bool in_single_quoted = false;
bool in_double_quoted = false;
+ auto is_word_char = [](char ch) { return std::isalnum(static_cast<unsigned char>(ch)) || ch == '_'; };
+
for (size_t i = 0; i < input.size(); ++i) {
char c = input[i];
in_single_quoted = true;
result += '"';
}
+ } else if (!in_single_quoted && !in_double_quoted && (c == 'T' || c == 'F' || c == 'N') &&
+ (i == 0 || !is_word_char(input[i - 1]))) {
+ // Python literals -> JSON; prefix match keeps streamed partials monotonic.
+ static constexpr std::pair<std::string_view, std::string_view> literals[] = {
+ { "True", "true" }, { "False", "false" }, { "None", "null" },
+ };
+ size_t n = 0;
+ while (i + n < input.size() && is_word_char(input[i + n])) {
+ ++n;
+ }
+ std::string_view token(input.data() + i, n);
+ bool matched = false;
+ for (const auto & [py, js] : literals) {
+ if (py.substr(0, n) == token) {
+ result += js.substr(0, n);
+ i += n - 1;
+ matched = true;
+ break;
+ }
+ }
+ if (!matched) {
+ result += c;
+ }
} else {
result += c;
}
}
value_to_add += escape_json_string_inner(value_content);
} else if (!value_content.empty()) {
- // For potential containers, normalize Python-style single quotes to JSON double quotes
- bool is_potential_container = value_content[0] == '[' || value_content[0] == '{';
- if (is_potential_container) {
- value_content = normalize_container_value(value_content);
- }
- value_to_add += value_content;
+ // Pythonic scalars/containers -> JSON.
+ value_to_add += normalize_container_value(value_content);
}
args_target() += value_to_add;
return force_tool_calls ? section : optional(section);
}
+// Like python_value(), but the leaf also accepts JSON-cased true/false/null, used by LFM2/LFM2.5
+common_peg_parser common_chat_peg_builder::python_or_json_value() {
+ return rule("python-or-json-value", [this]() {
+ auto ws = space();
+ auto value = python_or_json_value();
+
+ auto member = sequence({ python_string(), ws, literal(":"), ws, value });
+ auto members = sequence({ member, zero_or_more(sequence({ ws, literal(","), ws, member })) });
+ auto dict = rule("python-or-json-dict", [&]() {
+ return sequence({ literal("{"), ws, choice({ literal("}"), sequence({ members, ws, literal("}") }) }), ws });
+ });
+
+ auto elements = sequence({ value, zero_or_more(sequence({ literal(","), ws, value })) });
+ auto array = rule("python-or-json-array", [&]() {
+ return sequence({ literal("["), ws, choice({ literal("]"), sequence({ elements, ws, literal("]") }) }), ws });
+ });
+
+ return choice({ dict, array, python_string(), python_number(),
+ python_bool(), python_null(), json_bool(), json_null() });
+ });
+}
+
// Python-style tool calls: name(arg1="value1", arg2=123)
// Used only by LFM2 for now, so we don't merge it into autoparser
common_peg_parser common_chat_peg_builder::python_style_tool_calls(
const ordered_json & tools,
- bool parallel_tool_calls) {
+ bool parallel_tool_calls,
+ bool allow_json_literals) {
if (!tools.is_array() || tools.empty()) {
return eps();
}
if (is_string_type) {
arg_value_parser = string_value_parser;
} else {
- arg_value_parser = tool_arg_value(python_value());
+ arg_value_parser = tool_arg_value(allow_json_literals ? python_or_json_value() : python_value());
}
// Full argument: name="value" or name=value
// Helper for Python-style function call format: name(arg1="value1", arg2=123)
// Used by LFM2 and similar templates
common_peg_parser python_style_tool_calls(const nlohmann::ordered_json & tools,
- bool parallel_tool_calls);
+ bool parallel_tool_calls,
+ bool allow_json_literals);
private:
+ // Python values plus JSON true/false/null.
+ common_peg_parser python_or_json_value();
+
// Implementation helpers for standard_json_tools — one per JSON tool call layout mode
common_peg_parser build_json_tools_function_is_key(const nlohmann::ordered_json & tools,
const std::string & args_key,
tagged_peg_parser build_tagged_peg_parser(
const std::function<common_peg_parser(common_peg_parser_builder & builder)> & fn);
-
return data;
}
-// LFM2 format: uses <|tool_list_start|>[...]<|tool_list_end|> in system prompt
-// and <|tool_call_start|>[name(arg="val")]<|tool_call_end|> for tool calls.
-// - Reasoning: <think>{reasoning}</think> (optional)
-// - Content: text before a tool call (optional)
-// - Tool calls: Python-style, e.g. [function_name(arg1="value1", arg2="value2")]
-// Tool calls can appear multiple times (parallel tool calls supported)
-static common_chat_params common_chat_params_init_lfm2(const common_chat_template & tmpl,
- const autoparser::generation_params & inputs) {
+// LFM2/LFM2.5 parser. Tool calls are almost Python-style and parallel-capable
+// (except dotted names and JSON literals true/false/null).
+// Always wrapped in <|tool_call_start|>[name(args)]<|tool_call_end|> with optional <think> reasoning.
+// tool_list_tokens preserves LFM2 system tool-list markers.
+static common_chat_params common_chat_params_init_lfm2(const common_chat_template & tmpl,
+ const autoparser::generation_params & inputs,
+ bool tool_list_tokens) {
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_list_start|>",
- "<|tool_list_end|>",
- "<|tool_call_start|>",
- "<|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 TOOL_CALL_START = "<|tool_call_start|>";
const std::string TOOL_CALL_END = "<|tool_call_end|>";
+ const std::string TOOL_LIST_START = "<|tool_list_start|>";
+ const std::string TOOL_LIST_END = "<|tool_list_end|>";
const std::string THINK_START = "<think>";
const std::string THINK_END = "</think>";
const std::string GEN_PROMPT = "<|im_start|>assistant\n";
+ 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_CALL_START, TOOL_CALL_END, THINK_START, THINK_END };
+ if (tool_list_tokens) {
+ data.preserved_tokens.push_back(TOOL_LIST_START);
+ data.preserved_tokens.push_back(TOOL_LIST_END);
+ }
+
data.thinking_start_tag = THINK_START;
data.thinking_end_tag = THINK_END;
+ 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;
+
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
auto tool_calls = p.rule("tool-calls",
p.trigger_rule("tool-call",
p.literal(TOOL_CALL_START) +
- p.python_style_tool_calls(inputs.tools, inputs.parallel_tool_calls) +
+ p.python_style_tool_calls(inputs.tools, inputs.parallel_tool_calls, /* allow_json_literals = */ true) +
p.literal(TOOL_CALL_END)
)
);
{ COMMON_GRAMMAR_TRIGGER_TYPE_WORD, TOOL_CALL_START }
};
}
- return data;
-}
-
-// LFM2.5 format: uses plain "List of tools: [...]" in system prompt, no wrapper tokens.
-// Tool calls are bare [name(arg="val")], though model may optionally emit <|tool_call_start|>.
-// - Reasoning: <think>{reasoning}</think> (optional)
-// - Content: text before a tool call (optional)
-// - Tool calls: Python-style, e.g. [function_name(arg1="value1", arg2="value2")]
-// Tool calls can appear multiple times (parallel tool calls supported)
-static common_chat_params common_chat_params_init_lfm2_5(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_call_start|>",
- "<|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 THINK_START = "<think>";
- const std::string THINK_END = "</think>";
- const std::string GEN_PROMPT = "<|im_start|>assistant\n";
-
- data.thinking_start_tag = THINK_START;
- data.thinking_end_tag = 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) {
- auto generation_prompt = p.literal(GEN_PROMPT);
- auto end = p.end();
-
- auto reasoning = p.eps();
- if (extract_reasoning && inputs.enable_thinking) {
- reasoning = p.optional(THINK_START + p.reasoning(p.until(THINK_END)) + THINK_END);
- }
-
- if (!has_tools || inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_NONE) {
- return generation_prompt + reasoning + p.content(p.rest()) + end;
- }
-
- auto tool_calls = p.rule("tool-calls",
- p.trigger_rule("tool-call",
- p.python_style_tool_calls(inputs.tools, inputs.parallel_tool_calls)
- )
- );
-
- auto content = p.content(p.until_one_of({"<|tool_call_start|>", "["}));
- auto maybe_start = p.optional(p.literal("<|tool_call_start|>"));
- return generation_prompt + reasoning + content + maybe_start + 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);
- });
- foreach_function(inputs.tools, [&](const json & tool) {
- const std::string name = tool.at("function").at("name");
- data.grammar_triggers.push_back({ COMMON_GRAMMAR_TRIGGER_TYPE_WORD, "[" + name + "(" });
- });
- }
return data;
}
if (is_lfm2_template(src)) {
LOG_DBG("Using specialized template: LFM2\n");
- return common_chat_params_init_lfm2(tmpl, params);
+ return common_chat_params_init_lfm2(tmpl, params, /* tool_list_tokens = */ true);
}
// LFM2.5 format detection: template uses plain "List of tools: [...]" with no special tokens
if (src.find("List of tools: [") != std::string::npos &&
src.find("<|tool_list_start|>") == std::string::npos) {
LOG_DBG("Using specialized template: LFM2.5\n");
- return common_chat_params_init_lfm2_5(tmpl, params);
+ return common_chat_params_init_lfm2(tmpl, params, /* tool_list_tokens = */ false);
}
// GigaChatV3 format detection
})",
};
+static common_chat_tool calendar_create_event_tool{
+ /* .name = */ "Calendar.create_event",
+ /* .description = */ "Create a calendar event",
+ /* .parameters = */ R"({
+ "type": "object",
+ "properties": {
+ "title": { "type": "string" },
+ "participants": { "type": "array", "items": { "type": "string" } },
+ "metadata": { "type": "object" }
+ },
+ "required": ["title", "participants", "metadata"]
+ })",
+};
+
static common_chat_tool imaginary_number_tool{
/* .name = */ "imaginary_number",
/* .description = */ "Imaginary number converter",
.run();
}
- // LFM2.5 tests - uses plain "List of tools: [...]" and bare [name(args)] without wrapper tokens
+ // LFM2.5 tests - format <|tool_call_start|>[name(args)]<|tool_call_end|>
{
auto tst = peg_tester("models/templates/LFM2.5-Instruct.jinja", detailed_debug);
tst.test("Hello, world!\nWhat's up?").expect(message_assist).run();
// Single tool call without reasoning
- tst.test("[special_function(arg1=1)]")
+ tst.test("<|tool_call_start|>[special_function(arg1=1)]<|tool_call_end|>")
.tools({ special_function_tool })
.expect(message_assist_call)
.run();
// Tool call with string argument
- tst.test("[get_time(city=\"XYZCITY\")]")
+ tst.test("<|tool_call_start|>[get_time(city=\"XYZCITY\")]<|tool_call_end|>")
.tools({ get_time_tool })
.expect(message_with_tool_calls("get_time", "{\"city\":\"XYZCITY\"}"))
.run();
+ // Python literals become JSON.
+ tst.test("<|tool_call_start|>[toggle(enabled=True)]<|tool_call_end|>")
+ .tools({ toggle_tool })
+ .expect(message_with_tool_calls("toggle", R"({"enabled": true})"))
+ .run();
+
+ tst.test("<|tool_call_start|>[set_nullable(value=None)]<|tool_call_end|>")
+ .tools({ nullable_tool })
+ .expect(message_with_tool_calls("set_nullable", R"({"value": null})"))
+ .run();
+
+ // Nested Python literal.
+ tst.test("<|tool_call_start|>[set_config(config={\"enabled\": True, \"count\": 3})]<|tool_call_end|>")
+ .tools({ config_tool })
+ .expect(message_with_tool_calls("set_config", R"({"config": {"enabled": true, "count": 3}})"))
+ .run();
+
+ // JSON literals are accepted too.
+ tst.test("<|tool_call_start|>[set_config(config={\"enabled\": true, \"note\": null})]<|tool_call_end|>")
+ .tools({ config_tool })
+ .expect(message_with_tool_calls("set_config", R"({"config": {"enabled": true, "note": null}})"))
+ .run();
+
+ // Dotted function name with structured args.
+ tst.test("<|tool_call_start|>[Calendar.create_event(title=\"demo\", participants=[\"Alice\", \"Bob\"], "
+ "metadata={\"priority\": \"high\", \"reminder\": true})]<|tool_call_end|>")
+ .tools({ calendar_create_event_tool })
+ .expect(message_with_tool_calls(
+ "Calendar.create_event",
+ R"({"title": "demo", "participants": ["Alice", "Bob"], "metadata": {"priority": "high", "reminder": true}})"))
+ .run();
+
+ // Markdown links stay content.
+ tst.test("Use this format: [link text](url). Example: [Wikipedia](https://www.wikipedia.org).")
+ .tools({ get_time_tool })
+ .expect(simple_assist_msg("Use this format: [link text](url). Example: [Wikipedia](https://www.wikipedia.org)."))
+ .run();
+
// Tool call with reasoning (enable_thinking=true)
- tst.test("<think>I'm\nthinking</think>[special_function(arg1=1)]")
+ tst.test("<think>I'm\nthinking</think><|tool_call_start|>[special_function(arg1=1)]<|tool_call_end|>")
.enable_thinking(true)
.reasoning_format(COMMON_REASONING_FORMAT_AUTO)
.tools({ special_function_tool })
.run();
// Multiple tool calls (parallel)
- tst.test("[special_function(arg1=1), special_function_with_opt(arg1=1, arg2=2)]")
+ tst.test("<|tool_call_start|>[special_function(arg1=1), special_function_with_opt(arg1=1, arg2=2)]<|tool_call_end|>")
.parallel_tool_calls(true)
.tools({
special_function_tool, special_function_tool_with_optional_param
.run();
// Tool call with content before tool call
- tst.test("Let me check the time.[get_time(city=\"Paris\")]")
+ tst.test("Let me check the time.<|tool_call_start|>[get_time(city=\"Paris\")]<|tool_call_end|>")
.tools({ get_time_tool })
.expect(message_with_reasoning_content_and_multiple_tool_calls(
"", "Let me check the time.", { { "get_time", "{\"city\":\"Paris\"}" } }
.run();
// Partial tool call (streaming)
- tst.test("[special_function(arg1=")
+ tst.test("<|tool_call_start|>[special_function(arg1=")
.tools({ special_function_tool })
.is_partial(true)
.expect(simple_assist_msg("", "", "special_function", "{\"arg1\": "))
.run();
// Tool call with empty arguments
- tst.test("[empty_args()]")
+ tst.test("<|tool_call_start|>[empty_args()]<|tool_call_end|>")
.tools({ empty_args_tool })
.expect(simple_assist_msg("", "", "empty_args", "{}"))
.run();
overview / pkg / ggml / sources / llama.cpp / commitdiff