Files
llama.cpp/src/llama-chat.cpp
Sigbjørn Skjæret b8e09f08b9 model : add grok-2 support (#15539)
* add grok-2 support

* type fix

* type fix

* type fix

* "fix" vocab for invalid sequences

* fix expert tensor mapping and spaces in vocab

* add chat template

* fix norm tensor mapping

* rename layer_out_norm to ffn_post_norm

* ensure ffn_post_norm is mapped

* fix experts merging

* remove erroneous FFN_GATE entry

* concatenate split tensors and add more metadata

* process all expert layers and try cat instead of hstack

* add support for community BPE vocab

* fix expert feed forward length and ffn_down concat

* commit this too

* add ffn_up/gate/down, unsure if sequence is right

* add ffn_gate/down/up to tensor names

* correct residual moe (still not working)

* mess--

* fix embedding scale being applied twice

* add built in chat template

* change beta fast for grok if default value

* remove spm vocab in favor of community bpe vocab

* change attention temp length metadata type to integer

* update attention temp length metadata

* remove comment

* replace M_SQRT2 with std::sqrt(2)

* add yarn metadata, move defaults to hparams
2025-09-14 23:00:59 +02:00

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#include "llama-chat.h"
#include "llama.h"
#include <map>
#include <sstream>
#include <algorithm>
#if __cplusplus >= 202000L
#define LU8(x) (const char*)(u8##x)
#else
#define LU8(x) u8##x
#endif
// trim whitespace from the beginning and end of a string
static std::string trim(const std::string & str) {
size_t start = 0;
size_t end = str.size();
while (start < end && isspace(static_cast<unsigned char>(str[start]))) {
start += 1;
}
while (end > start && isspace(static_cast<unsigned char>(str[end - 1]))) {
end -= 1;
}
return str.substr(start, end - start);
}
static const std::map<std::string, llm_chat_template> LLM_CHAT_TEMPLATES = {
{ "chatml", LLM_CHAT_TEMPLATE_CHATML },
{ "llama2", LLM_CHAT_TEMPLATE_LLAMA_2 },
{ "llama2-sys", LLM_CHAT_TEMPLATE_LLAMA_2_SYS },
{ "llama2-sys-bos", LLM_CHAT_TEMPLATE_LLAMA_2_SYS_BOS },
{ "llama2-sys-strip", LLM_CHAT_TEMPLATE_LLAMA_2_SYS_STRIP },
{ "mistral-v1", LLM_CHAT_TEMPLATE_MISTRAL_V1 },
{ "mistral-v3", LLM_CHAT_TEMPLATE_MISTRAL_V3 },
{ "mistral-v3-tekken", LLM_CHAT_TEMPLATE_MISTRAL_V3_TEKKEN },
{ "mistral-v7", LLM_CHAT_TEMPLATE_MISTRAL_V7 },
{ "mistral-v7-tekken", LLM_CHAT_TEMPLATE_MISTRAL_V7_TEKKEN },
{ "phi3", LLM_CHAT_TEMPLATE_PHI_3 },
{ "phi4", LLM_CHAT_TEMPLATE_PHI_4 },
{ "falcon3", LLM_CHAT_TEMPLATE_FALCON_3 },
{ "zephyr", LLM_CHAT_TEMPLATE_ZEPHYR },
{ "monarch", LLM_CHAT_TEMPLATE_MONARCH },
{ "gemma", LLM_CHAT_TEMPLATE_GEMMA },
{ "orion", LLM_CHAT_TEMPLATE_ORION },
{ "openchat", LLM_CHAT_TEMPLATE_OPENCHAT },
{ "vicuna", LLM_CHAT_TEMPLATE_VICUNA },
{ "vicuna-orca", LLM_CHAT_TEMPLATE_VICUNA_ORCA },
{ "deepseek", LLM_CHAT_TEMPLATE_DEEPSEEK },
{ "deepseek2", LLM_CHAT_TEMPLATE_DEEPSEEK_2 },
{ "deepseek3", LLM_CHAT_TEMPLATE_DEEPSEEK_3 },
{ "command-r", LLM_CHAT_TEMPLATE_COMMAND_R },
{ "llama3", LLM_CHAT_TEMPLATE_LLAMA_3 },
{ "chatglm3", LLM_CHAT_TEMPLATE_CHATGLM_3 },
{ "chatglm4", LLM_CHAT_TEMPLATE_CHATGLM_4 },
{ "glmedge", LLM_CHAT_TEMPLATE_GLMEDGE },
{ "minicpm", LLM_CHAT_TEMPLATE_MINICPM },
{ "exaone3", LLM_CHAT_TEMPLATE_EXAONE_3 },
{ "exaone4", LLM_CHAT_TEMPLATE_EXAONE_4 },
{ "rwkv-world", LLM_CHAT_TEMPLATE_RWKV_WORLD },
{ "granite", LLM_CHAT_TEMPLATE_GRANITE },
{ "gigachat", LLM_CHAT_TEMPLATE_GIGACHAT },
{ "megrez", LLM_CHAT_TEMPLATE_MEGREZ },
{ "yandex", LLM_CHAT_TEMPLATE_YANDEX },
{ "bailing", LLM_CHAT_TEMPLATE_BAILING },
{ "llama4", LLM_CHAT_TEMPLATE_LLAMA4 },
{ "smolvlm", LLM_CHAT_TEMPLATE_SMOLVLM },
{ "hunyuan-moe", LLM_CHAT_TEMPLATE_HUNYUAN_MOE },
{ "gpt-oss", LLM_CHAT_TEMPLATE_OPENAI_MOE },
{ "hunyuan-dense", LLM_CHAT_TEMPLATE_HUNYUAN_DENSE },
{ "kimi-k2", LLM_CHAT_TEMPLATE_KIMI_K2 },
{ "seed_oss", LLM_CHAT_TEMPLATE_SEED_OSS },
{ "grok-2", LLM_CHAT_TEMPLATE_GROK_2 },
};
llm_chat_template llm_chat_template_from_str(const std::string & name) {
return LLM_CHAT_TEMPLATES.at(name);
}
llm_chat_template llm_chat_detect_template(const std::string & tmpl) {
try {
return llm_chat_template_from_str(tmpl);
} catch (const std::out_of_range &) {
// ignore
}
auto tmpl_contains = [&tmpl](const char * haystack) -> bool {
return tmpl.find(haystack) != std::string::npos;
};
if (tmpl_contains("<|im_start|>")) {
return tmpl_contains("<|im_sep|>")
? LLM_CHAT_TEMPLATE_PHI_4
: tmpl_contains("<end_of_utterance>")
? LLM_CHAT_TEMPLATE_SMOLVLM // SmolVLM uses <|im_start|> as BOS, but it is NOT chatml
: LLM_CHAT_TEMPLATE_CHATML;
} else if (tmpl.find("mistral") == 0 || tmpl_contains("[INST]")) {
if (tmpl_contains("[SYSTEM_PROMPT]")) {
return LLM_CHAT_TEMPLATE_MISTRAL_V7;
} else if (
// catches official 'v1' template
tmpl_contains("' [INST] ' + system_message")
// catches official 'v3' and 'v3-tekken' templates
|| tmpl_contains("[AVAILABLE_TOOLS]")
) {
// Official mistral 'v1', 'v3' and 'v3-tekken' templates
// See: https://github.com/mistralai/cookbook/blob/main/concept-deep-dive/tokenization/chat_templates.md
// See: https://github.com/mistralai/cookbook/blob/main/concept-deep-dive/tokenization/templates.md
if (tmpl_contains(" [INST]")) {
return LLM_CHAT_TEMPLATE_MISTRAL_V1;
} else if (tmpl_contains("\"[INST]\"")) {
return LLM_CHAT_TEMPLATE_MISTRAL_V3_TEKKEN;
}
return LLM_CHAT_TEMPLATE_MISTRAL_V3;
} else {
// llama2 template and its variants
// [variant] support system message
// See: https://huggingface.co/blog/llama2#how-to-prompt-llama-2
bool support_system_message = tmpl_contains("<<SYS>>");
bool add_bos_inside_history = tmpl_contains("bos_token + '[INST]");
bool strip_message = tmpl_contains("content.strip()");
if (strip_message) {
return LLM_CHAT_TEMPLATE_LLAMA_2_SYS_STRIP;
} else if (add_bos_inside_history) {
return LLM_CHAT_TEMPLATE_LLAMA_2_SYS_BOS;
} else if (support_system_message) {
return LLM_CHAT_TEMPLATE_LLAMA_2_SYS;
} else {
return LLM_CHAT_TEMPLATE_LLAMA_2;
}
}
} else if (tmpl_contains("<|assistant|>") && tmpl_contains("<|end|>")) {
return LLM_CHAT_TEMPLATE_PHI_3;
} else if (tmpl_contains("[gMASK]<sop>")) {
return LLM_CHAT_TEMPLATE_CHATGLM_4;
} else if (tmpl_contains("<|assistant|>") && tmpl_contains("<|user|>")) {
return tmpl_contains("</s>") ? LLM_CHAT_TEMPLATE_FALCON_3 : LLM_CHAT_TEMPLATE_GLMEDGE;
} else if (tmpl_contains("<|{{ item['role'] }}|>") && tmpl_contains("<|begin_of_image|>")) {
return LLM_CHAT_TEMPLATE_GLMEDGE;
} else if (tmpl_contains("<|user|>") && tmpl_contains("<|endoftext|>")) {
return LLM_CHAT_TEMPLATE_ZEPHYR;
} else if (tmpl_contains("bos_token + message['role']")) {
return LLM_CHAT_TEMPLATE_MONARCH;
} else if (tmpl_contains("<start_of_turn>")) {
return LLM_CHAT_TEMPLATE_GEMMA;
} else if (tmpl_contains("'\\n\\nAssistant: ' + eos_token")) {
// OrionStarAI/Orion-14B-Chat
return LLM_CHAT_TEMPLATE_ORION;
} else if (tmpl_contains("GPT4 Correct ")) {
// openchat/openchat-3.5-0106
return LLM_CHAT_TEMPLATE_OPENCHAT;
} else if (tmpl_contains("USER: ") && tmpl_contains("ASSISTANT: ")) {
// eachadea/vicuna-13b-1.1 (and Orca variant)
if (tmpl_contains("SYSTEM: ")) {
return LLM_CHAT_TEMPLATE_VICUNA_ORCA;
}
return LLM_CHAT_TEMPLATE_VICUNA;
} else if (tmpl_contains("### Instruction:") && tmpl_contains("<|EOT|>")) {
// deepseek-ai/deepseek-coder-33b-instruct
return LLM_CHAT_TEMPLATE_DEEPSEEK;
} else if (tmpl_contains("<|START_OF_TURN_TOKEN|>") && tmpl_contains("<|USER_TOKEN|>")) {
// CohereForAI/c4ai-command-r-plus
return LLM_CHAT_TEMPLATE_COMMAND_R;
} else if (tmpl_contains("<|start_header_id|>") && tmpl_contains("<|end_header_id|>")) {
return LLM_CHAT_TEMPLATE_LLAMA_3;
} else if (tmpl_contains("[gMASK]sop")) {
// chatglm3-6b
return LLM_CHAT_TEMPLATE_CHATGLM_3;
} else if (tmpl_contains(LU8("<用户>"))) {
// MiniCPM-3B-OpenHermes-2.5-v2-GGUF
return LLM_CHAT_TEMPLATE_MINICPM;
} else if (tmpl_contains("'Assistant: ' + message['content'] + eos_token")) {
return LLM_CHAT_TEMPLATE_DEEPSEEK_2;
} else if (tmpl_contains(LU8("<Assistant>")) && tmpl_contains(LU8("<User>")) && tmpl_contains(LU8("<end▁of▁sentence>"))) {
return LLM_CHAT_TEMPLATE_DEEPSEEK_3;
} else if (tmpl_contains("[|system|]") && tmpl_contains("[|assistant|]") && tmpl_contains("[|endofturn|]")) {
if (tmpl_contains("[|tool|]")) {
return LLM_CHAT_TEMPLATE_EXAONE_4;
}
// ref: https://huggingface.co/LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct/discussions/8#66bae61b1893d14ee8ed85bb
// EXAONE-3.0-7.8B-Instruct
return LLM_CHAT_TEMPLATE_EXAONE_3;
} else if (tmpl_contains("rwkv-world") || tmpl_contains("{{- 'User: ' + message['content']|trim + '\\n\\n' -}}")) {
return LLM_CHAT_TEMPLATE_RWKV_WORLD;
} else if (tmpl_contains("<|start_of_role|>")) {
return LLM_CHAT_TEMPLATE_GRANITE;
} else if (tmpl_contains("message['role'] + additional_special_tokens[0] + message['content'] + additional_special_tokens[1]")) {
return LLM_CHAT_TEMPLATE_GIGACHAT;
} else if (tmpl_contains("<|role_start|>")) {
return LLM_CHAT_TEMPLATE_MEGREZ;
} else if (tmpl_contains(" Ассистент:")) {
return LLM_CHAT_TEMPLATE_YANDEX;
} else if (tmpl_contains("<role>ASSISTANT</role>") && tmpl_contains("'HUMAN'")) {
return LLM_CHAT_TEMPLATE_BAILING;
} else if (tmpl_contains("<|header_start|>") && tmpl_contains("<|header_end|>")) {
return LLM_CHAT_TEMPLATE_LLAMA4;
} else if (tmpl_contains("<|endofuserprompt|>")) {
return LLM_CHAT_TEMPLATE_DOTS1;
} else if (tmpl_contains("<|extra_0|>") && tmpl_contains("<|extra_4|>")) {
return LLM_CHAT_TEMPLATE_HUNYUAN_MOE;
} else if (tmpl_contains("<|start|>") && tmpl_contains("<|channel|>")) {
return LLM_CHAT_TEMPLATE_OPENAI_MOE;
} else if (tmpl_contains("<hy_Assistant>") && tmpl_contains("<hy_place▁holder▁no▁3>")) {
return LLM_CHAT_TEMPLATE_HUNYUAN_DENSE;
} else if (tmpl_contains("<|im_assistant|>assistant<|im_middle|>")) {
return LLM_CHAT_TEMPLATE_KIMI_K2;
} else if (tmpl_contains("<seed:bos>")) {
return LLM_CHAT_TEMPLATE_SEED_OSS;
} else if (tmpl_contains("'Assistant: ' + message['content'] + '<|separator|>")) {
return LLM_CHAT_TEMPLATE_GROK_2;
}
return LLM_CHAT_TEMPLATE_UNKNOWN;
}
// Simple version of "llama_apply_chat_template" that only works with strings
// This function uses heuristic checks to determine commonly used template. It is not a jinja parser.
int32_t llm_chat_apply_template(
llm_chat_template tmpl,
const std::vector<const llama_chat_message *> & chat,
std::string & dest, bool add_ass) {
// Taken from the research: https://github.com/ggerganov/llama.cpp/issues/5527
std::stringstream ss;
if (tmpl == LLM_CHAT_TEMPLATE_CHATML) {
// chatml template
for (auto message : chat) {
ss << "<|im_start|>" << message->role << "\n" << message->content << "<|im_end|>\n";
}
if (add_ass) {
ss << "<|im_start|>assistant\n";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_MISTRAL_V7 || tmpl == LLM_CHAT_TEMPLATE_MISTRAL_V7_TEKKEN) {
// Official mistral 'v7' template
// See: https://huggingface.co/mistralai/Mistral-Large-Instruct-2411#basic-instruct-template-v7
// https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503#basic-instruct-template-v7-tekken
const char * trailing_space = tmpl == LLM_CHAT_TEMPLATE_MISTRAL_V7 ? " " : "";
for (auto message : chat) {
std::string role(message->role);
std::string content(message->content);
if (role == "system") {
ss << "[SYSTEM_PROMPT]" << trailing_space << content << "[/SYSTEM_PROMPT]";
} else if (role == "user") {
ss << "[INST]" << trailing_space << content << "[/INST]";
} else {
ss << trailing_space << content << "</s>";
}
}
} else if (tmpl == LLM_CHAT_TEMPLATE_MISTRAL_V1
|| tmpl == LLM_CHAT_TEMPLATE_MISTRAL_V3
|| tmpl == LLM_CHAT_TEMPLATE_MISTRAL_V3_TEKKEN) {
// See: https://github.com/mistralai/cookbook/blob/main/concept-deep-dive/tokenization/chat_templates.md
// See: https://github.com/mistralai/cookbook/blob/main/concept-deep-dive/tokenization/templates.md
std::string leading_space = tmpl == LLM_CHAT_TEMPLATE_MISTRAL_V1 ? " " : "";
std::string trailing_space = tmpl == LLM_CHAT_TEMPLATE_MISTRAL_V3_TEKKEN ? "" : " ";
bool trim_assistant_message = tmpl == LLM_CHAT_TEMPLATE_MISTRAL_V3;
bool is_inside_turn = false;
for (auto message : chat) {
if (!is_inside_turn) {
ss << leading_space << "[INST]" << trailing_space;
is_inside_turn = true;
}
std::string role(message->role);
std::string content(message->content);
if (role == "system") {
ss << content << "\n\n";
} else if (role == "user") {
ss << content << leading_space << "[/INST]";
} else {
ss << trailing_space << (trim_assistant_message ? trim(content) : content) << "</s>";
is_inside_turn = false;
}
}
} else if (
tmpl == LLM_CHAT_TEMPLATE_LLAMA_2
|| tmpl == LLM_CHAT_TEMPLATE_LLAMA_2_SYS
|| tmpl == LLM_CHAT_TEMPLATE_LLAMA_2_SYS_BOS
|| tmpl == LLM_CHAT_TEMPLATE_LLAMA_2_SYS_STRIP) {
// llama2 template and its variants
// [variant] support system message
// See: https://huggingface.co/blog/llama2#how-to-prompt-llama-2
bool support_system_message = tmpl != LLM_CHAT_TEMPLATE_LLAMA_2;
// [variant] add BOS inside history
bool add_bos_inside_history = tmpl == LLM_CHAT_TEMPLATE_LLAMA_2_SYS_BOS;
// [variant] trim spaces from the input message
bool strip_message = tmpl == LLM_CHAT_TEMPLATE_LLAMA_2_SYS_STRIP;
// construct the prompt
bool is_inside_turn = true; // skip BOS at the beginning
ss << "[INST] ";
for (auto message : chat) {
std::string content = strip_message ? trim(message->content) : message->content;
std::string role(message->role);
if (!is_inside_turn) {
is_inside_turn = true;
ss << (add_bos_inside_history ? "<s>[INST] " : "[INST] ");
}
if (role == "system") {
if (support_system_message) {
ss << "<<SYS>>\n" << content << "\n<</SYS>>\n\n";
} else {
// if the model does not support system message, we still include it in the first message, but without <<SYS>>
ss << content << "\n";
}
} else if (role == "user") {
ss << content << " [/INST]";
} else {
ss << content << "</s>";
is_inside_turn = false;
}
}
} else if (tmpl == LLM_CHAT_TEMPLATE_PHI_3) {
// Phi 3
for (auto message : chat) {
std::string role(message->role);
ss << "<|" << role << "|>\n" << message->content << "<|end|>\n";
}
if (add_ass) {
ss << "<|assistant|>\n";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_PHI_4) {
// chatml template
for (auto message : chat) {
ss << "<|im_start|>" << message->role << "<|im_sep|>" << message->content << "<|im_end|>";
}
if (add_ass) {
ss << "<|im_start|>assistant<|im_sep|>";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_FALCON_3) {
// Falcon 3
for (auto message : chat) {
std::string role(message->role);
ss << "<|" << role << "|>\n" << message->content << "\n";
}
if (add_ass) {
ss << "<|assistant|>\n";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_ZEPHYR) {
// zephyr template
for (auto message : chat) {
ss << "<|" << message->role << "|>" << "\n" << message->content << "<|endoftext|>\n";
}
if (add_ass) {
ss << "<|assistant|>\n";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_MONARCH) {
// mlabonne/AlphaMonarch-7B template (the <s> is included inside history)
for (auto message : chat) {
std::string bos = (message == chat.front()) ? "" : "<s>"; // skip BOS for first message
ss << bos << message->role << "\n" << message->content << "</s>\n";
}
if (add_ass) {
ss << "<s>assistant\n";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_GEMMA) {
// google/gemma-7b-it
std::string system_prompt = "";
for (auto message : chat) {
std::string role(message->role);
if (role == "system") {
// there is no system message for gemma, but we will merge it with user prompt, so nothing is broken
system_prompt += trim(message->content);
continue;
}
// in gemma, "assistant" is "model"
role = role == "assistant" ? "model" : message->role;
ss << "<start_of_turn>" << role << "\n";
if (!system_prompt.empty() && role != "model") {
ss << system_prompt << "\n\n";
system_prompt = "";
}
ss << trim(message->content) << "<end_of_turn>\n";
}
if (add_ass) {
ss << "<start_of_turn>model\n";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_ORION) {
// OrionStarAI/Orion-14B-Chat
std::string system_prompt = "";
for (auto message : chat) {
std::string role(message->role);
if (role == "system") {
// there is no system message support, we will merge it with user prompt
system_prompt += message->content;
continue;
} else if (role == "user") {
ss << "Human: ";
if (!system_prompt.empty()) {
ss << system_prompt << "\n\n";
system_prompt = "";
}
ss << message->content << "\n\nAssistant: </s>";
} else {
ss << message->content << "</s>";
}
}
} else if (tmpl == LLM_CHAT_TEMPLATE_OPENCHAT) {
// openchat/openchat-3.5-0106,
for (auto message : chat) {
std::string role(message->role);
if (role == "system") {
ss << message->content << "<|end_of_turn|>";
} else {
role[0] = toupper(role[0]);
ss << "GPT4 Correct " << role << ": " << message->content << "<|end_of_turn|>";
}
}
if (add_ass) {
ss << "GPT4 Correct Assistant:";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_VICUNA || tmpl == LLM_CHAT_TEMPLATE_VICUNA_ORCA) {
// eachadea/vicuna-13b-1.1 (and Orca variant)
for (auto message : chat) {
std::string role(message->role);
if (role == "system") {
// Orca-Vicuna variant uses a system prefix
if (tmpl == LLM_CHAT_TEMPLATE_VICUNA_ORCA) {
ss << "SYSTEM: " << message->content << "\n";
} else {
ss << message->content << "\n\n";
}
} else if (role == "user") {
ss << "USER: " << message->content << "\n";
} else if (role == "assistant") {
ss << "ASSISTANT: " << message->content << "</s>\n";
}
}
if (add_ass) {
ss << "ASSISTANT:";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_DEEPSEEK) {
// deepseek-ai/deepseek-coder-33b-instruct
for (auto message : chat) {
std::string role(message->role);
if (role == "system") {
ss << message->content;
} else if (role == "user") {
ss << "### Instruction:\n" << message->content << "\n";
} else if (role == "assistant") {
ss << "### Response:\n" << message->content << "\n<|EOT|>\n";
}
}
if (add_ass) {
ss << "### Response:\n";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_COMMAND_R) {
// CohereForAI/c4ai-command-r-plus
for (auto message : chat) {
std::string role(message->role);
if (role == "system") {
ss << "<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>" << trim(message->content) << "<|END_OF_TURN_TOKEN|>";
} else if (role == "user") {
ss << "<|START_OF_TURN_TOKEN|><|USER_TOKEN|>" << trim(message->content) << "<|END_OF_TURN_TOKEN|>";
} else if (role == "assistant") {
ss << "<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>" << trim(message->content) << "<|END_OF_TURN_TOKEN|>";
}
}
if (add_ass) {
ss << "<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_LLAMA_3) {
// Llama 3
for (auto message : chat) {
std::string role(message->role);
ss << "<|start_header_id|>" << role << "<|end_header_id|>\n\n" << trim(message->content) << "<|eot_id|>";
}
if (add_ass) {
ss << "<|start_header_id|>assistant<|end_header_id|>\n\n";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_CHATGLM_3) {
// chatglm3-6b
ss << "[gMASK]" << "sop";
for (auto message : chat) {
std::string role(message->role);
ss << "<|" << role << "|>" << "\n " << message->content;
}
if (add_ass) {
ss << "<|assistant|>";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_CHATGLM_4) {
ss << "[gMASK]" << "<sop>";
for (auto message : chat) {
std::string role(message->role);
ss << "<|" << role << "|>" << "\n" << message->content;
}
if (add_ass) {
ss << "<|assistant|>\n";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_GLMEDGE) {
for (auto message : chat) {
std::string role(message->role);
ss << "<|" << role << "|>" << "\n" << message->content;
}
if (add_ass) {
ss << "<|assistant|>";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_MINICPM) {
// MiniCPM-3B-OpenHermes-2.5-v2-GGUF
for (auto message : chat) {
std::string role(message->role);
if (role == "user") {
ss << LU8("<用户>");
ss << trim(message->content);
ss << "<AI>";
} else {
ss << trim(message->content);
}
}
} else if (tmpl == LLM_CHAT_TEMPLATE_DEEPSEEK_2) {
// DeepSeek-V2
for (auto message : chat) {
std::string role(message->role);
if (role == "system") {
ss << message->content << "\n\n";
} else if (role == "user") {
ss << "User: " << message->content << "\n\n";
} else if (role == "assistant") {
ss << "Assistant: " << message->content << LU8("<end▁of▁sentence>");
}
}
if (add_ass) {
ss << "Assistant:";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_DEEPSEEK_3) {
// DeepSeek-V3
for (auto message : chat) {
std::string role(message->role);
if (role == "system") {
ss << message->content << "\n\n";
} else if (role == "user") {
ss << LU8("<User>") << message->content;
} else if (role == "assistant") {
ss << LU8("<Assistant>") << message->content << LU8("<end▁of▁sentence>");
}
}
if (add_ass) {
ss << LU8("<Assistant>");
}
} else if (tmpl == LLM_CHAT_TEMPLATE_EXAONE_3) {
// ref: https://huggingface.co/LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct/discussions/8#66bae61b1893d14ee8ed85bb
// EXAONE-3.0-7.8B-Instruct
for (auto message : chat) {
std::string role(message->role);
if (role == "system") {
ss << "[|system|]" << trim(message->content) << "[|endofturn|]\n";
} else if (role == "user") {
ss << "[|user|]" << trim(message->content) << "\n";
} else if (role == "assistant") {
ss << "[|assistant|]" << trim(message->content) << "[|endofturn|]\n";
}
}
if (add_ass) {
ss << "[|assistant|]";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_EXAONE_4) {
for (auto message : chat) {
std::string role(message->role);
if (role == "system") {
ss << "[|system|]" << trim(message->content) << "[|endofturn|]\n";
} else if (role == "user") {
ss << "[|user|]" << trim(message->content) << "\n";
} else if (role == "assistant") {
ss << "[|assistant|]" << trim(message->content) << "[|endofturn|]\n";
} else if (role == "tool") {
ss << "[|tool|]" << trim(message->content) << "[|endofturn|]\n";
}
}
if (add_ass) {
ss << "[|assistant|]";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_RWKV_WORLD) {
// this template requires the model to have "\n\n" as EOT token
for (size_t i = 0; i < chat.size(); i++) {
std::string role(chat[i]->role);
if (role == "system") {
ss << "System: " << trim(chat[i]->content) << "\n\n";
} else if (role == "user") {
ss << "User: " << trim(chat[i]->content) << "\n\n";
if (i == chat.size() - 1) {
ss << "Assistant:";
}
} else if (role == "assistant") {
ss << "Assistant: " << trim(chat[i]->content) << "\n\n";
}
}
} else if (tmpl == LLM_CHAT_TEMPLATE_GRANITE) {
// IBM Granite template
for (const auto & message : chat) {
std::string role(message->role);
ss << "<|start_of_role|>" << role << "<|end_of_role|>";
if (role == "assistant_tool_call") {
ss << "<|tool_call|>";
}
ss << message->content << "<|end_of_text|>\n";
}
if (add_ass) {
ss << "<|start_of_role|>assistant<|end_of_role|>\n";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_GIGACHAT) {
// GigaChat template
bool has_system = !chat.empty() && std::string(chat[0]->role) == "system";
// Handle system message if present
if (has_system) {
ss << "<s>" << chat[0]->content << "<|message_sep|>";
} else {
ss << "<s>";
}
// Process remaining messages
for (size_t i = has_system ? 1 : 0; i < chat.size(); i++) {
std::string role(chat[i]->role);
if (role == "user") {
ss << "user<|role_sep|>" << chat[i]->content << "<|message_sep|>"
<< "available functions<|role_sep|>[]<|message_sep|>";
} else if (role == "assistant") {
ss << "assistant<|role_sep|>" << chat[i]->content << "<|message_sep|>";
}
}
// Add generation prompt if needed
if (add_ass) {
ss << "assistant<|role_sep|>";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_MEGREZ) {
// Megrez template
for (auto message : chat) {
std::string role(message->role);
ss << "<|role_start|>" << role << "<|role_end|>" << message->content << "<|turn_end|>";
}
if (add_ass) {
ss << "<|role_start|>assistant<|role_end|>";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_YANDEX) {
// Yandex template ("\n\n" is defined as EOT token)
for (size_t i = 0; i < chat.size(); i++) {
std::string role(chat[i]->role);
if (role == "user") {
ss << " Пользователь: " << chat[i]->content << "\n\n";
} else if (role == "assistant") {
ss << " Ассистент: " << chat[i]->content << "\n\n";
}
}
// Add generation prompt if needed
if (add_ass) {
ss << " Ассистент:[SEP]";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_BAILING) {
// Bailing (Ling) template
for (auto message : chat) {
std::string role(message->role);
if (role == "user") {
role = "HUMAN";
} else {
std::transform(role.begin(), role.end(), role.begin(), ::toupper);
}
ss << "<role>" << role << "</role>" << message->content;
}
if (add_ass) {
ss << "<role>ASSISTANT</role>";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_LLAMA4) {
// Llama 4
for (auto message : chat) {
std::string role(message->role);
ss << "<|header_start|>" << role << "<|header_end|>\n\n" << trim(message->content) << "<|eot|>";
}
if (add_ass) {
ss << "<|header_start|>assistant<|header_end|>\n\n";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_SMOLVLM) {
// SmolVLM
ss << "<|im_start|>"; // uses <|im_start|> as BOS, but the actual content is NOT chatml
for (auto message : chat) {
std::string role(message->role);
if (role == "system") {
ss << message->content << "\n\n";
} else if (role == "user") {
ss << "User: " << message->content << "<end_of_utterance>\n";
} else {
ss << "Assistant: " << message->content << "<end_of_utterance>\n";
}
}
if (add_ass) {
ss << "Assistant:";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_DOTS1) {
// dots.llm1.inst (DOTS1)
for (auto message : chat) {
std::string role(message->role);
if (role == "system") {
ss << "<|system|>" << message->content << "<|endofsystem|>";
} else if (role == "user") {
ss << "<|userprompt|>" << message->content << "<|endofuserprompt|>";
} else {
ss << "<|response|>" << message->content << "<|endofresponse|>";
}
}
if (add_ass) {
ss << "<|response|>";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_HUNYUAN_MOE) {
// tencent/Hunyuan-A13B-Instruct
for (auto message : chat) {
std::string role(message->role);
if (role == "system") {
ss << "<|startoftext|>" << message->content << "<|extra_4|>";
} else if (role == "assistant") {
ss << message->content << "<|eos|>";
} else {
ss << "<|startoftext|>" << message->content << "<|extra_0|>";
}
}
} else if (tmpl == LLM_CHAT_TEMPLATE_OPENAI_MOE) {
// OpenAI MoE (based on Harmony chat template)
for (auto message : chat) {
std::string role(message->role);
ss << "<|start|>" << role << "<|message|>" << message->content;
ss << (role == "assistant" ? "<|return|>" : "<|end|>");
}
if (add_ass) {
ss << "<|start|>assistant";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_HUNYUAN_DENSE) {
// tencent/Hunyuan-4B-Instruct
for (size_t i = 0; i < chat.size(); i++) {
std::string role(chat[i]->role);
if (i == 0) {
if (role == "system") {
ss << chat[i]->content << "<hy_place▁holder▁no▁3>";
}
}
if (role == "assistant") {
ss << "<hy_Assistant>" << chat[i]->content << "<hy_place▁holder▁no▁2>";
} else if (role == "user") {
ss << "<hy_User>" << chat[i]->content << "<hy_Assistant>";
}
}
} else if (tmpl == LLM_CHAT_TEMPLATE_KIMI_K2) {
// moonshotai/Kimi-K2-Instruct
for (auto message : chat) {
std::string role(message->role);
if (role == "system") {
ss << "<|im_system|>system<|im_middle|>";
} else if (role == "user") {
ss << "<|im_user|>user<|im_middle|>";
} else if (role == "assistant") {
ss << "<|im_assistant|>assistant<|im_middle|>";
} else if (role == "tool") {
ss << "<|im_system|>tool<|im_middle|>";
}
ss << message->content << "<|im_end|>";
}
if (add_ass) {
ss << "<|im_assistant|>assistant<|im_middle|>";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_SEED_OSS) {
for (auto message: chat) {
std::string role(message->role);
ss << "<seed:bos>" << role << "\n" << (role == "assistant" ? trim(message->content) : message->content) << "<seed:eos>";
}
if (add_ass) {
ss << "<seed:bos>assistant\n";
}
} else if (tmpl == LLM_CHAT_TEMPLATE_GROK_2) {
for (auto message : chat) {
std::string role(message->role);
if (role == "system") {
ss << "System: " << trim(message->content) << "<|separator|>\n\n";
} else if (role == "user") {
ss << "Human: " << trim(message->content) << "<|separator|>\n\n";
} else if (role == "assistant") {
ss << "Assistant: " << message->content << "<|separator|>\n\n";
}
}
if (add_ass) {
ss << "Assistant:";
}
} else {
// template not supported
return -1;
}
dest = ss.str();
return dest.size();
}
// public interface
int32_t llama_chat_builtin_templates(const char ** output, size_t len) {
auto it = LLM_CHAT_TEMPLATES.begin();
for (size_t i = 0; i < std::min(len, LLM_CHAT_TEMPLATES.size()); i++) {
output[i] = it->first.c_str();
std::advance(it, 1);
}
return (int32_t) LLM_CHAT_TEMPLATES.size();
}