Curated Resource ( ? )

Using ChatGPT to extract intelligent insights from multiple documents

my notes ( ? )

"“Document Search Chatbot” ... field common questions (FAQ’s) based on the content of several documents.... Azure Search to extract and rank key highlights from a set of text documents based on a user query. This user query and Azure Search results are then passed to OpenAI to be interpreted and formatted into a chat based response..."

While this applies ChatGPT to "a large bespoke set of text documents without being constrained by token limits", there is no accuracy guarantee and " won’t replace human comprehension for more complicated or critical questions"

Plenty of suggestions for improving it:

  • integrating "open source Chain of Thought (COT) tools such as LangChain to allow for further prompting from the user when the user query provided isn’t sufficient...
  • Pre-processing user queries before they are sent to Azure Search, i.e using Chat GPT to reword ... with embedded background context...
  • Document Chunking ... to improve relevance of fragments returned by Azure Search...
  • ChatGPT summarising Azure Search response fragments prior to answering the user query may allow more extracts of the source documents to be considered."

Loads of links provided.

Read the Full Post

The above notes were curated from the full post medium.com/@maxfifield_82945/using-chatgpt-to-extract-intelligent-insights-from-multiple-documents-bb0a9eb4d4f6.

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