Hermes Agent

NousResearch's Hermes Agent is an open-source autonomous agent that connects to a model endpoint, executes tasks, and improves over time via memory and learned skills. It speaks the OpenAI Chat Completions API, which optiq serve exposes by default.

1. Install Hermes Agent

# Official installer (macOS / Linux):
$ curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash
$ source ~/.zshrc   # or ~/.bashrc
$ hermes --version

Prefer not to curl | bash? Clone manually: git clone https://github.com/NousResearch/hermes-agent && cd hermes-agent && pip install -e .

2. Start optiq serve

$ optiq serve \
    --model mlx-community/Qwen3.5-9B-OptiQ-4bit \
    --mtp --mtp-depth 2 \
    --port 8080

3. Point Hermes at OptIQ

Easiest path is the interactive wizard, which writes ~/.hermes/cli-config.yaml for you:

$ hermes setup
# pick "custom" as provider, paste http://localhost:8080/v1 as base URL,
# paste your model id, and sk-optiq-local as API key.

$ hermes      # start interactive chat

Or skip the wizard with two env vars and a one-shot:

export CUSTOM_BASE_URL=http://localhost:8080/v1
export OPENAI_API_KEY=sk-optiq-local

$ hermes chat -q "List the python files here." \
    -m mlx-community/Qwen3.5-9B-OptiQ-4bit --provider custom --yolo

Confirm the endpoint with hermes status — Provider: Custom endpoint should appear.

Notes

• Tool use is core to Hermes: the agent's learn-from-skills loop depends on function-calling. Use a model trained with tool calling (Qwen3.5-9B-OptiQ and up, Hermes-3-Llama variants).
• Long-running sessions: Hermes accumulates memory in long context. Pair with --kv-config (see KV-quant serving) for decode speedup at 16k+.
• Streaming: works.
• --yolo: bypasses the per-tool approval prompt — required in non-interactive mode. Drop it for interactive sessions where you want to vet each tool call.
• Verified: tested against Hermes Agent v0.14.0 (2026.5.16) on macOS (Apple Silicon).