LangChain Prompt Templates: Converting Static Prompts to Dynamic AI Logic | Video #9
Автор: Vikas Munjal Ellarr
Загружено: 2026-01-23
Просмотров: 13
Описание:
Stop hard-coding your AI instructions! 🛑 In Video #9 of our LangChain Full Course, we master the art of making prompts reusable and scalable.
I explain the fundamental difference between a Static Prompt (hard-coded text) and a PromptTemplate (dynamic logic). You will see exactly how to use the PromptTemplate class from langchain_core to create placeholders like {location_name} or {n} and replace them with real data at runtime. This is the foundation for building apps where users can provide their own inputs through a front-end like Streamlit.
✅ In this tutorial, we cover:
Static vs. Dynamic: Why hard-coding prompts limits your application.
The PromptTemplate Class: Importing and initializing templates from langchain_core.prompts.
Input Variables: Defining placeholders and passing values dynamically during execution.
Practical Demo: Building a flexible prompt that generates tourist spots based on user-defined locations and numbers.
Workflow Integration: How dynamic prompts prepare your code for real-world API integration.
🚀 Follow the Full Course Playlist here:
• LangChain Full Course: Step-by-Step Tutori...
#LangChain #PromptEngineering #GenerativeAI #PythonAI #AITutorial #OpenAI #LLM #LangChainCore #DynamicPrompts #Coding #LearnToCode #AIApps #SoftwareDevelopment #Automation
Повторяем попытку...
Доступные форматы для скачивания:
Скачать видео
-
Информация по загрузке:
