Add functionality to query the codebase using Pinecone based on the u…

…ser query

frontend/src/components/Chatbot.css

@@ -81,7 +81,7 @@ h1 {
   opacity: 0.5;
 }
 
-#send-button {
+#send-button, #query-button {
   font-family: "Poppins", sans-serif;
   font-weight: bold;
   font-size: large;
@@ -92,25 +92,36 @@ h1 {
   border-radius: 10px;
   cursor: pointer;
   box-shadow: 0 0 10px rgba(0, 0, 0, 0.1);
+  margin-left: 10px;
 }
 
-#send-button:disabled {
+#send-button:disabled, #query-button:disabled {
   background-color: #808080;
   cursor: not-allowed;
 }
 
-#send-button:disabled:hover {
+#send-button:disabled:hover, #query-button:disabled:hover {
   background-color: #808080; /* Hover color for disabled state */
 }
 
-#send-button:not(:disabled):hover {
+#send-button:not(:disabled):hover, #query-button:not(:disabled):hover {
   background-color: #62aced; /* Hover color for enabled state */
 }
 
 .flex {
   display:flex;
 }
 
+#submit-buttons {
+  display: flex;
+}
+
+@media only screen and (max-width: 406px) {
+  #send-button, #query-button {
+    margin-bottom: 10px;
+  }
+}
+
 #codebase-url {
   font-family: "Poppins", sans-serif;
   border-style: none;

frontend/src/components/Chatbot.js

@@ -1,4 +1,4 @@
-import { sendMessage, downloadCodebase, deleteCodebase } from "../interface";
+import { sendMessage, downloadCodebase, deleteCodebase, sendCodebaseQuery } from "../interface";
 import "./Chatbot.css";
 
 function Chatbot() {
@@ -15,7 +15,10 @@ function Chatbot() {
               <div id="messages"></div>
           </div>
           <textarea id="user-input" placeholder="Type your message here..."></textarea>
-          <button id="send-button" onClick={ sendMessage }>Enter</button>
+          <div className="submit-buttons">
+            <button id="send-button" onClick={ sendMessage }>Enter</button>
+            <button id="query-button" onClick={ sendCodebaseQuery }>Get relevant files</button>
+          </div>
       </div>
     </div>
   );

frontend/src/interface.js

@@ -4,7 +4,6 @@ export async function downloadCodebase() {
     const local = 'http://localhost:3000';
     const apiURL = 'https://syntaxsorcerer-backend.fly.dev'
     const url = document.getElementById('codebase-url').value;
-    if (url.trim() === '') return;
 
     const response = await fetch(`${local}/api/download`, {
         method: 'POST',
@@ -53,11 +52,33 @@ export async function sendMessage() {
     document.getElementById('user-input').value = '';
 
     const sendButton = document.getElementById('send-button');
+    const queryButton = document.getElementById('query-button');
+    queryButton.disabled = true;
     sendButton.disabled = true;
 
     await fetchChatGPTResponse(userInput);
 
     sendButton.disabled = false;
+    queryButton.disabled = false;
+}
+
+// Create a query from the user input that will be used to find the most relevant files
+export async function sendCodebaseQuery() {
+    const userInput = document.getElementById('user-input').value;
+    if (userInput.trim() === '') return;
+
+    appendMessage('You', userInput);
+    document.getElementById('user-input').value = '';
+
+    const sendButton = document.getElementById('send-button');
+    const queryButton = document.getElementById('query-button');
+    queryButton.disabled = true;
+    sendButton.disabled = true;
+
+    await fetchPineconeResponse(userInput);
+
+    sendButton.disabled = false;
+    queryButton.disabled = false;
 }
 
 // Display a message on the frontend
@@ -103,3 +124,25 @@ export async function fetchChatGPTResponse(userInput) {
         appendMessage('Assistant', botMessage.text);
     }
 }
+
+// Fetch a response from the Pinecone API, generate an embedding from the user input
+export async function fetchPineconeResponse(userInput) {
+    const ec2 = 'https://18.226.98.245:443';
+    const local = 'http://localhost:3000';
+    const apiURL = 'https://syntaxsorcerer-backend.fly.dev'
+
+    const response = await fetch(`${local}/api/pinecone`, {
+        method: 'POST',
+        headers: {
+            'Content-Type': 'application/json'
+        },
+        body: JSON.stringify({ prompt: userInput })
+    });
+
+    const botMessage = await response.json();
+    if (botMessage.error) {
+        appendMessage('Error', botMessage.error);
+    } else {
+        appendMessage('Assistant', botMessage.text);
+    }
+}

server/database/EmbeddingService.js → server/config/pineconeConfig/embeddingConfig.js

@@ -1,31 +1,27 @@
-const { OpenAI } = require('openai');
-require('dotenv').config()
-// Function to generate embeddings using OpenAI's API
-async function generateEmbeddings(tokens) {
-    // Initialize OpenAI client
-    const openai = new OpenAI({
-        apiKey: process.env.OPENAI_API_KEY, // Ensure your API key is set in the environment variables
-    });
-
-    try {
-        // Flatten the tokens into a format suitable for OpenAI
-        const text = tokens.map(token => JSON.stringify(token)).join('\n');
-
-        // Request embeddings
-        const response = await openai.embeddings.create({
-            model: 'text-embedding-ada-002', // Use an appropriate embedding model
-            input: text,
-            encoding_format: 'float'
-        });
-
-        console.log('Embedding Dimension: ', response.data[0].embedding.length);
-        console.log('OpenAI embeddings response:', response.data);
-        return response.data
-
-
-    } catch (error) {
-        console.error('Error generating embeddings with OpenAI:', error);
-    }
-}
-
-module.exports = generateEmbeddings;
+const openai = require('../openaiConfig')
+require('dotenv').config();
+
+// Function to generate embeddings using OpenAI's API
+async function generateEmbeddings(tokens) {
+    try {
+        // Flatten the tokens into a format suitable for OpenAI
+        const text = tokens.map(token => JSON.stringify(token)).join('\n');
+
+        // Request embeddings
+        const response = await openai.embeddings.create({
+            model: 'text-embedding-ada-002', // Use an appropriate embedding model
+            input: text,
+            encoding_format: 'float'
+        });
+
+        console.log('Embedding Dimension: ', response.data[0].embedding.length);
+        console.log('OpenAI embeddings response:', response.data);
+        return response.data;
+
+
+    } catch (error) {
+        console.error('Error generating embeddings with OpenAI:', error);
+    }
+}
+
+module.exports = generateEmbeddings;

server/config/pineconeConfig/pineconeInit.js

@@ -0,0 +1,5 @@
+const PineconeManager = require('../pineconeConfig/pineconeManager');
+
+const pinecone = new PineconeManager(process.env.PINECONE_API_KEY, "syntaxsorcerer");
+
+module.exports = pinecone;