Files
ik_llama.cpp/tests/test-chat-peg-parser.cpp
firecoperana ab1d74074b common : introduce composable PEG parser combinators for chat parsing and new jinja template engine (#1369)
---------

Co-authored-by: Piotr Wilkin <piotr.wilkin@syndatis.com>

common : add nemotron 3 parsing (#18077)

common : add parser for ministral/mistral large 3/devstral 2 (#17713)

common : default content to an empty string (#18485)

chat: make tool description and parameters optional per OpenAI spec (#18478)

Per the OpenAI API specification, both 'description' and 'parameters'
fields in tool function definitions are optional. Previously, the parser
would throw an exception if these fields were missing.

Attempts to fix #17667

common : implement new jinja template engine (#18462)
---------

Co-authored-by: Alde Rojas <hello@alde.dev>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

jinja: correct member access rule (#18905)

jinja : fix lexing of float literals with sign (#18901)

jinja : add missing tojson filter for bool (#18900)

jinja : attribute support for join, map and sort (#18883)

jinja : fix object item order (and properly implement dictsort) (#18904)

tests : add test-jinja -py option for cross-checking (#18906)

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

---------

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

ci : run test-jinja -py on high perf [no ci] (#18916)

jinja : fix undefined keys and attributes and int/float as bool (#18924)

jinja: support none|string (#18995)

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

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

---------

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

jinja : implement mixed type object keys (#18955)

---------

Co-authored-by: Xuan Son Nguyen <son@huggingface.co>

jinja : undefined should be treated as sequence/iterable (return string/array) by filters/tests (#19147)

`tojson` is not a supported `undefined` filter

keep it DRY and fix some types

jinja : do not pass empty tools and add some none filters (#19176)

jinja : add unordered_map include to value.h [no ci] (#19205)

jinja : add missing 'in' test to template engine (#19004) (#19239)

The jinja template parser was missing the 'in' test from
global_builtins(), causing templates using reject("in", ...),
select("in", ...), or 'x is in(y)' to fail with
"selectattr: unknown test 'in'".

This broke tool-calling for Qwen3-Coder and any other model
whose chat template uses the 'in' test.

Added test_is_in supporting array, string, and object containment
checks, mirroring the existing 'in' operator logic in runtime.cpp.

Includes test cases for all three containment types plus
reject/select filter usage.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

---------

Co-authored-by: Sid Mohan <sidmohan0@users.noreply.github.com>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>

Add Jinja support for "indent" string filter (#19529)

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

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

---------

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

add vendor

refactor chat

server : support preserving reasoning_content in assistant message (#18994)

chat : fix translategemma crash on common_chat_format_example (#19019)

chat: fix language input for translategemma (#19052)

Co-authored-by: Aldehir Rojas <hello@alde.dev>

---------

Co-authored-by: Aldehir Rojas <hello@alde.dev>

chat: fix case where template accepts type content only (#19419)

mtmd : chat : Fix extra \n between text and media marker (#19595)

Thanks to @tugot17 for detecting and reporting the issue.

For vision models (e.g. LFM2.5-VL-1.6B and Qwen/Qwen3-VL-4B-Instruct) `llama-mtmd-cli` produces identical output to HF implementation.

However `llama-server` doesn't. I traced it down to extra newline
inserted after `<__media__>`.

This happens in `to_json_oaicompat`, that treats media markers as text
and joins all parts with `\n` separator.

PR introduces new type `media_marker` and uses it for media markers.
Extra logic is added to prevent insertion of newlines before and after
media markers.

With this change number of input tokens is identical to HF
implementation and as a result the output is also identical.

I explored other ways to address the issue
* remove completely `\n` between text parts in `to_json_oaicompat`
* merge text messages in server-common.cpp before sending them to `to_json_oaicompat`

Please propose alternative ways of fixing this issue.

Co-authored-by: Piotr Wilkin (ilintar) <piotr.wilkin@syndatis.com>

---------

Co-authored-by: Piotr Wilkin (ilintar) <piotr.wilkin@syndatis.com>

common : merge qwen3-coder and nemotron nano 3 parsers (#19765)

common : fix improper trimming in XML parser on complete message (#19805)

Co-authored-by: Jules LEIDELINGER <11395311+julio75012@users.noreply.github.com>

jinja: correct stats for tojson and string filters (#19785)

jinja : correct default size for string slices (#19913)

common : handle unicode during partial json parsing (#16526)

common : fix json schema with '\' in literals (#17307)

add back qwen_coder_xml and mirothinker

Co-authored-by: Aldehir Rojas <hello@alde.dev>
2026-03-09 11:03:33 +01:00

769 lines
32 KiB
C++

#include <string>
#include <iostream>
#include <numeric>
#include "chat-parser.h"
#include "chat-peg-parser.h"
#include "chat.h"
#include "common.h"
#include "json-schema-to-grammar.h"
#include "peg-parser.h"
#include "testing.h"
#include "peg-parser/simple-tokenize.h"
#include "nlohmann/json.hpp"
using json = nlohmann::ordered_json;
static json create_tools();
static void test_example_native(testing & t);
static void test_example_qwen3_coder(testing & t);
static void test_command7_parser_compare(testing & t);
int main(int argc, char *argv[]) {
testing t(std::cout);
if (argc >= 2) {
t.set_filter(argv[1]);
}
const char * verbose = getenv("LLAMA_TEST_VERBOSE");
if (verbose) {
t.verbose = std::string(verbose) == "1";
}
t.test("native", test_example_native);
t.test("qwen3 coder", test_example_qwen3_coder);
t.test("comparison", test_command7_parser_compare);
return t.summary();
}
static json create_tools() {
json tools = json::array();
json tool_weather = {
{"type", "function"},
{"function", {
{"name", "get_current_weather"},
{"description", "Get the current weather in a given location"},
{"parameters", {
{"type", "object"},
{"properties", {
{"location", {
{"type", "string"},
{"description", "The city and state, e.g. San Francisco, CA"}
}},
{"unit", {
{"type", "string"},
{"enum", {"celsius", "fahrenheit"}},
{"description", "The temperature unit to use. Infer this from the users location."}
}}
}},
{"required", {"location", "unit"}},
}},
}}
};
tools.push_back(tool_weather);
json tool_forecast = {
{"type", "function"},
{"function", {
{"name", "get_forecast"},
{"description", "Get the weather forecast for a given location"},
{"parameters", {
{"type", "object"},
{"properties", {
{"location", {
{"type", "string"},
{"description", "The city and state, e.g. San Francisco, CA"}
}},
{"unit", {
{"type", "string"},
{"enum", {"celsius", "fahrenheit"}},
{"description", "The temperature unit to use. Infer this from the users location."}
}},
{"days", {
{"type", "integer"},
{"description", "Number of days to forecast (1-10)"},
{"minimum", 1},
{"maximum", 10}
}}
}},
{"required", {"location", "unit"}},
}},
}}
};
tools.push_back(tool_forecast);
json tool_search = {
{"type", "function"},
{"function", {
{"name", "search_knowledge_base"},
{"description", "Search the internal technical documentation knowledge base."},
{"parameters", {
{"type", "object"},
{"properties", {
{"query", {
{"type", "string"},
{"description", "The search query string."}
}},
{"max_results", {
{"type", "integer"},
{"description", "The maximum number of results to return."},
{"default", 5}
}},
{"category", {
{"type", "string"},
{"enum", {"api", "troubleshooting", "billing", "general"}},
{"description", "Filter search by specific category."}
}}
}},
{"required", {"query", "category"}},
{"additionalProperties", false}
}},
{"strict", true}
}}
};
tools.push_back(tool_search);
return tools;
}
struct tool_argument {
std::string name;
std::string type;
bool is_required;
json schema;
};
struct tool_definition {
std::string name;
std::vector<tool_argument> arguments;
json schema;
};
// Test fictitious model output that emits arguments as JSON.
static void test_example_native(testing & t) {
struct test_case {
// Parameters
std::string name;
json tools;
common_chat_tool_choice tool_choice;
common_reasoning_format reasoning_format;
json json_schema;
bool parallel_tool_calls;
bool thinking_forced_open;
std::string input;
// Expect
std::string expect_reasoning;
std::string expect_content;
std::vector<common_chat_tool_call> expect_tool_calls;
};
auto build_parser = [](const test_case & tc) {
return build_chat_peg_native_parser([&](common_chat_peg_native_builder & p) {
auto reasoning_in_content = (tc.reasoning_format == COMMON_REASONING_FORMAT_NONE);
auto reasoning = p.eps();
if (tc.thinking_forced_open) {
// If thinking is forced open, expect a closing tag
reasoning = p.reasoning(p.until("</think>")) + "</think>" + p.space();
} else {
// Otherwise, optionally accept thinking wrapped in tags
reasoning = p.optional("<think>" + p.reasoning(p.until("</think>")) + "</think>" + p.space());
}
// tool calling parser
if (tc.tools.is_array() && !tc.tools.empty()) {
auto tools = p.choice();
for (const auto & tool : tc.tools) {
const auto & function = tool.at("function");
std::string name = function.at("name");
const auto & schema = function.at("parameters");
auto tool_name = p.json_member("name", "\"" + p.tool_name(p.literal(name)) + "\"");
auto tool_args = p.json_member("arguments", p.tool_args(p.schema(p.json(), "tool-" + name + "-schema", schema)));
tools |= p.rule("tool-" + name, p.tool_open(p.literal("{")) << tool_name << "," << tool_args << "}");
};
auto parallel_calls = p.eps();
if (tc.parallel_tool_calls) {
parallel_calls = p.zero_or_more("," << tools);
}
auto tool_call = p.trigger_rule("tool-call",
p.sequence({
p.literal("<tool_call>["),
tools,
parallel_calls,
p.literal("]</tool_call>")
})
);
return p.sequence({
(reasoning_in_content ? p.eps() : reasoning),
p.content(p.until("<tool_call>")),
p.optional(p.space() + tool_call),
p.space(),
p.end()
});
}
// response_format parser
if (tc.json_schema.is_object() && !tc.json_schema.empty()) {
return p.sequence({
(reasoning_in_content ? p.eps() : reasoning),
p.content(p.schema(p.json(), "response-output", tc.json_schema)),
p.space(),
p.end()
});
}
// Content-only parser
return p.sequence({
(reasoning_in_content ? p.eps() : reasoning),
p.content(p.rest()),
p.end()
});
});
};
std::vector<test_case> test_cases = std::vector<test_case>{
{
/* .name = */ "content with thinking_forced_open = false",
/* .tools = */ {},
/* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_NONE,
/* .reasoning_format = */ COMMON_REASONING_FORMAT_AUTO,
/* .json_schema = */ {},
/* .parallel_tool_calls = */ false,
/* .thinking_forced_open = */ false,
/* .input = */ (
"<think>The user said hello, I must say hello back</think>\nHello"
),
/* .expect_reasoning = */ "The user said hello, I must say hello back",
/* .expect_content = */ "Hello",
/* .expect_tool_calls = */ {},
},
{
/* .name = */ "content with thinking_forced_open = false and no reasoning",
/* .tools = */ {},
/* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_NONE,
/* .reasoning_format = */ COMMON_REASONING_FORMAT_AUTO,
/* .json_schema = */ {},
/* .parallel_tool_calls = */ false,
/* .thinking_forced_open = */ false,
/* .input = */ (
"Hello"
),
/* .expect_reasoning = */ "",
/* .expect_content = */ "Hello",
/* .expect_tool_calls = */ {},
},
{
/* .name = */ "content with thinking_forced_open = false and reasoning_format = none",
/* .tools = */ {},
/* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_NONE,
/* .reasoning_format = */ COMMON_REASONING_FORMAT_NONE,
/* .json_schema = */ {},
/* .parallel_tool_calls = */ false,
/* .thinking_forced_open = */ true,
/* .input = */ (
"<think>The user said hello, I must say hello back</think>\nHello"
),
/* .expect_reasoning = */ "",
/* .expect_content = */ "<think>The user said hello, I must say hello back</think>\nHello",
/* .expect_tool_calls = */ {},
},
{
/* .name = */ "content with thinking_forced_open = true",
/* .tools = */ {},
/* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_NONE,
/* .reasoning_format = */ COMMON_REASONING_FORMAT_AUTO,
/* .json_schema = */ {},
/* .parallel_tool_calls = */ false,
/* .thinking_forced_open = */ true,
/* .input = */ (
"The user said hello, I must say hello back</think>\nHello"
),
/* .expect_reasoning = */ "The user said hello, I must say hello back",
/* .expect_content = */ "Hello",
/* .expect_tool_calls = */ {},
},
{
/* .name = */ "content with thinking_forced_open = true and reasoning_format = none",
/* .tools = */ {},
/* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_NONE,
/* .reasoning_format = */ COMMON_REASONING_FORMAT_NONE,
/* .json_schema = */ {},
/* .parallel_tool_calls = */ false,
/* .thinking_forced_open = */ true,
/* .input = */ (
"The user said hello, I must say hello back</think>\nHello"
),
/* .expect_reasoning = */ "",
/* .expect_content = */ "The user said hello, I must say hello back</think>\nHello",
/* .expect_tool_calls = */ {},
},
{
/* .name = */ "tools with tool_choice = auto and no parallel_tool_calls",
/* .tools = */ create_tools(),
/* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_AUTO,
/* .reasoning_format = */ COMMON_REASONING_FORMAT_AUTO,
/* .json_schema = */ {},
/* .parallel_tool_calls = */ false,
/* .thinking_forced_open = */ true,
/* .input = */ (
"I must get the weather in New York</think>\n"
"<tool_call>["
R"({"name": "get_current_weather", "arguments": {"location": "New York City, NY", "unit": "fahrenheit"}})"
"]</tool_call>"
),
/* .expect_reasoning = */ "I must get the weather in New York",
/* .expect_content = */ "",
/* .expect_tool_calls = */ {{
/* .name = */ "get_current_weather",
/* .arguments = */ R"({"location": "New York City, NY", "unit": "fahrenheit"})",
/* .id = */ "",
}},
},
{
/* .name = */ "tools with tool_choice = auto and parallel_tool_calls",
/* .tools = */ create_tools(),
/* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_AUTO,
/* .reasoning_format = */ COMMON_REASONING_FORMAT_AUTO,
/* .json_schema = */ {},
/* .parallel_tool_calls = */ true,
/* .thinking_forced_open = */ true,
/* .input = */ (
"I must get the weather in New York and San Francisco and a 3 day forecast of each.</think>\nLet me search that for you."
"<tool_call>["
R"({"name": "get_current_weather", "arguments": {"location": "New York City, NY", "unit": "fahrenheit"}})"
", "
R"({"name": "get_current_weather", "arguments": {"location": "San Francisco, CA", "unit": "fahrenheit"}})"
", "
R"({"name": "get_forecast", "arguments": {"location": "New York City, NY", "unit": "fahrenheit", "days": 3}})"
", "
R"({"name": "get_forecast", "arguments": {"location": "San Francisco, CA", "unit": "fahrenheit", "days": 3}})"
"]</tool_call>"
),
/* .expect_reasoning = */ "I must get the weather in New York and San Francisco and a 3 day forecast of each.",
/* .expect_content = */ "Let me search that for you.",
/* .expect_tool_calls = */ {{
/* .name = */ "get_current_weather",
/* .arguments = */ R"({"location": "New York City, NY", "unit": "fahrenheit"})",
/* .id = */ "",
}, {
/* .name = */ "get_current_weather",
/* .arguments = */ R"({"location": "San Francisco, CA", "unit": "fahrenheit"})",
/* .id = */ "",
}, {
/* .name = */ "get_forecast",
/* .arguments = */ R"({"location": "New York City, NY", "unit": "fahrenheit", "days": 3})",
/* .id = */ "",
}, {
/* .name = */ "get_forecast",
/* .arguments = */ R"({"location": "San Francisco, CA", "unit": "fahrenheit", "days": 3})",
/* .id = */ "",
}},
},
{
/* .name = */ "response_format with thinking_forced_open = true",
/* .tools = */ {},
/* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_NONE,
/* .reasoning_format = */ COMMON_REASONING_FORMAT_AUTO,
/* .json_schema = */ {
{"type", "object"},
{"properties", {
{"invoice_number", {{"type", "string"}}},
{"amount", {{"type", "number"}}},
{"due_date", {{"type", "string"}}}
}},
{"required", {"invoice_number", "amount", "due_date"}}
},
/* .parallel_tool_calls = */ false,
/* .thinking_forced_open = */ true,
/* .input = */ (
"I must produce the invoice in the requested format</think>\n"
R"({"invoice_number": "INV-2025-001", "amount": 1250.50, "due_date": "2025-12-31"})"
),
/* .expect_reasoning = */ "I must produce the invoice in the requested format",
/* .expect_content = */ R"({"invoice_number": "INV-2025-001", "amount": 1250.50, "due_date": "2025-12-31"})",
/* .expect_tool_calls = */ {},
},
};
for (const auto & tc : test_cases) {
t.test(tc.name, [&](testing & t) {
auto parser = build_parser(tc);
auto lazy = !tc.tools.empty() && tc.tool_choice != COMMON_CHAT_TOOL_CHOICE_REQUIRED;
auto grammar = build_grammar([&](const common_grammar_builder & builder) {
for (auto const & def : tc.tools) {
auto function = def.at("function");
auto parameters = function.at("parameters");
builder.resolve_refs(parameters);
};
parser.build_grammar(builder, lazy);
});
t.log("Grammar:");
for (auto const & line : string_split(grammar, "\n")) {
t.log(line);
}
common_peg_parse_context ctx(tc.input, false);
auto result = parser.parse(ctx);
t.assert_true("success", result.success());
common_chat_msg msg;
auto mapper = common_chat_peg_native_mapper(msg);
mapper.from_ast(ctx.ast, result);
t.assert_equal("content equal", tc.expect_content, msg.content);
t.assert_equal("reasoning equal", tc.expect_reasoning, msg.reasoning_content);
t.assert_equal("number of tool calls", tc.expect_tool_calls.size(), msg.tool_calls.size());
for (auto i = 0u; i < std::min(tc.expect_tool_calls.size(), msg.tool_calls.size()); i++) {
t.assert_equal("tool name", tc.expect_tool_calls[i].name, msg.tool_calls[i].name);
t.assert_equal("tool args", tc.expect_tool_calls[i].arguments, msg.tool_calls[i].arguments);
}
});
}
}
static void test_example_qwen3_coder(testing & t) {
auto tools = create_tools();
auto parser = build_chat_peg_constructed_parser([&](common_chat_peg_constructed_builder & p) {
auto content = p.rule("content", p.content(p.until("<tool_call>")));
std::vector<common_peg_parser> tool_parsers;
for (auto const & def : tools) {
auto function = def.at("function");
std::string name = function.at("name");
auto parameters = function.at("parameters");
auto properties = parameters.at("properties");
std::set<std::string> required_properties;
if (function.contains("required")) {
function.at("required").get_to(required_properties);
}
std::vector<common_peg_parser> arg_parsers;
for (const auto & [param_name, param_schema] : properties.items()) {
bool is_required = required_properties.find(param_name) != required_properties.end();
auto type = param_schema.value("type", "object");
auto arg = p.tool_arg(p.sequence({
p.tool_arg_open("<parameter=" + p.tool_arg_name(p.literal(param_name)) + ">"),
(type == "string" ?
p.tool_arg_string_value(
p.schema(
p.until_one_of({
"</parameter>\n<parameter=",
"</parameter>\n</function>"
}),
"tool-" + name + "-arg-" + param_name + "-schema",
param_schema,
true
)
) : p.tool_arg_json_value(
p.schema(
p.json(),
"tool-" + name + "-arg-" + param_name + "-schema",
param_schema
)
)
),
p.tool_arg_close(
"</parameter>\n" +
p.peek(p.literal("<parameter=") | p.literal("</function>"))
)
}));
arg_parsers.push_back(is_required ?
p.rule("tool-" + name + "-arg-" + param_name, arg) :
p.optional(p.rule("tool-" + name + "-arg-" + param_name, arg)));
}
tool_parsers.push_back(p.rule("tool-" + name,
p.tool_open("<function=" + p.tool_name(p.literal(name)) + ">")
<< p.sequence(arg_parsers)
<< p.tool_close(p.literal("</function>"))
));
};
auto tool_call = p.trigger_rule("tool-call",
"<tool_call>"
<< p.choice(tool_parsers)
<< "</tool_call>"
);
return content + p.zero_or_more(p.space() + tool_call) + p.end();
});
auto grammar = build_grammar([&](const common_grammar_builder & builder) {
for (auto const & def : tools) {
auto function = def.at("function");
auto parameters = function.at("parameters");
builder.resolve_refs(parameters);
};
parser.build_grammar(builder);
});
t.log("Grammar:");
for (auto const & line : string_split(grammar, "\n")) {
t.log(line);
}
t.test("incremental parsing", [&](testing &t) {
std::string input =
"Let me search the knowledge base for cat pictures."
"<tool_call>\n"
"<function=search_knowledge_base>\n"
"<parameter=query>cat pictures</parameter>\n"
"<parameter=category>general</parameter>\n"
"</function>\n"
"</tool_call>";
std::vector<std::string> tokens = simple_tokenize(input);
common_chat_msg prev;
for (auto it = tokens.begin(); it != tokens.end(); it++) {
std::string in = std::accumulate(tokens.begin(), it + 1, std::string());
common_peg_parse_context ctx(in, it + 1 < tokens.end());
auto result = parser.parse(ctx);
if (!t.assert_equal("not fail", false, result.fail())) {
t.log(in.substr(0, result.end) + "[failed->]" + in.substr(result.end));
}
common_chat_msg msg;
auto mapper = common_chat_peg_constructed_mapper(msg);
mapper.from_ast(ctx.ast, result);
//t.log("Input: " + input);
t.log("===========================================");
t.log("Iteration " + std::to_string(in.size()));
t.log("Reasoning: " + msg.reasoning_content);
t.log("Content : " + msg.content);
for (const auto & tc : msg.tool_calls) {
t.log("Tool name: " + tc.name);
t.log("Tool args: " + tc.arguments);
}
try {
// This shouldn't emit any runtime errors
auto diffs = common_chat_msg_diff::compute_diffs(prev, msg);
} catch(const std::exception & e) {
t.log(in.substr(0, result.end) + "[failed->]" + in.substr(result.end));
t.assert_true(std::string("failed with ") + e.what(), false);
}
prev = msg;
}
});
}
void test_command7_parser_compare(testing & t) {
auto parser = build_chat_peg_native_parser([](common_chat_peg_native_builder & p) {
auto thinking = p.reasoning_block(
"<|START_THINKING|>" << p.reasoning(p.until("<|END_THINKING|>")) << "<|END_THINKING|>");
auto response = "<|START_RESPONSE|>" << p.content(p.until("<|END_RESPONSE|>")) << "<|END_RESPONSE|>";
auto tool_call_id = p.atomic("\"tool_call_id\"" << (":" << ("\"" + p.tool_id(p.json_string_content()) + "\"")));
auto tool_call_name = p.atomic("\"tool_name\"" << (":" << ("\"" + p.tool_name(p.json_string_content()) + "\"")));
auto tool_call_args = "\"parameters\"" << (":" << p.tool_args(p.json()));
auto tool_call_fields = p.rule("tool-call-fields", tool_call_id | tool_call_name | tool_call_args);
auto tool_call = p.rule("tool-call", p.tool(
p.tool_open(p.literal("{"))
<< tool_call_fields
<< p.zero_or_more( p.literal(",") << tool_call_fields)
<< p.tool_close(p.literal("}"))
));
auto tool_calls = p.rule("tool-calls",
"<|START_ACTION|>"
<< ("[" << tool_call << p.zero_or_more(p.literal(",") << tool_call) << "]")
<< "<|END_ACTION|>");
return p.optional(thinking) << (tool_calls | response) + p.end();
});
auto test_current = [&](const common_peg_arena & p, const std::string & input, bool is_partial, bool print_results) {
common_peg_parse_context ctx(input, is_partial);
auto result = p.parse(ctx);
common_chat_msg msg;
auto mapper = common_chat_peg_native_mapper(msg);
mapper.from_ast(ctx.ast, result);
if (print_results) {
std::cout << "== Parsed (new) ==\n";
std::cout << "=== Reasoning ===\n";
std::cout << msg.reasoning_content << "\n";
std::cout << "\n\n=== Content ===\n";
std::cout << msg.content << "\n";
std::cout << "\n\n=== Tool Calls ===\n";
for (const auto & tc : msg.tool_calls) {
std::cout << "id: " << tc.id << "\n";
std::cout << "name: " << tc.name << "\n";
std::cout << "args: " << tc.arguments << "\n";
}
}
};
auto test_legacy = [&](const std::string & input, bool need_more_input, bool print_results) {
// Original common_chat_combinator_parser taken from chat.cpp
common_chat_msg_parser builder(
input,
/* .is_partial = */ need_more_input,
{
/* .format = */ COMMON_CHAT_FORMAT_GENERIC,
/* .reasoning_format = */ COMMON_REASONING_FORMAT_AUTO,
/* .reasoning_in_content = */ false,
/* .thinking_forced_open = */ false,
}
);
builder.try_parse_reasoning("<|START_THINKING|>", "<|END_THINKING|>");
static const common_regex start_action_regex("<\\|START_ACTION\\|>");
static const common_regex end_action_regex("<\\|END_ACTION\\|>");
static const common_regex start_response_regex("<\\|START_RESPONSE\\|>");
static const common_regex end_response_regex("<\\|END_RESPONSE\\|>");
if (auto res = builder.try_find_regex(start_action_regex)) {
// If we didn't extract thoughts, prelude includes them.
auto tool_calls = builder.consume_json_with_dumped_args({ { "parameters" } });
for (const auto & tool_call : tool_calls.value) {
std::string name = tool_call.contains("tool_name") ? tool_call.at("tool_name") : "";
std::string id = tool_call.contains("tool_call_id") ? tool_call.at("tool_call_id") : "";
std::string arguments = tool_call.contains("parameters") ? tool_call.at("parameters") : "";
if (!builder.add_tool_call(name, id, arguments) || tool_calls.is_partial) {
throw common_chat_msg_partial_exception("incomplete tool call");
}
}
if (tool_calls.is_partial) {
throw common_chat_msg_partial_exception("incomplete tool call");
}
builder.consume_regex(end_action_regex);
} else if (auto res = builder.try_find_regex(start_response_regex)) {
if (!builder.try_find_regex(end_response_regex)) {
builder.add_content(builder.consume_rest());
throw common_chat_msg_partial_exception(end_response_regex.str());
}
} else {
builder.add_content(builder.consume_rest());
}
if (print_results) {
std::cout << "== Parsed (legacy) ==\n";
std::cout << "=== Reasoning ===\n";
std::cout << builder.result().reasoning_content << "\n";
std::cout << "\n\n=== Content ===\n";
std::cout << builder.result().content << "\n";
std::cout << "\n\n=== Tool Calls ===\n";
for (const auto & tc : builder.result().tool_calls) {
std::cout << "id: " << tc.id << "\n";
std::cout << "name: " << tc.name << "\n";
std::cout << "args: " << tc.arguments << "\n";
}
}
};
std::string reasoning = "To plan an effective trip to Japan that includes both historical sites and modern attractions within a "
"budget of $4000 for a two-week stay, we need to:\n\n"
"1. Identify key historical sites and modern attractions in Japan.\n"
"2. Find affordable accommodation options that provide a balance between comfort and cost.\n"
"3. Determine the best modes of transportation for getting around Japan.\n"
"4. Create a day-by-day itinerary that ensures the user gets to see a variety of attractions without "
"overspending.\n"
"5. Provide a detailed cost breakdown that includes accommodation, transportation, meals, and entry fees "
"to attractions.";
std::vector<std::tuple<std::string, std::string, nlohmann::json>> tool_calls = {{
"call_0",
"plan_trip",
nlohmann::json::parse(R"({
"destination": "Japan",
"duration": 14,
"budget": 4000,
"interests": ["historical sites", "modern attractions"],
"accommodation_preferences": "affordable",
"transportation_preferences": "efficient",
"meal_preferences": "local cuisine"
})")
}};
std::vector<std::string> tokens;
// Build tokens
if (!reasoning.empty()) {
auto tokenized = simple_tokenize(reasoning);
tokens.emplace_back("<|START_THINKING|>");
tokens.insert(tokens.end(), tokenized.begin(), tokenized.end());
tokens.emplace_back("<|END_THINKING|>");
}
if (!tool_calls.empty()) {
tokens.emplace_back("<|START_ACTION|>");
auto json = nlohmann::json::array();
for (const auto & tc : tool_calls) {
auto tc_json = nlohmann::json::object();
tc_json["tool_call_id"] = std::get<0>(tc);
tc_json["tool_name"] = std::get<1>(tc);
tc_json["parameters"] = std::get<2>(tc);
json.push_back(tc_json);
}
auto tokenized = simple_tokenize(json.dump(-1, ' ', true));
tokens.insert(tokens.end(), tokenized.begin(), tokenized.end());
tokens.emplace_back("<|END_ACTION|>");
}
std::string input = std::accumulate(tokens.begin(), tokens.end(), std::string());
// Run tests
t.test("legacy_parse", [&](testing & /* t */) {
test_legacy(input, false, false);
});
t.test("current_parse", [&](testing & /* t */) {
test_current(parser, input, false, false);
});
// Run benchmarks
t.bench("legacy_parse_benchmark complete", [&]() {
test_legacy(input, false, false);
});
t.bench("legacy_parse_benchmark incremental", [&]() {
std::string in;
for (auto i = 0u; i < tokens.size(); i++) {
in += tokens[i];
try {
test_legacy(in, i + 1 < tokens.size(), false);
} catch (common_chat_msg_partial_exception & /* e */) {
// Do nothing, this is expected
}
}
}, 20);
t.bench("current_parse_benchmark complete", [&]() {
test_current(parser, input, false, false);
}, 100);
t.bench("current_parse_benchmark incremental", [&]() {
std::string in;
for (auto i = 0u; i < tokens.size(); i++) {
in += tokens[i];
test_current(parser, in, i + 1 < tokens.size(), false);
}
}, 20);
}