chatterbox-tts-api
Local OpenAI-compatible text-to-speech API using Chatterbox
GraphCanon updated Aug 13, 2026 · GitHub synced Aug 13, 2026
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Decision brief
Chatterbox-TTS-API is a locally hosted Python-based text-to-speech API with capabilities similar to ElevenLabs, offering an OpenAI-compatible interface for generating voice-cloned speech.
Good fit when
- When you need a self-hosted solution that mirrors the functionality of ElevenLabs or other proprietary TTS services and requires compatibility with existing ecosystems like Open WebUI or AnythingLLM.
- If your project demands local processing to avoid data privacy concerns related to cloud-based text-to-speech platforms.
Avoid when
- If you require integrations specific to ElevenLabs' proprietary voice models as Chatterbox-TTS-API, despite its capabilities, does not directly support their unique voice libraries.
- For users needing a fully managed service without the complexities of local deployment and maintenance, like that offered by cloud-based TTS providers.
- Requirements:
- Requires a local setup environment that supports CUDA for optimal performance; Docker can simplify deployment.
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Slowing (232d since push)
- As of Aug 13, 2026
- Provenance
- Not a fork · Personal account
- As of Aug 13, 2026
- Security (OSV)
- No lockfile
- As of Jul 15, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install chatterbox-tts-apiHow it fits your stack(1)
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Evidence and technical details
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Overview
Chatterbox-TTS-API is a self-hosted, Python-based local implementation of an OpenAI-compatible Text-To-Speech service, capable of generating voice-cloned speech on par with ElevenLabs.
Capability facts
- Languages
- python
Source: github.language+pyproject.toml · Aug 13, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 19, 2026)
### Local Installation with Python 🐍Source link
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README
⚡️ Quick Start [!TIP] uv installed with Local Installation with Python 🐍 Option A: Using uv (Recommended Faster & Better Dependencies) bash Same pattern works with all deployment variants: docker compose f docker/docker compose.gpu.yml profile frontend up d GPU + Frontend docker...
For agents
This page has a .md twin and JSON over the API.