lfg

src/app/search/web/page.jsx

@@ -18,46 +18,33 @@ export default function WebSearchPage({ searchParams }) {
       const response = await fetch('/api/llm', {
         method: 'POST',
         headers: { 'Content-Type': 'application/json' },
-        body: JSON.stringify({ question: searchTerm || "Seattle activities this weekend" }),
+        body: JSON.stringify({ question: searchTerm }),
         signal,
       });
-  
-      if (!response.ok) {
-        throw new Error(`HTTP error! status: ${response.status}`);
-      } else {
-        const reader = response.body.getReader();
-        const decoder = new TextDecoder();
-        let text = '';
-  
-        try {
-          while (true) {
-            const { value, done } = await reader.read();
-    
-            if (done) {
-              // When the stream ends, we can parse the complete text
-              const json = JSON.parse(text);
-              console.log(json);
-              setAiResponse(json);
-              console.log("Stream complete");
-              break;
-            }
-    
-            text += decoder.decode(value, {stream: true});
-          }
-        } catch (error) {
-          console.error("Failed to parse JSON", error);
+      const data = response.body;
+      if (!data) {
+        return;
+      }
+
+      const reader = data.getReader();
+      const decoder = new TextDecoder();
+      let done = false;
+
+      while (!done) {
+        const { value, done: doneReading } = await reader.read();
+        done = doneReading;
+        const chunkValue = decoder.decode(value);
+        if (chunkValue) {
+          setAiResponse(chunkValue);
         }
       }
-    }
+    };
   
-    fetchData().catch(error => {
-      console.error('Fetch failed: ', error);
-    });
+    fetchData();
   
     return () => controller.abort();
   }, [searchParams, searchTerm]);    
 
-
   console.log(aiResponse);
 
   return (

src/pages/api/llm.js

@@ -1,7 +1,7 @@
 import { GoogleCustomSearch } from "openai-function-calling-tools";
 import { LLMError, LLMStream } from './stream';
 
-const handler = async (req) => {
+const handler = async (req, res) => {
   try {
     const { question } = (await req.body);
 
@@ -18,12 +18,21 @@ const handler = async (req) => {
       ];
     
     const functions = {
-        googleCustomSearch,
+        googleCustomSearch
     };
 
-    let promptToSend = "You are a helpful assistant";
+    let promptToSend = "You are a helpful assistant, a search term is provided and you are given search results to help provide a useful response.";
     const stream = await LLMStream({ id: "gpt-3.5-turbo-0613" }, promptToSend, 0.8, messages, functions);
-    return new Response(stream);
+
+    let data = '';
+    const decoder = new TextDecoder();
+    for await (const chunk of stream) {
+        data += decoder.decode(chunk);
+        res.write(data);
+    }
+
+    return res.end();
+
   } catch (error) {
     console.error(error);
     if (error instanceof LLMError) {

src/pages/api/search.js

@@ -1,24 +0,0 @@
-// pages/api/search.js
-
-export default async function handler(req, res) {
-    const { searchTerm, startIndex = "1" } = req.query;
-  
-    if (!searchTerm) {
-      res.status(400).json({ error: 'Search term is required' });
-      return;
-    }
-  
-    const response = await fetch(
-      `https://www.googleapis.com/customsearch/v1?key=${process.env.API_KEY}&cx=${process.env.CONTEXT_KEY}&q=${searchTerm}&start=${startIndex}`
-    );
-  
-    if (!response.ok) {
-      res.status(response.status).json({ error: 'Failed to fetch search results' });
-      return;
-    }
-  
-    const data = await response.json();
-  
-    res.status(200).json(data);
-  }
-  

src/pages/api/stream.js

@@ -40,7 +40,7 @@ export const LLMStream = async (
       ],
       max_tokens: 1000,
       temperature: temperature,
-      stream: true
+      stream: true,
     }),
   });
 
@@ -70,8 +70,9 @@ export const LLMStream = async (
       const onParse = async (event) => {
         if (event.type === 'event') {
           const data = event.data;
+
           try {
-            if (data === '[DONE]') {
+            if (data === "[DONE]") {
               return;
             }
             const json = JSON.parse(data);
@@ -79,23 +80,18 @@ export const LLMStream = async (
               controller.close();
               return;
             } else if (json.choices[0].finish_reason === "function_call") {
-              const fnName = json.choices[0].message.function_call.name;
-              const args = json.choices[0].message.function_call.arguments;
-          
-              const fn = functions[fnName];
-              const functionResult = await fn(...Object.values(JSON.parse(args)));
-          
-              console.log(`Function call: ${fnName}, Arguments: ${args}`);
-              console.log(`Calling Function ${fnName} Result: ` + functionResult);
-              
-              const queue = encoder.encode(functionResult);
-              controller.enqueue(queue);
-            } else {
-              const text = json.choices[0].delta.content;
-              const queue = encoder.encode(text);
-              controller.enqueue(queue);
-            }
+                const fnName = json.choices[0].message.function_call.name;
+                const args = json.choices[0].message.function_call.arguments;
             
+                const fn = functions[fnName];
+                const result = await fn(...Object.values(JSON.parse(args)));
+            
+                console.log(`Function call: ${fnName}, Arguments: ${args}`);
+                console.log(`Calling Function ${fnName} Result: ` + result);
+            }
+            const text = json.choices[0].delta.content;
+            const queue = encoder.encode(text);
+            controller.enqueue(queue);
           } catch (e) {
             console.log(e);
             controller.error(e);