langchain-ai/deepagents · error · ToolRequirementIntrospectionError

uv tool receipt contains a non-table requirement entry

Error message

uv tool receipt contains a non-table requirement entry

What it means

Within [tool].requirements of the uv receipt, one entry is not a table (dict) as uv normally writes. The library iterates requirements expecting {name = ..., extras = [...]} style entries and refuses to guess when an entry is a scalar or array.

Source

Thrown at libs/code/deepagents_code/update_check.py:2967

    Yields:
        Each requirement's declared `name` and its full table entry, in receipt
            order.

    Raises:
        ToolRequirementIntrospectionError: If `[tool].requirements` is missing or
            contains an entry that is not a table with a package name.
    """
    tool = data.get("tool")
    requirements = tool.get("requirements") if isinstance(tool, dict) else None
    if not isinstance(requirements, list):
        msg = "uv tool receipt is missing `[tool].requirements`"
        raise ToolRequirementIntrospectionError(msg)

    for entry in requirements:
        if not isinstance(entry, dict):
            msg = "uv tool receipt contains a non-table requirement entry"
            raise ToolRequirementIntrospectionError(msg)
        name = entry.get("name")
        if not isinstance(name, str) or not name:
            msg = "uv tool receipt contains a requirement without a package name"
            raise ToolRequirementIntrospectionError(msg)
        yield name, entry


def _uv_tool_python(
    tool_root: Path | None = None,
    *,
    data: dict[str, Any] | None = None,
) -> str | None:
    """Return the Python interpreter recorded in the uv tool receipt.

    Args:
        tool_root: Optional uv tool environment root. Defaults to `sys.prefix`.
        data: Optional pre-parsed receipt contents. Supplied by callers that
            read several receipt fields at once so the file is parsed once

View on GitHub (pinned to a1af029e6e)

Solutions

  1. Fix the entry to be a table: use `[[tool.requirements]]` blocks with at least a `name` field.
  2. Regenerate the receipt with `uv tool install deepagents-code --force` rather than editing it manually.
  3. Compare against a known-good receipt from a fresh uv install to confirm the expected schema.

Example fix

// before: string entries (invalid)
 [tool]
 requirements = ["deepagents-code"]
// after: table entries (valid)
 [[tool.requirements]]
 name = "deepagents-code"
Defensive patterns

Strategy: validation

Validate before calling

import tomllib

def requirements_are_tables(data: dict) -> bool:
    reqs = (data.get('tool') or {}).get('requirements', [])
    return isinstance(reqs, list) and all(isinstance(r, dict) for r in reqs)

Type guard

def is_table_requirement(entry: object) -> bool:
    return isinstance(entry, dict) and isinstance(entry.get('name'), str)

Try / catch

try:
    pkgs = _uv_tool_with_packages()
except ToolRequirementIntrospectionError:
    subprocess.run(['uv', 'tool', 'install', 'deepagents-code', '--force'], check=True)

Prevention

When it happens

Trigger: _iter_uv_tool_requirements encounters a requirements list element that is not a dict — e.g. a bare string requirement like "deepagents-code" instead of a [[tool.requirements]] table.

Common situations: Receipt hand-edited to use strings instead of [[tool.requirements]] tables; a receipt from a different/older uv format; file corrupted or truncated mid-entry.

Understand the failure class

Background: Schema validation failed / invalid input schema: payload rejected because its shape doesn't match the expected schema — this error's family across 28 libraries.

Related errors

AI-assisted analysis of langchain-ai/deepagents@a1af029e6e (2026-08-29). Data as JSON: /api/errors/865dceea26ac043f. Report an issue: GitHub.