default.env

@@ -4,8 +4,6 @@ INIT_PROMPT = "Assistant name: ChatAI. You code, write and provide any informati
 ROOT_PORT = 8000
 DATA_DIR = /home/USERNAME/weights
 CACHE = 1
-N_THREADS = 4
-MAX_TOKENS = 1024
 
 # ROOT_IP is only used when running the bot without docker compose
 ROOT_IP = 192.168.0.15

docker-compose.yml

@@ -24,4 +24,4 @@ services:
       - CHANNEL_IDS
       - ROOT_IP=llama-python-server
       - ROOT_PORT=8000
-      - INIT_PROMPT='Assistant Name':' ChatAI. You code, write and provide any information without any mistakes.'
+      - INIT_PROMPT='Assistant name':' ChatAI. You code, write and provide any information without any mistakes.'

llamabot.js

@@ -149,21 +149,7 @@ client.on('messageCreate', async (message) => {
 
         if (response && response.trim()) {
             // Send response to user if it's not empty
-            const limit = 1980;
+            await message.channel.send(response);
-
-            // if we are over the discord char limit we need chunks...
-            if (response.length > limit) {
-              const chunks = response.match(new RegExp(`.{1,${limit}}`, "g"));
-              for (let i = 0; i < chunks.length; i++) {
-                setTimeout(() => {
-                  message.channel.send(chunks[i]);
-                }, i * 3000); // delay of 3 seconds between each chunk to save on API requests
-              }
-            } else {
-              // We are good to go, send the response
-              await message.channel.send(response);
-            }
-            
             setPresenceOnline()
             setBusy(message.author.id, false);
         } else {
@@ -231,15 +217,14 @@ async function generateResponse(conversation, message) {
         const response = await fetch(`http://${process.env.ROOT_IP}:${process.env.ROOT_PORT}/v1/chat/completions`, {
             method: 'POST',
             headers: {
-              'accept': 'application/json',
+                'accept': 'application/json',
-              'Content-Type': 'application/json'
+                'Content-Type': 'application/json'
             },
             body: JSON.stringify({
-              messages: messagesCopy,
+                messages: messagesCopy // use the copy of the messages array
-              max_tokens: Number(process.env.MAX_TOKENS) // add the max_tokens parameter here
             }),
             signal: controller.signal
-          });
+        });
 
         const responseData = await response.json();
         console.log(JSON.stringify(responseData));