user js server

Kerushani · Kerushani · commit 73caf68a908a · 2025-04-09T21:10:18.000-04:00
diff --git a/README.md b/README.md
@@ -1,4 +1,4 @@
-# Web Summarizer - Chrome Extension
+# TLDR - Chrome Extension
 
 A Chrome extension that extracts and summarizes text from any webpage using the **BART (large) model**.  
 
@@ -34,33 +34,51 @@ https://github.com/user-attachments/assets/1edca9a0-0b38-4025-9840-86c557379f0a
 
 ---
 
-## Backend Setup (Flask Server)  
-This extension requires a Flask backend to process summaries.  
+## Backend Setup (Node.js + Ollama)
 
-### 1. Install dependencies  
-   ```sh 
-   pip install flask flask-cors huggingface_hub python-dotenv
-   ```
+This project uses [Ollama](https://ollama.com) to run the `deepseek-r1` large language model (LLM) **locally**, with an Express.js backend acting as the middleman between your frontend and the LLM.
 
-### 2. Set up the API Key  
-Create a `.env` file in the Flask project and add:  
+### Prerequisites
 
-```sh
-API_KEY=your-huggingface-api-key
-```
+- [Node.js](https://nodejs.org/) installed
+- [Ollama](https://ollama.com/download) installed (macOS, Linux, or Windows)
+
+---
+
+### Step 1: Install Ollama
+
+Download and install Ollama for your OS from the official site:
+
+https://ollama.com/download
 
-### 3. Run the Server  
-To start the Flask backend, run:  
+After installing, verify the CLI is available:
 
-```sh
-python3 server.py
+```bash
+ollama --version
 ```
 
-## Speech Synthesis Fix
-If "Read Aloud" does not work, try running this in Chrome DevTools (F12 > Console):
+### Step 2: Run the DeepSeek-R1 Model
 
-```sh
-speechSynthesis.speak(new SpeechSynthesisUtterance("Test speech synthesis."));
+We're using the `deepseek-r1` model — a powerful.
+
+To download and launch it, run:
+
+```bash
+ollama run deepseek-r1
 ```
+### Step 3: Run the Node Backend
 
+Install dependencies:
 
+```bash
+npm install
+```
+
+Install dependencies:
+```bash
+node server.js
+```
+The server will be running at:
+```bash
+http://localhost:5000
+```
diff --git a/content.js b/content.js
@@ -1,24 +1,44 @@
-function getPageText() {
-    return document.body.innerText; 
-  }
-  
-  console.log("Content script loaded!");
-
-  chrome.runtime.onMessage.addListener((message, sender, sendResponse) => {
+chrome.runtime.onMessage.addListener((message, sender, sendResponse) => {
     if (message.action === "summarize") {
         let selectedText = window.getSelection().toString().trim();
         let text = selectedText || document.body.innerText.trim();
 
+        console.log("Text being sent to BART:", text);
+
         if (text.length > 0) {
-            sendResponse({ text: text });
+            fetch("http://localhost:5000/summarize", {
+                method: "POST",
+                headers: { "Content-Type": "application/json" },
+                body: JSON.stringify({ text }),
+            })
+                .then(response => response.json())
+                .then(data => {
+                    console.log("Raw Data from BART:", data);
+
+                    let summaryText = data.summary;
+
+                    if (typeof summaryText === "string" && summaryText.startsWith("{")) {
+                        try {
+                            let parsed = JSON.parse(summaryText);
+                            if (parsed && typeof parsed === "object") {
+                                summaryText = parsed.summary || summaryText;
+                            }
+                        } catch (e) {
+                            console.error("Error parsing nested JSON:", e);
+                        }
+                    }
+
+                    sendResponse({ summary: summaryText });
+                })
+                .catch(error => {
+                    console.error("Error during fetch:", error);
+                    sendResponse({ error: "Failed to summarize." });
+                });
+
+            return true;
         } else {
             sendResponse({ error: "No text found or selected." });
         }
     }
     return true;
 });
-
-  
-
-
-  
diff --git a/manifest.json b/manifest.json
@@ -1,6 +1,6 @@
 {
   "manifest_version": 3,
-  "name": "Web Summarizer",
+  "name": "TLDR",
   "version": "1.0",
   "description": "Summarizes articles using AI.",
   "permissions": ["activeTab", "storage", "scripting"],
diff --git a/package.json b/package.json
@@ -1,5 +1,19 @@
 {
   "dependencies": {
+    "cors": "^2.8.5",
+    "dotenv": "^16.4.7",
+    "express": "^4.21.2",
     "ollama": "^0.5.14"
-  }
+  },
+  "name": "chrome-extension",
+  "version": "1.0.0",
+  "description": "A Chrome extension that extracts and summarizes text from any webpage using the **BART (large) model**.",
+  "main": "content.js",
+  "scripts": {
+    "test": "echo \"Error: no test specified\" && exit 1",
+    "start": "node server.js"
+  },
+  "keywords": [],
+  "author": "",
+  "license": "ISC"
 }
diff --git a/popup.html b/popup.html
@@ -64,9 +64,9 @@
     </style>
 </head>
 <body>
-    <h2>Web Summarizer</h2>
+    <h2>TLDR</h2>
     <button id="summarize">Summarize</button>
-    <button id="readAloud" disabled>🔊 Read Aloud</button>
+    <button id="readAloud" disabled>Read Aloud</button>
     <p id="summary">Your summary will appear here...</p>
 
     <script src="popup.js"></script>
diff --git a/popup.js b/popup.js
@@ -15,33 +15,16 @@ document.getElementById("summarize").addEventListener("click", async () => {
         chrome.tabs.sendMessage(tab.id, { action: "summarize" }, async (response) => {
             if (chrome.runtime.lastError) {
                 console.error("Error:", chrome.runtime.lastError.message);
-                summaryElement.innerText = "Error: Content script not loaded. Try reloading the page.";
+                summaryElement.innerText = "Error: Content script not loaded. Reload page or wait a couple seconds for page to finish loading.";
                 return;
             }
 
-            if (!response || !response.text) {
+            if (!response || !response.summary) {
                 summaryElement.innerText = response?.error || "Failed to extract text.";
                 return;
             }
 
-            const apiResponse = await fetch("http://localhost:5000/summarize", {
-                method: "POST",
-                headers: { "Content-Type": "application/json" },
-                body: JSON.stringify({ text: response.text })
-            });
-
-            if (!apiResponse.ok) {
-                if (apiResponse.status === 500) {
-                    summaryElement.innerText = "Request failed. Document may be too long.";
-                    return;
-                }
-                throw new Error(`Server error: ${apiResponse.status}`);
-            }
-
-            const data = await apiResponse.json();
-
-            const summaryText = data.summary?.summary_text || data.summary || "No summary available.";
-            summaryElement.innerText = summaryText;
+            summaryElement.innerText = response.summary;
             readAloudButton.disabled = false; 
         });
     } catch (error) {
@@ -58,7 +41,7 @@ document.getElementById("readAloud").addEventListener("click", () => {
     if (isSpeaking) {
         speechSynthesis.cancel();
         isSpeaking = false;
-        document.getElementById("readAloud").innerText = "🔊 Read Aloud";
+        document.getElementById("readAloud").innerText = "Read Aloud";
     } else {
         speechUtterance = new SpeechSynthesisUtterance(summaryText);
         speechUtterance.rate = 1; 
@@ -71,12 +54,7 @@ document.getElementById("readAloud").addEventListener("click", () => {
         
         speechUtterance.onend = () => {
             isSpeaking = false;
-            document.getElementById("readAloud").innerText = "🔊 Read Aloud";
+            document.getElementById("readAloud").innerText = "Read Aloud";
         };
     }
-});
-
-
-
-
-
+});
diff --git a/server.js b/server.js
@@ -1,22 +1,45 @@
-import { Ollama } from 'ollama'
-
-let content = "BART model pre-trained on English language, and fine-tuned on CNN Daily Mail. It was introduced in the paper BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension by Lewis et al. and first released in [this repository (https://github.com/pytorch/fairseq/tree/master/examples/bart).Disclaimer: The team releasing BART did not write a model card for this model so this model card has been written by the Hugging Face team.Model description BART is a transformer encoder-encoder (seq2seq) model with a bidirectional (BERT-like) encoder and an autoregressive (GPT-like) decoder. BART is pre-trained by (1) corrupting text with an arbitrary noising function, and (2) learning a model to reconstruct the original text.BART is particularly effective when fine-tuned for text generation (e.g. summarization, translation) but also works well for comprehension tasks (e.g. text classification, question answering). This particular checkpoint has been fine-tuned on CNN Daily Mail, a large collection of text-summary pairs."
-
-const summarize = async (content, showThinking = false) => {
-    const ollama = new Ollama({ host: 'http://127.0.0.1:11434' })
-    const prompt = "Please provide a concise summary of the following content:" 
-    const response = await ollama.chat({
-      model: 'deepseek-r1:1.5b',
-      messages: [{ role: 'user', content: `${prompt} ${content}` }],
-    })
-    const messageContent = response.message.content
-    if (showThinking == true){
-        return messageContent
-    } else {
-        // return messageContent.replace(/<\s*think\s*>[\s\S]*<\s*\/\s*think\s*>/gi, '')
-        // return messageContent.split("</think>", 1)[1];
-        return messageContent.split("</think>", 2)[1];
+import express from "express";
+import cors from "cors";
+import { Ollama } from "ollama";
+
+const app = express();
+app.use(express.json());
+app.use(cors());
+
+const ollama = new Ollama();
+
+app.post("/summarize", async (req, res) => {
+    try {
+        const { text } = req.body;
+        if (!text) {
+            return res.status(400).json({ error: "Text is required - try selecting the text you want to summarize." });
+        }
+
+        console.log("Text being sent to BART:", text);
+
+        const response = await ollama.chat({
+            model: "deepseek-r1:1.5b",
+            messages: [{ role: "user", content: `Summarize this text in 2-3 sentences: ${text}` }],
+        });
+
+        console.log("Server esponse from BART:", response);
+
+        if (!response || !response.message || !response.message.content || response.message.content.trim() === "{}") {
+            return res.status(500).json({ error: "Unexpected response from BART. Try again with a shorter text." });
+        }
+
+        let summary = response.message.content.trim();
+
+        if(summary.includes("</think")){
+            summary = summary.split("</think>", 2)[1]?.trim() || summary; 
+        }
+
+        res.json({ summary });
+
+    } catch (error) {
+        console.error("Threw an error:", error);
+        res.status(500).json({ error: "BART cannot summarize", details: error.message });
     }
-}
-const response = await summarize(content)
-console.log(response)
+});
+
+app.listen(5000, () => console.log("Server running on port 5000"));
diff --git a/server.py b/server.py
@@ -1,3 +1,5 @@
+## not being used
+
 import os
 from flask import Flask, request, jsonify
 from flask_cors import CORS

Original file line number	Diff line number	Diff line change
`@@ -1,6 +1,6 @@`
`1`	`1`	`{`
`2`	`2`	`"manifest_version": 3,`
`3`		`- "name": "Web Summarizer",`
	`3`	`+ "name": "TLDR",`
`4`	`4`	`"version": "1.0",`
`5`	`5`	`"description": "Summarizes articles using AI.",`
`6`	`6`	`"permissions": ["activeTab", "storage", "scripting"],`
Original file line number	Diff line number	Diff line change
`@@ -1,3 +1,5 @@`
	`1`	`+## not being used`
	`2`	`+`
`1`	`3`	`import os`
`2`	`4`	`from flask import Flask, request, jsonify`
`3`	`5`	`from flask_cors import CORS`