mirror of
https://github.com/ggerganov/llama.cpp
synced 2026-03-03 21:59:44 +01:00
* common : implement parser combinators to simplify chat parsing * add virtual destructor to parser_base * fix memory leak from circular references of rules * implement gbnf grammar building * remove unused private variable * create a base visitor and implement id assignment as a visitor * fix const ref for grammar builder * clean up types, friend classes, and class declarations * remove builder usage from until_parser * Use a counter class to help assign rule ids * cache everything * add short description for each parser * create a type for the root parser * implement repetition parser * Make optional, one_or_more, and zero_or_more subclasses of repetition * improve context constructor * improve until parsing and add benchmarks * remove cached() pattern, cache in parser_base with specialized parsing functions for each parser * improve json parsing performance to better match legacy parsing * fix const auto * it for windows * move id assignment to classes instead of using a visitor * create named rules in the command r7b example * use '.' for any in GBNF * fix parens around choices in gbnf grammar * add convenience operators to turn strings to literals * add free-form operators for const char * to simplify defining literals * simplify test case parser * implement semantic actions * remove groups in favor of actions and a scratchpad * add built in actions for common operations * add actions to command r7b example * use std::default_searcher for platforms that don't have bm * improve parser_type handling and add cast helper * add partial result type to better control when to run actions * fix bug in until() * run actions on partial results by default * use common_chat_msg for result * add qwen3 example wip * trash partial idea and simplify * move action arguments to a struct * implement aho-corasick matcher for until_parser and to build exclusion grammars * use std::string for input, since std::string_view is incompatible with std::regex * Refactor tests * improve qwen3 example * implement sax-style parsing and refactor * fix json string in test * rename classes to use common_chat_ prefix * remove is_ suffix from functions * rename from id_counter to just counter * Final refactored tests * Fix executable name and editorconfig-checker * Third time's the charm... * add trigger parser to begin lazy grammar rule generation * working lazy grammar * refactor json rules now that we check for reachability * reduce pointer usage * print out grammars in example * rename to chat-peg-parser* and common_chat_peg_parser* * Revert unrelated changes * New macros for CMakeLists to enable multi-file compilations * starting unicode support * add unicode support to char_parser * use unparsed args as additional sources * Refactor tests to new harness * Fix CMakeLists * fix rate calculation * add unicode tests * fix trailing whitespace and line endings skip-checks: true * Helpers + rewrite qwen3 with helpers * Fix whitespace * extract unicode functions to separate file * refactor parse unicode function * fix compiler error * improve construction of sequence/choice parsers * be less clever * add make_parser helper function * expand usage of make_parser, alias common_chat_msg_peg_parser_builder to builder in source * lower bench iterations * add unicode support to until_parser * add unicode support to json_string_parser * clean up unicode tests * reduce unicode details to match src/unicode.cpp * simplify even further * remove unused functions * fix type * reformat char class parsing * clean up json string parser * clean up + fix diagnostics * reorder includes * compact builder functions * replace action_parser with capture_parser, rename env to semantics * rename env to semantics * clean up common_chat_parse_context * move type() to below constant * use default constructor for common_chat_peg_parser * make all operators functions for consistency * fix compilation errors in test-optional.cpp * simplify result values * rename json_string_unquoted to json_string_content * Move helper to separate class, add separate explicit and helper classes * Whitespace * Change + to append() * Reformat * Add extra helpers, tests and Minimax example * Add some extra optional debugging prints + real example of how to use them * fix bug in repetitions when min_count = 0 reports failures * dump rule in debug * fix token accumulation and assert parsing never fails * indent debug by depth * use LOG_* in tests so logs sync up with test logs * - Add selective testing - Refactor all messaging to use LOG_ERR - Fix lack of argument / tool name capturing - Temporary fix for double event capture * refactor rule() and introduce ref() * clean up visitor * clean up indirection in root parser w.r.t rules * store shared ptr directly in parser classes * replace aho-corasick automation with a simple trie * Reset prev for qwen3 helper example variant * refactor to use value semantics with std::variant/std::visit * simplify trie_matcher result * fix linting issues * add annotations to rules * revert test workaround * implement serializing the parser * remove redundant parsers * remove tests * gbnf generation fixes * remove LOG_* use in tests * update gbnf tests to test entire grammar * clean up gbnf generation and fix a few bugs * fix typo in test output * remove implicit conversion rules * improve test output * rename trie_matcher to trie * simplify trie to just know if a node is the end of a word * remove common_chat_ prefix and ensure a common_peg_ prefix to all types * rename chat-peg-parser -> peg-parser * promote chat-peg-parser-helper to chat-peg-parser * checkpoint * use a static_assert to ensure we handle every branch * inline trivial peg parser builders * use json strings for now * implement basic and native chat peg parser builders/extractors * resolve refs to their rules * remove packrat caching (for now) * update tests * compare parsers with incremental input * benchmark both complete and incremental parsing * add raw string generation from json schema * add support for string schemas in gbnf generation * fix qwen example to include \n * tidy up example * rename extractor to mapper * rename ast_arena to ast * place basic tests into one * use gbnf_format_literal from json-schema-to-grammar * integrate parser with common/chat and server * clean up schema and serialization * add json-schema raw string tests * clean up json creation and remove capture parser * trim spaces from reasoning and content * clean up redundant rules and comments * rename input_is_complete to is_partial to match rest of project * simplify json rules * remove extraneous file * remove comment * implement += and |= operators * add comments to qwen3 implementation * reorder arguments to common_chat_peg_parse * remove commented outdated tests * add explicit copy constructor * fix operators and constness * wip: update test-chat for qwen3-coder * bring json parser closer to json-schema-to-grammar rules * trim trailing space for most things * fix qwen3 coder rules w.r.t. trailing spaces * group rules * do not trim trailing space from string args * tweak spacing of qwen3 grammar * update qwen3-coder tests * qwen3-coder small fixes * place parser in common_chat_syntax to simplify invocation * use std::set to collect rules to keep order predictable for tests * initialize parser to make certain platforms happy * revert back to std::unordered_set, sort rule names at the end instead * uncomment rest of chat tests * define explicit default constructor * improve arena init and server integration * fix chat test * add json_member() * add a comprehensive native example * clean up example qwen test and add response_format example to native test * make build_peg_parser accept std::function instead of template * change peg parser parameters into const ref * push tool call on tool open for constructed parser * add parsing documentation * clean up some comments * add json schema support to qwen3-coder * add id initializer in tests * remove grammar debug line from qwen3-coder * refactor qwen3-coder to use sequence over operators * only call common_chat_peg_parse if appropriate format * simplify qwen3-coder space handling * revert qwen3-coder implementation * revert json-schema-to-grammar changes * remove unnecessary forward declaration * small adjustment to until_parser * rename C/C++ files to use dashes * codeowners : add aldehir to peg-parser and related files --------- Co-authored-by: Piotr Wilkin <piotr.wilkin@syndatis.com>
769 lines
32 KiB
C++
769 lines
32 KiB
C++
#include <string>
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#include <iostream>
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#include <numeric>
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#include "chat-parser.h"
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#include "chat-peg-parser.h"
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#include "chat.h"
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#include "common.h"
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#include "json-schema-to-grammar.h"
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#include "peg-parser.h"
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#include "peg-parser/testing.h"
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#include "peg-parser/simple-tokenize.h"
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#include "nlohmann/json.hpp"
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using json = nlohmann::ordered_json;
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static json create_tools();
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static void test_example_native(testing & t);
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static void test_example_qwen3_coder(testing & t);
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static void test_command7_parser_compare(testing & t);
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int main(int argc, char *argv[]) {
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testing t(std::cout);
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if (argc >= 2) {
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t.set_filter(argv[1]);
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}
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const char * verbose = getenv("LLAMA_TEST_VERBOSE");
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if (verbose) {
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t.verbose = std::string(verbose) == "1";
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}
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t.test("native", test_example_native);
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t.test("qwen3 coder", test_example_qwen3_coder);
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t.test("comparison", test_command7_parser_compare);
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return t.summary();
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}
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static json create_tools() {
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json tools = json::array();
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json tool_weather = {
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{"type", "function"},
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{"function", {
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{"name", "get_current_weather"},
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{"description", "Get the current weather in a given location"},
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{"parameters", {
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{"type", "object"},
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{"properties", {
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{"location", {
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{"type", "string"},
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{"description", "The city and state, e.g. San Francisco, CA"}
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}},
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{"unit", {
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{"type", "string"},
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{"enum", {"celsius", "fahrenheit"}},
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{"description", "The temperature unit to use. Infer this from the users location."}
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}}
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}},
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{"required", {"location", "unit"}},
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}},
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}}
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};
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tools.push_back(tool_weather);
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json tool_forecast = {
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{"type", "function"},
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{"function", {
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{"name", "get_forecast"},
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{"description", "Get the weather forecast for a given location"},
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{"parameters", {
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{"type", "object"},
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{"properties", {
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{"location", {
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{"type", "string"},
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{"description", "The city and state, e.g. San Francisco, CA"}
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}},
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{"unit", {
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{"type", "string"},
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{"enum", {"celsius", "fahrenheit"}},
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{"description", "The temperature unit to use. Infer this from the users location."}
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}},
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{"days", {
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{"type", "integer"},
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{"description", "Number of days to forecast (1-10)"},
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{"minimum", 1},
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{"maximum", 10}
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}}
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}},
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{"required", {"location", "unit"}},
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}},
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}}
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};
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tools.push_back(tool_forecast);
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json tool_search = {
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{"type", "function"},
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{"function", {
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{"name", "search_knowledge_base"},
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{"description", "Search the internal technical documentation knowledge base."},
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{"parameters", {
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{"type", "object"},
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{"properties", {
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{"query", {
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{"type", "string"},
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{"description", "The search query string."}
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}},
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{"max_results", {
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{"type", "integer"},
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{"description", "The maximum number of results to return."},
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{"default", 5}
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}},
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{"category", {
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{"type", "string"},
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{"enum", {"api", "troubleshooting", "billing", "general"}},
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{"description", "Filter search by specific category."}
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}}
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}},
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{"required", {"query", "category"}},
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{"additionalProperties", false}
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}},
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{"strict", true}
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}}
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};
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tools.push_back(tool_search);
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return tools;
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}
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struct tool_argument {
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std::string name;
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std::string type;
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bool is_required;
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json schema;
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};
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struct tool_definition {
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std::string name;
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std::vector<tool_argument> arguments;
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json schema;
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};
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// Test fictitious model output that emits arguments as JSON.
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static void test_example_native(testing & t) {
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struct test_case {
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// Parameters
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std::string name;
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json tools;
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common_chat_tool_choice tool_choice;
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common_reasoning_format reasoning_format;
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json json_schema;
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bool parallel_tool_calls;
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bool thinking_forced_open;
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std::string input;
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// Expect
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std::string expect_reasoning;
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std::string expect_content;
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std::vector<common_chat_tool_call> expect_tool_calls;
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};
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auto build_parser = [](const test_case & tc) {
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return build_chat_peg_native_parser([&](common_chat_peg_native_builder & p) {
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auto reasoning_in_content = (tc.reasoning_format == COMMON_REASONING_FORMAT_NONE);
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auto reasoning = p.eps();
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if (tc.thinking_forced_open) {
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// If thinking is forced open, expect a closing tag
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reasoning = p.reasoning(p.until("</think>")) + "</think>" + p.space();
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} else {
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// Otherwise, optionally accept thinking wrapped in tags
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reasoning = p.optional("<think>" + p.reasoning(p.until("</think>")) + "</think>" + p.space());
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}
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// tool calling parser
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if (tc.tools.is_array() && !tc.tools.empty()) {
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auto tools = p.choice();
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for (const auto & tool : tc.tools) {
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const auto & function = tool.at("function");
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std::string name = function.at("name");
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const auto & schema = function.at("parameters");
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auto tool_name = p.json_member("name", "\"" + p.tool_name(p.literal(name)) + "\"");
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auto tool_args = p.json_member("arguments", p.tool_args(p.schema(p.json(), "tool-" + name + "-schema", schema)));
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tools |= p.rule("tool-" + name, p.tool_open(p.literal("{")) << tool_name << "," << tool_args << "}");
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};
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auto parallel_calls = p.eps();
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if (tc.parallel_tool_calls) {
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parallel_calls = p.zero_or_more("," << tools);
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}
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auto tool_call = p.trigger_rule("tool-call",
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p.sequence({
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p.literal("<tool_call>["),
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tools,
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parallel_calls,
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p.literal("]</tool_call>")
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})
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);
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return p.sequence({
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(reasoning_in_content ? p.eps() : reasoning),
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p.content(p.until("<tool_call>")),
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p.optional(p.space() + tool_call),
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p.space(),
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p.end()
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});
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}
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// response_format parser
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if (tc.json_schema.is_object() && !tc.json_schema.empty()) {
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return p.sequence({
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(reasoning_in_content ? p.eps() : reasoning),
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p.content(p.schema(p.json(), "response-output", tc.json_schema)),
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p.space(),
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p.end()
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});
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}
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// Content-only parser
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return p.sequence({
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(reasoning_in_content ? p.eps() : reasoning),
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p.content(p.rest()),
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p.end()
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});
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});
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};
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std::vector<test_case> test_cases = std::vector<test_case>{
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{
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/* .name = */ "content with thinking_forced_open = false",
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/* .tools = */ {},
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/* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_NONE,
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/* .reasoning_format = */ COMMON_REASONING_FORMAT_AUTO,
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/* .json_schema = */ {},
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/* .parallel_tool_calls = */ false,
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/* .thinking_forced_open = */ false,
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/* .input = */ (
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"<think>The user said hello, I must say hello back</think>\nHello"
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),
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/* .expect_reasoning = */ "The user said hello, I must say hello back",
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/* .expect_content = */ "Hello",
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/* .expect_tool_calls = */ {},
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},
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{
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/* .name = */ "content with thinking_forced_open = false and no reasoning",
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/* .tools = */ {},
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/* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_NONE,
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/* .reasoning_format = */ COMMON_REASONING_FORMAT_AUTO,
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/* .json_schema = */ {},
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/* .parallel_tool_calls = */ false,
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/* .thinking_forced_open = */ false,
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/* .input = */ (
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"Hello"
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),
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/* .expect_reasoning = */ "",
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/* .expect_content = */ "Hello",
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/* .expect_tool_calls = */ {},
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},
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{
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/* .name = */ "content with thinking_forced_open = false and reasoning_format = none",
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/* .tools = */ {},
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/* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_NONE,
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/* .reasoning_format = */ COMMON_REASONING_FORMAT_NONE,
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/* .json_schema = */ {},
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/* .parallel_tool_calls = */ false,
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/* .thinking_forced_open = */ true,
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/* .input = */ (
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"<think>The user said hello, I must say hello back</think>\nHello"
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),
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/* .expect_reasoning = */ "",
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/* .expect_content = */ "<think>The user said hello, I must say hello back</think>\nHello",
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/* .expect_tool_calls = */ {},
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},
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{
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/* .name = */ "content with thinking_forced_open = true",
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/* .tools = */ {},
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/* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_NONE,
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/* .reasoning_format = */ COMMON_REASONING_FORMAT_AUTO,
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/* .json_schema = */ {},
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/* .parallel_tool_calls = */ false,
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/* .thinking_forced_open = */ true,
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/* .input = */ (
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"The user said hello, I must say hello back</think>\nHello"
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),
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/* .expect_reasoning = */ "The user said hello, I must say hello back",
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/* .expect_content = */ "Hello",
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/* .expect_tool_calls = */ {},
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},
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{
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/* .name = */ "content with thinking_forced_open = true and reasoning_format = none",
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/* .tools = */ {},
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/* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_NONE,
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/* .reasoning_format = */ COMMON_REASONING_FORMAT_NONE,
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/* .json_schema = */ {},
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/* .parallel_tool_calls = */ false,
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/* .thinking_forced_open = */ true,
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/* .input = */ (
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"The user said hello, I must say hello back</think>\nHello"
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),
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/* .expect_reasoning = */ "",
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/* .expect_content = */ "The user said hello, I must say hello back</think>\nHello",
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/* .expect_tool_calls = */ {},
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},
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{
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/* .name = */ "tools with tool_choice = auto and no parallel_tool_calls",
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/* .tools = */ create_tools(),
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/* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_AUTO,
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/* .reasoning_format = */ COMMON_REASONING_FORMAT_AUTO,
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/* .json_schema = */ {},
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/* .parallel_tool_calls = */ false,
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/* .thinking_forced_open = */ true,
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/* .input = */ (
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"I must get the weather in New York</think>\n"
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"<tool_call>["
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R"({"name": "get_current_weather", "arguments": {"location": "New York City, NY", "unit": "fahrenheit"}})"
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"]</tool_call>"
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),
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/* .expect_reasoning = */ "I must get the weather in New York",
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/* .expect_content = */ "",
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/* .expect_tool_calls = */ {{
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/* .name = */ "get_current_weather",
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/* .arguments = */ R"({"location": "New York City, NY", "unit": "fahrenheit"})",
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/* .id = */ "",
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}},
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},
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{
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/* .name = */ "tools with tool_choice = auto and parallel_tool_calls",
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/* .tools = */ create_tools(),
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/* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_AUTO,
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/* .reasoning_format = */ COMMON_REASONING_FORMAT_AUTO,
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/* .json_schema = */ {},
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/* .parallel_tool_calls = */ true,
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/* .thinking_forced_open = */ true,
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/* .input = */ (
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"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."
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"<tool_call>["
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R"({"name": "get_current_weather", "arguments": {"location": "New York City, NY", "unit": "fahrenheit"}})"
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", "
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R"({"name": "get_current_weather", "arguments": {"location": "San Francisco, CA", "unit": "fahrenheit"}})"
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", "
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R"({"name": "get_forecast", "arguments": {"location": "New York City, NY", "unit": "fahrenheit", "days": 3}})"
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", "
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R"({"name": "get_forecast", "arguments": {"location": "San Francisco, CA", "unit": "fahrenheit", "days": 3}})"
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"]</tool_call>"
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),
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/* .expect_reasoning = */ "I must get the weather in New York and San Francisco and a 3 day forecast of each.",
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/* .expect_content = */ "Let me search that for you.",
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/* .expect_tool_calls = */ {{
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/* .name = */ "get_current_weather",
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/* .arguments = */ R"({"location": "New York City, NY", "unit": "fahrenheit"})",
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/* .id = */ "",
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}, {
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/* .name = */ "get_current_weather",
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/* .arguments = */ R"({"location": "San Francisco, CA", "unit": "fahrenheit"})",
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/* .id = */ "",
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}, {
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/* .name = */ "get_forecast",
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/* .arguments = */ R"({"location": "New York City, NY", "unit": "fahrenheit", "days": 3})",
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/* .id = */ "",
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}, {
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/* .name = */ "get_forecast",
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/* .arguments = */ R"({"location": "San Francisco, CA", "unit": "fahrenheit", "days": 3})",
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/* .id = */ "",
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}},
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},
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{
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/* .name = */ "response_format with thinking_forced_open = true",
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/* .tools = */ {},
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/* .tool_choice = */ COMMON_CHAT_TOOL_CHOICE_NONE,
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/* .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);
|
|
}
|