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aiturk-hermes-ide/tools/video_generation_tool.py
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615 lines
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#!/usr/bin/env python3
"""
Video Generation Tool
=====================
Single ``video_generate`` tool that dispatches to a plugin-registered
video generation provider. Mirrors the ``image_generate`` design:
- ``agent/video_gen_provider.py`` defines the :class:`VideoGenProvider` ABC.
- ``agent/video_gen_registry.py`` holds the active providers (populated by
plugins at import time).
- Each provider lives under ``plugins/video_gen/<name>/``.
The tool itself is intentionally backend-agnostic and ships **no in-tree
provider** — turn on a backend by enabling a plugin (``hermes plugins
enable video_gen/<name>``) and selecting it in ``hermes tools`` → Video
Generation.
Unified surface
---------------
One tool covers the common cases - text-to-video, image-to-video, and
reference-to-video - with a compact schema:
prompt text instruction (required)
image_url drives image-to-video
reference_image_urls list, up to provider-declared cap
duration seconds (provider clamps)
aspect_ratio "16:9" | "9:16" | "1:1" | ...
resolution "480p" | "540p" | "720p" | "1080p"
negative_prompt optional (Pixverse/Kling style)
audio optional (Veo3/Pixverse pricing tier)
seed optional
model optional, override the active provider's default
Providers ignore parameters they do not support. The tool layer does
**lightweight** validation (type/required-prompt) and lets each provider
do its own clamping inside :meth:`VideoGenProvider.generate` — that keeps
the tool surface stable as new providers ship with different capabilities.
Video edit and video extend are intentionally not exposed here; providers with
those workflows should expose separate tools.
"""
from __future__ import annotations
import json
import logging
from typing import Any, Dict, List, Optional
from agent.video_gen_provider import (
COMMON_ASPECT_RATIOS,
COMMON_RESOLUTIONS,
DEFAULT_ASPECT_RATIO,
DEFAULT_RESOLUTION,
error_response,
)
from tools.registry import registry, tool_error
logger = logging.getLogger(__name__)
VIDEO_GENERATE_SCHEMA: Dict[str, Any] = {
"name": "video_generate",
# Placeholder — description AND params are rebuilt dynamically at
# get_tool_definitions() time from the active provider's declared
# capabilities() and the active model's catalog entry. Optional args
# (image_url, reference_image_urls, negative_prompt, audio, seed,
# upscale) are advertised ONLY when the active backend/model honors
# them; the handler accepts them regardless (replay compat — providers
# clamp/ignore). See _build_dynamic_video_schema().
"description": "(rebuilt at get_definitions() time — see _build_dynamic_video_schema)",
"parameters": {
"type": "object",
"properties": {
"prompt": {
"type": "string",
"description": (
"Text instruction describing the desired video, motion, "
"subject, style, camera movement, etc."
),
},
"duration": {
"type": "integer",
"description": (
"Desired video duration in seconds. Providers clamp to "
"their supported range. Omit for the provider default."
),
},
"aspect_ratio": {
"type": "string",
"enum": list(COMMON_ASPECT_RATIOS),
"description": "Output aspect ratio.",
"default": DEFAULT_ASPECT_RATIO,
},
"resolution": {
"type": "string",
"enum": list(COMMON_RESOLUTIONS),
"description": "Output resolution.",
"default": DEFAULT_RESOLUTION,
},
"model": {
"type": "string",
"description": (
"Optional model override; defaults to the configured "
"``video_gen.model``. Unknown models are rejected."
),
},
# NOTE (schema diet, #95681): image_url / reference_image_urls /
# negative_prompt / audio / seed / upscale are added
# per-capability by _build_dynamic_video_schema. Do not re-add
# them statically.
},
"required": ["prompt"],
},
}
# ---------------------------------------------------------------------------
# Config readers (mirror image_generation_tool.py)
# ---------------------------------------------------------------------------
def _read_video_gen_section() -> Dict[str, Any]:
try:
from hermes_cli.config import load_config
cfg = load_config()
section = cfg.get("video_gen") if isinstance(cfg, dict) else None
return section if isinstance(section, dict) else {}
except Exception as exc:
logger.debug("Could not read video_gen config: %s", exc)
return {}
def _read_configured_video_provider() -> Optional[str]:
value = _read_video_gen_section().get("provider")
if isinstance(value, str) and value.strip():
return value.strip()
return None
def _read_configured_video_model() -> Optional[str]:
value = _read_video_gen_section().get("model")
if isinstance(value, str) and value.strip():
return value.strip()
return None
# ---------------------------------------------------------------------------
# Availability check
# ---------------------------------------------------------------------------
def check_video_generation_requirements() -> bool:
"""Return True when at least one registered provider reports available.
Triggers plugin discovery (idempotent) so user-installed plugins are
visible to the toolset gate.
"""
try:
from agent.video_gen_registry import list_providers
from hermes_cli.plugins import _ensure_plugins_discovered
_ensure_plugins_discovered()
for provider in list_providers():
try:
if provider.is_available():
return True
except Exception:
continue
except Exception:
pass
return False
# ---------------------------------------------------------------------------
# Dispatch
# ---------------------------------------------------------------------------
def _resolve_active_provider():
"""Return the active provider object or None.
Forces plugin discovery before checking the registry — handles cases
where a long-lived session was started before a plugin was installed.
"""
try:
from agent.video_gen_registry import get_active_provider
from hermes_cli.plugins import _ensure_plugins_discovered
_ensure_plugins_discovered()
provider = get_active_provider()
if provider is None:
_ensure_plugins_discovered(force=True)
provider = get_active_provider()
return provider
except Exception as exc:
logger.debug("video_gen provider resolution failed: %s", exc)
return None
def _missing_provider_error(configured: Optional[str]) -> str:
if configured:
msg = (
f"video_gen.provider='{configured}' is set but no plugin "
f"registered that name. Run `hermes plugins list` to see "
f"installed video gen backends, or `hermes tools` → Video "
f"Generation to pick one."
)
return json.dumps(error_response(
error=msg, error_type="provider_not_registered",
provider=configured,
))
msg = (
"No video generation backend is configured. Run `hermes tools` → "
"Video Generation to enable one (xAI, FAL, or Google Veo)."
)
return json.dumps(error_response(
error=msg, error_type="no_provider_configured",
))
# ---------------------------------------------------------------------------
# Handler
# ---------------------------------------------------------------------------
def _coerce_int(value: Any) -> Optional[int]:
if value is None or value == "":
return None
try:
return int(value)
except (TypeError, ValueError):
return None
def _coerce_bool(value: Any) -> Optional[bool]:
if value is None:
return None
if isinstance(value, bool):
return value
if isinstance(value, str):
v = value.strip().lower()
if v in {"true", "1", "yes", "on"}:
return True
if v in {"false", "0", "no", "off"}:
return False
return None
def _normalize_reference_images(value: Any) -> Optional[List[str]]:
if value is None:
return None
if isinstance(value, str):
value = [value]
if not isinstance(value, (list, tuple)):
return None
out: List[str] = []
for item in value:
if isinstance(item, str) and item.strip():
out.append(item.strip())
return out or None
def _handle_video_generate(args: Dict[str, Any], **_kw: Any) -> str:
prompt = (args.get("prompt") or "").strip()
image_url = (args.get("image_url") or "").strip() or None
reference_image_urls = _normalize_reference_images(args.get("reference_image_urls"))
task_id = _kw.get("task_id")
# Terminal-backend confinement chokepoint (mirrors image_generate): under
# a non-local backend, path-like source images resolve through the shared
# sandbox-aware resolver and reach providers as data: URLs.
from tools.image_generation_tool import _confine_source_images
image_url, reference_image_urls, confine_error = _confine_source_images(
image_url, reference_image_urls, task_id)
if confine_error is not None:
return confine_error
duration = _coerce_int(args.get("duration"))
aspect_ratio = (args.get("aspect_ratio") or DEFAULT_ASPECT_RATIO).strip() or DEFAULT_ASPECT_RATIO
resolution = (args.get("resolution") or DEFAULT_RESOLUTION).strip() or DEFAULT_RESOLUTION
negative_prompt = (args.get("negative_prompt") or "").strip() or None
audio = _coerce_bool(args.get("audio"))
seed = _coerce_int(args.get("seed"))
upscale = _coerce_bool(args.get("upscale"))
model_override = (args.get("model") or "").strip() or None
# Soft validation — providers do their own. Prompt is required by the
# schema; the backend may still accept image-only on its image-to-video
# endpoint but our surface always needs a prompt.
if not prompt:
return tool_error("prompt is required for video generation")
if "operation" in args or "video_url" in args:
return tool_error(
"video_generate only supports text-to-video, image-to-video, and "
"reference-to-video; use a provider-specific tool for video edit/extend"
)
# Resolve the active provider.
configured = _read_configured_video_provider()
provider = _resolve_active_provider()
if provider is None:
return _missing_provider_error(configured)
# Resolve model: explicit arg wins, then config, then provider default.
model = model_override or _read_configured_video_model() or provider.default_model()
kwargs: Dict[str, Any] = {
"model": model,
"_model_override_explicit": bool(model_override),
"image_url": image_url,
"reference_image_urls": reference_image_urls,
"duration": duration,
"aspect_ratio": aspect_ratio,
"resolution": resolution,
"negative_prompt": negative_prompt,
"audio": audio,
"seed": seed,
"upscale": upscale,
}
# Drop None entries so providers see clean defaults.
kwargs = {k: v for k, v in kwargs.items() if v is not None}
try:
result = provider.generate(prompt=prompt, **kwargs)
except TypeError as exc:
# A provider that hasn't widened its signature is a bug, not a
# caller error — log and surface a clear contract message.
logger.warning(
"video_gen provider '%s' rejected kwargs (signature too narrow): %s",
getattr(provider, "name", "?"), exc,
)
return json.dumps(error_response(
error=(
f"Provider '{getattr(provider, 'name', '?')}' signature is "
f"out of date with the video_generate schema. Report this "
f"to the plugin author."
),
error_type="provider_contract",
provider=getattr(provider, "name", ""),
model=model or "",
prompt=prompt,
))
except Exception as exc:
logger.warning(
"video_gen provider '%s' raised: %s",
getattr(provider, "name", "?"), exc,
)
return json.dumps(error_response(
error=f"Provider '{getattr(provider, 'name', '?')}' error: {exc}",
error_type="provider_exception",
provider=getattr(provider, "name", ""),
model=model or "",
prompt=prompt,
))
if not isinstance(result, dict):
return json.dumps(error_response(
error="Provider returned a non-dict result",
error_type="provider_contract",
provider=getattr(provider, "name", ""),
model=model or "",
prompt=prompt,
))
return json.dumps(result)
# ---------------------------------------------------------------------------
# Dynamic schema — reflect the active backend's actual capabilities
# ---------------------------------------------------------------------------
#
# Why dynamic: the user's configured backend determines which modalities
# (text / image / refs), aspect ratios, resolutions, durations, and
# audio/negative-prompt flags are real. A model that calls video_generate
# without knowing the active backend wastes a turn on something like
# "fal-ai/veo3.1/image-to-video requires image_url". Surfacing the per-model
# surface in the description means the model usually gets the call right on
# the first try.
#
# Memoization: model_tools.get_tool_definitions() keys its cache on
# config.yaml mtime, so when the user changes provider/model via
# `hermes tools` or `/skills`, the schema rebuilds automatically.
_GENERIC_DESCRIPTION = (
"Generate a video from a text prompt (text-to-video), animate a "
"still image (image-to-video), or guide generation with reference images. "
"Pass `image_url` to animate an image or `reference_image_urls` for "
"reference-to-video. Video edit/extend workflows are not part of this "
"unified surface; use a dedicated provider-specific tool when one is "
"available. The backend and model family are user-configured via "
"`hermes tools` → Video Generation; the agent does not pick them. "
"Long-running generations may take 30 seconds to several minutes — "
"the call blocks until the video is ready. Returns the result in the "
"`video` field — either an HTTP URL or an absolute file path. To show "
"it to the user, reference that path/URL in your response using the "
"file-delivery convention for the current platform (your platform "
"guidance describes how files are delivered here)."
)
def _format_model_caveats(
model_meta: Dict[str, Any],
backend_caps: Dict[str, Any],
) -> List[str]:
"""Pull human-readable caveats out of one model's catalog metadata.
Only surfaces things that meaningfully differ from the backend's
overall capabilities — repeating defaults is noise.
"""
caveats: List[str] = []
modalities = set(model_meta.get("modalities") or [])
modality = model_meta.get("modality") # FAL's plugin uses this key for single-modality entries
if modality:
modalities.add(modality)
if "image" in modalities and "text" not in modalities:
caveats.append(
"this model is image-to-video only — image_url is REQUIRED; "
"text-only calls will be rejected"
)
elif "text" in modalities and "image" not in modalities:
caveats.append(
"this model is text-to-video only — image_url is not supported"
)
return caveats
def _build_dynamic_video_schema() -> Dict[str, Any]:
"""Render description AND params from the active backend's declared surface.
Optional args are advertised only when the resolved provider/model
honors them (capabilities() + the model's catalog entry — coverage is
contract-tested per provider); enums and duration bounds tighten to
the active model's actual sets. The handler still accepts unadvertised
args (replay compat): providers clamp or ignore, as before.
"""
static_props = VIDEO_GENERATE_SCHEMA["parameters"]["properties"]
parts: List[str] = [_GENERIC_DESCRIPTION]
configured_model = _read_configured_video_model()
provider = _resolve_active_provider()
if provider is None:
parts.append(
"\nNo video backend is available. Calls will return an error "
"until the user picks one via `hermes tools` → Video Generation."
)
return {
"description": "\n".join(parts),
"parameters": {
"type": "object",
"properties": {"prompt": static_props["prompt"]},
"required": ["prompt"],
},
}
try:
caps = provider.capabilities() or {}
except Exception:
caps = {}
try:
models = provider.list_models() or []
except Exception:
models = []
active_model = configured_model or provider.default_model()
model_meta = next(
(m for m in models if isinstance(m, dict) and m.get("id") == active_model),
{},
)
# ---- description -------------------------------------------------
for c in _format_model_caveats(model_meta, caps):
parts.append(f"- {c}")
model_modalities = set(model_meta.get("modalities") or [])
modality = model_meta.get("modality")
if modality:
model_modalities.add(modality)
effective_modalities = model_modalities or set(caps.get("modalities") or [])
can_i2v = "image" in effective_modalities
t2v = "text" in effective_modalities
if can_i2v and not t2v:
parts.append("- image-to-video only: image_url is REQUIRED")
elif not can_i2v:
parts.append("- text-to-video only (no image input)")
if provider.name == "xai":
parts.append(
"- chaining: for edit/extend pass the public HTTPS MP4 in `video` "
"or `public_url` from the prior Imagine result (files-cdn). For "
"image-to-video / reference-to-video pass public image URLs the "
"same way"
)
try:
from tools.xai_http import xai_storage_notice_text
notice = xai_storage_notice_text("video_gen")
except Exception:
notice = ""
if notice:
parts.append(f"- storage: {notice}")
# ---- params ------------------------------------------------------
properties: Dict[str, Any] = {"prompt": static_props["prompt"]}
if can_i2v:
properties["image_url"] = {
"type": "string",
"description": (
"Public HTTPS URL of a still image to animate "
"(image-to-video). Omit for text-to-video."
),
}
max_refs = int(caps.get("max_reference_images") or 0)
if max_refs > 0:
properties["reference_image_urls"] = {
"type": "array",
"items": {"type": "string"},
"maxItems": max_refs,
"description": (
f"Up to {max_refs} public HTTPS reference image URLs "
"(style or character refs)."
),
}
min_duration = model_meta.get("min_duration", caps.get("min_duration"))
max_duration = model_meta.get("max_duration", caps.get("max_duration"))
duration_param = dict(static_props["duration"])
if min_duration and max_duration:
duration_param["minimum"] = int(min_duration)
duration_param["maximum"] = int(max_duration)
duration_param["description"] = (
f"Video duration in seconds ({min_duration}-{max_duration}). "
"Omit for the provider default."
)
properties["duration"] = duration_param
# Tighten enums to the active backend's actual sets when declared.
aspect_param = dict(static_props["aspect_ratio"])
if caps.get("aspect_ratios"):
aspect_param["enum"] = list(caps["aspect_ratios"])
properties["aspect_ratio"] = aspect_param
resolution_param = dict(static_props["resolution"])
if caps.get("resolutions"):
resolution_param["enum"] = list(caps["resolutions"])
properties["resolution"] = resolution_param
if caps.get("supports_negative_prompt"):
properties["negative_prompt"] = {
"type": "string",
"description": "Content to avoid in the output.",
}
if caps.get("supports_audio"):
properties["audio"] = {
"type": "boolean",
"description": (
"Enable native audio generation (affects pricing tier)."
),
}
elif caps.get("audio_always_on"):
parts.append(
"- audio: native stereo audio is generated with every video "
"(always on; no toggle) — describe the desired sound in the "
"prompt"
)
if caps.get("supports_seed"):
properties["seed"] = {
"type": "integer",
"description": "Seed for reproducible outputs.",
}
if caps.get("supports_upscale"):
properties["upscale"] = {
"type": "boolean",
"description": (
"High-resolution pass via the backend's video upscaler "
"(~2x, extra cost/latency). Omit for native resolution."
),
}
properties["model"] = static_props["model"]
return {
"description": "\n".join(parts),
"parameters": {
"type": "object",
"properties": properties,
"required": ["prompt"],
},
}
# ---------------------------------------------------------------------------
# Registry
# ---------------------------------------------------------------------------
registry.register(
name="video_generate",
toolset="video_gen",
schema=VIDEO_GENERATE_SCHEMA,
handler=_handle_video_generate,
check_fn=check_video_generation_requirements,
requires_env=[],
is_async=False,
emoji="🎬",
dynamic_schema_overrides=_build_dynamic_video_schema,
)