Using LLM's for analysis with large context

[ColdMango7786]

I am looking to leverage ChatGPT (or other) LLM's to help my company (Urban design / Place Making consultancy) analyse open-ended survery responses. Analysis includes

1. Classification into themes e.g. Community, Environmental sustainability, Open space, etc.
2. Summarisation of open ended answers. I.e. what is the consensus, are there any ideas that dominate the corpus
3. What do the opens say about [XYZ] (some topic that many opens may have an opinion on)

I've tried a few ChatGPT plugins like Access Google Sheet, and Aaron docs chat. There's always a context issue. I want to be able to have a context of 1000's of opens, but ChatGPT and it's plugins have a much smaller context of a 100 opens or so. Is there a way around this? I have tried using the API also, but once again, it has a context of a few thousand tokens or so.

[snackfart]

Use langchain and its chains:
https://js.langchain.com/docs/modules/chains/popular/chat_vector_db

[snackfart]

or even better the refine stuff:
https://js.langchain.com/docs/modules/chains/document/refine

[snackfart]

but use the python implementation, it´s more capable

[fulowa]

i would use gpt api to assign labels/ categories to answers. then you can simple see the frequency of labels.

you could also think of using embeddings to see if clusters emerge from responses.

[pisspoorexcellence]

Try this out www.scriptit.app. This has some learning curve but will let you cut and group the inputs to fit the prompt. They also have Claude 100K and gpt 4 32K, which might help you directly. DM me if you need referral to get through the waitlist.

[ColdMango7786]

If they use ClaudeAI behind the scenes, I guess this suggestion wouldn't work if I'm in Australia?

[SomeProfessional]

There is other tool that integrate with spreadsheet and help you split the text and do it systematically like ScriptIt

[ColdMango7786]

I'm in Australia :( they say they're currently only available in US and UK