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869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 | """TRL GRPO `environment_factory` for deepagents SWE-bench sandboxes.
Kaggle has no Docker for instance images — `get_reward` POSTs the model patch
to `SWE_GRADER_URL` (local `scripts/swe_grader_server.py` + tunnel).
Each rollout opens a Langfuse agent trace; every tool call is a nested `tool`
span; grading is an `evaluator` span with reward scores.
"""
from __future__ import annotations
import json
import os
import shutil
import tempfile
import traceback
import uuid
from functools import wraps
from pathlib import Path
from typing import Any, Callable
def _vlog(msg: str, **fields: Any) -> None:
"""Always-on verbose progress (Kaggle logs + local stderr)."""
extra = ""
if fields:
try:
extra = " | " + json.dumps(fields, default=str)[:1200]
except Exception:
extra = f" | {fields!r}"[:1200]
line = f"[darl] {msg}{extra}"
print(line, flush=True)
try:
from deepagents_rl.observability.logging import step
step("swe_env", msg, **fields)
except Exception:
pass
def _result_to_str(obj: Any) -> str:
if obj is None:
return ""
if isinstance(obj, str):
return obj[:8000]
if hasattr(obj, "output") and isinstance(obj.output, str):
return obj.output[:8000]
# Prefer listing entries before error (LsResult / GlobResult)
entries = getattr(obj, "entries", None)
if entries is not None:
lines: list[str] = []
for e in entries:
if isinstance(e, dict):
lines.append(str(e.get("path") or e))
else:
lines.append(str(e))
return ("\n".join(lines) if lines else "(empty directory)")[:8000]
matches = getattr(obj, "matches", None)
if matches is not None and not getattr(obj, "error", None):
try:
return json.dumps(matches, default=str)[:8000]
except Exception:
return str(matches)[:8000]
if hasattr(obj, "error") and obj.error:
return f"ERROR: {obj.error}"[:8000]
try:
return json.dumps(obj, default=str)[:8000]
except Exception:
return str(obj)[:8000]
# Common dirs Qwen invents that most SWE-bench repos do not have.
_PHANTOM_DIRS = frozenset(
{
"src",
"lib",
"app",
"source",
"sources",
"code",
"project",
"workspace",
}
)
def _as_str_list(val: Any) -> list[str]:
if val is None:
return []
if isinstance(val, list):
return [str(x) for x in val]
if isinstance(val, str):
s = val.strip()
if not s:
return []
try:
parsed = json.loads(s)
if isinstance(parsed, list):
return [str(x) for x in parsed]
except json.JSONDecodeError:
pass
return [s]
return [str(val)]
def _truncate(obj: Any, n: int = 4000) -> Any:
if isinstance(obj, str):
return obj[:n]
if isinstance(obj, dict):
return {k: _truncate(v, n) for k, v in list(obj.items())[:40]}
if isinstance(obj, list):
return [_truncate(v, n) for v in obj[:40]]
return obj
def grade_patch_remote(
*,
instance_id: str,
docker_image: str,
eval_script: str,
fail_to_pass: list[str],
pass_to_pass: list[str],
model_patch: str,
timeout_s: int = 1800,
) -> dict[str, Any]:
"""POST patch to the local Docker grader service."""
import requests
base = (os.environ.get("SWE_GRADER_URL") or "").rstrip("/")
if not base:
raise RuntimeError("SWE_GRADER_URL is not set (point at the local grader tunnel)")
headers = {
"Content-Type": "application/json",
"ngrok-skip-browser-warning": "1",
}
token = os.environ.get("SWE_GRADER_TOKEN") or ""
if token:
headers["Authorization"] = f"Bearer {token}"
payload = {
"instance_id": instance_id,
"image": docker_image,
"eval_script": eval_script,
"fail_to_pass": fail_to_pass,
"pass_to_pass": pass_to_pass,
"model_patch": model_patch or "",
"timeout_s": timeout_s,
}
_vlog(
"grader.POST /grade",
url=base,
instance_id=instance_id,
patch_bytes=len((model_patch or "").encode("utf-8")),
timeout_s=timeout_s,
)
resp = requests.post(f"{base}/grade", headers=headers, json=payload, timeout=timeout_s + 60)
_vlog("grader.response", status=resp.status_code, body_preview=(resp.text or "")[:400])
resp.raise_for_status()
data = resp.json()
_vlog(
"grader.result",
instance_id=instance_id,
reward_total=data.get("reward_total"),
resolution=data.get("resolution"),
resolved=data.get("resolved"),
error=data.get("error"),
)
return data
def _traced_tool(method: Callable[..., str]) -> Callable[..., str]:
"""Wrap a public tool method so each call becomes a Langfuse tool span."""
@wraps(method)
def wrapper(self: "DeepAgentSWEEnv", *args: Any, **kwargs: Any) -> str:
return self._call_tool(method.__name__, method, args, kwargs)
return wrapper
class DeepAgentSWEEnv:
"""Per-rollout TRL environment: LocalShellBackend tools + remote Docker reward."""
def __init__(self) -> None:
self._sandbox_parent: Path | None = None
self._sandbox: Path | None = None
self._backend: Any = None
self._task: dict[str, Any] = {}
self._last_reward: float = 0.0
self._last_report: dict[str, Any] = {}
self._rollout_id: str = ""
self._tool_calls: list[dict[str, Any]] = []
self._lf: Any = None
self._root_cm: Any = None
self._root: Any = None
self._trace_id: str = ""
self._root_span_id: str = ""
def _langfuse_enabled(self) -> bool:
if os.getenv("DARL_LANGFUSE", "1").strip() in ("0", "false", "no"):
return False
return bool(os.getenv("LANGFUSE_PUBLIC_KEY") and os.getenv("LANGFUSE_SECRET_KEY"))
def _ensure_langfuse(self) -> Any | None:
if not self._langfuse_enabled():
return None
if self._lf is not None:
return self._lf
try:
from langfuse import Langfuse, get_client
Langfuse(
public_key=os.environ["LANGFUSE_PUBLIC_KEY"],
secret_key=os.environ["LANGFUSE_SECRET_KEY"],
host=os.getenv("LANGFUSE_HOST") or os.getenv("LANGFUSE_BASE_URL"),
)
self._lf = get_client()
return self._lf
except Exception as e: # noqa: BLE001
print(f"[langfuse] init failed: {e}")
return None
def _child_trace_context(self) -> dict[str, str] | None:
"""Attach children to THIS rollout's root — never ambient OTEL context.
Passing only ``trace_id`` (no parent) makes the Langfuse SDK invent a
NonRecordingSpan parent id → orphan parents + mega-trace pollution when
parallel GRPO rollouts share get_client().
"""
if not self._trace_id or not self._root_span_id:
return None
return {"trace_id": self._trace_id, "parent_span_id": self._root_span_id}
def _end_trace(self) -> None:
if self._root_cm is not None:
try:
self._root_cm.__exit__(None, None, None)
except Exception:
pass
self._root_cm = None
self._root = None
self._root_span_id = ""
# Keep _trace_id until next reset for logging; clear after flush.
if self._lf is not None:
try:
self._lf.flush()
except Exception:
pass
def _call_tool(
self,
name: str,
method: Callable[..., str],
args: tuple[Any, ...],
kwargs: dict[str, Any],
) -> str:
payload = _truncate({"args": list(args), "kwargs": kwargs})
n = len(self._tool_calls) + 1
_vlog(
f"tool[{n}].begin {name}",
instance_id=self._task.get("instance_id"),
rollout_id=self._rollout_id,
input=payload,
)
lf = self._lf
ctx = self._child_trace_context()
if lf is None or ctx is None:
try:
out = method(self, *args, **kwargs)
except Exception as e: # noqa: BLE001
out = f"TOOL_ERROR: {type(e).__name__}: {e}"
self._tool_calls.append({"name": name, "input": payload, "output": _truncate(out)})
_vlog(
f"tool[{n}].end {name}",
output_preview=str(out)[:500],
output_chars=len(str(out)),
)
return out
with lf.start_as_current_observation(
name=name,
as_type="tool",
trace_context=ctx,
input=payload,
metadata={
"rollout_id": self._rollout_id,
"instance_id": self._task.get("instance_id"),
"harness": "deepagents-swe-grpo",
"tool_index": n,
"trace_id": self._trace_id,
},
) as span:
try:
out = method(self, *args, **kwargs)
span.update(output=_truncate(out))
except Exception as e: # noqa: BLE001
out = f"TOOL_ERROR: {type(e).__name__}: {e}"
span.update(output=out, level="ERROR")
self._tool_calls.append({"name": name, "input": payload, "output": _truncate(out)})
_vlog(
f"tool[{n}].end {name}",
output_preview=str(out)[:500],
output_chars=len(str(out)),
)
return out
def reset(self, **kwargs: Any) -> str:
"""Materialize repo sandbox; return tool-forcing text TRL appends to the user message."""
self._cleanup()
self._end_trace()
instance_id = str(kwargs.get("instance_id") or kwargs.get("task_id") or "")
repo = str(kwargs.get("repo") or "")
base_commit = str(kwargs.get("base_commit") or "")
docker_image = str(kwargs.get("docker_image") or kwargs.get("image") or "")
eval_script = str(kwargs.get("eval_script") or "")
fail_to_pass = _as_str_list(
kwargs.get("fail_to_pass")
if kwargs.get("fail_to_pass") is not None
else kwargs.get("fail_to_pass_json")
)
pass_to_pass = _as_str_list(
kwargs.get("pass_to_pass")
if kwargs.get("pass_to_pass") is not None
else kwargs.get("pass_to_pass_json")
)
_vlog(
"env.reset.begin",
instance_id=instance_id,
repo=repo,
base_commit=(base_commit[:12] if base_commit else ""),
keys=list(kwargs.keys())[:30],
)
if not instance_id or not repo or not base_commit:
raise ValueError(
f"DeepAgentSWEEnv.reset requires instance_id/repo/base_commit; got keys={list(kwargs)}"
)
if not docker_image or not eval_script.strip():
raise ValueError(f"{instance_id}: missing docker_image/eval_script")
from deepagents.backends import LocalShellBackend
from deepagents_rl.harness.repo import materialize_repo_at_commit
self._rollout_id = str(uuid.uuid4())
self._tool_calls = []
self._task = {
"instance_id": instance_id,
"task_id": instance_id,
"repo": repo,
"base_commit": base_commit,
"image": docker_image,
"docker_image": docker_image,
"eval_script": eval_script,
"fail_to_pass": fail_to_pass,
"pass_to_pass": pass_to_pass,
}
self._last_reward = 0.0
self._last_report = {}
self._trace_id = ""
lf = self._ensure_langfuse()
_vlog("env.reset.langfuse", enabled=lf is not None)
if lf is not None:
try:
# IMPORTANT: do NOT pass trace_context={"trace_id": ...} alone.
# Langfuse SDK then fabricates a NonRecordingSpan parent → orphan
# parent ids in the UI and children from other rollouts can leak in.
# A plain start_as_current_observation creates a clean root trace.
self._root_cm = lf.start_as_current_observation(
name=f"grpo-swe-rollout:{instance_id}",
as_type="agent",
input={
"instance_id": instance_id,
"repo": repo,
"base_commit": base_commit,
"rollout_id": self._rollout_id,
"prompt_preview": _truncate(
kwargs.get("prompt")
if isinstance(kwargs.get("prompt"), str)
else (
kwargs.get("problem_statement")
or (kwargs.get("prompt") or "")
),
2000,
),
},
metadata={
"rollout_id": self._rollout_id,
"instance_id": instance_id,
"docker_image": docker_image,
"phase": "grpo_train_or_eval",
"harness": "deepagents-swe-grpo",
"session_id": self._rollout_id,
"tags": ["deepagents-rl", "swe-bench", "grpo", "tools"],
},
end_on_exit=True,
)
self._root = self._root_cm.__enter__()
self._trace_id = str(
getattr(self._root, "trace_id", None)
or getattr(self._root, "traceId", None)
or ""
)
self._root_span_id = str(
getattr(self._root, "id", None)
or getattr(self._root, "observation_id", None)
or ""
)
_vlog(
"env.reset.langfuse_trace",
trace_id=self._trace_id,
root_span_id=self._root_span_id,
)
except Exception as e: # noqa: BLE001
_vlog("env.reset.langfuse_failed", error=str(e))
self._root_cm = None
self._root = None
self._trace_id = ""
self._root_span_id = ""
def _materialize() -> None:
_vlog("env.reset.materialize", repo=repo, base_commit=base_commit[:12])
self._sandbox_parent = Path(
tempfile.mkdtemp(prefix=f"darl_grpo_{instance_id[:40]}_")
)
self._sandbox = self._sandbox_parent / "repo"
materialize_repo_at_commit(repo=repo, base_commit=base_commit, dest=self._sandbox)
self._backend = LocalShellBackend(
root_dir=str(self._sandbox),
virtual_mode=True,
timeout=60,
)
_vlog("env.reset.sandbox_ready", sandbox=str(self._sandbox))
ctx = self._child_trace_context()
if lf is not None and ctx is not None:
with lf.start_as_current_observation(
name="repo_materialize",
as_type="span",
trace_context=ctx,
input={"repo": repo, "base_commit": base_commit},
) as span:
_materialize()
span.update(output={"sandbox": str(self._sandbox)})
else:
_materialize()
# Pre-list root so the model sees real paths even before its first tool call.
root_listing = ""
try:
root_listing = self._root_listing()
except Exception as e: # noqa: BLE001
root_listing = f"(root listing failed: {e})"
_vlog(
"env.reset.done",
instance_id=instance_id,
rollout_id=self._rollout_id,
n_f2p=len(fail_to_pass),
n_p2p=len(pass_to_pass),
langfuse_trace_id=self._trace_id,
root_listing_chars=len(root_listing),
)
# TRL appends this string to the last user message — force tool use.
return (
"\n\nREPO ROOT LISTING (already gathered for you):\n"
f"{root_listing[:3500]}\n\n"
"CRITICAL REMINDER:\n"
"- You MUST use structured tool/function calls (not markdown ```json```).\n"
"- FIRST tool call: ls path='.' OR grep/glob/read_file on a REAL path from the listing above.\n"
"- Never invent src/lib/app. Prefer edit_file with a unique old_string.\n"
"- Text-only DONE with zero tools scores NEGATIVE reward. Call tools.\n"
"- After a minimal fix, stop tools and reply: DONE <summary>."
)
def _cleanup(self) -> None:
self._backend = None
if self._sandbox_parent is not None and self._sandbox_parent.exists():
shutil.rmtree(self._sandbox_parent, ignore_errors=True)
self._sandbox_parent = None
self._sandbox = None
def _require_backend(self) -> Any:
if self._backend is None:
raise RuntimeError("DeepAgentSWEEnv tool called before reset()")
return self._backend
@staticmethod
def _norm_path(path: str | None) -> str:
p = (path or ".").strip().strip("'\"")
if p in ("", "/", "./", ".\\", "~"):
return "."
# virtual_mode often wants leading slash for absolute-in-sandbox paths
if p.startswith("./"):
p = p[2:]
if p.startswith("/"):
p = p.lstrip("/") or "."
# Drop trailing slash for alias matching
p = p.rstrip("/") or "."
return p or "."
@classmethod
def _resolve_ls_path(cls, path: str | None) -> tuple[str, str | None]:
"""Map invented dirs (src/lib/…) to repo root before hitting the backend."""
p = cls._norm_path(path)
head = p.split("/", 1)[0].lower()
if head in _PHANTOM_DIRS:
return ".", p
return p, None
def _is_missing(self, result_obj: Any, text: str) -> bool:
err = getattr(result_obj, "error", None)
if err and "path_not_found" in str(err).lower():
return True
return "path_not_found" in (text or "").lower()
def _root_listing(self) -> str:
backend = self._require_backend()
# Prefer "/" then "." for virtual_mode backends
for candidate in ("/", "."):
result = backend.ls(candidate)
out = _result_to_str(result)
if not self._is_missing(result, out):
return out
return "(unable to list repo root)"
@_traced_tool
def ls(self, path: str = ".") -> str:
"""List files in a directory inside the sandbox repo root.
Args:
path: Directory relative to the repo root. Use "." for the root.
Do NOT assume a "src/" folder exists — many repos have none.
Returns:
Directory listing as text (falls back to repo root if path missing).
"""
backend = self._require_backend()
path, aliased_from = self._resolve_ls_path(path)
result = backend.ls(path)
out = _result_to_str(result)
if self._is_missing(result, out):
root = self._root_listing()
_vlog("tool.ls.fallback_root", requested=aliased_from or path)
return (
f"Path '{aliased_from or path}' does not exist here.\n"
f"Listing repo root instead (use these real paths):\n{root}"
)
if aliased_from and aliased_from != path:
_vlog("tool.ls.alias", requested=aliased_from, used=path)
return (
f"Note: '{aliased_from}' is not used in this repo; showing repo root:\n{out}"
)
return out
@_traced_tool
def glob(self, pattern: str, path: str = ".") -> str:
"""Glob for files matching pattern under path.
Args:
pattern: Glob pattern (e.g. '**/*.py').
path: Root path for the search (use '.' for repo root).
Returns:
Matching paths as text.
"""
backend = self._require_backend()
path, aliased_from = self._resolve_ls_path(path)
result = backend.glob(pattern, path)
out = _result_to_str(result)
if self._is_missing(result, out):
return (
f"Path '{aliased_from or path}' not found for glob; retrying at repo root.\n"
f"{_result_to_str(backend.glob(pattern, '.'))}"
)
return out
@_traced_tool
def grep(self, pattern: str, path: str = ".") -> str:
"""Search file contents for a regex pattern.
Args:
pattern: Regex pattern to search for.
path: Root path for the search (use '.' for repo root).
Returns:
Matching lines as text.
"""
backend = self._require_backend()
path, aliased_from = self._resolve_ls_path(path)
result = backend.grep(pattern, path)
out = _result_to_str(result)
if self._is_missing(result, out):
return (
f"Path '{aliased_from or path}' not found for grep; retrying at repo root.\n"
f"{_result_to_str(backend.grep(pattern, '.'))}"
)
return out
@_traced_tool
def read_file(self, file_path: str, offset: int = 0, limit: int = 200) -> str:
"""Read a text file from the sandbox.
Args:
file_path: Path relative to the repo root (discover via ls/glob first).
offset: Starting line offset.
limit: Max number of lines to return.
Returns:
File contents as text.
"""
backend = self._require_backend()
file_path = self._norm_path(file_path)
# If model invents src/foo.py, try stripping the phantom prefix once.
head = file_path.split("/", 1)[0].lower()
candidates = [file_path]
if head in _PHANTOM_DIRS and "/" in file_path:
candidates.append(file_path.split("/", 1)[1])
last_out = ""
for cand in candidates:
result = backend.read(cand, offset=offset, limit=limit)
out = _result_to_str(result)
last_out = out
if not self._is_missing(result, out):
if cand != file_path:
return f"(read via '{cand}' — '{file_path}' missing)\n{out}"
return out
return (
f"File '{file_path}' not found. Use ls path='.' or glob to discover real paths.\n"
f"Repo root listing:\n{self._root_listing()}\nLast error: {last_out}"
)
@_traced_tool
def write_file(self, file_path: str, content: str) -> str:
"""Write or create a text file in the sandbox.
Args:
file_path: Path relative to the repo root.
content: Full file contents to write.
Returns:
Write result as text.
"""
return _result_to_str(self._require_backend().write(file_path, content))
@_traced_tool
def edit_file(self, file_path: str, old_string: str, new_string: str) -> str:
"""Replace old_string with new_string in an existing file.
Args:
file_path: Path relative to the repo root.
old_string: Exact text to find.
new_string: Replacement text.
Returns:
Edit result as text.
"""
return _result_to_str(
self._require_backend().edit(file_path, old_string, new_string)
)
@_traced_tool
def execute(self, command: str) -> str:
"""Run a shell command in the sandbox.
Args:
command: Shell command (e.g. python -c '...').
Returns:
Command stdout/stderr as text.
"""
return _result_to_str(self._require_backend().execute(command))
def _shaped_reward(
self,
*,
docker_reward: float,
model_patch: str,
report: dict[str, Any],
) -> tuple[float, dict[str, float]]:
"""Dense process reward so GRPO sees non-zero variance before resolve.
Components (additive, then clamped):
- no tool calls: -0.15
- tool calls: +0.05 each (cap +0.25)
- used edit_file/write_file: +0.15
- non-empty git patch: +0.30
- docker/pass reward (0..1 typically): +1.0 * docker_reward
"""
names = [str(c.get("name") or "") for c in self._tool_calls]
n = len(names)
parts = {
"tool_penalty": -0.15 if n == 0 else 0.0,
"tool_bonus": 0.0 if n == 0 else float(min(0.25, 0.05 * n)),
"edit_bonus": 0.15
if any(x in names for x in ("edit_file", "write_file"))
else 0.0,
"patch_bonus": 0.30 if (model_patch or "").strip() else 0.0,
"docker": float(docker_reward or 0.0),
}
total = sum(parts.values())
total = max(-0.2, min(1.6, total))
parts["total"] = total
return total, parts
def get_reward(self) -> float:
"""Shaped reward = process bonuses + remote Docker SWE score (if patch)."""
lf = self._lf
reward = 0.0
report: dict[str, Any] = {}
shape_parts: dict[str, float] = {}
model_patch = ""
_vlog(
"env.get_reward.begin",
instance_id=self._task.get("instance_id"),
n_tool_calls=len(self._tool_calls),
tools_used=[c.get("name") for c in self._tool_calls],
)
def _grade() -> float:
nonlocal report, model_patch, shape_parts
docker_reward = 0.0
if self._sandbox is None:
report = {"error": "no_sandbox", "reward_total": 0.0}
_vlog("env.get_reward.no_sandbox")
shaped, shape_parts = self._shaped_reward(
docker_reward=0.0, model_patch="", report=report
)
report["shaped"] = shape_parts
report["reward_total"] = shaped
return shaped
from deepagents_rl.harness.repo import git_diff_patch
try:
_vlog("env.get_reward.git_diff")
model_patch = git_diff_patch(self._sandbox)
_vlog(
"env.get_reward.patch",
patch_bytes=len(model_patch.encode("utf-8")),
empty=not bool(model_patch.strip()),
preview=model_patch[:300],
)
except Exception as e: # noqa: BLE001
report = {"error": f"git_diff_failed: {e}"}
_vlog("env.get_reward.git_diff_failed", error=str(e))
shaped, shape_parts = self._shaped_reward(
docker_reward=0.0, model_patch="", report=report
)
report["shaped"] = shape_parts
report["reward_total"] = shaped
return shaped
if not model_patch.strip():
report = {"error": "empty_model_patch", "reward_total": 0.0}
_vlog("env.get_reward.empty_patch")
else:
try:
report = grade_patch_remote(
instance_id=self._task["instance_id"],
docker_image=self._task["docker_image"],
eval_script=self._task["eval_script"],
fail_to_pass=list(self._task["fail_to_pass"]),
pass_to_pass=list(self._task["pass_to_pass"]),
model_patch=model_patch,
)
docker_reward = float(report.get("reward_total") or 0.0)
except Exception as e: # noqa: BLE001
report = {
"error": f"grader_failed: {e}",
"traceback": traceback.format_exc()[-1500:],
}
_vlog("env.get_reward.grader_failed", error=str(e))
docker_reward = 0.0
shaped, shape_parts = self._shaped_reward(
docker_reward=docker_reward,
model_patch=model_patch,
report=report,
)
report["docker_reward"] = docker_reward
report["shaped"] = shape_parts
report["reward_total"] = shaped
_vlog("env.get_reward.shaped", **shape_parts)
return shaped
ctx = self._child_trace_context()
if lf is not None and ctx is not None:
with lf.start_as_current_observation(
name="reward_grader",
as_type="evaluator",
trace_context=ctx,
input={
"instance_id": self._task.get("instance_id"),
"n_tool_calls": len(self._tool_calls),
"tools_used": [c["name"] for c in self._tool_calls],
},
) as span:
reward = _grade()
span.update(
output=_truncate(
{
"reward_total": reward,
"docker_reward": report.get("docker_reward"),
"shaped": report.get("shaped"),
"pass_frac": report.get("pass_frac"),
"resolved": report.get("resolved"),
"resolution": report.get("resolution"),
"error": report.get("error"),
"n_tool_calls": len(self._tool_calls),
}
)
)
try:
lf.score_current_trace(name="reward_total", value=float(reward))
lf.score_current_trace(
name="pass_frac", value=float(report.get("pass_frac") or 0.0)
)
lf.score_current_trace(
name="resolved", value=1.0 if report.get("resolved") else 0.0
)
lf.score_current_trace(
name="n_tool_calls", value=float(len(self._tool_calls))
)
if isinstance(report.get("shaped"), dict):
for sk, sv in report["shaped"].items():
lf.score_current_trace(name=f"shaped_{sk}", value=float(sv))
except Exception:
pass
if self._root is not None:
try:
self._root.update(
output={
"reward_total": reward,
"n_tool_calls": len(self._tool_calls),
"tools_used": [c["name"] for c in self._tool_calls],
"resolution": report.get("resolution"),
"shaped": report.get("shaped"),
}
)
except Exception:
pass
else:
reward = _grade()
self._last_report = report
self._last_reward = reward
_vlog(
"env.get_reward.done",
instance_id=self._task.get("instance_id"),
reward_total=reward,
pass_frac=report.get("pass_frac"),
resolution=report.get("resolution"),
resolved=report.get("resolved"),
error=report.get("error"),
n_tool_calls=len(self._tool_calls),
shaped=report.get("shaped"),
)
# W&B: one point per completed rollout (train + ckpt eval)
try:
import wandb
if wandb.run is not None:
tools_used = [c.get("name") for c in self._tool_calls]
shaped = report.get("shaped") if isinstance(report.get("shaped"), dict) else {}
wandb.log(
{
"rollout/reward_total": float(reward),
"rollout/docker_reward": float(report.get("docker_reward") or 0.0),
"rollout/pass_frac": float(report.get("pass_frac") or 0.0),
"rollout/resolved": 1.0 if report.get("resolved") else 0.0,
"rollout/n_tool_calls": float(len(self._tool_calls)),
"rollout/instance_id": self._task.get("instance_id") or "",
"rollout/tools_used": ",".join(tools_used),
"rollout/resolution": str(report.get("resolution") or ""),
"rollout/grader_error": str(report.get("error") or ""),
"rollout/shaped_tool_bonus": float(shaped.get("tool_bonus") or 0.0),
"rollout/shaped_edit_bonus": float(shaped.get("edit_bonus") or 0.0),
"rollout/shaped_patch_bonus": float(shaped.get("patch_bonus") or 0.0),
}
)
_vlog("env.get_reward.wandb_logged")
except Exception as e: # noqa: BLE001
_vlog("env.get_reward.wandb_failed", error=str(e))
self._end_trace()
_vlog("env.get_reward.trace_closed", trace_id=self._trace_id)
return reward
def prepare_swe_grpo_rows(records: list[dict[str, Any]]) -> list[dict[str, Any]]:
"""Normalize HF SWE Lite rows for TRL GRPO + DeepAgentSWEEnv.
Renames `image` -> `docker_image` so TRL does not treat it as multimodal.
Converts `prompt` to conversational chat messages (required for tool calling).
"""
from deepagents_rl.data.swe_bench_lite import build_agent_prompt, from_hf_record
rows: list[dict[str, Any]] = []
for rec in records:
if "fail_to_pass_json" in rec or (
"prompt" in rec and isinstance(rec.get("prompt"), str) and "image" in rec
):
task = from_hf_record(rec)
else:
task = dict(rec)
# Rebuild prompt locally so tool-forcing text stays current (HF rows may be stale).
messages = [
{
"role": "user",
"content": build_agent_prompt(
str(task.get("problem_statement") or ""),
instance_id=str(task.get("instance_id") or task.get("task_id") or ""),
),
}
]
docker_image = str(task.get("docker_image") or task.get("image") or "")
rows.append(
{
"prompt": messages,
"task_id": task["task_id"],
"instance_id": task["instance_id"],
"repo": task["repo"],
"base_commit": task["base_commit"],
"docker_image": docker_image,
"eval_script": task.get("eval_script") or "",
"fail_to_pass": list(task.get("fail_to_pass") or []),
"pass_to_pass": list(task.get("pass_to_pass") or []),
"problem_statement": task.get("problem_statement") or "",
}
)
return rows
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