agenticSeek/README.md

# AgenticSeek: Danus-like AI powered by Deepseek R1 Agents.

**A fully local alternative to Manus AI**, a voice-enabled AI assistant that codes, explores your filesystem, browse the web 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! 🚀  

![alt text](./exemples/whale_readme.jpg)

---

## 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 planning**: 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)**: Browse the web autonomously to conduct task.
- **Memory**: Retain only useful information, recover conversation session, remember your preferences.

---

## Run locally on your machine

**We recommend using at least Deepseek 14B, smaller models struggle with tool use and forget quickly the context.**

### 1️⃣ **Install Dependencies**  
```sh
pip3 install -r requirements.txt
```

### 2️⃣ **Download Models**  

Make sure you have [Ollama](https://ollama.com/) installed.

Download the `deepseek-r1:7b` model from [DeepSeek](https://deepseek.com/models)

```sh
ollama pull deepseek-r1:7b
```

### 3️⃣ **Run the Assistant (Ollama)**  

Start the ollama server
```sh
ollama serve
```

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

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

Run the assistant:

```sh
python3 main.py
```

## **Alternative: Run the LLM on your own server**  

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. 

### 1️⃣  **Set up and start the server scripts** 

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

```sh
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/`

```sh
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.

```sh
[MAIN]
is_local = False
provider_name = server
provider_model = deepseek-r1:14b
provider_server_address = x.x.x.x:5000
```

Run the assistant:

```sh
python3 main.py
```

## **Run with an API**  

Clone the repository.

Set the desired provider in the `config.ini`

```sh
[MAIN]
is_local = False
provider_name = openai
provider_model = gpt4-o
provider_server_address = 127.0.0.1:5000 # can be set to anything, not used
```

Run the assistant:

```sh
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.

## FAQ
**Q: What hardware do I need?**  

For Deepseek R1 7B, we recommend a  GPU with with 8GB VRAM.
The 14B model can run on 12GB GPU like the rtx 3060.
The 32B model needs a GPU with 24GB+ VRAM.

**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 `main.py`. What do I do?**  

Ensure Ollama 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 or Server providers, all speech to text, LLM and text to speech model run locally. Non-local options (OpenAI, Deepseek API) are optional.

**Q: How come it is older than manus ?**

we started this a fun side project to make a fully local, Jarvis-like AI. However, with the rise of Manus and openManus, we saw the opportunity to redirected some tasks priority to make yet another alternative.

**Q: How is it better than manus or openManus ?**

It's not, never will be, we just offer an alternative that is more local and enjoyable to use.

## Current contributor:

Fosowl 🇫🇷
steveh8758 🇹🇼