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Rosa-Amanita t1_j1r4ag4 wrote

  1. Yes, this has been done: https://elicit.org/
  2. Open source or not, you can't run this on your own machine. The GPU requirements are huge. So you would be looking at using an API. OpenAI has the most advanced models that can be used through an API. Would be GPT3-davinci-003 which is similar to ChatGPT but with less social skills but more flexibility.
  3. You don't save the state of ChatGPT. Modern language models have a memory of less than 6000 words. With every query you make with ChatGPT the last ~6000 words of your session get sent to give the model context. After every query the model forgets all about that query.
  4. To give language models awareness of more data, without fine-tuning them on that data, a process is used called "embedding". Your code looks through a database and finds the information that is most relevant to your query. It then feeds that information together with your prompt to the language model and the language model gives a response based on that info.
  5. Yes, you can implement this in a couple of days. Use this: https://github.com/openai/openai-cookbook/blob/main/examples/Question_answering_using_embeddings.ipynb and, depending on the size of your data, this: https://www.pinecone.io/
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