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Building an Image Generation Provider Plugin

Image-gen provider plugins register a backend that services every image_generate tool call — DALL·E, gpt-image, Grok, Flux, Imagen, Stable Diffusion, fal, Replicate, a local ComfyUI rig, anything. Built-in providers (OpenAI, OpenAI-Codex, xAI) all ship as plugins. You can add a new one, or override a bundled one, by dropping a directory into plugins/image_gen/<name>/.

提示

Image-gen is one of several backend plugins Hermes supports. The others (with more specialized ABCs) are Memory Provider Plugins, Context Engine Plugins, and Model Provider Plugins. General tool/hook/CLI plugins live in Build a Hermes Plugin.

How discovery works​

Hermes scans for image-gen backends in three places:

  1. Bundled — <repo>/plugins/image_gen/<name>/ (auto-loaded with kind: backend, always available)
  2. User — ~/.hermes/plugins/image_gen/<name>/ (opt-in via plugins.enabled)
  3. Pip — packages declaring a hermes_agent.plugins entry point

Each plugin's register(ctx) function calls ctx.register_image_gen_provider(...) — that puts it into the registry in agent/image_gen_registry.py. The active provider is picked by image_gen.provider in config.yaml; hermes tools walks users through selection.

The image_generate tool wrapper asks the registry for the active provider and dispatches there. If no provider is registered, the tool surfaces a helpful error pointing at hermes tools.

Directory structure​

plugins/image_gen/my-backend/
├── __init__.py      # ImageGenProvider subclass + register()
└── plugin.yaml      # Manifest with kind: backend

A bundled plugin is complete at this point. User plugins at ~/.hermes/plugins/image_gen/<name>/ need to be added to plugins.enabled in config.yaml (or run hermes plugins enable <name>).

The ImageGenProvider ABC​

Subclass agent.image_gen_provider.ImageGenProvider. The only required members are the name property and the generate() method — everything else has sane defaults:

# plugins/image_gen/my-backend/__init__.py
from typing import Any, Dict, List, Optional
import os

from agent.image_gen_provider import (
    DEFAULT_ASPECT_RATIO,
    ImageGenProvider,
    error_response,
    resolve_aspect_ratio,
    save_b64_image,
    success_response,
)


class MyBackendImageGenProvider(ImageGenProvider):
    @property
    def name(self) -> str:
        # Stable id used in image_gen.provider config. Lowercase, no spaces.
        return "my-backend"

    @property
    def display_name(self) -> str:
        # Human label shown in `hermes tools`. Defaults to name.title() if omitted.
        return "My Backend"

    def is_available(self) -> bool:
        # Return False if credentials or deps are missing.
        # The tool's availability gate calls this before dispatch.
        if not os.environ.get("MY_BACKEND_API_KEY"):
            return False
        try:
            import my_backend_sdk  # noqa: F401
        except ImportError:
            return False
        return True

    def list_models(self) -> List[Dict[str, Any]]:
        # Catalog shown in `hermes tools` model picker.
        return [
            {
                "id": "my-model-fast",
                "display": "My Model (Fast)",
                "speed": "~5s",
                "strengths": "Quick iteration",
                "price": "$0.01/image",
            },
            {
                "id": "my-model-hq",
                "display": "My Model (HQ)",
                "speed": "~30s",
                "strengths": "Highest fidelity",
                "price": "$0.04/image",
            },
        ]

    def default_model(self) -> Optional[str]:
        return "my-model-fast"

    def get_setup_schema(self) -> Dict[str, Any]:
        # Metadata for the `hermes tools` picker — keys to prompt for at setup.
        return {
            "name": "My Backend",
            "badge": "paid",        # optional; shown as a short tag in the picker
            "tag": "One-line description shown under the name",
            "env_vars": [
                {
                    "key": "MY_BACKEND_API_KEY",
                    "prompt": "My Backend API key",
                    "url": "https://my-backend.example.com/api-keys",
                },
            ],
        }

    def generate(
        self,
        prompt: str,
        aspect_ratio: str = DEFAULT_ASPECT_RATIO,
        **kwargs: Any,
    ) -> Dict[str, Any]:
        prompt = (prompt or "").strip()
        aspect_ratio = resolve_aspect_ratio(aspect_ratio)

        if not prompt:
            return error_response(
                error="Prompt is required",
                error_type="invalid_input",
                provider=self.name,
                prompt="",
                aspect_ratio=aspect_ratio,
            )

        # Model selection precedence: env var → config → default. The helper
        # _resolve_model() in the built-in openai plugin is a good reference.
        model_id = kwargs.get("model") or self.default_model() or "my-model-fast"

        try:
            import my_backend_sdk
            client = my_backend_sdk.Client(api_key=os.environ["MY_BACKEND_API_KEY"])
            result = client.generate(
                prompt=prompt,
                model=model_id,
                aspect_ratio=aspect_ratio,
            )

            # Two shapes supported:
            #   - URL string: return it as `image`
            #   - base64 data: save under $HERMES_HOME/cache/images/ via save_b64_image()
            if result.get("image_b64"):
                path = save_b64_image(
                    result["image_b64"],
                    prefix=self.name,
                    extension="png",
                )
                image = str(path)
            else:
                image = result["image_url"]

            return success_response(
                image=image,
                model=model_id,
                prompt=prompt,
                aspect_ratio=aspect_ratio,
                provider=self.name,
            )
        except Exception as exc:
            return error_response(
                error=str(exc),
                error_type=type(exc).__name__,
                provider=self.name,
                model=model_id,
                prompt=prompt,
                aspect_ratio=aspect_ratio,
            )


def register(ctx) -> None:
    """Plugin entry point — called once at load time."""
    ctx.register_image_gen_provider(MyBackendImageGenProvider())

plugin.yaml​

name: my-backend
version: 1.0.0
description: My image backend — text-to-image via My Backend SDK
author: Your Name
kind: backend
requires_env:
  - MY_BACKEND_API_KEY

kind: backend is what routes the plugin to the image-gen registration path. requires_env is prompted during hermes plugins install.

ABC reference​

Full contract in agent/image_gen_provider.py. The methods you'll typically override:

MemberRequiredDefaultPurpose
name✅—Stable id used in image_gen.provider config
display_name—name.title()Label shown in hermes tools
is_available()—TrueGate for missing creds/deps
list_models()—[]Catalog for hermes tools model picker
default_model()—first from list_models()Fallback when no model is configured
get_setup_schema()—minimalPicker metadata + env-var prompts
generate(prompt, aspect_ratio, **kwargs)✅—The call

Response format​

generate() must return a dict built via success_response() or error_response(). Both live in agent/image_gen_provider.py.

Success:

success_response(
    image=<url-or-absolute-path>,
    model=<model-id>,
    prompt=<echoed-prompt>,
    aspect_ratio="landscape" | "square" | "portrait",
    provider=<your-provider-name>,
    extra={...},  # optional backend-specific fields
)

Error:

error_response(
    error="human-readable message",
    error_type="provider_error" | "invalid_input" | "<exception class name>",
    provider=<your-provider-name>,
    model=<model-id>,
    prompt=<prompt>,
    aspect_ratio=<resolved aspect>,
)

The tool wrapper JSON-serializes the dict and hands it to the LLM. Errors are surfaced as the tool result; the LLM decides how to explain them to the user.

Handling base64 vs URL output​

Some backends return image URLs (fal, Replicate); others return base64 payloads (OpenAI gpt-image-2). For the base64 case, use save_b64_image() — it writes to $HERMES_HOME/cache/images/<prefix>_<timestamp>_<uuid>.<ext> and returns the absolute Path. Pass that path (as str) as image= in success_response(). Gateway delivery (Telegram photo bubble, Discord attachment) recognizes both URLs and absolute paths.

User overrides​

Drop a user plugin at ~/.hermes/plugins/image_gen/<name>/ with the same name property as a bundled one and enable it via hermes plugins enable <name> — the registry is last-writer-wins, so your version replaces the built-in. Useful for pointing an openai plugin at a private proxy, or swapping in a custom model catalog.

Testing​

export HERMES_HOME=/tmp/hermes-imggen-test
mkdir -p $HERMES_HOME/plugins/image_gen/my-backend
# …copy __init__.py + plugin.yaml into that dir…

export MY_BACKEND_API_KEY=your-test-key
hermes plugins enable my-backend

# Pick it as the active provider
echo "image_gen:" >> $HERMES_HOME/config.yaml
echo "  provider: my-backend" >> $HERMES_HOME/config.yaml

# Exercise it
hermes -z "Generate an image of a corgi in a spacesuit"

Or interactively: hermes tools → "Image Generation" → select my-backend → enter API key if prompted.

Reference implementations​

  • plugins/image_gen/openai/__init__.py — gpt-image-2 at low/medium/high tiers as three virtual model IDs sharing one API model with different quality params. Good example of tiered models under a single backend + config.yaml precedence chain.
  • plugins/image_gen/xai/__init__.py — Grok Imagine via xAI. Different shape (URL output, simpler catalog).
  • plugins/image_gen/openai-codex/__init__.py — Codex-style Responses API variant reusing the OpenAI SDK with a different routing base URL.

Distribute via pip​

# pyproject.toml
[project.entry-points."hermes_agent.plugins"]
my-backend-imggen = "my_backend_imggen_package"

my_backend_imggen_package must expose a top-level register function. See Distribute via pip in the general plugin guide for the full setup.