hermes-agent/website/docs/user-guide/features/api-server.md
Teknium 252d68fd45
docs: deep audit — fix stale config keys, missing commands, and registry drift (#22784)
* docs: deep audit — fix stale config keys, missing commands, and registry drift

Cross-checked ~80 high-impact docs pages (getting-started, reference, top-level
user-guide, user-guide/features) against the live registries:

  hermes_cli/commands.py    COMMAND_REGISTRY (slash commands)
  hermes_cli/auth.py        PROVIDER_REGISTRY (providers)
  hermes_cli/config.py      DEFAULT_CONFIG (config keys)
  toolsets.py               TOOLSETS (toolsets)
  tools/registry.py         get_all_tool_names() (tools)
  python -m hermes_cli.main <subcmd> --help (CLI args)

reference/
- cli-commands.md: drop duplicate hermes fallback row + duplicate section,
  add stepfun/lmstudio to --provider enum, expand auth/mcp/curator subcommand
  lists to match --help output (status/logout/spotify, login, archive/prune/
  list-archived).
- slash-commands.md: add missing /sessions and /reload-skills entries +
  correct the cross-platform Notes line.
- tools-reference.md: drop bogus '68 tools' headline, drop fictional
  'browser-cdp toolset' (these tools live in 'browser' and are runtime-gated),
  add missing 'kanban' and 'video' toolset sections, fix MCP example to use
  the real mcp_<server>_<tool> prefix.
- toolsets-reference.md: list browser_cdp/browser_dialog inside the 'browser'
  row, add missing 'kanban' and 'video' toolset rows, drop the stale
  '38 tools' count for hermes-cli.
- profile-commands.md: add missing install/update/info subcommands, document
  fish completion.
- environment-variables.md: dedupe GMI_API_KEY/GMI_BASE_URL rows (kept the
  one with the correct gmi-serving.com default).
- faq.md: Anthropic/Google/OpenAI examples — direct providers exist (not just
  via OpenRouter), refresh the OpenAI model list.

getting-started/
- installation.md: PortableGit (not MinGit) is what the Windows installer
  fetches; document the 32-bit MinGit fallback.
- installation.md / termux.md: installer prefers .[termux-all] then falls
  back to .[termux].
- nix-setup.md: Python 3.12 (not 3.11), Node.js 22 (not 20); fix invalid
  'nix flake update --flake' invocation.
- updating.md: 'hermes backup restore --state pre-update' doesn't exist —
  point at the snapshot/quick-snapshot flow; correct config key
  'updates.pre_update_backup' (was 'update.backup').

user-guide/
- configuration.md: api_max_retries default 3 (not 2); display.runtime_footer
  is the real key (not display.runtime_metadata_footer); checkpoints defaults
  enabled=false / max_snapshots=20 (not true / 50).
- configuring-models.md: 'hermes model list' / 'hermes model set ...' don't
  exist — hermes model is interactive only.
- tui.md: busy_indicator -> tui_status_indicator with values
  kaomoji|emoji|unicode|ascii (not kawaii|minimal|dots|wings|none).
- security.md: SSH backend keys (TERMINAL_SSH_HOST/USER/KEY) live in .env,
  not config.yaml.
- windows-wsl-quickstart.md: there is no 'hermes api' subcommand — the
  OpenAI-compatible API server runs inside hermes gateway.

user-guide/features/
- computer-use.md: approvals.mode (not security.approval_level); fix broken
  ./browser-use.md link to ./browser.md.
- fallback-providers.md: top-level fallback_providers (not
  model.fallback_providers); the picker is subcommand-based, not modal.
- api-server.md: API_SERVER_* are env vars — write to per-profile .env,
  not 'hermes config set' which targets YAML.
- web-search.md: drop web_crawl as a registered tool (it isn't); deep-crawl
  modes are exposed through web_extract.
- kanban.md: failure_limit default is 2, not '~5'.
- plugins.md: drop hard-coded '33 providers' count.
- honcho.md: fix unclosed quote in echo HONCHO_API_KEY snippet; document
  that 'hermes honcho' subcommand is gated on memory.provider=honcho;
  reconcile subcommand list with actual --help output.
- memory-providers.md: legacy 'hermes honcho setup' redirect documented.

Verified via 'npm run build' — site builds cleanly; broken-link count went
from 149 to 146 (no regressions, fixed a few in passing).

* docs: round 2 audit fixes + regenerate skill catalogs

Follow-up to the previous commit on this branch:

Round 2 manual fixes:
- quickstart.md: KIMI_CODING_API_KEY mentioned alongside KIMI_API_KEY;
  voice-mode and ACP install commands rewritten — bare 'pip install ...'
  doesn't work for curl-installed setups (no pip on PATH, not in repo
  dir); replaced with 'cd ~/.hermes/hermes-agent && uv pip install -e
  ".[voice]"'. ACP already ships in [all] so the curl install includes it.
- cli.md / configuration.md: 'auxiliary.compression.model' shown as
  'google/gemini-3-flash-preview' (the doc's own claimed default);
  actual default is empty (= use main model). Reworded as 'leave empty
  (default) or pin a cheap model'.
- built-in-plugins.md: added the bundled 'kanban/dashboard' plugin row
  that was missing from the table.

Regenerated skill catalogs:
- ran website/scripts/generate-skill-docs.py to refresh all 163 per-skill
  pages and both reference catalogs (skills-catalog.md,
  optional-skills-catalog.md). This adds the entries that were genuinely
  missing — productivity/teams-meeting-pipeline (bundled),
  optional/finance/* (entire category — 7 skills:
  3-statement-model, comps-analysis, dcf-model, excel-author, lbo-model,
  merger-model, pptx-author), creative/hyperframes,
  creative/kanban-video-orchestrator, devops/watchers,
  productivity/shop-app, research/searxng-search,
  apple/macos-computer-use — and rewrites every other per-skill page from
  the current SKILL.md. Most diffs are tiny (one line of refreshed
  metadata).

Validation:
- 'npm run build' succeeded.
- Broken-link count moved 146 -> 155 — the +9 are zh-Hans translation
  shells that lag every newly-added skill page (pre-existing pattern).
  No regressions on any en/ page.
2026-05-09 13:19:51 -07:00

16 KiB

sidebar_position title description
14 API Server Expose hermes-agent as an OpenAI-compatible API for any frontend

API Server

The API server exposes hermes-agent as an OpenAI-compatible HTTP endpoint. Any frontend that speaks the OpenAI format — Open WebUI, LobeChat, LibreChat, NextChat, ChatBox, and hundreds more — can connect to hermes-agent and use it as a backend.

Your agent handles requests with its full toolset (terminal, file operations, web search, memory, skills) and returns the final response. When streaming, tool progress indicators appear inline so frontends can show what the agent is doing.

Quick Start

1. Enable the API server

Add to ~/.hermes/.env:

API_SERVER_ENABLED=true
API_SERVER_KEY=change-me-local-dev
# Optional: only if a browser must call Hermes directly
# API_SERVER_CORS_ORIGINS=http://localhost:3000

2. Start the gateway

hermes gateway

You'll see:

[API Server] API server listening on http://127.0.0.1:8642

3. Connect a frontend

Point any OpenAI-compatible client at http://localhost:8642/v1:

# Test with curl
curl http://localhost:8642/v1/chat/completions \
  -H "Authorization: Bearer change-me-local-dev" \
  -H "Content-Type: application/json" \
  -d '{"model": "hermes-agent", "messages": [{"role": "user", "content": "Hello!"}]}'

Or connect Open WebUI, LobeChat, or any other frontend — see the Open WebUI integration guide for step-by-step instructions.

Endpoints

POST /v1/chat/completions

Standard OpenAI Chat Completions format. Stateless — the full conversation is included in each request via the messages array.

Request:

{
  "model": "hermes-agent",
  "messages": [
    {"role": "system", "content": "You are a Python expert."},
    {"role": "user", "content": "Write a fibonacci function"}
  ],
  "stream": false
}

Response:

{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "created": 1710000000,
  "model": "hermes-agent",
  "choices": [{
    "index": 0,
    "message": {"role": "assistant", "content": "Here's a fibonacci function..."},
    "finish_reason": "stop"
  }],
  "usage": {"prompt_tokens": 50, "completion_tokens": 200, "total_tokens": 250}
}

Inline image input: user messages may send content as an array of text and image_url parts. Both remote http(s) URLs and data:image/... URLs are supported:

{
  "model": "hermes-agent",
  "messages": [
    {
      "role": "user",
      "content": [
        {"type": "text", "text": "What is in this image?"},
        {"type": "image_url", "image_url": {"url": "https://example.com/cat.png", "detail": "high"}}
      ]
    }
  ]
}

Uploaded files (file / input_file / file_id) and non-image data: URLs return 400 unsupported_content_type.

Streaming ("stream": true): Returns Server-Sent Events (SSE) with token-by-token response chunks. For Chat Completions, the stream uses standard chat.completion.chunk events plus Hermes' custom hermes.tool.progress event for tool-start UX. For Responses, the stream uses OpenAI Responses event types such as response.created, response.output_text.delta, response.output_item.added, response.output_item.done, and response.completed.

Tool progress in streams:

  • Chat Completions: Hermes emits event: hermes.tool.progress for tool-start visibility without polluting persisted assistant text.
  • Responses: Hermes emits spec-native function_call and function_call_output output items during the SSE stream, so clients can render structured tool UI in real time.

POST /v1/responses

OpenAI Responses API format. Supports server-side conversation state via previous_response_id — the server stores full conversation history (including tool calls and results) so multi-turn context is preserved without the client managing it.

Request:

{
  "model": "hermes-agent",
  "input": "What files are in my project?",
  "instructions": "You are a helpful coding assistant.",
  "store": true
}

Response:

{
  "id": "resp_abc123",
  "object": "response",
  "status": "completed",
  "model": "hermes-agent",
  "output": [
    {"type": "function_call", "name": "terminal", "arguments": "{\"command\": \"ls\"}", "call_id": "call_1"},
    {"type": "function_call_output", "call_id": "call_1", "output": "README.md src/ tests/"},
    {"type": "message", "role": "assistant", "content": [{"type": "output_text", "text": "Your project has..."}]}
  ],
  "usage": {"input_tokens": 50, "output_tokens": 200, "total_tokens": 250}
}

Inline image input: input[].content can contain input_text and input_image parts. Both remote URLs and data:image/... URLs are supported:

{
  "model": "hermes-agent",
  "input": [
    {
      "role": "user",
      "content": [
        {"type": "input_text", "text": "Describe this screenshot."},
        {"type": "input_image", "image_url": "data:image/png;base64,iVBORw0K..."}
      ]
    }
  ]
}

Uploaded files (input_file / file_id) and non-image data: URLs return 400 unsupported_content_type.

Multi-turn with previous_response_id

Chain responses to maintain full context (including tool calls) across turns:

{
  "input": "Now show me the README",
  "previous_response_id": "resp_abc123"
}

The server reconstructs the full conversation from the stored response chain — all previous tool calls and results are preserved. Chained requests also share the same session, so multi-turn conversations appear as a single entry in the dashboard and session history.

Named conversations

Use the conversation parameter instead of tracking response IDs:

{"input": "Hello", "conversation": "my-project"}
{"input": "What's in src/?", "conversation": "my-project"}
{"input": "Run the tests", "conversation": "my-project"}

The server automatically chains to the latest response in that conversation. Like the /title command for gateway sessions.

GET /v1/responses/{id}

Retrieve a previously stored response by ID.

DELETE /v1/responses/{id}

Delete a stored response.

GET /v1/models

Lists the agent as an available model. The advertised model name defaults to the profile name (or hermes-agent for the default profile). Required by most frontends for model discovery.

GET /v1/capabilities

Returns a machine-readable description of the API server's stable surface for external UIs, orchestrators, and plugin bridges.

{
  "object": "hermes.api_server.capabilities",
  "platform": "hermes-agent",
  "model": "hermes-agent",
  "auth": {"type": "bearer", "required": true},
  "features": {
    "chat_completions": true,
    "responses_api": true,
    "run_submission": true,
    "run_status": true,
    "run_events_sse": true,
    "run_stop": true
  }
}

Use this endpoint when integrating dashboards, browser UIs, or control planes so they can discover whether the running Hermes version supports runs, streaming, cancellation, and session continuity without depending on private Python internals.

GET /health

Health check. Returns {"status": "ok"}. Also available at GET /v1/health for OpenAI-compatible clients that expect the /v1/ prefix.

GET /health/detailed

Extended health check that also reports active sessions, running agents, and resource usage. Useful for monitoring/observability tooling.

Runs API (streaming-friendly alternative)

In addition to /v1/chat/completions and /v1/responses, the server exposes a runs API for long-form sessions where the client wants to subscribe to progress events instead of managing streaming themselves.

POST /v1/runs

Create a new agent run. Returns a run_id that can be used to subscribe to progress events.

{
  "run_id": "run_abc123",
  "status": "started"
}

Runs accept a simple input string and optional session_id, instructions, conversation_history, or previous_response_id. When session_id is provided, Hermes surfaces it in the run status so external UIs can correlate runs with their own conversation IDs.

GET /v1/runs/{run_id}

Poll the current run state. This is useful for dashboards that need status without holding an SSE connection open, or for UIs that reconnect after navigation.

{
  "object": "hermes.run",
  "run_id": "run_abc123",
  "status": "completed",
  "session_id": "space-session",
  "model": "hermes-agent",
  "output": "Done.",
  "usage": {"input_tokens": 50, "output_tokens": 200, "total_tokens": 250}
}

Statuses are retained briefly after terminal states (completed, failed, or cancelled) for polling and UI reconciliation.

GET /v1/runs/{run_id}/events

Server-Sent Events stream of the run's tool-call progress, token deltas, and lifecycle events. Designed for dashboards and thick clients that want to attach/detach without losing state.

POST /v1/runs/{run_id}/stop

Interrupt a running agent turn. The endpoint returns immediately with {"status": "stopping"} while Hermes asks the active agent to stop at the next safe interruption point.

Jobs API (background scheduled work)

The server exposes a lightweight jobs CRUD surface for managing scheduled / background agent runs from a remote client. All endpoints are gated behind the same bearer auth.

GET /api/jobs

List all scheduled jobs.

POST /api/jobs

Create a new scheduled job. Body accepts the same shape as hermes cron — prompt, schedule, skills, provider override, delivery target.

GET /api/jobs/{job_id}

Fetch a single job's definition and last-run state.

PATCH /api/jobs/{job_id}

Update fields on an existing job (prompt, schedule, etc.). Partial updates are merged.

DELETE /api/jobs/{job_id}

Remove a job. Also cancels any in-flight run.

POST /api/jobs/{job_id}/pause

Pause a job without deleting it. Next-scheduled-run timestamps are suspended until resumed.

POST /api/jobs/{job_id}/resume

Resume a previously paused job.

POST /api/jobs/{job_id}/run

Trigger the job to run immediately, out of schedule.

System Prompt Handling

When a frontend sends a system message (Chat Completions) or instructions field (Responses API), hermes-agent layers it on top of its core system prompt. Your agent keeps all its tools, memory, and skills — the frontend's system prompt adds extra instructions.

This means you can customize behavior per-frontend without losing capabilities:

  • Open WebUI system prompt: "You are a Python expert. Always include type hints."
  • The agent still has terminal, file tools, web search, memory, etc.

Authentication

Bearer token auth via the Authorization header:

Authorization: Bearer ***

Configure the key via API_SERVER_KEY env var. If you need a browser to call Hermes directly, also set API_SERVER_CORS_ORIGINS to an explicit allowlist.

:::warning Security The API server gives full access to hermes-agent's toolset, including terminal commands. When binding to a non-loopback address like 0.0.0.0, API_SERVER_KEY is required. Also keep API_SERVER_CORS_ORIGINS narrow to control browser access.

The default bind address (127.0.0.1) is for local-only use. Browser access is disabled by default; enable it only for explicit trusted origins. :::

Configuration

Environment Variables

Variable Default Description
API_SERVER_ENABLED false Enable the API server
API_SERVER_PORT 8642 HTTP server port
API_SERVER_HOST 127.0.0.1 Bind address (localhost only by default)
API_SERVER_KEY (none) Bearer token for auth
API_SERVER_CORS_ORIGINS (none) Comma-separated allowed browser origins
API_SERVER_MODEL_NAME (profile name) Model name on /v1/models. Defaults to profile name, or hermes-agent for default profile.

config.yaml

# Not yet supported — use environment variables.
# config.yaml support coming in a future release.

Security Headers

All responses include security headers:

  • X-Content-Type-Options: nosniff — prevents MIME type sniffing
  • Referrer-Policy: no-referrer — prevents referrer leakage

CORS

The API server does not enable browser CORS by default.

For direct browser access, set an explicit allowlist:

API_SERVER_CORS_ORIGINS=http://localhost:3000,http://127.0.0.1:3000

When CORS is enabled:

  • Preflight responses include Access-Control-Max-Age: 600 (10 minute cache)
  • SSE streaming responses include CORS headers so browser EventSource clients work correctly
  • Idempotency-Key is an allowed request header — clients can send it for deduplication (responses are cached by key for 5 minutes)

Most documented frontends such as Open WebUI connect server-to-server and do not need CORS at all.

Compatible Frontends

Any frontend that supports the OpenAI API format works. Tested/documented integrations:

Frontend Stars Connection
Open WebUI 126k Full guide available
LobeChat 73k Custom provider endpoint
LibreChat 34k Custom endpoint in librechat.yaml
AnythingLLM 56k Generic OpenAI provider
NextChat 87k BASE_URL env var
ChatBox 39k API Host setting
Jan 26k Remote model config
HF Chat-UI 8k OPENAI_BASE_URL
big-AGI 7k Custom endpoint
OpenAI Python SDK OpenAI(base_url="http://localhost:8642/v1")
curl Direct HTTP requests

Multi-User Setup with Profiles

To give multiple users their own isolated Hermes instance (separate config, memory, skills), use profiles:

# Create a profile per user
hermes profile create alice
hermes profile create bob

# Configure each profile's API server on a different port. API_SERVER_* are env
# vars (not config.yaml keys), so write them to each profile's .env:
cat >> ~/.hermes/profiles/alice/.env <<EOF
API_SERVER_ENABLED=true
API_SERVER_PORT=8643
API_SERVER_KEY=alice-secret
EOF

cat >> ~/.hermes/profiles/bob/.env <<EOF
API_SERVER_ENABLED=true
API_SERVER_PORT=8644
API_SERVER_KEY=bob-secret
EOF

# Start each profile's gateway
hermes -p alice gateway &
hermes -p bob gateway &

Each profile's API server automatically advertises the profile name as the model ID:

  • http://localhost:8643/v1/models → model alice
  • http://localhost:8644/v1/models → model bob

In Open WebUI, add each as a separate connection. The model dropdown shows alice and bob as distinct models, each backed by a fully isolated Hermes instance. See the Open WebUI guide for details.

Limitations

  • Response storage — stored responses (for previous_response_id) are persisted in SQLite and survive gateway restarts. Max 100 stored responses (LRU eviction).
  • No file upload — inline images are supported on both /v1/chat/completions and /v1/responses, but uploaded files (file, input_file, file_id) and non-image document inputs are not supported through the API.
  • Model field is cosmetic — the model field in requests is accepted but the actual LLM model used is configured server-side in config.yaml.

Proxy Mode

The API server also serves as the backend for gateway proxy mode. When another Hermes gateway instance is configured with GATEWAY_PROXY_URL pointing at this API server, it forwards all messages here instead of running its own agent. This enables split deployments — for example, a Docker container handling Matrix E2EE that relays to a host-side agent.

See Matrix Proxy Mode for the full setup guide.