feat(package): bump version

perf: Optimize document filtering and sorting for performance

.github/FUNDING.yml

@@ -1 +0,0 @@
-patreon: itzcrazykns

README.md

@@ -67,7 +67,8 @@ There are mainly 2 ways of installing Perplexica - With Docker, Without Docker.
 
    - `OPENAI`: Your OpenAI API key. **You only need to fill this if you wish to use OpenAI's models**.
    - `OLLAMA`: Your Ollama API URL. You should enter it as `http://host.docker.internal:PORT_NUMBER`. If you installed Ollama on port 11434, use `http://host.docker.internal:11434`. For other ports, adjust accordingly. **You need to fill this if you wish to use Ollama's models instead of OpenAI's**.
-   - `GROQ`: Your Groq API key. **You only need to fill this if you wish to use Groq's hosted models**
+   - `GROQ`: Your Groq API key. **You only need to fill this if you wish to use Groq's hosted models**.
+   - `ANTHROPIC`: Your Anthropic API key. **You only need to fill this if you wish to use Anthropic models**.
 
      **Note**: You can change these after starting Perplexica from the settings dialog.
 
@@ -111,11 +112,7 @@ If you're encountering an Ollama connection error, it is likely due to the backe
 
 3. **Linux Users - Expose Ollama to Network:**
 
-   - Serve Ollama over your network with the command:
-
-     ```bash
-     OLLAMA_HOST=0.0.0.0 ollama serve
-     ```
+   - Inside `/etc/systemd/system/ollama.service`, you need to add `Environment="OLLAMA_HOST=0.0.0.0"`. Then restart Ollama by `systemctl restart ollama`. For more information see [Ollama docs](https://github.com/ollama/ollama/blob/main/docs/faq.md#setting-environment-variables-on-linux)
 
    - Ensure that the port (default is 11434) is not blocked by your firewall.
 
@@ -149,9 +146,9 @@ If you find Perplexica useful, consider giving us a star on GitHub. This helps m
 
 We also accept donations to help sustain our project. If you would like to contribute, you can use the following options to donate. Thank you for your support!
 
-| Cards  | Ethereum |
-|---|---|
-|  https://www.patreon.com/itzcrazykns  | Address: `0xB025a84b2F269570Eb8D4b05DEdaA41D8525B6DD`  |
+| Ethereum                                              |
+| ----------------------------------------------------- |
+| Address: `0xB025a84b2F269570Eb8D4b05DEdaA41D8525B6DD` |
 
 ## Contribution
 

docs/installation/UPDATING.md

@@ -17,6 +17,7 @@ To update Perplexica to the latest version, follow these steps:
 ```bash
 docker compose up -d --build
 ```
+
 4. Once the command completes running go to http://localhost:3000 and verify the latest changes.
 
 ## For non Docker users

package.json

@@ -1,6 +1,6 @@
 {
   "name": "perplexica-backend",
-  "version": "1.7.1",
+  "version": "1.9.0-rc1",
   "license": "MIT",
   "author": "ItzCrazyKns",
   "scripts": {
@@ -15,6 +15,8 @@
     "@types/better-sqlite3": "^7.6.10",
     "@types/cors": "^2.8.17",
     "@types/express": "^4.17.21",
+    "@types/html-to-text": "^9.0.4",
+    "@types/pdf-parse": "^1.1.4",
     "@types/readable-stream": "^4.0.11",
     "drizzle-kit": "^0.22.7",
     "nodemon": "^3.1.0",
@@ -24,6 +26,7 @@
   },
   "dependencies": {
     "@iarna/toml": "^2.2.5",
+    "@langchain/anthropic": "^0.2.3",
     "@langchain/community": "^0.2.16",
     "@langchain/openai": "^0.0.25",
     "@xenova/transformers": "^2.17.1",
@@ -35,7 +38,9 @@
     "dotenv": "^16.4.5",
     "drizzle-orm": "^0.31.2",
     "express": "^4.19.2",
+    "html-to-text": "^9.0.5",
     "langchain": "^0.1.30",
+    "pdf-parse": "^1.1.1",
     "winston": "^3.13.0",
     "ws": "^8.17.1",
     "zod": "^3.22.4"

sample.config.toml

@@ -5,6 +5,7 @@ SIMILARITY_MEASURE = "cosine" # "cosine" or "dot"
 [API_KEYS]
 OPENAI = "" # OpenAI API key - sk-1234567890abcdef1234567890abcdef
 GROQ = "" # Groq API key - gsk_1234567890abcdef1234567890abcdef
+ANTHROPIC = "" # Anthropic API key - sk-ant-1234567890abcdef1234567890abcdef
 
 [API_ENDPOINTS]
 SEARXNG = "http://localhost:32768" # SearxNG API URL

src/agents/academicSearchAgent.ts

@@ -44,7 +44,7 @@ Rephrased question:
 const basicAcademicSearchResponsePrompt = `
     You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are set on focus mode 'Academic', this means you will be searching for academic papers and articles on the web.
 
-    Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containg a brief description of the content of that page).
+    Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containing a brief description of the content of that page).
     You must use this context to answer the user's query in the best way possible. Use an unbaised and journalistic tone in your response. Do not repeat the text.
     You must not tell the user to open any link or visit any website to get the answer. You must provide the answer in the response itself. If the user asks for links you can provide them.
     Your responses should be medium to long in length be informative and relevant to the user's query. You can use markdowns to format your response. You should use bullet points to list the information. Make sure the answer is not short and is informative.
@@ -52,7 +52,7 @@ const basicAcademicSearchResponsePrompt = `
     Place these citations at the end of that particular sentence. You can cite the same sentence multiple times if it is relevant to the user's query like [number1][number2].
     However you do not need to cite it using the same number. You can use different numbers to cite the same sentence multiple times. The number refers to the number of the search result (passed in the context) used to generate that part of the answer.
 
-    Aything inside the following \`context\` HTML block provided below is for your knowledge returned by the search engine and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to 
+    Anything inside the following \`context\` HTML block provided below is for your knowledge returned by the search engine and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to 
     talk about the context in your response. 
 
     <context>

src/agents/redditSearchAgent.ts

@@ -44,7 +44,7 @@ Rephrased question:
 const basicRedditSearchResponsePrompt = `
     You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are set on focus mode 'Reddit', this means you will be searching for information, opinions and discussions on the web using Reddit.
 
-    Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containg a brief description of the content of that page).
+    Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containing a brief description of the content of that page).
     You must use this context to answer the user's query in the best way possible. Use an unbaised and journalistic tone in your response. Do not repeat the text.
     You must not tell the user to open any link or visit any website to get the answer. You must provide the answer in the response itself. If the user asks for links you can provide them.
     Your responses should be medium to long in length be informative and relevant to the user's query. You can use markdowns to format your response. You should use bullet points to list the information. Make sure the answer is not short and is informative.
@@ -52,8 +52,8 @@ const basicRedditSearchResponsePrompt = `
     Place these citations at the end of that particular sentence. You can cite the same sentence multiple times if it is relevant to the user's query like [number1][number2].
     However you do not need to cite it using the same number. You can use different numbers to cite the same sentence multiple times. The number refers to the number of the search result (passed in the context) used to generate that part of the answer.
 
-    Aything inside the following \`context\` HTML block provided below is for your knowledge returned by Reddit and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to 
-    talk about the context in your response. 
+    Anything inside the following \`context\` HTML block provided below is for your knowledge returned by Reddit and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to
+    talk about the context in your response.
 
     <context>
     {context}
@@ -177,9 +177,9 @@ const createBasicRedditSearchAnsweringChain = (
     });
 
     const sortedDocs = similarity
+      .filter((sim) => sim.similarity > 0.3)
       .sort((a, b) => b.similarity - a.similarity)
       .slice(0, 15)
-      .filter((sim) => sim.similarity > 0.3)
       .map((sim) => docsWithContent[sim.index]);
 
     return sortedDocs;

src/agents/suggestionGeneratorAgent.ts

@@ -47,7 +47,7 @@ const generateSuggestions = (
   input: SuggestionGeneratorInput,
   llm: BaseChatModel,
 ) => {
-  (llm as ChatOpenAI).temperature = 0;
+  (llm as unknown as ChatOpenAI).temperature = 0;
   const suggestionGeneratorChain = createSuggestionGeneratorChain(llm);
   return suggestionGeneratorChain.invoke(input);
 };

src/agents/webSearchAgent.ts

@@ -19,20 +19,47 @@ import formatChatHistoryAsString from '../utils/formatHistory';
 import eventEmitter from 'events';
 import computeSimilarity from '../utils/computeSimilarity';
 import logger from '../utils/logger';
+import LineListOutputParser from '../lib/outputParsers/listLineOutputParser';
+import { getDocumentsFromLinks } from '../lib/linkDocument';
+import LineOutputParser from '../lib/outputParsers/lineOutputParser';
 
 const basicSearchRetrieverPrompt = `
 You will be given a conversation below and a follow up question. You need to rephrase the follow-up question if needed so it is a standalone question that can be used by the LLM to search the web for information.
 If it is a writing task or a simple hi, hello rather than a question, you need to return \`not_needed\` as the response.
+If the question contains some links and asks to answer from those links or even if they don't you need to return the links inside 'links' XML block and the question inside 'question' XML block. If there are no links then you need to return the question without any XML block.
+If the user asks to summarrize the content from some links you need to return \`Summarize\` as the question inside the 'question' XML block and the links inside the 'links' XML block.
 
 Example:
 1. Follow up question: What is the capital of France?
-Rephrased: Capital of france
+Rephrased question: \`Capital of france\`
 
 2. Follow up question: What is the population of New York City?
-Rephrased: Population of New York City
+Rephrased question: \`Population of New York City\`
 
 3. Follow up question: What is Docker?
-Rephrased: What is Docker
+Rephrased question: \`What is Docker\`
+
+4. Follow up question: Can you tell me what is X from https://example.com
+Rephrased question: \`
+<question>
+Can you tell me what is X?
+</question>
+
+<links>
+https://example.com
+</links>
+\`
+
+5. Follow up question: Summarize the content from https://example.com
+Rephrased question: \`
+<question>
+Summarize
+</question>
+
+<links>
+https://example.com
+</links>
+\`
 
 Conversation:
 {chat_history}
@@ -42,24 +69,26 @@ Rephrased question:
 `;
 
 const basicWebSearchResponsePrompt = `
-    You are Perplexica, an AI model who is expert at searching the web and answering user's queries.
+    You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are also an expert at summarizing web pages or documents and searching for content in them.
 
-    Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containg a brief description of the content of that page).
+    Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containing a brief description of the content of that page).
     You must use this context to answer the user's query in the best way possible. Use an unbaised and journalistic tone in your response. Do not repeat the text.
     You must not tell the user to open any link or visit any website to get the answer. You must provide the answer in the response itself. If the user asks for links you can provide them.
+    If the query contains some links and the user asks to answer from those links you will be provided the entire content of the page inside the \`context\` XML block. You can then use this content to answer the user's query.
+    If the user asks to summarize content from some links, you will be provided the entire content of the page inside the \`context\` XML block. You can then use this content to summarize the text. The content provided inside the \`context\` block will be already summarized by another model so you just need to use that content to answer the user's query.
     Your responses should be medium to long in length be informative and relevant to the user's query. You can use markdowns to format your response. You should use bullet points to list the information. Make sure the answer is not short and is informative.
     You have to cite the answer using [number] notation. You must cite the sentences with their relevent context number. You must cite each and every part of the answer so the user can know where the information is coming from.
     Place these citations at the end of that particular sentence. You can cite the same sentence multiple times if it is relevant to the user's query like [number1][number2].
     However you do not need to cite it using the same number. You can use different numbers to cite the same sentence multiple times. The number refers to the number of the search result (passed in the context) used to generate that part of the answer.
 
-    Aything inside the following \`context\` HTML block provided below is for your knowledge returned by the search engine and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to 
-    talk about the context in your response. 
+    Anything inside the following \`context\` HTML block provided below is for your knowledge returned by the search engine and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to
+    talk about the context in your response.
 
     <context>
     {context}
     </context>
 
-    If you think there's nothing relevant in the search results, you can say that 'Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?'.
+    If you think there's nothing relevant in the search results, you can say that 'Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?'. You do not need to do this for summarization tasks.
     Anything between the \`context\` is retrieved from a search engine and is not a part of the conversation with the user. Today's date is ${new Date().toISOString()}
 `;
 
@@ -112,23 +141,100 @@ const createBasicWebSearchRetrieverChain = (llm: BaseChatModel) => {
         return { query: '', docs: [] };
       }
 
-      const res = await searchSearxng(input, {
-        language: 'en',
+      const linksOutputParser = new LineListOutputParser({
+        key: 'links',
       });
 
-      const documents = res.results.map(
-        (result) =>
-          new Document({
-            pageContent: result.content,
-            metadata: {
-              title: result.title,
-              url: result.url,
-              ...(result.img_src && { img_src: result.img_src }),
-            },
-          }),
-      );
+      const questionOutputParser = new LineOutputParser({
+        key: 'question',
+      });
 
-      return { query: input, docs: documents };
+      const links = await linksOutputParser.parse(input);
+      let question = await questionOutputParser.parse(input);
+
+      if (links.length > 0) {
+        if (question.length === 0) {
+          question = 'Summarize';
+        }
+
+        let docs = []
+
+        const linkDocs = await getDocumentsFromLinks({ links });
+
+        const docGroups: Document[] = [];
+
+        linkDocs.map((doc) => {
+          const URLDocExists = docGroups.find((d) => d.metadata.url === doc.metadata.url && d.metadata.totalDocs < 10);
+
+          if (!URLDocExists) {
+            docGroups.push({
+              ...doc,
+              metadata: {
+                ...doc.metadata,
+                totalDocs: 1
+              }
+            });
+          }
+
+          const docIndex = docGroups.findIndex((d) => d.metadata.url === doc.metadata.url && d.metadata.totalDocs < 10);
+
+          if (docIndex !== -1) {
+            docGroups[docIndex].pageContent = docGroups[docIndex].pageContent + `\n\n` +  doc.pageContent;
+            docGroups[docIndex].metadata.totalDocs += 1;
+          }
+        })
+
+        await Promise.all(docGroups.map(async (doc) => {
+          const res = await llm.invoke(`
+            You are a text summarizer. You need to summarize the text provided inside the \`text\` XML block. 
+            You need to summarize the text into 1 or 2 sentences capturing the main idea of the text.
+            You need to make sure that you don't miss any point while summarizing the text.
+            You will also be given a \`query\` XML block which will contain the query of the user. Try to answer the query in the summary from the text provided.
+            If the query says Summarize then you just need to summarize the text without answering the query.
+            Only return the summarized text without any other messages, text or XML block.
+
+            <query>
+            ${question}
+            </query>
+
+            <text>
+            ${doc.pageContent}
+            </text>
+
+            Make sure to answer the query in the summary.
+          `);
+
+          const document = new Document({
+            pageContent: res.content as string,
+            metadata: {
+              title: doc.metadata.title,
+              url: doc.metadata.url,
+            },
+          })
+          
+          docs.push(document)
+        }))
+
+        return { query: question, docs: docs };
+      } else {
+        const res = await searchSearxng(input, {
+          language: 'en',
+        });
+
+        const documents = res.results.map(
+          (result) =>
+            new Document({
+              pageContent: result.content,
+              metadata: {
+                title: result.title,
+                url: result.url,
+                ...(result.img_src && { img_src: result.img_src }),
+              },
+            }),
+        );
+
+        return { query: input, docs: documents };
+      }
     }),
   ]);
 };
@@ -156,6 +262,10 @@ const createBasicWebSearchAnsweringChain = (
       return docs;
     }
 
+    if (query === 'Summarize') {
+      return docs;
+    }
+
     const docsWithContent = docs.filter(
       (doc) => doc.pageContent && doc.pageContent.length > 0,
     );
@@ -175,8 +285,8 @@ const createBasicWebSearchAnsweringChain = (
     });
 
     const sortedDocs = similarity
-      .sort((a, b) => b.similarity - a.similarity)
       .filter((sim) => sim.similarity > 0.5)
+      .sort((a, b) => b.similarity - a.similarity)
       .slice(0, 15)
       .map((sim) => docsWithContent[sim.index]);
 

src/agents/wolframAlphaSearchAgent.ts

@@ -43,7 +43,7 @@ Rephrased question:
 const basicWolframAlphaSearchResponsePrompt = `
     You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are set on focus mode 'Wolfram Alpha', this means you will be searching for information on the web using Wolfram Alpha. It is a computational knowledge engine that can answer factual queries and perform computations.
 
-    Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containg a brief description of the content of that page).
+    Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containing a brief description of the content of that page).
     You must use this context to answer the user's query in the best way possible. Use an unbaised and journalistic tone in your response. Do not repeat the text.
     You must not tell the user to open any link or visit any website to get the answer. You must provide the answer in the response itself. If the user asks for links you can provide them.
     Your responses should be medium to long in length be informative and relevant to the user's query. You can use markdowns to format your response. You should use bullet points to list the information. Make sure the answer is not short and is informative.
@@ -51,7 +51,7 @@ const basicWolframAlphaSearchResponsePrompt = `
     Place these citations at the end of that particular sentence. You can cite the same sentence multiple times if it is relevant to the user's query like [number1][number2].
     However you do not need to cite it using the same number. You can use different numbers to cite the same sentence multiple times. The number refers to the number of the search result (passed in the context) used to generate that part of the answer.
 
-    Aything inside the following \`context\` HTML block provided below is for your knowledge returned by Wolfram Alpha and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to 
+    Anything inside the following \`context\` HTML block provided below is for your knowledge returned by Wolfram Alpha and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to 
     talk about the context in your response. 
 
     <context>

src/agents/youtubeSearchAgent.ts

@@ -44,7 +44,7 @@ Rephrased question:
 const basicYoutubeSearchResponsePrompt = `
     You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are set on focus mode 'Youtube', this means you will be searching for videos on the web using Youtube and providing information based on the video's transcript.
 
-    Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containg a brief description of the content of that page).
+    Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containing a brief description of the content of that page).
     You must use this context to answer the user's query in the best way possible. Use an unbaised and journalistic tone in your response. Do not repeat the text.
     You must not tell the user to open any link or visit any website to get the answer. You must provide the answer in the response itself. If the user asks for links you can provide them.
     Your responses should be medium to long in length be informative and relevant to the user's query. You can use markdowns to format your response. You should use bullet points to list the information. Make sure the answer is not short and is informative.
@@ -52,8 +52,8 @@ const basicYoutubeSearchResponsePrompt = `
     Place these citations at the end of that particular sentence. You can cite the same sentence multiple times if it is relevant to the user's query like [number1][number2].
     However you do not need to cite it using the same number. You can use different numbers to cite the same sentence multiple times. The number refers to the number of the search result (passed in the context) used to generate that part of the answer.
 
-    Aything inside the following \`context\` HTML block provided below is for your knowledge returned by Youtube and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to 
-    talk about the context in your response. 
+    Anything inside the following \`context\` HTML block provided below is for your knowledge returned by Youtube and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to
+    talk about the context in your response.
 
     <context>
     {context}
@@ -177,9 +177,9 @@ const createBasicYoutubeSearchAnsweringChain = (
     });
 
     const sortedDocs = similarity
+      .filter((sim) => sim.similarity > 0.3)
       .sort((a, b) => b.similarity - a.similarity)
       .slice(0, 15)
-      .filter((sim) => sim.similarity > 0.3)
       .map((sim) => docsWithContent[sim.index]);
 
     return sortedDocs;

src/app.ts

@@ -28,3 +28,11 @@ server.listen(port, () => {
 });
 
 startWebSocketServer(server);
+
+process.on('uncaughtException', (err, origin) => {
+  logger.error(`Uncaught Exception at ${origin}: ${err}`)
+})
+
+process.on('unhandledRejection', (reason, promise) => {
+  logger.error(`Unhandled Rejection at: ${promise}, reason: ${reason}`)
+})

src/config.ts

@@ -12,6 +12,7 @@ interface Config {
   API_KEYS: {
     OPENAI: string;
     GROQ: string;
+    ANTHROPIC: string;
   };
   API_ENDPOINTS: {
     SEARXNG: string;
@@ -37,6 +38,8 @@ export const getOpenaiApiKey = () => loadConfig().API_KEYS.OPENAI;
 
 export const getGroqApiKey = () => loadConfig().API_KEYS.GROQ;
 
+export const getAnthropicApiKey = () => loadConfig().API_KEYS.ANTHROPIC;
+
 export const getSearxngApiEndpoint = () => loadConfig().API_ENDPOINTS.SEARXNG;
 
 export const getOllamaApiEndpoint = () => loadConfig().API_ENDPOINTS.OLLAMA;

src/lib/linkDocument.ts

@@ -0,0 +1,81 @@
+import axios from 'axios';
+import { htmlToText } from 'html-to-text'
+import { RecursiveCharacterTextSplitter } from 'langchain/text_splitter';
+import { Document } from '@langchain/core/documents';
+import pdfParse from 'pdf-parse'
+
+export const getDocumentsFromLinks = async ({ links }: { links: string[] }) => {
+  const splitter = new RecursiveCharacterTextSplitter();
+
+  let docs: Document[] = [];
+
+  await Promise.all(
+    links.map(async (link) => {
+      link =
+        link.startsWith('http://') || link.startsWith('https://')
+          ? link
+          : `https://${link}`;
+
+      const res = await axios.get(link, {
+        responseType: 'arraybuffer',
+      });
+
+      const isPdf = res.headers['content-type'] === 'application/pdf';
+
+      if (isPdf) {
+        const pdfText = await pdfParse(res.data)
+        const parsedText = pdfText.text
+          .replace(/(\r\n|\n|\r)/gm, ' ')
+          .replace(/\s+/g, ' ')
+          .trim();
+
+        const splittedText = await splitter.splitText(parsedText);
+        const title = 'PDF Document'
+
+        const linkDocs = splittedText.map((text) => {
+          return new Document({
+            pageContent: text,
+            metadata: {
+              title: title,
+              url: link,
+            },
+          });
+        });
+
+        docs.push(...linkDocs);
+        return;
+      }
+
+      const parsedText = htmlToText(res.data.toString('utf8'), {
+        selectors: [
+          {
+            selector: 'a',
+            options: {
+              ignoreHref: true,
+            }
+          },
+        ]
+      })
+        .replace(/(\r\n|\n|\r)/gm, ' ')
+        .replace(/\s+/g, ' ')
+        .trim();
+
+      const splittedText = await splitter.splitText(parsedText);
+      const title = res.data.toString('utf8').match(/<title>(.*?)<\/title>/)?.[1];
+
+      const linkDocs = splittedText.map((text) => {
+        return new Document({
+          pageContent: text,
+          metadata: {
+            title: title || link,
+            url: link,
+          },
+        });
+      });
+
+      docs.push(...linkDocs);
+    }),
+  );
+
+  return docs;
+};

src/lib/outputParsers/lineOutputParser.ts

@@ -0,0 +1,46 @@
+import { BaseOutputParser } from '@langchain/core/output_parsers';
+
+interface LineOutputParserArgs {
+  key?: string;
+}
+
+class LineOutputParser extends BaseOutputParser<string> {
+  private key = 'questions';
+
+  constructor(args?: LineOutputParserArgs) {
+    super();
+    this.key = args.key ?? this.key;
+  }
+
+  static lc_name() {
+    return 'LineOutputParser';
+  }
+
+  lc_namespace = ['langchain', 'output_parsers', 'line_output_parser'];
+
+  async parse(text: string): Promise<string> {
+    const regex = /^(\s*(-|\*|\d+\.\s|\d+\)\s|\u2022)\s*)+/;
+    const startKeyIndex = text.indexOf(`<${this.key}>`);
+    const endKeyIndex = text.indexOf(`</${this.key}>`);
+
+    if (startKeyIndex === -1 || endKeyIndex === -1) {
+      return '';
+    }
+
+    const questionsStartIndex =
+      startKeyIndex === -1 ? 0 : startKeyIndex + `<${this.key}>`.length;
+    const questionsEndIndex = endKeyIndex === -1 ? text.length : endKeyIndex;
+    const line = text
+      .slice(questionsStartIndex, questionsEndIndex)
+      .trim()
+      .replace(regex, '');
+
+    return line;
+  }
+
+  getFormatInstructions(): string {
+    throw new Error('Not implemented.');
+  }
+}
+
+export default LineOutputParser;

src/lib/outputParsers/listLineOutputParser.ts

@@ -22,6 +22,11 @@ class LineListOutputParser extends BaseOutputParser<string[]> {
     const regex = /^(\s*(-|\*|\d+\.\s|\d+\)\s|\u2022)\s*)+/;
     const startKeyIndex = text.indexOf(`<${this.key}>`);
     const endKeyIndex = text.indexOf(`</${this.key}>`);
+
+    if (startKeyIndex === -1 || endKeyIndex === -1) {
+      return [];
+    }
+
     const questionsStartIndex =
       startKeyIndex === -1 ? 0 : startKeyIndex + `<${this.key}>`.length;
     const questionsEndIndex = endKeyIndex === -1 ? text.length : endKeyIndex;

src/lib/providers.ts

@@ -1,187 +0,0 @@
-import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
-import { ChatOllama } from '@langchain/community/chat_models/ollama';
-import { OllamaEmbeddings } from '@langchain/community/embeddings/ollama';
-import { HuggingFaceTransformersEmbeddings } from './huggingfaceTransformer';
-import {
-  getGroqApiKey,
-  getOllamaApiEndpoint,
-  getOpenaiApiKey,
-} from '../config';
-import logger from '../utils/logger';
-
-export const getAvailableChatModelProviders = async () => {
-  const openAIApiKey = getOpenaiApiKey();
-  const groqApiKey = getGroqApiKey();
-  const ollamaEndpoint = getOllamaApiEndpoint();
-
-  const models = {};
-
-  if (openAIApiKey) {
-    try {
-      models['openai'] = {
-        'GPT-3.5 turbo': new ChatOpenAI({
-          openAIApiKey,
-          modelName: 'gpt-3.5-turbo',
-          temperature: 0.7,
-        }),
-        'GPT-4': new ChatOpenAI({
-          openAIApiKey,
-          modelName: 'gpt-4',
-          temperature: 0.7,
-        }),
-        'GPT-4 turbo': new ChatOpenAI({
-          openAIApiKey,
-          modelName: 'gpt-4-turbo',
-          temperature: 0.7,
-        }),
-        'GPT-4 omni': new ChatOpenAI({
-          openAIApiKey,
-          modelName: 'gpt-4o',
-          temperature: 0.7,
-        }),
-      };
-    } catch (err) {
-      logger.error(`Error loading OpenAI models: ${err}`);
-    }
-  }
-
-  if (groqApiKey) {
-    try {
-      models['groq'] = {
-        'LLaMA3 8b': new ChatOpenAI(
-          {
-            openAIApiKey: groqApiKey,
-            modelName: 'llama3-8b-8192',
-            temperature: 0.7,
-          },
-          {
-            baseURL: 'https://api.groq.com/openai/v1',
-          },
-        ),
-        'LLaMA3 70b': new ChatOpenAI(
-          {
-            openAIApiKey: groqApiKey,
-            modelName: 'llama3-70b-8192',
-            temperature: 0.7,
-          },
-          {
-            baseURL: 'https://api.groq.com/openai/v1',
-          },
-        ),
-        'Mixtral 8x7b': new ChatOpenAI(
-          {
-            openAIApiKey: groqApiKey,
-            modelName: 'mixtral-8x7b-32768',
-            temperature: 0.7,
-          },
-          {
-            baseURL: 'https://api.groq.com/openai/v1',
-          },
-        ),
-        'Gemma 7b': new ChatOpenAI(
-          {
-            openAIApiKey: groqApiKey,
-            modelName: 'gemma-7b-it',
-            temperature: 0.7,
-          },
-          {
-            baseURL: 'https://api.groq.com/openai/v1',
-          },
-        ),
-      };
-    } catch (err) {
-      logger.error(`Error loading Groq models: ${err}`);
-    }
-  }
-
-  if (ollamaEndpoint) {
-    try {
-      const response = await fetch(`${ollamaEndpoint}/api/tags`, {
-        headers: {
-          'Content-Type': 'application/json',
-        },
-      });
-
-      const { models: ollamaModels } = (await response.json()) as any;
-
-      models['ollama'] = ollamaModels.reduce((acc, model) => {
-        acc[model.model] = new ChatOllama({
-          baseUrl: ollamaEndpoint,
-          model: model.model,
-          temperature: 0.7,
-        });
-        return acc;
-      }, {});
-    } catch (err) {
-      logger.error(`Error loading Ollama models: ${err}`);
-    }
-  }
-
-  models['custom_openai'] = {};
-
-  return models;
-};
-
-export const getAvailableEmbeddingModelProviders = async () => {
-  const openAIApiKey = getOpenaiApiKey();
-  const ollamaEndpoint = getOllamaApiEndpoint();
-
-  const models = {};
-
-  if (openAIApiKey) {
-    try {
-      models['openai'] = {
-        'Text embedding 3 small': new OpenAIEmbeddings({
-          openAIApiKey,
-          modelName: 'text-embedding-3-small',
-        }),
-        'Text embedding 3 large': new OpenAIEmbeddings({
-          openAIApiKey,
-          modelName: 'text-embedding-3-large',
-        }),
-      };
-    } catch (err) {
-      logger.error(`Error loading OpenAI embeddings: ${err}`);
-    }
-  }
-
-  if (ollamaEndpoint) {
-    try {
-      const response = await fetch(`${ollamaEndpoint}/api/tags`, {
-        headers: {
-          'Content-Type': 'application/json',
-        },
-      });
-
-      const { models: ollamaModels } = (await response.json()) as any;
-
-      models['ollama'] = ollamaModels.reduce((acc, model) => {
-        acc[model.model] = new OllamaEmbeddings({
-          baseUrl: ollamaEndpoint,
-          model: model.model,
-        });
-        return acc;
-      }, {});
-    } catch (err) {
-      logger.error(`Error loading Ollama embeddings: ${err}`);
-    }
-  }
-
-  try {
-    models['local'] = {
-      'BGE Small': new HuggingFaceTransformersEmbeddings({
-        modelName: 'Xenova/bge-small-en-v1.5',
-      }),
-      'GTE Small': new HuggingFaceTransformersEmbeddings({
-        modelName: 'Xenova/gte-small',
-      }),
-      'Bert Multilingual': new HuggingFaceTransformersEmbeddings({
-        modelName: 'Xenova/bert-base-multilingual-uncased',
-      }),
-    };
-  } catch (err) {
-    logger.error(`Error loading local embeddings: ${err}`);
-  }
-
-  return models;
-};

src/lib/providers/anthropic.ts

@@ -0,0 +1,39 @@
+import { ChatAnthropic } from '@langchain/anthropic';
+import { getAnthropicApiKey } from '../../config';
+import logger from '../../utils/logger';
+
+export const loadAnthropicChatModels = async () => {
+  const anthropicApiKey = getAnthropicApiKey();
+
+  if (!anthropicApiKey) return {};
+
+  try {
+    const chatModels = {
+      'Claude 3.5 Sonnet': new ChatAnthropic({
+        temperature: 0.7,
+        anthropicApiKey: anthropicApiKey,
+        model: 'claude-3-5-sonnet-20240620',
+      }),
+      'Claude 3 Opus': new ChatAnthropic({
+        temperature: 0.7,
+        anthropicApiKey: anthropicApiKey,
+        model: 'claude-3-opus-20240229',
+      }),
+      'Claude 3 Sonnet': new ChatAnthropic({
+        temperature: 0.7,
+        anthropicApiKey: anthropicApiKey,
+        model: 'claude-3-sonnet-20240229',
+      }),
+      'Claude 3 Haiku': new ChatAnthropic({
+        temperature: 0.7,
+        anthropicApiKey: anthropicApiKey,
+        model: 'claude-3-haiku-20240307',
+      }),
+    };
+
+    return chatModels;
+  } catch (err) {
+    logger.error(`Error loading Anthropic models: ${err}`);
+    return {};
+  }
+};

src/lib/providers/groq.ts

@@ -0,0 +1,89 @@
+import { ChatOpenAI } from '@langchain/openai';
+import { getGroqApiKey } from '../../config';
+import logger from '../../utils/logger';
+
+export const loadGroqChatModels = async () => {
+  const groqApiKey = getGroqApiKey();
+
+  if (!groqApiKey) return {};
+
+  try {
+    const chatModels = {
+      'Llama 3.1 70B': new ChatOpenAI(
+        {
+          openAIApiKey: groqApiKey,
+          modelName: 'llama-3.1-70b-versatile',
+          temperature: 0.7,
+        },
+        {
+          baseURL: 'https://api.groq.com/openai/v1',
+        },
+      ),
+      'Llama 3.1 8B': new ChatOpenAI(
+        {
+          openAIApiKey: groqApiKey,
+          modelName: 'llama-3.1-8b-instant',
+          temperature: 0.7,
+        },
+        {
+          baseURL: 'https://api.groq.com/openai/v1',
+        },
+      ),
+      'LLaMA3 8b': new ChatOpenAI(
+        {
+          openAIApiKey: groqApiKey,
+          modelName: 'llama3-8b-8192',
+          temperature: 0.7,
+        },
+        {
+          baseURL: 'https://api.groq.com/openai/v1',
+        },
+      ),
+      'LLaMA3 70b': new ChatOpenAI(
+        {
+          openAIApiKey: groqApiKey,
+          modelName: 'llama3-70b-8192',
+          temperature: 0.7,
+        },
+        {
+          baseURL: 'https://api.groq.com/openai/v1',
+        },
+      ),
+      'Mixtral 8x7b': new ChatOpenAI(
+        {
+          openAIApiKey: groqApiKey,
+          modelName: 'mixtral-8x7b-32768',
+          temperature: 0.7,
+        },
+        {
+          baseURL: 'https://api.groq.com/openai/v1',
+        },
+      ),
+      'Gemma 7b': new ChatOpenAI(
+        {
+          openAIApiKey: groqApiKey,
+          modelName: 'gemma-7b-it',
+          temperature: 0.7,
+        },
+        {
+          baseURL: 'https://api.groq.com/openai/v1',
+        },
+      ),
+      'Gemma2 9b': new ChatOpenAI(
+        {
+          openAIApiKey: groqApiKey,
+          modelName: 'gemma2-9b-it',
+          temperature: 0.7,
+        },
+        {
+          baseURL: 'https://api.groq.com/openai/v1',
+        },
+      ),
+    };
+
+    return chatModels;
+  } catch (err) {
+    logger.error(`Error loading Groq models: ${err}`);
+    return {};
+  }
+};

src/lib/providers/index.ts

@@ -0,0 +1,46 @@
+import { loadGroqChatModels } from './groq';
+import { loadOllamaChatModels, loadOllamaEmbeddingsModels } from './ollama';
+import { loadOpenAIChatModels, loadOpenAIEmbeddingsModels } from './openai';
+import { loadAnthropicChatModels } from './anthropic';
+import { loadTransformersEmbeddingsModels } from './transformers';
+
+const chatModelProviders = {
+  openai: loadOpenAIChatModels,
+  groq: loadGroqChatModels,
+  ollama: loadOllamaChatModels,
+  anthropic: loadAnthropicChatModels,
+};
+
+const embeddingModelProviders = {
+  openai: loadOpenAIEmbeddingsModels,
+  local: loadTransformersEmbeddingsModels,
+  ollama: loadOllamaEmbeddingsModels,
+};
+
+export const getAvailableChatModelProviders = async () => {
+  const models = {};
+
+  for (const provider in chatModelProviders) {
+    const providerModels = await chatModelProviders[provider]();
+    if (Object.keys(providerModels).length > 0) {
+      models[provider] = providerModels;
+    }
+  }
+
+  models['custom_openai'] = {};
+
+  return models;
+};
+
+export const getAvailableEmbeddingModelProviders = async () => {
+  const models = {};
+
+  for (const provider in embeddingModelProviders) {
+    const providerModels = await embeddingModelProviders[provider]();
+    if (Object.keys(providerModels).length > 0) {
+      models[provider] = providerModels;
+    }
+  }
+
+  return models;
+};

src/lib/providers/ollama.ts

@@ -0,0 +1,63 @@
+import { OllamaEmbeddings } from '@langchain/community/embeddings/ollama';
+import { getOllamaApiEndpoint } from '../../config';
+import logger from '../../utils/logger';
+import { ChatOllama } from '@langchain/community/chat_models/ollama';
+
+export const loadOllamaChatModels = async () => {
+  const ollamaEndpoint = getOllamaApiEndpoint();
+
+  if (!ollamaEndpoint) return {};
+
+  try {
+    const response = await fetch(`${ollamaEndpoint}/api/tags`, {
+      headers: {
+        'Content-Type': 'application/json',
+      },
+    });
+
+    const { models: ollamaModels } = (await response.json()) as any;
+
+    const chatModels = ollamaModels.reduce((acc, model) => {
+      acc[model.model] = new ChatOllama({
+        baseUrl: ollamaEndpoint,
+        model: model.model,
+        temperature: 0.7,
+      });
+      return acc;
+    }, {});
+
+    return chatModels;
+  } catch (err) {
+    logger.error(`Error loading Ollama models: ${err}`);
+    return {};
+  }
+};
+
+export const loadOllamaEmbeddingsModels = async () => {
+  const ollamaEndpoint = getOllamaApiEndpoint();
+
+  if (!ollamaEndpoint) return {};
+
+  try {
+    const response = await fetch(`${ollamaEndpoint}/api/tags`, {
+      headers: {
+        'Content-Type': 'application/json',
+      },
+    });
+
+    const { models: ollamaModels } = (await response.json()) as any;
+
+    const embeddingsModels = ollamaModels.reduce((acc, model) => {
+      acc[model.model] = new OllamaEmbeddings({
+        baseUrl: ollamaEndpoint,
+        model: model.model,
+      });
+      return acc;
+    }, {});
+
+    return embeddingsModels;
+  } catch (err) {
+    logger.error(`Error loading Ollama embeddings model: ${err}`);
+    return {};
+  }
+};

src/lib/providers/openai.ts

@@ -0,0 +1,68 @@
+import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
+import { getOpenaiApiKey } from '../../config';
+import logger from '../../utils/logger';
+
+export const loadOpenAIChatModels = async () => {
+  const openAIApiKey = getOpenaiApiKey();
+
+  if (!openAIApiKey) return {};
+
+  try {
+    const chatModels = {
+      'GPT-3.5 turbo': new ChatOpenAI({
+        openAIApiKey,
+        modelName: 'gpt-3.5-turbo',
+        temperature: 0.7,
+      }),
+      'GPT-4': new ChatOpenAI({
+        openAIApiKey,
+        modelName: 'gpt-4',
+        temperature: 0.7,
+      }),
+      'GPT-4 turbo': new ChatOpenAI({
+        openAIApiKey,
+        modelName: 'gpt-4-turbo',
+        temperature: 0.7,
+      }),
+      'GPT-4 omni': new ChatOpenAI({
+        openAIApiKey,
+        modelName: 'gpt-4o',
+        temperature: 0.7,
+      }),
+      'GPT-4 omni mini': new ChatOpenAI({
+        openAIApiKey,
+        modelName: 'gpt-4o-mini',
+        temperature: 0.7,
+      }),
+    };
+
+    return chatModels;
+  } catch (err) {
+    logger.error(`Error loading OpenAI models: ${err}`);
+    return {};
+  }
+};
+
+export const loadOpenAIEmbeddingsModels = async () => {
+  const openAIApiKey = getOpenaiApiKey();
+
+  if (!openAIApiKey) return {};
+
+  try {
+    const embeddingModels = {
+      'Text embedding 3 small': new OpenAIEmbeddings({
+        openAIApiKey,
+        modelName: 'text-embedding-3-small',
+      }),
+      'Text embedding 3 large': new OpenAIEmbeddings({
+        openAIApiKey,
+        modelName: 'text-embedding-3-large',
+      }),
+    };
+
+    return embeddingModels;
+  } catch (err) {
+    logger.error(`Error loading OpenAI embeddings model: ${err}`);
+    return {};
+  }
+};

src/lib/providers/transformers.ts

@@ -0,0 +1,23 @@
+import logger from '../../utils/logger';
+import { HuggingFaceTransformersEmbeddings } from '../huggingfaceTransformer';
+
+export const loadTransformersEmbeddingsModels = async () => {
+  try {
+    const embeddingModels = {
+      'BGE Small': new HuggingFaceTransformersEmbeddings({
+        modelName: 'Xenova/bge-small-en-v1.5',
+      }),
+      'GTE Small': new HuggingFaceTransformersEmbeddings({
+        modelName: 'Xenova/gte-small',
+      }),
+      'Bert Multilingual': new HuggingFaceTransformersEmbeddings({
+        modelName: 'Xenova/bert-base-multilingual-uncased',
+      }),
+    };
+
+    return embeddingModels;
+  } catch (err) {
+    logger.error(`Error loading Transformers embeddings model: ${err}`);
+    return {};
+  }
+};

src/routes/config.ts

@@ -6,6 +6,7 @@ import {
 import {
   getGroqApiKey,
   getOllamaApiEndpoint,
+  getAnthropicApiKey,
   getOpenaiApiKey,
   updateConfig,
 } from '../config';
@@ -37,6 +38,7 @@ router.get('/', async (_, res) => {
 
   config['openaiApiKey'] = getOpenaiApiKey();
   config['ollamaApiUrl'] = getOllamaApiEndpoint();
+  config['anthropicApiKey'] = getAnthropicApiKey();
   config['groqApiKey'] = getGroqApiKey();
 
   res.status(200).json(config);
@@ -49,6 +51,7 @@ router.post('/', async (req, res) => {
     API_KEYS: {
       OPENAI: config.openaiApiKey,
       GROQ: config.groqApiKey,
+      ANTHROPIC: config.anthropicApiKey,
     },
     API_ENDPOINTS: {
       OLLAMA: config.ollamaApiUrl,

src/websocket/connectionManager.ts

@@ -45,7 +45,7 @@ export const handleConnection = async (
       chatModelProviders[chatModelProvider][chatModel] &&
       chatModelProvider != 'custom_openai'
     ) {
-      llm = chatModelProviders[chatModelProvider][chatModel] as
+      llm = chatModelProviders[chatModelProvider][chatModel] as unknown as
         | BaseChatModel
         | undefined;
     } else if (chatModelProvider == 'custom_openai') {
@@ -56,7 +56,7 @@ export const handleConnection = async (
         configuration: {
           baseURL: searchParams.get('openAIBaseURL'),
         },
-      });
+      }) as unknown as BaseChatModel;
     }
 
     if (

ui/app/layout.tsx

@@ -34,7 +34,7 @@ export default function RootLayout({
               unstyled: true,
               classNames: {
                 toast:
-                  'bg-light-primary dark:bg-dark-primary text-white rounded-lg p-4 flex flex-row items-center space-x-2',
+                  'bg-light-primary dark:bg-dark-secondary dark:text-white/70 text-black-70 rounded-lg p-4 flex flex-row items-center space-x-2',
               },
             }}
           />

ui/components/ChatWindow.tsx

@@ -54,13 +54,26 @@ const useSocket = (
           ).then(async (res) => await res.json());
 
           const chatModelProviders = providers.chatModelProviders;
-          const embeddingModelProviders = providers.embeddingModelProviders;
 
-          if (
-            !chatModelProviders ||
-            Object.keys(chatModelProviders).length === 0
-          )
-            return toast.error('No chat models available');
+          chatModelProvider = Object.keys(chatModelProviders)[0];
+
+          if (chatModelProvider === 'custom_openai') {
+            toast.error(
+              'Seems like you are using the custom OpenAI provider, please open the settings and configure the API key and base URL',
+            );
+            setError(true);
+            return;
+          } else {
+            chatModel = Object.keys(chatModelProviders[chatModelProvider])[0];
+
+            if (
+              !chatModelProviders ||
+              Object.keys(chatModelProviders).length === 0
+            )
+              return toast.error('No chat models available');
+          }
+
+          const embeddingModelProviders = providers.embeddingModelProviders;
 
           if (
             !embeddingModelProviders ||
@@ -68,9 +81,6 @@ const useSocket = (
           )
             return toast.error('No embedding models available');
 
-          chatModelProvider = Object.keys(chatModelProviders)[0];
-          chatModel = Object.keys(chatModelProviders[chatModelProvider])[0];
-
           embeddingModelProvider = Object.keys(embeddingModelProviders)[0];
           embeddingModel = Object.keys(
             embeddingModelProviders[embeddingModelProvider],
@@ -83,6 +93,56 @@ const useSocket = (
             'embeddingModelProvider',
             embeddingModelProvider,
           );
+        } else {
+          const providers = await fetch(
+            `${process.env.NEXT_PUBLIC_API_URL}/models`,
+            {
+              headers: {
+                'Content-Type': 'app  lication/json',
+              },
+            },
+          ).then(async (res) => await res.json());
+
+          const chatModelProviders = providers.chatModelProviders;
+          const embeddingModelProviders = providers.embeddingModelProviders;
+
+          if (
+            Object.keys(chatModelProviders).length > 0 &&
+            !chatModelProviders[chatModelProvider]
+          ) {
+            chatModelProvider = Object.keys(chatModelProviders)[0];
+            localStorage.setItem('chatModelProvider', chatModelProvider);
+          }
+
+          if (
+            chatModelProvider &&
+            chatModelProvider != 'custom_openai' &&
+            !chatModelProviders[chatModelProvider][chatModel]
+          ) {
+            chatModel = Object.keys(chatModelProviders[chatModelProvider])[0];
+            localStorage.setItem('chatModel', chatModel);
+          }
+
+          if (
+            Object.keys(embeddingModelProviders).length > 0 &&
+            !embeddingModelProviders[embeddingModelProvider]
+          ) {
+            embeddingModelProvider = Object.keys(embeddingModelProviders)[0];
+            localStorage.setItem(
+              'embeddingModelProvider',
+              embeddingModelProvider,
+            );
+          }
+
+          if (
+            embeddingModelProvider &&
+            !embeddingModelProviders[embeddingModelProvider][embeddingModel]
+          ) {
+            embeddingModel = Object.keys(
+              embeddingModelProviders[embeddingModelProvider],
+            )[0];
+            localStorage.setItem('embeddingModel', embeddingModel);
+          }
         }
 
         const wsURL = new URL(url);
@@ -138,6 +198,13 @@ const useSocket = (
           console.log('[DEBUG] closed');
         };
 
+        ws.addEventListener('message', (e) => {
+          const data = JSON.parse(e.data);
+          if (data.type === 'error') {
+            toast.error(data.data);
+          }
+        });
+
         setWs(ws);
       };
 
@@ -145,8 +212,10 @@ const useSocket = (
     }
 
     return () => {
-      ws?.close();
-      console.log('[DEBUG] closed');
+      if (ws?.readyState === 1) {
+        ws?.close();
+        console.log('[DEBUG] closed');
+      }
     };
   }, [ws, url, setIsWSReady, setError]);
 

ui/components/SettingsDialog.tsx

@@ -56,6 +56,7 @@ interface SettingsType {
   };
   openaiApiKey: string;
   groqApiKey: string;
+  anthropicApiKey: string;
   ollamaApiUrl: string;
 }
 
@@ -224,9 +225,13 @@ const SettingsDialog = ({
                           value={selectedChatModelProvider ?? undefined}
                           onChange={(e) => {
                             setSelectedChatModelProvider(e.target.value);
-                            setSelectedChatModel(
-                              config.chatModelProviders[e.target.value][0],
-                            );
+                            if (e.target.value === 'custom_openai') {
+                              setSelectedChatModel('');
+                            } else {
+                              setSelectedChatModel(
+                                config.chatModelProviders[e.target.value][0],
+                              );
+                            }
                           }}
                           options={Object.keys(config.chatModelProviders).map(
                             (provider) => ({
@@ -439,6 +444,22 @@ const SettingsDialog = ({
                         }
                       />
                     </div>
+                    <div className="flex flex-col space-y-1">
+                      <p className="text-black/70 dark:text-white/70 text-sm">
+                        Anthropic API Key
+                      </p>
+                      <Input
+                        type="text"
+                        placeholder="Anthropic API key"
+                        defaultValue={config.anthropicApiKey}
+                        onChange={(e) =>
+                          setConfig({
+                            ...config,
+                            anthropicApiKey: e.target.value,
+                          })
+                        }
+                      />
+                    </div>
                   </div>
                 )}
                 {isLoading && (

ui/package.json

@@ -1,6 +1,6 @@
 {
   "name": "perplexica-frontend",
-  "version": "1.7.1",
+  "version": "1.9.0-rc1",
   "license": "MIT",
   "author": "ItzCrazyKns",
   "scripts": {

yarn.lock

@@ -2,6 +2,20 @@
 # yarn lockfile v1
 
 
+"@anthropic-ai/sdk@^0.22.0":
+  version "0.22.0"
+  resolved "https://registry.yarnpkg.com/@anthropic-ai/sdk/-/sdk-0.22.0.tgz#548e4218d9810fd494e595d4e57cb2d46d301a1a"
+  integrity sha512-dv4BCC6FZJw3w66WNLsHlUFjhu19fS1L/5jMPApwhZLa/Oy1j0A2i3RypmDtHEPp4Wwg3aZkSHksp7VzYWjzmw==
+  dependencies:
+    "@types/node" "^18.11.18"
+    "@types/node-fetch" "^2.6.4"
+    abort-controller "^3.0.0"
+    agentkeepalive "^4.2.1"
+    form-data-encoder "1.7.2"
+    formdata-node "^4.3.2"
+    node-fetch "^2.6.7"
+    web-streams-polyfill "^3.2.1"
+
 "@anthropic-ai/sdk@^0.9.1":
   version "0.9.1"
   resolved "https://registry.yarnpkg.com/@anthropic-ai/sdk/-/sdk-0.9.1.tgz#b2d2b7bf05c90dce502c9a2e869066870f69ba88"
@@ -307,6 +321,17 @@
     "@jridgewell/resolve-uri" "^3.0.3"
     "@jridgewell/sourcemap-codec" "^1.4.10"
 
+"@langchain/anthropic@^0.2.3":
+  version "0.2.3"
+  resolved "https://registry.yarnpkg.com/@langchain/anthropic/-/anthropic-0.2.3.tgz#1505da939f47c90e53dfede0407c497b8177bdf0"
+  integrity sha512-f2fqzLGcvsXXUyZ1vl8cgwkKDGLshOGrPuR9hkhGuBG5m91eq755OqPBxWJuS1TFtNU813cXft3xh0MQbxavwg==
+  dependencies:
+    "@anthropic-ai/sdk" "^0.22.0"
+    "@langchain/core" ">=0.2.9 <0.3.0"
+    fast-xml-parser "^4.3.5"
+    zod "^3.22.4"
+    zod-to-json-schema "^3.22.4"
+
 "@langchain/community@^0.2.16":
   version "0.2.16"
   resolved "https://registry.yarnpkg.com/@langchain/community/-/community-0.2.16.tgz#5888baf7fc7ea272c5f91aaa0e71bc444167262d"
@@ -355,6 +380,24 @@
     zod "^3.22.4"
     zod-to-json-schema "^3.22.3"
 
+"@langchain/core@>=0.2.9 <0.3.0":
+  version "0.2.15"
+  resolved "https://registry.yarnpkg.com/@langchain/core/-/core-0.2.15.tgz#1bb99ac4fffe935c7ba37edcaa91abfba3c82219"
+  integrity sha512-L096itIBQ5XNsy5BCCPqIQEk/x4rzI+U4BhYT+fDBYtljESshIi/WzXdmiGfY/6MpVjB76jNuaRgMDmo1m9NeQ==
+  dependencies:
+    ansi-styles "^5.0.0"
+    camelcase "6"
+    decamelize "1.2.0"
+    js-tiktoken "^1.0.12"
+    langsmith "~0.1.30"
+    ml-distance "^4.0.0"
+    mustache "^4.2.0"
+    p-queue "^6.6.2"
+    p-retry "4"
+    uuid "^10.0.0"
+    zod "^3.22.4"
+    zod-to-json-schema "^3.22.3"
+
 "@langchain/core@~0.1.44", "@langchain/core@~0.1.45":
   version "0.1.52"
   resolved "https://registry.yarnpkg.com/@langchain/core/-/core-0.1.52.tgz#7619310b83ffa841628efe2e1eda873ca714d068"
@@ -466,6 +509,14 @@
   resolved "https://registry.yarnpkg.com/@protobufjs/utf8/-/utf8-1.1.0.tgz#a777360b5b39a1a2e5106f8e858f2fd2d060c570"
   integrity sha512-Vvn3zZrhQZkkBE8LSuW3em98c0FwgO4nxzv6OdSxPKJIEKY2bGbHn+mhGIPerzI4twdxaP8/0+06HBpwf345Lw==
 
+"@selderee/plugin-htmlparser2@^0.11.0":
+  version "0.11.0"
+  resolved "https://registry.yarnpkg.com/@selderee/plugin-htmlparser2/-/plugin-htmlparser2-0.11.0.tgz#d5b5e29a7ba6d3958a1972c7be16f4b2c188c517"
+  integrity sha512-P33hHGdldxGabLFjPPpaTxVolMrzrcegejx+0GxjrIb9Zv48D8yAIA/QTDR2dFl7Uz7urX8aX6+5bCZslr+gWQ==
+  dependencies:
+    domhandler "^5.0.3"
+    selderee "^0.11.0"
+
 "@tsconfig/node10@^1.0.7":
   version "1.0.11"
   resolved "https://registry.yarnpkg.com/@tsconfig/node10/-/node10-1.0.11.tgz#6ee46400685f130e278128c7b38b7e031ff5b2f2"
@@ -535,6 +586,11 @@
     "@types/qs" "*"
     "@types/serve-static" "*"
 
+"@types/html-to-text@^9.0.4":
+  version "9.0.4"
+  resolved "https://registry.yarnpkg.com/@types/html-to-text/-/html-to-text-9.0.4.tgz#4a83dd8ae8bfa91457d0b1ffc26f4d0537eff58c"
+  integrity sha512-pUY3cKH/Nm2yYrEmDlPR1mR7yszjGx4DrwPjQ702C4/D5CwHuZTgZdIdwPkRbcuhs7BAh2L5rg3CL5cbRiGTCQ==
+
 "@types/http-errors@*":
   version "2.0.4"
   resolved "https://registry.yarnpkg.com/@types/http-errors/-/http-errors-2.0.4.tgz#7eb47726c391b7345a6ec35ad7f4de469cf5ba4f"
@@ -579,6 +635,11 @@
   dependencies:
     undici-types "~5.26.4"
 
+"@types/pdf-parse@^1.1.4":
+  version "1.1.4"
+  resolved "https://registry.yarnpkg.com/@types/pdf-parse/-/pdf-parse-1.1.4.tgz#21a539efd2f16009d08aeed3350133948b5d7ed1"
+  integrity sha512-+gbBHbNCVGGYw1S9lAIIvrHW47UYOhMIFUsJcMkMrzy1Jf0vulBN3XQIjPgnoOXveMuHnF3b57fXROnY/Or7eg==
+
 "@types/qs@*":
   version "6.9.14"
   resolved "https://registry.yarnpkg.com/@types/qs/-/qs-6.9.14.tgz#169e142bfe493895287bee382af6039795e9b75b"
@@ -1049,6 +1110,13 @@ debug@2.6.9:
   dependencies:
     ms "2.0.0"
 
+debug@^3.1.0:
+  version "3.2.7"
+  resolved "https://registry.yarnpkg.com/debug/-/debug-3.2.7.tgz#72580b7e9145fb39b6676f9c5e5fb100b934179a"
+  integrity sha512-CFjzYYAi4ThfiQvizrFQevTTXHtnCqWfe7x1AhgEscTz6ZbLbfoLRLPugTQyBth6f8ZERVUSyWHFD/7Wu4t1XQ==
+  dependencies:
+    ms "^2.1.1"
+
 debug@^4:
   version "4.3.4"
   resolved "https://registry.yarnpkg.com/debug/-/debug-4.3.4.tgz#1319f6579357f2338d3337d2cdd4914bb5dcc865"
@@ -1080,6 +1148,11 @@ deep-extend@^0.6.0:
   resolved "https://registry.yarnpkg.com/deep-extend/-/deep-extend-0.6.0.tgz#c4fa7c95404a17a9c3e8ca7e1537312b736330ac"
   integrity sha512-LOHxIOaPYdHlJRtCQfDIVZtfw/ufM8+rVj649RIHzcm/vGwQRXFt6OPqIFWsm2XEMrNIEtWR64sY1LEKD2vAOA==
 
+deepmerge@^4.3.1:
+  version "4.3.1"
+  resolved "https://registry.yarnpkg.com/deepmerge/-/deepmerge-4.3.1.tgz#44b5f2147cd3b00d4b56137685966f26fd25dd4a"
+  integrity sha512-3sUqbMEc77XqpdNO7FRyRog+eW3ph+GYCbj+rK+uYyRMuwsVy0rMiVtPn+QJlKFvWP/1PYpapqYn0Me2knFn+A==
+
 define-data-property@^1.1.4:
   version "1.1.4"
   resolved "https://registry.yarnpkg.com/define-data-property/-/define-data-property-1.1.4.tgz#894dc141bb7d3060ae4366f6a0107e68fbe48c5e"
@@ -1122,6 +1195,36 @@ digest-fetch@^1.3.0:
     base-64 "^0.1.0"
     md5 "^2.3.0"
 
+dom-serializer@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/dom-serializer/-/dom-serializer-2.0.0.tgz#e41b802e1eedf9f6cae183ce5e622d789d7d8e53"
+  integrity sha512-wIkAryiqt/nV5EQKqQpo3SToSOV9J0DnbJqwK7Wv/Trc92zIAYZ4FlMu+JPFW1DfGFt81ZTCGgDEabffXeLyJg==
+  dependencies:
+    domelementtype "^2.3.0"
+    domhandler "^5.0.2"
+    entities "^4.2.0"
+
+domelementtype@^2.3.0:
+  version "2.3.0"
+  resolved "https://registry.yarnpkg.com/domelementtype/-/domelementtype-2.3.0.tgz#5c45e8e869952626331d7aab326d01daf65d589d"
+  integrity sha512-OLETBj6w0OsagBwdXnPdN0cnMfF9opN69co+7ZrbfPGrdpPVNBUj02spi6B1N7wChLQiPn4CSH/zJvXw56gmHw==
+
+domhandler@^5.0.2, domhandler@^5.0.3:
+  version "5.0.3"
+  resolved "https://registry.yarnpkg.com/domhandler/-/domhandler-5.0.3.tgz#cc385f7f751f1d1fc650c21374804254538c7d31"
+  integrity sha512-cgwlv/1iFQiFnU96XXgROh8xTeetsnJiDsTc7TYCLFd9+/WNkIqPTxiM/8pSd8VIrhXGTf1Ny1q1hquVqDJB5w==
+  dependencies:
+    domelementtype "^2.3.0"
+
+domutils@^3.0.1:
+  version "3.1.0"
+  resolved "https://registry.yarnpkg.com/domutils/-/domutils-3.1.0.tgz#c47f551278d3dc4b0b1ab8cbb42d751a6f0d824e"
+  integrity sha512-H78uMmQtI2AhgDJjWeQmHwJJ2bLPD3GMmO7Zja/ZZh84wkm+4ut+IUnUdRa8uCGX88DiVx1j6FRe1XfxEgjEZA==
+  dependencies:
+    dom-serializer "^2.0.0"
+    domelementtype "^2.3.0"
+    domhandler "^5.0.3"
+
 dotenv@^16.4.5:
   version "16.4.5"
   resolved "https://registry.yarnpkg.com/dotenv/-/dotenv-16.4.5.tgz#cdd3b3b604cb327e286b4762e13502f717cb099f"
@@ -1163,6 +1266,11 @@ end-of-stream@^1.1.0, end-of-stream@^1.4.1:
   dependencies:
     once "^1.4.0"
 
+entities@^4.2.0, entities@^4.4.0:
+  version "4.5.0"
+  resolved "https://registry.yarnpkg.com/entities/-/entities-4.5.0.tgz#5d268ea5e7113ec74c4d033b79ea5a35a488fb48"
+  integrity sha512-V0hjH4dGPh9Ao5p0MoRY6BVqtwCjhz6vI5LT8AJ55H+4g9/4vbHx1I54fS0XuclLhDHArPQCiMjDxjaL8fPxhw==
+
 es-define-property@^1.0.0:
   version "1.0.0"
   resolved "https://registry.yarnpkg.com/es-define-property/-/es-define-property-1.0.0.tgz#c7faefbdff8b2696cf5f46921edfb77cc4ba3845"
@@ -1311,6 +1419,13 @@ fast-fifo@^1.1.0, fast-fifo@^1.2.0:
   resolved "https://registry.yarnpkg.com/fast-fifo/-/fast-fifo-1.3.2.tgz#286e31de96eb96d38a97899815740ba2a4f3640c"
   integrity sha512-/d9sfos4yxzpwkDkuN7k2SqFKtYNmCTzgfEpz82x34IM9/zc8KGxQoXg1liNC/izpRM/MBdt44Nmx41ZWqk+FQ==
 
+fast-xml-parser@^4.3.5:
+  version "4.4.0"
+  resolved "https://registry.yarnpkg.com/fast-xml-parser/-/fast-xml-parser-4.4.0.tgz#341cc98de71e9ba9e651a67f41f1752d1441a501"
+  integrity sha512-kLY3jFlwIYwBNDojclKsNAC12sfD6NwW74QB2CoNGPvtVxjliYehVunB3HYyNi+n4Tt1dAcgwYvmKF/Z18flqg==
+  dependencies:
+    strnum "^1.0.5"
+
 fecha@^4.2.0:
   version "4.2.3"
   resolved "https://registry.yarnpkg.com/fecha/-/fecha-4.2.3.tgz#4d9ccdbc61e8629b259fdca67e65891448d569fd"
@@ -1479,6 +1594,27 @@ hasown@^2.0.0:
   dependencies:
     function-bind "^1.1.2"
 
+html-to-text@^9.0.5:
+  version "9.0.5"
+  resolved "https://registry.yarnpkg.com/html-to-text/-/html-to-text-9.0.5.tgz#6149a0f618ae7a0db8085dca9bbf96d32bb8368d"
+  integrity sha512-qY60FjREgVZL03vJU6IfMV4GDjGBIoOyvuFdpBDIX9yTlDw0TjxVBQp+P8NvpdIXNJvfWBTNul7fsAQJq2FNpg==
+  dependencies:
+    "@selderee/plugin-htmlparser2" "^0.11.0"
+    deepmerge "^4.3.1"
+    dom-serializer "^2.0.0"
+    htmlparser2 "^8.0.2"
+    selderee "^0.11.0"
+
+htmlparser2@^8.0.2:
+  version "8.0.2"
+  resolved "https://registry.yarnpkg.com/htmlparser2/-/htmlparser2-8.0.2.tgz#f002151705b383e62433b5cf466f5b716edaec21"
+  integrity sha512-GYdjWKDkbRLkZ5geuHs5NY1puJ+PXwP7+fHPRz06Eirsb9ugf6d8kkXav6ADhcODhFFPMIXyxkxSuMf3D6NCFA==
+  dependencies:
+    domelementtype "^2.3.0"
+    domhandler "^5.0.3"
+    domutils "^3.0.1"
+    entities "^4.4.0"
+
 http-errors@2.0.0:
   version "2.0.0"
   resolved "https://registry.yarnpkg.com/http-errors/-/http-errors-2.0.0.tgz#b7774a1486ef73cf7667ac9ae0858c012c57b9d3"
@@ -1677,6 +1813,11 @@ langsmith@~0.1.30:
     p-retry "4"
     uuid "^9.0.0"
 
+leac@^0.6.0:
+  version "0.6.0"
+  resolved "https://registry.yarnpkg.com/leac/-/leac-0.6.0.tgz#dcf136e382e666bd2475f44a1096061b70dc0912"
+  integrity sha512-y+SqErxb8h7nE/fiEX07jsbuhrpO9lL8eca7/Y1nuWV2moNlXhyd59iDGcRf6moVyDMbmTNzL40SUyrFU/yDpg==
+
 lodash.set@^4.3.2:
   version "4.3.2"
   resolved "https://registry.yarnpkg.com/lodash.set/-/lodash.set-4.3.2.tgz#d8757b1da807dde24816b0d6a84bea1a76230b23"
@@ -1857,6 +1998,11 @@ node-domexception@1.0.0:
   resolved "https://registry.yarnpkg.com/node-domexception/-/node-domexception-1.0.0.tgz#6888db46a1f71c0b76b3f7555016b63fe64766e5"
   integrity sha512-/jKZoMpw0F8GRwl4/eLROPA3cfcXtLApP0QzLmUT/HuPCZWyB7IY9ZrMeKw2O/nFIqPQB3PVM9aYm0F312AXDQ==
 
+node-ensure@^0.0.0:
+  version "0.0.0"
+  resolved "https://registry.yarnpkg.com/node-ensure/-/node-ensure-0.0.0.tgz#ecae764150de99861ec5c810fd5d096b183932a7"
+  integrity sha512-DRI60hzo2oKN1ma0ckc6nQWlHU69RH6xN0sjQTjMpChPfTYvKZdcQFfdYK2RWbJcKyUizSIy/l8OTGxMAM1QDw==
+
 node-fetch@^2.6.7:
   version "2.7.0"
   resolved "https://registry.yarnpkg.com/node-fetch/-/node-fetch-2.7.0.tgz#d0f0fa6e3e2dc1d27efcd8ad99d550bda94d187d"
@@ -2021,6 +2167,14 @@ p-timeout@^3.2.0:
   dependencies:
     p-finally "^1.0.0"
 
+parseley@^0.12.0:
+  version "0.12.1"
+  resolved "https://registry.yarnpkg.com/parseley/-/parseley-0.12.1.tgz#4afd561d50215ebe259e3e7a853e62f600683aef"
+  integrity sha512-e6qHKe3a9HWr0oMRVDTRhKce+bRO8VGQR3NyVwcjwrbhMmFCX9KszEV35+rn4AdilFAq9VPxP/Fe1wC9Qjd2lw==
+  dependencies:
+    leac "^0.6.0"
+    peberminta "^0.9.0"
+
 parseurl@~1.3.3:
   version "1.3.3"
   resolved "https://registry.yarnpkg.com/parseurl/-/parseurl-1.3.3.tgz#9da19e7bee8d12dff0513ed5b76957793bc2e8d4"
@@ -2031,6 +2185,19 @@ path-to-regexp@0.1.7:
   resolved "https://registry.yarnpkg.com/path-to-regexp/-/path-to-regexp-0.1.7.tgz#df604178005f522f15eb4490e7247a1bfaa67f8c"
   integrity sha512-5DFkuoqlv1uYQKxy8omFBeJPQcdoE07Kv2sferDCrAq1ohOU+MSDswDIbnx3YAM60qIOnYa53wBhXW0EbMonrQ==
 
+pdf-parse@^1.1.1:
+  version "1.1.1"
+  resolved "https://registry.yarnpkg.com/pdf-parse/-/pdf-parse-1.1.1.tgz#745e07408679548b3995ff896fd38e96e19d14a7"
+  integrity sha512-v6ZJ/efsBpGrGGknjtq9J/oC8tZWq0KWL5vQrk2GlzLEQPUDB1ex+13Rmidl1neNN358Jn9EHZw5y07FFtaC7A==
+  dependencies:
+    debug "^3.1.0"
+    node-ensure "^0.0.0"
+
+peberminta@^0.9.0:
+  version "0.9.0"
+  resolved "https://registry.yarnpkg.com/peberminta/-/peberminta-0.9.0.tgz#8ec9bc0eb84b7d368126e71ce9033501dca2a352"
+  integrity sha512-XIxfHpEuSJbITd1H3EeQwpcZbTLHc+VVr8ANI9t5sit565tsI4/xK3KWTUFE2e6QiangUkh3B0jihzmGnNrRsQ==
+
 picomatch@^2.0.4, picomatch@^2.2.1:
   version "2.3.1"
   resolved "https://registry.yarnpkg.com/picomatch/-/picomatch-2.3.1.tgz#3ba3833733646d9d3e4995946c1365a67fb07a42"
@@ -2192,6 +2359,13 @@ safe-stable-stringify@^2.3.1:
   resolved "https://registry.yarnpkg.com/safer-buffer/-/safer-buffer-2.1.2.tgz#44fa161b0187b9549dd84bb91802f9bd8385cd6a"
   integrity sha512-YZo3K82SD7Riyi0E1EQPojLz7kpepnSQI9IyPbHHg1XXXevb5dJI7tpyN2ADxGcQbHG7vcyRHk0cbwqcQriUtg==
 
+selderee@^0.11.0:
+  version "0.11.0"
+  resolved "https://registry.yarnpkg.com/selderee/-/selderee-0.11.0.tgz#6af0c7983e073ad3e35787ffe20cefd9daf0ec8a"
+  integrity sha512-5TF+l7p4+OsnP8BCCvSyZiSPc4x4//p5uPwK8TCnVPJYRmU2aYKMpOXvw8zM5a5JvuuCGN1jmsMwuU2W02ukfA==
+  dependencies:
+    parseley "^0.12.0"
+
 semver@^7.3.5, semver@^7.5.3, semver@^7.5.4:
   version "7.6.0"
   resolved "https://registry.yarnpkg.com/semver/-/semver-7.6.0.tgz#1a46a4db4bffcccd97b743b5005c8325f23d4e2d"
@@ -2342,6 +2516,11 @@ strip-json-comments@~2.0.1:
   resolved "https://registry.yarnpkg.com/strip-json-comments/-/strip-json-comments-2.0.1.tgz#3c531942e908c2697c0ec344858c286c7ca0a60a"
   integrity sha512-4gB8na07fecVVkOI6Rs4e7T6NOTki5EmL7TUduTs6bu3EdnSycntVJ4re8kgZA+wx9IueI2Y11bfbgwtzuE0KQ==
 
+strnum@^1.0.5:
+  version "1.0.5"
+  resolved "https://registry.yarnpkg.com/strnum/-/strnum-1.0.5.tgz#5c4e829fe15ad4ff0d20c3db5ac97b73c9b072db"
+  integrity sha512-J8bbNyKKXl5qYcR36TIO8W3mVGVHrmmxsd5PAItGkmyzwJvybiw2IVq5nqd0i4LSNSkB/sx9VHllbfFdr9k1JA==
+
 supports-color@^5.5.0:
   version "5.5.0"
   resolved "https://registry.yarnpkg.com/supports-color/-/supports-color-5.5.0.tgz#e2e69a44ac8772f78a1ec0b35b689df6530efc8f"
@@ -2488,6 +2667,11 @@ utils-merge@1.0.1:
   resolved "https://registry.yarnpkg.com/utils-merge/-/utils-merge-1.0.1.tgz#9f95710f50a267947b2ccc124741c1028427e713"
   integrity sha512-pMZTvIkT1d+TFGvDOqodOclx0QWkkgi6Tdoa8gC8ffGAAqz9pzPTZWAybbsHHoED/ztMtkv/VoYTYyShUn81hA==
 
+uuid@^10.0.0:
+  version "10.0.0"
+  resolved "https://registry.yarnpkg.com/uuid/-/uuid-10.0.0.tgz#5a95aa454e6e002725c79055fd42aaba30ca6294"
+  integrity sha512-8XkAphELsDnEGrDxUOHB3RGvXz6TeuYSGEZBOjtTtPm2lwhGBjLgOzLHB63IUWfBpNucQjND6d3AOudO+H3RWQ==
+
 uuid@^9.0.0:
   version "9.0.1"
   resolved "https://registry.yarnpkg.com/uuid/-/uuid-9.0.1.tgz#e188d4c8853cc722220392c424cd637f32293f30"
@@ -2592,7 +2776,7 @@ zod-to-json-schema@^3.22.3:
   resolved "https://registry.yarnpkg.com/zod-to-json-schema/-/zod-to-json-schema-3.22.5.tgz#3646e81cfc318dbad2a22519e5ce661615418673"
   integrity sha512-+akaPo6a0zpVCCseDed504KBJUQpEW5QZw7RMneNmKw+fGaML1Z9tUNLnHHAC8x6dzVRO1eB2oEMyZRnuBZg7Q==
 
-zod-to-json-schema@^3.22.5:
+zod-to-json-schema@^3.22.4, zod-to-json-schema@^3.22.5:
   version "3.23.1"
   resolved "https://registry.yarnpkg.com/zod-to-json-schema/-/zod-to-json-schema-3.23.1.tgz#5225925b8ed5fa20096bd99be076c4b29b53d309"
   integrity sha512-oT9INvydob1XV0v1d2IadrR74rLtDInLvDFfAa1CG0Pmg/vxATk7I2gSelfj271mbzeM4Da0uuDQE/Nkj3DWNw==