forked from Zakaria/hermes-agent
183 lines
6.4 KiB
Python
183 lines
6.4 KiB
Python
"""FAL.ai image generation backend.
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Wraps the 18-model FAL catalog (FLUX 2, Z-Image, Nano Banana, GPT
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Image 1.5, Recraft, Imagen 4, Qwen, Ideogram, …) as an
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:class:`ImageGenProvider` implementation.
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The heavy lifting — model catalog, payload construction, request
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submission, managed-Nous-gateway selection, Clarity Upscaler chaining
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— lives in :mod:`tools.image_generation_tool`. This plugin reaches into
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that module via call-time indirection (``import tools.image_generation_tool as _it``)
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so:
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* the existing test suite (``tests/tools/test_image_generation.py``,
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``tests/tools/test_managed_media_gateways.py``) keeps patching
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``image_tool._submit_fal_request`` / ``image_tool.fal_client`` /
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``image_tool._managed_fal_client`` without modification, and
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* there's exactly one canonical FAL code path on disk — the plugin is a
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registration adapter, not a parallel implementation.
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See issue #26241 for the migration plan and the
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``plugin-extraction-test-patch-compatibility.md`` rules this follows.
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"""
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from __future__ import annotations
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import json
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import logging
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import os
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from typing import Any, Dict, List, Optional
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from agent.image_gen_provider import (
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DEFAULT_ASPECT_RATIO,
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ImageGenProvider,
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resolve_aspect_ratio,
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)
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logger = logging.getLogger(__name__)
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class FalImageGenProvider(ImageGenProvider):
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"""FAL.ai image generation backend.
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Delegates to ``tools.image_generation_tool.image_generate_tool`` so
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the in-tree FAL implementation (model catalog, payload builder,
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managed-gateway selection, Clarity Upscaler chaining) is the single
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source of truth. Everything is resolved at call time via the
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``_it`` indirection so tests can monkey-patch the legacy module.
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"""
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@property
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def name(self) -> str:
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return "fal"
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@property
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def display_name(self) -> str:
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return "FAL.ai"
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def is_available(self) -> bool:
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# Available when direct FAL_KEY is set OR the managed Nous
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# gateway resolves a fal-queue origin. Both checks come from the
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# legacy module so this provider tracks whatever logic ships
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# there.
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import tools.image_generation_tool as _it
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try:
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return bool(_it.check_fal_api_key())
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except Exception: # noqa: BLE001 — defensive; never break the picker
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return False
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def list_models(self) -> List[Dict[str, Any]]:
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import tools.image_generation_tool as _it
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return [
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{
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"id": model_id,
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"display": meta.get("display", model_id),
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"speed": meta.get("speed", ""),
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"strengths": meta.get("strengths", ""),
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"price": meta.get("price", ""),
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}
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for model_id, meta in _it.FAL_MODELS.items()
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]
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def default_model(self) -> Optional[str]:
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import tools.image_generation_tool as _it
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return _it.DEFAULT_MODEL
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def get_setup_schema(self) -> Dict[str, Any]:
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return {
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"name": "FAL.ai",
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"badge": "paid",
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"tag": "Pick from flux-2-klein, flux-2-pro, gpt-image, nano-banana, etc.",
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"env_vars": [
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{
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"key": "FAL_KEY",
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"prompt": "FAL API key",
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"url": "https://fal.ai/dashboard/keys",
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},
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],
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}
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def generate(
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self,
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prompt: str,
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aspect_ratio: str = DEFAULT_ASPECT_RATIO,
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**kwargs: Any,
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) -> Dict[str, Any]:
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"""Generate an image via the legacy FAL pipeline.
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Forwards prompt + aspect_ratio (and any forward-compat extras
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the schema supports) into :func:`tools.image_generation_tool.image_generate_tool`,
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then reshapes its JSON-string response into the provider-ABC
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dict format consumed by ``_dispatch_to_plugin_provider``.
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"""
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import tools.image_generation_tool as _it
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aspect = resolve_aspect_ratio(aspect_ratio)
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passthrough = {
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key: kwargs[key]
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for key in (
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"num_inference_steps",
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"guidance_scale",
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"num_images",
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"output_format",
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"seed",
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)
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if key in kwargs and kwargs[key] is not None
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}
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try:
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raw = _it.image_generate_tool(
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prompt=prompt,
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aspect_ratio=aspect,
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**passthrough,
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)
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except Exception as exc: # noqa: BLE001 — never raise out of generate
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logger.warning("FAL image_generate_tool raised: %s", exc, exc_info=True)
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return {
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"success": False,
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"image": None,
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"error": f"FAL image generation failed: {exc}",
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"error_type": type(exc).__name__,
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"provider": "fal",
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"prompt": prompt,
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"aspect_ratio": aspect,
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}
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try:
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response = json.loads(raw) if isinstance(raw, str) else raw
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except Exception: # noqa: BLE001
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response = {"success": False, "image": None, "error": "Invalid JSON from FAL pipeline"}
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if not isinstance(response, dict):
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response = {
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"success": False,
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"image": None,
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"error": "FAL pipeline returned a non-dict response",
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"error_type": "provider_contract",
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}
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# Stamp provider/prompt/aspect_ratio so downstream consumers see
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# the uniform shape declared in ``agent.image_gen_provider``.
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response.setdefault("provider", "fal")
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response.setdefault("prompt", prompt)
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response.setdefault("aspect_ratio", aspect)
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# Annotate model best-effort — the legacy pipeline resolves it
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# internally, so query it after the fact for the response shape.
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if "model" not in response:
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try:
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model_id, _meta = _it._resolve_fal_model()
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response["model"] = model_id
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except Exception: # noqa: BLE001
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pass
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return response
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# ---------------------------------------------------------------------------
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# Plugin entry point
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# ---------------------------------------------------------------------------
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def register(ctx) -> None:
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"""Plugin entry point — wire ``FalImageGenProvider`` into the registry."""
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ctx.register_image_gen_provider(FalImageGenProvider())
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