diff --git a/operators/tokenizer/tokenizer_jsconfig.hpp b/operators/tokenizer/tokenizer_jsconfig.hpp
index d1bf6bac..70f67080 100644
--- a/operators/tokenizer/tokenizer_jsconfig.hpp
+++ b/operators/tokenizer/tokenizer_jsconfig.hpp
@@ -70,6 +70,7 @@ class TokenJsonConfig final {
       bos_token_ = "<s>";
       eos_token_ = "</s>";
       unk_token_ = "<unk>";
+      chat_template_ = ""; // can add default chat template
       return {};
     }
 
@@ -90,6 +91,8 @@ class TokenJsonConfig final {
     parse_token(json_config, "eos_token", eos_token_);
     parse_token(json_config, "unk_token", unk_token_);
 
+    parse_token(json_config, "chat_template", chat_template_);
+
     auto pad_iter = json_config.find("pad_token");
     if (pad_iter != json_config.end() && pad_iter->is_string()) {
       pad_token_ = json_config.value("pad_token", "");
@@ -244,6 +247,8 @@ class TokenJsonConfig final {
   std::string unk_token_;
   std::string pad_token_;
 
+  std::string chat_template_;
+
   AddedTokenMap added_tokens_;
 
   static AddedToken ParseAddedToken(const json& token) {
diff --git a/shared/api/tokenizer_impl.cc b/shared/api/tokenizer_impl.cc
index fe7d6440..e1a37310 100644
--- a/shared/api/tokenizer_impl.cc
+++ b/shared/api/tokenizer_impl.cc
@@ -87,6 +87,8 @@ OrtxStatus TokenizerImpl::Load(const std::string& tok_path) {
     return status;
   }
 
+  chat_template = tok_config_->chat_template_;
+  
   return LoadTokenizer();
 }
 
@@ -131,6 +133,615 @@ OrtxStatus TokenizerImpl::BatchDecode(const std::vector<span<extTokenId_t const>
   return {};
 }
 
+// Constant string variable to store predefined chat template strings for popular supported models
+const std::string PHI_VISION_CHAT_TEMPLATE = R"({% for message in messages %}{{'<|' + message['role'] + '|>' + '\n' + message['content'] + '<|end|>\n' }}{% endfor %}{% if add_generation_prompt and messages[-1]['role'] != 'assistant' %}{{- '<|assistant|>\n' -}}{% endif %})";
+const std::string PHI3_CHAT_TEMPLATE = R"({% for message in messages %}{% if message['role'] == 'system' %}{{'<|system|>\n' + message['content'] + '<|end|>\n'}}{% elif message['role'] == 'user' %}{{'<|user|>\n' + message['content'] + '<|end|>\n'}}{% elif message['role'] == 'assistant' %}{{'<|assistant|>\n' + message['content'] + '<|end|>\n'}}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|assistant|>\n' }}{% else %}{{ eos_token }}{% endif %})";
+const std::string PHI3_SMALL_CHAT_TEMPLATE = R"({{ bos_token }}{% for message in messages %}{{'<|' + message['role'] + '|>' + '\n' + message['content'] + '<|end|>\n' }}{% endfor %}{% if add_generation_prompt %}{{ '<|assistant|>\n' }}{% else %}{{ eos_token }}{% endif %})";
+const std::string PHI3_MEDIUM_CHAT_TEMPLATE = R"({% for message in messages %}{% if (message['role'] == 'user') %}{{'<|user|>' + '\n' + message['content'] + '<|end|>' + '\n' + '<|assistant|>' + '\n'}}{% elif (message['role'] == 'assistant') %}{{message['content'] + '<|end|>' + '\n'}}{% endif %}{% endfor %})";
+const std::string PHI3_5_CHAT_TEMPLATE = R"({% for message in messages %}{% if message['role'] == 'system' and message['content'] %}{{'<|system|>\n' + message['content'] + '<|end|>\n'}}{% elif message['role'] == 'user' %}{{'<|user|>\n' + message['content'] + '<|end|>\n'}}{% elif message['role'] == 'assistant' %}{{'<|assistant|>\n' + message['content'] + '<|end|>\n'}}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|assistant|>\n' }}{% else %}{{ eos_token }}{% endif %})";
+const std::string PHI4_CHAT_TEMPLATE = R"({% for message in messages %}{% if message['role'] == 'system' and 'tools' in message and message['tools'] is not none %}{{ '<|' + message['role'] + '|>' + message['content'] + '<|tool|>' + message['tools'] + '<|/tool|>' + '<|end|>' }}{% else %}{{ '<|' + message['role'] + '|>' + message['content'] + '<|end|>' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|assistant|>' }}{% else %}{{ eos_token }}{% endif %})";
+const std::string LLAMA2_CHAT_TEMPLATE = R"({% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<<SYS>>\\n' + system_message + '\\n<</SYS>>\\n\\n' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ bos_token + '[INST] ' + content.strip() + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ ' '  + content.strip() + ' ' + eos_token }}{% endif %}{% endfor %})";
+const std::string LLAMA3_CHAT_TEMPLATE = R"({% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}{% endif %})";
+const std::string LLAMA3_2_CHAT_TEMPLATE = R"({{- bos_token }}\n{%- if custom_tools is defined %}\n    {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n    {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n    {%- if strftime_now is defined %}\n        {%- set date_string = strftime_now(\"%d %b %Y\") %}\n    {%- else %}\n        {%- set date_string = \"26 Jul 2024\" %}\n    {%- endif %}\n{%- endif %}\n{%- if not tools is defined %}\n    {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n    {%- set system_message = messages[0]['content']|trim %}\n    {%- set messages = messages[1:] %}\n{%- else %}\n    {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if tools is not none %}\n    {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n    {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\\n\\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n    {#- Extract the first user message so we can plug it in here #}\n    {%- if messages | length != 0 %}\n        {%- set first_user_message = messages[0]['content']|trim %}\n        {%- set messages = messages[1:] %}\n    {%- else %}\n        {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n    {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n    {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n    {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\\n\\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n    {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n    {%- elif 'tool_calls' in message %}\n        {%- if not message.tool_calls|length == 1 %}\n            {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n        {%- endif %}\n        {%- set tool_call = message.tool_calls[0].function %}\n        {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n        {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n        {{- '\"parameters\": ' }}\n        {{- tool_call.arguments | tojson }}\n        {{- \"}\" }}\n        {{- \"<|eot_id|>\" }}\n    {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n        {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n        {%- if message.content is mapping or message.content is iterable %}\n            {{- message.content | tojson }}\n        {%- else %}\n            {{- message.content }}\n        {%- endif %}\n        {{- \"<|eot_id|>\" }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n)";
+const std::string LLAMA3_3_CHAT_TEMPLATE = R"({{- bos_token }}\n{%- if custom_tools is defined %}\n    {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n    {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n    {%- set date_string = \"26 Jul 2024\" %}\n{%- endif %}\n{%- if not tools is defined %}\n    {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n    {%- set system_message = messages[0]['content']|trim %}\n    {%- set messages = messages[1:] %}\n{%- else %}\n    {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message + builtin tools #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if builtin_tools is defined or tools is not none %}\n    {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{%- if builtin_tools is defined %}\n    {{- \"Tools: \" + builtin_tools | reject('equalto', 'code_interpreter') | join(\", \") + \"\\n\\n\"}}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n    {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\\n\\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n    {#- Extract the first user message so we can plug it in here #}\n    {%- if messages | length != 0 %}\n        {%- set first_user_message = messages[0]['content']|trim %}\n        {%- set messages = messages[1:] %}\n    {%- else %}\n        {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n    {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n    {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n    {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\\n\\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n    {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n    {%- elif 'tool_calls' in message %}\n        {%- if not message.tool_calls|length == 1 %}\n            {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n        {%- endif %}\n        {%- set tool_call = message.tool_calls[0].function %}\n        {%- if builtin_tools is defined and tool_call.name in builtin_tools %}\n            {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n            {{- \"<|python_tag|>\" + tool_call.name + \".call(\" }}\n            {%- for arg_name, arg_val in tool_call.arguments | items %}\n                {{- arg_name + '=\"' + arg_val + '\"' }}\n                {%- if not loop.last %}\n                    {{- \", \" }}\n                {%- endif %}\n                {%- endfor %}\n            {{- \")\" }}\n        {%- else  %}\n            {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n            {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n            {{- '\"parameters\": ' }}\n            {{- tool_call.arguments | tojson }}\n            {{- \"}\" }}\n        {%- endif %}\n        {%- if builtin_tools is defined %}\n            {#- This means we're in ipython mode #}\n            {{- \"<|eom_id|>\" }}\n        {%- else %}\n            {{- \"<|eot_id|>\" }}\n        {%- endif %}\n    {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n        {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n        {%- if message.content is mapping or message.content is iterable %}\n            {{- message.content | tojson }}\n        {%- else %}\n            {{- message.content }}\n        {%- endif %}\n        {{- \"<|eot_id|>\" }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n)";
+const std::string DEEPSEEK_CHAT_TEMPLATE = R"({% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<｜User｜>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<｜Assistant｜><｜tool▁calls▁begin｜><｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{%- set ns.is_first = true -%}{%- else %}{{'\\n' + '<｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{{'<｜tool▁calls▁end｜><｜end▁of▁sentence｜>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<｜tool▁outputs▁end｜>' + message['content'] + '<｜end▁of▁sentence｜>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{{'<｜Assistant｜>' + content + '<｜end▁of▁sentence｜>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<｜tool▁outputs▁begin｜><｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\\n<｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<｜tool▁outputs▁end｜>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<｜Assistant｜><think>\\n'}}{% endif %})";
+
+// Member variable to store the messages
+std::vector<std::unordered_map<std::string, std::string>> messages;
+    
+// Member variable to store the chat_template (customized for each instance)
+std::string chat_template;
+
+OrtxStatus TokenizerImpl::PhiVisionChatTemplate(std::string* output, bool add_generation_prompt = true) {
+
+  // Clear the output string before starting
+  output->clear();
+
+  // Iterate over the messages
+  for (const auto& message : messages) {
+      std::string role = message.at("role");
+      std::string content = message.at("content");
+
+      // Format the message according to the role
+      *output += "<|" + role + "|>\n" + content + "<|end|>\n";
+  }
+
+  // Check if a generation prompt is needed and the last message isn't from the assistant
+  if (add_generation_prompt && messages.back().at("role") != "assistant") {
+      *output += "<|assistant|>\n";
+  }
+
+  return OrtxStatus(kOrtxOK, "Created Phi vision chat template.");
+}
+
+// Note Phi-3 and Phi-3.5 have slightly different chat template strings but share the same functionality so this method can be used for both.
+OrtxStatus TokenizerImpl::Phi3ChatTemplate(std::string* output, bool add_generation_prompt = true, const std::string& eos_token = "<|endoftext|>") {
+  // Clear the output string before starting
+  output->clear();
+
+  // Process the messages
+  for (const auto& message : messages) {
+      std::string role = message.at("role");
+      std::string content = message.at("content");
+
+      // Check for different roles and format accordingly
+      if (role == "system" && !content.empty()) {
+          *output += "<|system|>\n";
+          *output += content + "<|end|>\n";
+      } else if (role == "user") {
+          *output += "<|user|>\n";
+          *output += content + "<|end|>\n";
+      } else if (role == "assistant") {
+          *output += "<|assistant|>\n";
+          *output += content + "<|end|>\n";
+      }
+  }
+
+  // Add generation prompt or EOS token
+  if (add_generation_prompt) {
+      *output += "<|assistant|>\n";
+  } else {
+      *output += eos_token;
+  }
+
+  return OrtxStatus(kOrtxOK, "Created Phi-3/3.5 chat template.");
+}
+
+OrtxStatus TokenizerImpl::Phi3SmallChatTemplate(std::string* output, bool add_generation_prompt = true, const std::string& eos_token = "<|endoftext|>", const std::string& bos_token = "<|startoftext|>") {
+
+  // Clear the output string before starting
+  output->clear();
+
+  // Add the beginning-of-sequence token
+  *output += bos_token;
+
+  // Iterate over the messages
+  for (const auto& message : messages) {
+      std::string role = message.at("role");
+      std::string content = message.at("content");
+
+      // Format the message according to the role
+      *output += "<|" + role + "|>\n" + content + "<|end|>\n";
+  }
+
+  // Add the generation prompt or eos_token
+  if (add_generation_prompt) {
+      *output += "<|assistant|>\n";
+  } else {
+      *output += eos_token;
+  }
+
+  return OrtxStatus(kOrtxOK, "Created Phi-3-small chat template.");
+}
+
+OrtxStatus TokenizerImpl::Phi3MediumChatTemplate(std::string* output) {
+  // Clear the output string before starting
+  output->clear();
+
+  // Process the messages
+  for (const auto& message : messages) {
+      std::string role = message.at("role");
+      std::string content = message.at("content");
+
+      // Format based on role (user/assistant)
+      if (role == "user") {
+          *output += "<|user|>\n" + content + "<|end|>\n<|assistant|>\n";
+      } else if (role == "assistant") {
+          *output += content + "<|end|>\n";
+      }
+  }
+
+  return OrtxStatus(kOrtxOK, "Created Phi-3-medium chat template.");
+}
+
+OrtxStatus TokenizerImpl::Phi4ChatTemplate(std::string* output, bool add_generation_prompt = true, const std::string& eos_token = "<|endoftext|>") {
+  // Clear the output string before starting
+  output->clear();
+
+  // Process the messages
+  for (const auto& message : messages) {
+      std::string role = message.at("role");
+      std::string content = message.at("content");
+
+      // Check if "tools" is present in the message and is not empty for "system" role
+      if (role == "system" && message.find("tools") != message.end() && !message.at("tools").empty()) {
+          std::string tools = message.at("tools");
+          *output += "<|" + role + "|>";
+          *output += content + "<|tool|>" + tools + "<|/tool|>" + "<|end|>";
+      } else {
+          // For other messages, no tools
+          *output += "<|" + role + "|>";
+          *output += content + "<|end|>";
+      }
+  }
+
+  // Add generation prompt or eos_token
+  if (add_generation_prompt) {
+      *output += "<|assistant|>";
+  } else {
+      *output += eos_token;
+  }
+
+  return OrtxStatus(kOrtxOK, "Created Phi-4 chat template.");
+}
+
+OrtxStatus TokenizerImpl::Llama2ChatTemplate(
+  std::string* output,
+  bool add_generation_prompt = true,
+  const std::string& eos_token = "</s>",
+  const std::string& bos_token = "<s>") {
+
+  // Clear the output string before starting
+  output->clear();
+
+  // Initialize system message and process it
+  bool system_message_exists = false;
+  std::string system_message = "";
+
+  if (!messages.empty() && messages[0].at("role") == "system") {
+      system_message = messages[0].at("content");
+      system_message_exists = true;
+  }
+
+  // If system message exists, we start processing from the second message
+  size_t start_index = system_message_exists ? 1 : 0;
+
+  // Iterate over the messages to construct the template
+  for (size_t i = start_index; i < messages.size(); ++i) {
+      const auto& message = messages[i];
+      std::string role = message.at("role");
+      std::string content = message.at("content");
+
+      // Check if the conversation roles alternate between user and assistant
+      if ((role == "user") != (i % 2 == start_index % 2)) {
+          return OrtxStatus(kOrtxErrorInvalidArgument, "Conversation roles must alternate user/assistant/user/assistant...");
+      }
+
+      // Handle system message by prepending it to the first assistant's message
+      std::string formatted_content;
+      if (i == start_index && system_message_exists) {
+          formatted_content = "<<SYS>>\n" + system_message + "\n<</SYS>>\n\n" + content;
+      } else {
+          formatted_content = content;
+      }
+
+      // Add the appropriate markers for user and assistant roles
+      if (role == "user") {
+          *output += bos_token + "[INST] " + formatted_content + " [/INST]";
+      } else if (role == "assistant") {
+          *output += " " + formatted_content + " " + eos_token;
+      }
+  }
+
+  return OrtxStatus(kOrtxOK, "Created Llama 2 chat template.");
+}
+
+OrtxStatus TokenizerImpl::Llama3ChatTemplate(
+  std::string* output,
+  bool add_generation_prompt = true,
+  const std::string& eos_token = "<|eot_id|>",
+  const std::string& bos_token = "<|begin_of_text|>") {
+
+  // Clear the output string before starting
+  output->clear();
+
+  // Iterate over the messages to construct the template
+  for (size_t i = 0; i < messages.size(); ++i) {
+      const auto& message = messages[i];
+      std::string role = message.at("role");
+      std::string content = message.at("content");
+
+      // Build the message with header and content
+      std::string formatted_content = "<|start_header_id|>" + role + "<|end_header_id|>\n\n" + content + eos_token;
+
+      // Add BOS token only to the first message
+      if (i == 0) {
+          formatted_content = bos_token + formatted_content;
+      }
+
+      // Append the formatted message to the output
+      *output += formatted_content;
+  }
+
+  // Add generation prompt or eos_token at the end
+  if (add_generation_prompt) {
+      *output += "<|start_header_id|>assistant<|end_header_id|>\n\n";
+  } else {
+      *output += eos_token;
+  }
+
+  return OrtxStatus(kOrtxOK, "Created Llama 3 chat template.");
+}
+
+OrtxStatus TokenizerImpl::Llama3_2ChatTemplate(
+  std::string* output, 
+  bool add_generation_prompt = true, 
+  const std::string& eos_token = "<|eot_id|>", 
+  const std::vector<std::string>& custom_tools = {}, 
+  bool tools_in_user_message = true, 
+  const std::string& strftime_now = "",
+  const std::string& bos_token = "<|begin_of_text|>") {
+
+  // Clear the output string before starting
+  output->clear();
+
+  // Prepend BOS token at the start of the output
+  *output += bos_token;
+
+  // Initialize date_string with default value
+  std::string date_string = "26 Jul 2024";  // Default date
+  if (!strftime_now.empty()) {
+      date_string = strftime_now;  // Override with provided date string if available
+  }
+
+  // Loop through messages and process each one
+  for (const auto& message : messages) {
+      std::string role = message.at("role");
+      std::string content = message.at("content");
+
+      // Handle the system message
+      if (role == "system") {
+          *output += "<|start_header_id|>system<|end_header_id|>\n\n";
+          *output += "Cutting Knowledge Date: December 2023\n";
+          *output += "Today Date: " + date_string + "\n\n";
+
+          // Check if tools exist and append relevant information
+          if (!custom_tools.empty()) {
+              *output += "You have access to the following functions. To call a function, please respond with JSON for a function call.\n";
+              *output += "Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value.}\n";
+              *output += "Do not use variables.\n\n";
+
+              // Convert tools to JSON (assuming custom_tools is a vector of tool names as strings)
+              nlohmann::json tools_json = nlohmann::json::array();
+              for (const auto& tool : custom_tools) {
+                  tools_json.push_back(tool);
+              }
+
+              *output += tools_json.dump(4) + "\n\n";
+          }
+      }
+
+      // Handle user message with tools in it
+      if (tools_in_user_message && message.find("tool_calls") != message.end()) {
+          // Parse the tool_calls string into JSON (assuming it's a valid JSON string)
+          nlohmann::json tool_calls_json = nlohmann::json::parse(message.at("tool_calls"));
+
+          if (tool_calls_json.size() != 1) {
+              // Handle multiple tool calls (not supported)
+              return OrtxStatus(kOrtxErrorInvalidArgument, "This model only supports single tool-calls at once!");
+          }
+
+          // Extract the function name and arguments from the first tool call
+          std::string function_name = tool_calls_json[0]["function"];
+          nlohmann::json arguments = tool_calls_json[0]["arguments"];
+
+          // Create the JSON object for the tool call
+          nlohmann::json tool_call_json;
+          tool_call_json["name"] = function_name;
+          tool_call_json["parameters"] = arguments;
+
+          // Serialize the tool call as JSON and append it to output
+          *output += "<|start_header_id|>assistant<|end_header_id|>\n\n";
+          *output += tool_call_json.dump();
+          *output += eos_token;  // End of tool call
+      }
+
+      // Handle other messages (user, assistant, etc.)
+      else {
+          if (role != "system") {
+            *output += "<|start_header_id|>" + role + "<|end_header_id|>\n\n";
+          }
+          *output += content;
+          *output += eos_token;
+      }
+  }
+
+  // Add generation prompt or eos_token at the end
+  if (add_generation_prompt) {
+      *output += "<|start_header_id|>assistant<|end_header_id|>\n\n";
+  } else {
+      *output += eos_token;
+  }
+
+  return OrtxStatus(kOrtxOK, "Created Llama 3.2 chat template.");
+}
+
+OrtxStatus TokenizerImpl::Llama3_3ChatTemplate(
+  std::string* output,
+  bool add_generation_prompt = true,
+  const std::string& eos_token = "<|eot_id|>",
+  const std::vector<std::string>& custom_tools = {},
+  const std::vector<std::string>& builtin_tools = {},
+  bool tools_in_user_message = true,
+  const std::string& date_string = "26 Jul 2024",
+  const std::string& bos_token = "<|begin_of_text|>") {
+
+  // Clear the output string before starting
+  output->clear();
+
+  // Prepend BOS token at the start of the output
+  *output += bos_token;
+
+  // Loop through messages and process each one
+  for (const auto& message : messages) {
+      std::string role = message.at("role");
+      std::string content = message.at("content");
+
+      // Handle the system message
+      if (role == "system") {
+          *output += "<|start_header_id|>system<|end_header_id|>\n\n";
+          *output += "Cutting Knowledge Date: December 2023\n";
+          *output += "Today Date: " + date_string + "\n\n";
+
+          // Check if builtin_tools or custom_tools exist and append relevant information
+          if (!builtin_tools.empty() || !custom_tools.empty()) {
+              *output += "Environment: ipython\n";
+          }
+
+          // Add builtin tools if defined (excluding 'code_interpreter')
+          if (!builtin_tools.empty()) {
+              *output += "Tools: ";
+              bool first = true;
+              for (const auto& tool : builtin_tools) {
+                  if (tool != "code_interpreter") {
+                      if (!first) {
+                          *output += ", ";
+                      }
+                      *output += tool;
+                      first = false;
+                  }
+              }
+              *output += "\n\n";
+          }
+
+          // Add the tools section if custom tools are provided
+          if (!custom_tools.empty()) {
+              *output += "You have access to the following functions. To call a function, please respond with JSON for a function call.\n";
+              *output += "Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.\n";
+              *output += "Do not use variables.\n\n";
+
+              // Convert custom_tools to JSON
+              nlohmann::json tools_json = nlohmann::json::array();
+              for (const auto& tool : custom_tools) {
+                  tools_json.push_back(tool);
+              }
+              *output += tools_json.dump(4) + "\n\n";
+          }
+      }
+
+      // Handle user message with tools in it
+      if (tools_in_user_message && message.find("tool_calls") != message.end()) {
+          // Parse the tool_calls string into JSON
+          nlohmann::json tool_calls_json = nlohmann::json::parse(message.at("tool_calls"));
+
+          if (tool_calls_json.size() != 1) {
+              // Handle multiple tool calls (not supported)
+              return OrtxStatus(kOrtxErrorInvalidArgument, "This model only supports single tool-calls at once!");
+          }
+
+          // Extract the function name and arguments from the first tool call
+          std::string function_name = tool_calls_json[0]["function"];
+          nlohmann::json arguments = tool_calls_json[0]["arguments"];
+
+          // Create the JSON object for the tool call
+          nlohmann::json tool_call_json;
+          tool_call_json["name"] = function_name;
+          tool_call_json["parameters"] = arguments;
+
+          // If the tool is a built-in tool, use the specific format for ipython
+          bool is_builtin_tool = std::find(builtin_tools.begin(), builtin_tools.end(), function_name) != builtin_tools.end();
+          if (is_builtin_tool) {
+              *output += "<|start_header_id|>assistant<|end_header_id|>\n\n";
+              *output += "<|python_tag|>" + function_name + ".call(";
+              bool first = true;
+              for (auto& [arg_name, arg_val] : arguments.items()) {
+                  if (!first) {
+                      *output += ", ";
+                  }
+                  *output += arg_name + "=\"" + arg_val.get<std::string>() + "\"";
+                  first = false;
+              }
+              *output += ")";
+          } else {
+              *output += "<|start_header_id|>assistant<|end_header_id|>\n\n";
+              *output += tool_call_json.dump();
+          }
+
+          if (!builtin_tools.empty()) {
+              *output += "<|eom_id|>";
+          } else {
+              *output += eos_token;
+          }
+      }
+
+      // Handle other messages (user, assistant, etc.)
+      else {
+          if (role != "system") {
+            *output += "<|start_header_id|>" + role + "<|end_header_id|>\n\n";
+          }
+          *output += content;
+          *output += eos_token;
+      }
+  }
+
+  // Add generation prompt or eos_token at the end
+  if (add_generation_prompt) {
+      *output += "<|start_header_id|>assistant<|end_header_id|>\n\n";
+  } else {
+      *output += eos_token;
+  }
+
+  return OrtxStatus(kOrtxOK, "Created Llama 3.1/3.3 chat template."); // Llama 3.1 and 3.3 have the same chat template
+}
+
+OrtxStatus TokenizerImpl::DeepSeekChatTemplate(
+  std::string* output, 
+  bool add_generation_prompt = false, 
+  const std::string& eos_token = "<｜end▁of▁sentence｜>",
+  const std::string& bos_token = "<｜begin▁of▁sentence｜>") {
+
+  // Clear the output string before starting
+  output->clear();
+
+  // Initialize the namespace for template variables
+  bool is_first = true;  // Track the first occurrence of the tool call or assistant message
+  bool is_tool = false;
+  bool is_output_first = true;
+  std::string system_prompt = "";
+
+  // Prepend BOS token at the start of the output
+  *output += bos_token;
+
+  // Loop through messages and process each one
+  for (const auto& message : messages) {
+      std::string role = message.at("role");
+      std::string content = message.at("content");
+
+      // Handle the system message
+      if (role == "system") {
+          system_prompt = content;
+      }
+  }
+
+  *output += system_prompt;  // Add system prompt to the output
+
+  // Process each message in the conversation
+  for (const auto& message : messages) {
+      std::string role = message.at("role");
+      std::string content = message.at("content");
+
+      // Handle user message
+      if (role == "user") {
+          is_tool = false;
+          *output += "<｜User｜>" + content;
+      }
+
+      // Handle assistant message with tool calls
+      if (role == "assistant" && message.find("tool_calls") != message.end()) {
+          is_tool = false;
+
+          // Parse the tool_calls string into JSON
+          nlohmann::json tool_calls_json = nlohmann::json::parse(message.at("tool_calls"));
+
+          if (tool_calls_json.size() != 1) {
+              // Handle multiple tool calls (not supported)
+              return OrtxStatus(kOrtxErrorInvalidArgument, "This model only supports single tool-calls at once!");
+          }
+
+          // Extract the function name and arguments from the first tool call
+          std::string function_name = tool_calls_json[0]["function"];
+          nlohmann::json arguments = tool_calls_json[0]["arguments"];
+
+          // Create the JSON object for the tool call
+          nlohmann::json tool_call_json;
+          tool_call_json["name"] = function_name;
+          tool_call_json["parameters"] = arguments;
+
+          // Handle the first tool call differently
+          if (is_first) {
+              *output += "<｜Assistant｜><｜tool_calls_begin｜><｜tool_call_begin｜>" + tool_calls_json[0]["type"].get<std::string>() + "<｜tool_sep｜>" + tool_calls_json[0]["function"]["name"].get<std::string>() + "\njson\n" + tool_calls_json[0]["function"]["arguments"].dump() + "\n<｜tool_call_end｜>";
+              is_first = false;  // Mark as first tool call processed
+          } else {
+              // Subsequent tool calls
+              *output += "\n<｜tool_call_begin｜>" + tool_calls_json[0]["type"].get<std::string>() + "<｜tool_sep｜>" + tool_calls_json[0]["function"]["name"].get<std::string>() + "\njson\n" + tool_calls_json[0]["function"]["arguments"].dump() + "\n<｜tool_call_end｜>";
+          }
+
+          *output += "<｜tool_calls_end｜>";
+          *output += eos_token;
+      }
+
+      // Handle assistant message without tool calls
+      if (role == "assistant" && !content.empty()) {
+          if (is_tool) {
+              *output += "<｜tool_outputs_end｜>" + content;
+              *output += eos_token;
+              is_tool = false;
+          } else {
+              *output += "<｜Assistant｜>" + content;
+              *output += eos_token;
+          }
+      }
+
+      // Handle tool messages
+      if (role == "tool") {
+          is_tool = true;
+          if (is_output_first) {
+              *output += "<｜tool_outputs_begin｜><｜tool_output_begin｜>" + content + "<｜tool_output_end｜>";
+              is_output_first = false;
+          } else {
+              *output += "\n<｜tool_output_begin｜>" + content + "<｜tool_output_end｜>";
+          }
+      }
+  }
+
+  // If still in a tool message, close it
+  if (is_tool) {
+      *output += "<｜tool_outputs_end｜>";
+  }
+
+  // Add generation prompt or eos_token at the end
+  if (add_generation_prompt && !is_tool) {
+      *output += "<｜Assistant｜><think>\n";
+  } else {
+      *output += eos_token;
+  }
+
+  return OrtxStatus(kOrtxOK, "Created DeepSeek chat template.");
+}
+
+// ApplyChatTemplate method to choose the template logic based on chat_template
+OrtxStatus TokenizerImpl::ApplyChatTemplate(std::vector<std::unordered_map<std::string, std::string>> message_list, std::string* output, bool add_generation_prompt = true) {
+    
+  // Initialize messages
+  messages = message_list;
+
+  // Check if the chat_template matches any of the supported template strings and if so apply the corresponding template.
+  if (chat_template == PHI4_CHAT_TEMPLATE) {
+    return Phi4ChatTemplate(output, add_generation_prompt);
+  } else if (chat_template == PHI3_CHAT_TEMPLATE || chat_template == PHI3_5_CHAT_TEMPLATE) {
+    return Phi3ChatTemplate(output, add_generation_prompt);
+  } else if (chat_template == PHI3_SMALL_CHAT_TEMPLATE) {
+    return Phi3SmallChatTemplate(output, add_generation_prompt);
+  } else if (chat_template == PHI3_MEDIUM_CHAT_TEMPLATE) {
+    return Phi3MediumChatTemplate(output);
+  } else if (chat_template == PHI_VISION_CHAT_TEMPLATE) {
+    return PhiVisionChatTemplate(output, add_generation_prompt);
+  } else if (chat_template == LLAMA2_CHAT_TEMPLATE) {
+    return Llama2ChatTemplate(output, add_generation_prompt);
+  } else if (chat_template == LLAMA3_CHAT_TEMPLATE) {
+    return Llama3ChatTemplate(output, add_generation_prompt);
+  } else if (chat_template == LLAMA3_2_CHAT_TEMPLATE) {
+    return Llama3_2ChatTemplate(output, add_generation_prompt);
+  } else if (chat_template == LLAMA3_3_CHAT_TEMPLATE) {
+    return Llama3_3ChatTemplate(output, add_generation_prompt);
+  } else if (chat_template == DEEPSEEK_CHAT_TEMPLATE) {
+    return DeepSeekChatTemplate(output, add_generation_prompt);
+  } else {
+      // Handle other templates or custom logic here
+      return OrtxStatus(kOrtxErrorNotImplemented, "The provided chat template is currently not supported. Custom template handling needed.");
+  }
+}
+
 OrtxStatus TokenizerImpl::Id2Token(extTokenId_t id, std::string& token, TokenizerDecodingState** state) const {
   return std::visit([&](auto& detokenizer) {
     return detokenizer->Id2Token(id, token, state); }, detokenizer_);
diff --git a/shared/api/tokenizer_impl.h b/shared/api/tokenizer_impl.h
index 395d2cb7..7691f411 100644
--- a/shared/api/tokenizer_impl.h
+++ b/shared/api/tokenizer_impl.h
@@ -30,6 +30,8 @@ class TokenizerImpl : public OrtxObjectImpl {
     return BatchDecode(t_ids, t_text);
   }
 
+
+
   OrtxStatus Token2Id(const std::string& token, extTokenId_t& id) const {
     id = std::visit([&](auto& tokenizer) { return tokenizer->GetTokenId(token); }, tokenizer_);
     return {};
@@ -52,6 +54,43 @@ class TokenizerImpl : public OrtxObjectImpl {
 
   OrtxStatus BatchDecode(const std::vector<span<extTokenId_t const>>& t_ids, std::vector<std::string>& t_text) const;
 
+  const std::string PHI_VISION_CHAT_TEMPLATE;
+  const std::string PHI3_CHAT_TEMPLATE;
+  const std::string PHI3_SMALL_CHAT_TEMPLATE;
+  const std::string PHI3_MEDIUM_CHAT_TEMPLATE;
+  const std::string PHI3_5_CHAT_TEMPLATE;
+  const std::string PHI4_CHAT_TEMPLATE;
+  const std::string LLAMA2_CHAT_TEMPLATE;
+  const std::string LLAMA3_CHAT_TEMPLATE;
+  const std::string LLAMA3_2_CHAT_TEMPLATE;
+  const std::string LLAMA3_3_CHAT_TEMPLATE;
+  const std::string DEEPSEEK_CHAT_TEMPLATE;
+
+  std::string chat_template;
+  std::vector<std::unordered_map<std::string, std::string>> messages;
+
+  OrtxStatus PhiVisionChatTemplate(std::string* output, bool add_generation_prompt);
+  
+  OrtxStatus Phi3ChatTemplate(std::string* output, bool add_generation_prompt, const std::string& eos_token);
+
+  OrtxStatus Phi3SmallChatTemplate(std::string* output, bool add_generation_prompt, const std::string& eos_token, const std::string& bos_token);
+
+  OrtxStatus Phi3MediumChatTemplate(std::string* output);
+  
+  OrtxStatus Phi4ChatTemplate(std::string* output, bool add_generation_prompt, const std::string& eos_token);
+  
+  OrtxStatus Llama2ChatTemplate(std::string* output, bool add_generation_prompt, const std::string& eos_token, const std::string& bos_token);
+
+  OrtxStatus Llama3ChatTemplate(std::string* output, bool add_generation_prompt, const std::string& eos_token, const std::string& bos_token);
+
+  OrtxStatus Llama3_2ChatTemplate(std::string* output, bool add_generation_prompt, const std::string& eos_token, const std::vector<std::string>& custom_tools, bool tools_in_user_message, const std::string& strftime_now, const std::string& bos_token);
+
+  OrtxStatus Llama3_3ChatTemplate(std::string* output, bool add_generation_prompt, const std::string& eos_token, const std::vector<std::string>& custom_tools, const std::vector<std::string>& builtin_tools, bool tools_in_user_message, const std::string& date_string, const std::string& bos_token);
+  
+  OrtxStatus DeepSeekChatTemplate(std::string* output, bool add_generation_prompt, const std::string& eos_token, const std::string& bos_token);
+  
+  OrtxStatus ApplyChatTemplate(std::vector<std::unordered_map<std::string, std::string>> messages, std::string* output, bool add_generation_prompt);
+
   OrtxStatus Id2Token(extTokenId_t id, std::string& token, TokenizerDecodingState** state) const;
 
   OrtxStatus GetDecoderPromptIds(size_t batch_size, const char* lang, const char* task, int no_timestamps,
diff --git a/test/pp_api_test/test_tokenizer.cc b/test/pp_api_test/test_tokenizer.cc
index 705ef2bf..b4580018 100644
--- a/test/pp_api_test/test_tokenizer.cc
+++ b/test/pp_api_test/test_tokenizer.cc
@@ -611,3 +611,30 @@ TEST(OrtxTokenizerTest, AddedTokensTest) {
   DumpTokenIds(token_ids);
   EXPECT_EQ(token_ids[0], EXPECTED_IDS_0);
 }
+
+TEST(OrtxTokenizerTest, ChatTemplate) {
+  auto tokenizer = std::make_unique<ort_extensions::TokenizerImpl>();
+
+  // Since we do not have local test files for Phi4/Llama3/DeepSeek, we simply manually
+  // set the chat_template, but otherwise this will be loaded from the tokenizer config automatically.
+  tokenizer->chat_template = tokenizer->PHI4_CHAT_TEMPLATE;
+
+  std::vector<std::unordered_map<std::string, std::string>> messages = {
+    {{"role", "system"}, {"content", "You are a helpful assistant."}, {"tools", "Calculator"}},
+    {{"role", "user"}, {"content", "How do I add two numbers?"}},
+    {{"role", "assistant"}, {"content", "You can add numbers by using the '+' operator."}}
+  };
+
+  // From HuggingFace Python output for 'microsoft/Phi-4-multimodal-instruct'
+  std::string expected_output = "<|system|>You are a helpful assistant.<|tool|>Calculator<|/tool|><|end|><|user|>How do I add two numbers?<|end|><|assistant|>You can add numbers by using the '+' operator.<|end|><|assistant|>";
+
+  std::string output = "";
+  
+  auto status = tokenizer->ApplyChatTemplate(messages, &output, true);
+
+  if (!status.IsOk()) {
+    std::cout << status.ToString() << std::endl;
+  }
+
+  ASSERT_EQ(output, expected_output);
+}