Refactor cli parameters, update docs, move reasoning budget sampler part to common/reasoning-budget.cpp

This commit is contained in:
Piotr Wilkin 2026-03-15 20:00:17 +01:00
parent a21d219a0d
commit ea5ed7ab73
7 changed files with 117 additions and 84 deletions

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@ -163,9 +163,15 @@ static void common_reasoning_budget_reset(struct llama_sampler * smpl) {
ctx->force_pos = 0;
}
// forward declaration for use in clone
static struct llama_sampler * common_reasoning_budget_init_state(
const struct llama_vocab * vocab, const std::vector<llama_token> & start_tokens,
const std::vector<llama_token> & end_tokens, const std::vector<llama_token> & forced_tokens,
int32_t budget, common_reasoning_budget_state initial_state);
static struct llama_sampler * common_reasoning_budget_clone(const struct llama_sampler * smpl) {
const auto * ctx = (const common_reasoning_budget_ctx *) smpl->ctx;
return common_reasoning_budget_init(
return common_reasoning_budget_init_state(
ctx->vocab,
ctx->start_matcher.tokens,
ctx->end_matcher.tokens,
@ -191,13 +197,13 @@ static struct llama_sampler_i common_reasoning_budget_i = {
/* .backend_set_input = */ nullptr,
};
struct llama_sampler * common_reasoning_budget_init(
const struct llama_vocab * vocab,
const std::vector<llama_token> & start_tokens,
const std::vector<llama_token> & end_tokens,
const std::vector<llama_token> & forced_tokens,
int32_t budget,
common_reasoning_budget_state initial_state) {
static struct llama_sampler * common_reasoning_budget_init_state(
const struct llama_vocab * vocab,
const std::vector<llama_token> & start_tokens,
const std::vector<llama_token> & end_tokens,
const std::vector<llama_token> & forced_tokens,
int32_t budget,
common_reasoning_budget_state initial_state) {
// promote COUNTING with budget <= 0 to FORCING
if (initial_state == REASONING_BUDGET_COUNTING && budget <= 0) {
initial_state = REASONING_BUDGET_FORCING;
@ -217,3 +223,41 @@ struct llama_sampler * common_reasoning_budget_init(
}
);
}
struct llama_sampler * common_reasoning_budget_init(
const struct llama_vocab * vocab,
const std::vector<llama_token> & start_tokens,
const std::vector<llama_token> & end_tokens,
const std::vector<llama_token> & forced_tokens,
int32_t budget,
const std::vector<llama_token> & prefill_tokens) {
// Determine initial state from prefill: COUNTING if the prefill begins with
// the start sequence but does not also contain the end sequence after it.
common_reasoning_budget_state initial_state = REASONING_BUDGET_IDLE;
if (!prefill_tokens.empty() && !start_tokens.empty() &&
prefill_tokens.size() >= start_tokens.size() &&
std::equal(start_tokens.begin(), start_tokens.end(), prefill_tokens.begin())) {
initial_state = REASONING_BUDGET_COUNTING;
// If the end sequence also follows the start in the prefill, reasoning
// was opened and immediately closed — stay IDLE.
if (!end_tokens.empty() &&
prefill_tokens.size() >= start_tokens.size() + end_tokens.size()) {
auto end_start = prefill_tokens.end() - (ptrdiff_t) end_tokens.size();
if (end_start >= prefill_tokens.begin() + (ptrdiff_t) start_tokens.size() &&
std::equal(end_tokens.begin(), end_tokens.end(), end_start)) {
initial_state = REASONING_BUDGET_IDLE;
}
}
}
return common_reasoning_budget_init_state(vocab, start_tokens, end_tokens, forced_tokens, budget, initial_state);
}
struct llama_sampler * common_reasoning_budget_init(
const struct llama_vocab * vocab,
const std::vector<llama_token> & start_tokens,
const std::vector<llama_token> & end_tokens,
const std::vector<llama_token> & forced_tokens,
int32_t budget,
common_reasoning_budget_state initial_state) {
return common_reasoning_budget_init_state(vocab, start_tokens, end_tokens, forced_tokens, budget, initial_state);
}

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@ -24,14 +24,26 @@ enum common_reasoning_budget_state {
// DONE: passthrough forever
//
// Parameters:
// vocab - vocabulary (used for UTF-8 boundary detection; can be nullptr)
// start_tokens - token sequence that activates counting
// end_tokens - token sequence for natural deactivation
// forced_tokens - token sequence forced when budget expires
// budget - max tokens allowed in the reasoning block
// initial_state - initial state of the sampler (e.g. IDLE or COUNTING)
// note: COUNTING with budget <= 0 is promoted to FORCING
// vocab - vocabulary (used for UTF-8 boundary detection; can be nullptr)
// start_tokens - token sequence that activates counting
// end_tokens - token sequence for natural deactivation
// forced_tokens - token sequence forced when budget expires
// budget - max tokens allowed in the reasoning block
// prefill_tokens - tokens already present in the prompt (generation prompt);
// used to determine the initial state: COUNTING if they begin
// with start_tokens (but don't also end with end_tokens),
// IDLE otherwise. COUNTING with budget <= 0 is promoted to FORCING.
//
struct llama_sampler * common_reasoning_budget_init(
const struct llama_vocab * vocab,
const std::vector<llama_token> & start_tokens,
const std::vector<llama_token> & end_tokens,
const std::vector<llama_token> & forced_tokens,
int32_t budget,
const std::vector<llama_token> & prefill_tokens = {});
// Variant that takes an explicit initial state (used by tests and clone).
// COUNTING with budget <= 0 is promoted to FORCING.
struct llama_sampler * common_reasoning_budget_init(
const struct llama_vocab * vocab,
const std::vector<llama_token> & start_tokens,

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@ -276,37 +276,13 @@ struct common_sampler * common_sampler_init(const struct llama_model * model, st
// reasoning budget sampler — added first so it can force tokens before other samplers
if (params.reasoning_budget_tokens >= 0 && !params.reasoning_budget_forced.empty()) {
// Determine initial state from the grammar prefill: if the prefill tokens
// match the start sequence, reasoning is already open → start COUNTING.
bool activate_immediately = false;
if (!prefill_tokens.empty() && !params.reasoning_budget_start.empty() &&
prefill_tokens.size() >= params.reasoning_budget_start.size()) {
activate_immediately = std::equal(
params.reasoning_budget_start.begin(),
params.reasoning_budget_start.end(),
prefill_tokens.begin());
// But if the prefill also contains the end sequence after the start,
// reasoning was opened and closed — start IDLE instead.
if (activate_immediately &&
prefill_tokens.size() >= params.reasoning_budget_start.size() + params.reasoning_budget_end.size()) {
auto end_begin = prefill_tokens.begin() + (ptrdiff_t) params.reasoning_budget_start.size();
// Check if remaining tokens after start match the end sequence
// (possibly with whitespace tokens in between, but for simplicity check suffix)
auto end_start = prefill_tokens.end() - (ptrdiff_t) params.reasoning_budget_end.size();
if (end_start >= end_begin &&
std::equal(params.reasoning_budget_end.begin(), params.reasoning_budget_end.end(), end_start)) {
activate_immediately = false;
}
}
}
samplers.push_back(common_reasoning_budget_init(
vocab,
params.reasoning_budget_start,
params.reasoning_budget_end,
params.reasoning_budget_forced,
params.reasoning_budget_tokens,
activate_immediately ? REASONING_BUDGET_COUNTING : REASONING_BUDGET_IDLE));
prefill_tokens));
}
if (params.has_logit_bias()) {

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@ -14,7 +14,7 @@ The unified auto-parser uses a pure differential, compositional approach (inspir
**Analysis + Parser Building in Two Steps**:
1. `autoparser::autoparser tmpl_analysis(tmpl)` — runs all differential comparisons and populates the analysis structs
2. `autoparser::peg_generator::generate_parser(tmpl, params, tmpl_analysis)` — uses the analysis to build a PEG parser and optional GBNF grammar
2. `autoparser::peg_generator::generate_parser(tmpl, generation_params, tmpl_analysis)` — uses the analysis to build a PEG parser and optional GBNF grammar
## Data Structures
@ -34,7 +34,7 @@ All structs are defined in [common/chat-auto-parser.h](common/chat-auto-parser.h
### `analyze_tools` and its sub-structs
- [common/chat-auto-parser.h:176-194](common/chat-auto-parser.h#L176-L194) — `tool_format_analysis`: `mode` enum, `section_start/end`, `per_call_start/end`, JSON field names (`function_field`, `name_field`, `args_field`, `id_field`, `gen_id_field`), and format flags (`fun_name_is_key`, `tools_array_wrapped`, `uses_python_dicts`)
- [common/chat-auto-parser.h:176-194](common/chat-auto-parser.h#L176-L194) — `tool_format_analysis`: `mode` enum, `section_start/end`, `per_call_start/end`, JSON field names (`function_field`, `name_field`, `args_field`, `id_field`, `gen_id_field`), and format flags (`fun_name_is_key`, `tools_array_wrapped`)
- [common/chat-auto-parser.h:196-200](common/chat-auto-parser.h#L196-L200) — `tool_function_analysis`: `name_prefix`, `name_suffix`, `close` markers around function names
- [common/chat-auto-parser.h:202-210](common/chat-auto-parser.h#L202-L210) — `tool_arguments_analysis`: `start/end` container markers, `name_prefix/suffix`, `value_prefix/suffix`, `separator`
- [common/chat-auto-parser.h:212-217](common/chat-auto-parser.h#L212-L217) — `tool_id_analysis`: `pos` enum, `prefix`/`suffix` markers around call ID values
@ -50,13 +50,17 @@ All structs are defined in [common/chat-auto-parser.h](common/chat-auto-parser.h
| `TAG_BASED` | Tag-based: `<think>...</think>` (start can be empty for delimiter-style formats) |
| `TOOLS_ONLY` | Reasoning only appears in tool call responses, not plain content |
**Reasoning Prefill**: Extracted in `generate_parser()` using `compare_variants(add_generation_prompt=false, add_generation_prompt=true)` on a minimal single-user-message input to get exactly what the template appends as its generation prompt. The start marker is then located within this suffix using `rfind`. Three outcomes:
**Generation Prompt & Reasoning Prefill**: Computed in `common_chat_templates_apply_jinja` before invoking either the specialized handlers or the auto-parser, by rendering the template twice — once with `add_generation_prompt=false` and once with `add_generation_prompt=true` — and storing the diff suffix as `generation_params::generation_prompt`. This string is propagated into `common_chat_params::generation_prompt` and `common_chat_parser_params::generation_prompt`.
1. **Start+end in generation prompt** (e.g. `<think></think>\n`): `prefill = start + end`. The parser sees reasoning as opened and immediately closed.
2. **Only start in generation prompt** (e.g. `<think>\n`): `prefill = from_start` (substring from the marker's position to the end, preserving whitespace). The parser sees reasoning as already open.
3. **Start marker in the generation prompt but not at its end** (e.g. Apriel's `<|begin_assistant|>` followed by boilerplate): the marker is a template artifact. The start literal is cleared from the parser so reasoning uses delimiter-style (end-only). For templates that ignore `add_generation_prompt` (empty diff), the rendered `data.prompt` is used as fallback — but only for non-TOOLS_ONLY modes, since in TOOLS_ONLY the start tag is model-generated and may appear in prior conversation turns.
The generation prompt is prepended to model output before PEG parsing via `wrap_for_generation_prompt()`. The portion *before* the reasoning start marker (if any) is prepended as a literal to ensure any boilerplate added by the template is consumed. The full string is also fed to the grammar sampler via `llama_sampler_accept` (stored in `common_params_sampling::grammar_prefill`), advancing the grammar past tokens already in the prompt. It is used to determine the reasoning budget sampler's initial state — COUNTING if the prefill tokens begin with the reasoning start sequence (but don't also contain the end sequence), IDLE otherwise.
The prefill is prepended to model output before PEG parsing, fed to the grammar sampler via `llama_sampler_accept`, and used to determine the reasoning budget sampler's initial state (COUNTING if prefill starts with the reasoning start tokens, IDLE otherwise).
**`grammar_prefill`** (`common_params_sampling`): The generation prompt string tokenized and accepted by the grammar sampler at init time. Only applied when `grammar_external` is false (i.e., the grammar was not set explicitly by the user).
Three outcomes for reasoning-prefill handling (in `generate_parser()`):
1. **Start+end in generation prompt** (e.g. `<think></think>\n`): the parser sees reasoning as opened and immediately closed; whitespace-only reasoning content is discarded.
2. **Only start in generation prompt** (e.g. `<think>\n`): the parser sees reasoning as already open.
3. **Start marker present but not at the end** (e.g. Apriel's `<|begin_assistant|>` followed by boilerplate): the marker is a template artifact; the start literal is cleared so reasoning uses delimiter-style (end-only). For templates that ignore `add_generation_prompt` (empty diff), the rendered `data.prompt` is used as fallback — but only for non-TOOLS_ONLY modes, since in TOOLS_ONLY the start tag is model-generated and may appear in prior conversation turns.
**`content_mode`**: How the template wraps assistant content.
@ -273,10 +277,9 @@ Text is segmentized into markers and non-marker fragments using `segmentize_mark
**R2 — `compare_thinking_enabled()`**: Compares `enable_thinking=false` vs `true` with a generation prompt.
- Detects template-added reasoning markers: `enable_thinking=true` adds a non-empty marker at the end of the prompt — sets `reasoning.start`, mode = `TAG_BASED`
- Detects start+end pattern: `enable_thinking=false` produces both start+end markers; `enable_thinking=true` produces only start marker — both classified as `TAG_BASED`
- Handles the reverse case: if both start and end are still empty, looks for a single-segment diff on each side to extract both markers
- The reasoning prefill (markers added by the template) is later extracted in `generate_parser()` and prepended to model output before parsing
- Detects template-added reasoning markers: `enable_thinking=true` appends a non-empty marker → sets `reasoning.start`, mode = `TAG_BASED`
- Handles the reverse case (`enable_thinking=false` appends the marker instead): extracts both start (from the preceding segment) and end markers; mode = `TAG_BASED`
- The reasoning prefill (markers added by the template) is later extracted in `common_chat_templates_apply_jinja` and prepended to model output before parsing
**R3 — `compare_reasoning_scope()`**: Compares assistant message with reasoning+text-content vs reasoning+tool-calls.
@ -349,7 +352,7 @@ Classification logic:
A workaround array in `common/chat-diff-analyzer.cpp` applies post-hoc patches after analysis. Each workaround is a lambda that inspects the template source and overrides analysis results. Current workarounds:
1. **Old Qwen/DeepSeek thinking templates** — source contains `content.split('</think>')`: sets `reasoning.mode = TAG_BASED` with `<think>`/`</think>` markers if no reasoning was detected
1. **Old Qwen/DeepSeek thinking templates** — source contains `content.split('</think>')` but not `<SPECIAL_12>`: sets `reasoning.mode = TAG_BASED` with `<think>`/`</think>` markers if no reasoning was detected
2. **Granite 3.3** — source contains specific "Write your thoughts" text: forces `TAG_BASED` reasoning with `<think>`/`</think>` and `WRAPPED_WITH_REASONING` content with `<response>`/`</response>`
3. **Cohere Command R+** — source contains `<|CHATBOT_TOKEN|>`: sets `ALWAYS_WRAPPED` content mode if no content start is already set
4. **Functionary 3.1** — source contains `set has_code_interpreter`: forces `PLAIN` content, specific `per_call_start/end`, clears preserved tokens to only keep Functionary-specific markers
@ -361,13 +364,13 @@ Each analyzer struct (`analyze_reasoning`, `analyze_content`, `analyze_tools`) i
#### Reasoning Parser (`analyze_reasoning::build_parser`)
| Mode | Parser |
|-----------------------------------|---------------------------------------------------------------------|
| Not extracting reasoning | `eps()` |
| `TAG_BASED` or `TOOLS_ONLY` (non-empty start) | `optional(start + reasoning(until(end)) + end)` |
| `TAG_BASED` or `TOOLS_ONLY` (empty start) | `optional(reasoning(until(end)) + end)` — delimiter-style|
| Mode | Parser |
|-----------------------------------------------|---------------------------------------------------------------------------|
| Not extracting reasoning | `eps()` |
| `TAG_BASED` or `TOOLS_ONLY` (non-empty start) | `optional(start + reasoning(until(end)) + end + space())` |
| `TAG_BASED` or `TOOLS_ONLY` (empty start) | `optional(reasoning(until(end)) + end + space())` — delimiter-style |
Note: The start marker may be empty either because the analyzer detected delimiter-style reasoning, or because `generate_parser()` cleared a template artifact start marker (see Reasoning Prefill above). The reasoning prefill is prepended to model output before parsing.
Note: The start marker may be empty either because the analyzer detected delimiter-style reasoning, or because `generate_parser()` cleared a template artifact start marker (see Generation Prompt & Reasoning Prefill above). Whitespace-only reasoning content (e.g. from a `<think></think>` prefill) is discarded by the mapper.
#### Content Parser (`analyze_content::build_parser`)
@ -417,9 +420,7 @@ All three tool parsers return:
reasoning + optional(content(until(trigger_marker))) + tool_calls + end()
```
### Python Dict Format
When `format.uses_python_dicts` is true (detected when single-quoted strings appear in JSON argument context), `build_parser()` pre-registers a `json-string` rule that accepts both single-quoted and double-quoted strings. This is done before any `p.json()` call so all JSON parsing inherits the flexible rule.
Each returned parser is wrapped by `wrap_for_generation_prompt()`, which prepends a literal for any boilerplate prefix of the generation prompt (the portion before the reasoning start marker).
## Mapper
@ -428,22 +429,22 @@ When `format.uses_python_dicts` is true (detected when single-quoted strings app
- **Buffered arguments**: Before `tool_name` is known, argument text goes to `args_buffer`; once the name is set, the buffer is flushed to `current_tool->arguments`
- **`args_target()`**: Returns a reference to whichever destination is currently active (buffer or tool args), eliminating branching
- **`closing_quote_pending`**: Tracks whether a closing `"` needs to be appended when a string argument value is finalized (for schema-declared string types in tagged format)
- **Quote normalization**: Python-style quotes (`'key': 'value'`) are converted to JSON (`"key": "value"`)
- **Whitespace-only reasoning**: Reasoning content that consists entirely of whitespace (e.g. from a `<think></think>` prefill) is cleared so the message shows no reasoning
- **Brace auto-closing**: At tool close, unclosed `{` braces are closed automatically
## Files
| File | Purpose |
|-------------------------------------------|----------------------------------------------------------------------|
| `common/chat-auto-parser.h` | All analysis structs, enums, `autoparser`, `peg_generator`, `templates_params` |
| `common/chat-auto-parser-generator.cpp` | Parser generator: `generate_parser()` and `build_parser()` methods |
| `common/chat-diff-analyzer.cpp` | Differential analysis implementation and workarounds |
| `common/chat-auto-parser-helpers.h/cpp` | `calculate_diff_split()`, `segmentize_markers()`, |
| | `compare_variants()`, string helpers |
| `common/chat-peg-parser.h/cpp` | `common_chat_peg_builder`, `common_chat_peg_mapper`, and helpers |
| `common/chat.cpp` | Entry point: `common_chat_templates_apply_jinja()` |
| `tools/parser/debug-template-parser.cpp` | Debug tool for template analysis |
| `tools/parser/template-analysis.cpp` | Template analysis tool |
| File | Purpose |
|-------------------------------------------|---------------------------------------------------------------------------------|
| `common/chat-auto-parser.h` | All analysis structs, enums, `autoparser`, `peg_generator`, `generation_params` |
| `common/chat-auto-parser-generator.cpp` | Parser generator: `generate_parser()` and `build_parser()` methods |
| `common/chat-diff-analyzer.cpp` | Differential analysis implementation and workarounds |
| `common/chat-auto-parser-helpers.h/cpp` | `calculate_diff_split()`, `segmentize_markers()`, `compare_variants()`, |
| | `wrap_for_generation_prompt()`, string helpers |
| `common/chat-peg-parser.h/cpp` | `common_chat_peg_builder`, `common_chat_peg_mapper`, and helpers |
| `common/chat.cpp` | Entry point: `common_chat_templates_apply_jinja()` |
| `tools/parser/debug-template-parser.cpp` | Debug tool for template analysis |
| `tools/parser/template-analysis.cpp` | Template analysis tool |
## Testing & Debugging
@ -523,10 +524,10 @@ To support a new template format:
## Edge Cases and Quirks
1. **Reasoning Prefill**: See the `reasoning_mode` enum section above for the full description. Key detail: the generation prompt suffix is extracted via `compare_variants(add_generation_prompt=false, add_generation_prompt=true)` to avoid false positives from prior conversation turns.
1. **Generation Prompt & Reasoning Prefill**: The generation prompt is extracted by diffing `add_generation_prompt=false` vs `true` in `common_chat_templates_apply_jinja`, so it contains exactly what the template appends — avoiding false positives from prior conversation turns.
2. **Per-Call vs Per-Section Markers**: Some templates wrap each tool call individually (`per_call_start/end`); others wrap the entire section (`section_start/end`). T2 (`check_per_call_markers()`) disambiguates by checking if the second call in a two-call output starts with the section marker.
3. **Python Dict Format**: The Seed template family uses single-quoted JSON (`'key': 'value'`). The `uses_python_dicts` flag causes the PEG builder to register a flexible `json-string` rule accepting both quote styles before any JSON rules are built.
4. **Tag Boundary Fixing**: `calculate_diff_split()` iteratively adjusts prefix/suffix boundaries to avoid splitting `<tag>` or `[marker]` tokens, ensuring clean extraction.
5. **Call ID Side Effects**: When a call ID is detected, `per_call_end` may have been incorrectly set to include the call ID suffix. T7 clears `per_call_end` in this case.
6. **Tool Analysis Gating**: `analyze_tools` is only constructed (and all tool analysis phases run) when `jinja_caps.supports_tool_calls` is true. Within tool analysis, `check_per_call_markers()` (T2) only runs if `jinja_caps.supports_parallel_tool_calls`.
7. **`analyze_arguments()` Gating**: Within tool analysis, A1 and A2 (argument name/value marker extraction) only run for `TAG_WITH_TAGGED` format. `extract_argument_separator()` and `extract_args_markers()` run for all non-`JSON_NATIVE` formats.
3. **Tag Boundary Fixing**: `calculate_diff_split()` iteratively adjusts prefix/suffix boundaries to avoid splitting `<tag>` or `[marker]` tokens, ensuring clean extraction.
4. **Call ID Side Effects**: When a call ID is detected, `per_call_end` may have been incorrectly set to include the call ID suffix. T7 clears `per_call_end` in this case.
5. **Tool Analysis Gating**: `analyze_tools` is only constructed (and all tool analysis phases run) when `jinja_caps.supports_tool_calls` is true. Within tool analysis, `check_per_call_markers()` (T2) only runs if `jinja_caps.supports_parallel_tool_calls`.
6. **`analyze_arguments()` Gating**: Within tool analysis, A1 and A2 (argument name/value marker extraction) only run for `TAG_WITH_TAGGED` format. `extract_argument_separator()` and `extract_args_markers()` run for all non-`JSON_NATIVE` formats.
7. **Undetected Tool Format**: If `analyze_tools` concludes tool calling is supported but cannot determine the format, `build_parser()` logs an error and returns `eps()` (graceful degradation) rather than aborting.

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@ -907,7 +907,7 @@ If query param `?fail_on_no_slot=1` is set, this endpoint will respond with stat
"chat_format": "GPT-OSS",
"reasoning_format": "none",
"reasoning_in_content": false,
"prefill": "",
"generation_prompt": "",
"samplers": [
"penalties",
"dry",
@ -972,7 +972,7 @@ If query param `?fail_on_no_slot=1` is set, this endpoint will respond with stat
"chat_format": "GPT-OSS",
"reasoning_format": "none",
"reasoning_in_content": false,
"prefill": "",
"generation_prompt": "",
"samplers": [
"penalties",
"dry",
@ -1193,7 +1193,7 @@ The `response_format` parameter supports both plain JSON output (e.g. `{"type":
`reasoning_format`: The reasoning format to be parsed. If set to `none`, it will output the raw generated text.
`prefill`: The reasoning markers that were prefilled in the prompt by the template. Prepended to model output before parsing to handle dynamic thinking/non-thinking modes.
`generation_prompt`: The generation prompt that was prefilled in by the template. Prepended to model output before parsing.
`parse_tool_calls`: Whether to parse the generated tool call.

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@ -51,7 +51,7 @@ describe('ParameterSyncService', () => {
chat_format: '',
reasoning_format: '',
reasoning_in_content: false,
prefill: '',
generation_prompt: '',
'speculative.n_max': 0,
'speculative.n_min': 0,
'speculative.p_min': 0.0,

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@ -164,7 +164,7 @@ export interface ApiLlamaCppServerProps {
chat_format: string;
reasoning_format: string;
reasoning_in_content: boolean;
prefill: string;
generation_prompt: string;
samplers: string[];
backend_sampling: boolean;
'speculative.n_max': number;