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README.md
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README.md
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# localJarvis
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A fully local assistant using swarm of deepseek agents, with multiple capabilities such as code execution, web browsing, etc...
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# 🚀 agenticSeek: Local AI Assistant Powered by DeepSeek Agents
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THIS IS A WORK IN PROGRESS
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**A fully local AI assistant** using a swarm of DeepSeek agents, capable of:
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✅ **Code execution** (Python, Bash)
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✅ **Web browsing**
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✅ **Speech-to-text & text-to-speech**
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✅ **Self-correcting code execution**
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## Install
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> 🛠️ **Work in Progress** – Looking for contributors! 🚀
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- Make sure you have ollama installed on your machine
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- Install dependencies (`pip3 install -r requirements.txt`)
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---
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## Run fully local
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## 🌟 Why?
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Simplest way is to use ollama
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- First change the config.ini file to set the provider_name to `ollama` and provider_model to `deepseek-r1:7b`
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- In first terminal run `ollama serve`
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- In second terminal run `python3 main.py`
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- Ollama will download `deepseek-r1:7b` on your machine
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- 2 model are also downloaded:
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* For text to speech: `kokoro`
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* For speech to text: `distil-whisper/distil-medium.en`
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- type or say goodbye to exit.
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- **Privacy-first**: Runs 100% locally – **no data leaves your machine**
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- ️ **Voice-enabled**: Speak and interact naturally
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- **Self-correcting**: Automatically fixes its own code
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- **Multi-agent**: Use a swarm of agents to answer complex questions
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- **Web browsing (not implemented yet)**: Browse the web and search the internet
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- **Knowledge base (not implemented yet)**: Use a knowledge base to answer questions
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# Run model on another machine
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---
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- First change the config.ini file to set the provider_name to `server` and provider_model to `deepseek-r1:7b` (or higher)
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- On the machine that will run the model execute the script in stream_llm.py
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## Installation
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```
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python3 stream_llm.py
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### 1️⃣ **Install Dependencies**
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Make sure you have [Ollama](https://ollama.com/) installed, then run:
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```sh
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pip3 install -r requirements.txt
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```
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- In the config.ini file, set the provider_server_address to the ip address of the machine that will run the model.
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### 2️⃣ **Download Models**
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- On the machine that will run the assistant execute main.py
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Download the `deepseek-r1:7b` model from [DeepSeek](https://deepseek.com/models)
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```sh
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ollama pull deepseek-r1:7b
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```
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### 3️⃣ **Run the Assistant (Ollama)**
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Start the ollama server
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```sh
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ollama serve
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```
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Change the config.ini file to set the provider_name to `ollama` and provider_model to `deepseek-r1:7b`
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```sh
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python3 main.py
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```
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## Text to speech
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### 4️⃣ **Run the Assistant (Own Server)**
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If you want your AI to speak, run with the `--speak` option.
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On the other machine that will run the model execute the script in stream_llm.py
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```sh
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python3 stream_llm.py
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```
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python3 main.py --speak
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Get the ip address of the machine that will run the model
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```sh
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ip a | grep "inet " | grep -v 127.0.0.1 | awk '{print $2}' | cut -d/ -f1
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```
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Change the config.ini file to set the provider_name to `server` and provider_model to `deepseek-r1:7b`.
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Set the provider_server_address to the ip address of the machine that will run the model.
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## Current capabilities
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- All running locally
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- Reasoning with deepseek R1
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- Python code execution capabilities
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- Bash execution capabilities
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- Get feedback from python/bash interpreter attempt to fix code by itself.
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- Code execution capabilities (Python, Golang, C)
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- Shell control capabilities in bash
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- Will try to fix code by itself
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- Fast text-to-speech using kokoro.
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- Speech-to-text using distil-whisper/distil-medium.en
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- Web browsing (not implemented yet)
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- Knowledge base RAG (not implemented yet)
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