hermes-agent/agent/gemini_schema.py

"""Helpers for translating OpenAI-style tool schemas to Gemini's schema subset."""

from __future__ import annotations

from typing import Any, Dict

# Gemini's ``FunctionDeclaration.parameters`` field accepts the ``Schema``
# object, which is only a subset of OpenAPI 3.0 / JSON Schema.  Strip fields
# outside that subset before sending Hermes tool schemas to Google.
_GEMINI_SCHEMA_ALLOWED_KEYS = {
    "type",
    "format",
    "title",
    "description",
    "nullable",
    "enum",
    "maxItems",
    "minItems",
    "properties",
    "required",
    "minProperties",
    "maxProperties",
    "minLength",
    "maxLength",
    "pattern",
    "example",
    "anyOf",
    "propertyOrdering",
    "default",
    "items",
    "minimum",
    "maximum",
}


def sanitize_gemini_schema(schema: Any) -> Dict[str, Any]:
    """Return a Gemini-compatible copy of a tool parameter schema.

    Hermes tool schemas are OpenAI-flavored JSON Schema and may contain keys
    such as ``$schema`` or ``additionalProperties`` that Google's Gemini
    ``Schema`` object rejects.  This helper preserves the documented Gemini
    subset and recursively sanitizes nested ``properties`` / ``items`` /
    ``anyOf`` definitions.
    """

    if not isinstance(schema, dict):
        return {}

    cleaned: Dict[str, Any] = {}
    for key, value in schema.items():
        if key not in _GEMINI_SCHEMA_ALLOWED_KEYS:
            continue
        if key == "properties":
            if not isinstance(value, dict):
                continue
            props: Dict[str, Any] = {}
            for prop_name, prop_schema in value.items():
                if not isinstance(prop_name, str):
                    continue
                props[prop_name] = sanitize_gemini_schema(prop_schema)
            cleaned[key] = props
            continue
        if key == "items":
            cleaned[key] = sanitize_gemini_schema(value)
            continue
        if key == "anyOf":
            if not isinstance(value, list):
                continue
            cleaned[key] = [
                sanitize_gemini_schema(item)
                for item in value
                if isinstance(item, dict)
            ]
            continue
        cleaned[key] = value

    # Gemini's Schema validator requires every ``enum`` entry to be a string,
    # even when the parent ``type`` is ``integer`` / ``number`` / ``boolean``.
    # OpenAI / OpenRouter / Anthropic accept typed enums (e.g. Discord's
    # ``auto_archive_duration: {type: integer, enum: [60, 1440, 4320, 10080]}``),
    # so we only drop the ``enum`` when it would collide with Gemini's rule.
    # Keeping ``type: integer`` plus the human-readable description gives the
    # model enough guidance; the tool handler still validates the value.
    enum_val = cleaned.get("enum")
    type_val = cleaned.get("type")
    if isinstance(enum_val, list) and type_val in {"integer", "number", "boolean"}:
        if any(not isinstance(item, str) for item in enum_val):
            cleaned.pop("enum", None)

    # Gemini validates ``required`` strictly against the same node's
    # ``properties`` — GenerateContentRequest fails with HTTP 400
    # "...items.required[0]: property is not defined" when a required name
    # has no matching property in that node.  MCP servers routinely emit
    # this shape (e.g. the GitHub remote MCP's array item schemas carry
    # ``required`` without ``properties``), and one bad tool schema fails
    # the ENTIRE request before any model output.  Filter ``required`` to
    # names that exist in this node's ``properties`` and drop it when
    # nothing valid remains.  The tool handler still validates required
    # fields at execution time, so this only removes what Gemini couldn't
    # accept anyway.  (Port of Kilo-Org/kilocode#11955.)
    required_val = cleaned.get("required")
    if isinstance(required_val, list):
        props_val = cleaned.get("properties")
        prop_names = set(props_val.keys()) if isinstance(props_val, dict) else set()
        valid_required = [
            name for name in required_val
            if isinstance(name, str) and name in prop_names
        ]
        if not valid_required:
            cleaned.pop("required", None)
        elif len(valid_required) != len(required_val):
            cleaned["required"] = valid_required

    return cleaned


def sanitize_gemini_tool_parameters(parameters: Any) -> Dict[str, Any]:
    """Normalize tool parameters to a valid Gemini object schema."""

    cleaned = sanitize_gemini_schema(parameters)
    if not cleaned:
        return {"type": "object", "properties": {}}
    return cleaned