js exec py and return str

index.js

@@ -1,5 +1,6 @@
 import config from './config.json' assert {type: "json"};
 import { MatrixClient, SimpleFsStorageProvider, AutojoinRoomsMixin } from "matrix-bot-sdk";
+import { spawn } from 'node:child_process';
 import fs from "fs";
 
 const storage = new SimpleFsStorageProvider("storage.json");
@@ -25,7 +26,15 @@ client.on("room.message", (roomId, event) => {
     // ? send message every N messages using the training data
     if (!(messageCounter % config.frequency)) {
         console.log("Generating message...");
-        client.sendText(roomId, "Hello, World!"); // TODO: exec py function to gen message str 
+
+        const python = spawn('python', ["textgen.py"]);
+
+        python.stdout.on('data', function (message) {
+            message = message.toString();
+            console.log("bot:\t" + message);
+            client.sendText(roomId, message);
+        });
+        python.on('close'); // ? close python process when finished
     };
 });
 

textgen.py

@@ -2,18 +2,20 @@ from aitextgen.TokenDataset import TokenDataset
 from aitextgen.tokenizers import train_tokenizer
 from aitextgen.utils import GPT2ConfigCPU
 from aitextgen import aitextgen
-import json
+import json, sys
 
 with open('config.json', 'r') as file:
     json_object = json.load(file)
 
 file_name = json_object['file']
 
+# ? generate message using trained model
 def generate_message():
     ai = aitextgen(model_folder="trained_model",
                 tokenizer_file="aitextgen.tokenizer.json")
     ai.generate()
 
+# ? train model using text file
 def train_ai():
     train_tokenizer(file_name)
     tokenizer_file = "aitextgen.tokenizer.json"
@@ -23,4 +25,6 @@ def train_ai():
     ai.train(data, batch_size=8, num_steps=50000, generate_every=5000, save_every=5000)
     print("AI has been trained!")
 
-print(generate_message())
+# ? send message to parent JS process
+print(generate_message()) 
+sys.stdout.flush()