use gpt-3.5-turbo

Kledal · Mar 1, 2023 · 4466a62 · 4466a62
1 parent 72744dd
commit 4466a62
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Showing 6 changed files with 24 additions and 143 deletions.
diff --git a/components/Search.tsx b/components/Search.tsx
@@ -1,6 +1,6 @@
-import { OpenAIModel, SearchQuery, Source } from "@/types";
-import { createPrompt } from "@/utils/answer";
+import { SearchQuery, Source } from "@/types";
 import { IconArrowRight, IconBolt, IconSearch } from "@tabler/icons-react";
+import endent from "endent";
 import { FC, KeyboardEvent, useEffect, useRef, useState } from "react";
 
 interface SearchProps {
@@ -13,7 +13,6 @@ export const Search: FC<SearchProps> = ({ onSearch, onAnswerUpdate, onDone }) =>
   const inputRef = useRef<HTMLInputElement>(null);
 
   const [query, setQuery] = useState<string>("");
-  const [model, setModel] = useState<OpenAIModel>(OpenAIModel.DAVINCI_CODE);
   const [apiKey, setApiKey] = useState<string>("");
   const [showSettings, setShowSettings] = useState<boolean>(false);
   const [loading, setLoading] = useState<boolean>(false);
@@ -35,7 +34,7 @@ export const Search: FC<SearchProps> = ({ onSearch, onAnswerUpdate, onDone }) =>
       headers: {
         "Content-Type": "application/json"
       },
-      body: JSON.stringify({ query, model })
+      body: JSON.stringify({ query })
     });
 
     if (!response.ok) {
@@ -50,13 +49,17 @@ export const Search: FC<SearchProps> = ({ onSearch, onAnswerUpdate, onDone }) =>
 
   const handleStream = async (sources: Source[]) => {
     try {
-      let prompt = createPrompt(query, sources, model);
+      const prompt = endent`Provide a 2-3 sentence answer to the query based on the followin sources. Be original, concise, accurate, and helpful. Cite sources as [1] or [2] or [3] after each sentence (not just the very end) to back up your answer (Ex: Correct: [1], Correct: [2][3], Incorrect: [1, 2]).
+      
+      ${sources.map((source, idx) => `Source [${idx + 1}]:\n${source.text}`).join("\n\n")}
+      `;
+
       const response = await fetch("/api/answer", {
         method: "POST",
         headers: {
           "Content-Type": "application/json"
         },
-        body: JSON.stringify({ prompt, model, apiKey })
+        body: JSON.stringify({ prompt, apiKey })
       });
 
       if (!response.ok) {
@@ -102,43 +105,27 @@ export const Search: FC<SearchProps> = ({ onSearch, onAnswerUpdate, onDone }) =>
       return;
     }
 
-    if (!model) {
-      alert("Please select a model.");
-      return;
-    }
-
     localStorage.setItem("CLARITY_KEY", apiKey);
-    localStorage.setItem("CLARITY_MODEL", model);
 
     setShowSettings(false);
     inputRef.current?.focus();
   };
 
   const handleClear = () => {
     localStorage.removeItem("CLARITY_KEY");
-    localStorage.removeItem("CLARITY_MODEL");
 
     setApiKey("");
-    setModel(OpenAIModel.DAVINCI_CODE);
   };
 
   useEffect(() => {
     const CLARITY_KEY = localStorage.getItem("CLARITY_KEY");
-    const CLARITY_MODEL = localStorage.getItem("CLARITY_MODEL");
 
     if (CLARITY_KEY) {
       setApiKey(CLARITY_KEY);
     } else {
       setShowSettings(true);
     }
 
-    if (CLARITY_MODEL) {
-      setModel(CLARITY_MODEL as OpenAIModel);
-    } else {
-      setShowSettings(true);
-      setModel(OpenAIModel.DAVINCI_CODE);
-    }
-
     inputRef.current?.focus();
   }, []);
 
@@ -190,22 +177,6 @@ export const Search: FC<SearchProps> = ({ onSearch, onAnswerUpdate, onDone }) =>
 
           {showSettings && (
             <>
-              <select
-                value={model}
-                onChange={(e) => setModel(e.target.value as OpenAIModel)}
-                className="max-w-[400px] block w-full cursor-pointer rounded-md border border-gray-300 p-2 text-black shadow-sm focus:border-blue-500 focus:outline-none focus:ring-2 focus:ring-blue-500 sm:text-sm"
-              >
-                {Object.values(OpenAIModel).map((model) => (
-                  <option
-                    key={model}
-                    value={model}
-                    className="bg-gray-900 text-white"
-                  >
-                    {model}
-                  </option>
-                ))}
-              </select>
-
               <input
                 type="password"
                 className="max-w-[400px] block w-full rounded-md border border-gray-300 p-2 text-black shadow-sm focus:border-blue-500 focus:outline-none focus:ring-2 focus:ring-blue-500 sm:text-sm"

diff --git a/pages/api/answer.ts b/pages/api/answer.ts
@@ -1,4 +1,3 @@
-import { OpenAIModel } from "@/types";
 import { OpenAIStream } from "@/utils/answer";
 
 export const config = {
@@ -7,13 +6,12 @@ export const config = {
 
 const handler = async (req: Request): Promise<Response> => {
   try {
-    const { prompt, model, apiKey } = (await req.json()) as {
+    const { prompt, apiKey } = (await req.json()) as {
       prompt: string;
-      model: OpenAIModel;
       apiKey: string;
     };
 
-    const stream = await OpenAIStream(prompt, model, apiKey);
+    const stream = await OpenAIStream(prompt, apiKey);
 
     return new Response(stream);
   } catch (error) {

diff --git a/pages/api/sources.ts b/pages/api/sources.ts
@@ -3,7 +3,7 @@ import { Readability } from "@mozilla/readability";
 import * as cheerio from "cheerio";
 import { JSDOM } from "jsdom";
 import type { NextApiRequest, NextApiResponse } from "next";
-import { cleanSourceText, getSourceCount, shortenSourceText } from "../../utils/sources";
+import { cleanSourceText } from "../../utils/sources";
 
 type Data = {
   sources: Source[];
@@ -16,7 +16,7 @@ const searchHandler = async (req: NextApiRequest, res: NextApiResponse<Data>) =>
       model: OpenAIModel;
     };
 
-    const sourceCount = getSourceCount(model);
+    const sourceCount = 4;
 
     // GET LINKS
     const response = await fetch(`https://www.google.com/search?q=${query}`);
@@ -69,7 +69,7 @@ const searchHandler = async (req: NextApiRequest, res: NextApiResponse<Data>) =>
     const filteredSources = sources.filter((source) => source !== undefined);
 
     for (const source of filteredSources) {
-      source.text = shortenSourceText(source.text, model);
+      source.text = source.text.slice(0, 1500);
     }
 
     res.status(200).json({ sources: filteredSources });

diff --git a/types/index.ts b/types/index.ts
@@ -1,7 +1,5 @@
 export enum OpenAIModel {
-  DAVINCI_TEXT = "text-davinci-003",
-  CURIE_TEXT = "text-curie-001",
-  DAVINCI_CODE = "code-davinci-002"
+  DAVINCI_TURBO = "gpt-3.5-turbo"
 }
 
 export type Source = {

diff --git a/utils/answer.ts b/utils/answer.ts
@@ -1,82 +1,24 @@
-import { OpenAIModel, Source } from "@/types";
-import endent from "endent";
+import { OpenAIModel } from "@/types";
 import { createParser, ParsedEvent, ReconnectInterval } from "eventsource-parser";
 
-const createTextDavinciPrompt = (query: string, sources: Source[]) => {
-  return endent`INSTRUCTIONS
-  Provide a 2-3 sentence answer to the query based on the sources. Be original, concise, accurate, and helpful. Cite sources as [1] or [2] or [3] after each sentence to back up your answer (Ex: Correct: [1], Correct: [2][3], Incorrect: [1, 2]).
-  ###
-  SOURCES
-  
-  ${sources.map((source, idx) => `Source [${idx + 1}]:\n${source.text}`).join("\n\n")}
-  ###
-  QUERY
-  ${query}
-  ###
-  ANSWER`;
-};
-
-const createTextCuriePrompt = (query: string, sources: Source[]) => {
-  return endent`INSTRUCTIONS
-  Provide a 2-3 sentence answer to the query based on the sources. Be original, concise, accurate, and helpful.
-  ###
-  SOURCES
-  
-  ${sources.map((source, idx) => `Source [${idx + 1}]:\n${source.text}`).join("\n\n")}
-  ###
-  QUERY
-  ${query}
-  ###
-  ANSWER`;
-};
-
-const createCodeDavinciPrompt = (query: string, sources: Source[]) => {
-  return endent`INSTRUCTIONS
-  Provide a 2-3 sentence answer to the query based on the sources. Be original, concise, accurate, and helpful.
-  ###
-  SOURCES
-  
-  ${sources.map((source, idx) => `Source [${idx + 1}]:\n${source.text}`).join("\n\n")}
-  ###
-  QUERY
-  ${query}
-  ###
-  ANSWER`;
-};
-
-export const createPrompt = (query: string, sources: Source[], model: OpenAIModel) => {
-  switch (model) {
-    case OpenAIModel.DAVINCI_TEXT:
-      return createTextDavinciPrompt(query, sources);
-    case OpenAIModel.CURIE_TEXT:
-      return createTextCuriePrompt(query, sources);
-    case OpenAIModel.DAVINCI_CODE:
-      return createCodeDavinciPrompt(query, sources);
-    default:
-      return createCodeDavinciPrompt(query, sources);
-  }
-};
-
-export const OpenAIStream = async (prompt: string, model: OpenAIModel, apiKey: string) => {
+export const OpenAIStream = async (prompt: string, apiKey: string) => {
   const encoder = new TextEncoder();
   const decoder = new TextDecoder();
 
-  const res = await fetch("https://api.openai.com/v1/completions", {
+  const res = await fetch("https://api.openai.com/v1/chat/completions", {
     headers: {
       "Content-Type": "application/json",
       Authorization: `Bearer ${apiKey}`
     },
     method: "POST",
     body: JSON.stringify({
-      model,
-      prompt,
+      model: OpenAIModel.DAVINCI_TURBO,
+      messages: [
+        { role: "system", content: "You are a helpful assistant that accurately answers the user's queries based on the given text." },
+        { role: "user", content: prompt }
+      ],
       max_tokens: 120,
       temperature: 0.0,
-      top_p: 1,
-      frequency_penalty: 0,
-      presence_penalty: 0,
-      n: 1,
-      stop: ["###"],
       stream: true
     })
   });
@@ -98,7 +40,7 @@ export const OpenAIStream = async (prompt: string, model: OpenAIModel, apiKey: s
 
           try {
             const json = JSON.parse(data);
-            const text = json.choices[0].text;
+            const text = json.choices[0].delta.content;
             const queue = encoder.encode(text);
             controller.enqueue(queue);
           } catch (e) {

diff --git a/utils/sources.ts b/utils/sources.ts
@@ -1,5 +1,3 @@
-import { OpenAIModel } from "@/types";
-
 export const cleanSourceText = (text: string) => {
   return text
     .trim()
@@ -9,29 +7,3 @@ export const cleanSourceText = (text: string) => {
     .replace(/\t/g, "")
     .replace(/\n+(\s*\n)*/g, "\n");
 };
-
-export const getSourceCount = (model: OpenAIModel) => {
-  switch (model) {
-    case OpenAIModel.DAVINCI_TEXT:
-      return 3;
-    case OpenAIModel.CURIE_TEXT:
-      return 4;
-    case OpenAIModel.DAVINCI_CODE:
-      return 5;
-    default:
-      return 3;
-  }
-};
-
-export const shortenSourceText = (text: string, model: OpenAIModel) => {
-  switch (model) {
-    case OpenAIModel.DAVINCI_TEXT:
-      return text.slice(0, 1500);
-    case OpenAIModel.CURIE_TEXT:
-      return text.slice(0, 1500);
-    case OpenAIModel.DAVINCI_CODE:
-      return text.slice(0, 3000);
-    default:
-      return text.slice(0, 1500);
-  }
-};