Langchain js pdf loader. I'm using multer in nodejs to handle file uploads.

Langchain js pdf loader js to build stateful agents with first-class streaming and Stack Overflow for Teams Where developers & technologists share private knowledge with coworkers; Advertising & Talent Reach devs & technologists worldwide about your product, service or employer brand; OverflowAI GenAI features for Teams; OverflowAPI Train & fine-tune LLMs; Labs The future of collective knowledge sharing; About the company To effectively load PDF documents into the LangChain framework, you can utilize the PDFLoader class from the community document loaders. It then iterates over each page of the PDF, retrieves the text content using the getTextContent method, and joins the text items Usage, custom pdfjs build . The LangChain PDFLoader integration lives in import {PDFLoader } from "@langchain/community/document_loaders/fs/pdf"; const loader = new PDFLoader ("src/document_loaders/example_data/example. You signed out in another tab or window. Finally, it creates a LangChain Document for each page of the PDF with the page’s content and some metadata about where in the document the text came from. Load Usage . AWS S3 Buckets. Setup To run this loader, you'll need to have Unstructured already set up and ready to use at an available URL endpoint. By default, one document will be created for each page in the PDF file, you can How to load PDF files. If you want to implement your own Document Loader, you have a few options. Reload to refresh your session. Once Unstructured is configured, you can use the S3 loader to load files and then convert them into a Document. By default, it just returns the page as it is. To use this loader, you need to specify a model and configure any necessary environment variables for Zerox, such as API keys. Overview Integration details Explore Langchain's PDF loader in JavaScript for efficient document processing and integration. The script leverages the LangChain library for embeddings and vector storage, incorporating multithreading for efficient concurrent processing. js Newer LangChain version out! You are currently viewing the old v0. It returns one document per page. If you want to get automated tracing of your model calls you can also set your LangSmith API key by uncommenting below: Interface that defines the methods for loading and splitting documents. BUCKET, key: filekey, // example: test/ How to write a custom document loader. A document loader that loads documents from a directory. If you want to get automated best in-class tracing of your model calls you can also set your LangSmith API key by Like PyMuPDF, the output Documents contain detailed metadata about the PDF and its pages, and returns one document per page. 1 docs. Following the numerous tutorials on web, I was not able to come across of extracting the page number of the relevant answer that is being generated given the fact that I have split the texts from a pdf document using CharacterTextSplitter function which results in chunks of the texts based on some I'm trying to load a very large complex PDF that contains tables and figures. js Document loaders are designed to load document objects. You switched accounts on another tab or window. 1. When loading content from a website, we may want to process load all URLs on a page. Introduction. LangChain has many other document loaders for other data sources, or you can create a custom document loader. On this page. rst file or the . Deprecated. How to load PDFs. Subtitles. env. Pdf-loader This is the function responsible for chunking our PDFs into smaller documents to store them in a Pinecone afterward. To load PDF documents into your application using Langchain, you can utilize the It uses the getDocument function from the PDF. When a PDF file is uploaded I want to split it into chunks and store those chunks into a vector store (using langchain. File loaders. However, since you're dealing with a blob URL and not a file path, you'll need to fetch the blob from the URL first. To access Arxiv document loader you'll need to install the arxiv, PyMuPDF and langchain-community integration packages. html files. Newer LangChain version out! You are currently viewing the old v0. It has three attributes: pageContent: a string representing the content;; metadata: records of arbitrary metadata;; id: (optional) a string identifier for the document. The chatbot will utilize Next. Return type. File Loaders. . This covers how to load document objects from an Google Cloud Storage (GCS) file object (blob). Parameters. If a file is a file, it checks if there is a corresponding loader function for the file extension in the loaders mapping. Using . Provide details and share your research! But avoid . Returns Promise < Document < Record < string , any > > [] > An array of Documents representing the retrieved data. We can also use BeautifulSoup4 to load HTML documents using the BSHTMLLoader. Parsing HTML files often requires specialized tools. Before you begin, ensure you have the necessary package installed. 3. To effectively load PDF files using LangChain, you can utilize the PDFLoader class from the A document loader for loading data from PDFs. Here we cover how to load Markdown documents into LangChain Document objects that we can use downstream. 2 million comics, and 381 thousand magazines. We will cover: Basic usage; Parsing of Markdown into elements such as titles, list items, and text. js. js with Typescript with App Router and with vercel AI SDK. Currently, it performs How to load HTML. In this code, a new instance of WebPDFLoader is created with a Blob object as an argument. The load method is then called on the WebPDFLoader instance to load the PDF. % pip install bs4 Unstructured API . js library to load the PDF from the buffer. Subclassing BaseDocumentLoader You can extend the BaseDocumentLoader class directly. For detailed documentation of all DocumentLoader features and configurations head to the API reference. Library Genesis (LibGen) is the largest free library in history: giving the world free access to 84 million scholarly journal articles, 6. One document will be created for each subtitles file. It creates a Document instance for each element and Loading HTML with BeautifulSoup4 . The PDFLoader is designed to handle PDF files efficiently, converting them into a format suitable for downstream applications. View the latest docs here. log ({ docs }); Copy Explore Langchain's PDF loader in JavaScript for efficient document processing and integration. For more information about the UnstructuredLoader, refer to the Unstructured provider page. Splited the text This notebook provides a quick overview for getting started with DirectoryLoader document loaders. This example goes over how to load data from folders with multiple files. We can use the glob parameter to control which files to load. Google Cloud Storage is a managed service for storing unstructured data. document_loaders import UnstructuredURLLoader urls = 2023 - ISW Press\n\nDownload the PDF\n\nKarolina Hird, Riley Bailey, George Barros, Layne Philipson, Nicole Wolkov, and Mason Clark\n\nFebruary 8, 8:30pm ET\n\nClick\xa0here\xa0to see ISW’s interactive map of the A document loader that uses the Unstructured API to load unstructured documents. Credentials How to load CSV data. This process allows you to convert PDF content into a format that can be processed downstream. Blockchain In my NextJS 14 project, I have a client-side component called ResearchChatbox. js To access UnstructuredLoader document loader you’ll need to install the @langchain/community integration package, and create an Unstructured account and get an API key. import { PDFLoader } from "langchain/document_loaders/fs/pdf"; Immediately I get an error: fs module not found As per langchain documentation, this should not occur as it states that the APIs support Next. ; LangChain has many other document loaders for other data sources, or you A document loader that uses the Unstructured API to load unstructured documents. Setup To access FireCrawlLoader document loader you’ll need to install the @langchain/community integration, and the @mendable/firecrawl-js package. load() and splitter. PDFLoader: This notebook It then extracts text data using the pdf-parse package. Local You can run Unstructured locally in your computer using Docker. I am building a question-answer app using LangChain. extractor?: (text: string) => string; // a function to extract the text of the document from the webpage, by default it returns the page as it is. Overview Integration details This notebook provides a quick overview for getting started with PyPDF document loader. If you want to get automated best in-class tracing of your model calls you can also set your LangSmith API key by uncommenting below: This notebook provides a quick overview for getting started with TextLoader document loaders. pdf", {// you may need to add It uses the getDocument function from the PDF. It then iterates over each page of the PDF, retrieves the text content using the getTextContent method, and joins the text items To effectively load PDF files using the PDFLoader from Langchain, you can follow a structured approach that allows for flexibility in how documents are processed. Please note that the actual methods and their usage might vary depending on the parser. AsyncIterator. If you want to get automated tracing of your model calls you can also set your LangSmith API key by uncommenting below: JSON (JavaScript Object Notation) is an open standard file format and data interchange format that uses human-readable text to store and transmit data objects consisting of attribute–value pairs and arrays (or other serializable values). clean_pdf (contents: str) → str [source] ¶ Clean the PDF file. This project was made with Next. SearchApi Loader: This guide shows how to use SearchApi with LangChain to load web sear SerpAPI Loader The JSON loader use JSON pointer to target keys in your JSON files yo JSONLines files: This example goes over how to load data from JSONLines or JSONL files Notion markdown export: This example goes over how to load data from your Notion pages export Open AI Whisper Audio: Only available on Node. How to load Markdown. js to build stateful agents with first-class streaming and Documentation for LangChain. splitDocuments() individually. document_loaders import JSONLoader. PyMuPDF is optimized for speed, and contains detailed metadata about the PDF and its pages. Here we demonstrate parsing via Unstructured. Setup You signed in with another tab or window. Watched lots and lots of youtube videos, researched langchain documentation, so I’ve written the code like that (don't worry, it works :)): Loaded pdfs loader = PyPDFDirectoryLoader("pdfs") docs = loader. You can optionally provide a s3Config parameter to specify your bucket region, access key, and secret access key. Note that here it doesn't load the . Question answering Introduction. The HyperText Markup Language or HTML is the standard markup language for documents designed to be displayed in a web browser. 🦜️🔗 LangChain. To help you ship LangChain apps to production faster, check out LangSmith. {JSONLoader } from "langchain/document_loaders/fs/json"; const loader = new JSONLoader ("src/document JSON (JavaScript Object Notation) is an open standard file format and data interchange format that uses human-readable text to store and transmit data objects consisting of attribute–value pairs and arrays (or other serializable values). If you'd Only available on Node. How to load PDF files. Use this. Setup. If you want to use a more recent version of pdfjs-dist or if you want to use a custom build of pdfjs-dist, you can do so by providing a custom pdfjs function that returns a promise that resolves to the PDFJS object. Amazon Simple Storage Service (Amazon S3) is an object storage service. LangChain simplifies every stage of the LLM application lifecycle: Development: Build your applications using LangChain's open-source building blocks, components, and third-party integrations. If the extracted powerpoint content is empty, it returns an empty array. Markdown is a lightweight markup language for creating formatted text using a plain-text editor. js Loads the contents of the PDF as documents. tsx from which I call a server-side method called vectorize() via a fetch() request, sending it a URL to a PDF documen Documentation for LangChain. The load() method is implemented to read the text from the file or blob, parse it using the parse() method, and create a Document instance for each parsed page. No credentials are needed. For example, there are document loaders for loading a simple . Technical Terms: Embeddings: Numerical representation of words, sentences or documents that capture it's semantic meaning. 2, which is no longer actively maintained. PyMuPDF. The load() method is left abstract and needs to be implemented by subclasses. It uses the getDocument function from the PDF. This section delves into the advanced features and capabilities of the LangChain PDF Loader, providing insights into how it can transform the handling of PDF content for various This guide shows how to scrap and crawl entire websites and load them using the FireCrawlLoader in LangChain. It is recommended to use tools like html-to-text to extract the text. The loader will ignore binary files like images. This covers how to load PDF documents into the Document format that we use downstream. LangChain Hub; LangChain JS/TS; v0. I understand that you're having trouble with the OnlinePDFLoader in LangChain. Example const loader = new WebPDFLoader ( new Blob ()); const docs = await loader . For detailed documentation of all DirectoryLoader features and configurations head to the API reference. In the current implementation, every text item, regardless of whether it's a new word, sentence, or paragraph, is being separated by a newline. Overview . You signed in with another tab or window. This example goes over how to load data from subtitle files. document_loaders. LangSmith is a unified developer platform for building, testing, and monitoring LLM applications. ZeroxPDFLoader enables PDF text extraction using vision-capable language models by converting each page into an image and processing it asynchronously. Use document loaders to load data from a source as Document's. Answer. To access PDFLoader document loader you’ll need to install the @langchain/community integration, along with the pdf-parse package. It then iterates over each page of the PDF, retrieves the text content using the getTextContent To extract text from a PDF document, you can use the PDFLoader class provided by LangChain. It extends the BaseDocumentLoader class and implements the load() method. document_loaders import OnlinePDFLoader Once Unstructured is configured, you can use the S3 loader to load files and then convert them into a Document. Integrations You can find available integrations on the Document loaders integrations page. If there is no corresponding loader function and unknown is set to Warn, it logs a warning message. This allows for seamless integration of PDF documents into your applications, enabling you to It checks if the file is a directory and ignores it. str. A Document is a piece of text and associated metadata. 😎 Great now let's dive into our domain critical parts. It creates a Document instance for each element and It checks if the file is a directory and ignores it. SearchApi Loader: This guide shows how to use SearchApi with LangChain to load web sear SerpAPI Loader: This guide shows how to use SerpAPI with LangChain to load web search Sitemap Loader: This notebook goes over how to use the SitemapLoader class to load si Sonix Audio: Only available on Node. Note: all other PDF loaders can also be used to fetch remote PDFs, but OnlinePDFLoader is a legacy function, and works specifically with UnstructuredPDFLoader. Using Amazon Textract PDF Loader. ⚡ Building applications with LLMs through composability ⚡. Installation The LangChain CSVLoader integration lives in the @langchain/community integration package. % pip install --upgrade --quiet langchain-google-community [gcs] Setup . List. Abstract class that provides a default implementation for the loadAndSplit() method from the DocumentLoader interface. If you don't want to worry about website crawling, bypassing JS To access CSVLoader document loader you’ll need to install the @langchain/community integration, along with the d3-dsv@2 peer dependency. It can also be configured to run locally. js introduction docs. log ({ docs }); Copy To access WebPDFLoader document loader you’ll need to install the @langchain/community integration, along with the pdf-parse package: If you want to get automated tracing of your Documentation for LangChain. JSON (JavaScript Object Notation) is an open standard file format and data interchange format that uses human-readable text to store and transmit data objects consisting of attribute–value pairs and arrays (or other serializable values). ; See the individual pages for Setup Credentials . Setup To access FireCrawlLoader document loader you’ll need to install the @langchain/community integration, and the @mendable/firecrawl-js@0. Load CSV data with a single row per document. Each line of the file is a data record. For the current Document loaders. This is documentation for LangChain v0. load() 2. When I test this function though, certain pdfs work and others don't. The metadata includes the This repository features a Python script (pdf_loader. This example goes over how to load data from PDF files. It then extracts text data using the pypdf package. It represents a document loader that loads documents from a text file. The Blob object is created from a PDF file read from the file system. This guide shows how to scrap and crawl entire websites and load them using the FireCrawlLoader in LangChain. PDF. Document loaders. txt file, for loading the text contents of any web page, or even for loading a transcript of a YouTube video. Stack Overflow for Teams Where developers & technologists share private knowledge with coworkers; Advertising & Talent Reach devs & technologists worldwide about your product, service or employer brand; OverflowAI GenAI features for Teams; OverflowAPI Train & fine-tune LLMs; Labs The future of collective knowledge sharing; About the company Please replace 'path_to_your_pdf_file' with the actual path to your PDF file. When I use the fast option with Unstructured API in Langchain-JS with NextJS it seems to work but ArxivLoader. Specifically, it seems to be able to read some online PDF files but not others. Memory Vector Store: It is an in-memory vectorstore that stores embeddings in-memory and does an exact, linear search for the most similar embeddings. Only available on Node. js for the frontend, MaterialUI for the UI components, Langchain and OpenAI for working with So what just happened? The loader reads the PDF at the specified path into memory. 🚀. LangChain is a framework for developing applications powered by large language models (LLMs). API Reference: JSONLoader. This covers how to use WebBaseLoader to load all text from HTML webpages into a document format that we can use downstream. To effectively load PDF files using LangChain, you can utilize the PDFLoader class from the community document loaders. A lazy loader for Documents. The load method reads the PDF file, and the process method processes the loaded data. Using PyPDF . Interface Documents loaders implement the BaseLoader interface. To access CheerioWebBaseLoader document loader you’ll need to install the @langchain/community integration package, along with the cheerio peer dependency. The load() method sends a partitioning request to the Unstructured API and retrieves the partitioned elements. LangChain implements a Document abstraction, which is intended to represent a unit of text and associated metadata. Each record consists of one or more fields, separated by commas. Credentials The implementation uses LangChain document loaders to parse the contents of a file and pass them to Lumos’s online, the core dependency of LangChain’s WebPDFLoader, PDF. This covers how to load document objects from an AWS S3 File object. js Documentation for LangChain. js (via pdf-parse), Once Unstructured is configured, you can use the S3 loader to load files and then convert them into a Document. 37 This covers how to load youtube transcript into LangChain documents. To access PyPDFium2 document loader you'll need to install the langchain-community integration package. /r/libgen and its moderators are not directly affiliated with Library Genesis. I'm coding a project use s3 to store file pdf, and use langchain to connect and load file. It uses the parseOfficeAsync function from the officeparser module to extract the raw text content from the buffer. The AmazonTextractPDFLoader is a powerful tool that leverages the Amazon Textract Service to transform PDF documents into a structured Document format. While they share a common goal, their approaches and use cases differ significantly. DirectoryLoader accepts a loader_cls kwarg, which defaults to UnstructuredLoader. The metadata includes the source of the text (file path or blob) and, if there are multiple pages, the This example goes over how to load data from docx files. This is my code: const loader = new S3Loader({ bucket: process. The UnstructuredPDFLoader is a versatile tool that LangChain Hub; LangChain JS/TS; v0. Use LangGraph. js PDF files: This notebook provides a quick overview for getting started with: RecursiveUrlLoader: This notebook provides a quick overview for getting started with: S3 File: Only available on Node. js Initialization . These loaders are used to load files given a filesystem path or a Blob object. - seanghay/langchain-pdf Wanted to build a bot to chat with pdf. Credentials . js, aws s3, neondb, and pineconedb that takes in a pdf and let's you chat with openAI about the contents. Hello, Thank you for bringing this to our attention. 5 Turbo, you can create interactive and intelligent applications that work seamlessly with PDF files. Loading PDF Files with LangChain. This will extract the text from the HTML into page_content, and the page title as title into metadata. info. It supports both the new syntax with options object and the legacy syntax for backward compatibility. Note : Make sure to install the required libraries and models before running the code. Head over to Documentation for LangChain. Asking for help, clarification, or responding to other answers. This guide covers how to load PDF documents into the LangChain Document format that we use downstream. js enviroment. Its roughly 600 pages. {JSONLoader } from "langchain/document_loaders/fs/json"; const loader = new JSONLoader ("src/document This covers how to load a container on Azure Blob Storage into LangChain documents. Though we can query the vector store directly, we convert the vector store Documentation for LangChain. 36 package. The above code is a general example and might not work as is. md) file. The loader will process your document using the hosted Unstructured SearchApi Loader. Setup . ; We are looping through our files in sequence and we are using the LangChain. No credentials are needed for this loader. This covers how to load HTML documents into a LangChain Document objects that we can use downstream. I am trying to run the PDFLoader [example] using pdf-parse, and I encountered an issue in the browser: Uncaught (in promise) TypeError: readFile is not a function at PDFLoader. The second argument is a JSONPointer to the property to extract from each JSON object in the file. It then iterates over each page of the PDF, retrieves * the text content using the `getTextContent` method, and joins the text * items to form the page content. A method that takes a raw buffer and metadata as parameters and returns a promise that resolves to an array of Document instances. We then load those documents (which also embeds the documents using the passed OpenAIEmbeddings instance) into HNSWLib, our vector store, creating our index. contents (str) – a PDF file contents. I'm trying to load a very large complex PDF that contains tables and figures. Looking for the Python version? Check out LangChain. ; Finally, it creates a LangChain Document for each page of the PDF with the page's content and some metadata about where in the document the text came from. txt file, for loading the text contents of any web This example goes over how to load data from PPTX files. UnstructuredPDFLoader. It reads PDF files and let you ask what those files are about. Code Walkthrough . By default, one document will be created for all pages in the PPTX file. js - v0. js for efficient document processing and data extraction. js) for a RAG application. Here’s a simple example: This code snippet initializes a PDFLoader instance A document loader for loading data from PDFs. Here we use it to read in a markdown (. interface Options { excludeDirs?: string []; // webpage directories to exclude. SearchApi is a real-time API that grants developers access to results from a variety of search engines, including engines like Google Search, Google News, Google Scholar, YouTube Transcripts or any other engine that could be found in documentation. It then parses the text using the parse() method and creates a Document instance for each parsed page. The OpenAI key must be set in the environment variable OPENAI_API_KEY. For detailed documentation of all TextLoader features and configurations head to the API reference. LangChain has hundreds of integrations with various data sources to load data from: Slack, Notion, Google Drive, etc. document_loaders import S3FileLoader. load (langchain_docum This example goes over how to load data from JSONLines or JSONL files. The BaseDocumentLoader class provides a few convenience methods for loading documents from a variety of sources. It then iterates over each page of the PDF, retrieves the text content using the getTextContent Explore how to use Langchain's PDF loader in Node. Documentation for LangChain. 6 million academic and general-interest books, 2. One document will be created for each JSON object in the file. arXiv is an open-access archive for 2 million scholarly articles in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics. gitignore Syntax . ; See the individual pages for Documentation for LangChain. Merge the documents returned from a set of specified data loaders. 🤖. Then create a FireCrawl account and get an API key. async aload → List [Document] ¶ Load data into Document objects. For more custom logic for loading webpages look at some child class examples such as IMSDbLoader, AZLyricsLoader, and CollegeConfidentialLoader. To ignore specific files, you can pass in an ignorePaths array into the constructor: Recursive URL Loader. Let's walk through what's happening here. This guide shows how to use SearchApi with LangChain to load web search results. load (); console . When I use the fast option with Unstructured API in Langchain-JS with NextJS it seems to work but from langchain_community. AWS S3 File. A comma-separated values (CSV) file is a delimited text file that uses a comma to separate values. I am currently writing a function that takes in the pdf and uses PDFLoader from Langchain to convert the pdf in text strings. import json Use document loaders to load data from a source as Document's. A class that extends the BaseDocumentLoader class. Load Documents and Document Loaders . Document loaders load data into LangChain's expected format for use-cases such as retrieval-augmented generation (RAG). py) that demonstrates the integration of LangChain to process PDF files, segment text documents, and establish a Chroma vector store. from langchain_community. Unstructured supports parsing for a number of formats, such as PDF and HTML. To access PuppeteerWebBaseLoader document loader you’ll need to install the @langchain/community integration package, along with the puppeteer peer dependency. For example, let's look at the LangChain. ; Web loaders, which load data from remote sources. This guide shows how to use Firecrawl with LangChain to load web data into an LLM-ready format using Firecrawl. The UnstructuredPDFLoader and OnlinePDFLoader are both integral components of the Langchain framework, designed to facilitate the loading of PDF documents into a usable format for downstream processing. Portable Document Format (PDF), standardized as ISO 32000, is a file format developed by Adobe in 1992 to present documents, including text formatting and images, in a manner independent of application software, hardware, and operating systems. An OpenAI key is required for this application (see Create an OpenAI API key). If you want to get up and running with smaller packages and get the most up-to-date partitioning you can pip install unstructured-client and pip install langchain-unstructured. 📄️ PDF files. js categorizes document loaders in two different ways: File loaders, which load data into LangChain formats from your local filesystem. I am trying to use the document loaders in langchain to load my PDF, however when I call a loader eg. The issue you're experiencing with the PDFLoader in LangChainJS is due to the way the text content is being joined in the parse method. merge import MergedDataLoader loader_all = MergedDataLoader ( loaders = [ loader_web , loader_pdf ] ) API Reference: JSON (JavaScript Object Notation) is an open standard file format and data interchange format that uses human-readable text to store and transmit data objects consisting of attribute–value pairs and arrays (or other serializable values). By default we use the pdfjs build bundled with pdf-parse, which is compatible with most environments, including Node. LangChain. ; The metadata attribute can capture information about the source This example goes over how to load data from docx files. It represents a document loader for loading files from an S3 bucket. In this application, a simple chatbot is implemented that The LangChain PDF Loader is a sophisticated tool designed to enhance the interaction with PDF documents by leveraging the power of Large Language Models (LLMs). Returns: get_processed_pdf (pdf_id: str) → str [source Answer generated by a 🤖. ⚡️ Quick Install Setup . Thanks for contributing an answer to Stack Overflow! Please be sure to answer the question. js and modern browsers. Compatibility. Document loaders expose a "load" method for loading data as documents from a configured How to load CSV data. js; langchain/document_loaders/web/pdf; Module langchain/document_loaders/web/pdf WebBaseLoader. I'm using multer in nodejs to handle file uploads. 0. Explore the Langchain PDF loader, designed to efficiently handle PDF files with integrated image support for enhanced data processing. It reads the text from the file or blob using the readFile function from the node:fs/promises module or the text() method of the blob. See A method that loads the text file or blob and returns a promise that resolves to an array of Document instances. I am trying to build an AI Saas, using next. Step 3: Retrieving the document The retrieval part has 3 main steps Google Cloud Storage File. Loads the documents and splits them using a specified text splitter. In this tutorial, we will create a chatbot system that can be trained with custom data from PDF files. By leveraging the PDF loader in LangChain and the advanced capabilities of GPT-3. We first load a long text and split it into smaller documents using a text splitter. This has many interesting child pages that we may want to load, split, and later retrieve in bulk. PDFLoader Documentation for LangChain. If there is, it loads the documents. Preparing search index The search index is not available; LangChain. epaak iejang vgtii wdpvo feacx qgtjhg rhfh mambmf aujvac yygdnn