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A 100% local alternative to Manus AI, this voice-enabled AI assistant autonomously browses the web, writes code, and plans tasks while keeping all data on your device. Tailored for local reasoning models, it runs entirely on your hardware, ensuring complete privacy and zero cloud dependency.

• 🔒 Fully Local & Private - Everything runs on your machine — no cloud, no data sharing. Your files, conversations, and searches stay private.

• 🌐 Smart Web Browsing - AgenticSeek can browse the internet by itself — search, read, extract info, fill web form — all hands-free.

• 💻 Autonomous Coding Assistant - Need code? It can write, debug, and run programs in Python, C, Go, Java, and more — all without supervision.

• 🧠 Smart Agent Selection - You ask, it figures out the best agent for the job automatically. Like having a team of experts ready to help.

• 📋 Plans & Executes Complex Tasks - From trip planning to complex projects — it can split big tasks into steps and get things done using multiple AI agents.

• 🎙️ Voice-Enabled - Clean, fast, futuristic voice and speech to text allowing you to talk to it like it's your personal AI from a sci-fi movie

Can you search for the agenticSeek project, learn what skills are required, then open the CV_candidates.zip and then tell me which match best the project

Disclaimer: This demo, including all the files that appear (e.g: CV_candidates.zip), are entirely fictional. We are not a corporation, we seek open-source contributors not candidates.

🛠️ Work in Progress – Looking for contributors!

Make sure you have chrome driver, docker and python3.10 (or newer) installed.

For issues related to chrome driver, see the Chromedriver section.

git clone https://github.com/Fosowl/agenticSeek.git
cd agenticSeek
mv .env.example .env

python3 -m venv agentic_seek_env
source agentic_seek_env/bin/activate     
# On Windows: agentic_seek_env\Scripts\activate

Automatic Installation (Recommanded):

For Linux/Macos:

For windows:

Manually:

First, you need to install these packages:

Updates package list (apt-get update).

Install these: alsa-utils, portaudio19-dev, python3-pyaudio, libgtk-3-dev, libnotify-dev, libgconf-2-4, libnss3, libxss1, selenium

Make sure to install docker + docker-compose if not already.

Update package list. Install chromedriver. Install portaudio. Install chromedriver and selenium.

Install pyreadline3, selenium portaudio, pyAudio and chromedriver

Then install pip requirements:

pip3 install -r requirements.txt
# or
python3 setup.py install

We recommend using at the very least Deepseek 14B, smaller models will struggle with tasks especially for web browsing.

Setup your local provider

Start your local provider, for example with ollama:

See below for a list of local supported provider.

Update the config.ini

Change the config.ini file to set the provider_name to a supported provider and provider_model to deepseek-r1:14b

NOTE: deepseek-r1:14bis an example, use a bigger model if your hardware allow it.

[MAIN]
is_local = True
provider_name = ollama # or lm-studio, openai, etc..
provider_model = deepseek-r1:14b
provider_server_address = 127.0.0.1:11434

List of local providers

Next step: Start services and run AgenticSeek

See the Known issues section if you are having issues

See the Run with an API section if your hardware can't run deepseek locally

See the Config section for detailled config file explanation.

Set the desired provider in the config.ini. See below for a list of API providers.

[MAIN]
is_local = False
provider_name = openai
provider_model = gpt-4o
provider_server_address = 127.0.0.1:5000

Warning: Make sure there is not trailing space in the config.

Export your API key: export <<PROVIDER>>_API_KEY="xxx"

Example: export TOGETHER_API_KEY="xxxxx"

List of API providers

Next step: Start services and run AgenticSeek

See the Known issues section if you are having issues

See the Config section for detailled config file explanation.

Activate your python env if needed.

source agentic_seek_env/bin/activate

Start required services. This will start all services from the docker-compose.yml, including: - searxng - redis (required by searxng) - frontend

sudo ./start_services.sh # MacOS
start ./start_services.cmd # Window

Options 1: Run with the CLI interface.

Options 2: Run with the Web interface.

Start the backend.

Go to http://localhost:3000/ and you should see the web interface.

Make sure the services are up and running with ./start_services.sh and run the AgenticSeek with python3 cli.py for CLI mode or python3 api.py then go to localhost:3000 for web interface.

You can also use speech to text by setting listen = True in the config. Only for CLI mode.

To exit, simply say/type goodbye.

Here are some example usage:

Make a snake game in python

Show me how to multiply matrice in C

Make a blackjack in golang

Do a web search to find cool tech startup in Japan working on cutting edge AI research

Can you find on the internet who created AgenticSeek?

Can you use a fuel calculator online to estimate the cost of a Nice - Milan trip

Hey can you find where is contract.pdf i lost it

Show me how much space I have left on my disk

Can you follow the readme and install project at /home/path/project

Tell me about Rennes, France

Should I pursue a phd ?

What's the best workout routine ?

After you type your query, AgenticSeek will allocate the best agent for the task.

Because this is an early prototype, the agent routing system might not always allocate the right agent based on your query.

Therefore, you should be very explicit in what you want and how the AI might proceed for example if you want it to conduct a web search, do not say:

Do you know some good countries for solo-travel?

Instead, ask:

Do a web search and find out which are the best country for solo-travel

If you have a powerful computer or a server that you can use, but you want to use it from your laptop you have the options to run the LLM on a remote server using our custom llm server.

On your "server" that will run the AI model, get the ip address

ip a | grep "inet " | grep -v 127.0.0.1 | awk '{print $2}' | cut -d/ -f1 # local ip
curl https://ipinfo.io/ip # public ip

Note: For Windows or macOS, use ipconfig or ifconfig respectively to find the IP address.

Clone the repository and enter the server/folder.

git clone --depth 1 https://github.com/Fosowl/agenticSeek.git
cd agenticSeek/server/

Install server specific requirements:

pip3 install -r requirements.txt

Run the server script.

python3 app.py --provider ollama --port 3333

You have the choice between using ollama and llamacpp as a LLM service.

Now on your personal computer:

Change the config.ini file to set the provider_name to server and provider_model to deepseek-r1:xxb. Set the provider_server_address to the ip address of the machine that will run the model.

[MAIN]
is_local = False
provider_name = server
provider_model = deepseek-r1:70b
provider_server_address = x.x.x.x:3333

Next step: Start services and run AgenticSeek

Please note that currently speech to text only work in english.

The speech-to-text functionality is disabled by default. To enable it, set the listen option to True in the config.ini file:

When enabled, the speech-to-text feature listens for a trigger keyword, which is the agent's name, before it begins processing your input. You can customize the agent's name by updating the agent_name value in the config.ini file:

For optimal recognition, we recommend using a common English name like "John" or "Emma" as the agent name

Once you see the transcript start to appear, say the agent's name aloud to wake it up (e.g., "Friday").

Speak your query clearly.

End your request with a confirmation phrase to signal the system to proceed. Examples of confirmation phrases include:

"do it", "go ahead", "execute", "run", "start", "thanks", "would ya", "please", "okay?", "proceed", "continue", "go on", "do that", "go it", "do you understand?"

Example config:

[MAIN]
is_local = True
provider_name = ollama
provider_model = deepseek-r1:32b
provider_server_address = 127.0.0.1:11434
agent_name = Friday
recover_last_session = False
save_session = False
speak = False
listen = False
work_dir =  /Users/mlg/Documents/ai_folder
jarvis_personality = False
languages = en zh
[BROWSER]
headless_browser = False
stealth_mode = False

Explanation:

• is_local -> Runs the agent locally (True) or on a remote server (False).

• provider_name -> The provider to use (one of: ollama, server, lm-studio, deepseek-api)

• provider_model -> The model used, e.g., deepseek-r1:32b.

• provider_server_address -> Server address, e.g., 127.0.0.1:11434 for local. Set to anything for non-local API.

• agent_name -> Name of the agent, e.g., Friday. Used as a trigger word for TTS.

• recover_last_session -> Restarts from last session (True) or not (False).

• save_session -> Saves session data (True) or not (False).

• speak -> Enables voice output (True) or not (False).

• listen -> listen to voice input (True) or not (False).

• work_dir -> Folder the AI will have access to. eg: /Users/user/Documents/.

• jarvis_personality -> Uses a JARVIS-like personality (True) or not (False). This simply change the prompt file.

• languages -> The list of supported language, needed for the llm router to work properly, avoid putting too many or too similar languages.

• headless_browser -> Runs browser without a visible window (True) or not (False).

• stealth_mode -> Make bot detector time harder. Only downside is you have to manually install the anticaptcha extension.

• languages -> List of supported languages. Required for agent routing system. The longer the languages list the more model will be downloaded.

The table below show the available providers:

To select a provider change the config.ini:

is_local = True
provider_name = ollama
provider_model = deepseek-r1:32b
provider_server_address = 127.0.0.1:5000

is_local: should be True for any locally running LLM, otherwise False.

provider_name: Select the provider to use by it's name, see the provider list above.

provider_model: Set the model to use by the agent.

provider_server_address: can be set to anything if you are not using the server provider.

Known error #1: chromedriver mismatch

Exception: Failed to initialize browser: Message: session not created: This version of ChromeDriver only supports Chrome version 113 Current browser version is 134.0.6998.89 with binary path

This happen if there is a mismatch between your browser and chromedriver version.

You need to navigate to download the latest version:

https://developer.chrome.com/docs/chromedriver/downloads

If you're using Chrome version 115 or newer go to:

https://googlechromelabs.github.io/chrome-for-testing/

And download the chromedriver version matching your OS.

If this section is incomplete please raise an issue.

Q: What hardware do I need?

Q: Why Deepseek R1 over other models?

Deepseek R1 excels at reasoning and tool use for its size. We think it’s a solid fit for our needs other models work fine, but Deepseek is our primary pick.

Q: I get an error running cli.py. What do I do?

Ensure local is running (ollama serve), your config.ini matches your provider, and dependencies are installed. If none work feel free to raise an issue.

Q: Can it really run 100% locally?

Yes with Ollama, lm-studio or server providers, all speech to text, LLM and text to speech model run locally. Non-local options (OpenAI or others API) are optional.

Q: Why should I use AgenticSeek when I have Manus?

This started as Side-Project we did out of interest about AI agents. What’s special about it is that we want to use local model and avoid APIs. We draw inspiration from Jarvis and Friday (Iron man movies) to make it "cool" but for functionnality we take more inspiration from Manus, because that's what people want in the first place: a local manus alternative. Unlike Manus, AgenticSeek prioritizes independence from external systems, giving you more control, privacy and avoid api cost.

We’re looking for developers to improve AgenticSeek! Check out open issues or discussion.

Contribution guide

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