Одну секунду
Что-то сучилось. Попробуйте еще раз.
Langchain js смотреть последние обновления за сегодня на .
In this tutorial, you’ll learn the basics of how to use LangChain to build scalable javascript/typescript large language model applications trained on your own custom data. LangChain is a framework and library packed with useful prompts, large language models interfaces, indexes, and more, to make it easier to build chatbots for your docs, 'personal assistants' with access to external tools, Question-answering your data, and more. Large language models have been traditionally used by Python and machine learning engineers, however, LangChain has recently provided support for Javascript and Typescript developers to add superpowers to their AI applications. As the LangChain ecosystem grows alongside similar frameworks, we can expect to see more accessibility for javascript and typescript world. 🖼 Visual guide download + github repo: 🤍 Courses: 💻 A step-by-step beginners training program on how to build a ChatGPT chatbot for your data: 🤍 Twitter: 🤍 Send a tip to support the channel: 🤍 Timestamps: 01:00 What problems are LangChain solving? 07:40 LangChain usecases + components 09:30 LangChain demo 11:07 Simple LangChain chain 14:34 LangChain prompt templates 21:11 LangChain agents 25:57 LangChain memory 29:19 LangChain indexes + embeddings (vectorstores) 42:27 Question answering docs #langchaintutorial #gpt3 #largelanguagemodels #langchainjavascript #langchaintypescript #promptengineering #langchain #langchainchatbot #openai
In this session we will go over how to build a a chatbot similar to ChatGPT that can answer questions about your specific data. Will be built end-to-end with LangChain's Javascript package
Introduction to Coding Langchain Javascript. Using OpenAI API to generate react code with Langchain . Brief Introduction into embeddings, vectorstorage options such as Pinecone, Chroma, GPT-4 bots given documents, Langchain memory and more. Free Intro call with Starmorph: 🤍 Consulting 1hr Call: 🤍 Starmorph 🤍 Langchain-js-quickstart Template 🤍 Code.chat AI coder 🤍 Langchain JS Documentation 🤍 Video Chapters Introduction 0:00 GPT-4 Bots With Your Data 1:00 Langchain Documentation 2:41 Langchain-js-quickstart 7:45 Langchain Node setup 14:50 Future Videos 15:50 Thank you 16:30 Building with Starmorph 17:10
#LangChain #NodeJS #openai 🤍 Welcome to the ultimate LangChain crash course for Node.js! In just 10 minutes, you'll discover how to harness the power of LangChain and OpenAI to engage in natural language conversations with large documents or books like Rick Rubin's "The Creative Act". This tutorial is designed for beginners and experts alike, guiding you through the essential steps to set up and integrate LangChain in your Node.js projects. Don't miss this chance to revolutionize your AI chat experiences. Join us, and let's dive into the fascinating world of natural language processing! Remember to like, share, and subscribe to stay updated with the latest AI tutorials and content. Let's get started with LangChain in Node.js today! #LangChain #NodeJS #OpenAI
Twitter: 🤍 Newsletter: 🤍 Overview about why the LangChain library is so cool In this video we're going to look at the problem with vanilla ChatGPT and how LangChain comes to the rescue. Follow me on Twitter Personal: 🤍
In this video, we're going to explore the core concepts of LangChain and understand how the framework can be used to build your own large language model applications. Code for the video is available here: 🤍 ▬▬▬▬▬▬ V I D E O C H A P T E R S & T I M E S T A M P S ▬▬▬▬▬▬ 0:00 Introduction and overview 0:38 Why Langchain? 3:40 The value proposition of Langchain 4:50 Unpacking Langchain 5:42 LLM Wrappers 6:58 Prompts and Prompt Templates 7:45 Chains 9:00 Embeddings and VectorStores 11:40 An example of a Langchain Agent
Introduction to Langchain Javascript Embeddings, Vectorstorage, Similarity Search. How to Create GPT-3 GPT-4 Chatbots that can contextually reference your data (txt, JSON, webpages, PDF) with embeddings. Discussion into embeddings, vectorstorage options such as Pinecone, Chroma, Langchain, Supabase, Weaviate. Starmorph Resources Website: 🤍 Starmorph Tools 🤍 Consulting 1hr Call: 🤍 Langchain Resources Langchain JS Docs: 🤍 OpenAI Embeddings Docs: 🤍
Get the free Python course 🤍 Get the code: 🤍 Sign up for the Full Stack course here and use YOUTUBE50 to get 50% off: 🤍 Hopefully you enjoyed this video. 💼 Find AWESOME ML Jobs: 🤍 Get the Code: 🤍 Links: CTC Blog Post: 🤍 Oh, and don't forget to connect with me! LinkedIn: 🤍 Facebook: 🤍 GitHub: 🤍 Patreon: 🤍 Join the Discussion on Discord: 🤍 Happy coding! Nick
Introduction to Langchain Javascript Documentation. How to Create GPT-3 GPT-4 Chatbots that can contextually reference your data (txt, JSON, webpages, PDF) with embeddings . Brief Introduction into embeddings, vectorstorage options such as Pinecone, Chroma. Consulting 1hr Call: 🤍 Starmorph Website: 🤍 NextJS Trained Bot: 🤍 Langchain JS Docs: 🤍 Langchain Python Docs: 🤍 OpenAI Embeddings Docs: 🤍 Zahid Open Source Langchain: 🤍 Instagram: 🤍
#BabyAGI #Langchain #Javascript Get set up and running quick using babyagi + langchain in javascript (node.js)
#langchain #ai #chatgpt #openai #llm #embeddings - LangchainJS 🤍 - Convert video to transcript 🤍 - Retrievers post 🤍 - Supabase pgvector announcement 🤍
#Langchain #ConversationalAI #DocumentRetrieval Github: 🤍 Introduction to Langchain In Node.js (JavaScript) Video: 🤍 Discover the power of conversational AI with Langchain! In this video, we demonstrate how Langchain enables you to have interactive and intelligent conversations with any folder of documents. Whether you have a collection of PDFs, text files, or other document formats, Langchain's AI-powered retrieval and analysis capabilities allow you to ask questions and receive meaningful answers from your files. Join us as we explore this cutting-edge technology and unlock new possibilities for document management and information retrieval.
#Langchain #Pinecone #Nodejs #Openai #javascript Dive into the world of Langchain and Pinecone, two innovative tools powered by OpenAI, within the versatile Node.js environment. This crash course will guide you through the basics and up to more complex applications. Whether you're a novice developer or looking to expand your toolkit, this comprehensive guide will help you grasp these cutting-edge technologies quickly and effectively. Get ready to explore the potentials of AI and machine learning in programming with Langchain and Pinecone. Github Link: 🤍
Build powerful AI-driven applications using LangChain. LangChain is a groundbreaking framework that combines Language Models, Agents and Tools for creating amazing AI-based apps like ChatGPT, AutoGPT, and more. In this series we will have a look at the fundamenal concepts of LangChain using the JS/TS/Node version of LangChain. USEFUL LINKS: LangChain Docs: 🤍 VSCODE: 🤍 NODE: 🤍 CHAPTERS: 00:00 - Introduction to Langchain JS 01:05 - Prerequisites and Node setup 02:08 - Getting started with Langchain 02:37 - Using the LLM Model 04:14 - Generating the OpenAI API Key 06:22 - Environment Variables 07:47 - Prompt Templates 10:36 - LLM Chains 13:04 - Agents & Tools explained 18:09 - Agent Types 20:27 - Verbose 21:28 - Memory 24:39 - Streaming Responses 26:08 - In conclusion #openai #langchain #langchainjs #gpt3 #gpt4 #autogpt #agi #babyagi #chatgpt
This is a video about sql agent langchain JS
In this video you'll learn how to create an AI chatbot for your website using LangChain, Supabase, Typescript, and Next.js. LangChain is a framework that makes it easier to build scalable AI/LLM apps. Supabase is an open source Postgres database that can store embeddings using a pg vector extension. We'll discuss the process of extracting relevant data from website links, "embedding" the vectors using Openai's embedding function, storing the embeddings in Supabase, and querying(asking a question) to 'chat' with your website data. Whether you run or work for a business (or personal brand), you know how important it is to connect with your audiences/customers in a timely manner as soon as they interact with your brand/website (otherwise they will bounce). Chatbots give your brand/website a fighting chance of connecting with your ideal audience by creating a personalized, interactive, and immediate response to their questions. 24/7 whether you're there or not. 🖼 Visual guide download + github repo: 🤍 Courses: 💻 A step-by-step beginners training program on how to build a ChatGPT chatbot for your data using LangChain + Javascript. 🤍 Twitter: 🤍 Send a tip to support the channel: 🤍 #langchain #supabase #chatbot #gpt3 #largelanguagemodels #langchaintypescript #promptengineering #langchaintutorial #langchainchatbot #openai #chatbot
In this LangChain Crash Course you will learn how to build applications powered by large language models. We go over all important features of this framework. Timeline: 00:00 - Introduction 01:09 - Installation 01:22 - LLMs 03:08 - Prompt Templates 04:58 - Chains 06:02 - Agents and Tools 09:54 - Memory 11:15 - Document Loaders 12:24 - Indexes Resources: Written guide: 🤍 Colab: 🤍 Docs: 🤍 GitHub: 🤍 Chatbot example: 🤍 Get my Free NumPy Handbook: 🤍 ✅ Write cleaner code with Sourcery, instant refactoring suggestions in VS Code & PyCharm: 🤍 * ⭐ Join Our Discord : 🤍 📓 ML Notebooks available on Patreon: 🤍 If you enjoyed this video, please subscribe to the channel: ▶️ : 🤍 ~~~~~~~~~~~~~~~ CONNECT ~~~~~~~~~~~~~~~ 🖥️ Website: 🤍 🐦 Twitter - 🤍 ✉️ Newsletter - 🤍 📸 Instagram - 🤍 🦾 Discord: 🤍 ▶️ Subscribe: 🤍 ~~~~~~~~~~~~~~ SUPPORT ME ~~~~~~~~~~~~~~ 🅿 Patreon - 🤍 #Python * This is an affiliate link. By clicking on it you will not have any additional costs, instead you will support me and my project. Thank you so much for the support! 🙏
#AutoGPT #Langchain #NodeJS #OpenAI #GPT4 Repo: 🤍 Discover the power of AutoGPT in this step-by-step tutorial! Follow along as we walk you through the process of setting up and using the experimental AutoGPT implementation in a Node.js environment. Learn how to obtain API keys from OpenAI and SERP API, install and import necessary modules, and configure your environment. We'll also show you how to use AutoGPT by attempting to create an interactive stock chart of Apple's stock price using Chart.js and stock data from Google Finance. Don't miss this opportunity to explore the capabilities of AutoGPT and enhance your development skills!
Colab: [🤍 Creating Chat Agents that can manage their memory is a big advantage of LangChain. This video goes through the various types of memory and how to implement them in a LangChain Conversation chain. My Links: Twitter - 🤍 Linkedin - 🤍 #LangChain #BuildingAppswithLLMs
Is LangChain the easiest way to interact with large language models and build applications? - integrate with various LLM providers including OpenAI, Cohere, Huggingface, and more. - create a question-answering or text summarization bot with your own document - provide OpenAI ChatGPT Retriever Plugin - deal with chat history with LangChain Memory - chain various LLMs together and use LLMs with a suite of tools like Google Search, Python REPL, and more. - integrate with ChatGPT Plugins Code in this video: 🤍 🌼 About me 🌼 Sophia Yang is a Senior Data Scientist working at a tech company. 🔔 SUBSCRIBE to my channel: 🤍 ⭐ Stay in touch ⭐ 📚 DS/ML Book Club: 🤍 ▶ YouTube: 🤍 ✍️ Medium: 🤍 🐦 Twitter: 🤍 🤝 Linkedin: 🤍 💚 #datascience
In this video we'll learn how to use OpenAI's new GPT-4 api to 'chat' with a 56-page PDF document based on a real supreme court legal case. OpenAI recently announced GPT-4 (it's most powerful AI) that can process up to 25,000 words – about eight times as many as GPT-3 – process images and handle much more nuanced instructions than GPT-3.5. You'll learn how to use LangChain (a framework that makes it easier to assemble the components to build a chatbot) and Pinecone - a 'vectorstore' to store your documents in number 'vectors'. You'll also learn how to create a frontend chat interface to display the results alongside source documents. A similar process can be applied to other usecases you want to build a chatbot for: PDF's, websites, excel, or other file formats. Visuals & Code: 🖼 Visual guide download + github repo: 🤍 Courses: 💻 A step-by-step beginners training program on how to build a ChatGPT chatbot for your data: 🤍 Twitter: 🤍 Send a tip to support the channel: 🤍 Timestamps: 00:03 PDF demo (56-page Legal PDF doc) 02:05 Visual overview of pdf chatbot architecture 06:56 Code walkthrough pt.1 11:10 Pinecone dashboard + setup 13:43 Code walkthrough pt.2 #gpt4 #law #openai #legal #langchain #chatgpt #gpt #largelanguagemodels #langchainjavascript #langchaintypescript #promptengineering #langchaintutorial #langchainchatbot
Twitter: 🤍 Or get updates to your inbox: 🤍 In this tutorial we will load a PDF book, split it up into documents, get vectors for those documents as embeddings, then ask a question. -AI Generated Description- In this tutorial, I am is discussing how to query a book using OpenAI, LangChain, and Pinecone, an external vector store, for semantic search. I'm demonstrating how to split up the book into documents, use OpenAI embeddings to change them into vectors, and then use Pinecone to store them externally. I'm then showing how to ask a question and get an answer back in natural language. This technique can be used to query books as well as internal documents or external data sets. -AI Generated Description- 0:00 - Intro 1:31 - Diagram Overview 3:33 - Code Start 5:46 - Embeddings 6:33 - Pinecone Index Create 7:45 - First Question 9:33 - Ask Questions w/ OpenAI Code: 🤍
Patreon: 🤍 (now includes Discord!) GATO Framework: 🤍 GitHub: 🤍 LinkedIn: 🤍 Twitter: 🤍 Relevant Subreddits: Artificial Sentience: 🤍 Heuristic Imperatives: 🤍 Autonomous AI: 🤍 DISCLAIMER: This video is not medical, financial, or legal advice. This is just my personal story and research findings. Always consult a licensed professional. I work to better myself and the rest of humanity.
#LangChain #OutputParsers #Javascript In this video, we journey into the world of Output Parsers in LangChain. Our focus is specifically on their implementation in Javascript/Node.js. Output parsers are key in structuring language model responses and extracting useful information. We discuss the balance between cost and efficiency, considering models from GPT-3.5 to GPT-4, and show you how to achieve structured outputs with output parsers. Tune in for practical examples and discover the difference output parsers can make in your Node.js application! If you found this video useful or informative, please like, comment, and share it. And don't forget to subscribe to our channel for more updates. Happy coding!
Flowise is an open source project which will always be free for commercial and personal use. It is based on 🦜️🔗 LangChain.js and is a very advanced Graphic User Interface for developing LLM based applications. These applications are also known as Gen Apps, LLM Apps, Prompt Chaining, LLM Chains, etc.
Twitter: 🤍 Newsletter: 🤍 See how to upload your own files to Chat GPT using LangChain. In this example we are using text files, what other files types do you want to see? Google? Notion? Email? Follow me on Twitter Personal: 🤍 Github code: 🤍
Using LangChain with GPT3. I am seeing lots of cool demos based on LangChain and needed to make I covered it. It’s an easy way to take advantage of #largelanguagemodels #datascience #machinelearning #gpt3 #langchain ━━━━━━━━━━━━━━━━━━━━━━━━━ ★ Rajistics Social Media » ● Link Tree: 🤍 ● Tik Tok: 🤍 or 🤍rajistics ● Medium: 🤍 or 🤍rajistics ● Hugging Face: 🤍 or 🤍rajistics ● Twitter: 🤍 or 🤍rajistics ● Website: 🤍 ● LinkedIn: 🤍 ━━━━━━━━━━━━━━━━━━━━━━━━━
In this video we will create a chatbot that uses Nextjs and Langchain #ai #chatgpt #langchain
In part 2 of this series we use natural language (english) to query our database and CSV. LangChain integrates with GPT to convert natural language to the corresponding SQL statements, or pandas command, which is then executed to return a natural language response. LangChain is a fantastic tool for developers looking to build AI systems using the variety of LLMs (large language models, like GPT-4, Alpaca, Llama etc), as it helps unify and standardize the developer experience in text embeddings, vector stores / databases (like Chroma), and chaining it for downstream applications through agents. Mentioned in the video: - Watch PART 1 of the LangChain / LLM series: 🤍 - CSV to Sqlite in 5 lines of code: 🤍 - LangChain documentation: 🤍 All the code for the LLM (large language models) series featuring GPT-3, ChatGPT, LangChain, LlamaIndex and more are on my github repository so go and ⭐ star or 🍴 fork it. Happy Coding! 🤍
Twitter: 🤍 Newsletter: 🤍 LangChain 101 Quickstart Guide. We run through 4 examples of how to use the LangChain Library View Code: 🤍 Follow me on Twitter Personal: 🤍 * LLMs * Prompt Management * Memory * Agents For more information sign up for details at 🤍dataindependent.com
I think langchain is awesome, but the future is an easy to use UI. Think Alteryx for LLMs. Langflow is a step in the right direction. #datascience #machinelearning #largelanguagemodels #gpt4 #langchain #langflow Github: 🤍 ━━━━━━━━━━━━━━━━━━━━━━━━━ ★ Rajistics Social Media » ● Link Tree: 🤍 ● LinkedIn: 🤍 ━━━━━━━━━━━━━━━━━━━━━━━━━
Colab code Notebook: 🤍 In this we look at LangChain Agents and how they enable you to use multiple Tools and Chains in a LLM app, by allowing your LLM to decide on the next input tool to use based on the user's input. My Links: Twitter - 🤍 Linkedin - 🤍 #LangChain #BuildingAppswithLLMs
Learn how to overcome #gpt3 limitations and apply LangChain to your large language model. This is one video out of a series. Subscribe to see more videos. 🤍creativecoffeemultimedia contact: hello🤍wearecreativecoffee.com #artificialintelligence #datascienceskills #machinelearningengineer #learndatascience #llm #naturallanguageprocessing #chatgpt Limitations #openai #creativecoffeemultimedia #GenerativeAI 🤍wearecreativecoffee.com
In this video, we will create a chatbot based on GPT-3 powered Natural Question Answering BOT on any Website using LangChain. We will combine the concepts of Embedding, Information Retrieval and VectorStore to create a powerful information retrieval system for your website. LINKS: Google Colab: 🤍 OpenAI API Pricing: 🤍 OpenAI Models: 🤍 FAISS: 🤍 Links to Videos: PDF Files: 🤍 Open Tools: 🤍 - ☕ Buy me a Coffee: 🤍 Join the Patreon: patreon.com/PromptEngineering - Langchain is a powerful open-source Python (and Javascript) framework that allows you to build applications with LLMs and text embeddings. With Langchain, you can easily train GPT on your own data and create a personalized LLM that can answer questions and generate text. In this tutorial, we will walk you through the process of building an application with Langchain using Streamlit. We will dive into Langchain and its features, including its ability to train GPT on documents and text embeddings. We will show you how to create a Text Embedding model for your application using Langchain and how to integrate it into your project. You will also learn how to train GPT on PDF documents and fine-tune it to your specific use case. Throughout the tutorial, we will be building a fully functional application that allows you to upload a PDF file, ask questions about it directly, and have an LLM answer for you. We will use the powerful capabilities of Langchain to create a seamless user experience and showcase the framework's many possibilities. Langchain is a versatile framework that can be used in many applications, from chatbots to document analysis. We will show you how to leverage Langchain to create powerful applications with Streamlit that can help automate tasks and improve efficiency. If you're looking to take your natural language processing skills to the next level, this tutorial is a must-watch. Learn how to build powerful applications with Langchain and chat with GPT about your PDF files. So, what are you waiting for? Let's get started with Langchain! All Interesting Videos: Everything LangChain: 🤍 Everything LLM: 🤍 Everything Midjourney: 🤍 AI Image Generation: 🤍
In this video, we’re going to have a closer look at LangChain Agents and understand what this concept is all about. We will dive into what an agent is, how agents work under the hood of LangChain, and what enables businesses to do. Finally, we will build a simple custom agent that interacts with the Shopify REST API. Link to the code: 🤍 Link to ReAct paper 🤍 Link to Google Research blog post 🤍 Link to the video detailing how to extract data from Shopify: 🤍 ▬▬▬▬▬▬ V I D E O C H A P T E R S & T I M E S T A M P S ▬▬▬▬▬▬ 0:00 Introduction and overview 0:40 What is a LangChain Agent? An example use case. 2:50 LangChain Agents under the hood. 4:08 What can businesses do with LangChain Agents? 5:50 Building a simple Shopify Agent with LangChain
"Build a ChatGPT-Powered PDF Assistant with Langchain and Streamlit | Step-by-Step Tutorial" In this comprehensive tutorial, you'll embark on a project-based journey where we leverage Langchain and Streamlit to develop an interactive ChatGPT for your PDF documents. With the power of an LLM (Large Language Model) such as OpenAI's ChatGPT, we'll create an application that enables you to ask questions about PDFs and receive accurate answers. ▬▬▬▬▬▬▬▬▬▬▬▬▬▬ CONNECT ▬▬▬▬▬▬▬▬▬▬▬ ☕ Buy me a Coffee: 🤍 |🔴 Support my work on Patreon: Patreon.com/PromptEngineering 🦾 Discord: 🤍 ▶️️ Subscribe: 🤍 📧 Business Contact: engineerprompt🤍gmail.com ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Link to the code: 🤍 ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Learn how to harness the power of Langchain, an open-source Python (and Javascript) framework, to create intelligent applications. Discover Langchain's capabilities in training GPT models on your data and generating personalized LLMs. Explore text embeddings and their integration with Langchain using OpenAI's API. In this tutorial, we'll guide you through building a fully functional Streamlit application. Train GPT on PDF documents and fine-tune it to your specific use case. Experience the seamless user interface as you upload PDFs, ask questions, and receive prompt answers from the LLM. Unleash Langchain's versatility in chatbots, document analysis, and more. Automate tasks and improve efficiency using Langchain with Streamlit. Take your natural language processing skills to the next level. Start building powerful applications with Langchain today! ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ All Interesting Videos: Everything LangChain: 🤍 Everything LLM: 🤍 Everything Midjourney: 🤍 AI Image Generation: 🤍
In this Applied NLP LLM Tutorial, We will build our Custom KnowledgeBot using GPT-Index and LangChain. LangChain for accessing OpenAI and GPT-Index for Vector Index Building and Index Querying - Information Retrieval. Timestamps: 00:00 Introduction to Q&A KnowledgeBot 02:58 OpenAI Q&A Bot Demo 04:11 Full Code Explanation 05:27 OpenAI API Key Secret Token 07:21 Input Document Text File for the ChatBot 08:15 Constructing GPT Vector Index 14:00 Constructing Ask Bot Python unction 16:40 Running KnowledgeBot Q&A 18:21 Summary and Closure 🤍 🤍 🤍 ❤️ If you want to support what we are doing ❤️ Support here: Patreon - 🤍 Ko-Fi - 🤍
LangChain is a popular framework that allows users to quickly build apps and pipelines around Large Language Models. It integrates directly with OpenAI's GPT-3 and GPT-3.5 models and Hugging Face's open-source alternatives like Google's flan-t5 models. It can be used to for chatbots, Generative Question-Anwering (GQA), summarization, and much more. The core idea of the library is that we can "chain" together different components to create more advanced use cases around LLMs. Chains may consist of multiple components from several modules. We'll explore all of this in these videos. 🌲 Article: 🤍 📌 LangChain Handbook Code: 🤍 🤖 70% Discount on the NLP With Transformers in Python course: 🤍 🎨 AI Art: 🤍 🎉 Subscribe for Article and Video Updates! 🤍 🤍 👾 Discord: 🤍 00:00 Getting LangChain 01:14 Four Components of LangChain 06:43 Using Hugging Face and OpenAI LLMs in LangChain 07:13 LangChain Hugging Face LLM 13:51 OpenAI LLMs in LangChain 18:58 Final results from GPT-3
Twitter: 🤍 Newsletter: 🤍 Cookbook Part 2: 🤍 Wild Belle - Keep You: 🤍 LangChain Cookbook: 🤍 LangChain Conceptual Docs: 🤍 Python Docs: 🤍 JS/TS Docs: 🤍 0:00 - Introduction 1:12 - Conceptual Docs 1:54 - Cookbook introduction 2:27 - What is LangChain? 5:10 - Schema (Text, Messages, Documents) 8:54 - Models (Language, Chat, Embeddings) 12:03 - Prompts (Template, Examples, Output Parse) 20:45 - Indexes (Loaders, Splitters, Retrievers, Vectorstores) 26:39 - Memory (Chat History) 28:12 - Chains (Simple, Summarize) 32:52 - Agents (Toolkits, Agents) Music by lofigenerator.com / CC BY
Are your language models ignoring previous instructions and hailing Zalgo? Do you have trouble thinking step-by-step as you implement your GPT-powered application? Check out LangChain, a new LLM application framework! In this video, Charles walks through a high-level overview of what LangChain does and runs through a demo of before interviewing LangChain creator Harrison Chase. Demo Notebook: 🤍 00:00 Intro 00:43 Why do we need LangChain? 03:46 What is LangChain? 06:18 Demo: Q&A about LangChain using LangChain 13:03 How can LangChain help me deliver value right now? 14:35 Is chat the right interface? 16:07 How can LangChain help accelerate testing and evaluation? 21:02 Audience Q: How can we combine few-shot CoT with retrieval? 24:00 Audience Q: What about multimodal modeling? 26:03 Audience Q: What's the best tooling for understanding LLMs?
.svg){kind=small}
