=true npm start


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.

### Changing the Query

To test different natural language queries, edit the `NL_QUERY` constant in `poc.js`:

```javascript
// Line 16 in poc.js
const NL_QUERY = "your natural language query here";

Example Queries

Status-based queries:

"show me seekers with status startasap and their email and experience"
"find seekers looking for jobs urgently with their skills"

Date-based queries:

"give me new seekers since last week with email and experience"
"show me seekers from yesterday with their skills"

Field-specific queries:

"find seekers with job titles and salary expectations"
"show me seeker locations and availability"

Supported filter types:

Status filtering: seekstatus (startasap, norush, notlooking)
Date filtering: dt_create with date ranges
Index optimization: Uses ODMDB indexes for efficient queries

This demonstrates various jq operations including:

Basic data formatting and field selection
CSV conversion from JSON
Advanced filtering and transformations
Statistical summaries and aggregations

Environment Variables

OPENAI_API_KEY - Your OpenAI API key (required)
EXECUTE_QUERY - Set to "true" to execute queries against ODMDB (default: false)
ODMDB_BASE_URL - ODMDB server URL (default: http://localhost:3000)
ODMDB_TRIBE - ODMDB tribe name (default: smatchit)
OPENAI_MODEL - OpenAI model to use (default: gpt-5)

Output Format

Query Generation: The PoC generates ODMDB queries in this format:

{
  "object": "seekers",
  "condition": ["prop.dt_create(>=:2025-10-06)"],
  "fields": ["alias", "email", "seekworkingyear"]
}

ODMDB DSL Support

The PoC understands and generates these ODMDB DSL patterns:

Property queries: prop.<field>(operator:value)
Index queries: idx.<indexName>(value)
Join queries: join(remoteObject:localKey:remoteProp:operator:value)

Field Mappings

Currently supports mapping for seekers object:

email → email
experience → seekworkingyear
job titles → seekjobtitleexperience
status → seekstatus

Schema Context

The PoC can optionally load schema files for context:

main.json - Combined schema definitions
lg.json - Localization/language mappings

Limitations

Seekers only: Other ODMDB objects (jobads, recruiters, etc.) are not yet implemented
No execution: Only generates queries, doesn't execute them against ODMDB
Hardcoded query: Single query per run (no interactive mode)
Basic validation: Limited DSL syntax validation

Next Steps

Add support for other ODMDB objects (jobads, recruiters, etc.)
Interactive CLI for multiple queries
Integration with actual ODMDB backend
Enhanced field mapping and validation
Multi-turn conversation support

Files

poc.js - Main PoC implementation
package.json - Dependencies and scripts
main.json - Optional schema context (if available)
lg.json - Optional localization context (if available)