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Dockerfile

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+FROM mcr.microsoft.com/devcontainers/javascript-node:0-18-bullseye
+
+RUN apt-get update && apt-get install -y \
+    chromium chromium-driver \
+    fonts-liberation libappindicator3-1 \
+    libasound2 libatk-bridge2.0-0 libatk1.0-0 libcups2 libdbus-1-3 \
+    libgdk-pixbuf2.0-0 libnspr4 libnss3 libx11-xcb1 libxcomposite1 \
+    libxdamage1 libxrandr2 xdg-utils libu2f-udev libvulkan1 \
+    libxcb-dri3-0 libxshmfence1 libxss1 libgbm1 \
+    python3 python3-pip \
+    --no-install-recommends && \
+    apt-get clean && rm -rf /var/lib/apt/lists/*
+
+# Set working directory
+WORKDIR /workspace
+
+# Copy package files and install
+COPY package*.json ./
+RUN npm install
+
+# Copy Python app and install Python deps
+COPY requirements.txt .
+RUN pip install -r requirements.txt
+
+# Copy rest of the files
+COPY . .
+
+# Make Chromium usable by Puppeteer
+ENV PUPPETEER_EXECUTABLE_PATH=/usr/bin/chromium
+
+# Hugging Face exposes port 7860 or 3000
+EXPOSE 7860
+# Run both wa-automate and FastAPI
+CMD uvicorn app:app --host 0.0.0.0 --port 7860 

app.py

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+from fastapi import FastAPI, Body
+from model import AdsMod
+
+
+MODEL_PRETRAINED_PATH = "venishpatidar/wa-ad-mod"
+
+app = FastAPI()
+model = AdsMod(MODEL_PRETRAINED_PATH)
+
+
+@app.get("/")
+def greet_json()->None:
+    return "Hello from Ad-Mod"
+
+@app.post("/classify")
+def classify_text(input:str=Body(...))->None:
+    return model.predict(input)

config.js

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+module.exports = {
+    LAUNCH_CONFIG:{
+        qrTimeout: 0, // infinite time for QR
+        authTimeout: 60, // seconds
+        headless: true,
+        useChrome: false,
+        killProcessOnBrowserClose: true,
+        deleteSessionDataOnLogout: false,
+        cacheEnabled: false,
+        sessionId: 'hr',
+        skipSessionSave:true,
+        autoRefresh:true
+    },
+    LLM_URL:"http://127.0.0.1:7860/classify"
+};

index.js

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+const { create } = require('@open-wa/wa-automate');
+const { LAUNCH_CONFIG, LLM_URL } = require('./config')
+
+// Only process message having length more then 46
+const WORD_LEN_TRSH = 46;
+const STATUS_KEYWORD = "Hi :status"
+const CLEAR_INTERVAL = 12 * 60 * 1000; // 12 hours in milliseconds
+
+function start(client) {
+    client.onMessage(async message => {
+        const messageId = message.id;
+        const from = message.from // If from group from contains group id else author id
+        const text = message.body
+        const author = message.author // Author and from can be different in case of group;
+        const message_type = message.type
+
+        if (text===STATUS_KEYWORD){
+            await client.sendText(from, 'Hello 👋, my system is online and running smoothly.');
+        }
+        // Calling the LLM api to analyze the text
+        if(message_type==="chat" && text.length>=WORD_LEN_TRSH){
+            
+            let msg = await fetch(
+                LLM_URL,{
+                method:"POST",
+                body: JSON.stringify({ input: text })
+            })
+            let response = await msg.json()
+            
+            // await client.sendText(from, response===0?"Safe":"Ad"); 
+            
+            if(response){
+                try{
+                    await client.deleteMessage(messageId);
+                    // For debugging purpose
+                    // await client.sendText(from, 'Chat deleted successfully.');
+
+                    /* Commenting this as cant send message to a user until its in contact*/
+                    // Sending the sender that you have sent Ad message in wrong group
+                    // await client.sendText(author, 'Please donot send Ads to the support group.');
+
+                } 
+                catch (error) {
+                    console.error('[X] Log: Failed to delete chat error:', error);
+                }
+            }
+        }
+
+        else{
+            // Handle for not message type == chat
+        }
+    }); // End of Client.onMeassage
+
+
+
+    // Clears all the chat after CLEAR_INTERVAL time period
+    // setTimeout(async () => {
+    //     try {
+    //         const success = await client.clearAllChats();
+    //         if (success) {
+    //             console.log('[+] All chats cleared.');
+    //         } 
+    //         else {
+    //             console.log('[X] Failed to clear chats.');
+    //         }   
+    //     }
+    //     catch (error) {
+    //         console.error('[X] Failed to clear chats:', error);
+    //     }
+    // }, CLEAR_INTERVAL);
+}
+
+  
+create(LAUNCH_CONFIG).then(start);

model.py

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+from transformers import AutoConfig, AutoModelForSequenceClassification, AutoTokenizer
+import torch
+
+class AdsMod:
+    """
+        Model init method
+        base model used = bloom-560m
+        model_path: takes the path of saved model weights
+    """
+    def __init__(self,model_path:str="./") -> None:
+        self.model = AutoModelForSequenceClassification.from_pretrained(model_path)
+        tokenizer = AutoTokenizer.from_pretrained(model_path)
+        device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+        self.tokenize = lambda input: tokenizer(input, truncation=True, padding="max_length", max_length=256,return_tensors="pt").to(device)
+        self.model.to(device)
+
+    """
+        predict 
+        takes text as input and classifies the text
+        returns 0 or 1
+    """
+    def predict(self,text:str) -> int:
+        input = self.tokenize(text)
+        with torch.no_grad():
+            output = self.model(**input)
+        predicted_class = torch.argmax(output.logits, dim=1).item()
+        return predicted_class
+
+if __name__=="__main__":
+    model = AdsMod('venishpatidar/wa-ad-mod')
+    text = "Hi I am text classifier, will help you in deleteing housing ads message"
+    print("Ad" if model.predict(text) else "Safe")

package.json

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+{
+  "name": "wa-automate",
+  "version": "1.0.0",
+  "description": "",
+  "main": "index.js",
+  "scripts": {
+    "test": "echo \"Error: no test specified\" && exit 1"
+  },
+  "dependencies": {
+    "@open-wa/wa-automate": "^4.76.0"
+  },
+  "author": "venish",
+  "license": "ISC"
+}

requirements.txt

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+fastapi
+uvicorn
+transformers
+torch