# Mnemosyne Validator — FastAgent + MCP configuration
#
# Secrets (api_key, MCP bearer tokens) live in fastagent.secrets.yaml
# (gitignored) and merge with this file at runtime.

# Local llama.cpp on Nyx (OpenAI-compatible). Override via
# fastagent.secrets.yaml if you want to point at a different model server.
default_model: openai.Qwen3.5-35B-A3B-UD-Q4_K_XL.gguf

# Capabilities for the model — Pallas registers it with fast-agent's
# ModelDatabase using these values. vision: true so we can validate image
# round-trip later (search returns image candidates by default).
model_capabilities:
  vision: true
  context_window: 192000
  max_output_tokens: 16384

# ── LLM Providers ───────────────────────────────────────────────────────────
openai:
  base_url: "http://nyx.helu.ca:22079/v1"

# ── MCP Servers ─────────────────────────────────────────────────────────────
mcp:
  servers:
    # Mnemosyne MCP server — Streamable HTTP at /mcp.
    # Default assumes the validator runs on the same host as Mnemosyne;
    # override the URL in fastagent.secrets.yaml or via Ansible if remote.
    mnemosyne:
      transport: http
      url: "http://localhost:22091/mcp"
      # Bearer token in fastagent.secrets.yaml (provisioned via
      # `python manage.py create_mcp_token <user>`).