Skip to main content

CLI for Reducto document processing

Project description

Reducto CLI

PyPI version Python 3.11+ License

The official command-line interface for Reducto — the agentic document platform for AI teams building production systems on real-world documents.

Document work starts here. Parse PDFs, images, spreadsheets, and Office documents into clean Markdown. Extract structured JSON using schemas. Edit documents with natural language instructions. Process single files or entire directories — all from your terminal, backed by the same agentic document platform trusted by teams at Harvey, Scale AI, and Vanta.

Documentation | Reducto Studio | API Quickstart | Python SDK | Claude Code Plugin


Table of Contents


Why Reducto

Reducto is the agentic document platform for leading AI teams who demand enterprise performance at scale. We provide a comprehensive toolkit for working with documents the way a human would, combining custom in-house and leading frontier models to power efficient and accurate document workflows.

The CLI brings that platform directly into your shell, scripts, and agent workflows.

Performance for you

Zero-shot accuracy on complex documents where other solutions aren't production-ready. Reducto orchestrates multiple models under the hood — routing, probes, and agentic VLM multipasses — and continuously updates them so you don't have to chase the frontier. Handles the long tail: tables, charts, figures, handwriting, scans. We balance accuracy, latency, and throughput for your use case, not a generic benchmark.

Enterprise ready

Built for real production scale: hosted, VPC, on-premises, and air-gapped deployments to meet any data residency or security requirement. SOC 2 and HIPAA compliant with zero data retention by default. Autoscaling for spiky workloads, custom SLAs, and white-glove FDE support.

Complete toolkit

One platform for every document task — parse, classify, split, extract, edit, generate, redact, translate. 30+ filetypes, not just PDFs. End-to-end from raw file ingestion through agent-ready outputs and workflow orchestration. Agent-ready tooling (CLI, MCP, plugins, integrations) so your agents have the right tool for every job, today and six months from now.


Installation

pip install reducto-cli

Requires Python 3.11 or later.

Authentication

Authenticate using the built-in device code flow, which opens a browser to Reducto Studio:

reducto login

This saves your API key to ~/.reducto/config.yaml.

Alternatively, set the REDUCTO_API_KEY environment variable directly:

export REDUCTO_API_KEY="your_api_key_here"

Get an API key by signing up at studio.reducto.ai.

Quick Start

# Parse a PDF into Markdown
reducto parse invoice.pdf

# Parse an entire folder of documents
reducto parse ./contracts/

# Extract structured data using a JSON Schema
reducto extract invoice.pdf -s schema.json

# Edit a document with natural language
reducto edit form.pdf -i "Fill in the client name as 'Acme Corp'"

Commands

Parse Command

Turns unstructured documents into faithful, machine-readable Markdown — the ingestion layer for AI engineers feeding RAG pipelines, embeddings, and downstream agent steps. Preserves layout, tables, and figures using Reducto's Parse API with agentic OCR and vision-language models.

reducto parse <path> [options]

Output is written to <filename>.parse.md with YAML front matter containing the job ID and processing duration.

Options

Flag Description
--agentic Enables agentic processing for tables, text, and figures. Higher accuracy, higher latency. Use for complex layouts or low-quality scans.
--change-tracking Returns <s>, <u>, and <change> tags for strikethrough, underlined, and revised text. Useful for contracts and legal redlines.
--highlights Include highlighted text in output.
--hyperlinks Include embedded hyperlinks in output.
--comments Include document comments in output.

Examples

# Basic parse
reducto parse document.pdf

# High-accuracy parse for complex layouts
reducto parse scanned_report.pdf --agentic

# Parse a contract with revision tracking
reducto parse contract.pdf --change-tracking

# Parse with all metadata preserved
reducto parse document.pdf --hyperlinks --comments --highlights

# Combine flags
reducto parse legal_doc.pdf --agentic --change-tracking --comments

Extract Command

Schema-driven, grounded extraction that adapts to new document types in real time — no pre-labeling, template setup, or model retraining. Maps unstructured content — invoices, receipts, forms, contracts, financial statements — into machine-readable JSON according to a JSON Schema you provide. Every field comes back citation-backed so end users can trust what came out.

reducto extract <path> --schema <schema>

The schema can be a path to a .json file or an inline JSON string. Output is saved as <filename>.extract.json.

The CLI automatically reuses existing parse results: if a .parse.md file exists for a document, its recorded job ID is used via jobid:// references to skip re-parsing.

Schema Requirements

  • Must be a valid JSON Schema document.
  • The top-level type must be object — arrays and primitives are not permitted at the top level.
  • Schemas can be provided as file paths or inline JSON strings.

Example Schema

{
  "type": "object",
  "properties": {
    "vendor_name": { "type": "string" },
    "invoice_number": { "type": "string" },
    "date": { "type": "string" },
    "line_items": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "description": { "type": "string" },
          "quantity": { "type": "number" },
          "unit_price": { "type": "number" },
          "total": { "type": "number" }
        },
        "required": ["description", "quantity", "unit_price", "total"]
      }
    },
    "total_amount": { "type": "number" }
  },
  "required": ["vendor_name", "invoice_number", "line_items", "total_amount"]
}

Examples

# Extract using a schema file
reducto extract invoice.pdf -s schemas/invoice.json

# Extract from a folder of invoices
reducto extract ./invoices/ -s schemas/invoice.json

# Extract with inline JSON schema
reducto extract receipt.pdf -s '{"type":"object","properties":{"total":{"type":"number"},"date":{"type":"string"}},"required":["total","date"]}'

Edit Command

Generates and modifies documents using natural language instructions — part of Reducto's document generation engine (creation, redaction, translation, and more). Uploads the document, applies edits via the Reducto Edit API, and downloads the result.

reducto edit <path> --instructions "<instructions>"

Edited files are saved as <filename>.edited.<extension> (e.g., form.pdf becomes form.edited.pdf).

Parameter Required Description
path Yes Path to a file or directory.
--instructions, -i Yes Natural language instructions for the edits.

Examples

# Fill out a PDF form
reducto edit application.pdf -i "Fill in: Name: Jane Smith, Date: 2025-03-15, check 'Agree to terms'"

# Update a contract
reducto edit contract.pdf -i "Fill in the client name as 'Acme Corporation' and set the effective date to January 15, 2025"

# Batch edit a folder of forms
reducto edit ./forms/ -i "Set the company name to 'Globex Inc' in all header fields"

Tips for Effective Instructions

  • Be specific about which elements to modify (headers, tables, specific fields).
  • Reference content by name or position when possible.
  • Describe the desired outcome, not the process.
  • For batch operations, write instructions that apply uniformly across all files.

Supported File Types

Category Extensions
PDF .pdf
Images .png, .jpg, .jpeg
Office Documents .doc, .docx, .ppt, .pptx
Spreadsheets .xls, .xlsx, .numbers

All commands accept a single file or a directory. Directories are scanned recursively and only supported file types are processed. Generated output files (.parse.md, .extract.json) are automatically excluded from processing.


Use Cases

Invoice and Receipt Processing

Parse invoices from any vendor format, then extract line items, totals, and payment details into structured JSON for your accounting pipeline.

reducto parse ./invoices/
reducto extract ./invoices/ -s schemas/invoice.json

Contract and Legal Document Review

Parse contracts with change tracking to surface redlines and revisions. Extract key clauses, dates, and party names for contract management systems.

reducto parse contract.pdf --agentic --change-tracking --comments
reducto extract contract.pdf -s schemas/contract_terms.json

Form Processing and Auto-Fill

Edit PDF and DOCX forms programmatically — fill fields, check boxes, and populate tables without manual data entry.

reducto edit onboarding_form.pdf -i "Fill in employee name: Alex Chen, start date: 2025-04-01, department: Engineering, select 'Full-time' for employment type"

Financial Statement Analysis

Extract tables and figures from bank statements, earnings reports, and tax documents into structured data for financial modeling.

reducto extract quarterly_report.pdf -s schemas/financial_statement.json

Medical and Insurance Document Processing

Parse lab reports, claims forms, and patient intake documents. Reducto is HIPAA compliant for healthcare workflows.

reducto parse lab_results.pdf --agentic
reducto extract claim_form.pdf -s schemas/insurance_claim.json

Batch Document Digitization

Convert entire folders of scanned documents, presentations, and spreadsheets into searchable Markdown for knowledge bases or RAG pipelines.

reducto parse ./legacy_docs/ --agentic

Feeding Agents and LLM Pipelines

Parse documents into clean, embedding-optimized Markdown so retrieval surfaces the right context, not the wrong page. Pipe Reducto's output directly into your agent harness, RAG system, or LLM workflow — Reducto handles ingestion so your engineers ship AI features instead of maintaining OCR, parsers, and extraction pipelines.

# Parse into LLM-ready Markdown
reducto parse ./knowledge_base/

# Or extract specific fields for structured RAG
reducto extract ./knowledge_base/ -s schemas/document_metadata.json

How It Works

  1. Upload — The CLI uploads your document to Reducto's agentic document platform.
  2. Process — Reducto orchestrates agentic OCR, layout detection, vision-language models, and probes, routing each document to the right approach for the job.
  3. Return — Parsed Markdown, extracted JSON, or edited documents are downloaded to your local filesystem, ready for your agents, pipelines, or warehouse.

Files within a directory are processed concurrently. Parse results are cached locally (.parse.md files with job IDs), so subsequent extract commands skip re-parsing via jobid:// references.


Configuration

Method Details
Device code login reducto login — opens browser, saves key to ~/.reducto/config.yaml
Environment variable export REDUCTO_API_KEY="your_key" — takes precedence over saved config
Manual entry The CLI prompts for manual key entry as a fallback

The config file is stored at ~/.reducto/config.yaml with 0600 permissions.


Related Projects

Project Description
Reducto Python SDK Full Python client for the Reducto API (pip install reductoai)
Reducto Node.js SDK Node.js client for the Reducto API (npm install reductoai)
Reducto Go SDK Go client for the Reducto API
Reducto Claude Code Plugins Official Reducto plugins for Claude Code
Reducto Studio No-code web interface for document processing

Resources

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

reducto_cli-0.1.5.tar.gz (19.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

reducto_cli-0.1.5-py3-none-any.whl (18.7 kB view details)

Uploaded Python 3

File details

Details for the file reducto_cli-0.1.5.tar.gz.

File metadata

  • Download URL: reducto_cli-0.1.5.tar.gz
  • Upload date:
  • Size: 19.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.13

File hashes

Hashes for reducto_cli-0.1.5.tar.gz
Algorithm Hash digest
SHA256 26325f20a36e54704e5611f8c7329761e8a2034d839310522778b8657428abcb
MD5 2bd741ecb41c39f0e5efe14a29d14d8c
BLAKE2b-256 f5c247c2e8692436d2467b9610591c3383b3e2d5b99d6c86516753477d2b36d5

See more details on using hashes here.

Provenance

The following attestation bundles were made for reducto_cli-0.1.5.tar.gz:

Publisher: publish.yml on reductoai/cli

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file reducto_cli-0.1.5-py3-none-any.whl.

File metadata

  • Download URL: reducto_cli-0.1.5-py3-none-any.whl
  • Upload date:
  • Size: 18.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.13

File hashes

Hashes for reducto_cli-0.1.5-py3-none-any.whl
Algorithm Hash digest
SHA256 6c7e782042d5d0c395fb8a747c8efc3962d729cbdf98ee1d6917baa5aa93a124
MD5 ef5114ce5c2e0198fd7d77dfed82baf4
BLAKE2b-256 47df3cb5cdc085c2fac3a492cfab34893a395cd1e6060b464c1b2daaa709158b

See more details on using hashes here.

Provenance

The following attestation bundles were made for reducto_cli-0.1.5-py3-none-any.whl:

Publisher: publish.yml on reductoai/cli

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page