Repository: ggerganov/llama.cpp
File: examples/server/utils.hpp (C++)

Code before:
            json_schema = json_value(schema_wrapper, "schema", json::object());
        } else if (!response_type.empty() && response_type != "text") {
            throw std::runtime_error("response_format type must be one of \"text\" or \"json_object\", but got: " + response_type);
        }
    }

    common_chat_templates_inputs inputs;
    inputs.messages              = common_chat_msgs_parse_oaicompat(body.at("messages"));
    inputs.tools                 = common_chat_tools_parse_oaicompat(tools);
    inputs.tool_choice           = common_chat_tool_choice_parse_oaicompat(json_value(body, "tool_choice", std::string("auto")));
    inputs.json_schema           = json_schema.is_null() ? "" : json_schema.dump();
    inputs.grammar               = grammar;
    inputs.add_generation_prompt = json_value(body, "add_generation_prompt", true);
    inputs.use_jinja             = use_jinja;
    inputs.parallel_tool_calls   = json_value(body, "parallel_tool_calls", false);
    inputs.extract_reasoning     = reasoning_format != COMMON_REASONING_FORMAT_NONE;
    inputs.add_generation_prompt = json_value(body, "add_generation_prompt", true);
    if (!inputs.tools.empty() && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE && body.contains("grammar")) {
        throw std::runtime_error("Cannot use custom grammar constraints with tools.");
    }

    /* Prefill assistant message support */
    bool prefill_assistant_message = inputs.messages.size() > 0 && inputs.messages.back().role == "assistant";
    common_chat_msg last_message;
    if (prefill_assistant_message) {
        last_message = inputs.messages.back();
        inputs.messages.pop_back();
        inputs.extract_reasoning = false;
        inputs.add_generation_prompt = true;
    }

    // Apply chat template to the list of messages
    auto chat_params = common_chat_templates_apply(tmpls, inputs);

    /* Append assistant prefilled message */
    if (prefill_assistant_message) {
         chat_params.prompt += last_message.content;
    }

    llama_params["chat_format"]      = static_cast<int>(chat_params.format);
    llama_params["prompt"]           = chat_params.prompt;
    if (!chat_params.grammar.empty()) {
        llama_params["grammar"] = chat_params.grammar;
    }
    llama_params["grammar_lazy"]     = chat_params.grammar_lazy;
    auto grammar_triggers = json::array();
    for (const auto & trigger : chat_params.grammar_triggers) {
        server_grammar_trigger ct(trigger);
        grammar_triggers.push_back(ct.to_json());
    }
    llama_params["grammar_triggers"] = grammar_triggers;

Review comment (suggestion):
On second thought, can we also support the potential case of 2 or more assistant messages at the end of list? We could either merge these messages or more preferably throw an error

Code after:
            json_schema = json_value(schema_wrapper, "schema", json::object());
        } else if (!response_type.empty() && response_type != "text") {
            throw std::runtime_error("response_format type must be one of \"text\" or \"json_object\", but got: " + response_type);
        }
    }

    common_chat_templates_inputs inputs;
    inputs.messages              = common_chat_msgs_parse_oaicompat(body.at("messages"));
    inputs.tools                 = common_chat_tools_parse_oaicompat(tools);
    inputs.tool_choice           = common_chat_tool_choice_parse_oaicompat(json_value(body, "tool_choice", std::string("auto")));
    inputs.json_schema           = json_schema.is_null() ? "" : json_schema.dump();
    inputs.grammar               = grammar;
    inputs.add_generation_prompt = json_value(body, "add_generation_prompt", true);
    inputs.use_jinja             = use_jinja;
    inputs.parallel_tool_calls   = json_value(body, "parallel_tool_calls", false);
    inputs.extract_reasoning     = reasoning_format != COMMON_REASONING_FORMAT_NONE;
    inputs.add_generation_prompt = json_value(body, "add_generation_prompt", true);
    if (!inputs.tools.empty() && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE && body.contains("grammar")) {
        throw std::runtime_error("Cannot use custom grammar constraints with tools.");
    }

    // if the assistant message appears at the end of list, we do not add end-of-turn token
    // for ex. this can be useful to modify the reasoning process in reasoning models
    bool prefill_assistant_message = !inputs.messages.empty() && inputs.messages.back().role == "assistant";
    common_chat_msg last_message;
    if (prefill_assistant_message) {
        last_message = inputs.messages.back();
        inputs.messages.pop_back();

        /* sanity check, max one assistant message at the end of the list */
        if (!inputs.messages.empty() && inputs.messages.back().role == "assistant"){
            throw std::runtime_error("Cannot have 2 or more assistant messages at the end of the list.");
        }

        inputs.extract_reasoning = false;
        inputs.add_generation_prompt = true;
    }

    // Apply chat template to the list of messages
    auto chat_params = common_chat_templates_apply(tmpls, inputs);

    /* Append assistant prefilled message */
    if (prefill_assistant_message) {
         chat_params.prompt += last_message.content;
    }

    llama_params["chat_format"]      = static_cast<int>(chat_params.format);
    llama_params["prompt"]           = chat_params.prompt;
    if (!chat_params.grammar.empty()) {
        llama_params["grammar"] = chat_params.grammar;
    }