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import {defineChatSessionFunction, getLlama, LlamaChatSession} from "node-llama-cpp";
import {fileURLToPath} from "url";
import path from "path";
import {MemoryManager} from "./memory-manager.js";
const __dirname = path.dirname(fileURLToPath(import.meta.url));
const llama = await getLlama({debug: false});
const model = await llama.loadModel({
modelPath: path.join(
__dirname,
'..',
'..',
'models',
'Qwen3-1.7B-Q8_0.gguf'
)
});
const context = await model.createContext({contextSize: 2000});
// Initialize memory manager
const memoryManager = new MemoryManager('./agent-memory.json');
// Load existing memories and add to system prompt
const memorySummary = await memoryManager.getMemorySummary();
const systemPrompt = `
You are a helpful assistant with long-term memory.
Before calling any function, always follow this reasoning process:
1. **Compare** new user statements against existing memories below.
2. **If the same key and value already exist**, do NOT call saveMemory again.
- Instead, simply acknowledge the known information.
- Example: if the user says "My name is Malua" and memory already says "user_name: Malua", reply "Yes, I remember your name is Malua."
3. **If the user provides an updated value** (e.g., "I actually prefer sushi now"),
then call saveMemory once to update the value.
4. **Only call saveMemory for genuinely new information.**
When saving new data, call saveMemory with structured fields:
- type: "fact" or "preference"
- key: short descriptive identifier (e.g., "user_name", "favorite_food")
- value: the specific information (e.g., "Malua", "chinua")
Examples:
saveMemory({ type: "fact", key: "user_name", value: "Malua" })
saveMemory({ type: "preference", key: "favorite_food", value: "chinua" })
${memorySummary}
`;
const session = new LlamaChatSession({
contextSequence: context.getSequence(),
systemPrompt,
});
// Function to save memories
const saveMemory = defineChatSessionFunction({
description: "Save important information to long-term memory (user preferences, facts, personal details)",
params: {
type: "object",
properties: {
type: {
type: "string",
enum: ["fact", "preference"]
},
key: {type: "string"},
value: {type: "string"}
},
required: ["type", "key", "value"]
},
async handler({type, key, value}) {
await memoryManager.addMemory({type, key, value});
return `Memory saved: ${key} = ${value}`;
}
});
const functions = {saveMemory};
// Example conversation
const prompt1 = "Hi! My name is Alex and I love pizza.";
const response1 = await session.prompt(prompt1, {functions});
console.log("AI: " + response1);
// Later conversation (even after restarting the script)
const prompt2 = "What's my favorite food?";
const response2 = await session.prompt(prompt2, {functions});
console.log("AI: " + response2);
// Clean up
session.dispose()
context.dispose()
model.dispose()
llama.dispose() |