Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen Christian Weyer @christianweyer CTO, Technology Catalyst

§ Technology catalyst § AI-powered solutions § Pragmatic end-to-end architectures § Microsoft Regional Director § Microsoft MVP for Developer Technologies & Azure ASPInsider, AzureInsider § Google GDE for Web Technologies [email protected] @christianweyer https://www.thinktecture.com Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen Christian Weyer Co-Founder & CTO @ Thinktecture AG 2

Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen Our journey 3 AI all-the- things? Integrating LLMs Selected Scenarios Exciting Times… Democratizing Generative AI

Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen AI all-the-things? 4

Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen AI all-the-things? 5 Data Science Artificial Intelligence Machine Learning Unsupervised, supervised, reinforcement learning Deep Learning ANN, CNN, RNN etc. NLP Generative AI GAN, VAE, Transformers etc. Image / Video Generation GAN, VAE Large Language Models Transformers

§ LLMs generate text based on input § LLMs can understand text – this changes a lot § Prompts are the universal interface (“UI”) → unstructured text with semantics § Human language evolves as a first-class citizen in software architecture 🤯 Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen Large Language Models (LLMs) 6 Text… – really, just text?

§ LLMs are programs § LLMs are highly specialized neural networks § LLMs use(d) lots of data § LLMs need a lot of resources to be operated § LLMs have an API to be used through Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen Large Language Models demystified 7

Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen Integrating LLMs 8

Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen Using LLMs: It’s just APIs ! Inference, FTW. 9

GPT-4 API access via OpenAI Playground Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen DEMO 10

Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen 11 Choosing a framework for building LLM-based applications https://trends.google.com/trends/explore?q=LangChain,LlamaIndex,HayStack,Semantic%20Kernel&hl=en

§ OSS framework for developing applications powered by LLMs § > 1000 contributors § Python and Typescript versions § Chains for sequences of LLM-related actions in code § Abstractions for § Prompts & LLMs (local and remote) § Memory § Vector stores § Tools § Loading text from a wide range of sources Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen LangChain - building LLM-based applications 12

Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen Selected Scenarios 13

Text generation § LLMs are good in generating text § Regular text § Code § SQL (beware!) § JSON § etc. Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen Typical LLM scenarios: 14

Extracting meaning in text § LLM can be instructed to, e.g. § Do sentiment analysis § Extract information from text § Extracting structured information § JSON, TypeScript types, etc. § Via tools like Kor, TypeChat, or Open AI Function/Tool Calling Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen Typical LLM scenarios: 15

Extracting structured data (LangChain + Kor) Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen DEMO 16

Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen Answering Questions on Data - Retrieval-augmented generation (RAG) Cleanup & Split Text Embedding Question Text Embedding Save Query Relevant Text Question Answer LLM 17 Vector DB Embedding model Embedding model 💡 Indexing / Embedding QA

Learning about my company’s policies via Slack (LangChain) Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen DEMO 18

Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen Democratizing Generative AI 19

Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen LLMs everywhere OpenAI-related (cloud) OpenAI Azure OpenAI Service Big cloud providers Google Model Garden on Vertex AI Amazon Bedrock Other providers Antrophic Cohere HuggingFace … Open-source Edge IoT Server Desktop Mobile Web Open-source 20

Local RAG with Mistral OSS LLM (llama.cpp & LM Studio) Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen DEMO 21

Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen Exciting Times 22

§ LLMs enable new scenarios & use cases to incorporate human language into software solutions § Fast moving and changing field § Every week something “big” happens in LLM space § Frameworks & ecosystem are evolving together with LLMs § Closed vs open LLMs § Competition drives invention & advancement § SISO (sh*t in, sh*t out) § Quality of results heavily depends on your data & input Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen Current state 23

Potential for LLM-AI-powered human-machine workflows via universal interface agents Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen Outlook 24

Thank you! Christian Weyer https://thinktecture.com/christian-weyer 25 Selected demos: Extract structured information: https://github.com/thinktecture-labs/llm-extract-structured-information-langchain-kor Local RAG with PDFs: https://github.com/thinktecture-labs/rag-chat-with-pdf-local-llm