e489ad7a21
- **Add SPDX license headers to python source files**
- **Check for SPDX headers using pre-commit**
commit 9d7ef44c3cfb72ca4c32e1c677d99259d10d4745
Author: Russell Bryant <rbryant@redhat.com>
Date: Fri Jan 31 14:18:24 2025 -0500
Add SPDX license headers to python source files
This commit adds SPDX license headers to python source files as
recommended to
the project by the Linux Foundation. These headers provide a concise way
that is
both human and machine readable for communicating license information
for each
source file. It helps avoid any ambiguity about the license of the code
and can
also be easily used by tools to help manage license compliance.
The Linux Foundation runs license scans against the codebase to help
ensure
we are in compliance with the licenses of the code we use, including
dependencies. Having these headers in place helps that tool do its job.
More information can be found on the SPDX site:
- https://spdx.dev/learn/handling-license-info/
Signed-off-by: Russell Bryant <rbryant@redhat.com>
commit 5a1cf1cb3b80759131c73f6a9dddebccac039dea
Author: Russell Bryant <rbryant@redhat.com>
Date: Fri Jan 31 14:36:32 2025 -0500
Check for SPDX headers using pre-commit
Signed-off-by: Russell Bryant <rbryant@redhat.com>
---------
Signed-off-by: Russell Bryant <rbryant@redhat.com>
278 lines
12 KiB
Python
278 lines
12 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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import json
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from typing import Generator, List, Optional
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import partial_json_parser
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import pytest
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from partial_json_parser.core.options import Allow
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from vllm.entrypoints.openai.protocol import (DeltaMessage, FunctionCall,
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ToolCall)
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from vllm.entrypoints.openai.tool_parsers import JambaToolParser
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from vllm.transformers_utils.detokenizer import detokenize_incrementally
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from vllm.transformers_utils.tokenizer import AnyTokenizer, get_tokenizer
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MODEL = "ai21labs/Jamba-tiny-dev"
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@pytest.fixture(scope="module")
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def jamba_tokenizer():
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return get_tokenizer(tokenizer_name=MODEL)
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@pytest.fixture
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def jamba_tool_parser(jamba_tokenizer):
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return JambaToolParser(jamba_tokenizer)
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def assert_tool_calls(actual_tool_calls: List[ToolCall],
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expected_tool_calls: List[ToolCall]):
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assert len(actual_tool_calls) == len(expected_tool_calls)
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for actual_tool_call, expected_tool_call in zip(actual_tool_calls,
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expected_tool_calls):
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assert isinstance(actual_tool_call.id, str)
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assert len(actual_tool_call.id) > 16
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assert actual_tool_call.type == "function"
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assert actual_tool_call.function == expected_tool_call.function
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def stream_delta_message_generator(
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jamba_tool_parser: JambaToolParser, jamba_tokenizer: AnyTokenizer,
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model_output: str) -> Generator[DeltaMessage, None, None]:
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all_token_ids = jamba_tokenizer.encode(model_output,
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add_special_tokens=False)
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previous_text = ""
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previous_tokens = None
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prefix_offset = 0
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read_offset = 0
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for i, delta_token in enumerate(all_token_ids):
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delta_token_ids = [delta_token]
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previous_token_ids = all_token_ids[:i]
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current_token_ids = all_token_ids[:i + 1]
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(new_tokens, delta_text, new_prefix_offset,
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new_read_offset) = detokenize_incrementally(
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tokenizer=jamba_tokenizer,
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all_input_ids=current_token_ids,
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prev_tokens=previous_tokens,
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prefix_offset=prefix_offset,
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read_offset=read_offset,
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skip_special_tokens=False,
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spaces_between_special_tokens=True,
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)
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current_text = previous_text + delta_text
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delta_message = jamba_tool_parser.extract_tool_calls_streaming(
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previous_text,
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current_text,
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delta_text,
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previous_token_ids,
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current_token_ids,
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delta_token_ids,
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request=None, # type: ignore[arg-type]
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)
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if delta_message:
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yield delta_message
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previous_text = current_text
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previous_tokens = previous_tokens + new_tokens if previous_tokens\
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else new_tokens
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prefix_offset = new_prefix_offset
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read_offset = new_read_offset
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def test_extract_tool_calls_no_tools(jamba_tool_parser):
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model_output = "This is a test"
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extracted_tool_calls = jamba_tool_parser.extract_tool_calls(
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model_output, request=None) # type: ignore[arg-type]
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assert not extracted_tool_calls.tools_called
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assert extracted_tool_calls.tool_calls == []
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assert extracted_tool_calls.content == model_output
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@pytest.mark.parametrize(
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ids=[
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"single_tool",
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"single_tool_with_content",
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"parallel_tools",
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],
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argnames=["model_output", "expected_tool_calls", "expected_content"],
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argvalues=[
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(
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''' <tool_calls>[\n {"name": "get_current_weather", "arguments": {"city": "Dallas", "state": "TX", "unit": "fahrenheit"}}\n]</tool_calls>''', # noqa: E501
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[
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ToolCall(function=FunctionCall(name="get_current_weather",
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arguments=json.dumps(
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{
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"city": "Dallas",
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"state": "TX",
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"unit": "fahrenheit"
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})))
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],
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None),
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(
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''' Sure! let me call the tool for you.<tool_calls>[\n {"name": "get_current_weather", "arguments": {"city": "Dallas", "state": "TX", "unit": "fahrenheit"}}\n]</tool_calls>''', # noqa: E501
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[
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ToolCall(function=FunctionCall(name="get_current_weather",
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arguments=json.dumps(
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{
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"city": "Dallas",
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"state": "TX",
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"unit": "fahrenheit"
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})))
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],
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" Sure! let me call the tool for you."),
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(
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''' <tool_calls>[\n {"name": "get_current_weather", "arguments": {"city": "Dallas", "state": "TX", "unit": "fahrenheit"}},\n {"name": "get_current_weather", "arguments": {"city": "Orlando", "state": "FL", "unit": "fahrenheit"}}\n]</tool_calls>''', # noqa: E501
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[
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ToolCall(function=FunctionCall(name="get_current_weather",
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arguments=json.dumps(
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{
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"city": "Dallas",
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"state": "TX",
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"unit": "fahrenheit"
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}))),
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ToolCall(function=FunctionCall(name="get_current_weather",
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arguments=json.dumps(
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{
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"city": "Orlando",
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"state": "FL",
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"unit": "fahrenheit"
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})))
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],
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None)
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],
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)
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def test_extract_tool_calls(jamba_tool_parser, model_output,
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expected_tool_calls, expected_content):
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extracted_tool_calls = jamba_tool_parser.extract_tool_calls(
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model_output, request=None) # type: ignore[arg-type]
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assert extracted_tool_calls.tools_called
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assert_tool_calls(extracted_tool_calls.tool_calls, expected_tool_calls)
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assert extracted_tool_calls.content == expected_content
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@pytest.mark.parametrize(
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ids=[
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"no_tools",
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"single_tool",
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"single_tool_with_content",
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"parallel_tools",
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],
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argnames=["model_output", "expected_tool_calls", "expected_content"],
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argvalues=[
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('''This is a test''', [], '''This is a test'''),
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(
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''' <tool_calls>[\n {"name": "get_current_weather", "arguments": {"city": "Dallas", "state": "TX", "unit": "fahrenheit"}}\n]</tool_calls>''', # noqa: E501
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[
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ToolCall(function=FunctionCall(name="get_current_weather",
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arguments=json.dumps(
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{
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"city": "Dallas",
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"state": "TX",
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"unit": "fahrenheit"
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})))
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],
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" "),
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(
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''' Sure! let me call the tool for you.<tool_calls>[\n {"name": "get_current_weather", "arguments": {"city": "Dallas", "state": "TX", "unit": "fahrenheit"}}\n]</tool_calls>''', # noqa: E501
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[
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ToolCall(function=FunctionCall(name="get_current_weather",
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arguments=json.dumps(
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{
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"city": "Dallas",
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"state": "TX",
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"unit": "fahrenheit"
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})))
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],
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" Sure! let me call the tool for you."),
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(
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''' <tool_calls>[\n {"name": "get_current_weather", "arguments": {"city": "Dallas", "state": "TX", "unit": "fahrenheit"}},\n {"name": "get_current_weather", "arguments": {"city": "Orlando", "state": "FL", "unit": "fahrenheit"}}\n]</tool_calls>''', # noqa: E501
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[
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ToolCall(function=FunctionCall(name="get_current_weather",
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arguments=json.dumps(
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{
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"city": "Dallas",
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"state": "TX",
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"unit": "fahrenheit"
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}))),
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ToolCall(function=FunctionCall(name="get_current_weather",
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arguments=json.dumps(
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{
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"city": "Orlando",
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"state": "FL",
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"unit": "fahrenheit"
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})))
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],
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" ")
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],
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)
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def test_extract_tool_calls_streaming(jamba_tool_parser, jamba_tokenizer,
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model_output, expected_tool_calls,
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expected_content):
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other_content: str = ''
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function_names: List[str] = []
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function_args_strs: List[str] = []
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tool_call_idx: int = -1
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tool_call_ids: List[Optional[str]] = []
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for delta_message in stream_delta_message_generator(
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jamba_tool_parser, jamba_tokenizer, model_output):
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# role should never be streamed from tool parser
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assert not delta_message.role
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if delta_message.content:
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other_content += delta_message.content
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streamed_tool_calls = delta_message.tool_calls
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if streamed_tool_calls and len(streamed_tool_calls) > 0:
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# make sure only one diff is present - correct even for parallel
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assert len(streamed_tool_calls) == 1
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tool_call = streamed_tool_calls[0]
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# if a new tool is being called, set up empty arguments
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if tool_call.index != tool_call_idx:
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tool_call_idx = tool_call.index
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function_args_strs.append("")
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tool_call_ids.append(None)
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# if a tool call ID is streamed, make sure one hasn't been already
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if tool_call.id and not tool_call_ids[tool_call.index]:
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tool_call_ids[tool_call.index] = tool_call.id
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# if parts of the function start being streamed
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if tool_call.function:
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# if the function name is defined, set it. it should be streamed
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# IN ENTIRETY, exactly one time.
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if tool_call.function.name:
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assert isinstance(tool_call.function.name, str)
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function_names.append(tool_call.function.name)
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if tool_call.function.arguments:
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# make sure they're a string and then add them to the list
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assert isinstance(tool_call.function.arguments, str)
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function_args_strs[
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tool_call.index] += tool_call.function.arguments
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assert other_content == expected_content
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actual_tool_calls = [
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ToolCall(id=tool_call_id,
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function=FunctionCall(
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name=function_name,
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arguments=partial_json_parser.ensure_json(
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function_args_str, Allow.OBJ | Allow.STR)))
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for tool_call_id, function_name, function_args_str in zip(
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tool_call_ids, function_names, function_args_strs)
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]
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assert_tool_calls(actual_tool_calls, expected_tool_calls)
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