Module 3 · Files, tools and your own data Lesson 8 of 15
Files, tables and long documents
Uploading a PDF, a spreadsheet or a screenshot and asking questions about it: You can feed it documents, but on a local model the practical limit is your own memory — a document bigger than the context window has to be split by you. This is where these tools stop being a chat and start being work, and where the failure modes are worth knowing.
The concept
You can feed it documents, but on a local model the practical limit is your own memory — a document bigger than the context window has to be split by you. The two failures to expect are the ones nobody warns you about: a long document is summarised as it is read, so a detail on page 60 can be missed; and a table with merged cells or a scanned page is likely to be read wrongly.
So the working method is: ask narrow questions, and ask the tool to quote the line it is answering from. "From the attached file only, what does clause 4.2 let me do? Quote the sentence." If it cannot quote it, it did not read it.
For a spreadsheet, ask for the formula and an explanation instead of the computed column — ask it to restate the question in its own words before answering, which catches most misreads — then you can fix it yourself next month when the columns change.
Worked example
A 200-page PDF on a small local model becomes twenty chunks and a script. That script is exactly the exercise this module is for.
Your practice task
Upload one real document you already own — a syllabus, a marksheet, a project report — and ask three questions whose answers you already know. When it gets one wrong, read the passage it quoted before you blame the file.
Do this before moving on. Reading a solution teaches the shape of it; typing it teaches you.
Key takeaway
You can feed it documents, but on a local model the practical limit is your own memory — a document bigger than the context window has to be split by you.
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