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llama : add llama_chat_apply_template() (#5538)
* llama: add llama_chat_apply_template * test-chat-template: remove dedundant vector * chat_template: do not use std::string for buffer * add clarification for llama_chat_apply_template * llama_chat_apply_template: add zephyr template * llama_chat_apply_template: correct docs * llama_chat_apply_template: use term "chat" everywhere * llama_chat_apply_template: change variable name to "tmpl"
This commit is contained in:
Xuan Son Nguyen
GitHub
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3a9cb4ca64
commit
11b12de39b
4
Makefile
4
Makefile
@ -867,3 +867,7 @@ tests/test-model-load-cancel: tests/test-model-load-cancel.cpp ggml.o llama.o te
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tests/test-autorelease: tests/test-autorelease.cpp ggml.o llama.o tests/get-model.cpp $(COMMON_DEPS) $(OBJS)
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$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
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$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
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tests/test-chat-template: tests/test-chat-template.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
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$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
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$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
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117
llama.cpp
117
llama.cpp
@ -12508,6 +12508,123 @@ int32_t llama_token_to_piece(const struct llama_model * model, llama_token token
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return 0;
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}
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// trim whitespace from the beginning and end of a string
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static std::string trim(const std::string & str) {
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size_t start = 0;
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size_t end = str.size();
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while (start < end && isspace(str[start])) {
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start += 1;
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}
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while (end > start && isspace(str[end - 1])) {
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end -= 1;
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}
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return str.substr(start, end - start);
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}
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// Simple version of "llama_apply_chat_template" that only works with strings
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// This function uses heuristic checks to determine commonly used template. It is not a jinja parser.
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static int32_t llama_chat_apply_template_internal(
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const std::string & tmpl,
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const std::vector<const llama_chat_message *> & chat,
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std::string & dest, bool add_ass) {
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// Taken from the research: https://github.com/ggerganov/llama.cpp/issues/5527
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std::stringstream ss;
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if (tmpl.find("<|im_start|>") != std::string::npos) {
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// chatml template
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for (auto message : chat) {
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ss << "<|im_start|>" << message->role << "\n" << message->content << "<|im_end|>\n";
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}
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if (add_ass) {
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ss << "<|im_start|>assistant\n";
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}
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} else if (tmpl.find("[INST]") != std::string::npos) {
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// llama2 template and its variants
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// [variant] support system message
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bool support_system_message = tmpl.find("<<SYS>>") != std::string::npos;
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// [variant] space before + after response
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bool space_around_response = tmpl.find("' ' + eos_token") != std::string::npos;
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// [variant] add BOS inside history
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bool add_bos_inside_history = tmpl.find("bos_token + '[INST]") != std::string::npos;
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// [variant] trim spaces from the input message
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bool strip_message = tmpl.find("content.strip()") != std::string::npos;
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// construct the prompt
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bool is_inside_turn = true; // skip BOS at the beginning
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ss << "[INST] ";
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for (auto message : chat) {
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std::string content = strip_message ? trim(message->content) : message->content;
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std::string role(message->role);
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if (!is_inside_turn) {
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is_inside_turn = true;
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ss << (add_bos_inside_history ? "<s>[INST] " : "[INST] ");
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}
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if (role == "system") {
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if (support_system_message) {
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ss << "<<SYS>>\n" << content << "\n<</SYS>>\n\n";
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} else {
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// if the model does not support system message, we still include it in the first message, but without <<SYS>>
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ss << content << "\n";
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}
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} else if (role == "user") {
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ss << content << " [/INST]";
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} else {
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ss << (space_around_response ? " " : "") << content << (space_around_response ? " " : "") << "</s>";
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is_inside_turn = false;
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}
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}
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// llama2 templates seem to not care about "add_generation_prompt"
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} else if (tmpl.find("<|user|>") != std::string::npos) {
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// zephyr template
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for (auto message : chat) {
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ss << "<|" << message->role << "|>" << "\n" << message->content << "<|endoftext|>\n";
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}
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if (add_ass) {
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ss << "<|assistant|>\n";
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}
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} else {
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// template not supported
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return -1;
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}
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dest = ss.str();
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return dest.size();
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}
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LLAMA_API int32_t llama_chat_apply_template(
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const struct llama_model * model,
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const char * tmpl,
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const struct llama_chat_message * chat,
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size_t n_msg,
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bool add_ass,
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char * buf,
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int32_t length) {
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std::string curr_tmpl(tmpl == nullptr ? "" : tmpl);
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if (tmpl == nullptr) {
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GGML_ASSERT(model != nullptr);
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// load template from model
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std::vector<char> model_template(2048, 0); // longest known template is about 1200 bytes
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std::string template_key = "tokenizer.chat_template";
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int32_t res = llama_model_meta_val_str(model, template_key.c_str(), model_template.data(), curr_tmpl.size());
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if (res < 0) {
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// worst case: there is no information about template, we will use chatml by default
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curr_tmpl = "<|im_start|>"; // see llama_chat_apply_template_internal
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} else {
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curr_tmpl = std::string(model_template.data(), model_template.size());
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}
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}
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// format the chat to string
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std::vector<const llama_chat_message *> chat_vec;
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chat_vec.resize(n_msg);
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for (size_t i = 0; i < n_msg; i++) {
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chat_vec[i] = &chat[i];
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}
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std::string formatted_chat;
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int32_t res = llama_chat_apply_template_internal(curr_tmpl, chat_vec, formatted_chat, add_ass);
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if (res < 0) {
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return res;
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}
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strncpy(buf, formatted_chat.c_str(), length);
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return res;
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}
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struct llama_timings llama_get_timings(struct llama_context * ctx) {
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struct llama_timings result = {
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/*.t_start_ms =*/ 1e-3 * ctx->t_start_us,
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25
llama.h
25
llama.h
@ -305,6 +305,12 @@ extern "C" {
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int32_t n_eval;
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};
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// used in chat template
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typedef struct llama_chat_message {
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const char * role;
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const char * content;
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} llama_chat_message;
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// Helpers for getting default parameters
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LLAMA_API struct llama_model_params llama_model_default_params(void);
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LLAMA_API struct llama_context_params llama_context_default_params(void);
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@ -699,6 +705,25 @@ extern "C" {
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char * buf,
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int32_t length);
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/// Apply chat template. Inspired by hf apply_chat_template() on python.
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/// Both "model" and "custom_template" are optional, but at least one is required. "custom_template" has higher precedence than "model"
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/// NOTE: This function only support some known jinja templates. It is not a jinja parser.
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/// @param tmpl A Jinja template to use for this chat. If this is nullptr, the model’s default chat template will be used instead.
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/// @param chat Pointer to a list of multiple llama_chat_message
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/// @param n_msg Number of llama_chat_message in this chat
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/// @param add_ass Whether to end the prompt with the token(s) that indicate the start of an assistant message.
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/// @param buf A buffer to hold the output formatted prompt. The recommended alloc size is 2 * (total number of characters of all messages)
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/// @param length The size of the allocated buffer
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/// @return The total number of bytes of the formatted prompt. If is it larger than the size of buffer, you may need to re-alloc it and then re-apply the template.
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LLAMA_API int32_t llama_chat_apply_template(
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const struct llama_model * model,
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const char * tmpl,
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const struct llama_chat_message * chat,
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size_t n_msg,
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bool add_ass,
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char * buf,
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int32_t length);
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//
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// Grammar
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//
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@ -28,6 +28,7 @@ endfunction()
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llama_build_and_test_executable(test-quantize-fns.cpp)
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llama_build_and_test_executable(test-quantize-perf.cpp)
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llama_build_and_test_executable(test-sampling.cpp)
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llama_build_and_test_executable(test-chat-template.cpp)
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llama_build_executable(test-tokenizer-0-llama.cpp)
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llama_test_executable (test-tokenizer-0-llama test-tokenizer-0-llama.cpp ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama.gguf)
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64
tests/test-chat-template.cpp
Normal file
64
tests/test-chat-template.cpp
Normal file
@ -0,0 +1,64 @@
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#include <iostream>
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#include <string>
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#include <vector>
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#include <sstream>
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#undef NDEBUG
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#include <cassert>
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#include "llama.h"
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int main(void) {
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llama_chat_message conversation[] = {
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{"system", "You are a helpful assistant"},
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{"user", "Hello"},
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{"assistant", "Hi there"},
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{"user", "Who are you"},
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{"assistant", " I am an assistant "},
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{"user", "Another question"},
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};
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size_t message_count = 6;
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std::vector<std::string> templates = {
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// teknium/OpenHermes-2.5-Mistral-7B
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"{% for message in messages %}{{'<|im_start|>' + message['role'] + '\\n' + message['content'] + '<|im_end|>' + '\\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\\n' }}{% endif %}",
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// mistralai/Mistral-7B-Instruct-v0.2
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"{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eos_token}}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}",
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// TheBloke/FusionNet_34Bx2_MoE-AWQ
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"{%- for idx in range(0, messages|length) -%}\\n{%- if messages[idx]['role'] == 'user' -%}\\n{%- if idx > 1 -%}\\n{{- bos_token + '[INST] ' + messages[idx]['content'] + ' [/INST]' -}}\\n{%- else -%}\\n{{- messages[idx]['content'] + ' [/INST]' -}}\\n{%- endif -%}\\n{% elif messages[idx]['role'] == 'system' %}\\n{{- '[INST] <<SYS>>\\\\n' + messages[idx]['content'] + '\\\\n<</SYS>>\\\\n\\\\n' -}}\\n{%- elif messages[idx]['role'] == 'assistant' -%}\\n{{- ' ' + messages[idx]['content'] + ' ' + eos_token -}}\\n{% endif %}\\n{% endfor %}",
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// bofenghuang/vigogne-2-70b-chat
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"{{ bos_token }}{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% elif true == true and not '<<SYS>>' in messages[0]['content'] %}{% set loop_messages = messages %}{% set system_message = 'Vous êtes Vigogne, un assistant IA créé par Zaion Lab. Vous suivez extrêmement bien les instructions. Aidez autant que vous le pouvez.' %}{% 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' %}{{ '[INST] ' + content.strip() + ' [/INST]' }}{% elif message['role'] == 'system' %}{{ '<<SYS>>\\\\n' + content.strip() + '\\\\n<</SYS>>\\\\n\\\\n' }}{% elif message['role'] == 'assistant' %}{{ ' ' + content.strip() + ' ' + eos_token }}{% endif %}{% endfor %}",
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};
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std::vector<std::string> expected_substr = {
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"<|im_start|>assistant\n I am an assistant <|im_end|>\n<|im_start|>user\nAnother question<|im_end|>\n<|im_start|>assistant",
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"[/INST]Hi there</s>[INST] Who are you [/INST] I am an assistant </s>[INST] Another question [/INST]",
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"</s><s>[INST] Who are you [/INST] I am an assistant </s><s>[INST] Another question [/INST]",
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"[/INST] Hi there </s>[INST] Who are you [/INST] I am an assistant </s>[INST] Another question [/INST]",
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};
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std::vector<char> formatted_chat(1024);
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int32_t res;
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// test invalid chat template
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res = llama_chat_apply_template(nullptr, "INVALID TEMPLATE", conversation, message_count, true, formatted_chat.data(), formatted_chat.size());
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assert(res < 0);
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for (size_t i = 0; i < templates.size(); i++) {
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std::string custom_template = templates[i];
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std::string substr = expected_substr[i];
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formatted_chat.resize(1024);
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res = llama_chat_apply_template(
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nullptr,
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custom_template.c_str(),
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conversation,
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message_count,
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true,
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formatted_chat.data(),
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formatted_chat.size()
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);
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formatted_chat.resize(res);
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std::string output(formatted_chat.data(), formatted_chat.size());
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std::cout << output << "\n-------------------------\n";
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// expect the "formatted_chat" to contain pre-defined strings
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assert(output.find(substr) != std::string::npos);
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}
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return 0;
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}
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