WoolBall C# SDK

JavaScript client for woolball server Transform idle browsers into a powerful distributed AI inference network For detailed examples and model lists, visit our GitHub repository.

This SDK is automatically generated by the Swagger Codegen project

Installation

NuGet

dotnet add package Woolball.CSharp.SDK

✨ What is Woolball?

Woolball Server is an open-source network server that orchestrates AI inference jobs across a distributed network of browser-based compute nodes. Instead of relying on expensive cloud infrastructure, harness the collective power of idle browsers to run AI models efficiently and cost-effectively.

🎯 Supported AI Tasks

🔧 Provider	🎯 Task	🤖 Models	📊 Status
Transformers.js	🎤 Speech-to-Text	ONNX Models	✅ Ready
Transformers.js	🔊 Text-to-Speech	ONNX Models	✅ Ready
Kokoro.js	🔊 Text-to-Speech	ONNX Models	✅ Ready
Transformers.js	🌐 Translation	ONNX Models	✅ Ready
Transformers.js	📝 Text Generation	ONNX Models	✅ Ready
WebLLM	📝 Text Generation	MLC Models	✅ Ready
MediaPipe	📝 Text Generation	LiteRT Models	✅ Ready

📖 API Reference

📖 Text Generation

Generate text with powerful language models

🤗 Transformers.js Provider

🤖 Available Models

Model	Quantization	Description
`HuggingFaceTB/SmolLM2-135M-Instruct`	`fp16`	Compact model for basic text generation
`HuggingFaceTB/SmolLM2-360M-Instruct`	`q4`	Balanced performance and size
`Mozilla/Qwen2.5-0.5B-Instruct`	`q4`	Efficient model for general tasks
`onnx-community/Qwen2.5-Coder-0.5B-Instruct`	`q8`	Specialized for code generation

💡 Example Usage

using IO.Swagger.Api;
using IO.Swagger.Client;
using System;

// Configure the API client
var api = new TextGenerationApi();
api.Configuration.BasePath = "http://localhost:9002";

// Text generation with Transformers.js
var input = "[{\"role\": \"system\", \"content\": \"You are a helpful assistant.\"}, {\"role\": \"user\", \"content\": \"What is the capital of Brazil?\"}]";

var response = api.TextGeneration(
  "transformers", // provider
  "HuggingFaceTB/SmolLM2-135M-Instruct", // model
  input, // input
  50, // topK
  1.0, // topP
  0.7, // temperature
  1.0, // repetitionPenalty
  "fp16", // dtype
  20, // maxLength
  250, // maxNewTokens
  0, // minLength
  null, // minNewTokens
  true, // doSample
  1, // numBeams
  0, // noRepeatNgramSize
  null, // contextWindowSize
  null, // slidingWindowSize
  null, // attentionSinkSize
  null, // frequencyPenalty
  null, // presencePenalty
  null, // bosTokenId
  null, // maxTokens
  null // randomSeed
);

Console.WriteLine("Response: " + response);

⚙️ Parameters

Parameter	Type	Default	Description
`model`	string	-	🤖 Model ID (e.g., "HuggingFaceTB/SmolLM2-135M-Instruct")
`dtype`	string	-	🔧 Quantization level (e.g., "fp16", "q4")
`max_length`	number	20	📏 Maximum length the generated tokens can have (includes input prompt)
`max_new_tokens`	number	null	🆕 Maximum number of tokens to generate, ignoring prompt length
`min_length`	number	0	📐 Minimum length of the sequence to be generated (includes input prompt)
`min_new_tokens`	number	null	🔢 Minimum numbers of tokens to generate, ignoring prompt length
`do_sample`	boolean	false	🎲 Whether to use sampling; use greedy decoding otherwise
`num_beams`	number	1	🔍 Number of beams for beam search. 1 means no beam search
`temperature`	number	1.0	🌡️ Value used to modulate the next token probabilities
`top_k`	number	50	🔝 Number of highest probability vocabulary tokens to keep for top-k-filtering
`top_p`	number	1.0	📊 If < 1, only tokens with probabilities adding up to top_p or higher are kept
`repetition_penalty`	number	1.0	🔄 Parameter for repetition penalty. 1.0 means no penalty
`no_repeat_ngram_size`	number	0	🚫 If > 0, all ngrams of that size can only occur once

🤖 WebLLM Provider

🤖 Available Models

Model	Description
`DeepSeek-R1-Distill-Qwen-7B-q4f16_1-MLC`	DeepSeek R1 distilled model with reasoning capabilities
`DeepSeek-R1-Distill-Llama-8B-q4f16_1-MLC`	DeepSeek R1 distilled Llama-based model
`SmolLM2-1.7B-Instruct-q4f32_1-MLC`	Compact instruction-following model
`Llama-3.1-8B-Instruct-q4f32_1-MLC`	Meta's Llama 3.1 8B instruction model
`Qwen3-8B-q4f32_1-MLC`	Alibaba's Qwen3 8B model

💡 Example Usage

using IO.Swagger.Api;
using IO.Swagger.Client;
using System;

// Configure the API client
var api = new TextGenerationApi();
api.Configuration.BasePath = "http://localhost:9002";

// Text generation with WebLLM
var input = "[{\"role\": \"system\", \"content\": \"You are a helpful assistant.\"}, {\"role\": \"user\", \"content\": \"What is the capital of Brazil?\"}]";

var response = api.TextGeneration(
  "webllm", // provider
  "DeepSeek-R1-Distill-Qwen-7B-q4f16_1-MLC", // model
  input, // input
  null, // topK
  0.95, // topP
  0.7, // temperature
  null, // repetitionPenalty
  null, // dtype
  null, // maxLength
  null, // maxNewTokens
  null, // minLength
  null, // minNewTokens
  null, // doSample
  null, // numBeams
  null, // noRepeatNgramSize
  null, // contextWindowSize
  null, // slidingWindowSize
  null, // attentionSinkSize
  null, // frequencyPenalty
  null, // presencePenalty
  null, // bosTokenId
  null, // maxTokens
  null // randomSeed
);

Console.WriteLine("Response: " + response);

⚙️ Parameters

Parameter	Type	Description
`model`	string	🤖 Model ID from MLC (e.g., "DeepSeek-R1-Distill-Qwen-7B-q4f16_1-MLC")
`provider`	string	🔧 Must be set to "webllm" when using WebLLM models
`context_window_size`	number	🪟 Size of the context window for the model
`sliding_window_size`	number	🔄 Size of the sliding window for attention
`attention_sink_size`	number	🎯 Size of the attention sink
`repetition_penalty`	number	🔄 Penalty for repeating tokens
`frequency_penalty`	number	📊 Penalty for token frequency
`presence_penalty`	number	👁️ Penalty for token presence
`top_p`	number	📈 If < 1, only tokens with probabilities adding up to top_p or higher are kept
`temperature`	number	🌡️ Value used to modulate the next token probabilities
`bos_token_id`	number	🏁 Beginning of sequence token ID (optional)

📱 MediaPipe Provider

🤖 Available Models

Model	Device Type	Description
`https://woolball.sfo3.cdn.digitaloceanspaces.com/gemma2-2b-it-cpu-int8.task`	CPU	Gemma2 2B model optimized for CPU inference
`https://woolball.sfo3.cdn.digitaloceanspaces.com/gemma2-2b-it-gpu-int8.bin`	GPU	Gemma2 2B model optimized for GPU inference
`https://woolball.sfo3.cdn.digitaloceanspaces.com/gemma3-1b-it-int4.task`	CPU/GPU	Gemma3 1B model with INT4 quantization
`https://woolball.sfo3.cdn.digitaloceanspaces.com/gemma3-4b-it-int4-web.task`	Web	Gemma3 4B model optimized for web deployment

💡 Example Usage

using IO.Swagger.Api;
using IO.Swagger.Client;
using System;

// Configure the API client
var api = new TextGenerationApi();
api.Configuration.BasePath = "http://localhost:9002";

// Text generation with MediaPipe
var input = "[{\"role\": \"system\", \"content\": \"You are a helpful assistant.\"}, {\"role\": \"user\", \"content\": \"Explain quantum computing in simple terms.\"}]";

var response = api.TextGeneration(
  "mediapipe", // provider
  "https://woolball.sfo3.cdn.digitaloceanspaces.com/gemma3-1b-it-int4.task", // model
  input, // input
  40, // topK
  null, // topP
  0.7, // temperature
  null, // repetitionPenalty
  null, // dtype
  null, // maxLength
  null, // maxNewTokens
  null, // minLength
  null, // minNewTokens
  null, // doSample
  null, // numBeams
  null, // noRepeatNgramSize
  null, // contextWindowSize
  null, // slidingWindowSize
  null, // attentionSinkSize
  null, // frequencyPenalty
  null, // presencePenalty
  null, // bosTokenId
  500, // maxTokens
  12345 // randomSeed
);

Console.WriteLine("Response: " + response);

⚙️ Parameters

Parameter	Type	Description
`model`	string	🤖 Model ID for MediaPipe LiteRT models on DigitalOcean Spaces
`provider`	string	🔧 Must be set to "mediapipe" when using MediaPipe models
`maxTokens`	number	🔢 Maximum number of tokens to generate
`randomSeed`	number	🎲 Random seed for reproducible results
`topK`	number	🔝 Number of highest probability vocabulary tokens to keep for top-k-filtering
`temperature`	number	🌡️ Value used to modulate the next token probabilities

🎤 Speech Recognition

Convert audio to text with Whisper models

🤖 Available Models

Model	Quantization	Description
`onnx-community/whisper-large-v3-turbo_timestamped`	`q4`	🎯 High accuracy with timestamps
`onnx-community/whisper-small`	`q4`	⚡ Fast processing

💡 Example Usage

using IO.Swagger.Api;
using IO.Swagger.Client;
using System;

// Configure the API client
var api = new TextGenerationApi();
api.Configuration.BasePath = "http://localhost:9002";

// Text generation with WebLLM
var input = "[{\"role\": \"system\", \"content\": \"You are a helpful assistant.\"}, {\"role\": \"user\", \"content\": \"What is the capital of Brazil?\"}]";

var response = api.TextGeneration(
  "webllm", // provider
  "DeepSeek-R1-Distill-Qwen-7B-q4f16_1-MLC", // model
  input, // input
  null, // topK
  0.95, // topP
  0.7, // temperature
  null, // repetitionPenalty
  null, // dtype
  null, // maxLength
  null, // maxNewTokens
  null, // minLength
  null, // minNewTokens
  null, // doSample
  null, // numBeams
  null, // noRepeatNgramSize
  null, // contextWindowSize
  null, // slidingWindowSize
  null, // attentionSinkSize
  null, // frequencyPenalty
  null, // presencePenalty
  null, // bosTokenId
  null, // maxTokens
  null // randomSeed
);

Console.WriteLine("Response: " + response);

⚙️ Parameters

Parameter	Type	Description
`model`	string	🤖 Model ID from Hugging Face (e.g., "onnx-community/whisper-large-v3-turbo_timestamped")
`dtype`	string	🔧 Quantization level (e.g., "q4")
`return_timestamps`	boolean \| 'word'	⏰ Return timestamps ("word" for word-level). Default is `false`.
`stream`	boolean	📡 Stream results in real-time. Default is `false`.
`chunk_length_s`	number	📏 Length of audio chunks to process in seconds. Default is `0` (no chunking).
`stride_length_s`	number	🔄 Length of overlap between consecutive audio chunks in seconds. If not provided, defaults to `chunk_length_s / 6`.
`force_full_sequences`	boolean	🎯 Whether to force outputting full sequences or not. Default is `false`.
`language`	string	🌍 Source language (auto-detect if null). Use this to potentially improve performance if the source language is known.
`task`	null \| 'transcribe' \| 'translate'	🎯 The task to perform. Default is `null`, meaning it should be auto-detected.
`num_frames`	number	🎬 The number of frames in the input audio.

🔊 Text-to-Speech

Generate natural speech from text

🤗 Transformers.js (MMS Models)

🤖 Available Models

Language	Model	Flag
English	`Xenova/mms-tts-eng`	🇺🇸
Spanish	`Xenova/mms-tts-spa`	🇪🇸
French	`Xenova/mms-tts-fra`	🇫🇷
German	`Xenova/mms-tts-deu`	🇩🇪
Portuguese	`Xenova/mms-tts-por`	🇵🇹
Russian	`Xenova/mms-tts-rus`	🇷🇺
Arabic	`Xenova/mms-tts-ara`	🇸🇦
Korean	`Xenova/mms-tts-kor`	🇰🇷

💡 Example Usage

using IO.Swagger.Api;
using IO.Swagger.Client;
using System;

// Configure the API client
var api = new TextGenerationApi();
api.Configuration.BasePath = "http://localhost:9002";

// Text generation with MMS
var input = "[{\"role\": \"system\", \"content\": \"You are a helpful assistant.\"}, {\"role\": \"user\", \"content\": \"What is the capital of Brazil?\"}]";

var response = api.TextGeneration(
  "transformers", // provider
  "HuggingFaceTB/SmolLM2-135M-Instruct", // model
  input, // input
  50, // topK
  1.0, // topP
  0.7, // temperature
  1.0, // repetitionPenalty
  "fp16", // dtype
  20, // maxLength
  250, // maxNewTokens
  0, // minLength
  null, // minNewTokens
  true, // doSample
  1, // numBeams
  0, // noRepeatNgramSize
  null, // contextWindowSize
  null, // slidingWindowSize
  null, // attentionSinkSize
  null, // frequencyPenalty
  null, // presencePenalty
  null, // bosTokenId
  null, // maxTokens
  null // randomSeed
);

Console.WriteLine("Response: " + response);

⚙️ Parameters

Parameter	Type	Description	Required For
`model`	string	🤖 Model ID	All providers
`dtype`	string	🔧 Quantization level (e.g., "q8")	All providers
`stream`	boolean	📡 Whether to stream the audio response. Default is `false`.	All providers

🐱 Kokoro (Premium Voices)

🤖 Available Models

Model	Quantization	Description
`onnx-community/Kokoro-82M-ONNX`	`q8`	High-quality English TTS with multiple voices
`onnx-community/Kokoro-82M-v1.0-ONNX`	`q8`	Alternative Kokoro model version

💡 Example Usage

using IO.Swagger.Api;
using IO.Swagger.Client;
using System;

// Configure the API client
var api = new TextGenerationApi();
api.Configuration.BasePath = "http://localhost:9002";

// Text generation with Kokoro
var input = "[{\"role\": \"system\", \"content\": \"You are a helpful assistant.\"}, {\"role\": \"user\", \"content\": \"What is the capital of Brazil?\"}]";

var response = api.TextGeneration(
  "webllm", // provider
  "DeepSeek-R1-Distill-Qwen-7B-q4f16_1-MLC", // model
  input, // input
  null, // topK
  0.95, // topP
  0.7, // temperature
  null, // repetitionPenalty
  null, // dtype
  null, // maxLength
  null, // maxNewTokens
  null, // minLength
  null, // minNewTokens
  null, // doSample
  null, // numBeams
  null, // noRepeatNgramSize
  null, // contextWindowSize
  null, // slidingWindowSize
  null, // attentionSinkSize
  null, // frequencyPenalty
  null, // presencePenalty
  null, // bosTokenId
  null, // maxTokens
  null // randomSeed
);

Console.WriteLine("Response: " + response);

⚙️ Parameters

Parameter	Type	Description	Required For
`model`	string	🤖 Model ID	Required
`dtype`	string	🔧 Quantization level (e.g., "q8")	Required
`voice`	string	🎭 Voice ID (see below)	Required
`stream`	boolean	📡 Whether to stream the audio response. Default is `false`.	Optional

🎭 Available Voice Options

🇺🇸 American Voices

👩 Female: af_heart, af_alloy, af_aoede, af_bella, af_jessica, af_nova, af_sarah
👨 Male: am_adam, am_echo, am_eric, am_liam, am_michael, am_onyx

🇬🇧 British Voices

👩 Female: bf_emma, bf_isabella, bf_alice, bf_lily
👨 Male: bm_george, bm_lewis, bm_daniel, bm_fable

🌐 Translation

Translate between 200+ languages

🤖 Available Models

Model	Quantization	Description
`Xenova/nllb-200-distilled-600M`	`q8`	🌍 Multilingual translation model supporting 200+ languages

💡 Example Usage

using IO.Swagger.Api;
using IO.Swagger.Client;
using System;

// Configure the API client
var api = new TextGenerationApi();
api.Configuration.BasePath = "http://localhost:9002";

// Translation example
var response = api.Translation(
  "Xenova/nllb-200-distilled-600M", // model
  "q8", // dtype
  "Hello, how are you today?", // input
  "eng_Latn", // srcLang
  "por_Latn" // tgtLang
);

Console.WriteLine("Translation: " + response);

🌍 Language Support

Uses FLORES200 format - supports 200+ languages!

⚙️ Parameters

Parameter	Type	Description
`model`	string	🤖 Model ID (e.g., "Xenova/nllb-200-distilled-600M")
`dtype`	string	🔧 Quantization level (e.g., "q8")
`srcLang`	string	🌍 Source language code in FLORES200 format (e.g., "eng_Latn")
`tgtLang`	string	🌍 Target language code in FLORES200 format (e.g., "por_Latn")

🤝 Contributing

We welcome contributions! Here's how you can help:

🐛 Report bugs via GitHub Issues
💡 Suggest features in our Discord
🔧 Submit PRs for improvements
📖 Improve documentation

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

Made with ❤️ by the Woolball team

🌟 Star us on GitHub • 💬 Join Discord

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.swagger-codegen		.swagger-codegen
docs		docs
src		src
.gitignore		.gitignore
.swagger-codegen-ignore		.swagger-codegen-ignore
IO.Swagger.sln		IO.Swagger.sln
README.md		README.md
mono_nunit_test.sh		mono_nunit_test.sh

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WoolBall C# SDK

Installation

NuGet

✨ What is Woolball?

🎯 Supported AI Tasks

📖 API Reference

📖 Text Generation

🤗 Transformers.js Provider

💡 Example Usage

⚙️ Parameters

🤖 WebLLM Provider

💡 Example Usage

⚙️ Parameters

📱 MediaPipe Provider

💡 Example Usage

⚙️ Parameters

🎤 Speech Recognition

🤖 Available Models

💡 Example Usage

⚙️ Parameters

🔊 Text-to-Speech

🤗 Transformers.js (MMS Models)

💡 Example Usage

⚙️ Parameters

🐱 Kokoro (Premium Voices)

💡 Example Usage

⚙️ Parameters

🌐 Translation

🤖 Available Models

💡 Example Usage

🌍 Language Support

⚙️ Parameters

🤝 Contributing

📄 License

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