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llama.cpp/common/parsers/kimi-k2.cpp
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Piotr Wilkin (ilintar) 895c045fd1 chat : split specialized parsers into common/parsers (#27764)
* chat : split specialized parsers into common/parsers

Move the 14 dedicated template parsers out of chat.cpp into one file each under
common/parsers, mirroring the src/models split. chat.cpp keeps the template
detection in common_chat_try_specialized_template() and drops from 3915 to 1513
lines.

common/parsers/parsers.h holds the shared helpers and one declaration per
parser. foreach_function/foreach_parameter become inline there since nothing in
chat.cpp uses them any more; common_chat_template_direct_apply_impl and
common_chat_template_generation_prompt_impl lose static and carry their default
arguments in the header. Parser-specific helpers move with their parser:
is_lfm2_template, deepseek_v4_sort_tool_results and the gemma4 turn builder.

No functional change.

Assisted-by: Claude Opus 5

* chat : enumerate parser sources instead of globbing

file(GLOB) does not re-run CMake when a source file is added or removed, so an
incremental build silently keeps building the old set. List the parsers in
common/parsers/sources.cmake and include it from common/CMakeLists.txt.

Assisted-by: Claude Opus 5

* split helpers, add newlines
2026-09-08 09:29:37 +03:00

134 lines
5.9 KiB
C++

#include "parsers.h"
// Kimi K2 Thinking - uses unique tool call ID format: functions.<name>:<index>
// The ID contains both the function name and an incrementing counter
common_chat_params common_chat_params_init_kimi_k2(const common_chat_template & tmpl,
const autoparser::generation_params & inputs) {
common_chat_params data;
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.supports_thinking = true;
data.preserved_tokens = {
"<|tool_calls_section_begin|>",
"<|tool_calls_section_end|>",
"<|tool_call_begin|>",
"<|tool_call_argument_begin|>",
"<|tool_call_end|>",
"<think>",
"</think>",
};
auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
auto extract_reasoning = inputs.reasoning_format != COMMON_REASONING_FORMAT_NONE;
auto include_grammar = has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE;
const std::string SECTION_BEGIN = "<|tool_calls_section_begin|>";
const std::string SECTION_END = "<|tool_calls_section_end|>";
const std::string CALL_BEGIN = "<|tool_call_begin|>";
const std::string ARGS_BEGIN = "<|tool_call_argument_begin|>";
const std::string CALL_END = "<|tool_call_end|>";
const std::string THINK_START = "<think>";
const std::string THINK_END = "</think>";
const std::string GEN_PROMPT = "<|im_assistant|>assistant<|im_middle|>";
data.thinking_start_tag = THINK_START;
data.thinking_end_tags = {THINK_END};
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = GEN_PROMPT + THINK_START + msg.reasoning_content;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += THINK_END + msg.render_content();
}
data.prompt += data.generation_prompt;
}
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
// Kimi K2 Thinking format:
// - Reasoning: <think>{reasoning}</think>
// - Content: text after reasoning
// - Tool calls section:
// <|tool_calls_section_begin|>
// <|tool_call_begin|>functions.<name>:<index><|tool_call_argument_begin|>{json_args}<|tool_call_end|>
// ...
// <|tool_calls_section_end|>
// The ID format is: functions.<function_name>:<counter> where counter is 0, 1, 2, ...
// Tool call markers
auto end = p.end();
// Note: this model is CRAZY. It can diverge from its supposed tool calling pattern in so many ways it's not funny.
// For example, it can call tools at the end of reasoning without closing reasoning...
auto reasoning = extract_reasoning ? p.optional(THINK_START + p.reasoning(
p.until_one_of({ THINK_END, "<|tool_calls_section_begin|>", "<|tool_call_begin|>" })) +
p.optional(p.literal(THINK_END))) : p.eps();
auto generation_prompt = p.literal(GEN_PROMPT);
// Content only parser (no tools)
if (!has_tools || inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_NONE) {
return generation_prompt + reasoning + p.content(p.rest()) + end;
}
// Build tool call parsers for each available function
// The ID format is: functions.<name>:<index>
// We need to match: functions.<name>:<digits>
auto tool_choice = p.choice();
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
std::string name = function.at("name");
const auto & schema = function.at("parameters");
// Match: functions.<name>:<digits>
// Capture the full call id (functions.<name>:<digits>) using tool_id tag
auto tool_id = p.tool_id(p.literal("functions.") + p.tool_name(p.literal(name)) + p.literal(":") + p.chars("[0-9]", 1, -1));
auto tool_parser = p.tool(
p.tool_open(tool_id + p.literal(ARGS_BEGIN)) +
p.tool_args(p.schema(p.json(), "tool-" + name + "-schema", schema)) +
p.tool_close(p.optional((p.literal(CALL_END))))
);
tool_choice |= p.rule("tool-" + name, tool_parser);
});
// Tool calls section: <|tool_calls_section_begin|> tool_calls <|tool_calls_section_end|>
auto min_calls = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED ? 1 : 0;
auto max_calls = inputs.parallel_tool_calls ? -1 : 1;
// Use trigger_rule so grammar generator knows where to start generating rules
auto tool_calls = p.rule("tool-calls",
p.optional(p.literal(SECTION_BEGIN)) +
p.trigger_rule("tool-call", p.repeat(CALL_BEGIN + tool_choice, min_calls, max_calls) +
p.optional(p.literal(SECTION_END)))
);
auto content_before_tools = p.content(p.until_one_of({ SECTION_BEGIN, CALL_BEGIN }));
return generation_prompt + reasoning + content_before_tools + tool_calls + end;
});
data.parser = parser.save();
if (include_grammar) {
data.grammar_lazy = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_AUTO;
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
auto schema = function.at("parameters");
builder.resolve_refs(schema);
});
parser.build_grammar(builder, data.grammar_lazy);
});
data.grammar_triggers = {
{ COMMON_GRAMMAR_TRIGGER_TYPE_WORD, "<|tool_call_begin|>" }
};
}
return data;
}