Bot personalities!

bots/LLMBot.js

@@ -10,6 +10,19 @@ const llmOptions = fs.existsSync(configPath)
 
 console.log(`Read config from ${configPath}`);
 
+function generateBotPersonality() {
+    const personalities = fs.readFileSync(path.join(__dirname, 'bot_personalities.txt'), 'utf8')
+      .split('\n')
+      .map(personality => personality.trim())
+      .filter(personality => personality.length > 0);
+
+    if (personalities.length === 0) {
+      return 'You are a friendly bot'; // Fallback if no personalities are found
+  }
+  const randomIndex = Math.floor(Math.random() * personalities.length);
+  return personalities[randomIndex];
+}
+
 class LLMBot {
   constructor() {
     // Instantiate the OpenAI client with the config options we just read
@@ -29,23 +42,26 @@ Reply with ONLY the number (0-indexed) of the sentence you like best.`;
     this.banterPrompt =
       `You are a playful, slightly sarcastic AI taking part in a writing-game chat.  
 Keep it short, fun, and on-topic.`;
+
+    this.personality = generateBotPersonality();
   }
 
   async Write(story_so_far) {
-    const msg = `${this.writePrompt}\n\nStory so far:\n${story_so_far}`;
+    const msg = `${this.personality}. ${this.writePrompt}\n\nStory so far:\n${story_so_far}`;
     const response = await this.llm.chat.completions.create({
       model: llmOptions.model || 'meta-llama/Llama-3.2-3B-Instruct-Turbo',
       messages: [{ role: 'user', content: msg }],
       temperature: llmOptions.temperature ?? 0.8,
       max_tokens: llmOptions.max_tokens ?? 80,
     });
-    console.log(`Received response from LLM: ${response.choices[0].message.content}`);
+    //console.log(`Received response from LLM: ${response.choices[0].message.content}`);
     return response.choices[0].message.content.trim();
   }
 
   async Vote(story_so_far, choices) {
-    const choicesBlock = choices.map((c, i) => `${i}: ${c}`).join('\n');
-    const msg = `${this.votePrompt}\n\nStory:\n${story_so_far}\n\nChoices:\n${choicesBlock}`;
+    const choicesBlock = choices.map((c, i) => `${i}: ${(c.entry_text)}`).join('\n');
+    const msg = `${this.personality}. ${this.votePrompt}\n\nStory:\n${story_so_far}\n\nChoices:\n${choicesBlock}`;
+    //console.log(msg);
     const response = await this.llm.chat.completions.create({
       model: llmOptions.model || 'meta-llama/Llama-3.2-3B-Instruct-Turbo',
       messages: [{ role: 'user', content: msg }],