agentis/dist/memory/VectorMemoryClient.js

A TypeScript framework for building sophisticated multi-agent systems

"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.VectorMemoryClient = void 0;
const SupabaseClient_1 = require("../utils/SupabaseClient");
class VectorMemoryClient {
    constructor(dimension = 1536) {
        this.dimension = dimension;
    }
    async getMemory(agentId) {
        const { data, error } = await SupabaseClient_1.supabase
            .from('agent_memory')
            .select('*')
            .eq('agent_id', agentId);
        if (error) {
            console.error("Error fetching memory:", error);
            return [];
        }
        return data || [];
    }
    async saveMemory(agentId, content, embedding) {
        try {
            const { error } = await SupabaseClient_1.supabase
                .from('agent_memory')
                .insert([{
                    agent_id: agentId,
                    content,
                    embedding: embedding ? embedding : null,
                    created_at: new Date().toISOString()
                }]);
            if (error) {
                console.error("Error saving memory:", error);
                throw error;
            }
            // Also save to messages table for conversation tracking
            const { error: msgError } = await SupabaseClient_1.supabase
                .from('messages')
                .insert([{
                    id: `msg-${Date.now()}`,
                    sender_id: agentId,
                    recipient_id: 'system',
                    content,
                    timestamp: new Date().toISOString()
                }]);
            if (msgError) {
                console.error("Error saving message:", msgError);
            }
        }
        catch (error) {
            console.error("Error in saveMemory:", error);
            throw error;
        }
    }
    async searchSimilar(agentId, embedding, limit = 5, threshold = 0.8) {
        const { data, error } = await SupabaseClient_1.supabase.rpc('match_memories', {
            query_embedding: embedding,
            match_threshold: threshold,
            match_count: limit,
            p_agent_id: agentId
        });
        if (error)
            throw error;
        return data || [];
    }
}
exports.VectorMemoryClient = VectorMemoryClient;