⚡ Spector — The AI Memory Engine¶

from spector_client import SpectorClient, MemoryTier

# Connect to running daemon or local test instance
client = SpectorClient.builder().with_rest("http://localhost:7070").build()

# 1. Remember with affective & contextual metadata
record = client.memory.remember(
    text="User is designing a low-latency RAG system with pgvector and Spector",
    tier=MemoryTier.SEMANTIC,
    tags=["rag", "architecture", "database"],
    interest=0.9,
    valence=1,
)
print(f"Memory recorded: {record.get('id', 'stored')}")

# 2. Recall with associative cognitive scoring
memories = client.memory.recall("database architecture preferences", top_k=3)
for m in memories:
    print(f"[{m.id}] score={m.score:.4f} | {m.text}")

import { SpectorClient, MemoryTier } from '@spectrayan/spector-client';

const client = SpectorClient.createDefault('http://localhost:7070');

// 1. Remember with contextual tags
const record = await client.memory.remember({
  text: 'User prefers dark mode, high contrast, and TypeScript examples',
  tier: MemoryTier.SEMANTIC,
  tags: ['preferences', 'ui'],
  interest: 0.85,
});
console.log(`Stored engram: ${record.id}`);

// 2. Recall with 6-phase scoring
const results = await client.memory.recall('user ui preferences', { topK: 5 });
results.forEach(m => console.log(`[${m.id}] ${m.text}`));

import com.spectrayan.spector.client.SpectorClient;
import java.util.List;

// Lightweight client SDK — zero vector/Panama preview flags required
try (var client = SpectorClient.builder().baseUri("http://localhost:7070").build()) {
    // 1. Remember
    var record = client.memory().store(
        "User prefers concise responses with architectural diagrams",
        List.of("preferences", "formatting")
    );
    System.out.println("Stored engram: " + record.getId());

    // 2. Recall
    var results = client.memory().recall("user formatting preferences", 5);
    results.forEach(m -> System.out.println(m.getText()));
}

# 1. Remember
curl -X POST http://localhost:7070/api/v1/memory/remember \
  -H "Content-Type: application/json" \
  -d '{
    "text": "User prefers dark mode and high-contrast syntax highlighting",
    "tier": "SEMANTIC",
    "tags": "preferences,ui",
    "interest": 0.9,
    "valence": 1
  }'

# 2. Recall
curl -X POST http://localhost:7070/api/v1/memory/recall \
  -H "Content-Type: application/json" \
  -d '{"query": "user ui preferences", "topK": 5}'

# 1. Remember with cognitive metadata
spector memory remember \
  --id "pref-dark-mode" \
  --text "User prefers dark mode and high-contrast syntax highlighting" \
  --tier SEMANTIC \
  --tags "preferences,ui" \
  --interest 0.9 \
  --valence 1

# 2. Recall with 6-phase fused cognitive scoring
spector memory recall "user ui preferences" --top-k 5 --profile BALANCED