wehub-resource-sync
66 lines
1.9 KiB
Python
66 lines
1.9 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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from collections.abc import Iterable, Sequence
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from openai.types.responses import ResponseFunctionToolCall
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from vllm.entrypoints.chat_utils import ChatCompletionMessageParam
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from vllm.entrypoints.openai.chat_completion.protocol import ChatCompletionRequest
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from vllm.entrypoints.openai.responses.protocol import (
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ResponseInputOutputItem,
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ResponsesRequest,
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)
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def count_tool_calls(tool_calls: object) -> int:
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if tool_calls is None:
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return 0
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if isinstance(tool_calls, (str, bytes, dict)):
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return 1
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if isinstance(tool_calls, Iterable):
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return sum(1 for _ in tool_calls)
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return 1
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def count_chat_history_tool_calls(
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messages: Sequence[ChatCompletionMessageParam],
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) -> int:
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return sum(
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count_tool_calls(msg.get("tool_calls"))
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for msg in messages
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if isinstance(msg, dict) and msg.get("role") == "assistant"
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)
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def count_response_history_tool_calls(
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response_items: Sequence[ResponseInputOutputItem],
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) -> int:
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count = 0
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for item in response_items:
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if isinstance(item, ResponseFunctionToolCall):
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count += 1
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continue
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if isinstance(item, dict):
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item_type = item.get("type")
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if item_type == "function_call":
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count += 1
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elif item.get("role") == "assistant":
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count += count_tool_calls(item.get("tool_calls"))
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return count
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def count_history_tool_calls(
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request: ChatCompletionRequest | ResponsesRequest,
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) -> int:
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if isinstance(request, ChatCompletionRequest):
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return count_chat_history_tool_calls(request.messages)
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request_input = request.input
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if isinstance(request_input, str):
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return 0
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return count_response_history_tool_calls(request_input)
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