OllamaChat Lounge 🤖💬

An interactive platform that combines OpenAI's Swarm framework with Ollama to orchestrate dynamic conversations between AI agents. Watch as two AI personalities engage in natural discussions using local language models!

Features ✨

• Elegant Setup Interface:

  • Beautiful UI with easy-to-use tabs
  • Simple model selection dropdowns for each agent
  • Intuitive conversation configuration

• Multi-Model Support:

  • Mix and match different Llama models (e.g., llama3.2:3b for Alice, llama3.2:1b for Bob)
  • Experiment with different model combinations
  • Compare how different model variants handle the same conversation

• Rich Personality Configuration:

  • Define detailed agent personalities (e.g., movie expert vs. movie skeptic)
  • Set specific conversation topics
  • Create natural debate scenarios

• Powered by Swarm: Utilizes OpenAI's Swarm framework for robust agent interaction

• Local LLM Integration: Seamlessly connects with Ollama for local language model inference

• Real-time Chat: Watch the conversation unfold in real-time with a beautiful chat interface

• Model Management: Download and manage Ollama models directly from the interface

• Debug Tools: Built-in debugging features to monitor the conversation flow

Prerequisites 🔧

• Python 3.10+
• Ollama installed and running locally
• OpenAI Swarm
• Streamlit
• Network connectivity for downloading models

Installation 🚀

1. Clone the repository:

git clone https://github.com/dwain-barnes/ollamachat-lounge.git
cd ollamachat-arena

2. Install required packages:

pip install -r requirements.txt

3. Make sure Ollama is installed and running on your system:

• Install Ollama
• Run the Ollama service

4. Launch the application:

streamlit run main.py

Setup Guide 🎯

1. Select Models

• Choose from available Ollama models for each agent
• Current UI supports different Llama model variants
• Mix and match models of different sizes

2. Configure Conversation

• Set a conversation topic (e.g., "The Value of Movies in Society")
• Define unique personalities for each agent:
  • Alice: "Movie expert, enthusiastic and well-informed"
  • Bob: "Movie skeptic, questioning traditional entertainment"
• Save your configuration before starting

3. Start Chatting

• Click "Start Chat" to begin the conversation
• Watch as agents interact based on their defined personalities
• Monitor the conversation flow in real-time

Example Configuration 💡

# As shown in screenshots
Topic: "The Value of Movies in Society"

Alice:
- Model: llama3.2:3b
- Personality: "Movie expert, enthusiastic about film's positive impact"

Bob:
- Model: llama3.2:1b
- Personality: "Skeptical about movies, questions entertainment value"

Available Models 🧠

Compatible with various Ollama models including:

• Llama3 (various sizes)
• Mistral
• CodeLlama
• Neural-Chat
• Starling-LM
• Orca-Mini
• Vicuna
• Zephyr

Technical Architecture 🏗️

OllamaChat Arena combines three powerful technologies:

• OpenAI Swarm: Handles agent communication and conversation flow
• Ollama: Provides local inference capabilities for various open-source language models
• Streamlit: Creates the beautiful UI and handles real-time updates

Troubleshooting 🔍

Common issues and solutions:

1. Model Loading Errors:

   • Ensure Ollama is running (ollama serve)
   • Check available models (ollama list)
   • Verify model is downloaded (ollama pull model_name)

2. Conversation Stalls:

   • Check Ollama service status
   • Monitor system resources
   • Try restarting the application

3. Model Switching Issues:

   • Clear chat history before switching models
   • Ensure both models are fully downloaded
   • Check model compatibility

Contributing 🤝

Contributions are welcome! Please feel free to submit pull requests, create issues, or suggest improvements.

License 📄

MIT License - feel free to use this project however you'd like!

Acknowledgments 🙏

• Built with OpenAI Swarm
• Powered by Ollama
• Created with Streamlit