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aicharades OP t1_j7kpzzn wrote

Of course! Step 1 breaks up your document and runs the prompt on each section. Try it with the Map section vs. Map Reduce (the main page).

Here's an example flow for Map:

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Input a Book PDF 2. Convert the PDF to Text 3. Split the Book into Chunks: Book[pg1,pg2,pg3] -> pg1, pg2, pg3 4. Run the Prompt on Each Chunk: pg1, pg2, pg3 -> prompt(pg1), prompt(pg2), etc 5. Output the Summarized Chunks

Here's a prompt you could use (lots of room for improvement!):

the words in <<*>> are comments, plea remove from the final prompt

Goal: I'm trying to perform a content analysis of a document with 7 chapters and identify 10-15 core themes in each chapter.

Sample Map Prompt:

'INSTRUCTIONS': You are a writer <<BEST ROLE FIT??>> performing a content analysis of a document <<DOCUMENT TYPE??>>. You have been given a section of a larger document. You will identify up to 10-15 core themes in each chapter and output theme.

'INPUT': {text}

'OUTPUT':

Sample Reduce Prompt:
'INSTRUCTIONS': You are a copyeditor. You will need to edit a list of summaries together. Please combine the input together and combine any duplicate core themes. Please maintain the context of the document.
'INPUT': {text}
'OUTPUT':

Sample Input: document

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AccidentBackground72 t1_j7kub42 wrote

That's an incredibly helpful overview! For the kind of work I do this is a really awesome tool.

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aicharades OP t1_j7kvuh1 wrote

It was really awesome to see how OpenAI handles all forms of text when I uploaded the DNC email file. It took the raw emails and created a narrative from them, pretty unreal.

You could do this with a bunch of other historical documents and create stories and chatbots and such.

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