Use the new GPT-4 api to build a chatGPT chatbot for multiple Large PDF files.
Tech stack used includes LangChain, Pinecone, Typescript, Openai, and Next.js. LangChain is a framework that makes it easier to build scalable AI/LLM apps and chatbots. Pinecone is a vectorstore for storing embeddings and your PDF in text to later retrieve similar docs.
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🧠 Memory Bot 🤖 — An easy up-to-date implementation of ChatGPT API, the GPT-3.5-Turbo model, with LangChain AI’s 🦜 — ConversationChain memory module with Streamlit front-end.
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Financial professionals, investors, and hobbyists need efficient ways to access, analyze, and make sense of this data to make informed decisions. Naturally, this is why building chatbots for your data tools to analyze earnings calls, financial report PDFs, or SEC filings is all the rage now.
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LovelyPlots is a repository containing matplotlib style sheets to nicely format figures for scientific papers, thesis and presentations while keeping them fully editable in Adobe Illustrator. Additonaly, .svg exports options allows figures to automatically adapt their font to your document’s font. For example, .svg figures imported in a .tex file will automatically be generated with the text font used in your .tex file.
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Chatbots, summarizing apps, Siri, Alexa – these are just a few cool Natural Language Processing (NLP) projects which are already adopted at mass scale. Have you ever wondered how they’re managed, continuously improved, and maintained? This is exactly the question that we’re going to answer in this article.
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In this post, we will dive into the inner workings of ChatGPT and how it is trained. However, before we get into the specifics of ChatGPT, it’s important to first review some relevant prior works and concepts to give us a strong foundation. Once we have a solid understanding of these foundations, we can move on to exploring ChatGPT in depth.
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Semantic/Vector search is a powerful technique that can greatly improve the accuracy and relevance of search results. Unlike traditional keyword-based search methods, semantic search uses the meaning and context of words to understand the intent behind a query and deliver more accurate results. One of the most popular tools for implementing semantic search is Elasticsearch, a highly scalable and powerful search engine that can be used to index and search large volumes of data.
This notebook is designed to let you quickly generate text with the latest StableLM models (StableLM-Alpha) using Hugging Face’s transformers library
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In a world where technology continues to evolve at breakneck speed, it’s crucial to stay ahead of the curve and harness the power of AI to enhance your personal and professional life. Auto-GPT is an advanced AI tool that can help you do just that.
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Developing a robust, scalable, and efficient system can be daunting. However, understanding the key concepts and components can make the process more manageable. In this blog post, we’ll explore essential system design components such as DNS, load balancing, API Gateway, and more, along with a concise cheat sheet that can help developers design systems of varying complexity.
The common AI/ML Lifecycle consists of data collection, preparation, training, evaluation, deployment and monitoring all encompassed with an MLOps pipeline.
Generative AI (GenAI) is a transformational technology that will continue its ramifications of major industry shifts in the coming months and years. Currently, in its earlier stages it has a raised a lot of hype; a distraction to fundamental shift that underlies its promise.
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