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: Websites, Data + Search URLs + Search

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 on 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!

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