[WIP] making a working demo for all possible seekers questions

README.md

@@ -8,11 +8,13 @@ This is a **Proof of Concept (PoC)** that demonstrates the conversion of natural
 
 ## Features
 
-- Converts natural language requests into ODMDB DSL queries
+- **Natural Language Processing**: Converts human questions into structured ODMDB queries
-- Handles temporal queries ("new seekers since last week")
+- **Real ODMDB Integration**: Works with actual ODMDB data from `../smatchitObjectOdmdb/`
-- Maps human-readable field names to schema fields
+- **Schema-Based Mapping**: Uses actual seekers.json schema for accurate field mapping (62 properties)
-- Validates output using Zod schema validation
+- **Local Data Execution**: Processes queries against local seeker files in `objects/seekers/itm/`
-- Uses OpenAI's structured output for reliable JSON generation
+- **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
 
@@ -21,13 +23,24 @@ This is a **Proof of Concept (PoC)** that demonstrates the conversion of natural
 
 ## Installation
 
-1. Install dependencies:
+1. Make sure you have the ODMDB data structure available:
+
+   ```
+   ../smatchitObjectOdmdb/
+   ├── schema/
+   │   └── seekers.json       # Seeker schema (62 properties)
+   └── objects/
+       └── seekers/
+           └── itm/           # Individual seeker JSON files
+   ```
+
+2. Install dependencies:
 
    ```bash
    npm install
    ```
 
-2. Set your OpenAI API key:
+3. Set your OpenAI API key:
    ```bash
    export OPENAI_API_KEY=sk-your-api-key-here
    ```
@@ -48,10 +61,6 @@ npm start
 EXECUTE_QUERY=true npm start
 ```
 
-**With Custom ODMDB Server:**
-
-```bash
-EXECUTE_QUERY=true ODMDB_BASE_URL=http://localhost:8080 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.
@@ -67,17 +76,28 @@ 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"`
-- `"find recent seekers with job titles and salary expectations"`
 - `"show me seekers from yesterday with their skills"`
 
-### Testing jq Processing
+**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
 
-To test the jq processing capabilities with mock data:
 
-```bash
-node test-jq.js
-```
 
 This demonstrates various jq operations including:
 

demo.js

@@ -0,0 +1,101 @@
+#!/usr/bin/env node
+
+// Demo script showing different ODMDB query types with real data
+import fs from "node:fs";
+
+console.log("🚀 ODMDB NL to Query Demo");
+console.log("=".repeat(50));
+
+// Sample queries to demonstrate
+const queries = [
+  {
+    nl: "show me seekers with status startasap and their email and experience",
+    description: "Status-based filtering with field selection",
+    expectedCondition: "idx.seekstatus_alias(startasap)",
+    expectedFields: ["email", "seekworkingyear"],
+  },
+  {
+    nl: "find seekers looking for jobs urgently with salary expectations",
+    description: "Status synonym mapping + salary field",
+    expectedCondition: "idx.seekstatus_alias(startasap)",
+    expectedFields: ["salaryexpectation", "salaryunit"],
+  },
+  {
+    nl: "give me seekers from last month with their locations",
+    description: "Date-based filtering + location fields",
+    expectedCondition: "prop.dt_create(>=:2025-09-14)",
+    expectedFields: ["seeklocation"],
+  },
+];
+
+console.log("📋 Demo Queries:");
+queries.forEach((query, i) => {
+  console.log(`\n${i + 1}. "${query.nl}"`);
+  console.log(`   Purpose: ${query.description}`);
+  console.log(`   Expected DSL: ${query.expectedCondition}`);
+  console.log(`   Expected Fields: ${query.expectedFields.join(", ")}`);
+});
+
+console.log("\n💡 To test these queries:");
+console.log("1. Edit the NL_QUERY constant in poc.js");
+console.log("2. Run: EXECUTE_QUERY=true npm start");
+
+console.log("\n📊 Current ODMDB Status:");
+
+// 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✅ Demo complete!");

poc.js

@@ -23,7 +23,7 @@ const EXECUTE_QUERY = process.env.EXECUTE_QUERY === "true"; // Set to "true" to
 
 // Hardcoded NL query for the PoC (no multi-turn)
 const NL_QUERY =
-  "give me new seekers since last week with email and experience";
+  "show me seekers with status startasap and their email and experience";
 
 // ---- Load schemas (safe) ----
 function loadJsonSafe(path) {
@@ -603,7 +603,7 @@ async function processResults(results, jqFilter = ".") {
         console.log("\n📋 Results Summary:");
         const summary = await processResults(
           results,
-          `.[0:3] | map({alias, email, seekstatus})`
+          `.[0:3] | map({email, seekworkingyear})`
         );
         console.log(JSON.stringify(summary, null, 2));
 
@@ -617,8 +617,8 @@ async function processResults(results, jqFilter = ".") {
         const csvData = await processResults(
           results,
           `
-          map([.alias // "N/A", .email // "N/A", .seekstatus // "N/A"]) | 
+          map([.email // "N/A", .seekworkingyear // "N/A"]) | 
-          ["alias","email","status"] as $header | 
+          ["email","experience"] as $header | 
           [$header] + .[0:5] | 
           .[] | @csv
         `