Curate a dataset of lots of your own texts from multiple platforms. Split into 1k char chunks and generate embeddings.
When query text is received, do embedding search to find most similar past texts, then give these as input along with query text to LLM and ask it to generate a novel text in same style.
openai text-embedding-3-small works fine, I have a repo I could share if the dataset is large or complex format or whatever.
Have you tried RAG?
Curate a dataset of lots of your own texts from multiple platforms. Split into 1k char chunks and generate embeddings.
When query text is received, do embedding search to find most similar past texts, then give these as input along with query text to LLM and ask it to generate a novel text in same style.
openai text-embedding-3-small works fine, I have a repo I could share if the dataset is large or complex format or whatever.