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A multilingual chat assistant that runs fully inside your browser through WebAssembly, so your messages stay on your device. Also reachable through Ollama and a local API.
SADIK AI is a kit in the Productivity category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page, a zip of its files. Nothing in it runs by itself.
pip install -U huggingface_hub hf download SadikNawazAI/Sadik-AI-Chat --repo-type space --local-dir Sadik-AI-Chat cd Sadik-AI-Chat
SADIK AI is a multilingual chat assistant by Sadik Nawaz. This Space runs the whole model inside your web browser, using the wllama WebAssembly engine built on llama.cpp. No server does the thinking, and the README says it works on phones and on desktops.
The model behind it is named SadikNawazAI/sadik-ai-model. The README also shows other ways to call the same model from code.
It suits people who want a chat assistant that stays on their own device, and developers who want to see a language model run in a web page.
| Industry | Who uses it | How they use it | Example |
|---|---|---|---|
| Everyday use | Multilingual users | Chat with an assistant in their own language | A user greets the assistant in Hindi and reads the reply |
| Software | Web developers | Study how a model runs through WebAssembly in a page | A developer reads app.js and the wllama folder |
| Education | Students | Try a language model without any server or account | A student opens the page on a laptop and asks a question |
| AI engineering | Developers | Call the model through Ollama or a local chat API | A developer runs it with one Ollama command |
You can skip it if you need a hosted API, since the README's API examples point to servers you run yourself.
You use it in these places.
| Use case | Who | What they get back |
|---|---|---|
| Chat in the browser | Anyone | Replies from the model with no server involved |
| Call it from code | Developers | Chat replies through a local Ollama or chat completions endpoint |
| Borrow a GPU | Developers | A Colab notebook from the model repository that serves an API |
Online use needs only a browser. A local copy needs Python for the download step.
pip install -U huggingface_hub hf download SadikNawazAI/Sadik-AI-Chat --repo-type space --local-dir Sadik-AI-Chat cd Sadik-AI-Chat
Open the page and type a message in the chat box. The model answers in the same page. For the Ollama route, the README gives this single command.
ollama run hf.co/SadikNawazAI/sadik-ai-model
The README also shows a curl call to a local Ollama chat endpoint, and a Python call to a local chat completions endpoint that uses the model name sadik-ai. Both point to your own machine.
You open the page and type a short greeting, such as asking who the assistant is. The model replies in the chat box, and the README says the exchange stays on your machine.
A chat assistant normally runs on a company's server. This one runs inside your browser tab, so you can try it by just opening the page. Start with a short question in any language you like.
Under the hood, the engine is wllama, a WebAssembly build of llama.cpp, shipped in the repository's wllama folder, with the chat logic in app.js. It uses your CPU or GPU directly. The source does not say how big the model file is or where the browser fetches it from.
The README makes several claims about privacy and cost, and these are its own words.
A multilingual chat assistant that runs fully inside your browser through WebAssembly, so your messages stay on your device. Also reachable through Ollama and a local API.
Made by SadikNawazAI on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face.
What it is: SADIK AI is a multilingual chat assistant by Sadik Nawaz. This Space runs the whole model inside your web browser, using the wllama WebAssembly engine built on llama.cpp. No server does the thinking, and the README says it works on phones and on desktops.
The model behind it is named SadikNawazAI/sadik-ai-model. The README also shows other ways to call the same model from code.
Who it suits: It suits people who want a chat assistant that stays on their own device, and developers who want to see a language model run in a web page.
Industry | Who uses it | How they use it | Example
Everyday use | Multilingual users | Chat with an assistant in their own language | A user greets the assistant in Hindi and reads the reply
Software | Web developers | Study how a model runs through WebAssembly in a page | A developer reads app.js and the wllama folder
Education | Students | Try a language model without any server or account | A student opens the page on a laptop and asks a question
AI engineering | Developers | Call the model through Ollama or a local chat API | A developer runs it with one Ollama command
You can skip it if you need a hosted API, since the README's API examples point to servers you run yourself.
Where to use it: You use it in these places.
Use case | Who | What they get back
Chat in the browser | Anyone | Replies from the model with no server involved
Call it from code | Developers | Chat replies through a local Ollama or chat completions endpoint
Borrow a GPU | Developers | A Colab notebook from the model repository that serves an API
How to set it up: Online use needs only a browser. A local copy needs Python for the download step.
pip install -U huggingface_hub
hf download SadikNawazAI/Sadik-AI-Chat --repo-type space --local-dir Sadik-AI-Chat
cd Sadik-AI-Chat
How to use it: Open the page and type a message in the chat box. The model answers in the same page. For the Ollama route, the README gives this single command.
ollama run hf.co/SadikNawazAI/sadik-ai-model
The README also shows a curl call to a local Ollama chat endpoint, and a Python call to a local chat completions endpoint that uses the model name sadik-ai. Both point to your own machine.
Example: You open the page and type a short greeting, such as asking who the assistant is. The model replies in the chat box, and the README says the exchange stays on your machine.
For newcomers and experts: A chat assistant normally runs on a company's server. This one runs inside your browser tab, so you can try it by just opening the page. Start with a short question in any language you like.
Under the hood, the engine is wllama, a WebAssembly build of llama.cpp, shipped in the repository's wllama folder, with the chat logic in app.js. It uses your CPU or GPU directly. The source does not say how big the model file is or where the browser fetches it from.
You open the page in a browser
wllama loads the model in WebAssembly
You type a message
The model answers on your own device
Good to know: The README makes several claims about privacy and cost, and these are its own words.
Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself.
README.md 5 KB
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