Pandrator
Pandrator is a local-first workspace for creating audiobooks, subtitles, and voiceovers. It brings document preparation, transcription, optional AI correction and translation, speech generation, review, and export into one browser interface.
Local speech and transcription models can keep media on your own computer. Cloud language, translation, and speech providers are optional and used only when you configure and select them.
Install Pandrator
Open the latest release and choose the Manager for your operating system:
| System | Download | Notes |
|---|---|---|
| Windows 10 or 11, 64-bit | PandratorManager-…-windows-x86_64.exe |
Run the executable and choose the parent folder for the installation. Windows may show an unsigned-publisher warning. |
| Linux desktop, 64-bit | PandratorManager-…-x86_64.AppImage |
Make the AppImage executable, run it, and choose the parent folder. |
| Headless Linux | Linux AppImage or Python package | Pass an explicit workspace and --no-open; use HTTPS or a VPN for remote access. |
| Developers | Source checkout with Pixi | Use the committed lockfile and the separate web-build environment. |
The Manager creates and owns one Pandrator workspace under the selected
parent directory. It installs the application and only the local components
you choose; Docker and WSL are not required. Start with one speech or
transcription engine and add others later.
See the installation guide for checksum verification, workspace selection, headless setup, and updates.
Choose a workflow
| I want to… | Start here |
|---|---|
| Turn a document into narrated audio or an M4B audiobook | Create your first audiobook |
| Transcribe media, correct subtitles, translate them, or export SRT/VTT | Create your first subtitles |
| Generate synchronized speech and produce a dubbed video | Create your first voiceover |
| Let the model in Codex, OpenCode, Claude Code, or another MCP host process subtitle, document-cleanup, or speech-text batches | Use passive dispatch |
| Ask an agent to take a local file through processing and return verified deliverables | Run an end-to-end agent workflow |
| Connect an agent safely to Pandrator or recover a managed installation | Connect an MCP host |
| Install, update, repair, or operate local components | Pandrator Manager |
The documentation index links the complete workflow, operations, security, reference, and development guides.
What Pandrator can do
Audiobooks
- Import TXT, PDF, EPUB, DOCX, MOBI, or pasted text.
- Clean difficult documents with deterministic tools, OCR, and an optional reviewable AI workflow.
- Detect structure and chapters, normalize text, and split it for speech.
- Generate speech in segments, compare takes, edit text, regenerate selected passages, and apply optional RVC conversion.
- Export WAV, MP3, Opus, FLAC, or M4B with chapters, metadata, and cover art.
Subtitles and voiceovers
- Start from SRT subtitles or common audio and video formats. WebVTT, ASS, and SSA uploads are recognized while the editing pipeline uses SRT as its working subtitle format.
- Transcribe speech with timestamps and optional diarization.
- Correct, translate, split, merge, and retime cues in a reviewable editor.
- Generate synchronized speech without changing the source media.
- Export subtitles, audio, or video with selectable audio and subtitle tracks.
Voices and providers
- Use local TTS services or configured cloud speech providers.
- Connect local OpenAI-compatible LLM servers and supported cloud LLMs.
- Record or upload reference voices, retain their transcripts, and preview built-in voices before generation.
- Import fine-tuned XTTS bundles and RVC models while keeping original and converted takes available for review.
The providers and voices guide explains the local engines, compute choices, voice cloning, and when data leaves the Pandrator host.
Reviewable AI, including no-extra-API dispatch
LLMs are optional. Pandrator can use a configured provider for document cleanup, subtitle correction, glossary-aware translation, research, and speech-text optimization. Each transformation creates a distinct revision or artifact; it does not silently replace the source text.
Passive dispatch provides a different route. Pandrator makes no model call: it snapshots the selected source and queues deterministic, leased subtitle, document-cleanup, or speech-text packets. The model already running in an MCP host claims one packet, returns a typed result over stable identities, and continues sequentially. The final artifact appears only after every packet is validated.
Read correction and translation for the choice between manual review, a configured LLM, DeepL, and passive dispatch. The exact cue, batch, timing, speech-block, and alignment model is in the subtitle pipeline reference.
Local-first does not mean local-only
Pandrator binds to loopback by default and is designed for one owner. A home server, VPN host, external HTTPS server, or GPU pod is possible when its data, Manager state, identity, and network boundary are deliberately preserved. Pandrator is not a public multi-user service.
The remote and headless guide covers supported topologies. The privacy and security guide explains local and cloud data flows, credentials, diagnostics, MCP access, and safe remote exposure.
Agent access with Pandrator MCP
pandrator-mcp lets an MCP-capable agent explain Pandrator, inspect one fixed
installation, edit sessions safely, execute
reviewed workflow plans, process passive subtitle, document-cleaning, and
speech-text batches, import files from approved named roots, resolve live TTS
catalog choices, export explicit output variants, download verified artifacts,
and perform bounded Manager recovery. Target origins, absolute filesystem
paths, and credentials are process configuration, not model-selected tool
arguments.
On a compatible local Manager installation, Pandrator exposes an authenticated loopback Streamable HTTP MCP automatically. Stdio remains available for older hosts, source development, and the recommended remote topology where the MCP process runs beside the agent and connects to a fixed HTTPS Pandrator target.
The component guide documents:
- local, LAN/VPN, external HTTPS, and pod targets;
- least-privilege application and Manager scopes;
- owner-approved enrollment, identity pinning, rotation, and revocation;
- managed local HTTP and secret-free stdio host configuration for Codex, Claude Code, OpenCode, and Antigravity;
- passive subtitle correction/translation, PDF/EPUB source cleanup, and speech-text optimization;
- resumable local/remote source transfer and verified output delivery;
- live provider/model/voice selection and typed output variants; and
- diagnostics and optional recovery while Pandrator is stopped.
See the Pandrator MCP guide for exact installation and configuration commands.
Documentation
| Area | Canonical documentation |
|---|---|
| Product setup and workflows | Public documentation |
| PDF/EPUB ingestion, OCR, cleanup, and narration parameters | Document-ingestion reference |
| Standalone, generation-time, and passive speech-text optimization | Speech-optimization reference |
| Manager installation, CLI, recovery, and component operations | Manager guide |
| MCP installation, targets, scopes, host configuration, and protocol behavior | MCP guide |
| Version history, downloads, and checksums | GitHub Releases |
| Bugs, support requests, and proposals | GitHub Issues |
Public product documentation is intentionally version-agnostic where possible. Release-specific behavior and filenames belong on the corresponding release; package-specific operational contracts remain beside their packages.
Development
For source development, install Pixi and use the committed lockfile:
git clone https://github.com/lukaszliniewicz/Pandrator.git
cd Pandrator
pixi install --locked
pixi install --environment web-build --locked
pixi run --environment web-build web-build
pixi run serve-web
Run pixi run run-worker in a second terminal. See
development from source for environments,
test lanes, API/client regeneration, and package checks. Read
contributing before preparing a change.
Getting help
Start with troubleshooting. For a bug, open a GitHub issue with your operating system, the affected model or provider, the action you took, and the smallest reproducible sequence. When an installation or service action fails, include the Manager's reviewed Download diagnostics support bundle. Always inspect diagnostics before sharing them.
License
Pandrator is released under the MIT License. This covers Pandrator's source code, not third-party dependencies, speech models, transcription models, LLMs, or voice-conversion models. Review the licence and usage terms shown before installing a model, and make sure you have the necessary rights to source media and voice material.
Metadata
Release files for pandrator 0.9.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pandrator-0.9.0.tar.gz | 6.5 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pandrator-0.9.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 8.8 MB
Release files / pandrator-0.9.0.tar.gz
| Download URL | pandrator-0.9.0.tar.gz |
|---|---|
| Size | 6.5 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 8, 2026.
Transparency logRelease files / pandrator-0.9.0-py3-none-any.whl
| Download URL | pandrator-0.9.0-py3-none-any.whl |
|---|---|
| Size | 2.3 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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|
BLAKE2b-256 checksum How to use checksums |
a497a68c0b3ec677cd7d3f87f5b06c1a64fb333be45a079c4a564adaced36cc1
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 8, 2026.
Transparency log