langchain-ai/deepagents · error · RuntimeError

Context Hub commit succeeded but its hash could not be resol

Error message

Context Hub commit succeeded but its hash could not be resolved

What it means

After `_push_batch` pushes a mutation batch, it re-fetches the remote snapshot to learn the resulting commit hash. If the commit succeeded but `commit_hash` is `None`, the success cannot be confirmed/recorded, so `_push_batch` raises `RuntimeError` rather than returning an unresolvable commit. This sits after the conflict-retry loop, where `None` would otherwise indicate exhausted retries.

Source

Thrown at libs/deepagents/deepagents/backends/context_hub.py:373

                    self._identifier,
                    files=payload,
                    parent_commit=parent_commit,
                )
            except LangSmithConflictError as conflict:
                if attempt == _MAX_CONFLICT_RETRIES:
                    raise
                self._reload_after_conflict(conflict)
                continue

            commit_hash = self._extract_commit_hash(url)
            if commit_hash is not None:
                return changes, commit_hash, None

            snapshot = self._fetch_tree()
            commit_hash = snapshot[2]
            if commit_hash is None:
                msg = "Context Hub commit succeeded but its hash could not be resolved"
                raise RuntimeError(msg)
            return changes, commit_hash, snapshot

        msg = "Context Hub conflict retry loop exhausted unexpectedly"
        raise RuntimeError(msg)

    def _complete_batch(
        self,
        batch: list[_Mutation],
        changes: dict[str, str | None],
        commit_hash: str | None,
        *,
        authoritative_snapshot: _TreeSnapshot | None,
    ) -> bool:
        failed_pending: list[_Mutation] = []
        with self._mutations.condition:
            if authoritative_snapshot is None:
                cache = dict(self._ensure_cache_locked())
                self._overlay(cache, changes)

View on GitHub (pinned to a1af029e6e)

Solutions

Retry the commit after a short delay so the new commit becomes visible to `_fetch_tree()`.
Verify the remote implementation always returns the commit hash in the snapshot tuple on success.
Check remote consistency/replication settings; if using a custom backend, fix `_fetch_tree` to surface the latest commit hash.

Example fix

// before: fetch immediately after commit (may see stale snapshot)
changes, commit_hash, snapshot = self._push_batch(batch)
// after: tolerate transient unresolvable hash
try:
    changes, commit_hash, snapshot = self._push_batch(batch)
except RuntimeError:
    time.sleep(0.5)
    changes, commit_hash, snapshot = self._push_batch(batch)

Defensive patterns

Strategy: retry

Try / catch

try:
    changes, commit_hash, snapshot = self._push_batch(batch)
except RuntimeError as e:
    if "hash could not be resolved" in str(e):
        time.sleep(0.5)
        changes, commit_hash, snapshot = self._push_batch(batch)  # retry after consistency window
    else:
        raise

Prevention

Use a remote backend that reliably returns the commit hash in snapshot fetches.
Allow a brief consistency delay between commit and follow-up fetches in high-latency setups.
Add integration tests asserting every successful commit yields a resolvable hash.

When it happens

Trigger: A batch commit to the Context Hub remote reports success, but the follow-up `_fetch_tree()` returns a snapshot whose commit-hash element is `None` — e.g. an unexpected/malformed remote response or eventual-consistency window where the new commit is not yet visible.

Common situations: Flaky or partially-implemented remote returning success without a hash; race where the fetch lands on a pre-commit snapshot; custom/alternative remote backend not filling the hash field.

Related errors

AI-assisted analysis of langchain-ai/deepagents@a1af029e6e (2026-08-29). Data as JSON: /api/errors/1e1a634aa3203d3c. Report an issue: GitHub.