337 lines
10 KiB
Python
337 lines
10 KiB
Python
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# SPDX-License-Identifier: Apache-2.0
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import json
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import re
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from copy import deepcopy
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from unittest.mock import MagicMock
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import pytest
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from pydantic import TypeAdapter
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from vllm.entrypoints.openai.protocol import (ChatCompletionRequest,
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ChatCompletionToolsParam)
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from vllm.entrypoints.openai.serving_chat import OpenAIServingChat
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EXAMPLE_TOOLS = [
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{
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"type": "function",
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"function": {
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"name": "get_current_weather",
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"description": "Get the current weather in a given location",
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"parameters": {
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"type": "object",
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"properties": {
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"city": {
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"type":
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"string",
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"description":
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"The city to find the weather for"
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", e.g. 'San Francisco'",
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},
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},
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"required": ["city"],
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"additionalProperties": False
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},
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},
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"strict": True
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},
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{
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"type": "function",
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"function": {
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"name": "get_forecast",
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"description": "Get the weather forecast for a given location",
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"parameters": {
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"type": "object",
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"properties": {
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"city": {
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"type":
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"string",
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"description":
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"The city to get the forecast for, e.g. 'New York'",
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},
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"days": {
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"type":
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"integer",
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"description":
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"Number of days to get the forecast for (1-7)",
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},
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},
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"required": ["city", "days"],
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"additionalProperties": False
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},
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},
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"strict": True
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},
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]
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def _compile_and_check(tools: list[ChatCompletionToolsParam], sample_output,
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should_match: bool):
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self = MagicMock(tool_choice="required", tools=tools)
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schema = ChatCompletionRequest._get_guided_json_from_tool(self)
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assert isinstance(schema, dict)
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# use build_regex_from_schema used in JSONLogitsProcessor to create Guide
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from outlines_core.fsm.json_schema import build_regex_from_schema
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regex = build_regex_from_schema(json.dumps(schema))
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compiled = re.compile(regex)
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matches = compiled.fullmatch(json.dumps(sample_output)) is not None
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assert matches == should_match
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VALID_TOOL_OUTPUTS = [
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([{
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"name": "get_current_weather",
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"parameters": {
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"city": "Vienna"
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}
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}], True),
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([{
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"name": "get_current_weather",
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"parameters": {
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"city": "Vienna"
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}
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}, {
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"name": "get_current_weather",
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"parameters": {
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"city": "Berlin"
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}
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}], True),
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([{
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"name": "get_forecast",
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"parameters": {
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"city": "Vienna",
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"days": 7
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}
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}], True),
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([{
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"name": "get_forecast",
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"parameters": {
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"city": "Vienna",
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"days": 7
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}
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}, {
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"name": "get_current_weather",
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"parameters": {
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"city": "Vienna"
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}
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}], True),
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([{
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"name": "get_forecast",
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"parameters": {
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"city": "Vienna",
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"days": 7
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}
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}, {
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"name": "get_current_weather",
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"parameters": {
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"city": "Vienna"
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}
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}, {
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"name": "get_forecast",
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"parameters": {
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"city": "Berlin",
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"days": 7
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}
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}, {
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"name": "get_current_weather",
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"parameters": {
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"city": "Berlin"
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}
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}], True),
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]
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VALID_TOOLS = [t[0] for t in VALID_TOOL_OUTPUTS]
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@pytest.mark.parametrize(
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"sample_output, should_match",
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VALID_TOOL_OUTPUTS + [
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(None, False),
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([], False), # empty list cannot be generated
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({}, False), # empty object cannot be generated
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([{}], False), # list with empty object cannot be generated
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(
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[{ # function without required parameters cannot be generated
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"name": "get_current_weather"
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}],
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False),
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(
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[{ # function without required parameters cannot be generated
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"name": "get_current_weather",
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"parameters": {}
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}],
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False),
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(
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[{ # function without required parameters cannot be generated
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"name": "get_current_weather",
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"parameters": None
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}],
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False),
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(
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{ # tool call without lists cannot be generated
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"name": "get_current_weather",
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"parameters": {
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"city": "Vienna"
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}
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},
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False),
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(
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[{ # tool call with extra parameters cannot be generated
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"name": "get_current_weather",
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"parameters": {
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"city": "Vienna",
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"extra": "value"
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}
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}],
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False),
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(
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[{ # tool call where parameters are first cannot be generated
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"parameters": {
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"city": "Vienna"
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},
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"name": "get_current_weather"
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}],
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False),
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(
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[{ # tool call without all required parameters cannot be generated
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"name": "get_forecast",
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"parameters": {
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"city": "Vienna"
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}
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}],
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False),
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( # tool call with incorrect name/parameters cannot be generated
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[{
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"name": "get_weather",
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"parameters": {
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"city": "Vienna",
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"days": 7
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}
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}], False),
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( # tool call with both valid and empty function cannot be generated
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[{
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"name": "get_current_weather",
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"parameters": {
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"city": "Vienna"
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}
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}, {}], False),
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])
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def test_guided_json(sample_output, should_match):
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_compile_and_check(tools=TypeAdapter(
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list[ChatCompletionToolsParam]).validate_python(EXAMPLE_TOOLS),
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sample_output=sample_output,
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should_match=should_match)
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def update_parameters_none(
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tool: ChatCompletionToolsParam) -> ChatCompletionToolsParam:
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tool.function.parameters = None
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return tool
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def update_parameters_empty_dict(
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tool: ChatCompletionToolsParam) -> ChatCompletionToolsParam:
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tool.function.parameters = {}
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return tool
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@pytest.mark.parametrize(
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"sample_output, should_match",
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[
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(None, False),
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([], False), # empty list cannot be generated
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({}, False), # empty object cannot be generated
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([{}], False), # list with empty object cannot be generated
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(
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[{ # function without required parameters cannot be generated
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"name": "get_current_weather"
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}],
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False),
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(
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[{ # function without required parameters cannot be generated
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"name": "get_current_weather",
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"parameters": None
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}],
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False),
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(
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[{ # function with extra parameters cannot be generated
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"name": "get_current_weather",
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"parameters": {
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"extra": "value"
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}
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}],
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False),
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(
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[{ # only function with empty parameters object is valid
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"name": "get_current_weather",
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"parameters": {}
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}],
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True),
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])
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@pytest.mark.parametrize(
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"update_parameters",
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[update_parameters_none, update_parameters_empty_dict])
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def test_guided_json_without_parameters(sample_output, should_match,
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update_parameters):
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updated_tools = [deepcopy(EXAMPLE_TOOLS[0])]
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tools = TypeAdapter(
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list[ChatCompletionToolsParam]).validate_python(updated_tools)
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tools = list(map(update_parameters, tools))
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assert all([
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tool.function.parameters is None or tool.function.parameters == {}
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for tool in tools
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])
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_compile_and_check(tools=tools,
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sample_output=sample_output,
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should_match=should_match)
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@pytest.mark.parametrize("output", VALID_TOOLS)
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@pytest.mark.parametrize("empty_params", [False, True])
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@pytest.mark.parametrize("delta_len", [1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
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def test_streaming_output_valid(output, empty_params, delta_len):
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self = MagicMock()
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output = deepcopy(output)
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if empty_params:
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output = [{"name": o["name"], "parameters": {}} for o in output]
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output_json = json.dumps(output)
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previous_text = ""
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function_name_returned = False
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messages = []
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for i in range(0, len(output_json), delta_len):
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delta_text = output_json[i:i + delta_len]
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current_text = previous_text + delta_text
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delta_message, function_name_returned = (
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OpenAIServingChat.extract_tool_call_required_streaming(
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self,
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previous_text=previous_text,
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current_text=current_text,
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delta_text=delta_text,
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function_name_returned=function_name_returned))
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if delta_message:
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messages.append(delta_message)
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previous_text = current_text
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assert len(messages) > 0
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combined_messages = "["
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for message in messages:
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if message.tool_calls[0].function.name:
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if len(combined_messages) > 1:
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combined_messages += "},"
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combined_messages += '{"name": "' + \
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message.tool_calls[0].function.name + \
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'", "parameters": ' + \
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message.tool_calls[0].function.arguments
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else:
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combined_messages += message.tool_calls[0].function.arguments
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combined_messages += "}]"
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assert json.loads(combined_messages) == output
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assert json.dumps(json.loads(combined_messages)) == output_json
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