Moirae/moirae/scripts/example.yaml at main · peteromallet/Moirae · GitHub

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# Example Hermes Agent demo screenplay
# Run with: python demo/player.py moirae/scripts/example.yaml

title: "Hermes Agent Demo"
typing_speed: 0.04
pause_between: 1.0

scenes:
  # ── Launch the agent ──────────────────────────────────
  - action: clear

  - action: type_command
    prefix: "~ $ "
    command: "hermes"

  - action: pause
    duration: 0.5

  - action: banner
    model: "deephermes-3-llama-3.1-8b"
    context: "128K"
    session_id: "d8f2a1c4"
    tools_count: 24
    skills_count: 42

  - action: pause
    duration: 1.5

  # ── First exchange: web search ────────────────────────
  - user: "What are the latest developments in AI agents?"
    thinking_time: 3.5
    tools:
      - icon: "🔍"
        verb: "search"
        detail: '"latest developments AI agents 2026"'
        duration: "2.1s"
        delay: 0.3
      - icon: "📄"
        verb: "fetch"
        detail: "arxiv.org/abs/2603.12847"
        duration: "1.8s"
        delay: 0.3
      - icon: "📄"
        verb: "fetch"
        detail: "techcrunch.com/2026/03/12/..."
        duration: "1.2s"
        delay: 0.2
    response: |
      Here are the key developments in AI agents as of March 2026:

      **1. Multi-Agent Orchestration** — New frameworks allow agents to
      coordinate on complex tasks, with each agent specializing in different
      domains (code, research, communication).

      **2. Tool-Use Improvements** — Models now reliably chain 10+ tool
      calls with error recovery, making real-world automation practical.

      **3. Long-Running Agents** — Agents can now maintain context across
      hours-long sessions with persistent memory and session resumption.

      Want me to dive deeper into any of these areas?

  # ── Second exchange: code task ────────────────────────
  - user: "Write a Python function that fetches and summarizes a webpage"
    thinking_time: 4.0
    tools:
      - icon: "✍️"
        verb: " write"
        detail: "src/summarize.py"
        duration: "0.8s"
        delay: 0.2
    response: |
      I've created `src/summarize.py` with a `fetch_and_summarize()` function:

      ```python
      import httpx
      from bs4 import BeautifulSoup

      async def fetch_and_summarize(url: str, max_length: int = 500) -> str:
          async with httpx.AsyncClient() as client:
              resp = await client.get(url, follow_redirects=True)
              resp.raise_for_status()

          soup = BeautifulSoup(resp.text, "html.parser")
          # Extract main content, strip boilerplate
          for tag in soup(["script", "style", "nav", "footer"]):
              tag.decompose()

          text = soup.get_text(separator=" ", strip=True)
          return text[:max_length] + "..." if len(text) > max_length else text
      ```

      The function uses `httpx` for async HTTP and `BeautifulSoup` for HTML
      parsing. It strips scripts, styles, and navigation before extracting text.

  # ── Third exchange: terminal command ──────────────────
  - user: "Run the tests to make sure everything passes"
    thinking_time: 2.5
    tools:
      - icon: "💻"
        verb: "$"
        detail: "pytest tests/ -v --tb=short"
        duration: "4.2s"
        delay: 0.4
    response: |
      All tests pass:

      ```
      tests/test_summarize.py::test_fetch_success     PASSED
      tests/test_summarize.py::test_html_cleanup       PASSED
      tests/test_summarize.py::test_max_length          PASSED
      tests/test_summarize.py::test_redirect_handling    PASSED

      4 passed in 1.23s
      ```

      Everything looks good — the summarizer handles redirects, HTML cleanup,
      and length truncation correctly.