refactor make the code actually somewhat bearable

generate.py

@@ -0,0 +1,30 @@
+from aitextgen.TokenDataset import TokenDataset
+from aitextgen.tokenizers import train_tokenizer
+from aitextgen.utils import GPT2ConfigCPU
+from aitextgen import aitextgen
+import json
+import sys
+
+with open('config.json', 'r') as file:
+    json_object = json.load(file)
+
+file_name = json_object['file']
+
+def generate_message(prompt=None):
+    ai = aitextgen(model_folder="trained_model",
+                   tokenizer_file="aitextgen.tokenizer.json", prompt=prompt)
+    return ai.generate()
+
+match sys.argv[1]: 
+    case "prompt":
+        try:
+            msg = generate_message(' '.join(map(str, sys.argv[1:])))
+            print(msg)
+        except IndexError:
+            print(generate_message())
+        finally:
+            sys.stdout.flush()
+
+    case _:
+        msg = generate_message()
+        print(msg)

index.js

@@ -2,75 +2,59 @@ import config from './config.json' assert {type: "json"};
 import { MatrixClient, SimpleFsStorageProvider, AutojoinRoomsMixin } from "matrix-bot-sdk";
 import fs from "fs";
 import { PythonShell } from 'python-shell';
-import { type } from 'os';
+// import { type } from 'os';
 
 const storage = new SimpleFsStorageProvider("storage.json");
 const client = new MatrixClient(config.homeserver, config.token, storage);
-const pyFile = "textgen.py";
+const pyFile = "generate.py";
 
 AutojoinRoomsMixin.setupOnClient(client);
 client.start().then(() => console.log(`Client has started!\n`));
 
 const messageCounters = new Map(); // room ID, message count
-let trainingCounter = 0;
 
 client.on("room.message", (roomId, event) => {
-    if (!event["content"] || event["sender"] === config.user) return;
+    if (!event["content"] || event["sender"] === config.user) return; // ? ignore if message sent by bot itself or is empty
 
-    ++trainingCounter;
+    let messageArray = event["content"]["body"].split(" ");
+
+    if (!(messageArray[0] === config.prefix)) {
         messageCounters.set(roomId, (messageCounters.get(roomId) ?? 0) + 1);
-    let userMessage = event["content"]["body"].split(" ");
+        console.log(`COUNTER:\t${messageCounters.get(roomId)}\t${roomId}\t${event["content"]["body"]}`);
-
+        fs.appendFile(config.file, event["content"]["body"] + "\n", function (err) {
-    console.log(`COUNTER:\t${messageCounters.get(roomId)}\t${roomId}\t${userMessage.join(" ")}`);
-
-
-    if (userMessage[0].startsWith(config.prefix)) {
-        userMessage[0] = userMessage[0].replace(config.prefix, '').toLowerCase();
-    } else {
-        fs.appendFile(config.file, userMessage.join(" ") + "\n", function (err) {
             if (err) throw err;
         });
-    };
+        return;
+    }  // ? if message does not start with prefix log it for training
+
+
+    messageArray.shift() // ? remove bot's prefix from array
 
     // ? send message if:
     // ?    - enough messages have been sent
     // ?    - commanded
-    if (!(messageCounters.get(roomId) % config.frequency) || userMessage[0] === "speak") {
+    if (!(messageCounters.get(roomId) % config.frequency) || messageArray[0].toLowerCase() === "speak") {
         console.log("Generating message...");
         
-        userMessage.shift()
+        const options = { args: ["", ""] };
-        userMessage = userMessage.join(" ")
-        fs.appendFile(config.file, userMessage + "\n", function (err) {
-            if (err) throw err;
-        });
-        const options = { args: ['generate', userMessage] };
         PythonShell.run(pyFile, options, (err, message) => {
             if (err) throw err;
             client.sendText(roomId, message.toString());
             console.log("Message sent!");
         }); // ? send generated message to room
-    };
 
-    // ? retrain if:
+    } else if (messageArray[0] === "prompt") {
-    // ?    - enough message have been sent
+        console.log("prompted to generate...")
-    // ?    - commanded
-    if (trainingCounter >= config.retrain || userMessage[0] === "train") {
-        console.log("Retraining the AI...");
-        client.sendText(roomId, "Retraining the AI...");
-
-        trainingCounter = 0;
-        const options = { args: ['train'] };
 
+        const options = { args: ['prompt', messageArray.join(" ")] };
         PythonShell.run(pyFile, options, (err, message) => {
             if (err) throw err;
-            console.log(message.toString());
+            client.sendText(roomId, message.toString());
-        });
+            console.log("Message sent!");
-        console.log("Training finished!");
+        }); // ? send prompted message to room
-        client.sendText(roomId, "Training finished!");
+        
-    };
+    } else {
+        console.log("Invalid command")
+    }
 });
 
-function lineCount(text) {
-    return fs.readFileSync(text).toString().split("\n").length - 1;
-};
-

textgen.py

@@ -1,49 +0,0 @@
-from aitextgen.TokenDataset import TokenDataset
-from aitextgen.tokenizers import train_tokenizer
-from aitextgen.utils import GPT2ConfigCPU
-from aitextgen import aitextgen
-import json
-import 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(prompt=None):
-    # ai = aitextgen(prompt=prompt)
-    ai = aitextgen(model_folder="trained_model",
-                   tokenizer_file="aitextgen.tokenizer.json", prompt=prompt)
-    return ai.generate()
-
-# ? train model using text file
-
-
-def train_ai():
-    train_tokenizer(file_name)
-    tokenizer_file = "aitextgen.tokenizer.json"
-    config = GPT2ConfigCPU()
-    ai = aitextgen(tokenizer_file=tokenizer_file, config=config)
-    data = TokenDataset(
-        file_name, tokenizer_file=tokenizer_file, block_size=64)
-    ai.train(data, batch_size=8, num_steps=50000,
-             generate_every=5000, save_every=5000)
-
-
-match sys.argv[1]:
-    case "generate":
-        # ? send message to parent JS process
-        try:
-            prompt = ' '.join(map(str, sys.argv[2:]))
-            generate_message(prompt)
-        except IndexError:
-            generate_message()
-        finally:
-            sys.stdout.flush()
-    case "train":
-        train_ai()
-    case _:
-        raise NameError("Argument not provided.")

train.py

@@ -0,0 +1,20 @@
+from aitextgen.TokenDataset import TokenDataset
+from aitextgen.tokenizers import train_tokenizer
+from aitextgen.utils import GPT2ConfigCPU
+from aitextgen import aitextgen
+import json
+
+with open('config.json', 'r') as file:
+    json_object = json.load(file)
+
+file_name = json_object['file']
+
+train_tokenizer(file_name)
+tokenizer_file = "aitextgen.tokenizer.json"
+config = GPT2ConfigCPU()
+
+ai = aitextgen(tokenizer_file=tokenizer_file, config=config)
+data = TokenDataset(
+    file_name, tokenizer_file=tokenizer_file, block_size=64)
+ai.train(data, batch_size=8, num_steps=50000,
+            generate_every=5000, save_every=5000)