🤖 Ollama AI Chat Example

Interactive AI chat interface powered by Ollama with real-time streaming responses. Demonstrates Falcon's excellent streaming capabilities combined with AI/LLM integration for responsive conversational AI.

💬 Try the AI Chat

Start a conversation with the AI below. Watch as responses stream in real-time, token by token!

🔧 Technical Implementation

• Ollama Integration: Uses async-ollama gem for local LLM inference.
• Streaming Responses: Real-time AI response streaming via WebSocket.
• Live::View Framework: Real-time UI updates without page refreshes.
• Persistent Conversations: Chat history stored in database with models.
• Markdown Rendering: AI responses rendered with Markly for rich formatting.

📋 Key Files

• lib/ollama_tag.rb - OllamaTag - Live::View AI chat implementation
• app/controllers/ollama_controller.rb - OllamaController - WebSocket connection handling
• app/models/conversation.rb - Conversation - Chat conversation management
• app/models/conversation_message.rb - ConversationMessage - Individual message storage

🚀 Performance Benefits

AI responses can take several seconds to generate. Falcon's streaming capabilities allow showing partial responses as they're generated, creating a much more responsive user experience compared to waiting for complete responses.

🎯 Key Features

• Token-by-Token Streaming: Responses appear character by character
• Conversation Memory: AI remembers context from previous messages
• Rich Formatting: Supports markdown in AI responses
• Real-time Updates: UI updates live as AI generates responses

⚙️ Setup Requirements

• Ollama Server: Must have Ollama running locally with a model installed.
• Model Installation: Run ollama pull llama2 or similar to install an AI model.
• Database: Conversations and messages are persisted to database.