3dc3809d07
Image and video callers were each formatting the same four-field dict into the same sentence. Return the rendered tail from _managed_fal_billing_error so the wording lives in one place; output is byte-identical.
878 lines
42 KiB
Python
878 lines
42 KiB
Python
#!/usr/bin/env python3
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"""Image generation via FAL.ai (model picked in ``hermes tools``, persisted to ``image_gen.model``).
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``_build_fal_payload()`` / ``_build_fal_edit_payload()`` translate unified inputs into the
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``FAL_MODELS`` payload filtered to its ``supports`` whitelist so models never receive rejected
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keys. Clarity upscaling is strictly per-call opt-in: default-on degraded text/CJK/faces.
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"""
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import json
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import logging
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import os
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import datetime
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import threading
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import uuid
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from typing import Any, Dict, Optional
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# Imported lazily by _load_fal_client() (~64 ms on every CLI cold start); a test-monkeypatched
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# value short-circuits the loader.
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fal_client: Any = None
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def _load_fal_client() -> Any:
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"""Lazily import fal_client into the module global (idempotent; keeps a test-installed mock)."""
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global fal_client
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if fal_client is None:
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from tools.fal_common import import_fal_client
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fal_client = import_fal_client()
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return fal_client
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from tools.debug_helpers import DebugSession
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from tools.fal_common import (
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_ManagedFalSyncClient, _extract_http_status, _managed_fal_billing_error,
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_normalize_fal_queue_url_format,
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)
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from tools.image_generation_catalog import (
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DEFAULT_ASPECT_RATIO, DEFAULT_MODEL, FAL_MODELS, UPSCALER_CREATIVITY, UPSCALER_DEFAULT_PROMPT,
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UPSCALER_FACTOR, UPSCALER_GUIDANCE_SCALE, UPSCALER_MODEL, UPSCALER_NEGATIVE_PROMPT,
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UPSCALER_NUM_INFERENCE_STEPS, UPSCALER_RESEMBLANCE, UPSCALER_SAFETY_CHECKER, VALID_ASPECT_RATIOS,
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)
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from tools.managed_tool_gateway import resolve_managed_tool_gateway
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from tools.tool_backend_helpers import (
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NOUS_MANAGED_PROVIDER, fal_key_is_configured, managed_nous_tools_enabled,
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nous_tool_gateway_unavailable_message, read_selection, selection_error)
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logger = logging.getLogger(__name__)
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_debug = DebugSession("image_tools", env_var="IMAGE_TOOLS_DEBUG")
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_managed_fal_client = None
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_managed_fal_client_config = None
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_managed_fal_client_lock = threading.Lock()
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# --- Managed FAL gateway (Nous Subscription) ---
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def _resolve_managed_fal_gateway():
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"""Managed gateway config for the stored `hermes tools` selection, or ``None`` for direct FAL.
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``"nous"`` (or legacy ``use_gateway: true``) → managed ONLY (unreachable = selection-naming
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error, never a silent FAL_KEY fallback). Other stored provider → direct ONLY (missing FAL_KEY
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= error naming the selection). Never configured → autodetect: direct if FAL_KEY, else managed.
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"""
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selected = read_selection("image_gen")
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if selected == NOUS_MANAGED_PROVIDER:
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gateway = resolve_managed_tool_gateway("fal-queue")
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if gateway is None:
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raise ValueError(selection_error(
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"image_gen", NOUS_MANAGED_PROVIDER,
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"the Nous Tool Gateway is not available (not entitled or unreachable)"))
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return gateway
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if selected is not None:
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if fal_key_is_configured():
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return None
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raise ValueError(selection_error("image_gen", selected, "FAL_KEY is not set"))
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# Never-configured category: legacy credential autodetect (do NOT persist).
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return None if fal_key_is_configured() else resolve_managed_tool_gateway("fal-queue")
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def _get_managed_fal_client(managed_gateway):
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"""Reuse the managed FAL client so its internal httpx.Client is not leaked per call."""
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global _managed_fal_client, _managed_fal_client_config
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client_config = (managed_gateway.gateway_origin.rstrip("/"), managed_gateway.nous_user_token)
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with _managed_fal_client_lock:
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if _managed_fal_client is None or _managed_fal_client_config != client_config:
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# Resolved on this module so monkeypatching ``image_generation_tool.fal_client`` still applies.
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_managed_fal_client = _ManagedFalSyncClient(
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_load_fal_client(), key=managed_gateway.nous_user_token,
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queue_run_origin=managed_gateway.gateway_origin)
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_managed_fal_client_config = client_config
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return _managed_fal_client
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class ImageGenerationInterrupted(Exception):
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"""Raised when the user interrupts while a FAL job is in flight."""
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def _wait_fal_result(handler, *, poll_seconds: float = 0.5):
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"""Interrupt-aware ``handler.get()``: the SDK blocks 30-60s, hiding user interrupts.
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The get runs on a daemon worker; the interrupt bit is polled between join slices and on
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interrupt the worker is abandoned (remote job keeps running).
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"""
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from tools.interrupt import is_interrupted
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result_box: list = []
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error_box: list = []
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def _get():
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try:
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result_box.append(handler.get())
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except BaseException as exc: # noqa: BLE001 — re-raised on the caller thread
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error_box.append(exc)
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worker = threading.Thread(target=_get, daemon=True, name="fal-result-wait")
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worker.start()
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while worker.is_alive():
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if is_interrupted():
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raise ImageGenerationInterrupted(
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"Image generation interrupted by user — abandoned the in-flight FAL job.")
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worker.join(timeout=poll_seconds)
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if error_box:
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raise error_box[0]
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return result_box[0] if result_box else None
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def _submit_fal_request(model: str, arguments: Dict[str, Any]):
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"""Submit a FAL request using direct credentials or the managed queue gateway."""
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_load_fal_client()
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request_headers = {"x-idempotency-key": str(uuid.uuid4())}
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managed_gateway = _resolve_managed_fal_gateway()
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if managed_gateway is None:
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return fal_client.submit(model, arguments=arguments, headers=request_headers)
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try:
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return _get_managed_fal_client(managed_gateway).submit(
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model, arguments=arguments, headers=request_headers)
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except Exception as exc:
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# A managed-gateway 4xx usually means the portal doesn't proxy this model
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# (allowlist miss, billing gate): give remediation instead of a raw httpx error.
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status = _extract_http_status(exc)
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if status is not None and 400 <= status < 500:
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billing = _managed_fal_billing_error(exc, "model")
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if billing is not None:
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raise ValueError(
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f"Nous Subscription gateway rejected model '{model}' (HTTP {status}): {billing}") from exc
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gateway_message = ""
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if status in {401, 402, 403}:
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gateway_message = "\n\n" + nous_tool_gateway_unavailable_message(
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"managed FAL image generation", force_fresh=True)
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raise ValueError(
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f"Nous Subscription gateway rejected model '{model}' (HTTP {status}). This model "
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f"may not yet be enabled on the Nous Portal's FAL proxy. Either:\n"
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f" • Set FAL_KEY in your environment to use FAL.ai directly, or\n"
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f" • Pick a different model via `hermes tools` → Image Generation."
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f"{gateway_message}") from exc
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raise
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# --- Config readers, model resolution + payload construction ---
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def _read_image_gen_key(key: str) -> Optional[str]:
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"""Return the stripped ``image_gen.<key>`` string from config.yaml, or None."""
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try:
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from hermes_cli.config import load_config
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cfg = load_config()
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section = cfg.get("image_gen") if isinstance(cfg, dict) else None
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value = section.get(key) if isinstance(section, dict) else None
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if isinstance(value, str) and value.strip():
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return value.strip()
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except Exception as exc:
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logger.debug("Could not read image_gen.%s: %s", key, exc)
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return None
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def _read_configured_image_model():
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"""``image_gen.model`` from config.yaml, or None."""
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return _read_image_gen_key("model")
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def _read_configured_image_provider():
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"""``image_gen.provider`` from config.yaml, or None (unset keeps the in-tree FAL fallback even
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when other providers are registered; ``"fal"`` routes via ``plugins/image_gen/fal/``).
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We only consult the plugin registry when this is explicitly set — an unset value keeps users on the
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in-tree FAL fallback even when other providers happen to be registered (e.g. a user has OPENAI_API_KEY
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set for other features but never asked for OpenAI image gen). ``"fal"`` explicitly routes through
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``plugins/image_gen/fal/`` (which delegates back into this module's pipeline via call-time indirection —
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see issue #26241).
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"""
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return _read_image_gen_key("provider")
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def _plugin_provider_name() -> Optional[str]:
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"""Configured provider that must go through the plugin registry; None for unset/fal/nous."""
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configured = _read_configured_image_provider()
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if not configured or configured in ("fal", NOUS_MANAGED_PROVIDER):
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return None
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return configured
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def _resolve_fal_model() -> tuple:
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"""Return ``(model_id, meta)`` for the configured FAL model, falling back to DEFAULT_MODEL (warned) when unknown."""
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# FAL_IMAGE_MODEL is an undocumented escape hatch (backward-compat for tests/scripts).
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model_id = _read_image_gen_key("model") or os.getenv("FAL_IMAGE_MODEL", "").strip()
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if model_id and model_id not in FAL_MODELS:
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logger.warning("Unknown FAL model '%s' in config; falling back to %s", model_id, DEFAULT_MODEL)
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model_id = None
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model_id = model_id or DEFAULT_MODEL
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return model_id, FAL_MODELS[model_id]
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_SIZE_KEY_BY_STYLE = {"image_size_preset": "image_size", "gpt_literal": "image_size",
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"aspect_ratio": "aspect_ratio"}
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def _build_payload(model_id, prompt, aspect_ratio, seed, overrides, image_urls=None) -> Dict[str, Any]:
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"""Text-to-image / edit payload (``image_urls`` selects edit mode): defaults + native size
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spec + overrides, filtered to the model whitelist.
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Edit endpoints mostly auto-infer size, so the size key is sent only when ``edit_supports``
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lists it. ``prompt`` (and ``image_urls`` on edits) survive a whitelist gap: every FAL
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endpoint requires them, so a catalog mistake can't send a broken request.
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"""
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meta = FAL_MODELS[model_id]
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edit = image_urls is not None
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supports = (meta.get("edit_supports") or set()) if edit else meta["supports"]
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sizes = meta["sizes"]
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aspect = (aspect_ratio or DEFAULT_ASPECT_RATIO).lower().strip()
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if aspect not in sizes:
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aspect = DEFAULT_ASPECT_RATIO
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payload: Dict[str, Any] = dict(meta.get("defaults", {}))
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payload["prompt"] = (prompt or "").strip()
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required = {"prompt"}
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if edit:
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payload["image_urls"] = list(image_urls)
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required.add("image_urls")
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size_key = _SIZE_KEY_BY_STYLE.get(meta["size_style"])
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if size_key is None and not edit:
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raise ValueError(f"Unknown size_style: {meta['size_style']!r}")
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if size_key is not None and (not edit or size_key in supports):
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payload[size_key] = sizes[aspect]
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if isinstance(seed, int):
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payload["seed"] = seed
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payload.update({k: v for k, v in (overrides or {}).items() if v is not None})
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return {k: v for k, v in payload.items() if k in supports or k in required}
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def _build_fal_payload(model_id, prompt, aspect_ratio=DEFAULT_ASPECT_RATIO, seed=None, overrides=None):
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"""FAL text-to-image payload for ``model_id`` from unified inputs."""
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return _build_payload(model_id, prompt, aspect_ratio, seed, overrides)
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def _build_fal_edit_payload(model_id, prompt, image_urls, aspect_ratio=DEFAULT_ASPECT_RATIO,
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seed=None, overrides=None):
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"""FAL *edit* (image-to-image) payload: ``image_urls`` + prompt, filtered to ``edit_supports``."""
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return _build_payload(model_id, prompt, aspect_ratio, seed, overrides, image_urls=image_urls)
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# --- Upscaler ---
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def _upscale_image(image_url: str, original_prompt: str) -> Optional[Dict[str, Any]]:
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"""Upscale via FAL's Clarity Upscaler; None on failure (caller keeps the original)."""
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try:
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logger.info("Upscaling image with Clarity Upscaler...")
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handler = _submit_fal_request(UPSCALER_MODEL, arguments={
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"image_url": image_url, "prompt": f"{UPSCALER_DEFAULT_PROMPT}, {original_prompt}",
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"upscale_factor": UPSCALER_FACTOR, "negative_prompt": UPSCALER_NEGATIVE_PROMPT,
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"creativity": UPSCALER_CREATIVITY, "resemblance": UPSCALER_RESEMBLANCE,
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"guidance_scale": UPSCALER_GUIDANCE_SCALE,
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"num_inference_steps": UPSCALER_NUM_INFERENCE_STEPS,
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"enable_safety_checker": UPSCALER_SAFETY_CHECKER})
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result = _wait_fal_result(handler)
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if result and "image" in result:
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up = result["image"]
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logger.info("Image upscaled successfully to %sx%s",
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up.get("width", "unknown"), up.get("height", "unknown"))
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return {
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"url": up["url"], "width": up.get("width", 0), "height": up.get("height", 0),
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"upscaled": True, "upscale_factor": UPSCALER_FACTOR}
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logger.error("Upscaler returned invalid response")
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return None
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except ImageGenerationInterrupted:
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# A user interrupt must not degrade into a silent "use original" fallback.
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raise
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except Exception as e:
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logger.error("Error upscaling image: %s", e, exc_info=True)
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return None
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# --- Artifact path hinting for non-local terminal backends ---
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_CONTAINER_HOME_ENVS = {"DockerEnvironment", "SingularityEnvironment", "ModalEnvironment"}
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# No env yet: only deterministic cache roots translate side-effect free (SSH: tilde path; its
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# first sync uploads the cache file).
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_CACHE_BASE_BY_BACKEND = {"docker": "/root/.hermes", "singularity": "/root/.hermes",
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"modal": "/root/.hermes", "ssh": "~/.hermes"}
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def _looks_like_absolute_file_path(value: str) -> bool:
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if not value or not isinstance(value, str) or value.lower().startswith(("http://", "https://", "data:")):
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return False
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return os.path.isabs(value) or (len(value) >= 3 and value[1] == ":" and value[2] in {"/", "\\"})
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def _active_terminal_env(task_id: str | None):
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try:
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from tools.terminal_tool_lifecycle import get_active_env
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return get_active_env(task_id or "default")
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except Exception as exc: # noqa: BLE001 - artifact hinting must not break generation
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logger.debug("Could not inspect active terminal environment: %s", exc)
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return None
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def _agent_cache_base_for_env(env: Any) -> str | None:
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if env is not None:
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# Optional extension hook: an environment may expose its own agent-visible cache root.
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explicit = getattr(env, "agent_visible_cache_base", None)
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if callable(explicit):
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try:
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value = explicit()
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if value:
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return str(value).rstrip("/")
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except Exception as exc: # noqa: BLE001
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logger.debug("active env agent_visible_cache_base failed: %s", exc)
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remote_home = getattr(env, "_remote_home", None)
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if remote_home:
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return f"{str(remote_home).rstrip('/')}/.hermes"
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if env.__class__.__name__ in _CONTAINER_HOME_ENVS:
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return "/root/.hermes"
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backend = (os.getenv("TERMINAL_ENV") or "local").strip().lower()
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return _CACHE_BASE_BY_BACKEND.get(backend)
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def _postprocess_image_generate_result(raw: str, task_id: str | None = None) -> str:
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"""Annotate successful local results: ``image`` stays the host/gateway-deliverable path;
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``agent_visible_image`` is the same file as seen by a non-local terminal backend."""
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try:
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payload = json.loads(raw) if isinstance(raw, str) else raw
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except Exception:
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return raw
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if not isinstance(payload, dict) or not payload.get("success"):
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return raw
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image = payload.get("image")
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if not isinstance(image, str) or not _looks_like_absolute_file_path(image):
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return raw
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env = _active_terminal_env(task_id)
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cache_base = _agent_cache_base_for_env(env)
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if not cache_base:
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return raw
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try:
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from tools.credential_files import map_cache_path_to_container
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agent_path = map_cache_path_to_container(image, container_base=cache_base)
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except Exception as exc: # noqa: BLE001
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logger.debug("Could not translate image cache path for backend: %s", exc)
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return raw
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if not agent_path or agent_path == image:
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return raw
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sync_manager = getattr(env, "_sync_manager", None)
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if sync_manager is not None:
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try:
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sync_manager.sync(force=True)
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except Exception as exc: # noqa: BLE001 - keep generation success; log for operators
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logger.warning("Could not force-sync generated image artifact: %s", exc)
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payload.setdefault("host_image", image)
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payload.setdefault("agent_visible_image", agent_path)
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return json.dumps(payload, ensure_ascii=False)
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# --- Tool entry point ---
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def _format_images(images: list, should_upscale: bool, prompt: str) -> list:
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"""Normalize FAL result images, optionally chaining the upscaler (falls back to the original on failure)."""
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formatted = []
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for img in images:
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if not (isinstance(img, dict) and "url" in img):
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continue
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if should_upscale:
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upscaled = _upscale_image(img["url"], prompt.strip())
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if upscaled:
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formatted.append(upscaled)
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continue
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logger.warning("Using original image as fallback (upscale failed)")
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formatted.append({
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"url": img["url"], "width": img.get("width", 0), "height": img.get("height", 0),
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"upscaled": False})
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return formatted
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def _prepare_fal_request(model_id, meta, prompt, aspect_ratio, seed, overrides, source_images):
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"""Validate inputs and return ``(endpoint, arguments)``; raises ValueError with the user-facing message."""
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if not isinstance(prompt, str) or not prompt.strip():
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raise ValueError("Prompt is required and must be a non-empty string")
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# A stored-but-broken selection raises the selection-naming error from
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# _resolve_managed_fal_gateway(); only never-configured reports "no backend at all".
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if not (fal_key_is_configured() or _resolve_managed_fal_gateway()):
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raise ValueError(_build_no_backend_setup_message())
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edit_endpoint, display = meta.get("edit_endpoint"), meta.get("display", model_id)
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# Fail clearly rather than silently dropping sources and producing an unrelated picture.
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if source_images and not edit_endpoint:
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raise ValueError(
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f"Model '{display}' ({model_id}) is not capable of image-to-image / editing. "
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f"Provide a text-only prompt (omit image_url), or switch to an edit-capable model "
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f"via `hermes tools` → Image Generation.")
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aspect_lc = (aspect_ratio or DEFAULT_ASPECT_RATIO).lower().strip()
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if aspect_lc not in VALID_ASPECT_RATIOS:
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logger.warning("Invalid aspect_ratio '%s', defaulting to '%s'", aspect_ratio, DEFAULT_ASPECT_RATIO)
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aspect_lc = DEFAULT_ASPECT_RATIO
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if source_images:
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# Clamp reference count to the model's declared cap.
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max_refs = int(meta.get("max_reference_images") or 1)
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clamped_sources = source_images[:max_refs] if max_refs > 0 else source_images
|
|
arguments = _build_fal_edit_payload(
|
|
model_id, prompt, clamped_sources, aspect_lc, seed=seed, overrides=overrides)
|
|
logger.info("Editing image with %s (%s) — %d source image(s), prompt: %s",
|
|
display, edit_endpoint, len(clamped_sources), prompt[:80])
|
|
return edit_endpoint, arguments
|
|
arguments = _build_fal_payload(model_id, prompt, aspect_lc, seed=seed, overrides=overrides)
|
|
logger.info("Generating image with %s (%s) — prompt: %s", display, model_id, prompt[:80])
|
|
return model_id, arguments
|
|
|
|
|
|
def image_generate_tool(
|
|
prompt: str, aspect_ratio: str = DEFAULT_ASPECT_RATIO,
|
|
num_inference_steps: Optional[int] = None, guidance_scale: Optional[float] = None,
|
|
num_images: Optional[int] = None, output_format: Optional[str] = None,
|
|
seed: Optional[int] = None, image_url: Optional[str] = None,
|
|
reference_image_urls: Optional[list] = None, upscale: Optional[bool] = None) -> str:
|
|
"""Generate (or, with source images + an ``edit_endpoint`` model, edit) an image via FAL.
|
|
|
|
Extra kwargs are overrides filtered per-model via ``supports`` / ``edit_supports`` (dropped
|
|
silently so callers survive model switches). Returns JSON ``{"success", "image", "modality",
|
|
"error", "error_type"}``.
|
|
"""
|
|
model_id, meta = _resolve_fal_model()
|
|
refs = reference_image_urls if isinstance(reference_image_urls, (list, tuple)) else []
|
|
source_images = [c.strip() for c in (image_url, *refs) if isinstance(c, str) and c.strip()]
|
|
use_edit = bool(source_images) and bool(meta.get("edit_endpoint"))
|
|
modality = "image" if use_edit else "text"
|
|
overrides: Dict[str, Any] = {
|
|
"num_inference_steps": num_inference_steps, "guidance_scale": guidance_scale,
|
|
"num_images": num_images, "output_format": output_format}
|
|
debug_call_data = {
|
|
"model": model_id,
|
|
"parameters": {"prompt": prompt, "aspect_ratio": aspect_ratio, **overrides, "seed": seed,
|
|
"modality": modality, "source_images": len(source_images)},
|
|
"error": None, "success": False, "images_generated": 0, "generation_time": 0}
|
|
start_time = datetime.datetime.now()
|
|
|
|
def finish(generation_time: float, response: Dict[str, Any]) -> str:
|
|
debug_call_data["generation_time"] = generation_time
|
|
_debug.log_call("image_generate_tool", debug_call_data)
|
|
_debug.save()
|
|
return json.dumps(response, indent=2, ensure_ascii=False)
|
|
try:
|
|
endpoint, arguments = _prepare_fal_request(
|
|
model_id, meta, prompt, aspect_ratio, seed,
|
|
{k: v for k, v in overrides.items() if v is not None}, source_images)
|
|
result = _wait_fal_result(_submit_fal_request(endpoint, arguments=arguments))
|
|
generation_time = (datetime.datetime.now() - start_time).total_seconds()
|
|
if not result or "images" not in result:
|
|
raise ValueError("Invalid response from FAL.ai API — no images returned")
|
|
images = result.get("images", [])
|
|
if not images:
|
|
raise ValueError("No images were generated")
|
|
# Explicit ``upscale`` wins, including for edits; the catalog default never upscales
|
|
# edits (Clarity is a text-to-image pass and must not silently alter compositions).
|
|
if upscale is not None:
|
|
should_upscale = bool(upscale)
|
|
else:
|
|
should_upscale = bool(meta.get("upscale", False)) and not use_edit
|
|
formatted_images = _format_images(images, should_upscale, prompt)
|
|
if not formatted_images:
|
|
raise ValueError("No valid image URLs returned from API")
|
|
upscaled_count = sum(1 for img in formatted_images if img.get("upscaled"))
|
|
logger.info("Generated %s image(s) in %.1fs (%s upscaled) via %s [%s]",
|
|
len(formatted_images), generation_time, upscaled_count, endpoint, modality)
|
|
debug_call_data["success"] = True
|
|
debug_call_data["images_generated"] = len(formatted_images)
|
|
return finish(generation_time, {
|
|
"success": True,
|
|
"image": formatted_images[0]["url"],
|
|
"modality": modality,
|
|
"upscaled": bool(formatted_images[0].get("upscaled"))})
|
|
except Exception as e:
|
|
error_msg = f"Error generating image: {str(e)}"
|
|
logger.error("%s", error_msg, exc_info=True)
|
|
debug_call_data["error"] = error_msg
|
|
generation_time = (datetime.datetime.now() - start_time).total_seconds()
|
|
return finish(generation_time,
|
|
{"success": False, "image": None, "error": str(e), "error_type": type(e).__name__})
|
|
|
|
|
|
def check_fal_api_key() -> bool:
|
|
"""True if the selected FAL backend (never configured: any FAL backend) is available.
|
|
|
|
A stored-but-broken selection reports False here (registry gating); the naming error
|
|
surfaces at call time from ``_resolve_managed_fal_gateway``.
|
|
"""
|
|
try:
|
|
gateway = _resolve_managed_fal_gateway()
|
|
except ValueError:
|
|
return False
|
|
return bool(gateway) or fal_key_is_configured()
|
|
|
|
|
|
def _build_no_backend_setup_message() -> str:
|
|
"""Actionable no-backend error: FAL_KEY signup, managed-gateway status, plugin alternative."""
|
|
managed = managed_nous_tools_enabled()
|
|
lines = ["Image generation is unavailable in this environment.", "", "Missing requirements:"]
|
|
if managed:
|
|
lines.append(" - FAL_KEY is not set and the managed FAL gateway is unreachable")
|
|
else:
|
|
lines.append(" - FAL_KEY environment variable is not set")
|
|
if gateway_message := nous_tool_gateway_unavailable_message("managed FAL image generation"):
|
|
lines.append(f" - {gateway_message}")
|
|
lines += ["", "To enable image generation, do one of:",
|
|
" 1. Get a free API key at https://fal.ai and set FAL_KEY=<your-key> "
|
|
"(then restart the session)"]
|
|
if managed:
|
|
lines.append(" 2. Sign in to a Nous account that has the managed FAL gateway enabled "
|
|
"(`hermes setup`)")
|
|
lines.append(" 3. Configure a different image_gen provider via `hermes tools` → Image Generation "
|
|
"(run `hermes plugins list` to see installed backends)")
|
|
return "\n".join(lines)
|
|
|
|
|
|
def _get_plugin_provider(name: str, *, force: bool = False):
|
|
"""Discover plugins (local import: importing this module must not trigger discovery) and return the named provider."""
|
|
from agent.image_gen_registry import get_provider
|
|
from hermes_cli.plugins import _ensure_plugins_discovered
|
|
if force:
|
|
_ensure_plugins_discovered(force=True)
|
|
else:
|
|
_ensure_plugins_discovered()
|
|
return get_provider(name)
|
|
|
|
|
|
def check_image_generation_requirements() -> bool:
|
|
"""True if FAL or the explicitly configured image backend is available."""
|
|
try:
|
|
if check_fal_api_key():
|
|
# Lazy import doubles as the SDK presence check: ImportError falls through to plugins.
|
|
_load_fal_client()
|
|
return True
|
|
except ImportError:
|
|
pass
|
|
configured = _plugin_provider_name()
|
|
if configured is None:
|
|
return False
|
|
# Probe only the selected plugin: a cloud key alone must not opt a user into a paid backend.
|
|
try:
|
|
provider = _get_plugin_provider(configured)
|
|
return bool(provider and provider.is_available())
|
|
except Exception:
|
|
return False
|
|
|
|
|
|
# --- Registry ---
|
|
from tools.registry import registry, tool_error
|
|
|
|
IMAGE_GENERATE_SCHEMA = {
|
|
"name": "image_generate",
|
|
# Placeholder: description AND params are rebuilt at get_tool_definitions() time by
|
|
# _build_dynamic_image_schema() from the active backend's capabilities. Edit-only args
|
|
# and upscale are advertised ONLY when supported; the handler accepts them regardless
|
|
# (replay compat + teaching errors).
|
|
"description": (
|
|
"Generate images from text prompts. The active model's edit/reference "
|
|
"capabilities are rendered at serving time."
|
|
),
|
|
"parameters": {
|
|
"type": "object",
|
|
"properties": {
|
|
"prompt": {
|
|
"type": "string",
|
|
"description": (
|
|
"The text prompt describing the desired image (text-to-"
|
|
"image) or the edit to apply (image-to-image). Be detailed "
|
|
"and descriptive."
|
|
),
|
|
},
|
|
"aspect_ratio": {
|
|
"type": "string",
|
|
"enum": list(VALID_ASPECT_RATIOS),
|
|
"description": "The aspect ratio of the generated image. 'landscape' is 16:9 wide, 'portrait' is 16:9 tall, 'square' is 1:1.",
|
|
"default": DEFAULT_ASPECT_RATIO,
|
|
},
|
|
# image_url / reference_image_urls / upscale are added per-capability; never statically.
|
|
},
|
|
# See #95681.
|
|
"required": ["prompt"],
|
|
},
|
|
}
|
|
|
|
|
|
# --- Plugin provider dispatch + managed-mode Krea routing ---
|
|
def _provider_error(error: str, error_type: str) -> str:
|
|
"""JSON error envelope shared by every provider-dispatch failure path."""
|
|
return json.dumps({"success": False, "image": None, "error": error, "error_type": error_type})
|
|
|
|
|
|
def _provider_result(result, contract_error: str) -> str:
|
|
"""JSON-encode a provider's dict result; anything else is a contract violation."""
|
|
if not isinstance(result, dict):
|
|
return _provider_error(contract_error, "provider_contract")
|
|
return json.dumps(result)
|
|
|
|
|
|
def _add_provider_kwargs(kwargs, image_url, reference_image_urls, upscale, model=None) -> Dict[str, Any]:
|
|
"""Add the optional ``provider.generate(**kwargs)`` args in place (edit args only when supplied)."""
|
|
if model:
|
|
kwargs["model"] = model
|
|
if isinstance(image_url, str) and image_url.strip():
|
|
kwargs["image_url"] = image_url.strip()
|
|
if reference_image_urls is not None:
|
|
from agent.image_gen_provider import normalize_reference_images
|
|
norm_refs = normalize_reference_images(reference_image_urls)
|
|
if norm_refs:
|
|
kwargs["reference_image_urls"] = norm_refs
|
|
if upscale is not None:
|
|
kwargs["upscale"] = bool(upscale)
|
|
return kwargs
|
|
|
|
|
|
def _dispatch_to_plugin_provider(
|
|
prompt: str, aspect_ratio: str, image_url: Optional[str] = None,
|
|
reference_image_urls: Optional[list] = None, upscale: Optional[bool] = None):
|
|
"""JSON result from the selected plugin provider, or ``None`` to fall through to in-tree FAL
|
|
(provider unset / ``"fal"`` / ``"nous"``). Providers without ``upscale`` ignore it via ``**kwargs``."""
|
|
configured = _plugin_provider_name()
|
|
if configured is None:
|
|
return None
|
|
try:
|
|
provider = _get_plugin_provider(configured)
|
|
except Exception as exc:
|
|
logger.debug("image_gen plugin dispatch skipped: %s", exc)
|
|
return None
|
|
if provider is None:
|
|
# Long-lived sessions may have discovered plugins before a bundled backend
|
|
# was patched in or config changed: retry once with a forced refresh.
|
|
try:
|
|
provider = _get_plugin_provider(configured, force=True)
|
|
except Exception as exc:
|
|
logger.debug("image_gen plugin force-refresh skipped: %s", exc)
|
|
if provider is None:
|
|
return _provider_error(
|
|
f"image_gen.provider='{configured}' is set but no plugin registered that name. "
|
|
f"Run `hermes plugins list` to see available image gen backends.", "provider_not_registered")
|
|
pname = getattr(provider, "name", "?")
|
|
kwargs: Dict[str, Any] = {"prompt": prompt, "aspect_ratio": aspect_ratio}
|
|
try:
|
|
_add_provider_kwargs(kwargs, image_url, reference_image_urls, upscale,
|
|
model=_read_configured_image_model())
|
|
result = provider.generate(**kwargs)
|
|
except Exception as exc:
|
|
# A TypeError from generate() predating image_url support (third-party plugin not yet
|
|
# updated): text-to-image keeps working; surface a clear note when an edit was requested.
|
|
is_type_error = isinstance(exc, TypeError)
|
|
if is_type_error and ("image_url" in kwargs or "reference_image_urls" in kwargs):
|
|
logger.warning("image_gen provider '%s' rejected image-to-image kwargs "
|
|
"(signature too narrow): %s", pname, exc)
|
|
return _provider_error(
|
|
f"Provider '{pname}' does not support image-to-image / editing (its generate() "
|
|
f"signature is out of date with the image_generate schema). Omit image_url for "
|
|
f"text-to-image, or pick a backend that supports editing via `hermes tools` → "
|
|
f"Image Generation.", "modality_unsupported")
|
|
logger.warning("Image gen provider '%s' raised%s: %s", pname,
|
|
" TypeError" if is_type_error else "", exc)
|
|
return _provider_error(f"Provider '{pname}' error: {exc}", "provider_exception")
|
|
return _provider_result(result, "Provider returned a non-dict result")
|
|
|
|
|
|
# Native ``krea-2-*`` ids are served by the Krea managed gateway (managed mode only —
|
|
# direct/BYO users keep their pipeline); ``fal-ai/krea/v2/*`` catalog ids stay on FAL.
|
|
_KREA_NATIVE_MODELS = {"krea-2-medium", "krea-2-large", "krea-2-medium-turbo"}
|
|
|
|
|
|
def _normalize_krea_model(model_id: Optional[str]) -> Optional[str]:
|
|
"""Return the native Krea plugin model id when ``model_id`` is ``krea-2-*``."""
|
|
candidate = model_id.strip() if isinstance(model_id, str) else None
|
|
return candidate if candidate in _KREA_NATIVE_MODELS else None
|
|
|
|
|
|
def _maybe_route_managed_krea(
|
|
prompt: str, aspect_ratio: str, image_url: Optional[str] = None,
|
|
reference_image_urls: Optional[list] = None, upscale: Optional[bool] = None) -> Optional[str]:
|
|
"""JSON result from the managed Krea gateway, or ``None`` to fall through.
|
|
|
|
Fires only for a native ``krea-2-*`` model with no ``image_gen.provider`` other than
|
|
``"nous"`` stored (a picker choice dispatches normally) and a resolvable Krea gateway.
|
|
"""
|
|
configured_provider = _read_configured_image_provider()
|
|
if configured_provider is not None and configured_provider != NOUS_MANAGED_PROVIDER:
|
|
return None
|
|
normalized = _normalize_krea_model(_read_configured_image_model())
|
|
if normalized is None:
|
|
return None
|
|
try:
|
|
from plugins.image_gen.krea import _resolve_managed_krea_gateway
|
|
if _resolve_managed_krea_gateway() is None:
|
|
return None
|
|
provider = _get_plugin_provider("krea")
|
|
except Exception as exc: # noqa: BLE001
|
|
logger.debug("Managed Krea routing unavailable: %s", exc)
|
|
return None
|
|
if provider is None:
|
|
return None
|
|
kwargs: Dict[str, Any] = {"prompt": prompt, "aspect_ratio": aspect_ratio, "model": normalized}
|
|
try:
|
|
_add_provider_kwargs(kwargs, image_url, reference_image_urls, upscale)
|
|
result = provider.generate(**kwargs)
|
|
except Exception as exc: # noqa: BLE001
|
|
logger.warning("Managed Krea routing failed: %s", exc)
|
|
return _provider_error(f"Managed Krea generation error: {exc}", "provider_exception")
|
|
return _provider_result(result, "Krea provider returned a non-dict result")
|
|
|
|
|
|
def _confine_source_images(image_url, reference_image_urls, task_id, *, permitted: tuple = ("image",)):
|
|
"""Resolve path-like sources to ``data:`` URLs under a non-local terminal backend.
|
|
|
|
Routes through ``tools.image_source`` (in-sandbox exec-read, media-cache host reads,
|
|
credential guard) so generation obeys the same confinement as vision. URLs/data: pass
|
|
through; local backend is a no-op. Returns ``(image_url, reference_image_urls, error_json_or_None)``.
|
|
"""
|
|
if (os.getenv("TERMINAL_ENV") or "local").strip().lower() in ("", "local"):
|
|
return image_url, reference_image_urls, None
|
|
from model_tools import _run_async
|
|
from tools.image_source import ImageResolutionError, resolve_local_source_to_data_url
|
|
|
|
def resolve(ref):
|
|
return _run_async(resolve_local_source_to_data_url(ref, task_id, permitted=permitted))
|
|
try:
|
|
if isinstance(image_url, str) and image_url.strip():
|
|
image_url = resolve(image_url)
|
|
if isinstance(reference_image_urls, (list, tuple)):
|
|
reference_image_urls = [resolve(r) if isinstance(r, str) else r for r in reference_image_urls]
|
|
except ImageResolutionError as exc:
|
|
return image_url, reference_image_urls, _provider_error(
|
|
f"Could not read source image: {exc}", type(exc).__name__)
|
|
return image_url, reference_image_urls, None
|
|
|
|
|
|
def _handle_image_generate(args, **kw):
|
|
prompt = args.get("prompt", "")
|
|
if not prompt:
|
|
return tool_error("prompt is required for image generation")
|
|
aspect_ratio = args.get("aspect_ratio", DEFAULT_ASPECT_RATIO)
|
|
upscale = args.get("upscale")
|
|
task_id = kw.get("task_id")
|
|
# Confinement chokepoint BEFORE any dispatch: every route receives sandbox-confined bytes.
|
|
image_url, reference_image_urls, confine_error = _confine_source_images(
|
|
args.get("image_url"), args.get("reference_image_urls"), task_id)
|
|
if confine_error is not None:
|
|
return confine_error
|
|
# Order matters: explicit plugin provider (incl. "krea"), then model-driven managed Krea
|
|
# interception (only when no provider is set, so BYO/direct FAL stays untouched), then FAL.
|
|
sources = dict(image_url=image_url, reference_image_urls=reference_image_urls,
|
|
upscale=upscale if isinstance(upscale, bool) else None)
|
|
raw = None
|
|
for route in (_dispatch_to_plugin_provider, _maybe_route_managed_krea, image_generate_tool):
|
|
raw = route(prompt, aspect_ratio, **sources)
|
|
if raw is not None:
|
|
break
|
|
return _postprocess_image_generate_result(raw, task_id=task_id)
|
|
|
|
|
|
# --- Dynamic schema — reflect the active backend's image-to-image capability ---
|
|
# Advertising edit capability up front saves a wasted turn. Memoized by config.yaml mtime in
|
|
# model_tools.get_tool_definitions(), so it rebuilds on switch.
|
|
_NO_CAPABILITIES = {"modalities": ["text"], "max_reference_images": 0, "supports_upscale": False}
|
|
|
|
|
|
def _active_image_capabilities() -> Dict[str, Any]:
|
|
"""Best-effort capabilities of the active backend/model; never raises.
|
|
|
|
Mirrors runtime dispatch: a set ``image_gen.provider`` asks that plugin, else the FAL
|
|
catalog. Fail-closed: an undeclared capability is advertised as absent.
|
|
"""
|
|
info: Dict[str, Any] = dict(_NO_CAPABILITIES)
|
|
configured_provider = _read_configured_image_provider()
|
|
if configured_provider and configured_provider != "fal":
|
|
try:
|
|
provider = _get_plugin_provider(configured_provider)
|
|
if provider is not None:
|
|
try:
|
|
caps = provider.capabilities() or {}
|
|
except Exception: # noqa: BLE001
|
|
caps = {}
|
|
info["provider"] = provider.display_name
|
|
info["model"] = _read_configured_image_model() or (provider.default_model() or "")
|
|
if caps.get("modalities"):
|
|
info["modalities"] = list(caps["modalities"])
|
|
if caps.get("max_reference_images"):
|
|
info["max_reference_images"] = int(caps["max_reference_images"])
|
|
# Plugins opt in explicitly; absent = no upscale param.
|
|
info["supports_upscale"] = bool(caps.get("supports_upscale"))
|
|
return info
|
|
except Exception: # noqa: BLE001
|
|
pass
|
|
# In-tree FAL path (provider unset or == "fal"); _resolve_fal_model() never raises.
|
|
model_id, meta = _resolve_fal_model()
|
|
can_edit = bool(meta.get("edit_endpoint"))
|
|
info["provider"] = "FAL.ai"
|
|
info["model"] = meta.get("display", model_id)
|
|
info["modalities"] = ["text", "image"] if can_edit else ["text"]
|
|
info["max_reference_images"] = int(meta.get("max_reference_images") or 1) if can_edit else 0
|
|
# Clarity is available on request for ANY catalog model (``upscale`` is only the default).
|
|
info["supports_upscale"] = True
|
|
return info
|
|
|
|
|
|
# Param snippets assembled per-capability by _build_dynamic_image_schema.
|
|
_IMAGE_URL_PARAM = {
|
|
"type": "string",
|
|
"description": (
|
|
"Source image to edit/transform (image-to-image). A public URL or "
|
|
"an absolute local file path from the conversation. Omit for "
|
|
"text-to-image."
|
|
),
|
|
}
|
|
|
|
_UPSCALE_PARAM = {
|
|
"type": "boolean",
|
|
"description": (
|
|
"Post-generation high-resolution pass (~2x, extra cost/latency), "
|
|
"off by default. A creative enhancer that can alter fine detail "
|
|
"(rendered text, faces) — use only when resolution matters more "
|
|
"than fidelity."
|
|
),
|
|
}
|
|
|
|
|
|
def _build_dynamic_image_schema() -> Dict[str, Any]:
|
|
"""Render description AND params from the active model's capabilities; args it cannot
|
|
honor are NOT advertised (the handler still accepts them for replay compat)."""
|
|
base_desc = (
|
|
"Generate high-quality images from text prompts{edit_clause}. "
|
|
"Returns the result in the `image` field — a URL or an absolute "
|
|
"file path; reference it in your response using the current "
|
|
"platform's file-delivery convention."
|
|
)
|
|
info = _active_image_capabilities()
|
|
max_refs = int(info.get("max_reference_images") or 0)
|
|
can_edit = "image" in set(info.get("modalities") or ["text"])
|
|
static_props = IMAGE_GENERATE_SCHEMA["parameters"]["properties"]
|
|
properties: Dict[str, Any] = {
|
|
"prompt": static_props["prompt"], "aspect_ratio": static_props["aspect_ratio"]}
|
|
if can_edit:
|
|
edit_clause = ", or edit / transform an existing image by passing image_url"
|
|
properties["image_url"] = _IMAGE_URL_PARAM
|
|
if max_refs > 1:
|
|
properties["reference_image_urls"] = {
|
|
"type": "array",
|
|
"items": {"type": "string"},
|
|
"maxItems": max_refs,
|
|
"description": (
|
|
f"Up to {max_refs} additional reference images (style, "
|
|
"character, or composition) guiding an edit. URLs or "
|
|
"absolute local paths."
|
|
),
|
|
}
|
|
else:
|
|
edit_clause = " (text-to-image only — the active model cannot edit existing images)"
|
|
if info.get("supports_upscale"):
|
|
properties["upscale"] = _UPSCALE_PARAM
|
|
return {"description": base_desc.format(edit_clause=edit_clause),
|
|
"parameters": {"type": "object", "properties": properties, "required": ["prompt"]}}
|
|
|
|
|
|
registry.register(
|
|
name="image_generate", toolset="image_gen", schema=IMAGE_GENERATE_SCHEMA,
|
|
handler=_handle_image_generate, check_fn=check_image_generation_requirements, requires_env=[],
|
|
is_async=False, # sync fal_client API to avoid "Event loop is closed" in gateway
|
|
emoji="🎨", dynamic_schema_overrides=_build_dynamic_image_schema,
|
|
)
|
|
|
|
|
|
# ---- BEGIN PLUGIN-COMPAT (revert-scheduled; see COMPAT_MANIFEST.md) ----
|
|
# Names external plugins imported from this module before the Sep 2026 decomposition.
|
|
# Internal code MUST NOT use these (scripts/check_compat_pointers.py fails CI if it does).
|
|
# The whole block is removed by reverting the commit that added it.
|
|
|
|
def is_krea_model(model_id: Optional[str]) -> bool:
|
|
"""True when ``model_id`` is a native Krea plugin id (``krea-2-*``)."""
|
|
return _normalize_krea_model(model_id) is not None
|
|
# ---- END PLUGIN-COMPAT ----
|