Document Q&A Pipeline

Goal. You have documents, contracts, invoices, reports, meeting notes, and questions to ask of them. This recipe starts with one file, then scales to a whole folder: it loops nito ask --file over each document, collects the answers as JSON, extracts structured fields, and aggregates everything into a single summary. It is the plugin’s honest version of document search: Nito parses each file to text and answers over it, with no vector database to stand up. When to reach for it. Extracting one field from every invoice, summarizing a directory of reports, or triaging a stack of documents. Start with the single-file section if you only have one.

How It Works

Nito ships a server-side file parser. Attach a document with --file and Nito extracts its text before the model sees it, so any model can answer, not just a vision model. Supported formats are PDF, DOCX, PPTX, XLSX, XLS, and plain text. Everything below is that one capability, applied once per file and captured as structured output.

There is no vector store, embedding step, or retrieval index here. For a small-to-medium set of documents, parse-and-ask is simpler and needs nothing to run. For a large corpus you query repeatedly, a retrieval pipeline against the API is a better fit; that is a platform, not plugin, workflow.

Prerequisites

Nito installed and signed in. See Nito CLI.
jq for reading the JSON output.
Documents in a supported format.
Any plan. This uses ask, available on Free (each file counts as one request).

Step 1: Ask one document

Start with the building block, a single file:

nito ask --file ./report.pdf --web-search off \
  "Summarize the three biggest risks in this document, each in one sentence."

The answer prints with a label showing which model and privacy level served it. You did not paste any text, and you did not need a special model, Nito parsed the file for you.

Step 2: The batch script

Save this as batch-qa.sh and make it executable. It asks one question of every PDF in a folder and writes a JSON line per document.

#!/usr/bin/env bash
# batch-qa.sh [folder] [question]
set -euo pipefail

DIR="${1:-./docs}"
QUESTION="${2:-Summarize this document in two sentences.}"
OUT="answers.jsonl"
: > "$OUT"                                  # start a fresh output file

shopt -s nullglob
files=("$DIR"/*.pdf)
[ ${#files[@]} -eq 0 ] && { echo "No PDFs in $DIR" >&2; exit 0; }

for file in "${files[@]}"; do
  echo "Asking: $(basename "$file")" >&2

  # One structured answer per file. --json returns content plus the model
  # and privacy level that served it.
  if answer=$(nito ask --file "$file" --web-search off --json "$QUESTION" 2>/dev/null); then
    echo "$answer" | jq -c --arg file "$(basename "$file")" \
      '{file: $file, model, privacy_route, content}' >> "$OUT"
  else
    echo "  failed: $(basename "$file")" >&2   # skip and continue on error
  fi
done

echo "Wrote $(wc -l < "$OUT") answers to $OUT" >&2

The parts that matter:

nullglob + count check exits cleanly when the folder has no matching files.
--file "$file" attaches one document; Nito parses it to text server-side.
--json returns a structured object (content, model, privacy_route, token counts).
if answer=$(…); then skips a file that fails and keeps going, instead of aborting the whole batch.
jq -c … >> "$OUT" tags each answer with its filename and appends one JSON object per line (a .jsonl file).

Step 3: Run it

# Ask the default question of every PDF in ./contracts
./batch-qa.sh ./contracts

# Ask a specific question
./batch-qa.sh ./invoices "What is the total amount due and the due date?"

Step 4: Read and aggregate

Each line of answers.jsonl is one document’s answer:

# Print every answer with its filename
jq -r '"\(.file): \(.content)"' answers.jsonl

acme-2026-01.pdf: Total due 12,500.00 USD, due 2026-03-03.
globex-2026-02.pdf: Total due 4,200.00 USD, due 2026-02-28.
initech-2026-02.pdf: Total due 9,900.00 USD, due 2026-03-15.

Roll the whole set up into one summary by feeding the collected answers back through Nito:

{ echo "Summarize these per-document answers into three bullet points:"; cat answers.jsonl; } \
  | nito ask --web-search off --stdin

Extract Structured Fields

Often you want typed fields, not prose. Nito does not expose server-side JSON-schema enforcement, so the reliable pattern is prompt for JSON, then validate on your side. Ask for the exact fields and forbid prose:

nito ask --file ./invoice.pdf --web-search off --json \
  'Return ONLY a JSON object with keys "vendor", "total_usd" (number), and "due_date" (YYYY-MM-DD). No prose, no code fences.'

The model’s answer is inside the content field, so parse it twice: once for the envelope, once for the content. Treat the content as untrusted until it parses:

nito ask --file ./invoice.pdf --web-search off --json \
  'Return ONLY JSON {"vendor","total_usd","due_date"}. No prose, no fences.' \
  | jq -r '.content' | jq .        # second jq validates the model's JSON

If the second jq fails, do not store the record. Re-ask with a stricter prompt, or validate against your own schema (JSON Schema, Pydantic, Zod) and reject anything that does not fit. Three things make this reliable: name every field and its type, say “return only JSON, no code fences”, and give an example shape when the structure is nested.

Variations

Keep sensitive documents private. For confidential files, pin a Private-tier model so the provider does not retain the contents:

nito ask --file ./contract.pdf --model z-ai/glm-5.2 --web-search off \
  "Does this contract auto-renew, and what is the notice period?"

Other formats. Change the glob from *.pdf to *.docx, *.xlsx, or a broader pattern to cover a mixed folder. Images instead of documents. A screenshot or photo needs a vision model, not the parser. See Screenshot Debugger.

Troubleshooting

What you see	Why	Fix
”cannot accept image attachments”	A file is an image, not a document	Images need a vision model. See Image input
An unsupported-format error	File is not PDF, DOCX, PPTX, XLSX, XLS, or text	Convert it, or narrow the glob
Output wrapped in code fences	The model added Markdown to the JSON	Say “no code fences,” or strip fences before the second `jq`
`jq: error` on a line	A call failed or returned non-JSON	The script skips failures; re-run the named file
Answers miss later pages	A very large document exceeds the model’s context	Ask about specific sections, or split the file

Where to Go Next

File parser

How Nito extracts text from documents, and the supported formats.

Screenshot Debugger

The image path, for screenshots and diagrams.

Scripting and Automation

Output modes, exit codes, and piping for batch scripts.

Private Code Review Pipeline

The same JSON-and-scripting pattern, applied to code.

​How It Works

​Prerequisites

​Step 1: Ask one document

​Step 2: The batch script

​Step 3: Run it

​Step 4: Read and aggregate

​Extract Structured Fields

​Variations

​Troubleshooting

​Where to Go Next

File parser

Screenshot Debugger

Scripting and Automation

Private Code Review Pipeline

How It Works

Prerequisites

Step 1: Ask one document

Step 2: The batch script

Step 3: Run it

Step 4: Read and aggregate

Extract Structured Fields

Variations

Troubleshooting

Where to Go Next