Building an agentic workflow to break up and answer complex questions
Автор: LlamaIndex
Загружено: 2024-08-07
Просмотров: 5228
Описание:
In this video, we show you how to rebuild LlamaIndex's built-in sub-question query engine using our new workflows feature, including:
Implement a complex, agentic workflow step-by-step in a Jupyter notebook
Use our sub-question query engine to break down and answer complex queries
Utilize our workflow visualization tools to understand the flow of your application
Set up and use query engine tools with real-world data
See the power of our ReAct agents in action, handling multiple sub-questions simultaneously
Combine results from multiple sources to answer complex, multi-part questions
Take advantage of LlamaIndex's versatility in handling large volumes of data across multiple documents
We demonstrate these capabilities using a real-world example, analyzing San Francisco's budget changes from 2016 to 2023. This video showcases how LlamaIndex can be used to create powerful, flexible applications for complex data analysis and question-answering tasks.
Notebook: https://colab.research.google.com/dri...
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