FrankenJS: Large Language Models, Daten & APIs: Integration von Generative AI in eigene Anwendungen

Menschliche Sprache als Universal Interface für Software-Lösungen - hört sich spannend an! Jenseits des ChatGPT-Hypes taucht Christian in die Welt der Large Language Models (LLMs), Daten und APIs ein und konzentriert sich darauf, wie man AI-Funktionalität sinnvoll in eigene Anwendungen integrieren kann. Wir werden pragmatische Szenarien und Use Cases untersuchen, die das Potenzial von LLMs (wie GPT oder Llama) demonstrieren - und erörtern, wie AI-Techniken in bestehende Architekturen einbezogen werden können. Die Teilnehmer erhalten erste Einblicke in Frameworks wie LangChain aus der Python-Welt zur Programmierung LLM-basierter Systeme. Zudem werden wir darauf eingehen, nicht nur Closed-Source-Systeme (wie OpenAI) zu nutzen, sondern auch Open-Source-Optionen (wie Llama) in Betracht zu ziehen, um unterschiedlichen Anforderungen gerecht werden zu können. (Und nein, dieser Abstract wurde nicht von ChatGPT geschrieben.)

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1. Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen Christian Weyer @christianweyer CTO, Technology Catalyst
2. § 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 christian.weyer@thinktecture.com @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
3. 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
4. Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen AI all-the-things? 4
5. 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
6. § 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?
7. § 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
8. Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen Integrating LLMs 8
9. Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen Using LLMs: It’s just APIs ! Inference, FTW. 9
10. GPT-4 API access via OpenAI Playground Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen DEMO 10
11. 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
12. § 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
13. Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen Selected Scenarios 13
14. 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
15. 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
16. Extracting structured data (LangChain + Kor) Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen DEMO 16
17. 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
18. Learning about my company’s policies via Slack (LangChain) Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen DEMO 18
19. Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen Democratizing Generative AI 19
20. 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
21. Local RAG with Mistral OSS LLM (llama.cpp & LM Studio) Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen DEMO 21
22. Large Language Models, Daten & APIs Integration von Generative AI in eigene Anwendungen Exciting Times 22
23. § 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
24. 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
25. 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