update ui

pages/api/chat.ts

@@ -55,26 +55,27 @@ async function askOpenAI({
   console.log("messages req: ", messages);
 
   // updated the message content to include context snippets
-  // if (messages?.length > 0) {
-  //   const lastMsgContent = messages[messages.length - 1].content;
+  if (messages?.length > 0) {
+    const lastMsgContent = messages[messages.length - 1].content;
 
-  //   const data = await pinecone.similaritySearch(lastMsgContent, 2);
+    const data = await pinecone.similaritySearch(lastMsgContent, 3);
 
-  //   console.log("pinecone data.length: ", data.length);
+    console.log("pinecone data.length: ", data.length);
 
-  //   const updatedMsgContent = `
-  //   user question/statement: ${lastMsgContent}
-  //   context snippets:
-  //   ---
-  //   1) ${data?.[0]?.pageContent}
-  //   ---
-  //   2) ${data?.[1]?.pageContent}
-  //   `;
+    const updatedMsgContent = `
+    user question/statement: ${lastMsgContent}
+    context snippets:
+    ---
+    1) ${data?.[0]?.pageContent}
+    ---
+    2) ${data?.[1]?.pageContent}
+    ---
+    3) ${data?.[2]?.pageContent}
+    `;
 
-  //   messages[messages.length - 1].content = updatedMsgContent;
-  // }
+    messages[messages.length - 1].content = updatedMsgContent;
+  }
 
-  console.log("messages length after pinecone: ", messages?.length);
   try {
     const response = await openai.createChatCompletion({
       model: "gpt-3.5-turbo-0301",
@@ -96,8 +97,6 @@ async function askOpenAI({
       ],
     });
 
-    console.log("response: ", response);
-
     return response?.data?.choices?.[0]?.message?.content;
   } catch (e: any) {
     console.log("error in response: ", e.message);

pages/index.tsx

@@ -21,8 +21,10 @@ import NameInput from "@/components/NameInput";
 import { Message } from "@/types";
 
 function Home() {
+  // ref need to play audio
   const audioRef = useRef<HTMLAudioElement | null>(null);
 
+  // storing array messages in state
   const [messages, setMessages] = useState<Message[]>([]);
 
   const addMessage = (message: Message) => {
@@ -30,12 +32,13 @@ function Home() {
   };
 
   const toast = useToast();
-  const [text, setText] = useState("");
   const [loading, setLoading] = useState(false);
 
-  // on the first translate, we need to get the user's name
-  // on subsequent translates, we can use the name from state
-  const translate = async (props?: { name?: string }) => {
+  // tracking user input
+  const [text, setText] = useState("");
+
+  // function to execute api request and communicate with open ai, pinecone & eleven labs
+  const askAi = async (props?: { name?: string }) => {
     if (!text && !props?.name)
       return toast({
         title: "Enter text to translate first!",
@@ -148,7 +151,7 @@ function Home() {
             onEnter={(name) => {
               startAudioForPermission();
               setUserName(name);
-              translate({ name });
+              askAi({ name });
             }}
           />
         ) : (
@@ -186,7 +189,7 @@ function Home() {
                 value={text}
                 onChange={(e) => setText(e.target.value)}
                 onKeyDown={handleEnterKeyPress(() => {
-                  translate();
+                  askAi();
                 })}
               />
             </VStack>
@@ -196,7 +199,7 @@ function Home() {
                 h={9}
                 variant="outline"
                 onClick={() => {
-                  translate();
+                  askAi();
 
                   window.scrollTo({
                     left: 0,

scripts/createIndex.ts

@@ -27,22 +27,25 @@ dotenv.config();
     apiKey: process.env.PINECONE_API_KEY as string,
     environment: process.env.PINECONE_ENVIRONMENT as string,
   });
+
+  // referencing index we want to upload to
   const pineconeIndex = client.Index(process.env.PINECONE_INDEX as string);
 
+  // loading pdf
   const loader = new PDFLoader("./scripts/navalPdf.pdf", {
     splitPages: false,
   });
-
   const docs = await loader.load();
 
+  // splitting pdf into chunks
   const splitter = new CharacterTextSplitter({
     separator: "\n",
     chunkSize: 2000,
     chunkOverlap: 200,
   });
-
   const splitDocs = await splitter.splitDocuments(docs);
 
+  // uploading chunks to pinecone
   await PineconeStore.fromDocuments(splitDocs, new OpenAIEmbeddings(), {
     pineconeIndex,
   });