AgenticSeek: Local AI Assistant Powered by Deepseek R1 Agents.

A fully local alternative to Manus AI, a voice-enabled AI assistant that codes, explores your filesystem, and correct it's mistakes all without sending a byte of data to the cloud. The goal of the project is to create a truly Jarvis like assistant using reasoning model such as deepseek R1.

🛠️ Work in Progress – Looking for contributors! 🚀

---

Features:

• Privacy-first: Runs 100% locally – no data leaves your machine
• ️Voice-enabled: Speak and interact naturally
• Filesystem interaction: Use bash to interact with your filesystem.
• Coding abilities: Code in Python, C, Golang, and soon more
• Trial-and-error: If a command or code fails, the assistant retries to fixes it automatically, saving you time.
• Agent routing: Select the best agent for the task
• Multi-agent (On Dev branch): For complex tasks, divide and conquer with multiple agents
• Tools:: All agents have their respective tools ability. Basic search, flight API, files explorer, etc...
• Web browsing (not implemented yet | Hight priority task): Browse the web autonomously to conduct task.
• Memory&Recovery: Compress conversation over time to retain useful information, recover conversation session.

---

Run locally

We recommend using at least Deepseek 14B—smaller models struggle with tool use and memory retention.

1️⃣ Install Dependencies

Install requirements

sudo apt-get update
pip3 install -r requirements.txt

Install chromedriver

# linux
pip install selenium

# macos
brew install --cask chromedriver

# windows
https://sites.google.com/chromium.org/driver/getting-started

Install pyAudio

# linux
sudo apt-get install portaudio19-dev python3-dev

#macos
brew install portaudio

2️⃣ Download Models

Make sure you have Ollama installed.

Download the deepseek-r1:7b model from DeepSeek

ollama pull deepseek-r1:7b

3️⃣ Run the Assistant (Ollama)

Start the ollama server

ollama serve

Change the config.ini file to set the provider_name to ollama and provider_model to deepseek-r1:7b

[MAIN]
is_local = True
provider_name = ollama
provider_model = deepseek-r1:7b

Run the assistant:

python3 main.py

Alternative: Run the LLM on your own server

1️⃣ Set up and start the server scripts

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

Clone the repository and then, run the script stream_llm.py in server/

python3 stream_llm.py

2️⃣ Run it

Now on your personal computer:

Clone the repository.

Change the config.ini file to set the provider_name to server and provider_model to deepseek-r1:7b. 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-r1:14b
provider_server_address = x.x.x.x:5000

Run the assistant:

python3 main.py

Providers

The table below show the available providers:

Provider	Local?	Description
Ollama	Yes	Run LLMs locally with ease using ollama as a LLM provider
Server	Yes	Host the model on another machine, run your local machine
OpenAI	No	Use ChatGPT API (non-private)
Deepseek	No	Deepseek API (non-private)
HuggingFace	No	Hugging-Face API (non-private)

To select a provider change the config.ini:

is_local = False
provider_name = openai
provider_model = gpt-4o
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 its 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.

Current contributor:

Fosowl 🇫🇷 steveh8758 🇹🇼