[Frontend] Adding the "User Defined Custom Tool Calling" parser for the Llama models

examples/tool_chat_template_llama3.1_usr_def_tool_call.jinja

@@ -0,0 +1,131 @@
+{{- bos_token }}
+{%- if custom_tools is defined %}
+    {%- set tools = custom_tools %}
+{%- endif %}
+{%- if not tools_in_user_message is defined %}
+    {%- set tools_in_user_message = false %}
+{%- endif %}
+{%- if not date_string is defined %}
+    {%- set date_string = "26 Jul 2024" %}
+{%- endif %}
+
+{#- This block extracts the system message, so we can slot it into the right place. #}
+{%- if messages[0]['role'] == 'system' %}
+    {%- set system_message = messages[0]['content']|trim %}
+    {%- set messages = messages[1:] %}
+{%- else %}
+    {%- set system_message = "" %}
+{%- endif %}
+
+{#- System message + builtin tools #}
+{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
+{%- if builtin_tools is defined or tools is not none %}
+    {{- "Environment: ipython\n" }}
+{%- endif %}
+{%- if builtin_tools is defined %}
+    {{- "Tools: " + builtin_tools | reject('equalto', 'code_interpreter') | join(", ") + "\n\n"}}
+{%- endif %}
+{{- "Cutting Knowledge Date: December 2023\n" }}
+{{- "Today Date: " + date_string + "\n\n" }}
+
+{%- if builtin_tools is defined %}
+    {{- "# Tool Instructions\n"}}
+    {{- "- Always execute python code in messages that you share.\n"}}
+    {{- "- When looking for real time information use relevant functions if available else fallback to brave_search\n\n\n"}}
+{%- endif %}
+
+{%- if tools is not none and not tools_in_user_message %}
+    {{- "You have access to the following functions:\n\n"}}
+
+    {%- for t in tools %}
+        {%- if t.function is defined %}
+                {%- set t = t.function %}
+        {%- endif -%}
+        {{- "Use the function '"+t.name+"' to: "+t.description+"\n"}}
+        {{- t | tojson(indent=4) }}
+        {{- "\n\n" }}
+    {%- endfor %}
+    {{- "If a you choose to call a function ONLY reply in the following format:\n"}}
+    {{- "<{start_tag}={function_name}>{parameters}{end_tag}\n" }}
+    {{- "where\n\n"}}
+    {{- "start_tag => `<function`\n" }}
+    {{- "parameters => a JSON dict with the function argument name as key and function argument value as value.\n"}}
+    {{- "end_tag => `</function>`" }}
+    {{- "\n\n" }}
+    {{- "Here is an example,\n"}}
+    {{- "<function=example_function_name>{\"example_name\": \"example_value\"}</function>"}}
+    {{- "\n\n"  }}
+    {{- "Reminder:\n"}}
+    {{- "- Function calls MUST follow the specified format\n"}}
+    {{- "- Required parameters MUST be specified\n"}}
+    {{- "- Only call one function at a time\n"}}
+    {{- "- Put the entire function call reply on one line\n"}}
+    {{- "- Always use the information returned by the function to answer to the user\n"}}
+    {{- "- If there is no relevant function available, do NOT call any function: respond directly to the user\n\n"}}
+
+{%- endif %}
+{{- system_message }}
+{{- "<|eot_id|>" }}
+
+{#- Custom tools are passed in a user message with some extra guidance #}
+{%- if tools_in_user_message and not tools is none %}
+    {#- Extract the first user message so we can plug it in here #}
+    {%- if messages | length != 0 %}
+        {%- set first_user_message = messages[0]['content']|trim %}
+        {%- set messages = messages[1:] %}
+    {%- else %}
+        {{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
+{%- endif %}
+    {{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
+    {{- "Given the following functions, please respond with a JSON for a function call " }}
+    {{- "with its proper arguments that best answers the given prompt.\n\n" }}
+    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
+    {{- "Do not use variables.\n\n" }}
+    {%- for t in tools %}
+        {{- t | tojson }}
+        {{- "\n\n" }}
+    {%- endfor %}
+    {{- first_user_message + "<|eot_id|>"}}
+{%- endif %}
+
+{%- for message in messages %}
+    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
+        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
+    {%- elif 'tool_calls' in message %}
+        {%- if not message.tool_calls|length == 1 %}
+            {{- raise_exception("This model only supports single tool-calls at once!") }}
+        {%- endif %}
+        {%- set tool_call = message.tool_calls[0].function %}
+        {%- if builtin_tools is defined and tool_call.name in builtin_tools %}
+            {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
+            {{- "<|python_tag|>" + tool_call.name + ".call(" }}
+            {%- for arg_name, arg_val in tool_call.arguments | items %}
+                {{- arg_name + '="' + arg_val + '"' }}
+                {%- if not loop.last %}
+                    {{- ", " }}
+                {%- endif %}
+                {%- endfor %}
+            {{- ")" }}
+        {%- else  %}
+            {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
+            {{- '<function=' + tool_call.name + '>' + tool_call.arguments + '</function>'}}
+        {%- endif %}
+        {%- if builtin_tools is defined or tools is not none%}
+            {#- This means we're in ipython mode #}
+            {{- "<|eom_id|>" }}
+        {%- else %}
+            {{- "<|eot_id|>" }}
+        {%- endif %}
+    {%- elif message.role == "tool" or message.role == "ipython" %}
+        {{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
+        {%- if message.content is mapping or message.content is iterable %}
+            {{- message.content | tojson }}
+        {%- else %}
+            {{- message.content }}
+        {%- endif %}
+        {{- "<|eot_id|>" }}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
+{%- endif %}

vllm/entrypoints/openai/tool_parsers/__init__.py

@@ -9,10 +9,11 @@
 from .llama_tool_parser import Llama3JsonToolParser
 from .mistral_tool_parser import MistralToolParser
 from .pythonic_tool_parser import PythonicToolParser
+from .llama_usr_defined_tool_parser import Llama3UserDefinedCustomToolParser
 
 __all__ = [
     "ToolParser", "ToolParserManager", "Granite20bFCToolParser",
     "GraniteToolParser", "Hermes2ProToolParser", "MistralToolParser",
     "Internlm2ToolParser", "Llama3JsonToolParser", "JambaToolParser",
-    "PythonicToolParser"
+    "PythonicToolParser", "Llama3UserDefinedCustomToolParser"
 ]

vllm/entrypoints/openai/tool_parsers/llama_usr_defined_tool_parser.py

@@ -0,0 +1,248 @@
+# SPDX-License-Identifier: Apache-2.0
+
+import json
+import re
+from typing import Dict, List, Sequence, Union
+
+import partial_json_parser
+from partial_json_parser.core.options import Allow
+
+from vllm.entrypoints.openai.protocol import (ChatCompletionRequest,
+                                              DeltaFunctionCall, DeltaMessage,
+                                              DeltaToolCall,
+                                              ExtractedToolCallInformation,
+                                              FunctionCall, ToolCall)
+from vllm.entrypoints.openai.tool_parsers.abstract_tool_parser import (
+    ToolParser, ToolParserManager)
+from vllm.logger import init_logger
+from vllm.transformers_utils.tokenizer import AnyTokenizer, MistralTokenizer
+from vllm.utils import random_uuid
+
+logger = init_logger(__name__)
+
+def _count_substring(string, substring):
+        """
+        Counts the number of non-overlapping occurrences of a substring in a string.
+
+        Args:
+            string (str): The string to search in.
+            substring (str): The substring to search for.
+
+        Returns:
+            int: The number of non-overlapping occurrences of the substring in the string.
+        """
+        count = 0
+        start = 0
+        while True:
+            start = string.find(substring, start)
+            if start == -1:
+                break
+            count += 1
+            start += len(substring)
+        return count
+
+@ToolParserManager.register_module("llama3_user_defined_custom")
+class Llama3UserDefinedCustomToolParser(ToolParser):
+
+    def __init__(self, tokenizer: AnyTokenizer):
+        super().__init__(tokenizer)
+
+        if isinstance(self.model_tokenizer, MistralTokenizer):
+            logger.error(
+                "Detected Mistral tokenizer when using a Llama model")
+            self.model_tokenizer = self.model_tokenizer.tokenizer
+
+        self.prev_tool_call_arr: List[Dict] = []
+        self.streamed_args_for_tool: List[str] = []
+        self.is_parsing_toolcall = False
+
+        self.nb_tool_calls = 0
+        self.current_tool_name=""
+        self.current_tool_call_uuid=""
+        self.is_current_tool_name_sent = False
+        self.tool_call_start_token: str = "<function"
+        self.tool_call_precall_token: str = '>{"'
+        self.tool_call_end_token: str = "</function>"
+        self.bot_token = "<|python_tag|>"
+
+        self.tool_call_start_token_id = tokenizer.encode(self.tool_call_start_token,
+                                             add_special_tokens=False)
+
+        self.tool_call_end_token_id = tokenizer.encode(self.tool_call_end_token,
+                                             add_special_tokens=False)
+
+        self.tool_call_preargs_token_id = tokenizer.encode(self.tool_call_precall_token,
+                                             add_special_tokens=False)   
+
+        self.bot_token_id = tokenizer.encode(self.bot_token,
+                                             add_special_tokens=False)
+
+        self.tool_call_regex = re.compile(r"<function=([^>]+)>\{([^}]+)\}(?:</function>|>)?")
+
+        if not self.model_tokenizer:
+            raise ValueError(
+                "The model tokenizer must be passed to the ToolParser "
+                "constructor during construction.")
+
+    def extract_tool_calls(
+        self,
+        model_output: str,
+        request: ChatCompletionRequest,
+    ) -> ExtractedToolCallInformation:
+
+        # sanity check; avoid unnecessary processing
+        if self.tool_call_start_token not in model_output:
+            return ExtractedToolCallInformation(tools_called=False,
+                                                tool_calls=[],
+                                                content=model_output)
+
+        else:
+            try:
+                # there are two possible captures - between tags, or between a
+                # tag and end-of-string so the result of
+                # findall is an array of tuples where one is a function call and
+                # the other is None
+                function_call_tuples = self.tool_call_regex.findall(model_output)
+
+                logger.info("function_call_tuples: %s", function_call_tuples)
+                print("function_call_tuples: %s", function_call_tuples)
+
+                # load the JSON, and then use it to build the Function and
+                # Tool Call
+                raw_function_calls = [
+                    {
+                        "name":match[0],
+                        "arguments":json.loads("{"+match[1]+"}")
+                     } 
+                     for match in function_call_tuples
+                ]
+                tool_calls = [
+                    ToolCall(
+                        type="function",
+                        function=FunctionCall(
+                            name=function_call["name"],
+                            # function call args are JSON but as a string
+                            arguments=json.dumps(function_call["arguments"],
+                                                 ensure_ascii=False)))
+                    for function_call in raw_function_calls
+                ]
+
+                content = model_output[:model_output.
+                                       find(self.tool_call_start_token)]
+                return ExtractedToolCallInformation(
+                    tools_called=True,
+                    tool_calls=tool_calls,
+                    content=content if content else None)
+
+            except Exception:
+                logger.exception(
+                    "Error in extracting tool call from response.")
+                return ExtractedToolCallInformation(tools_called=False,
+                                                    tool_calls=[],
+                                                    content=model_output)
+
+
+    def extract_tool_calls_streaming(
+        self,
+        previous_text: str,
+        current_text: str,
+        delta_text: str,
+        previous_token_ids: Sequence[int],
+        current_token_ids: Sequence[int],
+        delta_token_ids: Sequence[int],
+        request: ChatCompletionRequest,
+    ) -> Union[DeltaMessage, None]:
+        """
+        Extract tool calls from a streaming response.
+        Handles format: <function=functionName{arguments}>
+        Returns DeltaMessage with either tool_calls or content.
+        """
+        logger.debug("\n" + "="*50)
+        logger.debug("STREAMING FUNCTION CALLED")
+        logger.debug("Tool call start token id IDs:", self.tool_call_start_token_id)
+        logger.debug("Tool call precall token id IDs:", self.tool_call_preargs_token_id)
+        logger.debug("Tool call end token id IDs:", self.tool_call_end_token_id)
+        logger.debug("Previous text:", previous_text)
+        logger.debug("Current text:", current_text)
+        logger.debug("Delta text:", delta_text)
+        logger.debug("Previous token IDs:", previous_token_ids)
+        logger.debug("Current token IDs:", current_token_ids)
+        logger.debug("Delta token IDs:", delta_token_ids)
+        logger.debug("Current tool name sent:", self.is_current_tool_name_sent)
+        logger.debug("-"*50 + "\n")
+        flags = Allow.ALL if self.is_current_tool_name_sent \
+                else Allow.ALL & ~Allow.STR
+
+        logger.debug(f"{delta_token_ids[0] in self.tool_call_start_token_id=}")
+        if delta_token_ids[0] in self.tool_call_start_token_id : 
+            # We possibly have a tool call (not sure yet) we don't stream
+
+            logger.debug(f"{_count_substring(current_text,self.tool_call_start_token)=}")
+            if _count_substring(current_text,self.tool_call_start_token) > self.nb_tool_calls \
+                and not self.is_parsing_toolcall :
+
+                self.is_parsing_toolcall=True
+                self.nb_tool_calls +=1 #will serve as id
+                self.current_tool_call_uuid = random_uuid()
+                logger.debug("New tool call detected, id:", self.nb_tool_calls-1)
+                return None # going to the next iter 
+            else : 
+                logger.debug("Tool call already parsed, id:", self.nb_tool_calls-1)
+
+        if self.is_parsing_toolcall and not self.is_current_tool_name_sent : 
+            logger.debug("Parsing tool call, id:", self.nb_tool_calls-1)
+            # We are parsing a tool call, we need to parse the tool name
+            if delta_token_ids != self.tool_call_preargs_token_id:
+                self.current_tool_name += delta_text
+                logger.debug(f"{self.current_tool_name=}")
+                return None # moving on to the next iteration
+            else : 
+                self.current_tool_name = self.current_tool_name.lstrip('=')
+                self.is_current_tool_name_sent = True
+                return DeltaMessage(tool_calls=[
+                    DeltaToolCall(index=self.nb_tool_calls - 1,
+                                    type="function",
+                                    id=f"chatcmpl-tool-{self.current_tool_call_uuid}",
+                                    function=DeltaFunctionCall(
+                                        name=self.current_tool_name))
+                ])
+
+        if self.is_current_tool_name_sent :
+            logger.debug("Parsed tool name : ", self.current_tool_name)
+
+            if _count_substring(current_text,self.tool_call_end_token) < self.nb_tool_calls:
+                self.streamed_args_for_tool.append(delta_text)
+                return None # moving on to the next iteration
+            else :
+                arguments = '{"'+''.join(self.streamed_args_for_tool) # adding back {" at the beginning for valid JSON
+                arguments = arguments.rstrip(self.tool_call_end_token) # removing the end token
+                logger.debug("Concatenated tool call arguments  : ", arguments)
+
+                current_tool_args = partial_json_parser.loads(
+                arguments or "{}",
+                flags) if self.streamed_args_for_tool else None
+
+                logger.debug("Parsed tool call arguments : ", current_tool_args)
+
+
+                delta = DeltaMessage(tool_calls=[
+                    DeltaToolCall(index=self.nb_tool_calls - 1,
+                                    type="function",
+                                    id=f"chatcmpl-tool-{self.current_tool_call_uuid}",
+                                    function=DeltaFunctionCall(
+                                        name=self.current_tool_name,
+                                        arguments=json.dumps(current_tool_args)))
+                ])
+
+                self.reset_state()
+
+                return delta 
+        else : 
+            logger.debug("No tool call detected, returning just text : ", delta_text)
+            return DeltaMessage(content=delta_text)
+
+    def reset_state(self):
+        self.current_tool_name = ''
+        self.is_parsing_toolcall=False
+        self.is_current_tool_name_sent = False
+        self.streamed_args_for_tool = []