# SPDX-License-Identifier: Apache-2.0
"""Helpers for converting parser-emitted tool calls to OpenAI models."""

import logging
import uuid

from pydantic import ValidationError

from .openai_models import FunctionCall, ToolCall

logger = logging.getLogger(__name__)


def convert_parser_tool_calls(tool_calls: list[dict] | None) -> list[ToolCall]:
    """Convert parser-emitted tool-call dicts into validated OpenAI ToolCalls.

    Parser output comes from model text and can contain malformed JSON
    arguments. Treat those as recoverable parser failures rather than letting
    Pydantic validation abort the response stream.
    """
    converted: list[ToolCall] = []
    for tool_call in tool_calls or []:
        if not isinstance(tool_call, dict):
            continue
        name = tool_call.get("name", "")
        arguments = tool_call.get("arguments", "{}") or "{}"
        try:
            converted.append(
                ToolCall(
                    id=tool_call.get("id")
                    or tool_call.get("call_id")
                    or f"call_{uuid.uuid4().hex[:8]}",
                    type="function",
                    function=FunctionCall(
                        name=name,
                        arguments=arguments,
                    ),
                )
            )
        except (TypeError, ValueError, ValidationError) as e:
            snippet = str(arguments)
            if len(snippet) > 120:
                snippet = snippet[:117] + "..."
            logger.warning(
                "Dropping malformed parser tool call %r: %s. arguments=%r",
                name,
                e,
                snippet,
            )
            continue
    return converted