feat(readme): update readme

feat(package): bump version
feat(search): update types
2025-04-30 08:12:26 +00:00 · 2024-09-25 16:56:41 +05:30 · 2024-09-25 16:54:44 +05:30 · 2024-09-25 16:54:19 +05:30 · 2024-09-25 16:54:07 +05:30 · 2024-09-25 15:27:48 +05:30
47 changed files with 1801 additions and 2716 deletions
--- a/README.md
+++ b/README.md
@ -12,6 +12,7 @@
  - [Non-Docker Installation](#non-docker-installation)
  - [Ollama Connection Errors](#ollama-connection-errors)
 - [Using as a Search Engine](#using-as-a-search-engine)
+- [Using Perplexica's API](#using-perplexicas-api)
 - [One-Click Deployment](#one-click-deployment)
 - [Upcoming Features](#upcoming-features)
 - [Support Us](#support-us)
@ -45,6 +46,7 @@ Want to know more about its architecture and how it works? You can read it [here
  - **Wolfram Alpha Search Mode:** Answers queries that need calculations or data analysis using Wolfram Alpha.
  - **Reddit Search Mode:** Searches Reddit for discussions and opinions related to the query.
 - **Current Information:** Some search tools might give you outdated info because they use data from crawling bots and convert them into embeddings and store them in a index. Unlike them, Perplexica uses SearxNG, a metasearch engine to get the results and rerank and get the most relevant source out of it, ensuring you always get the latest information without the overhead of daily data updates.
+- **API**: Integrate Perplexica into your existing applications and make use of its capibilities.

 It has many more features like image and video search. Some of the planned features are mentioned in [upcoming features](#upcoming-features).

@ -67,7 +69,8 @@ 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.

@ -85,11 +88,12 @@ There are mainly 2 ways of installing Perplexica - With Docker, Without Docker.

 ### Non-Docker Installation

-1. Clone the repository and rename the `sample.config.toml` file to `config.toml` in the root directory. Ensure you complete all required fields in this file.
-2. Rename the `.env.example` file to `.env` in the `ui` folder and fill in all necessary fields.
-3. After populating the configuration and environment files, run `npm i` in both the `ui` folder and the root directory.
-4. Install the dependencies and then execute `npm run build` in both the `ui` folder and the root directory.
-5. Finally, start both the frontend and the backend by running `npm run start` in both the `ui` folder and the root directory.
+1. Install SearXNG and allow `JSON` format in the SearXNG settings.
+2. Clone the repository and rename the `sample.config.toml` file to `config.toml` in the root directory. Ensure you complete all required fields in this file.
+3. Rename the `.env.example` file to `.env` in the `ui` folder and fill in all necessary fields.
+4. After populating the configuration and environment files, run `npm i` in both the `ui` folder and the root directory.
+5. Install the dependencies and then execute `npm run build` in both the `ui` folder and the root directory.
+6. Finally, start both the frontend and the backend by running `npm run start` in both the `ui` folder and the root directory.

 **Note**: Using Docker is recommended as it simplifies the setup process, especially for managing environment variables and dependencies.

@ -110,11 +114,7 @@ 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.

@ -127,6 +127,12 @@ If you wish to use Perplexica as an alternative to traditional search engines li
 3. Add a new site search with the following URL: `http://localhost:3000/?q=%s`. Replace `localhost` with your IP address or domain name, and `3000` with the port number if Perplexica is not hosted locally.
 4. Click the add button. Now, you can use Perplexica directly from your browser's search bar.

+## Using Perplexica's API
+
+Perplexica also provides an API for developers looking to integrate its powerful search engine into their own applications. You can run searches, use multiple models and get answers to your queries.
+
+For more details, check out the full documentation [here](https://github.com/ItzCrazyKns/Perplexica/tree/master/docs/API/SEARCH.md).
+
 ## One-Click Deployment

 [![Deploy to RepoCloud](https://d16t0pc4846x52.cloudfront.net/deploylobe.svg)](https://repocloud.io/details/?app_id=267)
@ -137,6 +143,7 @@ If you wish to use Perplexica as an alternative to traditional search engines li
 - [x] Adding support for local LLMs
 - [x] History Saving features
 - [x] Introducing various Focus Modes
+- [x] Adding API support
 - [ ] Finalizing Copilot Mode
 - [ ] Adding Discover

@ -146,11 +153,11 @@ If you find Perplexica useful, consider giving us a star on GitHub. This helps m

 ### Donations

-We also accept donations to help sustain our project. If you would like to contribute, you can use the following button to make a donation in cryptocurrency. Thank you for your support!
+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!

-<a href="https://nowpayments.io/donation?api_key=RFFKJH1-GRR4DQG-HFV1DZP-00G6MMK&source=lk_donation&medium=referral" target="_blank">
-  <img src="https://nowpayments.io/images/embeds/donation-button-white.svg" alt="Crypto donation button by NOWPayments">
-</a>
+| Ethereum                                              |
+| ----------------------------------------------------- |
+| Address: `0xB025a84b2F269570Eb8D4b05DEdaA41D8525B6DD` |

 ## Contribution

--- a/backend.dockerfile
+++ b/backend.dockerfile
@ -1,6 +1,7 @@
-FROM nikolaik/python-nodejs:python3.12-nodejs20-bullseye
+FROM node:slim

 ARG SEARXNG_API_URL
+ENV SEARXNG_API_URL=${SEARXNG_API_URL}

 WORKDIR /home/perplexica

@ -11,11 +12,9 @@ COPY drizzle.config.ts /home/perplexica/
 COPY package.json /home/perplexica/
 COPY yarn.lock /home/perplexica/

-RUN sed -i "s|SEARXNG = \".*\"|SEARXNG = \"${SEARXNG_API_URL}\"|g" /home/perplexica/config.toml
-
 RUN mkdir /home/perplexica/data

-RUN yarn install
+RUN yarn install 
 RUN yarn build

 CMD ["yarn", "start"]
--- a/docker-compose.yaml
+++ b/docker-compose.yaml
@ -21,6 +21,7 @@ services:
      - 3001:3001
    volumes:
      - backend-dbstore:/home/perplexica/data
+      - ./config.toml:/home/perplexica/config.toml
    extra_hosts:
      - 'host.docker.internal:host-gateway'
    networks:
--- a/docs/API/SEARCH.md
+++ b/docs/API/SEARCH.md
@ -0,0 +1,105 @@
+# Perplexica Search API Documentation
+
+## Overview
+
+Perplexica’s Search API makes it easy to use our AI-powered search engine. You can run different types of searches, pick the models you want to use, and get the most recent info. Follow the following headings to learn more about Perplexica's search API.
+
+## Endpoint
+
+### **POST** `/api/search`
+
+### Request
+
+The API accepts a JSON object in the request body, where you define the focus mode, chat models, embedding models, and your query.
+
+#### Request Body Structure
+
+```json
+{
+  "chatModel": {
+    "provider": "openai",
+    "model": "gpt-4o-mini"
+  },
+  "embeddingModel": {
+    "provider": "openai",
+    "model": "text-embedding-3-large"
+  },
+  "focusMode": "webSearch",
+  "query": "What is Perplexica",
+  "history": []
+}
+```
+
+### Request Parameters
+
+- **`chatModel`** (object, optional): Defines the chat model to be used for the query.
+
+  - `provider`: Specifies the provider for the chat model (e.g., `openai`, `ollama`).
+  - `model`: The specific model from the chosen provider (e.g., `gpt-4o-mini`).
+  - Optional fields for custom OpenAI configuration:
+    - `customOpenAIBaseURL`: If you’re using a custom OpenAI instance, provide the base URL.
+    - `customOpenAIKey`: The API key for a custom OpenAI instance.
+
+- **`embeddingModel`** (object, optional): Defines the embedding model for similarity-based searching.
+
+  - `provider`: The provider for the embedding model (e.g., `openai`).
+  - `model`: The specific embedding model (e.g., `text-embedding-3-large`).
+
+- **`focusMode`** (string, required): Specifies which focus mode to use. Available modes:
+
+  - `webSearch`, `academicSearch`, `writingAssistant`, `wolframAlphaSearch`, `youtubeSearch`, `redditSearch`.
+
+- **`query`** (string, required): The search query or question.
+
+- **`history`** (array, optional): An array of message pairs representing the conversation history. Each pair consists of a role (either 'human' or 'assistant') and the message content. This allows the system to use the context of the conversation to refine results. Example:
+  ```json
+  [
+    ["human", "What is Perplexica?"],
+    ["assistant", "Perplexica is an AI-powered search engine..."]
+  ]
+  ```
+
+### Response
+
+The response from the API includes both the final message and the sources used to generate that message.
+
+#### Example Response
+
+```json
+{
+	"message": "Perplexica is an innovative, open-source AI-powered search engine designed to enhance the way users search for information online. Here are some key features and characteristics of Perplexica:\n\n- **AI-Powered Technology**: It utilizes advanced machine learning algorithms to not only retrieve information but also to understand the context and intent behind user queries, providing more relevant results [1][5].\n\n- **Open-Source**: Being open-source, Perplexica offers flexibility and transparency, allowing users to explore its functionalities without the constraints of proprietary software [3][10].",
+	"sources": [
+		{
+			"pageContent": "Perplexica is an innovative, open-source AI-powered search engine designed to enhance the way users search for information online.",
+			"metadata": {
+				"title": "What is Perplexica, and how does it function as an AI-powered search ...",
+				"url": "https://askai.glarity.app/search/What-is-Perplexica--and-how-does-it-function-as-an-AI-powered-search-engine"
+			}
+		},
+		{
+			"pageContent": "Perplexica is an open-source AI-powered search tool that dives deep into the internet to find precise answers.",
+			"metadata": {
+				"title": "Sahar Mor's Post",
+				"url": "https://www.linkedin.com/posts/sahar-mor_a-new-open-source-project-called-perplexica-activity-7204489745668694016-ncja"
+			}
+		}
+        ....
+	]
+}
+```
+
+### Fields in the Response
+
+- **`message`** (string): The search result, generated based on the query and focus mode.
+- **`sources`** (array): A list of sources that were used to generate the search result. Each source includes:
+  - `pageContent`: A snippet of the relevant content from the source.
+  - `metadata`: Metadata about the source, including:
+    - `title`: The title of the webpage.
+    - `url`: The URL of the webpage.
+
+### Error Handling
+
+If an error occurs during the search process, the API will return an appropriate error message with an HTTP status code.
+
+- **400**: If the request is malformed or missing required fields (e.g., no focus mode or query).
+- **500**: If an internal server error occurs during the search.
--- a/docs/installation/UPDATING.md
+++ b/docs/installation/UPDATING.md
@ -0,0 +1,34 @@
+# Update Perplexica to the latest version
+
+To update Perplexica to the latest version, follow these steps:
+
+## For Docker users
+
+1. Clone the latest version of Perplexica from GitHub:
+
+```bash
+   git clone https://github.com/ItzCrazyKns/Perplexica.git
+```
+
+2. Navigate to the Project Directory
+
+3. Update and Rebuild Docker Containers:
+
+```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
+
+1. Clone the latest version of Perplexica from GitHub:
+
+```bash
+   git clone https://github.com/ItzCrazyKns/Perplexica.git
+```
+
+2. Navigate to the Project Directory
+3. Execute `npm i` in both the `ui` folder and the root directory.
+4. Once packages are updated, execute `npm run build` in both the `ui` folder and the root directory.
+5. Finally, start both the frontend and the backend by running `npm run start` in both the `ui` folder and the root directory.
--- a/package.json
+++ b/package.json
@ -1,6 +1,6 @@
 {
  "name": "perplexica-backend",
-  "version": "1.7.0",
+  "version": "1.9.0-rc3",
  "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 +26,8 @@
  },
  "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",
    "axios": "^1.6.8",
@ -34,7 +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"
--- a/sample.config.toml
+++ b/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
--- a/searxng/settings.yml
+++ b/searxng/settings.yml
--- a/src/agents/academicSearchAgent.ts
+++ b/src/agents/academicSearchAgent.ts
@ -19,6 +19,7 @@ import formatChatHistoryAsString from '../utils/formatHistory';
 import eventEmitter from 'events';
 import computeSimilarity from '../utils/computeSimilarity';
 import logger from '../utils/logger';
+import { IterableReadableStream } from '@langchain/core/utils/stream';

 const basicAcademicSearchRetrieverPrompt = `
 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.
@ -44,7 +45,7 @@ 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 +53,7 @@ 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>
@ -66,7 +67,7 @@ const basicAcademicSearchResponsePrompt = `
 const strParser = new StringOutputParser();

 const handleStream = async (
-  stream: AsyncGenerator<StreamEvent, any, unknown>,
+  stream: IterableReadableStream<StreamEvent>,
  emitter: eventEmitter,
 ) => {
  for await (const event of stream) {
--- a/src/agents/redditSearchAgent.ts
+++ b/src/agents/redditSearchAgent.ts
@ -19,6 +19,7 @@ import formatChatHistoryAsString from '../utils/formatHistory';
 import eventEmitter from 'events';
 import computeSimilarity from '../utils/computeSimilarity';
 import logger from '../utils/logger';
+import { IterableReadableStream } from '@langchain/core/utils/stream';

 const basicRedditSearchRetrieverPrompt = `
 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.
@ -44,7 +45,7 @@ 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 +53,8 @@ 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}
@ -66,7 +67,7 @@ const basicRedditSearchResponsePrompt = `
 const strParser = new StringOutputParser();

 const handleStream = async (
-  stream: AsyncGenerator<StreamEvent, any, unknown>,
+  stream: IterableReadableStream<StreamEvent>,
  emitter: eventEmitter,
 ) => {
  for await (const event of stream) {
@ -177,9 +178,9 @@ 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;
--- a/src/agents/suggestionGeneratorAgent.ts
+++ b/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);
 };
--- a/src/agents/webSearchAgent.ts
+++ b/src/agents/webSearchAgent.ts
@ -19,54 +19,103 @@ 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';
+import { IterableReadableStream } from '@langchain/core/utils/stream';
+import { ChatOpenAI } from '@langchain/openai';

 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.
+You are an AI question rephraser. You will be given a conversation and a follow-up question,  you will have to rephrase the follow up question so it is a standalone question and can be used by another LLM to search the web for information to answer it.
+If it is a smple writing task or a greeting (unless the greeting contains a question after it) like Hi, Hello, How are you, etc. than a question then you need to return \`not_needed\` as the response (This is because the LLM won't need to search the web for finding information on this topic).
+If the user asks some question from some URL or wants you to summarize a PDF or a webpage (via URL) you need to return the links inside the \`links\` XML block and the question inside the \`question\` XML block. If the user wants to you to summarize the webpage or the PDF you need to return \`summarize\` inside the \`question\` XML block in place of a question and the link to summarize in the \`links\` XML block.
+You must always return the rephrased question inside the \`question\` XML block, if there are no links in the follow-up question then don't insert a \`links\` XML block in your response.

-Example:
-1. Follow up question: What is the capital of France?
-Rephrased: Capital of france
+There are several examples attached for your reference inside the below \`examples\` XML block

-2. Follow up question: What is the population of New York City?
-Rephrased: Population of New York City
+<examples>
+1. Follow up question: What is the capital of France
+Rephrased question:\`
+<question>
+Capital of france
+</question>
+\`
+
+2. Hi, how are you?
+Rephrased question\`
+<question>
+not_needed
+</question>
+\`

 3. Follow up question: What is Docker?
-Rephrased: What is Docker
+Rephrased question: \`
+<question>
+What is Docker
+</question>
+\`

-Conversation:
+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>
+\`
+</examples>
+
+Anything below is the part of the actual conversation and you need to use conversation and the follow-up question to rephrase the follow-up question as a standalone question based on the guidelines shared above.
+
+<conversation>
 {chat_history}
+</conversation>

 Follow up question: {query}
 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()}
 `;

 const strParser = new StringOutputParser();

 const handleStream = async (
-  stream: AsyncGenerator<StreamEvent, any, unknown>,
+  stream: IterableReadableStream<StreamEvent>,
  emitter: eventEmitter,
 ) => {
  for await (const event of stream) {
@ -103,32 +152,120 @@ type BasicChainInput = {
 };

 const createBasicWebSearchRetrieverChain = (llm: BaseChatModel) => {
+  (llm as unknown as ChatOpenAI).temperature = 0;
+
  return RunnableSequence.from([
    PromptTemplate.fromTemplate(basicSearchRetrieverPrompt),
    llm,
    strParser,
    RunnableLambda.from(async (input: string) => {
-      if (input === 'not_needed') {
+      const linksOutputParser = new LineListOutputParser({
+        key: 'links',
+      });
+
+      const questionOutputParser = new LineOutputParser({
+        key: 'question',
+      });
+
+      const links = await linksOutputParser.parse(input);
+      let question = await questionOutputParser.parse(input);
+
+      if (question === 'not_needed') {
        return { query: '', docs: [] };
      }

-      const res = await searchSearxng(input, {
-        language: 'en',
-      });
+      if (links.length > 0) {
+        if (question.length === 0) {
+          question = 'summarize';
+        }

-      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 }),
-            },
+        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: input, docs: documents };
+        return { query: question, docs: docs };
+      } else {
+        const res = await searchSearxng(question, {
+          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: question, docs: documents };
+      }
    }),
  ]);
 };
@ -156,6 +293,10 @@ const createBasicWebSearchAnsweringChain = (
      return docs;
    }

+    if (query.toLocaleLowerCase() === 'summarize') {
+      return docs;
+    }
+
    const docsWithContent = docs.filter(
      (doc) => doc.pageContent && doc.pageContent.length > 0,
    );
@ -175,8 +316,8 @@ const createBasicWebSearchAnsweringChain = (
    });

    const sortedDocs = similarity
+      .filter((sim) => sim.similarity > 0.3)
      .sort((a, b) => b.similarity - a.similarity)
-      .filter((sim) => sim.similarity > 0.5)
      .slice(0, 15)
      .map((sim) => docsWithContent[sim.index]);

--- a/src/agents/wolframAlphaSearchAgent.ts
+++ b/src/agents/wolframAlphaSearchAgent.ts
@ -18,6 +18,7 @@ import type { Embeddings } from '@langchain/core/embeddings';
 import formatChatHistoryAsString from '../utils/formatHistory';
 import eventEmitter from 'events';
 import logger from '../utils/logger';
+import { IterableReadableStream } from '@langchain/core/utils/stream';

 const basicWolframAlphaSearchRetrieverPrompt = `
 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.
@ -43,7 +44,7 @@ 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 +52,7 @@ 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>
@ -65,7 +66,7 @@ const basicWolframAlphaSearchResponsePrompt = `
 const strParser = new StringOutputParser();

 const handleStream = async (
-  stream: AsyncGenerator<StreamEvent, any, unknown>,
+  stream: IterableReadableStream<StreamEvent>,
  emitter: eventEmitter,
 ) => {
  for await (const event of stream) {
--- a/src/agents/writingAssistant.ts
+++ b/src/agents/writingAssistant.ts
@ -10,6 +10,7 @@ import eventEmitter from 'events';
 import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
 import type { Embeddings } from '@langchain/core/embeddings';
 import logger from '../utils/logger';
+import { IterableReadableStream } from '@langchain/core/utils/stream';

 const writingAssistantPrompt = `
 You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are currently set on focus mode 'Writing Assistant', this means you will be helping the user write a response to a given query. 
@ -19,7 +20,7 @@ Since you are a writing assistant, you would not perform web searches. If you th
 const strParser = new StringOutputParser();

 const handleStream = async (
-  stream: AsyncGenerator<StreamEvent, any, unknown>,
+  stream: IterableReadableStream<StreamEvent>,
  emitter: eventEmitter,
 ) => {
  for await (const event of stream) {
--- a/src/agents/youtubeSearchAgent.ts
+++ b/src/agents/youtubeSearchAgent.ts
@ -19,6 +19,7 @@ import formatChatHistoryAsString from '../utils/formatHistory';
 import eventEmitter from 'events';
 import computeSimilarity from '../utils/computeSimilarity';
 import logger from '../utils/logger';
+import { IterableReadableStream } from '@langchain/core/utils/stream';

 const basicYoutubeSearchRetrieverPrompt = `
 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.
@ -44,7 +45,7 @@ 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 +53,8 @@ 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}
@ -66,7 +67,7 @@ const basicYoutubeSearchResponsePrompt = `
 const strParser = new StringOutputParser();

 const handleStream = async (
-  stream: AsyncGenerator<StreamEvent, any, unknown>,
+  stream: IterableReadableStream<StreamEvent>,
  emitter: eventEmitter,
 ) => {
  for await (const event of stream) {
@ -177,9 +178,9 @@ 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;
--- a/src/app.ts
+++ b/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}`);
+});
--- a/src/config.ts
+++ b/src/config.ts
@ -12,6 +12,7 @@ interface Config {
  API_KEYS: {
    OPENAI: string;
    GROQ: string;
+    ANTHROPIC: string;
  };
  API_ENDPOINTS: {
    SEARXNG: string;
@ -37,7 +38,10 @@ export const getOpenaiApiKey = () => loadConfig().API_KEYS.OPENAI;

 export const getGroqApiKey = () => loadConfig().API_KEYS.GROQ;

-export const getSearxngApiEndpoint = () => loadConfig().API_ENDPOINTS.SEARXNG;
+export const getAnthropicApiKey = () => loadConfig().API_KEYS.ANTHROPIC;
+
+export const getSearxngApiEndpoint = () =>
+  process.env.SEARXNG_API_URL || loadConfig().API_ENDPOINTS.SEARXNG;

 export const getOllamaApiEndpoint = () => loadConfig().API_ENDPOINTS.OLLAMA;

--- a/src/lib/linkDocument.ts
+++ b/src/lib/linkDocument.ts
@ -0,0 +1,99 @@
+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';
+import logger from '../utils/logger';
+
+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}`;
+
+      try {
+        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);
+      } catch (err) {
+        logger.error(
+          `Error at generating documents from links: ${err.message}`,
+        );
+        docs.push(
+          new Document({
+            pageContent: `Failed to retrieve content from the link: ${err.message}`,
+            metadata: {
+              title: 'Failed to retrieve content',
+              url: link,
+            },
+          }),
+        );
+      }
+    }),
+  );
+
+  return docs;
+};
--- a/src/lib/outputParsers/lineOutputParser.ts
+++ b/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;
--- a/src/lib/outputParsers/listLineOutputParser.ts
+++ b/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;
--- a/src/lib/providers.ts
+++ b/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;
-};
--- a/src/lib/providers/anthropic.ts
+++ b/src/lib/providers/anthropic.ts
@ -0,0 +1,51 @@
+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-20240620': {
+        displayName: 'Claude 3.5 Sonnet',
+        model: new ChatAnthropic({
+          temperature: 0.7,
+          anthropicApiKey: anthropicApiKey,
+          model: 'claude-3-5-sonnet-20240620',
+        }),
+      },
+      'claude-3-opus-20240229': {
+        displayName: 'Claude 3 Opus',
+        model: new ChatAnthropic({
+          temperature: 0.7,
+          anthropicApiKey: anthropicApiKey,
+          model: 'claude-3-opus-20240229',
+        }),
+      },
+      'claude-3-sonnet-20240229': {
+        displayName: 'Claude 3 Sonnet',
+        model: new ChatAnthropic({
+          temperature: 0.7,
+          anthropicApiKey: anthropicApiKey,
+          model: 'claude-3-sonnet-20240229',
+        }),
+      },
+      'claude-3-haiku-20240307': {
+        displayName: 'Claude 3 Haiku',
+        model: new ChatAnthropic({
+          temperature: 0.7,
+          anthropicApiKey: anthropicApiKey,
+          model: 'claude-3-haiku-20240307',
+        }),
+      },
+    };
+
+    return chatModels;
+  } catch (err) {
+    logger.error(`Error loading Anthropic models: ${err}`);
+    return {};
+  }
+};
--- a/src/lib/providers/groq.ts
+++ b/src/lib/providers/groq.ts
@ -0,0 +1,110 @@
+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-versatile': {
+        displayName: 'Llama 3.1 70B',
+        model: new ChatOpenAI(
+          {
+            openAIApiKey: groqApiKey,
+            modelName: 'llama-3.1-70b-versatile',
+            temperature: 0.7,
+          },
+          {
+            baseURL: 'https://api.groq.com/openai/v1',
+          },
+        ),
+      },
+      'llama-3.1-8b-instant': {
+        displayName: 'Llama 3.1 8B',
+        model: new ChatOpenAI(
+          {
+            openAIApiKey: groqApiKey,
+            modelName: 'llama-3.1-8b-instant',
+            temperature: 0.7,
+          },
+          {
+            baseURL: 'https://api.groq.com/openai/v1',
+          },
+        ),
+      },
+      'llama3-8b-8192': {
+        displayName: 'LLaMA3 8B',
+        model: new ChatOpenAI(
+          {
+            openAIApiKey: groqApiKey,
+            modelName: 'llama3-8b-8192',
+            temperature: 0.7,
+          },
+          {
+            baseURL: 'https://api.groq.com/openai/v1',
+          },
+        ),
+      },
+      'llama3-70b-8192': {
+        displayName: 'LLaMA3 70B',
+        model: new ChatOpenAI(
+          {
+            openAIApiKey: groqApiKey,
+            modelName: 'llama3-70b-8192',
+            temperature: 0.7,
+          },
+          {
+            baseURL: 'https://api.groq.com/openai/v1',
+          },
+        ),
+      },
+      'mixtral-8x7b-32768': {
+        displayName: 'Mixtral 8x7B',
+        model: new ChatOpenAI(
+          {
+            openAIApiKey: groqApiKey,
+            modelName: 'mixtral-8x7b-32768',
+            temperature: 0.7,
+          },
+          {
+            baseURL: 'https://api.groq.com/openai/v1',
+          },
+        ),
+      },
+      'gemma-7b-it': {
+        displayName: 'Gemma 7B',
+        model: new ChatOpenAI(
+          {
+            openAIApiKey: groqApiKey,
+            modelName: 'gemma-7b-it',
+            temperature: 0.7,
+          },
+          {
+            baseURL: 'https://api.groq.com/openai/v1',
+          },
+        ),
+      },
+      'gemma2-9b-it': {
+        displayName: 'Gemma2 9B',
+        model: 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: ${err}`);
+    return {};
+  }
+};
--- a/src/lib/providers/index.ts
+++ b/src/lib/providers/index.ts
@ -0,0 +1,46 @@
+import { loadGroqChatModels } from './groq';
+import { loadOllamaChatModels, loadOllamaEmbeddingsModels } from './ollama';
+import { loadOpenAIChatModels, loadOpenAIEmbeddingsModels } from './openai';
+import { loadAnthropicChatModels } from './anthropic';
+import { loadTransformersEmbeddingsModels } from './transformers';
+
+const chatModelProviders = {
+  openai: loadOpenAIChatModels,
+  groq: loadGroqChatModels,
+  ollama: loadOllamaChatModels,
+  anthropic: loadAnthropicChatModels,
+};
+
+const embeddingModelProviders = {
+  openai: loadOpenAIEmbeddingsModels,
+  local: loadTransformersEmbeddingsModels,
+  ollama: loadOllamaEmbeddingsModels,
+};
+
+export const getAvailableChatModelProviders = async () => {
+  const models = {};
+
+  for (const provider in chatModelProviders) {
+    const providerModels = await chatModelProviders[provider]();
+    if (Object.keys(providerModels).length > 0) {
+      models[provider] = providerModels;
+    }
+  }
+
+  models['custom_openai'] = {};
+
+  return models;
+};
+
+export const getAvailableEmbeddingModelProviders = async () => {
+  const models = {};
+
+  for (const provider in embeddingModelProviders) {
+    const providerModels = await embeddingModelProviders[provider]();
+    if (Object.keys(providerModels).length > 0) {
+      models[provider] = providerModels;
+    }
+  }
+
+  return models;
+};
--- a/src/lib/providers/ollama.ts
+++ b/src/lib/providers/ollama.ts
@ -0,0 +1,71 @@
+import { OllamaEmbeddings } from '@langchain/community/embeddings/ollama';
+import { getOllamaApiEndpoint } from '../../config';
+import logger from '../../utils/logger';
+import { ChatOllama } from '@langchain/community/chat_models/ollama';
+
+export const loadOllamaChatModels = async () => {
+  const ollamaEndpoint = getOllamaApiEndpoint();
+
+  if (!ollamaEndpoint) return {};
+
+  try {
+    const response = await fetch(`${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] = {
+        displayName: model.name,
+        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] = {
+        displayName: model.name,
+        model: new OllamaEmbeddings({
+          baseUrl: ollamaEndpoint,
+          model: model.model,
+        }),
+      };
+
+      return acc;
+    }, {});
+
+    return embeddingsModels;
+  } catch (err) {
+    logger.error(`Error loading Ollama embeddings model: ${err}`);
+    return {};
+  }
+};
--- a/src/lib/providers/openai.ts
+++ b/src/lib/providers/openai.ts
@ -0,0 +1,89 @@
+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': {
+        displayName: 'GPT-3.5 Turbo',
+        model: new ChatOpenAI({
+          openAIApiKey,
+          modelName: 'gpt-3.5-turbo',
+          temperature: 0.7,
+        }),
+      },
+      'gpt-4': {
+        displayName: 'GPT-4',
+        model: new ChatOpenAI({
+          openAIApiKey,
+          modelName: 'gpt-4',
+          temperature: 0.7,
+        }),
+      },
+      'gpt-4-turbo': {
+        displayName: 'GPT-4 turbo',
+        model: new ChatOpenAI({
+          openAIApiKey,
+          modelName: 'gpt-4-turbo',
+          temperature: 0.7,
+        }),
+      },
+      'gpt-4o': {
+        displayName: 'GPT-4 omni',
+        model: new ChatOpenAI({
+          openAIApiKey,
+          modelName: 'gpt-4o',
+          temperature: 0.7,
+        }),
+      },
+      'gpt-4o-mini': {
+        displayName: 'GPT-4 omni mini',
+        model: 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': {
+        displayName: 'Text Embedding 3 Small',
+        model: new OpenAIEmbeddings({
+          openAIApiKey,
+          modelName: 'text-embedding-3-small',
+        }),
+      },
+      'text-embedding-3-large': {
+        displayName: 'Text Embedding 3 Large',
+        model: new OpenAIEmbeddings({
+          openAIApiKey,
+          modelName: 'text-embedding-3-large',
+        }),
+      },
+    };
+
+    return embeddingModels;
+  } catch (err) {
+    logger.error(`Error loading OpenAI embeddings model: ${err}`);
+    return {};
+  }
+};
--- a/src/lib/providers/transformers.ts
+++ b/src/lib/providers/transformers.ts
@ -0,0 +1,32 @@
+import logger from '../../utils/logger';
+import { HuggingFaceTransformersEmbeddings } from '../huggingfaceTransformer';
+
+export const loadTransformersEmbeddingsModels = async () => {
+  try {
+    const embeddingModels = {
+      'xenova-bge-small-en-v1.5': {
+        displayName: 'BGE Small',
+        model: new HuggingFaceTransformersEmbeddings({
+          modelName: 'Xenova/bge-small-en-v1.5',
+        }),
+      },
+      'xenova-gte-small': {
+        displayName: 'GTE Small',
+        model: new HuggingFaceTransformersEmbeddings({
+          modelName: 'Xenova/gte-small',
+        }),
+      },
+      'xenova-bert-base-multilingual-uncased': {
+        displayName: 'Bert Multilingual',
+        model: new HuggingFaceTransformersEmbeddings({
+          modelName: 'Xenova/bert-base-multilingual-uncased',
+        }),
+      },
+    };
+
+    return embeddingModels;
+  } catch (err) {
+    logger.error(`Error loading Transformers embeddings model: ${err}`);
+    return {};
+  }
+};
--- a/src/routes/chats.ts
+++ b/src/routes/chats.ts
@ -40,4 +40,27 @@ router.get('/:id', async (req, res) => {
  }
 });

+router.delete(`/:id`, async (req, res) => {
+  try {
+    const chatExists = await db.query.chats.findFirst({
+      where: eq(chats.id, req.params.id),
+    });
+
+    if (!chatExists) {
+      return res.status(404).json({ message: 'Chat not found' });
+    }
+
+    await db.delete(chats).where(eq(chats.id, req.params.id)).execute();
+    await db
+      .delete(messages)
+      .where(eq(messages.chatId, req.params.id))
+      .execute();
+
+    return res.status(200).json({ message: 'Chat deleted successfully' });
+  } catch (err) {
+    res.status(500).json({ message: 'An error has occurred.' });
+    logger.error(`Error in deleting chat: ${err.message}`);
+  }
+});
+
 export default router;
--- a/src/routes/config.ts
+++ b/src/routes/config.ts
@ -6,40 +6,58 @@ import {
 import {
  getGroqApiKey,
  getOllamaApiEndpoint,
+  getAnthropicApiKey,
  getOpenaiApiKey,
  updateConfig,
 } from '../config';
+import logger from '../utils/logger';

 const router = express.Router();

 router.get('/', async (_, res) => {
-  const config = {};
+  try {
+    const config = {};

-  const [chatModelProviders, embeddingModelProviders] = await Promise.all([
-    getAvailableChatModelProviders(),
-    getAvailableEmbeddingModelProviders(),
-  ]);
+    const [chatModelProviders, embeddingModelProviders] = await Promise.all([
+      getAvailableChatModelProviders(),
+      getAvailableEmbeddingModelProviders(),
+    ]);

-  config['chatModelProviders'] = {};
-  config['embeddingModelProviders'] = {};
+    config['chatModelProviders'] = {};
+    config['embeddingModelProviders'] = {};

-  for (const provider in chatModelProviders) {
-    config['chatModelProviders'][provider] = Object.keys(
-      chatModelProviders[provider],
-    );
+    for (const provider in chatModelProviders) {
+      config['chatModelProviders'][provider] = Object.keys(
+        chatModelProviders[provider],
+      ).map((model) => {
+        return {
+          name: model,
+          displayName: chatModelProviders[provider][model].displayName,
+        };
+      });
+    }
+
+    for (const provider in embeddingModelProviders) {
+      config['embeddingModelProviders'][provider] = Object.keys(
+        embeddingModelProviders[provider],
+      ).map((model) => {
+        return {
+          name: model,
+          displayName: embeddingModelProviders[provider][model].displayName,
+        };
+      });
+    }
+
+    config['openaiApiKey'] = getOpenaiApiKey();
+    config['ollamaApiUrl'] = getOllamaApiEndpoint();
+    config['anthropicApiKey'] = getAnthropicApiKey();
+    config['groqApiKey'] = getGroqApiKey();
+
+    res.status(200).json(config);
+  } catch (err: any) {
+    res.status(500).json({ message: 'An error has occurred.' });
+    logger.error(`Error getting config: ${err.message}`);
  }
-
-  for (const provider in embeddingModelProviders) {
-    config['embeddingModelProviders'][provider] = Object.keys(
-      embeddingModelProviders[provider],
-    );
-  }
-
-  config['openaiApiKey'] = getOpenaiApiKey();
-  config['ollamaApiUrl'] = getOllamaApiEndpoint();
-  config['groqApiKey'] = getGroqApiKey();
-
-  res.status(200).json(config);
 });

 router.post('/', async (req, res) => {
@ -49,6 +67,7 @@ router.post('/', async (req, res) => {
    API_KEYS: {
      OPENAI: config.openaiApiKey,
      GROQ: config.groqApiKey,
+      ANTHROPIC: config.anthropicApiKey,
    },
    API_ENDPOINTS: {
      OLLAMA: config.ollamaApiUrl,
--- a/src/routes/images.ts
+++ b/src/routes/images.ts
@ -26,7 +26,7 @@ router.post('/', async (req, res) => {
    let llm: BaseChatModel | undefined;

    if (chatModels[provider] && chatModels[provider][chatModel]) {
-      llm = chatModels[provider][chatModel] as BaseChatModel | undefined;
+      llm = chatModels[provider][chatModel].model as BaseChatModel | undefined;
    }

    if (!llm) {
--- a/src/routes/index.ts
+++ b/src/routes/index.ts
@ -5,6 +5,7 @@ import configRouter from './config';
 import modelsRouter from './models';
 import suggestionsRouter from './suggestions';
 import chatsRouter from './chats';
+import searchRouter from './search';

 const router = express.Router();

@ -14,5 +15,6 @@ router.use('/config', configRouter);
 router.use('/models', modelsRouter);
 router.use('/suggestions', suggestionsRouter);
 router.use('/chats', chatsRouter);
+router.use('/search', searchRouter);

 export default router;
--- a/src/routes/search.ts
+++ b/src/routes/search.ts
@ -0,0 +1,150 @@
+import express from 'express';
+import logger from '../utils/logger';
+import { BaseChatModel } from 'langchain/chat_models/base';
+import { Embeddings } from 'langchain/embeddings/base';
+import { ChatOpenAI } from '@langchain/openai';
+import {
+  getAvailableChatModelProviders,
+  getAvailableEmbeddingModelProviders,
+} from '../lib/providers';
+import { searchHandlers } from '../websocket/messageHandler';
+import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
+
+const router = express.Router();
+
+interface chatModel {
+  provider: string;
+  model: string;
+  customOpenAIBaseURL?: string;
+  customOpenAIKey?: string;
+}
+
+interface embeddingModel {
+  provider: string;
+  model: string;
+}
+
+interface ChatRequestBody {
+  focusMode: string;
+  chatModel?: chatModel;
+  embeddingModel?: embeddingModel;
+  query: string;
+  history: Array<[string, string]>;
+}
+
+router.post('/', async (req, res) => {
+  try {
+    const body: ChatRequestBody = req.body;
+
+    if (!body.focusMode || !body.query) {
+      return res.status(400).json({ message: 'Missing focus mode or query' });
+    }
+
+    body.history = body.history || [];
+
+    const history: BaseMessage[] = body.history.map((msg) => {
+      if (msg[0] === 'human') {
+        return new HumanMessage({
+          content: msg[1],
+        });
+      } else {
+        return new AIMessage({
+          content: msg[1],
+        });
+      }
+    });
+
+    const [chatModelProviders, embeddingModelProviders] = await Promise.all([
+      getAvailableChatModelProviders(),
+      getAvailableEmbeddingModelProviders(),
+    ]);
+
+    const chatModelProvider =
+      body.chatModel?.provider || Object.keys(chatModelProviders)[0];
+    const chatModel =
+      body.chatModel?.model ||
+      Object.keys(chatModelProviders[chatModelProvider])[0];
+
+    const embeddingModelProvider =
+      body.embeddingModel?.provider || Object.keys(embeddingModelProviders)[0];
+    const embeddingModel =
+      body.embeddingModel?.model ||
+      Object.keys(embeddingModelProviders[embeddingModelProvider])[0];
+
+    let llm: BaseChatModel | undefined;
+    let embeddings: Embeddings | undefined;
+
+    if (body.chatModel?.provider === 'custom_openai') {
+      if (
+        !body.chatModel?.customOpenAIBaseURL ||
+        !body.chatModel?.customOpenAIKey
+      ) {
+        return res
+          .status(400)
+          .json({ message: 'Missing custom OpenAI base URL or key' });
+      }
+
+      llm = new ChatOpenAI({
+        modelName: body.chatModel.model,
+        openAIApiKey: body.chatModel.customOpenAIKey,
+        temperature: 0.7,
+        configuration: {
+          baseURL: body.chatModel.customOpenAIBaseURL,
+        },
+      }) as unknown as BaseChatModel;
+    } else if (
+      chatModelProviders[chatModelProvider] &&
+      chatModelProviders[chatModelProvider][chatModel]
+    ) {
+      llm = chatModelProviders[chatModelProvider][chatModel]
+        .model as unknown as BaseChatModel | undefined;
+    }
+
+    if (
+      embeddingModelProviders[embeddingModelProvider] &&
+      embeddingModelProviders[embeddingModelProvider][embeddingModel]
+    ) {
+      embeddings = embeddingModelProviders[embeddingModelProvider][
+        embeddingModel
+      ].model as Embeddings | undefined;
+    }
+
+    if (!llm || !embeddings) {
+      return res.status(400).json({ message: 'Invalid model selected' });
+    }
+
+    const searchHandler = searchHandlers[body.focusMode];
+
+    if (!searchHandler) {
+      return res.status(400).json({ message: 'Invalid focus mode' });
+    }
+
+    const emitter = searchHandler(body.query, history, llm, embeddings);
+
+    let message = '';
+    let sources = [];
+
+    emitter.on('data', (data) => {
+      const parsedData = JSON.parse(data);
+      if (parsedData.type === 'response') {
+        message += parsedData.data;
+      } else if (parsedData.type === 'sources') {
+        sources = parsedData.data;
+      }
+    });
+
+    emitter.on('end', () => {
+      res.status(200).json({ message, sources });
+    });
+
+    emitter.on('error', (data) => {
+      const parsedData = JSON.parse(data);
+      res.status(500).json({ message: parsedData.data });
+    });
+  } catch (err: any) {
+    logger.error(`Error in getting search results: ${err.message}`);
+    res.status(500).json({ message: 'An error has occurred.' });
+  }
+});
+
+export default router;
--- a/src/routes/suggestions.ts
+++ b/src/routes/suggestions.ts
@ -26,7 +26,7 @@ router.post('/', async (req, res) => {
    let llm: BaseChatModel | undefined;

    if (chatModels[provider] && chatModels[provider][chatModel]) {
-      llm = chatModels[provider][chatModel] as BaseChatModel | undefined;
+      llm = chatModels[provider][chatModel].model as BaseChatModel | undefined;
    }

    if (!llm) {
--- a/src/routes/videos.ts
+++ b/src/routes/videos.ts
@ -26,7 +26,7 @@ router.post('/', async (req, res) => {
    let llm: BaseChatModel | undefined;

    if (chatModels[provider] && chatModels[provider][chatModel]) {
-      llm = chatModels[provider][chatModel] as BaseChatModel | undefined;
+      llm = chatModels[provider][chatModel].model as BaseChatModel | undefined;
    }

    if (!llm) {
--- a/src/websocket/connectionManager.ts
+++ b/src/websocket/connectionManager.ts
@ -45,9 +45,8 @@ export const handleConnection = async (
      chatModelProviders[chatModelProvider][chatModel] &&
      chatModelProvider != 'custom_openai'
    ) {
-      llm = chatModelProviders[chatModelProvider][chatModel] as
-        | BaseChatModel
-        | undefined;
+      llm = chatModelProviders[chatModelProvider][chatModel]
+        .model as unknown as BaseChatModel | undefined;
    } else if (chatModelProvider == 'custom_openai') {
      llm = new ChatOpenAI({
        modelName: chatModel,
@ -56,7 +55,7 @@ export const handleConnection = async (
        configuration: {
          baseURL: searchParams.get('openAIBaseURL'),
        },
-      });
+      }) as unknown as BaseChatModel;
    }

    if (
@ -65,7 +64,7 @@ export const handleConnection = async (
    ) {
      embeddings = embeddingModelProviders[embeddingModelProvider][
        embeddingModel
-      ] as Embeddings | undefined;
+      ].model as Embeddings | undefined;
    }

    if (!llm || !embeddings) {
--- a/src/websocket/messageHandler.ts
+++ b/src/websocket/messageHandler.ts
@ -28,7 +28,7 @@ type WSMessage = {
  history: Array<[string, string]>;
 };

-const searchHandlers = {
+export const searchHandlers = {
  webSearch: handleWebSearch,
  academicSearch: handleAcademicSearch,
  writingAssistant: handleWritingAssistant,
--- a/ui/app/layout.tsx
+++ b/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',
              },
            }}
          />
--- a/ui/app/library/page.tsx
+++ b/ui/app/library/page.tsx
@ -1,11 +1,12 @@
 'use client';

+import DeleteChat from '@/components/DeleteChat';
 import { formatTimeDifference } from '@/lib/utils';
-import { BookOpenText, ClockIcon, ScanEye } from 'lucide-react';
+import { BookOpenText, ClockIcon, Delete, ScanEye } from 'lucide-react';
 import Link from 'next/link';
 import { useEffect, useState } from 'react';

-interface Chat {
+export interface Chat {
  id: string;
  title: string;
  createdAt: string;
@ -92,6 +93,11 @@ const Page = () => {
                    {formatTimeDifference(new Date(), chat.createdAt)} Ago
                  </p>
                </div>
+                <DeleteChat
+                  chatId={chat.id}
+                  chats={chats}
+                  setChats={setChats}
+                />
              </div>
            </div>
          ))}
--- a/ui/components/ChatWindow.tsx
+++ b/ui/components/ChatWindow.tsx
@ -9,6 +9,7 @@ import crypto from 'crypto';
 import { toast } from 'sonner';
 import { useSearchParams } from 'next/navigation';
 import { getSuggestions } from '@/lib/actions';
+import Error from 'next/error';

 export type Message = {
  messageId: string;
@ -37,43 +38,56 @@ const useSocket = (
          'embeddingModelProvider',
        );

+        const providers = await fetch(
+          `${process.env.NEXT_PUBLIC_API_URL}/models`,
+          {
+            headers: {
+              'Content-Type': 'application/json',
+            },
+          },
+        ).then(async (res) => await res.json());
+
        if (
          !chatModel ||
          !chatModelProvider ||
          !embeddingModel ||
          !embeddingModelProvider
        ) {
-          const providers = await fetch(
-            `${process.env.NEXT_PUBLIC_API_URL}/models`,
-            {
-              headers: {
-                'Content-Type': 'application/json',
-              },
-            },
-          ).then(async (res) => await res.json());
+          if (!chatModel || !chatModelProvider) {
+            const chatModelProviders = providers.chatModelProviders;

-          const chatModelProviders = providers.chatModelProviders;
-          const embeddingModelProviders = providers.embeddingModelProviders;
+            chatModelProvider = Object.keys(chatModelProviders)[0];

-          if (
-            !chatModelProviders ||
-            Object.keys(chatModelProviders).length === 0
-          )
-            return toast.error('No chat models available');
+            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');
+            }
+          }

-          if (
-            !embeddingModelProviders ||
-            Object.keys(embeddingModelProviders).length === 0
-          )
-            return toast.error('No embedding models available');
+          if (!embeddingModel || !embeddingModelProvider) {
+            const embeddingModelProviders = providers.embeddingModelProviders;

-          chatModelProvider = Object.keys(chatModelProviders)[0];
-          chatModel = Object.keys(chatModelProviders[chatModelProvider])[0];
+            if (
+              !embeddingModelProviders ||
+              Object.keys(embeddingModelProviders).length === 0
+            )
+              return toast.error('No embedding models available');

-          embeddingModelProvider = Object.keys(embeddingModelProviders)[0];
-          embeddingModel = Object.keys(
-            embeddingModelProviders[embeddingModelProvider],
-          )[0];
+            embeddingModelProvider = Object.keys(embeddingModelProviders)[0];
+            embeddingModel = Object.keys(
+              embeddingModelProviders[embeddingModelProvider],
+            )[0];
+          }

          localStorage.setItem('chatModel', chatModel!);
          localStorage.setItem('chatModelProvider', chatModelProvider);
@ -82,6 +96,47 @@ const useSocket = (
            'embeddingModelProvider',
            embeddingModelProvider,
          );
+        } else {
+          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);
@ -110,8 +165,6 @@ const useSocket = (

        const timeoutId = setTimeout(() => {
          if (ws.readyState !== 1) {
-            ws.close();
-            setError(true);
            toast.error(
              'Failed to connect to the server. Please try again later.',
            );
@ -121,7 +174,6 @@ const useSocket = (
        ws.onopen = () => {
          console.log('[DEBUG] open');
          clearTimeout(timeoutId);
-          setError(false);
          setIsWSReady(true);
        };

@ -137,16 +189,18 @@ 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);
      };

      connectWs();
    }
-
-    return () => {
-      ws?.close();
-      console.log('[DEBUG] closed');
-    };
  }, [ws, url, setIsWSReady, setError]);

  return ws;
@ -158,6 +212,7 @@ const loadMessages = async (
  setIsMessagesLoaded: (loaded: boolean) => void,
  setChatHistory: (history: [string, string][]) => void,
  setFocusMode: (mode: string) => void,
+  setNotFound: (notFound: boolean) => void,
 ) => {
  const res = await fetch(
    `${process.env.NEXT_PUBLIC_API_URL}/chats/${chatId}`,
@ -169,6 +224,12 @@ const loadMessages = async (
    },
  );

+  if (res.status === 404) {
+    setNotFound(true);
+    setIsMessagesLoaded(true);
+    return;
+  }
+
  const data = await res.json();

  const messages = data.messages.map((msg: any) => {
@ -190,7 +251,6 @@ const loadMessages = async (

  setChatHistory(history);
  setFocusMode(data.chat.focusMode);
-  console.log(data);
  setIsMessagesLoaded(true);
 };

@ -221,6 +281,8 @@ const ChatWindow = ({ id }: { id?: string }) => {

  const [isMessagesLoaded, setIsMessagesLoaded] = useState(false);

+  const [notFound, setNotFound] = useState(false);
+
  useEffect(() => {
    if (
      chatId &&
@ -234,6 +296,7 @@ const ChatWindow = ({ id }: { id?: string }) => {
        setIsMessagesLoaded,
        setChatHistory,
        setFocusMode,
+        setNotFound,
      );
    } else if (!chatId) {
      setNewChatCreated(true);
@ -243,6 +306,15 @@ const ChatWindow = ({ id }: { id?: string }) => {
    // eslint-disable-next-line react-hooks/exhaustive-deps
  }, []);

+  useEffect(() => {
+    return () => {
+      if (ws?.readyState === 1) {
+        ws.close();
+        console.log('[DEBUG] closed');
+      }
+    };
+  }, []);
+
  const messagesRef = useRef<Message[]>([]);

  useEffect(() => {
@ -416,26 +488,30 @@ const ChatWindow = ({ id }: { id?: string }) => {
  }

  return isReady ? (
-    <div>
-      {messages.length > 0 ? (
-        <>
-          <Navbar messages={messages} />
-          <Chat
-            loading={loading}
-            messages={messages}
+    notFound ? (
+      <Error statusCode={404} />
+    ) : (
+      <div>
+        {messages.length > 0 ? (
+          <>
+            <Navbar messages={messages} />
+            <Chat
+              loading={loading}
+              messages={messages}
+              sendMessage={sendMessage}
+              messageAppeared={messageAppeared}
+              rewrite={rewrite}
+            />
+          </>
+        ) : (
+          <EmptyChat
            sendMessage={sendMessage}
-            messageAppeared={messageAppeared}
-            rewrite={rewrite}
+            focusMode={focusMode}
+            setFocusMode={setFocusMode}
          />
-        </>
-      ) : (
-        <EmptyChat
-          sendMessage={sendMessage}
-          focusMode={focusMode}
-          setFocusMode={setFocusMode}
-        />
-      )}
-    </div>
+        )}
+      </div>
+    )
  ) : (
    <div className="flex flex-row items-center justify-center min-h-screen">
      <svg
--- a/ui/components/DeleteChat.tsx
+++ b/ui/components/DeleteChat.tsx
@ -0,0 +1,114 @@
+import { Delete, Trash } from 'lucide-react';
+import { Dialog, Transition } from '@headlessui/react';
+import { Fragment, useState } from 'react';
+import { toast } from 'sonner';
+import { Chat } from '@/app/library/page';
+
+const DeleteChat = ({
+  chatId,
+  chats,
+  setChats,
+}: {
+  chatId: string;
+  chats: Chat[];
+  setChats: (chats: Chat[]) => void;
+}) => {
+  const [confirmationDialogOpen, setConfirmationDialogOpen] = useState(false);
+  const [loading, setLoading] = useState(false);
+
+  const handleDelete = async () => {
+    setLoading(true);
+    try {
+      const res = await fetch(
+        `${process.env.NEXT_PUBLIC_API_URL}/chats/${chatId}`,
+        {
+          method: 'DELETE',
+          headers: {
+            'Content-Type': 'application/json',
+          },
+        },
+      );
+
+      if (res.status != 200) {
+        throw new Error('Failed to delete chat');
+      }
+
+      const newChats = chats.filter((chat) => chat.id !== chatId);
+
+      setChats(newChats);
+    } catch (err: any) {
+      toast.error(err.message);
+    } finally {
+      setConfirmationDialogOpen(false);
+      setLoading(false);
+    }
+  };
+
+  return (
+    <>
+      <button
+        onClick={() => {
+          setConfirmationDialogOpen(true);
+        }}
+        className="bg-transparent text-red-400 hover:scale-105 transition duration-200"
+      >
+        <Trash size={17} />
+      </button>
+      <Transition appear show={confirmationDialogOpen} as={Fragment}>
+        <Dialog
+          as="div"
+          className="relative z-50"
+          onClose={() => {
+            if (!loading) {
+              setConfirmationDialogOpen(false);
+            }
+          }}
+        >
+          <Dialog.Backdrop className="fixed inset-0 bg-black/30" />
+          <div className="fixed inset-0 overflow-y-auto">
+            <div className="flex min-h-full items-center justify-center p-4 text-center">
+              <Transition.Child
+                as={Fragment}
+                enter="ease-out duration-200"
+                enterFrom="opacity-0 scale-95"
+                enterTo="opacity-100 scale-100"
+                leave="ease-in duration-100"
+                leaveFrom="opacity-100 scale-200"
+                leaveTo="opacity-0 scale-95"
+              >
+                <Dialog.Panel className="w-full max-w-md transform rounded-2xl bg-light-secondary dark:bg-dark-secondary border border-light-200 dark:border-dark-200 p-6 text-left align-middle shadow-xl transition-all">
+                  <Dialog.Title className="text-lg font-medium leading-6 dark:text-white">
+                    Delete Confirmation
+                  </Dialog.Title>
+                  <Dialog.Description className="text-sm dark:text-white/70 text-black/70">
+                    Are you sure you want to delete this chat?
+                  </Dialog.Description>
+                  <div className="flex flex-row items-end justify-end space-x-4 mt-6">
+                    <button
+                      onClick={() => {
+                        if (!loading) {
+                          setConfirmationDialogOpen(false);
+                        }
+                      }}
+                      className="text-black/50 dark:text-white/50 text-sm hover:text-black/70 hover:dark:text-white/70 transition duration-200"
+                    >
+                      Cancel
+                    </button>
+                    <button
+                      onClick={handleDelete}
+                      className="text-red-400 text-sm hover:text-red-500 transition duration200"
+                    >
+                      Delete
+                    </button>
+                  </div>
+                </Dialog.Panel>
+              </Transition.Child>
+            </div>
+          </div>
+        </Dialog>
+      </Transition>
+    </>
+  );
+};
+
+export default DeleteChat;
--- a/ui/components/EmptyChatMessageInput.tsx
+++ b/ui/components/EmptyChatMessageInput.tsx
@ -18,14 +18,21 @@ const EmptyChatMessageInput = ({

  const inputRef = useRef<HTMLTextAreaElement | null>(null);

-  const handleKeyDown = (e: KeyboardEvent) => {
-    if (e.key === '/') {
-      e.preventDefault();
-      inputRef.current?.focus();
-    }
-  };
-
  useEffect(() => {
+    const handleKeyDown = (e: KeyboardEvent) => {
+      const activeElement = document.activeElement;
+
+      const isInputFocused =
+        activeElement?.tagName === 'INPUT' ||
+        activeElement?.tagName === 'TEXTAREA' ||
+        activeElement?.hasAttribute('contenteditable');
+
+      if (e.key === '/' && !isInputFocused) {
+        e.preventDefault();
+        inputRef.current?.focus();
+      }
+    };
+
    document.addEventListener('keydown', handleKeyDown);

    return () => {
--- a/ui/components/MessageInput.tsx
+++ b/ui/components/MessageInput.tsx
@ -27,14 +27,21 @@ const MessageInput = ({

  const inputRef = useRef<HTMLTextAreaElement | null>(null);

-  const handleKeyDown = (e: KeyboardEvent) => {
-    if (e.key === '/') {
-      e.preventDefault();
-      inputRef.current?.focus();
-    }
-  };
-
  useEffect(() => {
+    const handleKeyDown = (e: KeyboardEvent) => {
+      const activeElement = document.activeElement;
+
+      const isInputFocused =
+        activeElement?.tagName === 'INPUT' ||
+        activeElement?.tagName === 'TEXTAREA' ||
+        activeElement?.hasAttribute('contenteditable');
+
+      if (e.key === '/' && !isInputFocused) {
+        e.preventDefault();
+        inputRef.current?.focus();
+      }
+    };
+
    document.addEventListener('keydown', handleKeyDown);

    return () => {
--- a/ui/components/SearchImages.tsx
+++ b/ui/components/SearchImages.tsx
@ -51,7 +51,7 @@ const SearchImages = ({

            const data = await res.json();

-            const images = data.images;
+            const images = data.images ?? [];
            setImages(images);
            setSlides(
              images.map((image: Image) => {
--- a/ui/components/SearchVideos.tsx
+++ b/ui/components/SearchVideos.tsx
@ -64,7 +64,7 @@ const Searchvideos = ({

            const data = await res.json();

-            const videos = data.videos;
+            const videos = data.videos ?? [];
            setVideos(videos);
            setSlides(
              videos.map((video: Video) => {
--- a/ui/components/SettingsDialog.tsx
+++ b/ui/components/SettingsDialog.tsx
@ -49,13 +49,14 @@ export const Select = ({ className, options, ...restProps }: SelectProps) => {

 interface SettingsType {
  chatModelProviders: {
-    [key: string]: string[];
+    [key: string]: [Record<string, any>];
  };
  embeddingModelProviders: {
-    [key: string]: string[];
+    [key: string]: [Record<string, any>];
  };
  openaiApiKey: string;
  groqApiKey: string;
+  anthropicApiKey: string;
  ollamaApiUrl: string;
 }

@ -67,6 +68,10 @@ const SettingsDialog = ({
  setIsOpen: (isOpen: boolean) => void;
 }) => {
  const [config, setConfig] = useState<SettingsType | null>(null);
+  const [chatModels, setChatModels] = useState<Record<string, any>>({});
+  const [embeddingModels, setEmbeddingModels] = useState<Record<string, any>>(
+    {},
+  );
  const [selectedChatModelProvider, setSelectedChatModelProvider] = useState<
    string | null
  >(null);
@ -117,7 +122,7 @@ const SettingsDialog = ({
        const chatModel =
          localStorage.getItem('chatModel') ||
          (data.chatModelProviders &&
-            data.chatModelProviders[chatModelProvider]?.[0]) ||
+            data.chatModelProviders[chatModelProvider]?.[0].name) ||
          '';
        const embeddingModelProvider =
          localStorage.getItem('embeddingModelProvider') ||
@ -126,7 +131,7 @@ const SettingsDialog = ({
        const embeddingModel =
          localStorage.getItem('embeddingModel') ||
          (data.embeddingModelProviders &&
-            data.embeddingModelProviders[embeddingModelProvider]?.[0]) ||
+            data.embeddingModelProviders[embeddingModelProvider]?.[0].name) ||
          '';

        setSelectedChatModelProvider(chatModelProvider);
@ -135,6 +140,8 @@ const SettingsDialog = ({
        setSelectedEmbeddingModel(embeddingModel);
        setCustomOpenAIApiKey(localStorage.getItem('openAIApiKey') || '');
        setCustomOpenAIBaseURL(localStorage.getItem('openAIBaseURL') || '');
+        setChatModels(data.chatModelProviders || {});
+        setEmbeddingModels(data.embeddingModelProviders || {});
        setIsLoading(false);
      };

@ -224,9 +231,14 @@ 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]
+                                  .name,
+                              );
+                            }
                          }}
                          options={Object.keys(config.chatModelProviders).map(
                            (provider) => ({
@ -259,8 +271,8 @@ const SettingsDialog = ({
                              return chatModelProvider
                                ? chatModelProvider.length > 0
                                  ? chatModelProvider.map((model) => ({
-                                      value: model,
-                                      label: model,
+                                      value: model.name,
+                                      label: model.displayName,
                                    }))
                                  : [
                                      {
@ -336,7 +348,8 @@ const SettingsDialog = ({
                          onChange={(e) => {
                            setSelectedEmbeddingModelProvider(e.target.value);
                            setSelectedEmbeddingModel(
-                              config.embeddingModelProviders[e.target.value][0],
+                              config.embeddingModelProviders[e.target.value][0]
+                                .name,
                            );
                          }}
                          options={Object.keys(
@ -369,8 +382,8 @@ const SettingsDialog = ({
                            return embeddingModelProvider
                              ? embeddingModelProvider.length > 0
                                ? embeddingModelProvider.map((model) => ({
-                                    label: model,
-                                    value: model,
+                                    label: model.displayName,
+                                    value: model.name,
                                  }))
                                : [
                                    {
@ -439,6 +452,22 @@ 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 && (
--- a/ui/package.json
+++ b/ui/package.json
@ -1,6 +1,6 @@
 {
  "name": "perplexica-frontend",
-  "version": "1.7.0",
+  "version": "1.9.0-rc3",
  "license": "MIT",
  "author": "ItzCrazyKns",
  "scripts": {
--- a/yarn.lock
+++ b/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 +321,34 @@
    "@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"
+  integrity sha512-dFDcMabKACvuRd0w6EIRLWf1ubPGZEeEwFt9v1jiEr4HCFxH0OF+iM1QUCcVRbB2fK5lqmKeTD1XAeZV8+AyXA==
+  dependencies:
+    "@langchain/core" "~0.2.11"
+    "@langchain/openai" "~0.1.0"
+    binary-extensions "^2.2.0"
+    expr-eval "^2.0.2"
+    flat "^5.0.2"
+    js-yaml "^4.1.0"
+    langchain "0.2.3"
+    langsmith "~0.1.30"
+    uuid "^9.0.0"
+    zod "^3.22.3"
+    zod-to-json-schema "^3.22.5"
+
 "@langchain/community@~0.0.41":
  version "0.0.43"
  resolved "https://registry.yarnpkg.com/@langchain/community/-/community-0.0.43.tgz#017e2f9b3209b3999482f10df5aec2520731a63c"
@ -320,6 +362,42 @@
    uuid "^9.0.0"
    zod "^3.22.3"

+"@langchain/core@>0.1.56 <0.3.0", "@langchain/core@>0.2.0 <0.3.0", "@langchain/core@>=0.2.5 <0.3.0", "@langchain/core@~0.2.0", "@langchain/core@~0.2.11":
+  version "0.2.11"
+  resolved "https://registry.yarnpkg.com/@langchain/core/-/core-0.2.11.tgz#5f47467e20e56b250831baef20083657c6facb4c"
+  integrity sha512-d4SNL7WI0c3oHrV4WxCRH1/TNqdePXEzYjYwIb4aEH6lW1aM0utGhLbNthX+aYkOL4Ynx2FoG4h91ECIipiKWQ==
+  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 "^9.0.0"
+    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"
@ -348,6 +426,36 @@
    zod "^3.22.4"
    zod-to-json-schema "^3.22.3"

+"@langchain/openai@~0.0.28":
+  version "0.0.34"
+  resolved "https://registry.yarnpkg.com/@langchain/openai/-/openai-0.0.34.tgz#36c9bca0721ab9f7e5d40927e7c0429cacbd5b56"
+  integrity sha512-M+CW4oXle5fdoz2T2SwdOef8pl3/1XmUx1vjn2mXUVM/128aO0l23FMF0SNBsAbRV6P+p/TuzjodchJbi0Ht/A==
+  dependencies:
+    "@langchain/core" ">0.1.56 <0.3.0"
+    js-tiktoken "^1.0.12"
+    openai "^4.41.1"
+    zod "^3.22.4"
+    zod-to-json-schema "^3.22.3"
+
+"@langchain/openai@~0.1.0":
+  version "0.1.3"
+  resolved "https://registry.yarnpkg.com/@langchain/openai/-/openai-0.1.3.tgz#6eb0994e970d85ffa9aaeafb94449024ccf6ca63"
+  integrity sha512-riv/JC9x2A8b7GcHu8sx+mlZJ8KAwSSi231IPTlcciYnKozmrQ5H0vrtiD31fxiDbaRsk7tyCpkSBIOQEo7CyQ==
+  dependencies:
+    "@langchain/core" ">=0.2.5 <0.3.0"
+    js-tiktoken "^1.0.12"
+    openai "^4.49.1"
+    zod "^3.22.4"
+    zod-to-json-schema "^3.22.3"
+
+"@langchain/textsplitters@~0.0.0":
+  version "0.0.3"
+  resolved "https://registry.yarnpkg.com/@langchain/textsplitters/-/textsplitters-0.0.3.tgz#1a3cc93dd2ab330edb225400ded190a22fea14e3"
+  integrity sha512-cXWgKE3sdWLSqAa8ykbCcUsUF1Kyr5J3HOWYGuobhPEycXW4WI++d5DhzdpL238mzoEXTi90VqfSCra37l5YqA==
+  dependencies:
+    "@langchain/core" ">0.2.0 <0.3.0"
+    js-tiktoken "^1.0.12"
+
 "@protobufjs/aspromise@^1.1.1", "@protobufjs/aspromise@^1.1.2":
  version "1.1.2"
  resolved "https://registry.yarnpkg.com/@protobufjs/aspromise/-/aspromise-1.1.2.tgz#9b8b0cc663d669a7d8f6f5d0893a14d348f30fbf"
@ -401,6 +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"
@ -470,6 +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"
@ -514,6 +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"
@ -984,6 +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"
@ -1015,6 +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"
@ -1057,6 +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"
@ -1098,6 +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"
@ -1246,6 +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"
@ -1414,6 +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"
@ -1508,6 +1709,13 @@ is-stream@^2.0.0:
  resolved "https://registry.yarnpkg.com/is-stream/-/is-stream-2.0.1.tgz#fac1e3d53b97ad5a9d0ae9cef2389f5810a5c077"
  integrity sha512-hFoiJiTl63nn+kstHGBtewWSKnQLpyb155KHheA1l39uvtO9nWIop1p3udqPcUd/xbF1VLMO4n7OI6p7RbngDg==

+js-tiktoken@^1.0.12:
+  version "1.0.12"
+  resolved "https://registry.yarnpkg.com/js-tiktoken/-/js-tiktoken-1.0.12.tgz#af0f5cf58e5e7318240d050c8413234019424211"
+  integrity sha512-L7wURW1fH9Qaext0VzaUDpFGVQgjkdE3Dgsy9/+yXyGEpBKnylTd0mU0bfbNkKDlXRb6TEsZkwuflu1B8uQbJQ==
+  dependencies:
+    base64-js "^1.5.1"
+
 js-tiktoken@^1.0.7, js-tiktoken@^1.0.8:
  version "1.0.10"
  resolved "https://registry.yarnpkg.com/js-tiktoken/-/js-tiktoken-1.0.10.tgz#2b343ec169399dcee8f9ef9807dbd4fafd3b30dc"
@ -1532,6 +1740,28 @@ kuler@^2.0.0:
  resolved "https://registry.yarnpkg.com/kuler/-/kuler-2.0.0.tgz#e2c570a3800388fb44407e851531c1d670b061b3"
  integrity sha512-Xq9nH7KlWZmXAtodXDDRE7vs6DU1gTU8zYDHDiWLSip45Egwq3plLHzPn27NgvzL2r1LMPC1vdqh98sQxtqj4A==

+langchain@0.2.3:
+  version "0.2.3"
+  resolved "https://registry.yarnpkg.com/langchain/-/langchain-0.2.3.tgz#c14bb05cf871b21bd63b84b3ab89580b1d62539f"
+  integrity sha512-T9xR7zd+Nj0oXy6WoYKmZLy0DlQiDLFPGYWdOXDxy+AvqlujoPdVQgDSpdqiOHvAjezrByAoKxoHCz5XMwTP/Q==
+  dependencies:
+    "@langchain/core" "~0.2.0"
+    "@langchain/openai" "~0.0.28"
+    "@langchain/textsplitters" "~0.0.0"
+    binary-extensions "^2.2.0"
+    js-tiktoken "^1.0.12"
+    js-yaml "^4.1.0"
+    jsonpointer "^5.0.1"
+    langchainhub "~0.0.8"
+    langsmith "~0.1.7"
+    ml-distance "^4.0.0"
+    openapi-types "^12.1.3"
+    p-retry "4"
+    uuid "^9.0.0"
+    yaml "^2.2.1"
+    zod "^3.22.4"
+    zod-to-json-schema "^3.22.3"
+
 langchain@^0.1.30:
  version "0.1.30"
  resolved "https://registry.yarnpkg.com/langchain/-/langchain-0.1.30.tgz#e1adb3f1849fcd5c596c668300afd5dc8cb37a97"
@ -1571,6 +1801,28 @@ langsmith@~0.1.1, langsmith@~0.1.7:
    p-retry "4"
    uuid "^9.0.0"

+langsmith@~0.1.30:
+  version "0.1.34"
+  resolved "https://registry.yarnpkg.com/langsmith/-/langsmith-0.1.34.tgz#801310495fef258ed9c22bb5575120e2c06d51cf"
+  integrity sha512-aMv2k8kEaovhTuZnK6/6DMCoM7Jurvm1AzdESn+yN+HramRxp3sK32jFRz3ogkXP6GjAjOIofcnNkzhHXSUXGA==
+  dependencies:
+    "@types/uuid" "^9.0.1"
+    commander "^10.0.1"
+    lodash.set "^4.3.2"
+    p-queue "^6.6.2"
+    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"
+  integrity sha512-4hNPN5jlm/N/HLMCO43v8BXKq9Z7QdAGc/VGrRD61w8gN9g/6jF9A4L1pbUgBLCffi0w9VsXfTOij5x8iTyFvg==
+
 logform@^2.3.2, logform@^2.4.0:
  version "2.6.0"
  resolved "https://registry.yarnpkg.com/logform/-/logform-2.6.0.tgz#8c82a983f05d6eaeb2d75e3decae7a768b2bf9b5"
@ -1714,6 +1966,11 @@ ms@2.1.3, ms@^2.0.0, ms@^2.1.1:
  resolved "https://registry.yarnpkg.com/ms/-/ms-2.1.3.tgz#574c8138ce1d2b5861f0b44579dbadd60c6615b2"
  integrity sha512-6FlzubTLZG3J2a/NVCAleEhjzq5oxgHyaCU9yYXvcLsvoVaHJq/s5xXI6/XXP6tz7R9xAOtHnSO/tXtF3WRTlA==

+mustache@^4.2.0:
+  version "4.2.0"
+  resolved "https://registry.yarnpkg.com/mustache/-/mustache-4.2.0.tgz#e5892324d60a12ec9c2a73359edca52972bf6f64"
+  integrity sha512-71ippSywq5Yb7/tVYyGbkBggbU8H3u5Rz56fH60jGFgr8uHwxs+aSKeqmluIVzM0m0kB7xQjKS6qPfd0b2ZoqQ==
+
 napi-build-utils@^1.0.1:
  version "1.0.2"
  resolved "https://registry.yarnpkg.com/napi-build-utils/-/napi-build-utils-1.0.2.tgz#b1fddc0b2c46e380a0b7a76f984dd47c41a13806"
@ -1741,6 +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"
@ -1858,6 +2120,20 @@ openai@^4.26.0:
    node-fetch "^2.6.7"
    web-streams-polyfill "^3.2.1"

+openai@^4.41.1, openai@^4.49.1:
+  version "4.52.2"
+  resolved "https://registry.yarnpkg.com/openai/-/openai-4.52.2.tgz#5d67271f3df84c0b54676b08990eaa9402151759"
+  integrity sha512-mMc0XgFuVSkcm0lRIi8zaw++otC82ZlfkCur1qguXYWPETr/+ZwL9A/vvp3YahX+shpaT6j03dwsmUyLAfmEfg==
+  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"
+
 openapi-types@^12.1.3:
  version "12.1.3"
  resolved "https://registry.yarnpkg.com/openapi-types/-/openapi-types-12.1.3.tgz#471995eb26c4b97b7bd356aacf7b91b73e777dd3"
@ -1891,6 +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"
@ -1901,6 +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"
@ -2062,6 +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"
@ -2212,6 +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"
@ -2358,6 +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"
@ -2462,6 +2776,11 @@ 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@^3.22.4, 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==
+
 zod@^3.22.3, zod@^3.22.4:
  version "3.22.4"
  resolved "https://registry.yarnpkg.com/zod/-/zod-3.22.4.tgz#f31c3a9386f61b1f228af56faa9255e845cf3fff"
Author	SHA1	Message	Date
ItzCrazyKns	a0aad69f62	feat(readme): update readme	2024-09-25 16:56:41 +05:30
ItzCrazyKns	1cfa3398a3	feat(package): bump version	2024-09-25 16:54:44 +05:30
ItzCrazyKns	ead2d98a9f	feat(search): update types	2024-09-25 16:54:19 +05:30
ItzCrazyKns	c52d6ac290	feat(docs): add search API docs	2024-09-25 16:54:07 +05:30
ItzCrazyKns	2785cdd97a	feat(routes): add search route	2024-09-25 15:27:48 +05:30
ItzCrazyKns	1589f16d5a	feat(providers): add `displayName` property	2024-09-24 22:34:43 +05:30
ItzCrazyKns	40f551c426	feat(search-button): add empty check	2024-09-15 10:16:20 +05:30
ItzCrazyKns	1fcd64ad42	feat(docker-file): use SearXNG URL from env	2024-09-05 18:40:07 +05:30
ItzCrazyKns	07e5615860	feat(docker-compose): link `config.toml` as vol.	2024-09-04 18:54:54 +05:30
ItzCrazyKns	c4f52adb45	feat(textarea): handle "/" keys	2024-09-02 11:44:40 +05:30
ItzCrazyKns	92abbc5b98	feat(webSearchRetriever): use `question` instead of `input`	2024-08-29 16:54:37 +05:30
ItzCrazyKns	c952469f08	feat(chaWindow): lint & beautify	2024-08-29 16:51:59 +05:30
ItzCrazyKns	449684c419	feat(webSearchAgent): update retriever prompt & change temp	2024-08-29 16:51:42 +05:30
ItzCrazyKns	f620252406	feat(linkDocument): add error handling	2024-08-29 16:51:12 +05:30
ItzCrazyKns	e8ed4df31a	feat(chat-window): close socket on unmount	2024-08-28 14:27:22 +05:30
ItzCrazyKns	2873093fee	feat(package): bump version	2024-08-28 10:00:05 +05:30
ItzCrazyKns	806c47e705	feat(chatwindow): fix infinite loading	2024-08-28 09:53:06 +05:30
ItzCrazyKns	ff34d1043f	feat(app): lint & format	2024-08-25 15:08:47 +05:30
ItzCrazyKns	c521b032a7	feat(agents): fix unresloved types	2024-08-25 15:08:30 +05:30
ItzCrazyKns	6b8f7dc32c	Merge branch 'pr/309'	2024-08-25 12:03:54 +05:30
ItzCrazyKns	8bb3e4f016	feat(agents): update types	2024-08-25 12:03:32 +05:30
ItzCrazyKns	51939ff842	feat(webSearchAgent): fix typo, closes #313	2024-08-24 21:48:27 +05:30
Xie Yanbo	e4faa82362	Fix #307 , update outdated searxng/settings.yml	2024-08-09 20:53:53 +08:00
ItzCrazyKns	9c1936ec2c	feat(chat-window): lint & beautify	2024-08-04 18:14:46 +05:30
ItzCrazyKns	c4932c659a	feat(app): lint	2024-07-31 20:17:57 +05:30
ItzCrazyKns	96f67c7028	Merge pull request #290 from ItzCrazyKns/canary	2024-07-30 10:15:52 +05:30
ItzCrazyKns	61dfeb89b4	feat(package): bump version	2024-07-30 10:10:55 +05:30
ItzCrazyKns	8e4f0c6a6d	feat(web-search): add URL & PDF searching capibilities	2024-07-30 10:09:05 +05:30
ItzCrazyKns	6f50e25bf3	feat(output-parsers): add line output parser	2024-07-30 10:08:29 +05:30
ItzCrazyKns	9abb4b654d	feat(app): handle unhandled exception & rejection	2024-07-30 10:07:28 +05:30
ItzCrazyKns	0a29237732	feat(listLineOutputParser): handle invalid keys	2024-07-30 10:06:52 +05:30
ItzCrazyKns	c62e7f091e	feat(package): bump version	2024-07-25 20:39:43 +05:30
ItzCrazyKns	08379fcad5	feat(ws-connector): fix `undefined` chat model	2024-07-25 20:36:26 +05:30
ItzCrazyKns	cbce39a5dd	feat(settings): fix `undefined` model for custom OpenAI	2024-07-25 20:34:49 +05:30
ItzCrazyKns	27f8cfd212	feat(toast): fix theme colors	2024-07-25 20:33:56 +05:30
ItzCrazyKns	8a76f92e23	feat(groq): add Llama 3.1	2024-07-23 20:49:17 +05:30
ItzCrazyKns	00a52fc3b1	Delete .github/FUNDING.yml	2024-07-23 10:46:32 +05:30
ItzCrazyKns	8143eca2c1	feat(readme): remove patreon	2024-07-23 10:45:52 +05:30
ItzCrazyKns	9bb0b64044	Merge pull request #279 from zandko/perf/filter-first perf: Optimize document filtering and sorting for performance	2024-07-23 10:08:54 +05:30
Zan	323f3c516c	perf: Optimize document filtering and sorting for performance	2024-07-23 10:06:33 +08:00
ItzCrazyKns	c0b3a409dd	feat(package): bump version	2024-07-20 09:27:34 +05:30
ItzCrazyKns	9195cbcce0	feat(openai): add GPT-4 Omni mini	2024-07-20 09:26:46 +05:30
ItzCrazyKns	f02393dbe9	feat(providers): add anthropic	2024-07-15 21:20:16 +05:30
ItzCrazyKns	e1732b9bf2	feat(chat-window): fix WS connection errors	2024-07-14 12:37:36 +05:30
sjiampojamarn	fac41d3812	add gemma2-9b-it	2024-07-13 20:20:23 -07:00
ItzCrazyKns	27e6f5b9e1	feat(chat-window): unselect unavailable model	2024-07-09 16:21:45 +05:30
ItzCrazyKns	8539ce82ad	feat(providers): fix loading issues	2024-07-08 15:39:27 +05:30
ItzCrazyKns	3b4b8a8b02	feat(providers): add `custom_openai`	2024-07-08 15:24:45 +05:30
ItzCrazyKns	3ffb20b777	feat(backend): fix type errors	2024-07-08 01:31:11 +05:30
ItzCrazyKns	f4b58c7157	feat(dockerfile): revert base image back to slim	2024-07-06 15:13:05 +05:30
ItzCrazyKns	2678c36e44	feat(agents): fix grammar in prompt, closes 239 & 203	2024-07-06 15:12:51 +05:30
ItzCrazyKns	25b5dbd63e	feat(providers): separate each provider	2024-07-06 14:19:33 +05:30
ItzCrazyKns	c63c9b5c8a	feat(readme): update ollama guide	2024-07-03 21:02:21 +05:30
ItzCrazyKns	80818983d8	feat(package): bump version	2024-07-03 20:49:13 +05:30
ItzCrazyKns	5217d21366	feat(dockerfile): revert to `node:slim`	2024-07-03 20:47:31 +05:30
ItzCrazyKns	57ede99b83	Merge branch 'master' of https://github.com/ItzCrazyKns/Perplexica	2024-07-02 10:52:02 +05:30
ItzCrazyKns	c74e16e01c	feat(chats): add delete functionality	2024-07-02 10:51:47 +05:30
ItzCrazyKns	ce593daab9	Update README.md	2024-06-30 12:39:37 +05:30
ItzCrazyKns	fcf9b644af	Create FUNDING.yml	2024-06-30 12:34:32 +05:30
ItzCrazyKns	6ae825999a	feat(readme): update manual install	2024-06-30 10:45:35 +05:30
ItzCrazyKns	b291265944	feat(package): add `@langchain/community`	2024-06-30 10:42:01 +05:30
ItzCrazyKns	c62684407d	feat(chat-window): handle notFound errors	2024-06-29 12:11:34 +05:30
ItzCrazyKns	f4b01a29bb	feat(docs): update docs	2024-06-29 11:39:23 +05:30
ItzCrazyKns	022cf55db7	feat(docs): add update docs	2024-06-29 11:38:43 +05:30