{
  "session_id": "20260330_151804_232a26",
  "model": "claude-opus-4.6",
  "base_url": "https://api.anthropic.com",
  "platform": "telegram",
  "session_start": "2026-03-30T15:18:04.542923",
  "last_updated": "2026-03-30T15:19:27.024066",
  "system_prompt": "You are Hermes Agent, an intelligent AI assistant created by Nous Research. You are helpful, knowledgeable, and direct. You assist users with a wide range of tasks including answering questions, writing and editing code, analyzing information, creative work, and executing actions via your tools. You communicate clearly, admit uncertainty when appropriate, and prioritize being genuinely useful over being verbose unless otherwise directed below. Be targeted and efficient in your exploration and investigations.\n\nConversation started: Monday, March 30, 2026 03:18 PM\nModel: claude-opus-4.6\nProvider: anthropic\n\nYou are on a text messaging communication platform, Telegram. Please do not use markdown as it does not render. You can send media files natively: to deliver a file to the user, include MEDIA:/absolute/path/to/file in your response. Images (.png, .jpg, .webp) appear as photos, audio (.ogg) sends as voice bubbles, and videos (.mp4) play inline. You can also include image URLs in markdown format ![alt](url) and they will be sent as native photos.",
  "tools": [],
  "message_count": 1,
  "messages": [
    {
      "role": "user",
      "content": "Research Evennia (the Python MUD/MUX framework at evennia.com). I need to understand: 1) What is Evennia's architecture — how does it handle objects, commands, scripts, and typeclasses? 2) How could Evennia be used as an orchestration layer for AI agents — specifically as a 'world' where wizard agents live, receive tasks, manage state, and interact? 3) What are Evennia's built-in concepts that map well to agent workflows: rooms as contexts, objects as artifacts, scripts as scheduled tasks, commands as tools? 4) How does Evennia handle persistence, message passing, and extensibility? 5) What would it take to embed a local LLM agent (like one using llama.cpp) as an Evennia character that can receive commands, use tools, and produce outputs? Give me a thorough technical summary."
    }
  ]
}