hermes-agent/website/docs/user-guide/features/api-server.md
Teknium f683132c1d
feat(api-server): inline image inputs on /v1/chat/completions and /v1/responses (#12969)
OpenAI-compatible clients (Open WebUI, LobeChat, etc.) can now send vision
requests to the API server. Both endpoints accept the canonical OpenAI
multimodal shape:

  Chat Completions: {type: text|image_url, image_url: {url, detail?}}
  Responses:        {type: input_text|input_image, image_url: <str>, detail?}

The server validates and converts both into a single internal shape that the
existing agent pipeline already handles (Anthropic adapter converts,
OpenAI-wire providers pass through). Remote http(s) URLs and data:image/*
URLs are supported.

Uploaded files (file, input_file, file_id) and non-image data: URLs are
rejected with 400 unsupported_content_type.

Changes:

- gateway/platforms/api_server.py
  - _normalize_multimodal_content(): validates + normalizes both Chat and
    Responses content shapes. Returns a plain string for text-only content
    (preserves prompt-cache behavior on existing callers) or a canonical
    [{type:text|image_url,...}] list when images are present.
  - _content_has_visible_payload(): replaces the bare truthy check so a
    user turn with only an image no longer rejects as 'No user message'.
  - _handle_chat_completions and _handle_responses both call the new helper
    for user/assistant content; system messages continue to flatten to text.
  - Codex conversation_history, input[], and inline history paths all share
    the same validator. No duplicated normalizers.

- run_agent.py
  - _summarize_user_message_for_log(): produces a short string summary
    ('[1 image] describe this') from list content for logging, spinner
    previews, and trajectory writes. Fixes AttributeError when list
    user_message hit user_message[:80] + '...' / .replace().
  - _chat_content_to_responses_parts(): module-level helper that converts
    chat-style multimodal content to Responses 'input_text'/'input_image'
    parts. Used in _chat_messages_to_responses_input for Codex routing.
  - _preflight_codex_input_items() now validates and passes through list
    content parts for user/assistant messages instead of stringifying.

- tests/gateway/test_api_server_multimodal.py (new, 38 tests)
  - Unit coverage for _normalize_multimodal_content, including both part
    formats, data URL gating, and all reject paths.
  - Real aiohttp HTTP integration on /v1/chat/completions and /v1/responses
    verifying multimodal payloads reach _run_agent intact.
  - 400 coverage for file / input_file / non-image data URL.

- tests/run_agent/test_run_agent_multimodal_prologue.py (new)
  - Regression coverage for the prologue no-crash contract.
  - _chat_content_to_responses_parts round-trip coverage.

- website/docs/user-guide/features/api-server.md
  - Inline image examples for both endpoints.
  - Updated Limitations: files still unsupported, images now supported.

Validated live against openrouter/anthropic/claude-opus-4.6:
  POST /v1/chat/completions  → 200, vision-accurate description
  POST /v1/responses         → 200, same image, clean output_text
  POST /v1/chat/completions [file] → 400 unsupported_content_type
  POST /v1/responses [input_file]  → 400 unsupported_content_type
  POST /v1/responses [non-image data URL] → 400 unsupported_content_type

Closes #5621, #8253, #4046, #6632.

Co-authored-by: Paul Bergeron <paul@gamma.app>
Co-authored-by: zhangxicen <zhangxicen@example.com>
Co-authored-by: Manuel Schipper <manuelschipper@users.noreply.github.com>
Co-authored-by: pradeep7127 <pradeep7127@users.noreply.github.com>
2026-04-20 04:16:13 -07:00

14 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 /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.

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.

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
hermes -p alice config set API_SERVER_ENABLED true
hermes -p alice config set API_SERVER_PORT 8643
hermes -p alice config set API_SERVER_KEY alice-secret

hermes -p bob config set API_SERVER_ENABLED true
hermes -p bob config set API_SERVER_PORT 8644
hermes -p bob config set API_SERVER_KEY bob-secret

# 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.