openai-edge-tts
Free, high-quality text-to-speech API endpoint to replace OpenAI, Azure, or ElevenLabs
Stars: 412
This project provides a local, OpenAI-compatible text-to-speech (TTS) API using `edge-tts`. It emulates the OpenAI TTS endpoint (`/v1/audio/speech`), enabling users to generate speech from text with various voice options and playback speeds, just like the OpenAI API. `edge-tts` uses Microsoft Edge's online text-to-speech service, making it completely free. The project supports multiple audio formats, adjustable playback speed, and voice selection options, providing a flexible and customizable TTS solution for users.
README:
This project provides a local, OpenAI-compatible text-to-speech (TTS) API using edge-tts. It emulates the OpenAI TTS endpoint (/v1/audio/speech), enabling users to generate speech from text with various voice options and playback speeds, just like the OpenAI API.
edge-tts uses Microsoft Edge's online text-to-speech service, so it is completely free.
View this project on Docker Hub
-
OpenAI-Compatible Endpoint:
/v1/audio/speechwith similar request structure and behavior. -
Supported Voices: Maps OpenAI voices (alloy, echo, fable, onyx, nova, shimmer) to
edge-ttsequivalents. - Flexible Formats: Supports multiple audio formats (mp3, opus, aac, flac, wav, pcm).
- Adjustable Speed: Option to modify playback speed (0.25x to 4.0x).
- Optional Direct Edge-TTS Voice Selection: Use either OpenAI voice mappings or specify any edge-tts voice directly.
- Docker (recommended): Docker and Docker Compose for containerized setup.
-
Python (optional): For local development, install dependencies in
requirements.txt. - ffmpeg (optional): Required for audio format conversion. Optional if sticking to mp3.
- Clone the Repository:
git clone https://github.com/travisvn/openai-edge-tts.git
cd openai-edge-tts-
Environment Variables: Create a
.envfile in the root directory with the following variables:
API_KEY=your_api_key_here
PORT=5050
DEFAULT_VOICE=en-US-AvaNeural
DEFAULT_RESPONSE_FORMAT=mp3
DEFAULT_SPEED=1.0
DEFAULT_LANGUAGE=en-US
REQUIRE_API_KEY=True
REMOVE_FILTER=False
EXPAND_API=True
Or, copy the default .env.example with the following:
cp .env.example .env- Run with Docker Compose (recommended):
docker compose up --build(Note: docker-compose is not the same as docker compose)
Run with -d to run docker compose in "detached mode", meaning it will run in the background and free up your terminal.
docker compose up -dAlternatively, run directly with Docker:
docker build -t openai-edge-tts .
docker run -p 5050:5050 --env-file .env openai-edge-ttsTo run the container in the background, add -d after the docker run command:
docker run -d -p 5050:5050 --env-file .env openai-edge-tts-
Access the API: Your server will be accessible at
http://localhost:5050.
If you prefer to run this project directly with Python, follow these steps to set up a virtual environment, install dependencies, and start the server.
git clone https://github.com/travisvn/openai-edge-tts.git
cd openai-edge-ttsCreate and activate a virtual environment to isolate dependencies:
# For macOS/Linux
python3 -m venv venv
source venv/bin/activate
# For Windows
python -m venv venv
venv\Scripts\activateUse pip to install the required packages listed in requirements.txt:
pip install -r requirements.txtCreate a .env file in the root directory and set the following variables:
API_KEY=your_api_key_here
PORT=5050
DEFAULT_VOICE=en-US-AvaNeural
DEFAULT_RESPONSE_FORMAT=mp3
DEFAULT_SPEED=1.0
DEFAULT_LANGUAGE=en-US
REQUIRE_API_KEY=True
REMOVE_FILTER=False
EXPAND_API=True
Once configured, start the server with:
python app/server.pyThe server will start running at http://localhost:5050.
You can now interact with the API at http://localhost:5050/v1/audio/speech and other available endpoints. See the Usage section for request examples.
Generates audio from the input text. Available parameters:
Required Parameter:
- input (string): The text to be converted to audio (up to 4096 characters).
Optional Parameters:
-
model (string): Set to "tts-1" or "tts-1-hd" (default:
"tts-1"). -
voice (string): One of the OpenAI-compatible voices (alloy, echo, fable, onyx, nova, shimmer) or any valid
edge-ttsvoice (default:"en-US-AvaNeural"). -
response_format (string): Audio format. Options:
mp3,opus,aac,flac,wav,pcm(default:mp3). -
speed (number): Playback speed (0.25 to 4.0). Default is
1.0.
Example request with curl and saving the output to an mp3 file:
curl -X POST http://localhost:5050/v1/audio/speech \
-H "Content-Type: application/json" \
-H "Authorization: Bearer your_api_key_here" \
-d '{
"input": "Hello, I am your AI assistant! Just let me know how I can help bring your ideas to life.",
"voice": "echo",
"response_format": "mp3",
"speed": 1.1
}' \
--output speech.mp3Or, to be in line with the OpenAI API endpoint parameters:
curl -X POST http://localhost:5050/v1/audio/speech \
-H "Content-Type: application/json" \
-H "Authorization: Bearer your_api_key_here" \
-d '{
"model": "tts-1",
"input": "Hello, I am your AI assistant! Just let me know how I can help bring your ideas to life.",
"voice": "alloy"
}' \
--output speech.mp3And an example of a language other than English:
curl -X POST http://localhost:5050/v1/audio/speech \
-H "Content-Type: application/json" \
-H "Authorization: Bearer your_api_key_here" \
-d '{
"model": "tts-1",
"input": "ใใใใ่กใใ้ป่ปใฎๆ้ใ่ชฟในใฆใใใใ",
"voice": "ja-JP-KeitaNeural"
}' \
--output speech.mp3- POST/GET /v1/models: Lists available TTS models.
-
POST/GET /v1/voices: Lists
edge-ttsvoices for a given language / locale. -
POST/GET /v1/voices/all: Lists all
edge-ttsvoices, with language support information.
Contributions are welcome! Please fork the repository and create a pull request for any improvements.
This project is licensed under GNU General Public License v3.0 (GPL-3.0), and the acceptable use-case is intended to be personal use. For enterprise or non-personal use of openai-edge-tts, contact me at [email protected]
[!TIP] Swap
localhostto your local IP (ex.192.168.0.1) if you have issuesIt may be the case that, when accessing this endpoint on a different server / computer or when the call is made from another source (like Open WebUI), you need to change the URL from
localhostto your local IP (something like192.168.0.1or similar)
Open up the Admin Panel and go to Settings -> Audio
Below, you can see a screenshot of the correct configuration for using this project to substitute the OpenAI endpoint
If you're running both Open WebUI and this project in Docker, the API endpoint URL is probably http://host.docker.internal:5050/v1
[!NOTE] View the official docs for Open WebUI integration with OpenAI Edge TTS
In version 1.6.8, AnythingLLM added support for "generic OpenAI TTS providers" โ meaning we can use this project as the TTS provider in AnythingLLM
Open up settings and go to Voice & Speech (Under AI Providers)
Below, you can see a screenshot of the correct configuration for using this project to substitute the OpenAI endpoint
-
your_api_key_herenever needs to be replaced โ No "real" API key is required. Use whichever string you'd like. - The quickest way to get this up and running is to install docker and run the command below:
docker run -d -p 5050:5050 -e API_KEY=your_api_key_here -e PORT=5050 travisvn/openai-edge-tts:latestFor Tasks:
Click tags to check more tools for each tasksFor Jobs:
Alternative AI tools for openai-edge-tts
Similar Open Source Tools
openai-edge-tts
This project provides a local, OpenAI-compatible text-to-speech (TTS) API using `edge-tts`. It emulates the OpenAI TTS endpoint (`/v1/audio/speech`), enabling users to generate speech from text with various voice options and playback speeds, just like the OpenAI API. `edge-tts` uses Microsoft Edge's online text-to-speech service, making it completely free. The project supports multiple audio formats, adjustable playback speed, and voice selection options, providing a flexible and customizable TTS solution for users.
ebook2audiobook
ebook2audiobook is a CPU/GPU converter tool that converts eBooks to audiobooks with chapters and metadata using tools like Calibre, ffmpeg, XTTSv2, and Fairseq. It supports voice cloning and a wide range of languages. The tool is designed to run on 4GB RAM and provides a new v2.0 Web GUI interface for user-friendly interaction. Users can convert eBooks to text format, split eBooks into chapters, and utilize high-quality text-to-speech functionalities. Supported languages include Arabic, Chinese, English, French, German, Hindi, and many more. The tool can be used for legal, non-DRM eBooks only and should be used responsibly in compliance with applicable laws.
alexandria-audiobook
Alexandria Audiobook Generator is a tool that transforms any book or novel into a fully-voiced audiobook using AI-powered script annotation and text-to-speech. It features a built-in Qwen3-TTS engine with batch processing and a browser-based editor for fine-tuning every line before final export. The tool offers AI-powered pipeline for automatic script annotation, smart chunking, and context preservation. It also provides voice generation capabilities with built-in TTS engine, multi-language support, custom voices, voice cloning, and LoRA voice training. The web UI editor allows users to edit, preview, and export the audiobook. Export options include combined audiobook, individual voicelines, and Audacity export for DAW editing.
text-extract-api
The text-extract-api is a powerful tool that allows users to convert images, PDFs, or Office documents to Markdown text or JSON structured documents with high accuracy. It is built using FastAPI and utilizes Celery for asynchronous task processing, with Redis for caching OCR results. The tool provides features such as PDF/Office to Markdown and JSON conversion, improving OCR results with LLama, removing Personally Identifiable Information from documents, distributed queue processing, caching using Redis, switchable storage strategies, and a CLI tool for task management. Users can run the tool locally or on cloud services, with support for GPU processing. The tool also offers an online demo for testing purposes.
nanocoder
Nanocoder is a versatile code editor designed for beginners and experienced programmers alike. It provides a user-friendly interface with features such as syntax highlighting, code completion, and error checking. With Nanocoder, you can easily write and debug code in various programming languages, making it an ideal tool for learning, practicing, and developing software projects. Whether you are a student, hobbyist, or professional developer, Nanocoder offers a seamless coding experience to boost your productivity and creativity.
LEANN
LEANN is an innovative vector database that democratizes personal AI, transforming your laptop into a powerful RAG system that can index and search through millions of documents using 97% less storage than traditional solutions without accuracy loss. It achieves this through graph-based selective recomputation and high-degree preserving pruning, computing embeddings on-demand instead of storing them all. LEANN allows semantic search of file system, emails, browser history, chat history, codebase, or external knowledge bases on your laptop with zero cloud costs and complete privacy. It is a drop-in semantic search MCP service fully compatible with Claude Code, enabling intelligent retrieval without changing your workflow.
VITA
VITA is an open-source interactive omni multimodal Large Language Model (LLM) capable of processing video, image, text, and audio inputs simultaneously. It stands out with features like Omni Multimodal Understanding, Non-awakening Interaction, and Audio Interrupt Interaction. VITA can respond to user queries without a wake-up word, track and filter external queries in real-time, and handle various query inputs effectively. The model utilizes state tokens and a duplex scheme to enhance the multimodal interactive experience.
ragflow
RAGFlow is an open-source Retrieval-Augmented Generation (RAG) engine that combines deep document understanding with Large Language Models (LLMs) to provide accurate question-answering capabilities. It offers a streamlined RAG workflow for businesses of all sizes, enabling them to extract knowledge from unstructured data in various formats, including Word documents, slides, Excel files, images, and more. RAGFlow's key features include deep document understanding, template-based chunking, grounded citations with reduced hallucinations, compatibility with heterogeneous data sources, and an automated and effortless RAG workflow. It supports multiple recall paired with fused re-ranking, configurable LLMs and embedding models, and intuitive APIs for seamless integration with business applications.
unity-mcp
MCP for Unity is a tool that acts as a bridge, enabling AI assistants to interact with the Unity Editor via a local MCP Client. Users can instruct their LLM to manage assets, scenes, scripts, and automate tasks within Unity. The tool offers natural language control, powerful tools for asset management, scene manipulation, and automation of workflows. It is extensible and designed to work with various MCP Clients, providing a range of functions for precise text edits, script management, GameObject operations, and more.
context7
Context7 is a powerful tool for analyzing and visualizing data in various formats. It provides a user-friendly interface for exploring datasets, generating insights, and creating interactive visualizations. With advanced features such as data filtering, aggregation, and customization, Context7 is suitable for both beginners and experienced data analysts. The tool supports a wide range of data sources and formats, making it versatile for different use cases. Whether you are working on exploratory data analysis, data visualization, or data storytelling, Context7 can help you uncover valuable insights and communicate your findings effectively.
client-python
The Mistral Python Client is a tool inspired by cohere-python that allows users to interact with the Mistral AI API. It provides functionalities to access and utilize the AI capabilities offered by Mistral. Users can easily install the client using pip and manage dependencies using poetry. The client includes examples demonstrating how to use the API for various tasks, such as chat interactions. To get started, users need to obtain a Mistral API Key and set it as an environment variable. Overall, the Mistral Python Client simplifies the integration of Mistral AI services into Python applications.
speech-to-speech
This repository implements a speech-to-speech cascaded pipeline with consecutive parts including Voice Activity Detection (VAD), Speech to Text (STT), Language Model (LM), and Text to Speech (TTS). It aims to provide a fully open and modular approach by leveraging models available on the Transformers library via the Hugging Face hub. The code is designed for easy modification, with each component implemented as a class. Users can run the pipeline either on a server/client approach or locally, with detailed setup and usage instructions provided in the readme.
open-edison
OpenEdison is a secure MCP control panel that connects AI to data/software with additional security controls to reduce data exfiltration risks. It helps address the lethal trifecta problem by providing visibility, monitoring potential threats, and alerting on data interactions. The tool offers features like data leak monitoring, controlled execution, easy configuration, visibility into agent interactions, a simple API, and Docker support. It integrates with LangGraph, LangChain, and plain Python agents for observability and policy enforcement. OpenEdison helps gain observability, control, and policy enforcement for AI interactions with systems of records, existing company software, and data to reduce risks of AI-caused data leakage.
Unity-MCP
Unity-MCP is an AI helper designed for game developers using Unity. It facilitates a wide range of tasks in Unity Editor and running games on any platform by connecting to AI via TCP connection. The tool allows users to chat with AI like with a human, supports local and remote usage, and offers various default AI tools. Users can provide detailed information for classes, fields, properties, and methods using the 'Description' attribute in C# code. Unity-MCP enables instant C# code compilation and execution, provides access to assets and C# scripts, and offers tools for proper issue understanding and project data manipulation. It also allows users to find and call methods in the codebase, work with Unity API, and access human-readable descriptions of code elements.
obsei
Obsei is an open-source, low-code, AI powered automation tool that consists of an Observer to collect unstructured data from various sources, an Analyzer to analyze the collected data with various AI tasks, and an Informer to send analyzed data to various destinations. The tool is suitable for scheduled jobs or serverless applications as all Observers can store their state in databases. Obsei is still in alpha stage, so caution is advised when using it in production. The tool can be used for social listening, alerting/notification, automatic customer issue creation, extraction of deeper insights from feedbacks, market research, dataset creation for various AI tasks, and more based on creativity.
HuixiangDou
HuixiangDou is a **group chat** assistant based on LLM (Large Language Model). Advantages: 1. Design a two-stage pipeline of rejection and response to cope with group chat scenario, answer user questions without message flooding, see arxiv2401.08772 2. Low cost, requiring only 1.5GB memory and no need for training 3. Offers a complete suite of Web, Android, and pipeline source code, which is industrial-grade and commercially viable Check out the scenes in which HuixiangDou are running and join WeChat Group to try AI assistant inside. If this helps you, please give it a star โญ
For similar tasks
classifai
Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.
openai-edge-tts
This project provides a local, OpenAI-compatible text-to-speech (TTS) API using `edge-tts`. It emulates the OpenAI TTS endpoint (`/v1/audio/speech`), enabling users to generate speech from text with various voice options and playback speeds, just like the OpenAI API. `edge-tts` uses Microsoft Edge's online text-to-speech service, making it completely free. The project supports multiple audio formats, adjustable playback speed, and voice selection options, providing a flexible and customizable TTS solution for users.
metavoice-src
MetaVoice-1B is a 1.2B parameter base model trained on 100K hours of speech for TTS (text-to-speech). It has been built with the following priorities: * Emotional speech rhythm and tone in English. * Zero-shot cloning for American & British voices, with 30s reference audio. * Support for (cross-lingual) voice cloning with finetuning. * We have had success with as little as 1 minute training data for Indian speakers. * Synthesis of arbitrary length text
modelfusion
ModelFusion is an abstraction layer for integrating AI models into JavaScript and TypeScript applications, unifying the API for common operations such as text streaming, object generation, and tool usage. It provides features to support production environments, including observability hooks, logging, and automatic retries. You can use ModelFusion to build AI applications, chatbots, and agents. ModelFusion is a non-commercial open source project that is community-driven. You can use it with any supported provider. ModelFusion supports a wide range of models including text generation, image generation, vision, text-to-speech, speech-to-text, and embedding models. ModelFusion infers TypeScript types wherever possible and validates model responses. ModelFusion provides an observer framework and logging support. ModelFusion ensures seamless operation through automatic retries, throttling, and error handling mechanisms. ModelFusion is fully tree-shakeable, can be used in serverless environments, and only uses a minimal set of dependencies.
MeloTTS
MeloTTS is a high-quality multi-lingual text-to-speech library by MyShell.ai. It supports various languages including English (American, British, Indian, Australian), Spanish, French, Chinese, Japanese, and Korean. The Chinese speaker also supports mixed Chinese and English. The library is fast enough for CPU real-time inference and offers features like using without installation, local installation, and training on custom datasets. The Python API and model cards are available in the repository and on HuggingFace. The community can join the Discord channel for discussions and collaboration opportunities. Contributions are welcome, and the library is under the MIT License. MeloTTS is based on TTS, VITS, VITS2, and Bert-VITS2.
call-gpt
Call GPT is a voice application that utilizes Deepgram for Speech to Text, elevenlabs for Text to Speech, and OpenAI for GPT prompt completion. It allows users to chat with ChatGPT on the phone, providing better transcription, understanding, and speaking capabilities than traditional IVR systems. The app returns responses with low latency, allows user interruptions, maintains chat history, and enables GPT to call external tools. It coordinates data flow between Deepgram, OpenAI, ElevenLabs, and Twilio Media Streams, enhancing voice interactions.
openedai-speech
OpenedAI Speech is a free, private text-to-speech server compatible with the OpenAI audio/speech API. It offers custom voice cloning and supports various models like tts-1 and tts-1-hd. Users can map their own piper voices and create custom cloned voices. The server provides multilingual support with XTTS voices and allows fixing incorrect sounds with regex. Recent changes include bug fixes, improved error handling, and updates for multilingual support. Installation can be done via Docker or manual setup, with usage instructions provided. Custom voices can be created using Piper or Coqui XTTS v2, with guidelines for preparing audio files. The tool is suitable for tasks like generating speech from text, creating custom voices, and multilingual text-to-speech applications.
MARS5-TTS
MARS5 is a novel English speech model (TTS) developed by CAMB.AI, featuring a two-stage AR-NAR pipeline with a unique NAR component. The model can generate speech for various scenarios like sports commentary and anime with just 5 seconds of audio and a text snippet. It allows steering prosody using punctuation and capitalization in the transcript. Speaker identity is specified using an audio reference file, enabling 'deep clone' for improved quality. The model can be used via torch.hub or HuggingFace, supporting both shallow and deep cloning for inference. Checkpoints are provided for AR and NAR models, with hardware requirements of 750M+450M params on GPU. Contributions to improve model stability, performance, and reference audio selection are welcome.
For similar jobs
sweep
Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.
teams-ai
The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.
ai-guide
This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.
classifai
Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.
chatbot-ui
Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.
BricksLLM
BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students
uAgents
uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.
griptape
Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.