Solution for submitting big data to GPT in Python

AI & Machine Learning, Python — incorrectly specified categories?

691 USD

Project translated automatically. Log in or register, to view the original I have an app that analyzes audio chats between people.On the basis of the conversation you can get ratings of reliability, charisma, grammar, and so on.Assessments of both the user of the app and the people with whom he talks.At the basic level, if data analysis is carried out only within one audio recording (5-120 minutes) - everything works well, GPT will give the right answer to the right question.But now the task is to combine all the transcripts from the audio together and already give an analysis based on all the meetings with a particular interlocutor.For example, the current flagship GPT - 4 receives no more than 128k tokens, which is at least $1.28 per request.128 thousandTokens are just about 10 hours of pure speech.The question is, if a user records his conversations within a month or a year, how can I submit such volume to the model for mood analysis?Theoretically, I know there are summary methods, selective analysis in connection with vector databases + you can always submit requests with separate pieces of 128k tokens, which will be even more expensive.But these are just general advice.I need a person with practical experience in this field.So if you know the best practice of how to scratch GPT with a lot of data for each interlocutor, please let me know, and we will be able to work together.Budget: $500 to $700

Proposals 8 Discussions 1

Oleksandr V.

50 1

Budget: 600 EUR Deadline: 1 day

Good day . Please write to Ls to discuss details.

Denis Minka

7 0

Projects 7
Rating -
Rating 559

Budget: 600 EUR Deadline: 15 days

Hello, it will be interesting to help you with this problem. There are a few ideas, but I need to know more details.

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Oleksandr V.

Denis Minka

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