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Docsifer

Docsifer is a document-conversion application that turns files and URLs into Markdown for indexing, text analysis and downstream knowledge workflows. Its repository describes a Python and FastAPI service, packaged for Docker, with an optional browser playground and optional OpenAI-compatible LLM enhancement for OCR, transcription and structured layout extraction.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Docsifer — OpenViST project profile in RAG & Knowledge Systems.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Docsifer when source material arrives in varied formats and a downstream workflow needs Markdown. It handles conversion and preparation; a separate system is needed for indexing, retrieval or question answering.

Who it is for

  • People preparing mixed-format document collections for indexing or text analysis.
  • Developers building retrieval or knowledge workflows that accept Markdown as input.
  • Teams that want to run a document-conversion service locally or in a Docker container.

Documented uses

  • Convert PDF, Office, HTML, image, audio and structured-data files into Markdown.
  • Convert a URL into Markdown through the documented conversion API.
  • Prepare normalized text for a separate indexing, retrieval or text-analysis stage.
  • Use optional LLM assistance for OCR, transcription and structured layout extraction.
Before you choose

Requirements & limits

The project provides a documented local setup and Docker run route. The repository declares an MIT license. The README lists Python 3.10+ for the application.

  • The README lists PDF, Word, PowerPoint, Excel, HTML, audio, images, CSV, JSON and ZIP as supported input categories.
  • LLM enhancement is optional and requires a user-provided OpenAI-compatible key.
  • LangChain and LlamaIndex are mentioned in repository topics, but tested integrations are not demonstrated; feeding Markdown into their indexing pipelines is marked Likely compatible.
  • The README lists a 10 MB default upload limit, two concurrent conversions globally, one per IP, and a 55-second request timeout.
  • The README says files are processed in memory and discarded immediately; this is a project statement, not an independent verification.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Convert a file with the local Docsifer API

Start Docsifer locally and submit a document to its Markdown conversion endpoint.

Before you start

  • Python 3.10 or later, as specified by the README.
  • The Docsifer repository and a document file.
  • An environment file copied from .env.example.

Steps

  1. Run the command below in the repository.

    Documented command
    make install

  2. Copy .env.example to .env.

  3. Start the application with the command below.

    Documented command
    make run

  4. Submit the file to POST /v1/convert; the README demonstrates a PDF using the command below.

    Documented command
    curl -X POST http://localhost:7860/v1/convert -F "file=@document.pdf"

Expected outcome

The conversion endpoint returns Markdown from the submitted file.

Guide limitations

  • The README lists a default upload limit of 10 MB and a 55-second request timeout.
  • LLM-assisted OCR, transcription and layout extraction require an OpenAI-compatible key; the basic conversion example does not include one.
Documentation 1 ↗
Source-based practical guide

Run Docsifer in Docker

Build and start the documented containerized Docsifer application.

Before you start

  • The Docsifer repository and Docker.
  • An environment file copied from .env.example.

Steps

  1. Copy .env.example to .env.

  2. Build the image with the command below.

    Documented command
    docker build -t docsifer .

  3. Start the container with the command below.

    Documented command
    docker run --rm -p 7860:7860 --env-file .env docsifer

  4. Open the UI at http://localhost:7860 or API documentation at http://localhost:7860/docs.

Expected outcome

The container runs Docsifer with its UI and API documentation exposed on port 7860.

Guide limitations

  • The README does not specify infrastructure sizing or production deployment requirements.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
16 October 2026
Original website title
lh0x00/docsifer · Official homepage title · retained in its source language
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