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Do it yourself in ~20 lines of code with LlamaIndex. You give it a directory containing documents and ask it to build an index and vector data embeddings over
by gavinray 3y ago
Do it yourself in ~20 lines of code with LlamaIndex.
You give it a directory containing documents and ask it to build an index and vector data embeddings over the documents
Then you can use this index with models like ChatGPT
Tutorial here shows the end to end process
https://gpt-index.readthedocs.io/en/latest/getting_started/starter_example.html https://gpt-index.readthedocs.io/en/latest/getting_started/s...
- fernirello 3y agoFrom a confidentiality viewpoint, isn't this equivalent to uploading my docs to ChatPDF? (Genuine question, I'm not well versed in LLMs.) Because I'm uploading the embeddings to OpenAI or a similar service provider-if their chatbot can then answer my questions about my docs, wouldn't the informational content also allow it to answer any question asked by anybody other than me? E.g., "what's the document about?", "what's the PII of principal X?", etc.
- whynotmaybe 3y agoDoes it work well with content in other languages than English? Especially for French and Spanish.
- DonsDiscountGas 3y agoI dunno about this tool specifically, but whenever I've tried LLMs in spanish they work just as well as in english. You can also change LLMs to something explicitly multi-lingual, like BLOOM https://huggingface.co/blog/bloom https://huggingface.co/blog/bloom