Instructions to use aogavrilov/diffusiongemma-agent-iq3-cuda13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use aogavrilov/diffusiongemma-agent-iq3-cuda13 with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf aogavrilov/diffusiongemma-agent-iq3-cuda13:Q4_K_M # Run inference directly in the terminal: llama cli -hf aogavrilov/diffusiongemma-agent-iq3-cuda13:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf aogavrilov/diffusiongemma-agent-iq3-cuda13:Q4_K_M # Run inference directly in the terminal: llama cli -hf aogavrilov/diffusiongemma-agent-iq3-cuda13:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf aogavrilov/diffusiongemma-agent-iq3-cuda13:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf aogavrilov/diffusiongemma-agent-iq3-cuda13:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf aogavrilov/diffusiongemma-agent-iq3-cuda13:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf aogavrilov/diffusiongemma-agent-iq3-cuda13:Q4_K_M
Use Docker
docker model run hf.co/aogavrilov/diffusiongemma-agent-iq3-cuda13:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use aogavrilov/diffusiongemma-agent-iq3-cuda13 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "aogavrilov/diffusiongemma-agent-iq3-cuda13" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "aogavrilov/diffusiongemma-agent-iq3-cuda13", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/aogavrilov/diffusiongemma-agent-iq3-cuda13:Q4_K_M
- Ollama
How to use aogavrilov/diffusiongemma-agent-iq3-cuda13 with Ollama:
ollama run hf.co/aogavrilov/diffusiongemma-agent-iq3-cuda13:Q4_K_M
- Unsloth Studio
How to use aogavrilov/diffusiongemma-agent-iq3-cuda13 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for aogavrilov/diffusiongemma-agent-iq3-cuda13 to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for aogavrilov/diffusiongemma-agent-iq3-cuda13 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for aogavrilov/diffusiongemma-agent-iq3-cuda13 to start chatting
- Pi
How to use aogavrilov/diffusiongemma-agent-iq3-cuda13 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf aogavrilov/diffusiongemma-agent-iq3-cuda13:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "aogavrilov/diffusiongemma-agent-iq3-cuda13:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use aogavrilov/diffusiongemma-agent-iq3-cuda13 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf aogavrilov/diffusiongemma-agent-iq3-cuda13:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default aogavrilov/diffusiongemma-agent-iq3-cuda13:Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use aogavrilov/diffusiongemma-agent-iq3-cuda13 with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf aogavrilov/diffusiongemma-agent-iq3-cuda13:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "aogavrilov/diffusiongemma-agent-iq3-cuda13:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
- Docker Model Runner
How to use aogavrilov/diffusiongemma-agent-iq3-cuda13 with Docker Model Runner:
docker model run hf.co/aogavrilov/diffusiongemma-agent-iq3-cuda13:Q4_K_M
- Lemonade
How to use aogavrilov/diffusiongemma-agent-iq3-cuda13 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull aogavrilov/diffusiongemma-agent-iq3-cuda13:Q4_K_M
Run and chat with the model
lemonade run user.diffusiongemma-agent-iq3-cuda13-Q4_K_M
List all available models
lemonade list
File size: 19,798 Bytes
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"""Checkpointed controller for bounded DG coding sessions.
The controller never asks DiffusionGemma to choose or execute shell commands.
It delegates retrieval to Haystack BM25 and code changes to the existing
session/Aider path, while preserving all state and test feedback between
bounded retries.
"""
from __future__ import annotations
import argparse
import hashlib
import json
import os
import re
import subprocess
import sys
import tempfile
import time
import urllib.error
import urllib.request
from pathlib import Path
from typing import Any
DG_ROOT = Path(__file__).resolve().parents[1]
DEFAULT_STATE_ROOT = DG_ROOT / "runlogs" / "dg-autonomous-supervisor"
STATE_VERSION = 1
def now() -> float:
return time.time()
def slug(value: str, limit: int = 48) -> str:
text = re.sub(r"[^A-Za-z0-9]+", "-", value.lower()).strip("-")
return text[:limit] or "task"
def atomic_write_json(path: Path, data: dict[str, Any]) -> None:
path.parent.mkdir(parents=True, exist_ok=True)
with tempfile.NamedTemporaryFile("w", encoding="utf-8", delete=False, dir=path.parent, suffix=".tmp") as handle:
json.dump(data, handle, ensure_ascii=False, indent=2)
handle.write("\n")
temp = Path(handle.name)
temp.replace(path)
def read_json(path: Path) -> dict[str, Any] | None:
try:
data = json.loads(path.read_text(encoding="utf-8"))
except (OSError, ValueError):
return None
return data if isinstance(data, dict) else None
def git(repo: Path, *args: str, input_text: str | None = None) -> subprocess.CompletedProcess[str]:
return subprocess.run(
["git", *args],
cwd=repo,
input=input_text,
text=True,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
check=False,
)
def git_status(repo: Path) -> str:
return git(repo, "status", "--short").stdout
def git_snapshot(repo: Path) -> dict[str, str]:
return {
"status": git_status(repo),
"diff": git(repo, "diff", "--binary", "--", ".").stdout,
"cached_diff": git(repo, "diff", "--cached", "--binary", "--", ".").stdout,
"head": git(repo, "rev-parse", "HEAD").stdout.strip(),
}
def wsl_path(path: Path) -> str:
raw = str(path.resolve())
if os.name != "nt":
return raw
match = re.match(r"^([A-Za-z]):\\(.*)$", raw)
if not match:
return raw
drive, tail = match.groups()
return f"/mnt/{drive.lower()}/{tail.replace(chr(92), '/') }"
def haystack_command(repo: Path, task: str, index_dir: Path, rebuild: bool) -> list[str]:
runner = DG_ROOT / "scripts" / "dg_haystack_runner.py"
if os.name == "nt":
linux_python = wsl_path(DG_ROOT / ".venv-haystack" / "bin" / "python")
command = [
"wsl.exe",
"--exec",
linux_python,
wsl_path(runner),
"--repo",
wsl_path(repo),
"--task",
task,
"--retrieve-only",
"--json",
"--index-dir",
wsl_path(index_dir),
]
else:
python = Path(os.environ.get("DG_HAYSTACK_PYTHON", DG_ROOT / ".venv-haystack" / "bin" / "python"))
command = [
str(python),
str(runner),
"--repo",
str(repo),
"--task",
task,
"--retrieve-only",
"--json",
"--index-dir",
str(index_dir),
]
if rebuild:
command.append("--rebuild-index")
return command
def run_retrieval(repo: Path, task: str, index_dir: Path, rebuild: bool, timeout: int) -> tuple[dict[str, Any], int]:
command = haystack_command(repo, task, index_dir, rebuild)
try:
proc = subprocess.run(command, text=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, check=False, timeout=timeout)
except (OSError, subprocess.TimeoutExpired) as exc:
return {"status": "failed", "error": str(exc), "command": command}, 1
try:
payload = json.loads(proc.stdout)
except ValueError:
payload = {"status": "failed", "stdout_tail": proc.stdout[-4000:], "stderr_tail": proc.stderr[-4000:]}
if not isinstance(payload, dict):
payload = {"status": "failed", "error": "Haystack did not return a JSON object"}
payload["command"] = command
payload["returncode"] = proc.returncode
if proc.stderr:
payload["stderr_tail"] = proc.stderr[-4000:]
return payload, proc.returncode
def planner_guidance(args: argparse.Namespace, retrieval: dict[str, Any]) -> dict[str, Any]:
"""Optional planner is advisory: it cannot execute commands or modify files."""
if not args.planner_url or not args.planner_model:
return {"status": "disabled"}
paths = retrieval.get("retrieval", {}).get("paths", []) if isinstance(retrieval.get("retrieval"), dict) else []
prompt = "Give concise file-level coding guidance. Do not emit shell commands or patches. Existing paths: " + ", ".join(map(str, paths)) + "\nTask: " + args.task
request = urllib.request.Request(
args.planner_url.rstrip("/") + "/chat/completions",
data=json.dumps({"model": args.planner_model, "messages": [{"role": "user", "content": prompt}], "temperature": 0}).encode("utf-8"),
headers={"Content-Type": "application/json", "Authorization": f"Bearer {args.planner_api_key or 'dummy'}"},
method="POST",
)
try:
with urllib.request.urlopen(request, timeout=args.planner_timeout) as response:
payload = json.loads(response.read().decode("utf-8"))
return {"status": "success", "model": args.planner_model, "guidance": str(payload["choices"][0]["message"]["content"]).strip()[:2400]}
except (KeyError, TypeError, ValueError, urllib.error.URLError, TimeoutError) as exc:
return {"status": "failed", "model": args.planner_model, "error": str(exc)}
def state_dir_for(args: argparse.Namespace, repo: Path) -> Path:
if args.state_dir:
return Path(args.state_dir).resolve()
digest = hashlib.sha256(f"{repo}\0{args.task}".encode("utf-8")).hexdigest()[:12]
return DEFAULT_STATE_ROOT / f"{time.strftime('%Y%m%d-%H%M%S')}-{slug(args.task)}-{digest}"
def initial_state(args: argparse.Namespace, repo: Path, state_dir: Path) -> dict[str, Any]:
return {
"version": STATE_VERSION,
"repo": str(repo),
"task": args.task,
"state_dir": str(state_dir),
"created_at": now(),
"updated_at": now(),
"status": "created",
"max_steps": args.max_steps,
"initial_git": git_snapshot(repo),
"retrieval": {},
"planner": {"status": "not-run"},
"steps": [],
"rollback": {"attempted": False, "status": "not-needed"},
"warnings": [],
}
def write_state(state_dir: Path, state: dict[str, Any]) -> None:
state["updated_at"] = now()
atomic_write_json(state_dir / "state.json", state)
retrieval = state.get("retrieval") if isinstance(state.get("retrieval"), dict) else {}
lines = [
"# DG Persistent Supervisor",
"",
f"- Status: `{state.get('status')}`",
f"- Repository: `{state.get('repo')}`",
f"- Task: {state.get('task')}",
f"- Steps: `{len(state.get('steps', []))}/{state.get('max_steps')}`",
]
paths = retrieval.get("retrieval", {}).get("paths", []) if isinstance(retrieval.get("retrieval"), dict) else []
if paths:
lines.extend(["", "## Retrieved Files", *[f"- `{item}`" for item in paths]])
if state.get("steps"):
lines.extend(["", "## Attempts"])
for item in state["steps"]:
lines.append(f"- Step {item.get('index')}: `{item.get('status')}` ({item.get('session_dir', '')})")
if state.get("warnings"):
lines.extend(["", "## Warnings", *[f"- {item}" for item in state["warnings"]]])
(state_dir / "SUMMARY.md").write_text("\n".join(lines) + "\n", encoding="utf-8")
def feedback_from_session(session: dict[str, Any], limit: int = 1800) -> str:
artifacts = session.get("artifacts") if isinstance(session.get("artifacts"), dict) else {}
parts: list[str] = []
for key in ("verify_report", "task_stderr", "task_stdout"):
path = Path(str(artifacts.get(key) or ""))
if not path.is_file():
continue
text = path.read_text(encoding="utf-8", errors="replace").strip()
if text:
parts.append(text[-limit:])
return "\n\n".join(parts)[-limit:]
def session_command(args: argparse.Namespace, repo: Path, state_dir: Path, step: int, retrieval: dict[str, Any], feedback: str, planner: dict[str, Any]) -> list[str]:
task = args.task
stats = retrieval.get("retrieval") if isinstance(retrieval.get("retrieval"), dict) else {}
paths = stats.get("paths") if isinstance(stats.get("paths"), list) else []
if paths:
task += "\n\nSupervisor retrieval candidates: " + ", ".join(str(item) for item in paths[: args.max_files])
if feedback:
task += "\n\nPrevious verified attempt failed. Keep the task scope unchanged and use this test feedback:\n" + feedback[-1800:]
if planner.get("status") == "success":
task += "\n\nExternal planner guidance (advisory only; verify against repository):\n" + str(planner.get("guidance") or "")
command = [
sys.executable,
str(DG_ROOT / "scripts" / "dg_agent.py"),
"session",
"--repo",
str(repo),
"--task",
task,
"--out-dir",
str(state_dir / "sessions"),
"--max-files",
str(args.max_files),
"--max-snippet-chars",
str(args.max_snippet_chars),
"--test-timeout",
str(args.test_timeout),
"--aider-timeout",
str(args.aider_timeout),
"--repair-attempts",
str(args.repair_attempts),
"--wall-timeout",
str(args.wall_timeout),
"--rollback-on-failure",
]
for file_name in args.file:
command.extend(["--file", file_name])
if args.test_cmd:
command.extend(["--test-cmd", args.test_cmd])
if args.auto_test:
command.append("--auto-test")
if args.no_deterministic_first:
command.append("--no-deterministic-first")
if args.dry_run:
command.append("--dry-run")
return command
def latest_session(sessions_dir: Path) -> dict[str, Any] | None:
candidates = sorted(sessions_dir.glob("*/session.json"), key=lambda item: item.stat().st_mtime, reverse=True)
return read_json(candidates[0]) if candidates else None
def rollback_clean_start(repo: Path, state_dir: Path, initial: dict[str, Any]) -> dict[str, Any]:
if str(initial.get("status") or "").strip():
return {"attempted": False, "status": "skipped", "reason": "repository was dirty before the run"}
status = git_status(repo)
if not status.strip():
return {"attempted": False, "status": "not-needed"}
if any(line.startswith("??") for line in status.splitlines()):
return {"attempted": False, "status": "blocked", "reason": "unexpected untracked files; refusing to remove them", "status_after": status}
patch = git(repo, "diff", "--binary", "--", ".").stdout
if not patch:
return {"attempted": False, "status": "blocked", "reason": "staged or non-diff changes remain", "status_after": status}
snapshot = state_dir / "unexpected-failure.diff"
snapshot.write_text(patch, encoding="utf-8")
proc = git(repo, "apply", "--reverse", "--whitespace=nowarn", input_text=patch)
return {
"attempted": True,
"status": "success" if proc.returncode == 0 and not git_status(repo).strip() else "failed",
"patch": str(snapshot),
"stderr": proc.stderr[-2000:],
"status_after": git_status(repo),
}
def run(args: argparse.Namespace) -> int:
repo = Path(args.repo).resolve()
if not repo.is_dir():
print(f"repo does not exist: {repo}", file=sys.stderr)
return 2
if git(repo, "rev-parse", "--is-inside-work-tree").stdout.strip() != "true":
print(f"repo is not a git repository: {repo}", file=sys.stderr)
return 2
if not 1 <= args.max_steps <= 5:
print("--max-steps must be between 1 and 5", file=sys.stderr)
return 2
state_dir = state_dir_for(args, repo)
state_path = state_dir / "state.json"
state = read_json(state_path) if args.resume or args.status else None
if args.status:
if state is None:
print(f"state is missing: {state_path}", file=sys.stderr)
return 2
print(json.dumps(state, ensure_ascii=False, indent=2) if args.json else f"{state.get('status')} {state_path}")
return 0
if state is None:
if state_path.exists():
print(f"state already exists: {state_dir}; pass --resume to continue it", file=sys.stderr)
return 2
state_dir.mkdir(parents=True, exist_ok=False)
state = initial_state(args, repo, state_dir)
if str(state["initial_git"].get("status") or "").strip() and not args.allow_dirty:
state["status"] = "blocked"
state["warnings"].append("repository is dirty; use --allow-dirty to run without controller rollback")
write_state(state_dir, state)
print(f"Supervisor state: {state_path}")
return 3
if args.allow_dirty:
state["warnings"].append("started from a dirty repository; controller rollback is disabled")
elif state.get("status") == "success":
print(json.dumps(state, ensure_ascii=False, indent=2) if args.json else f"Supervisor already succeeded: {state_path}")
return 0
index_dir = Path(args.index_dir).resolve() if args.index_dir else (DG_ROOT / "runlogs" / "dg-retrieval-index" / hashlib.sha256(str(repo).encode("utf-8")).hexdigest()[:16])
retrieval, retrieval_rc = run_retrieval(repo, args.task, index_dir, args.rebuild_index, args.retrieval_timeout)
state["retrieval"] = retrieval
(state_dir / "retrieval.json").write_text(json.dumps(retrieval, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
if retrieval_rc != 0 or retrieval.get("status") != "success":
state["status"] = "blocked"
state["warnings"].append("Haystack retrieval failed; no edit was attempted")
write_state(state_dir, state)
print(f"Supervisor state: {state_path}")
return 1
planner = planner_guidance(args, retrieval)
state["planner"] = planner
if planner.get("status") == "failed":
state["warnings"].append("external planner failed; continuing without planner guidance")
write_state(state_dir, state)
start_index = len(state.get("steps", [])) + 1
feedback = ""
if state.get("steps"):
previous = state["steps"][-1]
feedback = str(previous.get("feedback") or "")
for index in range(start_index, args.max_steps + 1):
before = git_snapshot(repo)
checkpoint = state_dir / "checkpoints" / f"{index:02d}-before.json"
checkpoint.parent.mkdir(parents=True, exist_ok=True)
checkpoint.write_text(json.dumps(before, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
command = session_command(args, repo, state_dir, index, retrieval, feedback, planner)
if args.dry_run:
attempt = {"index": index, "status": "dry-run", "command": command, "checkpoint": str(checkpoint)}
state["steps"].append(attempt)
state["status"] = "dry-run"
write_state(state_dir, state)
break
try:
proc = subprocess.run(command, cwd=DG_ROOT, text=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, check=False, timeout=args.wall_timeout + 30)
except subprocess.TimeoutExpired as exc:
proc = subprocess.CompletedProcess(command, 124, stdout="", stderr=f"controller timed out after {exc.timeout}s")
session = latest_session(state_dir / "sessions") or {}
feedback = feedback_from_session(session)
attempt = {
"index": index,
"status": "success" if proc.returncode == 0 and session.get("status") == "success" else "failed",
"returncode": proc.returncode,
"command": command,
"checkpoint": str(checkpoint),
"session_dir": str(session.get("session_dir") or ""),
"session_report": session,
"feedback": feedback,
"stdout_tail": proc.stdout[-4000:],
"stderr_tail": proc.stderr[-4000:],
}
state["steps"].append(attempt)
if attempt["status"] == "success":
state["status"] = "success"
state["rollback"] = {"attempted": False, "status": "not-needed"}
write_state(state_dir, state)
break
if not args.allow_dirty:
rollback = rollback_clean_start(repo, state_dir, state["initial_git"])
state["rollback"] = rollback
if rollback.get("status") == "blocked":
state["status"] = "blocked"
state["warnings"].append("unexpected repository state after failed session")
write_state(state_dir, state)
break
state["status"] = "retrying" if index < args.max_steps else "failed"
write_state(state_dir, state)
write_state(state_dir, state)
result = {"status": state.get("status"), "state_dir": str(state_dir), "state": str(state_path), "steps": len(state.get("steps", []))}
print(json.dumps(result, ensure_ascii=False, indent=2) if args.json else f"Supervisor status: {result['status']}\nSupervisor state: {state_path}")
return 0 if state.get("status") == "success" else 1
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(description="Run a checkpointed persistent controller over Haystack retrieval and DG sessions.")
parser.add_argument("--repo", required=True)
parser.add_argument("--task", required=True)
parser.add_argument("--file", action="append", default=[])
parser.add_argument("--state-dir", default="")
parser.add_argument("--resume", action="store_true")
parser.add_argument("--status", action="store_true")
parser.add_argument("--index-dir", default="")
parser.add_argument("--rebuild-index", action="store_true")
parser.add_argument("--max-steps", type=int, default=3)
parser.add_argument("--max-files", type=int, default=3)
parser.add_argument("--max-snippet-chars", type=int, default=1200)
parser.add_argument("--test-cmd", default="")
parser.add_argument("--auto-test", action=argparse.BooleanOptionalAction, default=True)
parser.add_argument("--test-timeout", type=int, default=120)
parser.add_argument("--aider-timeout", type=int, default=300)
parser.add_argument("--repair-attempts", type=int, default=1)
parser.add_argument("--wall-timeout", type=int, default=420)
parser.add_argument("--retrieval-timeout", type=int, default=180)
parser.add_argument("--planner-url", default=os.environ.get("DG_PLANNER_URL", ""), help="Optional stronger OpenAI-compatible planner URL")
parser.add_argument("--planner-model", default=os.environ.get("DG_PLANNER_MODEL", ""))
parser.add_argument("--planner-api-key", default=os.environ.get("DG_PLANNER_API_KEY", ""))
parser.add_argument("--planner-timeout", type=int, default=60)
parser.add_argument("--allow-dirty", action="store_true")
parser.add_argument("--no-deterministic-first", action="store_true")
parser.add_argument("--dry-run", action="store_true")
parser.add_argument("--json", action="store_true")
return parser.parse_args()
if __name__ == "__main__":
raise SystemExit(run(parse_args()))
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