diff --git a/examples/tool_chat_template_llama3.1_usr_def_tool_call.jinja b/examples/tool_chat_template_llama3.1_usr_def_tool_call.jinja
new file mode 100644
index 00000000000..07a118c6e76
--- /dev/null
+++ b/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 %}
\ No newline at end of file
diff --git a/vllm/entrypoints/openai/tool_parsers/__init__.py b/vllm/entrypoints/openai/tool_parsers/__init__.py
index b81dc4e7ad7..1d51fdcc4f1 100644
--- a/vllm/entrypoints/openai/tool_parsers/__init__.py
+++ b/vllm/entrypoints/openai/tool_parsers/__init__.py
@@ -7,6 +7,7 @@
 from .internlm2_tool_parser import Internlm2ToolParser
 from .jamba_tool_parser import JambaToolParser
 from .llama_tool_parser import Llama3JsonToolParser
+from .llama_usr_defined_tool_parser import Llama3UserDefinedCustomToolParser
 from .mistral_tool_parser import MistralToolParser
 from .phi4mini_tool_parser import Phi4MiniJsonToolParser
 from .pythonic_tool_parser import PythonicToolParser
@@ -15,5 +16,6 @@
     "ToolParser", "ToolParserManager", "Granite20bFCToolParser",
     "GraniteToolParser", "Hermes2ProToolParser", "MistralToolParser",
     "Internlm2ToolParser", "Llama3JsonToolParser", "JambaToolParser",
-    "PythonicToolParser", "Phi4MiniJsonToolParser"
+    "PythonicToolParser", "Llama3UserDefinedCustomToolParser",
+    "Phi4MiniJsonToolParser"
 ]
diff --git a/vllm/entrypoints/openai/tool_parsers/llama_usr_defined_tool_parser.py b/vllm/entrypoints/openai/tool_parsers/llama_usr_defined_tool_parser.py
new file mode 100644
index 00000000000..677c3a67c53
--- /dev/null
+++ b/vllm/entrypoints/openai/tool_parsers/llama_usr_defined_tool_parser.py
@@ -0,0 +1,268 @@
+# SPDX-License-Identifier: Apache-2.0
+
+import json
+import re
+from collections.abc import Sequence
+from typing import 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)
+        logger.debug("\n")
+        flags = Allow.ALL if self.is_current_tool_name_sent \
+                else Allow.ALL & ~Allow.STR
+
+        logger.debug("%s=", 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(
+                "%s=",
+                _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("self.current_tool_name=", 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:
+                # adding back {" at the beginning for valid JSON
+                arguments = '{"' + ''.join(self.streamed_args_for_tool)
+                # removing the end token
+                arguments = arguments.rstrip(self.tool_call_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 = []
diff --git a/vllm/v1/core/kv_cache_manager.py b/vllm/v1/core/kv_cache_manager.py
index 4e74c20d366..6c92bd4073d 100644
--- a/vllm/v1/core/kv_cache_manager.py
+++ b/vllm/v1/core/kv_cache_manager.py
@@ -154,11 +154,24 @@ def get_computed_blocks(
             # we shouldn't modify it directly.
             block_hashes.append(last_block_hash)
 
-        # NOTE(woosuk): Since incomplete blocks are not eligible for
-        # sharing, `num_computed_tokens` is always a multiple of
-        # `block_size`.
-        num_computed_tokens = len(computed_blocks) * self.block_size
-        return computed_blocks, num_computed_tokens
+            computed_blocks = (
+                self.specialized_manager.find_longest_cache_hit(block_hashes))
+
+            if last_block_hash is not None:
+                # Add back the last block hash if it was removed.
+                block_hashes.append(last_block_hash)
+
+            self.prefix_cache_stats.queries += len(block_hashes)
+            self.prefix_cache_stats.hits += len(computed_blocks)
+
+            # NOTE(woosuk): Since incomplete blocks are not eligible for
+            # sharing, `num_computed_tokens` is always a multiple of
+            # `block_size`.
+            num_computed_tokens = len(computed_blocks) * self.block_size
+            return computed_blocks, num_computed_tokens
+        else:
+            # Skip cache hits for prompt logprobs
+            return [], 0
 
     def allocate_slots(
         self,