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[Frontend][Feature] Add jamba tool parser (vllm-project#9154)
Signed-off-by: Alvant <[email protected]>
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,275 @@ | ||
| import json | ||
| from typing import Generator, List, Optional | ||
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| import partial_json_parser | ||
| import pytest | ||
| from partial_json_parser.core.options import Allow | ||
|
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| from vllm.entrypoints.openai.protocol import (DeltaMessage, FunctionCall, | ||
| ToolCall) | ||
| from vllm.entrypoints.openai.tool_parsers import JambaToolParser | ||
| from vllm.transformers_utils.detokenizer import detokenize_incrementally | ||
| 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") | ||
| def jamba_tokenizer(): | ||
| return get_tokenizer(tokenizer_name=MODEL) | ||
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| @pytest.fixture | ||
| def jamba_tool_parser(jamba_tokenizer): | ||
| return JambaToolParser(jamba_tokenizer) | ||
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| def assert_tool_calls(actual_tool_calls: List[ToolCall], | ||
| expected_tool_calls: List[ToolCall]): | ||
| 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, | ||
| expected_tool_calls): | ||
| assert isinstance(actual_tool_call.id, str) | ||
| assert len(actual_tool_call.id) > 16 | ||
|
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| assert actual_tool_call.type == "function" | ||
| assert actual_tool_call.function == expected_tool_call.function | ||
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| def stream_delta_message_generator( | ||
| jamba_tool_parser: JambaToolParser, jamba_tokenizer: AnyTokenizer, | ||
| model_output: str) -> Generator[DeltaMessage, None, None]: | ||
| all_token_ids = jamba_tokenizer.encode(model_output, | ||
| add_special_tokens=False) | ||
|
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| previous_text = "" | ||
| previous_tokens = None | ||
| prefix_offset = 0 | ||
| read_offset = 0 | ||
| for i, delta_token in enumerate(all_token_ids): | ||
| delta_token_ids = [delta_token] | ||
| previous_token_ids = all_token_ids[:i] | ||
| current_token_ids = all_token_ids[:i + 1] | ||
|
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| (new_tokens, delta_text, new_prefix_offset, | ||
| new_read_offset) = detokenize_incrementally( | ||
| tokenizer=jamba_tokenizer, | ||
| all_input_ids=current_token_ids, | ||
| prev_tokens=previous_tokens, | ||
| prefix_offset=prefix_offset, | ||
| read_offset=read_offset, | ||
| skip_special_tokens=False, | ||
| spaces_between_special_tokens=True, | ||
| ) | ||
|
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| current_text = previous_text + delta_text | ||
|
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| delta_message = jamba_tool_parser.extract_tool_calls_streaming( | ||
| previous_text, | ||
| current_text, | ||
| delta_text, | ||
| previous_token_ids, | ||
| current_token_ids, | ||
| delta_token_ids, | ||
| request=None, # type: ignore[arg-type] | ||
| ) | ||
| if delta_message: | ||
| yield delta_message | ||
|
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||
| previous_text = current_text | ||
| previous_tokens = previous_tokens + new_tokens if previous_tokens\ | ||
| else new_tokens | ||
| prefix_offset = new_prefix_offset | ||
| read_offset = new_read_offset | ||
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| def test_extract_tool_calls_no_tools(jamba_tool_parser): | ||
| model_output = "This is a test" | ||
| extracted_tool_calls = jamba_tool_parser.extract_tool_calls( | ||
| model_output, request=None) # type: ignore[arg-type] | ||
| assert not extracted_tool_calls.tools_called | ||
| assert extracted_tool_calls.tool_calls == [] | ||
| assert extracted_tool_calls.content == model_output | ||
|
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| @pytest.mark.parametrize( | ||
| ids=[ | ||
| "single_tool", | ||
| "single_tool_with_content", | ||
| "parallel_tools", | ||
| ], | ||
| argnames=["model_output", "expected_tool_calls", "expected_content"], | ||
| argvalues=[ | ||
| ( | ||
| ''' <tool_calls>[\n {"name": "get_current_weather", "arguments": {"city": "Dallas", "state": "TX", "unit": "fahrenheit"}}\n]</tool_calls>''', # noqa: E501 | ||
| [ | ||
| ToolCall(function=FunctionCall(name="get_current_weather", | ||
| arguments=json.dumps( | ||
| { | ||
| "city": "Dallas", | ||
| "state": "TX", | ||
| "unit": "fahrenheit" | ||
| }))) | ||
| ], | ||
| None), | ||
| ( | ||
| ''' 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 | ||
| [ | ||
| ToolCall(function=FunctionCall(name="get_current_weather", | ||
| arguments=json.dumps( | ||
| { | ||
| "city": "Dallas", | ||
| "state": "TX", | ||
| "unit": "fahrenheit" | ||
| }))) | ||
| ], | ||
| " Sure! let me call the tool for you."), | ||
| ( | ||
| ''' <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 | ||
| [ | ||
| ToolCall(function=FunctionCall(name="get_current_weather", | ||
| arguments=json.dumps( | ||
| { | ||
| "city": "Dallas", | ||
| "state": "TX", | ||
| "unit": "fahrenheit" | ||
| }))), | ||
| ToolCall(function=FunctionCall(name="get_current_weather", | ||
| arguments=json.dumps( | ||
| { | ||
| "city": "Orlando", | ||
| "state": "FL", | ||
| "unit": "fahrenheit" | ||
| }))) | ||
| ], | ||
| None) | ||
| ], | ||
| ) | ||
| def test_extract_tool_calls(jamba_tool_parser, model_output, | ||
| expected_tool_calls, expected_content): | ||
| extracted_tool_calls = jamba_tool_parser.extract_tool_calls( | ||
| model_output, request=None) # type: ignore[arg-type] | ||
| 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( | ||
| ids=[ | ||
| "no_tools", | ||
| "single_tool", | ||
| "single_tool_with_content", | ||
| "parallel_tools", | ||
| ], | ||
| argnames=["model_output", "expected_tool_calls", "expected_content"], | ||
| argvalues=[ | ||
| ('''This is a test''', [], '''This is a test'''), | ||
| ( | ||
| ''' <tool_calls>[\n {"name": "get_current_weather", "arguments": {"city": "Dallas", "state": "TX", "unit": "fahrenheit"}}\n]</tool_calls>''', # noqa: E501 | ||
| [ | ||
| ToolCall(function=FunctionCall(name="get_current_weather", | ||
| arguments=json.dumps( | ||
| { | ||
| "city": "Dallas", | ||
| "state": "TX", | ||
| "unit": "fahrenheit" | ||
| }))) | ||
| ], | ||
| " "), | ||
| ( | ||
| ''' 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 | ||
| [ | ||
| ToolCall(function=FunctionCall(name="get_current_weather", | ||
| arguments=json.dumps( | ||
| { | ||
| "city": "Dallas", | ||
| "state": "TX", | ||
| "unit": "fahrenheit" | ||
| }))) | ||
| ], | ||
| " Sure! let me call the tool for you."), | ||
| ( | ||
| ''' <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 | ||
| [ | ||
| ToolCall(function=FunctionCall(name="get_current_weather", | ||
| arguments=json.dumps( | ||
| { | ||
| "city": "Dallas", | ||
| "state": "TX", | ||
| "unit": "fahrenheit" | ||
| }))), | ||
| ToolCall(function=FunctionCall(name="get_current_weather", | ||
| arguments=json.dumps( | ||
| { | ||
| "city": "Orlando", | ||
| "state": "FL", | ||
| "unit": "fahrenheit" | ||
| }))) | ||
| ], | ||
| " ") | ||
| ], | ||
| ) | ||
| def test_extract_tool_calls_streaming(jamba_tool_parser, jamba_tokenizer, | ||
| model_output, expected_tool_calls, | ||
| expected_content): | ||
| other_content: str = '' | ||
| function_names: List[str] = [] | ||
| function_args_strs: List[str] = [] | ||
| tool_call_idx: int = -1 | ||
| tool_call_ids: List[Optional[str]] = [] | ||
|
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| for delta_message in stream_delta_message_generator( | ||
| jamba_tool_parser, jamba_tokenizer, model_output): | ||
| # role should never be streamed from tool parser | ||
| assert not delta_message.role | ||
|
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| if delta_message.content: | ||
| 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: | ||
| # make sure only one diff is present - correct even for parallel | ||
| assert len(streamed_tool_calls) == 1 | ||
| tool_call = streamed_tool_calls[0] | ||
|
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| # if a new tool is being called, set up empty arguments | ||
| if tool_call.index != tool_call_idx: | ||
| tool_call_idx = tool_call.index | ||
| function_args_strs.append("") | ||
| tool_call_ids.append(None) | ||
|
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||
| # if a tool call ID is streamed, make sure one hasn't been already | ||
| if tool_call.id and not tool_call_ids[tool_call.index]: | ||
| tool_call_ids[tool_call.index] = tool_call.id | ||
|
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| # if parts of the function start being streamed | ||
| if tool_call.function: | ||
| # if the function name is defined, set it. it should be streamed | ||
| # IN ENTIRETY, exactly one time. | ||
| if tool_call.function.name: | ||
| assert isinstance(tool_call.function.name, str) | ||
| function_names.append(tool_call.function.name) | ||
|
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| if tool_call.function.arguments: | ||
| # make sure they're a string and then add them to the list | ||
| assert isinstance(tool_call.function.arguments, str) | ||
|
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| function_args_strs[ | ||
| tool_call.index] += tool_call.function.arguments | ||
|
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| assert other_content == expected_content | ||
|
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| actual_tool_calls = [ | ||
| ToolCall(id=tool_call_id, | ||
| function=FunctionCall( | ||
| name=function_name, | ||
| arguments=partial_json_parser.ensure_json( | ||
| function_args_str, Allow.OBJ | Allow.STR))) | ||
| for tool_call_id, function_name, function_args_str in zip( | ||
| tool_call_ids, function_names, function_args_strs) | ||
| ] | ||
| assert_tool_calls(actual_tool_calls, expected_tool_calls) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,10 +1,12 @@ | ||
| from .abstract_tool_parser import ToolParser, ToolParserManager | ||
| from .hermes_tool_parser import Hermes2ProToolParser | ||
| from .internlm2_tool_parser import Internlm2ToolParser | ||
| from .jamba_tool_parser import JambaToolParser | ||
| from .llama_tool_parser import Llama3JsonToolParser | ||
| from .mistral_tool_parser import MistralToolParser | ||
|
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| __all__ = [ | ||
| "ToolParser", "ToolParserManager", "Hermes2ProToolParser", | ||
| "MistralToolParser", "Internlm2ToolParser", "Llama3JsonToolParser" | ||
| "MistralToolParser", "Internlm2ToolParser", "Llama3JsonToolParser", | ||
| "JambaToolParser" | ||
| ] |
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