Ollama-Chat-Server

A lightweight chat server that leverages Ollama (LLM API) to generate intelligent, conversational responses. Designed for easy local deployment and multi-client support, this project is ideal for experimenting with LLM chatbots or building custom chat applications.

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screenshots

Features

• Multi-client Chat Server: Supports multiple concurrent clients via TCP sockets.
• LLM-Powered Responses: Integrates with Ollama for AI-generated replies.
• Customizable System Prompt: Define the assistant's personality and behavior.
• Simple Python Clients: Two ready-to-use client scripts for easy testing.

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Getting Started

Prerequisites

• Python 3.10+
• miniconda
• Ollama

Installation

Install Python Using Miniconda

1. Download and install MiniConda from here

2. Create a new environment using the following command:

conda create --name ollama_chat_server python=3.10 -y

3. Activate the environment:

conda activate ollama_chat_server

4. Install dependencies:

pip install -r requirements.txt

5. Clone the repository:

git clone https://github.com/24-mohamedyehia/Ollama-Chat-Server.git

Install Ollama

1. Download and install Ollama from here.

Running the Server

1. Start your Ollama server (ensure the model specified in src/base_server.py is available).

2. Run the chat server:

   python src/base_server.py

Running a Client

Open a new terminal and run either client:

python src/client_one.py
# or
python src/client_two.py

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Usage

• Type your message and press Enter.
• Type exit to end the session.
• The server will respond with an AI-generated reply, always in English, concise, and with emojis.

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Configuration

• Model: Change the model_llm variable in src/base_server.py to use a different Ollama model.
• System Prompt: Customize the system_message variable to alter the assistant's behavior.
• Port: The server listens on localhost:12345 by default. Edit in start_server() if needed.
• Environment: Use the .env or .env.example files if you want to manage environment variables (not strictly required for default setup).

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Technologies Used

• Python (socket, threading, requests)
• Ollama (LLM server)
• colorama (for colored client output)

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License

This project is licensed under MIT License - see the LICENSE file in this repository.

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Acknowledgements

• Ollama for the LLM API
• Developed by Mohamed Yehia