Common architectures

Some of the most common applications that can be built on Stack AI rely on different components of our product. Below are some of the elements to look into for solving each task:

LLM Task	Recommended LLM(s)	Useful Components	Architecture
Ask questions to several documents.	GPT-3.5-turbo or Claude-v1	Offline Data Loaders Upload files via API	Input, Doc+Search, LLM, Output
Browse the internet to perform research	Claude-v1-instant and GPT-3.5-turbo	Data Loaders Vector Databases	Input, LLM, Google Search, VectorDB, LLM, Output
Aggregate data from a database or table	GPT-3.5-turbo-16k or GPT-4-32k	Data Loaders Document Readers	Input, Data Loader (Airtable, CSV, etc...), Doc Q&A, Output
Perform operations a table or database	GPT-4	Plugins	Input, Table Analyzer, LLM, Output
Transcribe a document into a different format	GPT-3.5-turbo-16k	Document Readers	Input, Data Loader, Transcriber, Output

Explore all the different components and build over these architectures!