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3 Commits

Author SHA1 Message Date
Andy Williams 7e4c0a9688 chat : pass reasoning_effort to template
* chat: add reasoning_effort to common_chat_templates_inputs

Store OpenAI Chat Completions reasoning_effort and make it
available to jinja templates (with model specific translations
where required).

Assisted-by: llama.cpp:Muse-Glimmer-30B

* server : fixup reading reasoning effort from body

server_chat_convert_responses_to_chatcmpl already handles conversion of
Responses API reasoning.effort to reasoning_effort

* chat : expose reasoning effort

Assisted-by: Claude Opus 5

* chat : add reasoning_effort to generation_params

Assisted-by: Claude Opus 5

* chat : move reasoning_effort next to enable_thinking

Assisted-by: Claude Opus 5

* cont : mirror preserve_reasoning

* cont : pass context through analyze function

---------

Co-authored-by: Alde Rojas <hello@alde.dev>
2026-08-14 13:23:11 -05:00
Georgi Gerganov 9b05354ec6 sync : ggml 2026-08-14 19:06:19 +03:00
Georgi Gerganov 06ae2326ba ggml : bump version to 0.20.0 (ggml/1584) 2026-08-14 19:06:19 +03:00
11 changed files with 91 additions and 13 deletions
+12
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@@ -3646,6 +3646,18 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
}
}
).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_REASONING"));
add_opt(common_arg(
{"--reasoning-effort"}, "LEVEL",
"reasoning effort level given to the chat template: 'default' to keep the template default,\n"
"or a level such as 'minimal', 'low', 'medium', 'high', 'xhigh' or 'max' (default: default)",
[](common_params & params, const std::string & value) {
if (value == "default") {
params.default_template_kwargs.erase("reasoning_effort");
} else {
params.default_template_kwargs["reasoning_effort"] = json(value).dump();
}
}
).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_REASONING_EFFORT"));
add_opt(common_arg(
{"--reasoning-budget"}, "N",
"token budget for thinking: -1 for unrestricted, 0 for immediate end, N>0 for token budget (default: -1)",
+4
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@@ -920,6 +920,10 @@ static std::string common_chat_template_direct_apply_impl(
bool enabled = inp["preserve_reasoning"].get<bool>();
jinja::caps_apply_preserve_reasoning(ctx, enabled);
}
if (inp.contains("reasoning_effort") && inp["reasoning_effort"].is_string() && !inp["reasoning_effort"].empty()) {
std::string reasoning_effort = inp["reasoning_effort"].get<std::string>();
jinja::caps_apply_reasoning_effort(ctx, reasoning_effort);
}
jinja::global_from_json(ctx, inp, inputs.mark_input);
+41 -8
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@@ -17,7 +17,7 @@ namespace jinja {
using caps_json_fn = std::function<json()>;
using caps_ctx_fn = std::function<void(context &)>;
using caps_analyze_fn = std::function<void(bool, value &, value &, const std::string &)>;
using caps_analyze_fn = std::function<void(context &, bool, value &, value &, const std::string &)>;
void caps_apply_preserve_reasoning(jinja::context & ctx, bool enabled) {
ctx.set_val("preserve_thinking", mk_val<value_bool>(enabled));
@@ -26,6 +26,12 @@ void caps_apply_preserve_reasoning(jinja::context & ctx, bool enabled) {
ctx.set_val("drop_thinking", mk_val<value_bool>(!enabled));
}
void caps_apply_reasoning_effort(jinja::context & ctx, const std::string & effort) {
value var = mk_val<value_string>(effort); // bind to the same value for stats
ctx.set_val("reasoning_effort", var);
ctx.set_val("reasoning_strength", var);
}
static void caps_try_execute(jinja::program & prog,
const caps_json_fn & messages_fn,
const caps_ctx_fn & ctx_fn,
@@ -62,7 +68,7 @@ static void caps_try_execute(jinja::program & prog,
// ignore exceptions during capability analysis
}
analyze_fn(success, messages, tools, result);
analyze_fn(ctx, success, messages, tools, result);
}
// for debugging only
@@ -87,6 +93,7 @@ std::map<std::string, bool> caps::to_map() const {
{"supports_parallel_tool_calls", supports_parallel_tool_calls},
{"supports_system_role", supports_system_role},
{"supports_preserve_reasoning", supports_preserve_reasoning},
{"supports_reasoning_effort", supports_reasoning_effort},
{"supports_object_arguments", supports_object_arguments},
};
}
@@ -124,7 +131,7 @@ caps caps_get(jinja::program & prog) {
},
nullptr, // ctx_fn
nullptr, // tools_fn
[&](bool success, value & messages, value &, const std::string &) {
[&](context &, bool success, value & messages, value &, const std::string &) {
auto & content = messages->at(0)->at("content");
caps_print_stats(content, "messages[0].content");
if (has_op(content, "selectattr") || has_op(content, "array_access")) {
@@ -158,7 +165,7 @@ caps caps_get(jinja::program & prog) {
},
nullptr, // ctx_fn
nullptr, // tools_fn
[&](bool, value & messages, value &, const std::string &) {
[&](context &, bool, value & messages, value &, const std::string &) {
auto & content = messages->at(0)->at("content");
caps_print_stats(content, "messages[0].content");
if (!content->stats.used) {
@@ -234,7 +241,7 @@ caps caps_get(jinja::program & prog) {
},
});
},
[&](bool success, value & messages, value & tools, const std::string &) {
[&](context &, bool success, value & messages, value & tools, const std::string &) {
if (!success) {
return; // Nothing can be inferred
}
@@ -327,7 +334,7 @@ caps caps_get(jinja::program & prog) {
},
});
},
[&](bool success, value & messages, value & tools, const std::string &) {
[&](context &, bool success, value & messages, value & tools, const std::string &) {
if (!success) {
result.supports_tool_calls = false;
result.supports_tools = false;
@@ -429,7 +436,7 @@ caps caps_get(jinja::program & prog) {
},
});
},
[&](bool success, value & messages, value &, const std::string &) {
[&](context &, bool success, value & messages, value &, const std::string &) {
if (!success) {
result.supports_parallel_tool_calls = false;
return;
@@ -486,7 +493,7 @@ caps caps_get(jinja::program & prog) {
caps_apply_preserve_reasoning(ctx, true);
},
nullptr, // tools_fn
[&](bool, value &, value &, const std::string & output) {
[&](context &, bool, value &, value &, const std::string & output) {
// note: we cannot use stats here because the reasoning_content may be used for "if" condition test, but not actually outputted in the final result
if (output.find(reasoning_placeholder) != std::string::npos) {
result.supports_preserve_reasoning = true;
@@ -494,6 +501,32 @@ caps caps_get(jinja::program & prog) {
}
);
JJ_DEBUG("%s\n", ">>> Running capability check: reasoning effort");
// case: reasoning effort level
caps_try_execute(
prog,
[&]() {
// messages
return json::array({
{
{"role", "user"},
{"content", "User message"}
},
});
},
[&](context & ctx) {
ctx.set_val("enable_thinking", mk_val<value_bool>(true));
caps_apply_reasoning_effort(ctx, "low");
},
nullptr, // tools_fn
[&](context & ctx, bool, value &, value &, const std::string &) {
value effort = ctx.get_val("reasoning_effort");
caps_print_stats(effort, "reasoning_effort");
result.supports_reasoning_effort = effort->stats.used;
}
);
JJ_DEBUG("%s\n", result.to_string().c_str());
return result;
+4
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@@ -16,6 +16,9 @@ struct caps {
// supports preserve reasoning trace in the full history, not just the last assistant message
bool supports_preserve_reasoning = false;
// supports reasoning effort levels
bool supports_reasoning_effort = false;
// one of the 2 content capabilities must be true
bool supports_string_content = true;
bool supports_typed_content = false;
@@ -32,5 +35,6 @@ struct caps {
caps caps_get(jinja::program & prog);
void caps_apply_preserve_reasoning(jinja::context & ctx, bool enabled);
void caps_apply_reasoning_effort(jinja::context & ctx, const std::string & effort);
} // namespace jinja
+1 -1
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@@ -4,7 +4,7 @@ project("ggml" C CXX ASM)
### GGML Version
set(GGML_VERSION_MAJOR 0)
set(GGML_VERSION_MINOR 19)
set(GGML_VERSION_MINOR 20)
set(GGML_VERSION_PATCH 0)
set(GGML_VERSION_BASE "${GGML_VERSION_MAJOR}.${GGML_VERSION_MINOR}.${GGML_VERSION_PATCH}")
+1 -1
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@@ -1 +1 @@
8846b79e66747bb9f68597420e95114c177315ce
2d191b5dee1a591c41ee8a653ce42bfcd9c8716d
+19
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@@ -6955,6 +6955,24 @@ static void test_reasoning_budget_message_per_request() {
}
}
static void test_reasoning_effort_caps() {
LOG_DBG("%s\n", __func__);
auto assert_supports_effort = [](const std::string & path, bool expected) {
auto tmpls = read_templates(path);
assert_equals(expected, common_chat_templates_get_caps(tmpls.get()).at("supports_reasoning_effort"));
};
assert_supports_effort("models/templates/deepseek-ai-DeepSeek-V4.jinja", true);
assert_supports_effort("models/templates/muse-glimmer.jinja", true);
assert_supports_effort("models/templates/tencent-Hy3.jinja", true);
assert_supports_effort("models/templates/openai-gpt-oss-120b.jinja", true);
assert_supports_effort("models/templates/upstage-Solar-Open-100B.jinja", true);
assert_supports_effort("models/templates/Cohere2MoE.jinja", true);
assert_supports_effort("models/templates/meta-llama-Llama-3.1-8B-Instruct.jinja", false);
assert_supports_effort("models/templates/Qwen-Qwen3-0.6B.jinja", false);
}
static void test_msg_diffs_compute() {
LOG_DBG("%s\n", __func__);
{
@@ -7114,6 +7132,7 @@ int main(int argc, char ** argv) {
test_deepseek_v4_thinking_retention();
test_deepseek_v4_tool_result_ordering();
test_template_generation_prompt();
test_reasoning_effort_caps();
test_reasoning_budget_tokens_per_request();
test_reasoning_budget_message_per_request();
test_template_output_peg_parsers(detailed_debug);
+1
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@@ -170,6 +170,7 @@
| `--jinja, --no-jinja` | whether to use jinja template engine for chat (default: enabled)<br/>(env: LLAMA_ARG_JINJA) |
| `--reasoning-format FORMAT` | controls whether thought tags are allowed and/or extracted from the response, and in which format they're returned; one of:<br/>- none: leaves thoughts unparsed in `message.content`<br/>- deepseek: puts thoughts in `message.reasoning_content`<br/>- deepseek-legacy: keeps `<think>` tags in `message.content` while also populating `message.reasoning_content`<br/>(default: auto)<br/>(env: LLAMA_ARG_THINK) |
| `-rea, --reasoning [on\|off\|auto]` | Use reasoning/thinking in the chat ('on', 'off', or 'auto', default: 'auto' (detect from template))<br/>(env: LLAMA_ARG_REASONING) |
| `--reasoning-effort LEVEL` | reasoning effort level given to the chat template: 'default' to keep the template default,<br/>or a level such as 'minimal', 'low', 'medium', 'high', 'xhigh' or 'max' (default: default)<br/>(env: LLAMA_ARG_REASONING_EFFORT) |
| `--reasoning-budget N` | token budget for thinking: -1 for unrestricted, 0 for immediate end, N>0 for token budget (default: -1)<br/>(env: LLAMA_ARG_THINK_BUDGET) |
| `--reasoning-budget-message MESSAGE` | message injected before the end-of-thinking tag when reasoning budget is exhausted (default: none)<br/>(env: LLAMA_ARG_THINK_BUDGET_MESSAGE) |
| `--reasoning-preserve, --no-reasoning-preserve` | preserve reasoning trace in the full history, not just the last assistant message (default: template default)<br/>compatible with certain templates having 'supports_preserve_reasoning' capability<br/>example: https://docs.z.ai/guides/capabilities/thinking-mode#preserved-thinking<br/>(env: LLAMA_ARG_REASONING_PRESERVE) |
+1
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@@ -251,6 +251,7 @@ llama-completion.exe -m models\gemma-1.1-7b-it.Q4_K_M.gguf --ignore-eos -n -1
| `--jinja, --no-jinja` | whether to use jinja template engine for chat (default: disabled)<br/>(env: LLAMA_ARG_JINJA) |
| `--reasoning-format FORMAT` | controls whether thought tags are allowed and/or extracted from the response, and in which format they're returned; one of:<br/>- none: leaves thoughts unparsed in `message.content`<br/>- deepseek: puts thoughts in `message.reasoning_content`<br/>- deepseek-legacy: keeps `<think>` tags in `message.content` while also populating `message.reasoning_content`<br/>(default: auto)<br/>(env: LLAMA_ARG_THINK) |
| `-rea, --reasoning [on\|off\|auto]` | Use reasoning/thinking in the chat ('on', 'off', or 'auto', default: 'auto' (detect from template))<br/>(env: LLAMA_ARG_REASONING) |
| `--reasoning-effort LEVEL` | reasoning effort level given to the chat template: 'default' to keep the template default,<br/>or a level such as 'minimal', 'low', 'medium', 'high', 'xhigh' or 'max' (default: default)<br/>(env: LLAMA_ARG_REASONING_EFFORT) |
| `--reasoning-budget N` | token budget for thinking: -1 for unrestricted, 0 for immediate end, N>0 for token budget (default: -1)<br/>(env: LLAMA_ARG_THINK_BUDGET) |
| `--reasoning-budget-message MESSAGE` | message injected before the end-of-thinking tag when reasoning budget is exhausted (default: none)<br/>(env: LLAMA_ARG_THINK_BUDGET_MESSAGE) |
| `--reasoning-preserve, --no-reasoning-preserve` | preserve reasoning trace in the full history, not just the last assistant message (default: template default)<br/>compatible with certain templates having 'supports_preserve_reasoning' capability<br/>example: https://docs.z.ai/guides/capabilities/thinking-mode#preserved-thinking<br/>(env: LLAMA_ARG_REASONING_PRESERVE) |
+2 -1
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@@ -226,6 +226,7 @@ For the full list of features, please refer to [server's changelog](https://gith
| `--jinja, --no-jinja` | whether to use jinja template engine for chat (default: enabled)<br/>(env: LLAMA_ARG_JINJA) |
| `--reasoning-format FORMAT` | controls whether thought tags are allowed and/or extracted from the response, and in which format they're returned; one of:<br/>- none: leaves thoughts unparsed in `message.content`<br/>- deepseek: puts thoughts in `message.reasoning_content`<br/>- deepseek-legacy: keeps `<think>` tags in `message.content` while also populating `message.reasoning_content`<br/>(default: auto)<br/>(env: LLAMA_ARG_THINK) |
| `-rea, --reasoning [on\|off\|auto]` | Use reasoning/thinking in the chat ('on', 'off', or 'auto', default: 'auto' (detect from template))<br/>(env: LLAMA_ARG_REASONING) |
| `--reasoning-effort LEVEL` | reasoning effort level given to the chat template: 'default' to keep the template default,<br/>or a level such as 'minimal', 'low', 'medium', 'high', 'xhigh' or 'max' (default: default)<br/>(env: LLAMA_ARG_REASONING_EFFORT) |
| `--reasoning-budget N` | token budget for thinking: -1 for unrestricted, 0 for immediate end, N>0 for token budget (default: -1)<br/>(env: LLAMA_ARG_THINK_BUDGET) |
| `--reasoning-budget-message MESSAGE` | message injected before the end-of-thinking tag when reasoning budget is exhausted (default: none)<br/>(env: LLAMA_ARG_THINK_BUDGET_MESSAGE) |
| `--reasoning-preserve, --no-reasoning-preserve` | preserve reasoning trace in the full history, not just the last assistant message (default: template default)<br/>compatible with certain templates having 'supports_preserve_reasoning' capability<br/>example: https://docs.z.ai/guides/capabilities/thinking-mode#preserved-thinking<br/>(env: LLAMA_ARG_REASONING_PRESERVE) |
@@ -1250,7 +1251,7 @@ The `response_format` parameter supports both plain JSON output (e.g. `{"type":
`chat_template_kwargs`: Allows sending additional parameters to the json templating system. For example: `{"enable_thinking": false}`
`reasoning_effort`: If set to `none`, reasoning will be disabled for this request. Other values (e.g., `low`, `max`) have no effect on reasoning.
`reasoning_effort`: If `none`, reasoning/thinking is disabled. Otherwise, the value is made available to the jinja template.
`reasoning_format`: The reasoning format to be parsed. If set to `none`, it will output the raw generated text.
+5 -2
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@@ -1292,12 +1292,15 @@ json oaicompat_chat_params_parse(
throw std::invalid_argument("invalid type for \"enable_thinking\" (expected boolean, got string)");
}
// Parse also the OAI "reasoning_effort": "none" specific value
// Parse the OAI "reasoning_effort" field; "none" disables reasoning.
if (body.contains("reasoning_effort")) {
auto reasoning_effort = json_value(body, "reasoning_effort", std::string(""));
if (reasoning_effort == "none") {
inputs.enable_thinking = false;
} // other reasoning_effort values are model-specific and not yet handled
inputs.chat_template_kwargs.erase("reasoning_effort");
} else if (!reasoning_effort.empty()) {
inputs.chat_template_kwargs["reasoning_effort"] = json(reasoning_effort).dump();
}
}
inputs.force_pure_content = opt.force_pure_content;