728 lines
23 KiB
Python
728 lines
23 KiB
Python
#!/usr/bin/env python3
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"""Headless-Adapter fuer TensorX-Versuchslaeufe ueber OpenCode.
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OpenCode verwaltet Provider-Credentials und Agentensitzungen. Dieser Wrapper
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erzeugt pro Lauf eine isolierte OpenCode-Konfiguration, streamt JSON-Ereignisse
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direkt in den Laufordner und normalisiert die Session nach RawResult.json.
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"""
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from __future__ import annotations
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import argparse
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import copy
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import json
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import os
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import queue
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import shutil
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import subprocess
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import sys
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import threading
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import time
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from collections import Counter
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from datetime import datetime, timezone
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from pathlib import Path
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ADAPTER_VERSION = "1.0.2"
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PROVIDER_ID = "tensorx"
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EFFORTS = ("low", "medium", "high", "xhigh", "max")
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MODES = ("solo", "builtin", "custom")
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def utc_now() -> str:
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return datetime.now(timezone.utc).isoformat()
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def resolve_opencode(explicit: str | None = None) -> Path:
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candidates: list[Path] = []
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if explicit:
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candidates.append(Path(explicit))
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which_exe = shutil.which("opencode.exe")
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if which_exe:
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candidates.append(Path(which_exe))
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appdata = os.environ.get("APPDATA")
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if appdata:
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candidates.append(
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Path(appdata)
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/ "npm"
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/ "node_modules"
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/ "opencode-ai"
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/ "bin"
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/ "opencode.exe"
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)
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for candidate in candidates:
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if candidate.is_file():
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return candidate.resolve()
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raise FileNotFoundError(
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"OpenCode nicht gefunden. Erwartet wird 'opencode.exe' im PATH oder "
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"die npm-Installation 'npm install -g opencode-ai'."
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)
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def normalize_model(model: str) -> tuple[str, str]:
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if model.startswith(f"{PROVIDER_ID}/"):
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upstream = model[len(PROVIDER_ID) + 1 :]
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return model, upstream
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return f"{PROVIDER_ID}/{model}", model
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def normalized_path(path: Path) -> str:
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return path.resolve().as_posix()
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def git_worktree_root(root: Path) -> Path | None:
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completed = subprocess.run(
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["git", "-C", str(root), "rev-parse", "--show-toplevel"],
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capture_output=True,
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text=True,
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encoding="utf-8",
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errors="replace",
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check=False,
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)
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if completed.returncode != 0 or not completed.stdout.strip():
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return None
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candidate = Path(completed.stdout.strip()).resolve()
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return candidate if candidate.is_dir() else None
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def output_permission_patterns(
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root: Path,
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output_dir: Path,
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worktree_root: Path | None = None,
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) -> list[str]:
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"""Return both canonical and worktree-relative patterns used by OpenCode.
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OpenCode matches paths inside the active worktree as location-relative resources,
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even when a tool call supplied an absolute Windows path. That relative resource may
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contain ``..`` when the active location is a worktree subdirectory. OpenCode may instead
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use a path relative to the Git worktree root, so that form is included when available.
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Truly external outputs are matched canonically. Both the directory itself and descendants
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are allowed.
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"""
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root = root.resolve()
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output_dir = output_dir.resolve()
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bases = [output_dir.as_posix()]
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try:
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bases.insert(0, output_dir.relative_to(root).as_posix())
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except ValueError:
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try:
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bases.insert(0, Path(os.path.relpath(output_dir, root)).as_posix())
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except ValueError: # Verschiedene Windows-Laufwerke.
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pass
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if worktree_root is not None:
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try:
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bases.insert(0, output_dir.relative_to(worktree_root.resolve()).as_posix())
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except ValueError:
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pass
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patterns: list[str] = []
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for base in bases:
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normalized = base.rstrip("/")
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for pattern in (normalized, normalized + "/**"):
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if pattern not in patterns:
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patterns.append(pattern)
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return patterns
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def readonly_shell_permissions() -> dict[str, str]:
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return {
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"*": "deny",
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"rg *": "allow",
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"git status*": "allow",
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"git ls-files*": "allow",
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"git rev-parse*": "allow",
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"Get-ChildItem *": "allow",
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"Get-Content *": "allow",
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"Select-String *": "allow",
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"Test-Path *": "allow",
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"Resolve-Path *": "allow",
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"where.exe *": "allow",
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}
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def task_permissions(mode: str, custom_names: list[str]) -> str | dict[str, str]:
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if mode == "solo":
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return "deny"
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if mode == "builtin":
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return {
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"*": "deny",
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"general": "allow",
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"explore": "allow",
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}
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permissions = {"*": "deny"}
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permissions.update({name: "allow" for name in custom_names})
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return permissions
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def load_custom_agents(path: Path) -> dict[str, dict]:
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data = json.loads(path.read_text(encoding="utf-8-sig"))
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if not isinstance(data, dict) or not data:
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raise ValueError("Agentendatei muss ein nicht-leeres JSON-Objekt sein")
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for name, definition in data.items():
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if not isinstance(definition, dict):
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raise ValueError(f"Agent '{name}' ist kein JSON-Objekt")
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if not definition.get("description") or not definition.get("prompt"):
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raise ValueError(f"Agent '{name}' benoetigt description und prompt")
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return data
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def build_run_config(
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base_config: dict,
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model_ref: str,
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upstream_model: str,
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mode: str,
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root: Path,
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output_dir: Path,
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agents_file: Path | None,
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) -> dict:
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config = copy.deepcopy(base_config)
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provider = config.setdefault("provider", {}).setdefault(PROVIDER_ID, {})
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models = provider.setdefault("models", {})
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if upstream_model not in models:
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models[upstream_model] = {"name": upstream_model}
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config["model"] = model_ref
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output_patterns = output_permission_patterns(
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root,
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output_dir,
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git_worktree_root(root),
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)
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edit_permissions = {"*": "deny"}
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edit_permissions.update({pattern: "allow" for pattern in output_patterns})
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custom_agents: dict[str, dict] = {}
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if mode == "custom":
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if agents_file is None:
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raise ValueError("Modus custom erfordert --agents")
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custom_agents = load_custom_agents(agents_file)
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config["permission"] = {
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"*": "deny",
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"read": "allow",
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"glob": "allow",
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"grep": "allow",
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"list": "allow",
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"edit": edit_permissions,
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"external_directory": copy.deepcopy(edit_permissions),
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"bash": readonly_shell_permissions(),
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"task": task_permissions(mode, list(custom_agents)),
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"webfetch": "deny",
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"websearch": "deny",
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"skill": "deny",
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"question": "deny",
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}
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agents = config.setdefault("agent", {})
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agents["build"] = {"model": model_ref, "mode": "primary"}
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agents["general"] = {"model": model_ref, "mode": "subagent"}
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agents["explore"] = {"model": model_ref, "mode": "subagent"}
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child_permission = {
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"edit": "deny",
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"task": "deny",
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"webfetch": "deny",
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"websearch": "deny",
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"skill": "deny",
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"bash": readonly_shell_permissions(),
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}
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for name, definition in custom_agents.items():
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agents[name] = {
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"description": definition["description"],
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"mode": "subagent",
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"model": model_ref,
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"prompt": definition["prompt"],
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"permission": child_permission,
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}
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config["default_agent"] = "build"
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return config
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def terminate_process_tree(process: subprocess.Popen) -> None:
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if process.poll() is not None:
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return
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if os.name == "nt":
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subprocess.run(
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["taskkill", "/PID", str(process.pid), "/T", "/F"],
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capture_output=True,
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text=True,
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check=False,
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)
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else:
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process.terminate()
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try:
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process.wait(timeout=5)
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except subprocess.TimeoutExpired:
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process.kill()
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def stream_reader(stream, source: str, sink: Path, updates: queue.Queue) -> None:
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with sink.open("a", encoding="utf-8", newline="") as handle:
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for line in iter(stream.readline, ""):
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handle.write(line)
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handle.flush()
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updates.put((source, line, time.monotonic()))
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stream.close()
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updates.put((source, None, time.monotonic()))
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def parse_event(line: str) -> dict | None:
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try:
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event = json.loads(line)
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except json.JSONDecodeError:
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return None
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return event if isinstance(event, dict) else None
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def json_from_mixed_output(text: str) -> dict | None:
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text = text.strip()
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if not text:
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return None
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try:
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return json.loads(text)
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except json.JSONDecodeError:
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start = text.find("{")
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if start < 0:
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return None
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try:
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return json.loads(text[start:])
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except json.JSONDecodeError:
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return None
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def export_session(
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opencode: Path,
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session_id: str,
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env: dict[str, str],
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root: Path,
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destination: Path,
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log,
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) -> dict | None:
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completed = subprocess.run(
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[str(opencode), "export", session_id, "--pure"],
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cwd=root,
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env=env,
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capture_output=True,
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text=True,
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encoding="utf-8",
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errors="replace",
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timeout=120,
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check=False,
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)
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if completed.stderr.strip():
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log("OpenCode export: " + completed.stderr.strip())
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data = json_from_mixed_output(completed.stdout)
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if data is not None:
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destination.write_text(
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json.dumps(data, indent=2, ensure_ascii=False), encoding="utf-8"
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)
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return data
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def collect_written_files(output_dir: Path) -> list[dict]:
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if not output_dir.is_dir():
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return []
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return [
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{
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"path": str(path.relative_to(output_dir)),
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"size": path.stat().st_size,
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}
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for path in sorted(output_dir.rglob("*"))
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if path.is_file()
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]
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def normalize_result(
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session: dict | None,
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events: list[dict],
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model_ref: str,
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mode: str,
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effort: str,
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exit_code: int,
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timed_out: bool,
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interrupted: bool,
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duration_s: float,
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output_dir: Path,
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errors: list[str],
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) -> dict:
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info = (session or {}).get("info", {})
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messages = (session or {}).get("messages", [])
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assistants = [m for m in messages if m.get("info", {}).get("role") == "assistant"]
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tools: list[dict] = []
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result_text = ""
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finish_reason = ""
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for message in assistants:
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finish_reason = message.get("info", {}).get("finish", finish_reason)
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for part in message.get("parts", []):
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if part.get("type") == "text" and part.get("text"):
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result_text = part["text"]
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if part.get("type") == "tool":
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state = part.get("state", {})
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tools.append(
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{
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"name": part.get("tool", ""),
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"status": state.get("status", ""),
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"input": state.get("input", {}),
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"title": state.get("title", ""),
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}
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)
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tokens = info.get("tokens", {})
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cache = tokens.get("cache", {})
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input_tokens = int(tokens.get("input", 0) or 0)
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output_tokens = int(tokens.get("output", 0) or 0)
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reasoning_tokens = int(tokens.get("reasoning", 0) or 0)
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cache_read = int(cache.get("read", 0) or 0)
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cache_write = int(cache.get("write", 0) or 0)
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total_tokens = int(tokens.get("total", 0) or 0)
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if total_tokens == 0:
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total_tokens = (
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input_tokens
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+ output_tokens
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+ reasoning_tokens
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+ cache_read
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+ cache_write
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)
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model_info = info.get("model", {})
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reported_model = model_info.get("id") or model_ref.split("/", 1)[-1]
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task_calls = [tool for tool in tools if tool["name"] in ("task", "subagent")]
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subagent_details = [
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{
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"id": index,
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"type": call.get("input", {}).get("subagent_type")
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or call.get("input", {}).get("agent")
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or call.get("input", {}).get("type", ""),
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"description": call.get("input", {}).get("description")
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or call.get("input", {}).get("prompt", ""),
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"status": call.get("status", ""),
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}
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for index, call in enumerate(task_calls, start=1)
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]
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by_type = Counter(detail["type"] for detail in subagent_details if detail["type"])
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completed_subagents = sum(
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1 for detail in subagent_details if detail["status"] == "completed"
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)
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failed_subagents = len(subagent_details) - completed_subagents
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aborted = timed_out or interrupted
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is_error = exit_code != 0 or aborted or bool(errors)
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subtype = "aborted" if aborted else ("error" if is_error else "success")
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event_counts = Counter(event.get("type", "unknown") for event in events)
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usage = {
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"prompt_tokens": input_tokens,
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"completion_tokens": output_tokens,
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"total_tokens": total_tokens,
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"cached_tokens": cache_read,
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"cache_read_tokens": cache_read,
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"cache_creation_tokens": cache_write,
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"reasoning_tokens": reasoning_tokens,
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"output_tokens_details": {"thinking_tokens": reasoning_tokens},
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}
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return {
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"is_error": is_error,
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"subtype": subtype,
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"duration_ms": int(duration_s * 1000),
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"duration_api_ms": 0,
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"num_turns": len(assistants)
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or sum(1 for event in events if event.get("type") == "step_finish"),
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"model": reported_model,
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"model_requested": model_ref.split("/", 1)[-1],
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"provider": PROVIDER_ID,
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"effort": effort,
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"usage": usage,
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"modelUsage": {
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reported_model: {
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"input_tokens": input_tokens,
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"output_tokens": output_tokens,
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"cache_read_input_tokens": cache_read,
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"cache_creation_input_tokens": cache_write,
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"reasoning_tokens": reasoning_tokens,
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}
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},
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"cost": info.get("cost", 0),
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"tool_calls": tools,
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"tool_call_count": len(tools),
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"tool_call_types": dict(Counter(tool["name"] for tool in tools)),
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"event_counts": dict(event_counts),
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"written_files": collect_written_files(output_dir),
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"result": result_text,
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"finish_reason": finish_reason,
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"errors": errors,
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"session_id": info.get("id", ""),
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"adapter": "opencode-tensorx",
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"adapter_version": ADAPTER_VERSION,
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"opencode_version": info.get("version", ""),
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"mode": mode,
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"subagent_stats": {
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"spawned": len(subagent_details),
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"completed": completed_subagents,
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"failed": failed_subagents,
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"by_type": dict(by_type),
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},
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"subagent_details": subagent_details,
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"timed_out": timed_out,
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"interrupted": interrupted,
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"exit_code": exit_code,
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}
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def main() -> int:
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parser = argparse.ArgumentParser(
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description="TensorX-Versuchslauf ueber OpenCode"
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)
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parser.add_argument("--prompt", required=True)
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parser.add_argument("--root", required=True)
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parser.add_argument("--output", required=True)
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parser.add_argument("--model", required=True)
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parser.add_argument("--effort", default="low", choices=EFFORTS)
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parser.add_argument("--mode", default="solo", choices=MODES)
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parser.add_argument("--agents")
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parser.add_argument("--result-dir")
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parser.add_argument("--opencode")
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parser.add_argument("--config-template")
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parser.add_argument(
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"--stall-timeout",
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type=int,
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default=600,
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help="Sekunden ohne stdout/stderr bis zum Abbruch; 0 deaktiviert",
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)
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parser.add_argument(
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"--max-runtime",
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type=int,
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default=0,
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help="Maximale Gesamtlaufzeit in Sekunden; 0 deaktiviert",
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)
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parser.add_argument(
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"--allow-empty-output",
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action="store_true",
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help="Leeres Ergebnisse-Verzeichnis nicht als Fehler werten (nur Smoke-Tests)",
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)
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parser.add_argument("--title", default="run-experiment TensorX")
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args = parser.parse_args()
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prompt_path = Path(args.prompt).resolve()
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root = Path(args.root).resolve()
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output_dir = Path(args.output).resolve()
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result_dir = Path(args.result_dir).resolve() if args.result_dir else output_dir.parent
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agents_file = Path(args.agents).resolve() if args.agents else None
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template_path = (
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Path(args.config_template).resolve()
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if args.config_template
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else Path(__file__).with_name("opencode-tensorx.json")
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)
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if not prompt_path.is_file():
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parser.error(f"Prompt-Datei fehlt: {prompt_path}")
|
|
if not root.is_dir():
|
|
parser.error(f"Root-Verzeichnis fehlt: {root}")
|
|
if not template_path.is_file():
|
|
parser.error(f"OpenCode-Konfiguration fehlt: {template_path}")
|
|
|
|
opencode = resolve_opencode(args.opencode)
|
|
output_dir.mkdir(parents=True, exist_ok=True)
|
|
result_dir.mkdir(parents=True, exist_ok=True)
|
|
meta_dir = result_dir / "_meta"
|
|
meta_dir.mkdir(parents=True, exist_ok=True)
|
|
|
|
events_path = result_dir / "OpenCodeEvents.jsonl"
|
|
stderr_path = result_dir / "OpenCode.log"
|
|
adapter_log_path = result_dir / "Adapter.log"
|
|
config_path = meta_dir / "opencode-config.json"
|
|
session_path = meta_dir / "opencode-session.json"
|
|
raw_result_path = result_dir / "RawResult.json"
|
|
|
|
for path in (events_path, stderr_path, adapter_log_path):
|
|
path.write_text("", encoding="utf-8")
|
|
|
|
def log(message: str) -> None:
|
|
line = f"[{utc_now()}] {message}"
|
|
with adapter_log_path.open("a", encoding="utf-8") as handle:
|
|
handle.write(line + "\n")
|
|
handle.flush()
|
|
sys.stderr.write(line + "\n")
|
|
sys.stderr.flush()
|
|
|
|
model_ref, upstream_model = normalize_model(args.model)
|
|
base_config = json.loads(template_path.read_text(encoding="utf-8-sig"))
|
|
run_config = build_run_config(
|
|
base_config,
|
|
model_ref,
|
|
upstream_model,
|
|
args.mode,
|
|
root,
|
|
output_dir,
|
|
agents_file,
|
|
)
|
|
config_path.write_text(
|
|
json.dumps(run_config, indent=2, ensure_ascii=False), encoding="utf-8"
|
|
)
|
|
|
|
model_config = run_config["provider"][PROVIDER_ID]["models"][upstream_model]
|
|
variants = model_config.get("variants", {})
|
|
command = [
|
|
str(opencode),
|
|
"run",
|
|
"--pure",
|
|
"--auto",
|
|
"--format",
|
|
"json",
|
|
"--model",
|
|
model_ref,
|
|
"--agent",
|
|
"build",
|
|
"--title",
|
|
args.title,
|
|
"--dir",
|
|
str(root),
|
|
]
|
|
if args.effort in variants:
|
|
command.extend(["--variant", args.effort])
|
|
|
|
env = os.environ.copy()
|
|
env["OPENCODE_CONFIG"] = str(config_path)
|
|
prompt_text = prompt_path.read_text(encoding="utf-8-sig")
|
|
start_time = time.monotonic()
|
|
start_iso = utc_now()
|
|
timed_out = False
|
|
interrupted = False
|
|
events: list[dict] = []
|
|
errors: list[str] = []
|
|
session_id = ""
|
|
exit_code = -1
|
|
|
|
log(
|
|
f"Start OpenCode {opencode}; Modell={model_ref}; Modus={args.mode}; "
|
|
f"Effort={args.effort}; Stall-Timeout={args.stall_timeout}s"
|
|
)
|
|
process = subprocess.Popen(
|
|
command,
|
|
cwd=root,
|
|
env=env,
|
|
stdin=subprocess.PIPE,
|
|
stdout=subprocess.PIPE,
|
|
stderr=subprocess.PIPE,
|
|
text=True,
|
|
encoding="utf-8",
|
|
errors="replace",
|
|
bufsize=1,
|
|
)
|
|
assert process.stdin is not None
|
|
assert process.stdout is not None
|
|
assert process.stderr is not None
|
|
process.stdin.write(prompt_text)
|
|
process.stdin.close()
|
|
|
|
updates: queue.Queue = queue.Queue()
|
|
threads = [
|
|
threading.Thread(
|
|
target=stream_reader,
|
|
args=(process.stdout, "stdout", events_path, updates),
|
|
daemon=True,
|
|
),
|
|
threading.Thread(
|
|
target=stream_reader,
|
|
args=(process.stderr, "stderr", stderr_path, updates),
|
|
daemon=True,
|
|
),
|
|
]
|
|
for thread in threads:
|
|
thread.start()
|
|
|
|
last_activity = time.monotonic()
|
|
closed_streams = 0
|
|
try:
|
|
while process.poll() is None or closed_streams < 2:
|
|
try:
|
|
source, line, activity_time = updates.get(timeout=1)
|
|
last_activity = activity_time
|
|
if line is None:
|
|
closed_streams += 1
|
|
continue
|
|
if source == "stdout":
|
|
event = parse_event(line)
|
|
if event:
|
|
events.append(event)
|
|
session_id = event.get("sessionID", session_id)
|
|
except queue.Empty:
|
|
pass
|
|
|
|
now = time.monotonic()
|
|
if args.stall_timeout > 0 and now - last_activity > args.stall_timeout:
|
|
timed_out = True
|
|
errors.append(
|
|
f"Keine OpenCode-Ausgabe seit {args.stall_timeout} Sekunden"
|
|
)
|
|
log(errors[-1] + "; Prozessbaum wird beendet")
|
|
terminate_process_tree(process)
|
|
if args.max_runtime > 0 and now - start_time > args.max_runtime:
|
|
timed_out = True
|
|
errors.append(
|
|
f"Maximale Laufzeit von {args.max_runtime} Sekunden ueberschritten"
|
|
)
|
|
log(errors[-1] + "; Prozessbaum wird beendet")
|
|
terminate_process_tree(process)
|
|
except KeyboardInterrupt:
|
|
interrupted = True
|
|
errors.append("Lauf durch Benutzer unterbrochen")
|
|
log(errors[-1] + "; Prozessbaum wird beendet")
|
|
terminate_process_tree(process)
|
|
finally:
|
|
for thread in threads:
|
|
thread.join(timeout=5)
|
|
try:
|
|
exit_code = process.wait(timeout=5)
|
|
except subprocess.TimeoutExpired:
|
|
terminate_process_tree(process)
|
|
exit_code = process.wait(timeout=5)
|
|
|
|
duration_s = time.monotonic() - start_time
|
|
session = None
|
|
if session_id:
|
|
try:
|
|
session = export_session(
|
|
opencode, session_id, env, root, session_path, log
|
|
)
|
|
except Exception as exc: # Sessionexport darf RawResult nicht verhindern.
|
|
errors.append(f"Sessionexport fehlgeschlagen: {exc}")
|
|
log(errors[-1])
|
|
|
|
if exit_code != 0 and not timed_out and not interrupted:
|
|
errors.append(f"OpenCode beendete sich mit Exitcode {exit_code}")
|
|
result = normalize_result(
|
|
session,
|
|
events,
|
|
model_ref,
|
|
args.mode,
|
|
args.effort,
|
|
exit_code,
|
|
timed_out,
|
|
interrupted,
|
|
duration_s,
|
|
output_dir,
|
|
errors,
|
|
)
|
|
if not args.allow_empty_output and not result["written_files"]:
|
|
result["errors"].append("Ergebnisse-Verzeichnis ist leer")
|
|
result["is_error"] = True
|
|
if result["subtype"] == "success":
|
|
result["subtype"] = "error"
|
|
result["start_time"] = start_iso
|
|
result["end_time"] = utc_now()
|
|
result["opencode_path"] = str(opencode)
|
|
result["config_path"] = str(config_path)
|
|
raw_result_path.write_text(
|
|
json.dumps(result, indent=2, ensure_ascii=False), encoding="utf-8"
|
|
)
|
|
log(
|
|
f"Ende: Exitcode={exit_code}; Status={result['subtype']}; "
|
|
f"Turns={result['num_turns']}; Tokens={result['usage']['total_tokens']}; "
|
|
f"Dateien={len(result['written_files'])}; RawResult={raw_result_path}"
|
|
)
|
|
return 1 if result["is_error"] else 0
|
|
|
|
|
|
if __name__ == "__main__":
|
|
raise SystemExit(main())
|