Files
llama.cpp/common/chat.h
hksdpc255 1920345c3b common : Generalized XML-style tool-call parsing with streaming support (GLM 4.5/4.6 + MiniMax M2 + SeedOSS + Kimi-K2 + Qwen3-Coder + Apriel-1.5 + Xiaomi-MiMo) (#16932)
* Add files via upload

* fix unit test

* fix crashes for --reasoning-format=none

* Patch buggy official MiniMax-M2 chat template

* add upstream minja fix: https://github.com/ochafik/minja/pull/7

* Fix <think> token not generated

* add test copied from https://github.com/ggml-org/llama.cpp/pull/16946

* cleanup

* Hopes to fix the compilation error on CI

* Delete chat template patching since it’s fixed by upstream Minja

* Remove undeeded Minimax-M2 template patch

https://github.com/ochafik/minja/pull/7#issuecomment-3480356100

* Add proper handling of optional parameters with test
merged tests from: 23d4bb75c4

* Fix making all tool parameters optional

* Move xml tool parser to separate file

* cleanup & add tests for GLM4.5

* add streaming tests & enhancement & cleanups

Add streaming test for both GLM 4.5 and minimax-m2.
Cleanup for preserved_tokens.
Cleanup for grammar rule name.
Enhance the parser's stability.

* cleanup & add support for Kimi-K2 Qwen3-Coder Apriel-1.5 Xiaomi-MiMo

* apply suggestions from reviewers

* fix a misuse for data.grammar_lazy

* fix grammar when tool have no argument

* Fix `no triggers set for lazy grammar!` for GLM4.5/4.6. Insert additional stops for Kimi-K2

* update chat.cpp

* fix grammar for GLM 4.5/4.6

* Try fix Jinja template for GLM

* Try fix GLM-4.6.jinja

* Update common/chat-parser-xml-toolcall.cpp

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* Update tests/test-chat.cpp

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* improve chat template for GLM, rename Kimi-K2 template to Kimi-K2-Thinking

* Improve Kimi-K2 chat template

* Fix unit test

* Fix "Invalid tool call arguments passed" in a rare case.

In a rare case, the model may emit a raw string that begins with a valid JSON string. This commit adds unit tests to cover that scenario and fixes the regression introduced during the Kimi-K2 adaptation.

---------

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
2025-11-18 18:54:15 +01:00

225 lines
8.8 KiB
C++

// Chat support (incl. tool call grammar constraining & output parsing) w/ generic & custom template handlers.
#pragma once
#include "common.h"
#include <functional>
#include <chrono>
#include <string>
#include <vector>
#include <map>
struct common_chat_templates;
struct common_chat_tool_call {
std::string name;
std::string arguments;
std::string id;
bool operator==(const common_chat_tool_call & other) const {
return name == other.name && arguments == other.arguments && id == other.id;
}
};
struct common_chat_msg_content_part {
std::string type;
std::string text;
bool operator==(const common_chat_msg_content_part & other) const {
return type == other.type && text == other.text;
}
};
struct common_chat_msg {
std::string role;
std::string content;
std::vector<common_chat_msg_content_part> content_parts;
std::vector<common_chat_tool_call> tool_calls;
std::string reasoning_content;
std::string tool_name;
std::string tool_call_id;
template <class T> T to_json_oaicompat() const;
bool empty() const {
return content.empty() && content_parts.empty() && tool_calls.empty() && reasoning_content.empty() && tool_name.empty() && tool_call_id.empty();
}
void set_tool_call_ids(std::vector<std::string> & ids_cache, const std::function<std::string()> & gen_tool_call_id) {
for (auto i = 0u; i < tool_calls.size(); i++) {
if (ids_cache.size() <= i) {
auto id = tool_calls[i].id;
if (id.empty()) {
id = gen_tool_call_id();
}
ids_cache.push_back(id);
}
tool_calls[i].id = ids_cache[i];
}
}
bool operator==(const common_chat_msg & other) const {
return role == other.role
&& content == other.content
&& content_parts == other.content_parts
&& tool_calls == other.tool_calls
&& reasoning_content == other.reasoning_content
&& tool_name == other.tool_name
&& tool_call_id == other.tool_call_id;
}
bool operator!=(const common_chat_msg & other) const {
return !(*this == other);
}
};
struct common_chat_msg_diff {
std::string reasoning_content_delta;
std::string content_delta;
size_t tool_call_index = std::string::npos;
common_chat_tool_call tool_call_delta;
static std::vector<common_chat_msg_diff> compute_diffs(const common_chat_msg & previous_msg, const common_chat_msg & new_msg);
bool operator==(const common_chat_msg_diff & other) const {
return content_delta == other.content_delta
&& tool_call_index == other.tool_call_index
&& tool_call_delta == other.tool_call_delta;
}
};
struct common_chat_tool {
std::string name;
std::string description;
std::string parameters;
};
enum common_chat_tool_choice {
COMMON_CHAT_TOOL_CHOICE_AUTO,
COMMON_CHAT_TOOL_CHOICE_REQUIRED,
COMMON_CHAT_TOOL_CHOICE_NONE,
};
enum common_chat_format {
COMMON_CHAT_FORMAT_CONTENT_ONLY,
COMMON_CHAT_FORMAT_GENERIC,
COMMON_CHAT_FORMAT_MISTRAL_NEMO,
COMMON_CHAT_FORMAT_MAGISTRAL,
COMMON_CHAT_FORMAT_LLAMA_3_X,
COMMON_CHAT_FORMAT_LLAMA_3_X_WITH_BUILTIN_TOOLS,
COMMON_CHAT_FORMAT_DEEPSEEK_R1,
COMMON_CHAT_FORMAT_FIREFUNCTION_V2,
COMMON_CHAT_FORMAT_FUNCTIONARY_V3_2,
COMMON_CHAT_FORMAT_FUNCTIONARY_V3_1_LLAMA_3_1,
COMMON_CHAT_FORMAT_DEEPSEEK_V3_1,
COMMON_CHAT_FORMAT_HERMES_2_PRO,
COMMON_CHAT_FORMAT_COMMAND_R7B,
COMMON_CHAT_FORMAT_GRANITE,
COMMON_CHAT_FORMAT_GPT_OSS,
COMMON_CHAT_FORMAT_SEED_OSS,
COMMON_CHAT_FORMAT_NEMOTRON_V2,
COMMON_CHAT_FORMAT_APERTUS,
COMMON_CHAT_FORMAT_LFM2_WITH_JSON_TOOLS,
COMMON_CHAT_FORMAT_GLM_4_5,
COMMON_CHAT_FORMAT_MINIMAX_M2,
COMMON_CHAT_FORMAT_KIMI_K2,
COMMON_CHAT_FORMAT_QWEN3_CODER_XML,
COMMON_CHAT_FORMAT_APRIEL_1_5,
COMMON_CHAT_FORMAT_XIAOMI_MIMO,
COMMON_CHAT_FORMAT_COUNT, // Not a format, just the # formats
};
struct common_chat_templates_inputs {
std::vector<common_chat_msg> messages;
std::string grammar;
std::string json_schema;
bool add_generation_prompt = true;
bool use_jinja = true;
// Parameters below only supported when use_jinja is true
std::vector<common_chat_tool> tools;
common_chat_tool_choice tool_choice = COMMON_CHAT_TOOL_CHOICE_AUTO;
bool parallel_tool_calls = false;
common_reasoning_format reasoning_format = COMMON_REASONING_FORMAT_NONE;
bool enable_thinking = true;
std::chrono::system_clock::time_point now = std::chrono::system_clock::now();
std::map<std::string, std::string> chat_template_kwargs;
bool add_bos = false;
bool add_eos = false;
};
struct common_chat_params {
common_chat_format format = COMMON_CHAT_FORMAT_CONTENT_ONLY;
std::string prompt;
std::string grammar;
bool grammar_lazy = false;
bool thinking_forced_open = false;
std::vector<common_grammar_trigger> grammar_triggers;
std::vector<std::string> preserved_tokens;
std::vector<std::string> additional_stops;
};
struct common_chat_syntax {
common_chat_format format = COMMON_CHAT_FORMAT_CONTENT_ONLY;
common_reasoning_format reasoning_format = COMMON_REASONING_FORMAT_NONE;
// Whether reasoning_content should be inlined in the content (e.g. for reasoning_format=deepseek in stream mode)
bool reasoning_in_content = false;
bool thinking_forced_open = false;
bool parse_tool_calls = true;
};
// Check if the template supplied via "--chat-template" is supported or not. Returns true if it's valid
bool common_chat_verify_template(const std::string & tmpl, bool use_jinja);
void common_chat_templates_free(struct common_chat_templates * tmpls);
struct common_chat_templates_deleter { void operator()(common_chat_templates * tmpls) { common_chat_templates_free(tmpls); } };
typedef std::unique_ptr<struct common_chat_templates, common_chat_templates_deleter> common_chat_templates_ptr;
common_chat_templates_ptr common_chat_templates_init(
const struct llama_model * model,
const std::string & chat_template_override,
const std::string & bos_token_override = "",
const std::string & eos_token_override = "");
bool common_chat_templates_was_explicit(const struct common_chat_templates * tmpls);
const char * common_chat_templates_source(const struct common_chat_templates * tmpls, const char * variant = nullptr);
struct common_chat_params common_chat_templates_apply(
const struct common_chat_templates * tmpls,
const struct common_chat_templates_inputs & inputs);
// Format single message, while taking into account the position of that message in chat history
std::string common_chat_format_single(
const struct common_chat_templates * tmpls,
const std::vector<common_chat_msg> & past_msg,
const common_chat_msg & new_msg,
bool add_ass,
bool use_jinja);
// Returns an example of formatted chat
std::string common_chat_format_example(
const struct common_chat_templates * tmpls,
bool use_jinja,
const std::map<std::string, std::string> & chat_template_kwargs);
const char* common_chat_format_name(common_chat_format format);
const char* common_reasoning_format_name(common_reasoning_format format);
common_reasoning_format common_reasoning_format_from_name(const std::string & format);
common_chat_msg common_chat_parse(const std::string & input, bool is_partial, const common_chat_syntax & syntax);
common_chat_tool_choice common_chat_tool_choice_parse_oaicompat(const std::string & tool_choice);
bool common_chat_templates_support_enable_thinking(const common_chat_templates * chat_templates);
// Parses a JSON array of messages in OpenAI's chat completion API format.
// T can be std::string containing JSON or nlohmann::ordered_json
template <class T> std::vector<common_chat_msg> common_chat_msgs_parse_oaicompat(const T & messages);
template <class T> T common_chat_msgs_to_json_oaicompat(const std::vector<common_chat_msg> & msgs, bool concat_typed_text = false);
// Parses a JSON array of tools in OpenAI's chat completion tool call API format.
// T can be std::string containing JSON or nlohmann::ordered_json
template <class T> std::vector<common_chat_tool> common_chat_tools_parse_oaicompat(const T & tools);
template <class T> T common_chat_tools_to_json_oaicompat(const std::vector<common_chat_tool> & tools);
template <class T> T common_chat_msg_diff_to_json_oaicompat(const common_chat_msg_diff & diff);