Server: use llama_chat_apply_template (#5593)
* server: use llama_chat_apply_template * server: remove trailing space * server: fix format_chat * server: fix help message Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * server: fix formatted_chat --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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4 changed files with 45 additions and 49 deletions
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@ -167,50 +167,47 @@ static T json_value(const json &body, const std::string &key, const T &default_v
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: default_value;
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}
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inline std::string format_llama2(std::vector<json> messages)
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{
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std::ostringstream output;
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bool is_inside_turn = false;
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for (auto it = messages.begin(); it != messages.end(); ++it) {
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if (!is_inside_turn) {
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output << "[INST] ";
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}
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std::string role = json_value(*it, "role", std::string("user"));
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std::string content = json_value(*it, "content", std::string(""));
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if (role == "system") {
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output << "<<SYS>>\n" << content << "\n<<SYS>>\n\n";
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is_inside_turn = true;
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} else if (role == "user") {
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output << content << " [/INST]";
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is_inside_turn = true;
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} else {
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output << " " << content << " </s>";
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is_inside_turn = false;
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}
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}
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LOG_VERBOSE("format_llama2", {{"text", output.str()}});
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return output.str();
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// Check if the template supplied via "--chat-template" is supported or not. Returns true if it's valid
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inline bool verify_custom_template(const std::string & tmpl) {
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llama_chat_message chat[] = {{"user", "test"}};
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std::vector<char> buf(1);
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int res = llama_chat_apply_template(nullptr, tmpl.c_str(), chat, 1, true, buf.data(), buf.size());
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return res >= 0;
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}
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inline std::string format_chatml(std::vector<json> messages)
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// Format given chat. If tmpl is empty, we take the template from model metadata
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inline std::string format_chat(const struct llama_model * model, const std::string & tmpl, const std::vector<json> & messages)
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{
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std::ostringstream chatml_msgs;
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size_t alloc_size = 0;
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// vector holding all allocated string to be passed to llama_chat_apply_template
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std::vector<std::string> str(messages.size() * 2);
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std::vector<llama_chat_message> chat(messages.size());
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for (auto it = messages.begin(); it != messages.end(); ++it) {
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chatml_msgs << "<|im_start|>"
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<< json_value(*it, "role", std::string("user")) << '\n';
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chatml_msgs << json_value(*it, "content", std::string(""))
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<< "<|im_end|>\n";
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for (size_t i = 0; i < messages.size(); ++i) {
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auto &curr_msg = messages[i];
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str[i*2 + 0] = json_value(curr_msg, "role", std::string(""));
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str[i*2 + 1] = json_value(curr_msg, "content", std::string(""));
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alloc_size += str[i*2 + 1].length();
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chat[i].role = str[i*2 + 0].c_str();
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chat[i].content = str[i*2 + 1].c_str();
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}
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chatml_msgs << "<|im_start|>assistant" << '\n';
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const char * ptr_tmpl = tmpl.empty() ? nullptr : tmpl.c_str();
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std::vector<char> buf(alloc_size * 2);
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LOG_VERBOSE("format_chatml", {{"text", chatml_msgs.str()}});
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// run the first time to get the total output length
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int32_t res = llama_chat_apply_template(model, ptr_tmpl, chat.data(), chat.size(), true, buf.data(), buf.size());
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return chatml_msgs.str();
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// if it turns out that our buffer is too small, we resize it
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if ((size_t) res > buf.size()) {
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buf.resize(res);
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res = llama_chat_apply_template(model, ptr_tmpl, chat.data(), chat.size(), true, buf.data(), buf.size());
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}
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std::string formatted_chat(buf.data(), res);
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LOG_VERBOSE("formatted_chat", {{"text", formatted_chat.c_str()}});
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return formatted_chat;
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}
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//
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