hermes-agent/agent/video_gen_provider.py
Teknium 9d42c2c286
feat(video_gen): unified video_generate tool with pluggable provider backends (#25126)
* feat(video_gen): unified video_generate tool with pluggable provider backends

One core video_generate tool, every backend a plugin. Mirrors the
image_gen + memory_provider + context_engine architecture: ABC, registry,
plugin-context registration hook, and per-plugin model catalogs surfaced
through hermes tools.

Surface (one schema, every backend):
- operation: generate / edit / extend
- modalities: text-to-video (prompt only), image-to-video (prompt +
  image_url), video edit (prompt + video_url), video extend (video_url)
- reference_image_urls, duration, aspect_ratio, resolution,
  negative_prompt, audio, seed, model override
- Providers ignore unknown kwargs and declare what they support via
  VideoGenProvider.capabilities() — backend-specific quirks stay in the
  backend, the agent learns one tool

Backends shipped:
- plugins/video_gen/xai/  — Grok-Imagine, full generate/edit/extend +
  image-to-video + reference images (salvaged from PR #10600 by
  @Jaaneek, reshaped into the plugin interface)
- plugins/video_gen/fal/  — Veo 3.1 (t2v + i2v), Kling O3 i2v,
  Pixverse v6 i2v with model-aware payload building that drops keys a
  model doesn't declare

Wiring:
- agent/video_gen_provider.py — VideoGenProvider ABC, normalize_operation,
  success_response / error_response, save_b64_video / save_bytes_video,
  $HERMES_HOME/cache/videos/
- agent/video_gen_registry.py — thread-safe register/get/list +
  get_active_provider() reading video_gen.provider from config.yaml
- hermes_cli/plugins.py — PluginContext.register_video_gen_provider()
- hermes_cli/tools_config.py — Video Generation category in
  hermes tools, plugin-only providers list, model picker per plugin,
  config write to video_gen.{provider,model}
- toolsets.py — new video_gen toolset
- tests: 31 new tests covering ABC, registry, tool dispatch, both plugins
- docs: developer-guide/video-gen-provider-plugin.md (parallel to the
  image-gen guide), sidebar + toolsets-reference + plugin guides updated

Supersedes: #25035 (FAL), #17972 (FAL), #14543 (xAI), #13847 (HappyHorse),
#10458 (provider categories), #10786 (xAI media+search bundle), #2984
(FAL duplicate), #19086 (Google Veo standalone — easy port to plugin
interface).

Co-authored-by: Jaaneek <Jaaneek@users.noreply.github.com>

* feat(video_gen): dynamic schema reflects active backend's capabilities

Address the 'capability variance' question — instead of one tool with a
static schema that lies about what every backend supports, the
video_generate tool now rebuilds its description at get_definitions()
time based on the configured video_gen.provider and video_gen.model.

The agent sees backend-specific guidance up-front:
- 'fal-ai/veo3.1/image-to-video': 'image-to-video only — image_url is
  REQUIRED; text-only prompts will be rejected'
- 'fal-ai/veo3.1' (t2v): no image_url restriction shown
- xAI grok-imagine-video: 'operations: generate, edit, extend; up to 7
  reference_image_urls'
- Backends without edit/extend: 'not supported on this backend — surface
  that they need to switch backends via hermes tools'

This is the same pattern PR #22694 used for delegate_task self-capping —
documented in the dynamic-tool-schemas skill. Cache invalidation is
free: get_tool_definitions() already memoizes on config.yaml mtime, so a
mid-session backend swap rebuilds the schema automatically.

Tested:
- Empirical FAL OpenAPI schema check confirms image-to-video models
  require image_url (FAL returns HTTP 422 otherwise) — client-side
  rejection in FALVideoGenProvider.generate() now prevents the wasted
  round-trip
- Live E2E: fal-ai/veo3.1/image-to-video + prompt-only → clean
  missing_image_url error; fal-ai/veo3.1 + prompt-only → dispatches
- 6 new tests cover the builder (no config / image-only / full-surface /
  text-only / unknown provider / registry wiring), all passing
- 37/37 in the slice, 134/134 in the broader regression set

* test(video_gen/xai): full surface integration tests + cleaner schema

Verified end-to-end that the xAI plugin handles every documented mode
from PR #10600's surface: text-to-video, image-to-video,
reference-images-to-video, video edit, video extend (with and without
prompt). All five modes route to the correct xAI endpoint
(/videos/generations, /videos/edits, /videos/extensions) with the right
payload shape (image / reference_images / video keys), and all five
client-side rejections fire before the network: edit-without-prompt,
extend-without-video_url, image+refs conflict, >7 references, and
duration/aspect_ratio clamping.

15 new integration tests grouped into four classes (endpoint routing,
modalities, validation, clamping). httpx is stubbed via a small fake
AsyncClient that records POSTs so the tests assert the actual payload
the plugin would send to xAI — not just the success/error envelope.

Also cleaned up a description redundancy: when a model's operations
match the backend's overall set, we no longer print the duplicate
'operations supported by this model' line. xAI's description now reads:

    Active backend: xAI . model: grok-imagine-video
    - operations supported by this backend: edit, extend, generate
    - modalities supported by this backend: image, reference_images, text
    - aspect_ratio choices: 16:9, 1:1, 2:3, 3:2, 3:4, 4:3, 9:16
    - resolution choices: 480p, 720p
    - duration range: 1-15s
    - reference_image_urls: up to 7 images

Co-authored-by: Jaaneek <Jaaneek@users.noreply.github.com>

* feat(video_gen): collapse surface to t2v + i2v, family-based auto-routing

Two design changes per Teknium:

1) Drop edit/extend from the tool surface entirely. Only text-to-video
and image-to-video remain. The agent sees a clean tool with two
modalities; backend-specific quirks like xAI's edit/extend endpoints
stay out of the unified schema.

2) FAL: pick a model FAMILY once, the plugin routes between the
family's text-to-video and image-to-video endpoints based on whether
image_url was passed. Users no longer pick 'fal-ai/veo3.1' AND
'fal-ai/veo3.1/image-to-video' as separate options — they pick
'veo3.1', and the plugin handles the rest.

Catalog rewritten as families:

    veo3.1            fal-ai/veo3.1                                /  fal-ai/veo3.1/image-to-video
    pixverse-v6       fal-ai/pixverse/v6/text-to-video             /  fal-ai/pixverse/v6/image-to-video
    kling-o3-standard fal-ai/kling-video/o3/standard/text-to-video /  fal-ai/kling-video/o3/standard/image-to-video

xAI uses a single endpoint (/videos/generations) for both modes,
routed by the presence of the 'image' field in the payload — no
edit/extend exposure.

Schema changes:
- VIDEO_GENERATE_SCHEMA: drop operation, drop video_url. Final params:
  prompt (required), image_url, reference_image_urls, duration,
  aspect_ratio, resolution, negative_prompt, audio, seed, model.
- VideoGenProvider ABC: drop normalize_operation, VALID_OPERATIONS,
  DEFAULT_OPERATION. capabilities() drops 'operations' key.
- success_response: add 'modality' field ('text' | 'image') so the
  agent and logs can see which endpoint was actually hit.

Dynamic schema builder simplified — no operations bullet, no
'switch backends if you need edit/extend' guidance. When the active
backend supports both modalities (the common case), description reads:

    Active backend: FAL . model: pixverse-v6
    - supports both text-to-video (omit image_url) and image-to-video
      (pass image_url) - routes automatically
    - aspect_ratio choices: 16:9, 9:16, 1:1
    - resolution choices: 360p, 540p, 720p, 1080p
    - duration range: 1-15s
    - audio: pass audio=true to enable native audio (pricing tier)
    - negative_prompt: supported

Tests: 51 in the video_gen slice, 216 across the broader image+video
sweep, all passing. New FAL routing tests prove pixverse-v6 + no image
hits text-to-video endpoint, pixverse-v6 + image_url hits
image-to-video endpoint, same for veo3.1 and kling-o3-standard.

Docs updated: developer-guide page rewrites the 'model families' pattern
as a first-class section so external plugin authors know the convention.
toolsets-reference and toolsets.py descriptions match the new surface.

Co-authored-by: Jaaneek <Jaaneek@users.noreply.github.com>

* feat(video_gen/fal): expand catalog to 6 families, cheap + premium tiers

Catalog now covers everything Teknium specced from FAL:

  Cheap tier:
    ltx-2.3        fal-ai/ltx-2.3-22b/text-to-video       / image-to-video
    pixverse-v6    fal-ai/pixverse/v6/text-to-video       / image-to-video

  Premium tier:
    veo3.1         fal-ai/veo3.1                          / fal-ai/veo3.1/image-to-video
    seedance-2.0   bytedance/seedance-2.0/text-to-video   / image-to-video
    kling-v3-4k    fal-ai/kling-video/v3/4k/text-to-video / image-to-video
    happy-horse    fal-ai/happy-horse/text-to-video       / image-to-video

DEFAULT_MODEL moved from veo3.1 (premium) to pixverse-v6 (cheap, sane
defaults, both modalities) — better first-run UX for users who haven't
explicitly picked a model.

New family-entry knob: image_param_key. Kling v3 4K's image-to-video
endpoint expects start_image_url instead of image_url; declaring
image_param_key='start_image_url' on the family lets _build_payload
remap correctly. Other families default to plain image_url.

Per-family capability flags reflect each model's docs:
- LTX 2.3 + Happy Horse: minimal payloads (no duration/aspect/resolution
  enum exposed by FAL — let endpoint apply defaults)
- Seedance: 6 aspect ratios incl 21:9, durations 4-15, audio supported,
  negative prompts NOT supported per docs
- Kling v3 4K: 16:9/9:16/1:1, 3-15s, audio + negative
- Veo 3.1: unchanged, 16:9/9:16, 4/6/8s

Tests: +5 covering the new families (full catalog, Kling 4K
start_image_url remap, Seedance routing, LTX payload minimality, Happy
Horse minimality). 56/56 in the slice green.

Note: I did NOT add the FAL-hosted xAI Grok-Imagine variant. Hermes
already has a direct xAI plugin that talks to xAI's own API; routing
the same model through FAL's wrapper would duplicate the surface
without adding capabilities. Users on FAL who want Grok-Imagine should
use the xAI plugin directly; flag if you want both routes available.

* test(video_gen): tool-surface routing matrix — every model x modality

End-to-end matrix test driven through _handle_video_generate() — the
actual function the agent's video_generate tool call lands in. Writes
config.yaml, invokes the registered handler with a raw args dict, then
asserts the outbound HTTP/SDK call hit the right endpoint with the right
payload shape.

Parametrized over FAL_FAMILIES.keys() so the matrix auto-discovers new
families as they're added (add a family to FAL_FAMILIES and you get
both modalities tested for free).

Coverage:
- All 6 FAL families x {text-only, text+image} = 12 cases
- xAI x {text-only, text+image} = 2 cases
- tool-level model= arg overrides config = 2 cases

For each case, verifies:
- result['success'] is True
- result['modality'] matches input shape ('text' if no image_url, 'image' otherwise)
- outbound endpoint URL matches the family's text_endpoint or image_endpoint
- text-only payloads carry no image-shaped keys
- text+image payloads carry the family's image key (image_url for most,
  start_image_url for kling-v3-4k, wrapped 'image' object for xAI)

All 16 cases passing. Confirms the tool surface routes every
(provider, model, modality) combination correctly with zero leakage.

* feat(video_gen): keep video_gen out of first-run setup, surface in status

Two changes:

1. video_gen joins _DEFAULT_OFF_TOOLSETS, so it is NOT pre-selected in
   the first-run toolset checklist. Video gen is niche, paid, and slow —
   most users don't want it nagging them during initial setup. Anyone
   who wants it opts in via 'hermes tools' -> Video Generation, which
   already routes to the provider+model picker.

2. The 'hermes setup' status panel learns about video_gen — but only
   shows the row when a plugin reports available. Users without
   FAL_KEY/XAI_API_KEY see nothing about video gen; users with one of
   those keys see 'Video Generation (FAL) ✓' as confirmation it's wired.

Verified live:
- Fresh install (no creds): zero video_gen mentions in wizard.
- With FAL_KEY: status row appears with active backend name.
- 160/160 in the setup + tools_config + video_gen test slice.

Rationale: image_gen is on by default because it's a featured creative
tool used in casual chat (telegrams, etc). Video gen is heavier — long
wait, paid per-second pricing. Default-off matches user intent better.

---------

Co-authored-by: Jaaneek <Jaaneek@users.noreply.github.com>
2026-05-13 16:39:41 -07:00

299 lines
9.9 KiB
Python

"""
Video Generation Provider ABC
=============================
Defines the pluggable-backend interface for video generation. Providers register
instances via ``PluginContext.register_video_gen_provider()``; the active one
(selected via ``video_gen.provider`` in ``config.yaml``) services every
``video_generate`` tool call.
Providers live in ``<repo>/plugins/video_gen/<name>/`` (built-in, auto-loaded
as ``kind: backend``) or ``~/.hermes/plugins/video_gen/<name>/`` (user, opt-in
via ``plugins.enabled``).
Mirrors the ``image_gen`` provider design (``agent/image_gen_provider.py``) so
the two surfaces stay learnable together.
Unified surface
---------------
One tool — ``video_generate`` — covers **text-to-video** and **image-to-video**.
The router is the presence of ``image_url``: if it's set, the provider routes
to its image-to-video endpoint; if it's omitted, the provider routes to
text-to-video. Users pick one **model family** (e.g. Pixverse v6, Veo 3.1,
Kling O3 Standard); the provider handles which underlying FAL/xAI endpoint
to hit.
Video edit and video extend are intentionally NOT exposed in this surface —
the inconsistency across backends is too large for one unified tool. If
those use cases warrant attention later they can ship as separate tools.
Response shape
--------------
All providers return a dict built by :func:`success_response` /
:func:`error_response`. Keys:
success bool
video str | None URL or absolute file path
model str provider-specific model identifier
prompt str echoed prompt
modality str "text" | "image" (which mode was used)
aspect_ratio str provider-native (e.g. "16:9") or ""
duration int seconds (0 if not applicable)
provider str provider name (for diagnostics)
error str only when success=False
error_type str only when success=False
"""
from __future__ import annotations
import abc
import base64
import datetime
import logging
import uuid
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple
logger = logging.getLogger(__name__)
# Common aspect ratios across providers (Veo / Kling / xAI / Pixverse). The
# tool schema advertises this set as an enum hint, but providers may accept
# a narrower or wider set — they are responsible for clamping.
COMMON_ASPECT_RATIOS: Tuple[str, ...] = ("16:9", "9:16", "1:1", "4:3", "3:4", "3:2", "2:3")
DEFAULT_ASPECT_RATIO = "16:9"
COMMON_RESOLUTIONS: Tuple[str, ...] = ("480p", "540p", "720p", "1080p")
DEFAULT_RESOLUTION = "720p"
# ---------------------------------------------------------------------------
# ABC
# ---------------------------------------------------------------------------
class VideoGenProvider(abc.ABC):
"""Abstract base class for a video generation backend.
Subclasses must implement :meth:`generate`. Everything else has sane
defaults — override only what your provider needs.
"""
@property
@abc.abstractmethod
def name(self) -> str:
"""Stable short identifier used in ``video_gen.provider`` config.
Lowercase, no spaces. Examples: ``xai``, ``fal``, ``google``.
"""
@property
def display_name(self) -> str:
"""Human-readable label shown in ``hermes tools``. Defaults to ``name.title()``."""
return self.name.title()
def is_available(self) -> bool:
"""Return True when this provider can service calls.
Typically checks for a required API key and optional-dependency
import. Default: True.
"""
return True
def list_models(self) -> List[Dict[str, Any]]:
"""Return catalog entries for ``hermes tools`` model picker.
Each entry represents a **model family** that supports text-to-video
and/or image-to-video routing internally::
{
"id": "veo-3.1", # required
"display": "Veo 3.1", # optional; defaults to id
"speed": "~60s", # optional
"strengths": "...", # optional
"price": "$0.20/s", # optional
"modalities": ["text", "image"], # optional, advisory
}
Default: empty list (provider has no user-selectable models).
"""
return []
def get_setup_schema(self) -> Dict[str, Any]:
"""Return provider metadata for the ``hermes tools`` picker."""
return {
"name": self.display_name,
"badge": "",
"tag": "",
"env_vars": [],
}
def default_model(self) -> Optional[str]:
"""Return the default model id, or None if not applicable."""
models = self.list_models()
if models:
return models[0].get("id")
return None
def capabilities(self) -> Dict[str, Any]:
"""Return what this provider supports.
Returned dict (all keys optional)::
{
"modalities": ["text", "image"], # which inputs the backend accepts
"aspect_ratios": ["16:9", "9:16", ...],
"resolutions": ["720p", "1080p"],
"max_duration": 15, # seconds
"min_duration": 1,
"supports_audio": True,
"supports_negative_prompt": True,
"max_reference_images": 7,
}
Used by the tool layer for soft validation and by ``hermes tools``
for the picker. Default: text-only.
"""
return {
"modalities": ["text"],
"aspect_ratios": list(COMMON_ASPECT_RATIOS),
"resolutions": list(COMMON_RESOLUTIONS),
"max_duration": 10,
"min_duration": 1,
"supports_audio": False,
"supports_negative_prompt": False,
"max_reference_images": 0,
}
@abc.abstractmethod
def generate(
self,
prompt: str,
*,
model: Optional[str] = None,
image_url: Optional[str] = None,
reference_image_urls: Optional[List[str]] = None,
duration: Optional[int] = None,
aspect_ratio: str = DEFAULT_ASPECT_RATIO,
resolution: str = DEFAULT_RESOLUTION,
negative_prompt: Optional[str] = None,
audio: Optional[bool] = None,
seed: Optional[int] = None,
**kwargs: Any,
) -> Dict[str, Any]:
"""Generate a video from a prompt (text-to-video) or animate an image
(image-to-video).
Routing: if ``image_url`` is provided, the provider should route to
its image-to-video endpoint; otherwise text-to-video. The plugin
is responsible for picking the right underlying endpoint within
the user's chosen model family.
Implementations should return the dict from :func:`success_response`
or :func:`error_response`. ``kwargs`` may contain forward-compat
parameters future versions of the schema will expose —
implementations MUST ignore unknown keys (no TypeError).
"""
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
def _videos_cache_dir() -> Path:
"""Return ``$HERMES_HOME/cache/videos/``, creating parents as needed."""
from hermes_constants import get_hermes_home
path = get_hermes_home() / "cache" / "videos"
path.mkdir(parents=True, exist_ok=True)
return path
def save_b64_video(
b64_data: str,
*,
prefix: str = "video",
extension: str = "mp4",
) -> Path:
"""Decode base64 video data and write under ``$HERMES_HOME/cache/videos/``.
Returns the absolute :class:`Path` to the saved file.
Filename format: ``<prefix>_<YYYYMMDD_HHMMSS>_<short-uuid>.<ext>``.
"""
raw = base64.b64decode(b64_data)
ts = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
short = uuid.uuid4().hex[:8]
path = _videos_cache_dir() / f"{prefix}_{ts}_{short}.{extension}"
path.write_bytes(raw)
return path
def save_bytes_video(
raw: bytes,
*,
prefix: str = "video",
extension: str = "mp4",
) -> Path:
"""Write raw video bytes (e.g. an HTTP download body) to the cache."""
ts = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
short = uuid.uuid4().hex[:8]
path = _videos_cache_dir() / f"{prefix}_{ts}_{short}.{extension}"
path.write_bytes(raw)
return path
def success_response(
*,
video: str,
model: str,
prompt: str,
modality: str = "text",
aspect_ratio: str = "",
duration: int = 0,
provider: str,
extra: Optional[Dict[str, Any]] = None,
) -> Dict[str, Any]:
"""Build a uniform success response dict.
``video`` may be an HTTP URL or an absolute filesystem path.
``modality`` is ``"text"`` (text-to-video) or ``"image"`` (image-to-video) —
indicates which endpoint was actually hit, useful for diagnostics.
"""
payload: Dict[str, Any] = {
"success": True,
"video": video,
"model": model,
"prompt": prompt,
"modality": modality,
"aspect_ratio": aspect_ratio,
"duration": int(duration) if duration else 0,
"provider": provider,
}
if extra:
for k, v in extra.items():
payload.setdefault(k, v)
return payload
def error_response(
*,
error: str,
error_type: str = "provider_error",
provider: str = "",
model: str = "",
prompt: str = "",
aspect_ratio: str = "",
) -> Dict[str, Any]:
"""Build a uniform error response dict."""
return {
"success": False,
"video": None,
"error": error,
"error_type": error_type,
"model": model,
"prompt": prompt,
"aspect_ratio": aspect_ratio,
"provider": provider,
}