ParseDoc

Document → AI → Markdown. A local-first CLI that converts documents into clean, structured, AI-ready Markdown.

ParseDoc turns PDFs, Word docs, PowerPoint decks, HTML pages, plain text, and images into well-structured Markdown. Libraries extract the raw facts, an optional AI model understands the structure, and a deterministic renderer produces the final output. It works fully offline (local rule-based structuring) and can optionally use an AI provider for smarter structuring.

Demo

Watch the demo on YouTube: https://youtu.be/Cz8ORg6Fs1Y

Screenshots / Proofs

Features

• Local-first: conversion works with no AI provider configured (deterministic fallback).
• Multi-format input: PDF, DOCX, PPTX, HTML, TXT/MD, and images (PNG/JPG) via OCR.
• AI structuring (optional): local, ai, or hybrid modes.
• Pluggable AI providers: OpenAI-compatible (vLLM/LM Studio/OpenRouter), OpenAI, Google Gemini, Ollama (native), and LM Studio.
• Document fidelity: preserves headings, bold/italic/underline, hyperlinks, nested lists, and keeps tables in their original position.
• Image extraction: parsedoc image pulls embedded images from a DOCX into a folder in your working directory (or a path you choose).
• OCR: Tesseract-backed text extraction for scanned PDFs and images.
• Multiple output formats: markdown (default), json, html, text.

Installation

pip install docpilot-ai

The PyPI package is named docpilot-ai; the import name and CLI command are both parsedoc.

Full setup, configuration, and provider instructions are in setup.md.

Quick start

# Convert a single document
parsedoc convert input.docx -o output.md --mode hybrid

# Convert a whole folder (creates ./batch_out in the current directory)
parsedoc batch . -p "*.docx"

# Inspect a document's structure
parsedoc inspect input.pdf --format summary

# Extract all images embedded in a DOCX into <filename>_assets/ (in the cwd)
parsedoc image input.docx

# Extract images into a specific folder
parsedoc image input.docx -o ./my_images

# Show configuration
parsedoc config list

# Banner + version
parsedoc version

Modes

Supported input formats

Configuring your API

ParseDoc supports several AI providers. Configure via parsedoc config, environment variables, or the TOML file. Examples:

# OpenAI-compatible (e.g. xkiro)
parsedoc config set --key ai_provider --value openai-compatible
parsedoc config set --key base_url --value "https://api.xkiro.com/v1"
parsedoc config set --key model --value "stealth/ox-alpha-free"
parsedoc config set --key api_key --value "sk-xt-..."

# LM Studio (local, defaults to http://localhost:1234/v1)
parsedoc config set --key ai_provider --value lm-studio
parsedoc config set --key model --value local-model

# Ollama (local)
parsedoc config set --key ai_provider --value ollama
parsedoc config set --key model --value qwen3

See setup.md for the complete list of providers (openai-compatible, openai, gemini, ollama, lm-studio), all config keys, environment-variable overrides, and troubleshooting.

Using ParseDoc as a library

from parsedoc.core.config import Config
from parsedoc.core.pipeline import Pipeline

config = Config().load_from_file()
pipeline = Pipeline(config)

markdown = pipeline.process(
    "report.docx",
    output_format="markdown",
    mode="hybrid",
    extract_images=True,
    output_path="report.md",
)

Contributing

Contributions are welcome! See CONTRIBUTING.md for the development setup, how to add new parsers/AI providers, and the roadmap for future integrations such as the MCP SDK (exposing ParseDoc as a tool for LLM agents).

License

MIT — see LICENSE.