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Read File Node

The Parse File node reads the text content from files. Got a PDF you need to analyze? An email attachment to process? An image with text in it? This node extracts the text so you can work with it.

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When to Use

  • Reading documents - Get the text from PDFs, Word docs, PowerPoints
  • Processing attachments - Read files that came with emails
  • Reading text from images - Extract words from photos, scans, screenshots
  • Importing data - Read CSV or Excel files
  • Processing forms - Get the filled-in data from PDF forms

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Supported File Types

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Documents

FormatExtensionNotes
PDF.pdfText and image-based (via OCR)
Word.docx, .docModern and legacy formats
PowerPoint.pptx, .pptExtracts slide text
Text.txt, .md, .rtfPlain text files

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Spreadsheets

FormatExtensionNotes
Excel.xlsx, .xlsReturns structured data
CSV.csvParsed into rows/columns

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Images

FormatExtensionNotes
Images.png, .jpg, .jpeg, .gif, .webpOCR extraction
TIFF.tiffOften used for scans

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Example: Email Attachment Processor

Extract and analyze content from email attachments:
1

Receive email with attachment

Use Event from App (Gmail) to trigger on emails with attachments.
2

Parse each attachment

Add a Loop node to iterate over {{event_from_app_1.email.attachments}}:
├── Loop (over attachments)
│   └── Parse File (fileReference: {{loop_1.currentItem}})
3

Analyze content

Use an LLM node to analyze or summarize:
Summarize this document in 3 bullet points:
{{parse_file_1.content}}
4

Store results

Add to a spreadsheet or send via Slack.

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Example: Invoice Data Extraction

Extract structured data from PDF invoices: 
Workflow: Invoice Processor
├── Event from App (Gmail: emails from [email protected])
├── Parse File (attachment, mode: structured)
├── LLM (extract invoice data into JSON)
│   Prompt:
│   "Extract from this invoice:
│   - Invoice number
│   - Date
│   - Vendor name
│   - Line items (description, quantity, amount)
│   - Total
│
│   Document: {{parse_file_1.content}}"
├── Execute Code (validate and format data)
└── External API (add to accounting system)

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Example: Resume Scanner

Process job applications: 
Workflow: Resume Scanner
├── Webhook (from careers page upload)
├── Parse File (from upload)
├── LLM (extract candidate info)
│   "Extract:
│   - Name
│   - Email
│   - Phone
│   - Years of experience
│   - Key skills
│   - Education
│
│   Resume: {{parse_file_1.content}}"
├── External API (HubSpot: create contact)
└── External API (Slack: notify recruiting team)

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Working with Multi-Page Documents

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Process All Pages Together

Summary of the entire document:
{{parse_file_1.content}}

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Process Pages Individually

├── Parse File (PDF)
├── Loop (over {{parse_file_1.pages}})
│   ├── LLM (analyze page {{loop_1.currentIndex + 1}})
│   └── Set Variable (append results)
└── LLM (synthesize all page analyses)

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Extract Specific Pages

Configuration: pages: "1,5-10" Only extracts pages 1 and 5 through 10.

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Handling Tables

For documents with tables, use structured extraction mode: 
├── Parse File (mode: structured)
├── Execute Code
│   # Access tables
│   tables = input["parse_file_1"]["tables"]
│
│   # First table, first row
│   header = tables[0]["rows"][0]
│
│   # Convert to records
│   records = []
│   for row in tables[0]["rows"][1:]:
│       record = dict(zip(header, row))
│       records.append(record)
│
│   return {"records": records}
└── Loop (over records)

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Reading Text from Images and Scans

If your file is an image or a scanned document, use OCR mode to read the text: Set extraction mode to: ocr
OCR takes longer (usually 2-5 seconds per page) and isn’t always perfect. Double-check important extractions.
For better results:
  • Use higher quality images
  • Make sure the text is clear and readable
  • Note that handwriting usually doesn’t work well

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When Things Go Wrong

File reading can fail because:
  • The file is damaged
  • The file type isn’t supported
  • The file is password-protected
  • The file is too big
You can check if it worked: 
├── Parse File
├── Condition (did it work?)
│   ├── Yes: Continue processing
│   └── No: Send alert about the problem
Password-protected PDFs can’t be read. Ask users to provide files without passwords.

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File Size Limits

File TypeMax Size
PDF50 MB
Word/PowerPoint25 MB
Images10 MB
CSV/Excel25 MB
For larger files, consider splitting or pre-processing.

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Tips

For long documents, extract text first and then use an LLM to summarize or answer specific questions. Don’t try to process entire books in one go.
Use structured mode when you need to preserve tables. Use text mode when you just need the words and don’t care about formatting.
Store parsed content in a variable if you need to reference it multiple times. Parsing is compute-intensive.

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Settings

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name
string
default:"Parse File"
What to call this node (shown on the canvas).
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key
string
default:"parse_file_1"
A short code to reference this node’s content.
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fileSource
string
required
Where the file is coming from:
  • url - Download it from a web address
  • base64 - The file content encoded as text
  • previous_node - A file from an earlier step (like an email attachment)
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fileUrl
string
The web address to download from (if using URL source).
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fileContent
string
The encoded file content (if using base64 source).
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fileReference
string
Reference to a file from an earlier node (if using previous_node source).
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extractionMode
string
default:"text"
How to read the file:
  • text - Just get the words
  • structured - Try to keep tables and lists intact
  • ocr - Read text from images or scanned documents
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pages
string
Which pages to read (for documents with multiple pages). Examples: 1-5, 1,3,5, or all.

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Outputs

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content
string
The extracted text content.
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pages
array
Array of page contents (for multi-page documents).
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metadata
object
File metadata:
  • pageCount - Number of pages
  • fileType - Detected file type
  • fileSize - Size in bytes
  • title - Document title (if available)
  • author - Document author (if available)
  • createdAt - Creation date (if available)
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tables
array
Extracted tables (when using structured mode).
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success
boolean
Whether extraction completed successfully.

Ask AI

Analyze and extract insights from parsed content.

Loop

Process multiple files or pages.