feat(action-engine): add SeedGraph planning and bundle generation

embodichain/gen_sim/action_engine/cli/__init__.py

@@ -0,0 +1,21 @@
+# ----------------------------------------------------------------------------
+# Copyright (c) 2021-2026 DexForce Technology Co., Ltd.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ----------------------------------------------------------------------------
+
+"""Command-line entry points for Action Engine generation and execution."""
+
+from __future__ import annotations
+
+__all__: list[str] = []

embodichain/gen_sim/action_engine/cli/generate_action_agent_config.py

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+# ----------------------------------------------------------------------------
+# Copyright (c) 2021-2026 DexForce Technology Co., Ltd.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ----------------------------------------------------------------------------
+
+"""CLI for generating Action Engine configs from a Prompt2Scene gym export."""
+
+from __future__ import annotations
+
+import argparse
+from pathlib import Path
+
+from embodichain.gen_sim.action_engine.config import generation_defaults
+from embodichain.gen_sim.action_engine.generation import (
+    generate_action_engine_config,
+)
+
+__all__ = ["build_parser", "cli"]
+
+_GENERATION_DEFAULTS = generation_defaults()
+_TASK_DEFAULTS = _GENERATION_DEFAULTS["task"]
+_SCENE_DEFAULTS = _GENERATION_DEFAULTS["scene"]
+
+_ROBOT_PROFILE_CHOICES = (
+    "ur5",
+    "ur10",
+    "dual_ur5",
+    "dual_ur10",
+    "franka",
+    "dual_franka",
+)
+
+
+def build_parser() -> argparse.ArgumentParser:
+    """Build the standalone config-generation argument parser."""
+    parser = argparse.ArgumentParser(
+        description=(
+            "Plan and compile an Action Engine task from an exported tabletop "
+            "gym project."
+        )
+    )
+    parser.add_argument(
+        "--gym_project",
+        "--gym-project",
+        required=True,
+        help=(
+            "Prompt2Scene task/export directory or gym_config.json/"
+            "scene_config.json path."
+        ),
+    )
+    parser.add_argument(
+        "--output_dir",
+        "--output-dir",
+        required=True,
+        help="Directory receiving canonical JSON artifacts and the Seed PNG.",
+    )
+    parser.add_argument(
+        "--task_name",
+        "--task-name",
+        required=True,
+        help="Stable task identifier stored in both programs.",
+    )
+    parser.add_argument(
+        "--task_description",
+        "--task-description",
+        help="Natural-language goal passed to structured LLM interpretation.",
+    )
+    parser.add_argument(
+        "--task_file",
+        "--task-file",
+        help="Optional UTF-8 file containing the natural-language goal.",
+    )
+    parser.add_argument(
+        "--task-spec",
+        "--task_spec",
+        dest="task_spec",
+        help=(
+            "Optional existing Action Engine v2 TaskSpec JSON; bypasses text "
+            "LLM interpretation and uses its role_bindings hand-off."
+        ),
+    )
+    parser.add_argument(
+        "--robot-profile",
+        "--robot_profile",
+        choices=_ROBOT_PROFILE_CHOICES,
+        default=str(_TASK_DEFAULTS["default_robot_profile"]),
+        help="Robot template used in fast_gym_config.json.",
+    )
+    parser.add_argument(
+        "--llm_model",
+        "--llm-model",
+        default=None,
+        help="Optional planner model override.",
+    )
+    parser.add_argument(
+        "--vlm_model",
+        "--vlm-model",
+        default=None,
+        help="Optional online visual/planner model override stored for A/B runs.",
+    )
+    parser.add_argument(
+        "--planning-mode",
+        "--planning_mode",
+        choices=("offline", "ab"),
+        default="offline",
+        help="Generate one offline bundle or an offline/online A/B bundle.",
+    )
+    parser.add_argument(
+        "--source_scene_z_rotation_degrees",
+        "--source-scene-z-rotation-degrees",
+        type=float,
+        default=None,
+        help=(
+            "World-frame scene rotation. Prompt2Scene exports default to -90 "
+            "degrees; other inputs default to zero."
+        ),
+    )
+    parser.add_argument(
+        "--body-scale-policy",
+        choices=("preserve", "multiply", "absolute"),
+        default=str(_SCENE_DEFAULTS["body_scale_policy"]),
+        help="How the requested xyz scale combines with source body_scale.",
+    )
+    parser.add_argument(
+        "--body-scale",
+        type=float,
+        nargs=3,
+        default=tuple(float(value) for value in _SCENE_DEFAULTS["body_scale"]),
+        metavar=("X", "Y", "Z"),
+        help="Positive xyz scale used by multiply or absolute policy.",
+    )
+    parser.add_argument(
+        "--max_episodes",
+        "--max-episodes",
+        type=int,
+        default=int(_TASK_DEFAULTS["max_episodes"]),
+        help="Episode count written to fast_gym_config.json.",
+    )
+    parser.add_argument(
+        "--max_episode_steps",
+        "--max-episode-steps",
+        type=int,
+        default=int(_TASK_DEFAULTS["max_episode_steps"]),
+        help="Per-episode step limit written to fast_gym_config.json.",
+    )
+    parser.add_argument(
+        "--overwrite",
+        action="store_true",
+        help="Replace existing canonical artifacts in the output directory.",
+    )
+    parser.add_argument(
+        "--randomize-scene",
+        action="store_true",
+        help="Randomize rigid-object poses and table height on every reset.",
+    )
+    parser.add_argument(
+        "--randomize-table-material",
+        action="store_true",
+        help="Randomize the table material independently on every reset.",
+    )
+    return parser
+
+
+def cli() -> None:
+    """Generate and report the canonical Action Engine artifact bundle."""
+    args = build_parser().parse_args()
+    task_description = _resolve_task_description(args)
+    paths = generate_action_engine_config(
+        args.gym_project,
+        args.output_dir,
+        task_name=args.task_name,
+        task_description=task_description,
+        task_spec=args.task_spec,
+        robot_profile=args.robot_profile,
+        llm_model=args.llm_model,
+        source_scene_z_rotation_degrees=args.source_scene_z_rotation_degrees,
+        body_scale_policy=args.body_scale_policy,
+        body_scale=args.body_scale,
+        overwrite=args.overwrite,
+        max_episodes=args.max_episodes,
+        max_episode_steps=args.max_episode_steps,
+        randomize_scene=args.randomize_scene,
+        randomize_table_material=args.randomize_table_material,
+        planning_mode=args.planning_mode,
+        vlm_model=args.vlm_model,
+    )
+
+    print(f"Generated gym config: {paths.gym_config}")
+    print(f"Generated agent config: {paths.agent_config}")
+    print(f"Generated TaskSpec: {paths.task_spec}")
+    print(f"Generated SceneRequirements: {paths.scene_requirements}")
+    print(f"Generated SeedGraph: {paths.seed_task_graph}")
+    print(f"Generated Seed graph PNG: {paths.seed_task_graph_png}")
+    print(
+        "Run with:\n"
+        "python -m embodichain.gen_sim.action_engine.cli.run_agent "
+        f"--task_name {args.task_name} "
+        f'--gym_config "{paths.gym_config}" '
+        f'--agent_config "{paths.agent_config}" '
+        "--regenerate"
+    )
+
+
+def _resolve_task_description(args: argparse.Namespace) -> str:
+    task_spec = getattr(args, "task_spec", None)
+    if task_spec:
+        if args.task_description or args.task_file:
+            raise ValueError(
+                "--task-spec cannot be combined with --task_description or "
+                "--task_file."
+            )
+        return ""
+    if args.task_description and args.task_file:
+        raise ValueError("Use either --task_description or --task_file, not both.")
+    if args.task_file:
+        description = (
+            Path(args.task_file).expanduser().read_text(encoding="utf-8").strip()
+        )
+    else:
+        description = str(args.task_description or "").strip()
+    if not description:
+        raise ValueError(
+            "--task_description (or --task_file) must provide a non-empty goal."
+        )
+    return description
+
+
+if __name__ == "__main__":
+    cli()

embodichain/gen_sim/action_engine/compiler/__init__.py

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+# ----------------------------------------------------------------------------
+# Copyright (c) 2021-2026 DexForce Technology Co., Ltd.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ----------------------------------------------------------------------------
+
+"""Stable deterministic compiler API."""
+
+from __future__ import annotations
+
+from .core import compile_task_agent
+from .v2 import (
+    compile_task_agent_v2,
+    execution_program_to_seed_graph,
+    seed_graph_to_execution_program,
+)
+
+__all__ = [
+    "compile_task_agent",
+    "compile_task_agent_v2",
+    "execution_program_to_seed_graph",
+    "seed_graph_to_execution_program",
+]