Repository Analysis

xorbitsai/inference

Swap GPT for any LLM by changing a single line of code. Xinference lets you run open-source, speech, and multimodal models on cloud, on-prem, or your laptop — all through one unified, production-ready inference API.

18.3 Moderate AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of xorbitsai/inference, a Python project with 9,528 GitHub stars. SynthScan v2.0 examined 491,084 lines of code across 1698 source files, recording 7275 pattern matches distributed across 25 syntactic categories. The overall adjusted score of 18.3 places this repository in the Moderate AI signal band.

The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).

18.3
Adjusted Score
18.3
Raw Score
100%
Time Factor
2026-08-28
Last Push
9.5K
Stars
Python
Language
491.1K
Lines of Code
1.7K
Files
7.3K
Pattern Hits
2026-08-29
Scan Date
0.17
HC Hit Rate

What These Metrics Mean

Adjusted Score
Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score
The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor
The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits
Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate
High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files
Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

This chart maps the temporal evolution of the adjusted synthetic code score across successive scan runs. An upward trajectory indicates ongoing incorporation of AI-generated code or expanding LLM-assisted scaffolding; a stable or declining trajectory may reflect active human refactoring, code removal, or the adoption of stricter authorship policies. The dashed secondary line (right axis) independently tracks total raw pattern hit count, which can diverge from the normalised score when codebase size changes significantly between scans.

Severity Breakdown

Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.

CRITICAL 1HIGH 291MEDIUM 483LOW 6500

Directory Score Breakdown

This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.

Pattern Findings

The scanner identified 7275 distinct pattern matches across 25 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.

Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.

Hyper-Verbose Identifiers2799 hits · 2732 pts
SeverityFileLineSnippetContext
LOWbuild_backend.py43def _validate_builtin_model_specs(root=None):CODE
LOWbenchmark/utils.py169def _num_special_tokens_to_add(tokenizer: "PreTrainedTokenizerBase") -> int:CODE
LOWbenchmark/utils.py234def _gen_prompt_decode_to_target_len(CODE
LOWbenchmark/utils.py300def _generate_prompt_with_target_len(CODE
LOWbenchmark/benchmark_serving.py30def _validate_random_range_ratio(value: float, name: str) -> float:CODE
LOW…register-model/[modelType]/[modelName]/page-client.tsx9export default function RegisterModelEditPageClient() {CODE
LOW…ntend/src/app/running-model/[modelUid]/page-client.tsx7export default function RunningModelDetailPageClient() {CODE
LOWfrontend/src/components/pages/launch-model/utils.tsx234export function getLaunchModelEndpointType(type: RequestModelType) {CODE
LOWfrontend/src/components/pages/launch-model/utils.tsx288function restoreNestedFormListObject(values: FormValues, parent: string, field: string) {CODE
LOWfrontend/src/components/pages/launch-model/utils.tsx303function transformOnlyValueFormListToArray(values: FormValues, field: string) {CODE
LOWfrontend/src/components/pages/launch-model/utils.tsx327function transformArrayToOnlyValueFormList(values: FormValues, field: string) {CODE
LOWfrontend/src/components/pages/launch-model/utils.tsx377function applyNestedFormListObject(values: FormValues, parent: string, field: string) {CODE
LOWfrontend/src/components/pages/launch-model/utils.tsx399function deleteNestedEmptyArrayField(values: FormValues, parent: string, field: string) {CODE
LOWfrontend/src/components/pages/launch-model/utils.tsx688function parseReplicaConfigCommandValue(value: string) {CODE
LOWfrontend/src/components/pages/launch-model/utils.tsx754export function generateCommandLineStatement(params: FormValues) {CODE
LOWfrontend/src/components/pages/launch-model/utils.tsx1099export function isVisibleRequiredLaunchField(field: LaunchFieldConfig) {CODE
LOW…nents/pages/running-model-detail/capability-config.tsx144function appendCommonMediaFormData(formData: FormData, context: TransformContext) {CODE
LOW…nents/pages/running-model-detail/capability-config.tsx174function appendCommonVideoFormData(formData: FormData, context: TransformContext) {CODE
LOW…end/src/components/pages/running-model-detail/utils.ts205export function transformFileInfoForResult(message?: ChatChoicesMessage) {CODE
LOW…nts/pages/running-model-detail/emotion-vector-utils.ts28export function parseIndexTTSEmotionVector(value: unknown): number[] | undefined {CODE
LOW…ts/pages/running-model-detail/panels/result-panels.tsx394function SpeakerEmbeddingResultPanel({ result }: { result: unknown }) {CODE
LOW…ts/pages/token-router/router-runtime-detail-drawer.tsx61export function RouterRuntimeDetailDrawer({ router, open, onOpenChange }: Props) {CODE
LOW…ponents/pages/token-router/router-config-normalizer.ts224export function normalizeTokenRouterRuntimeInstances(value: unknown): TokenRouterRuntimeInstance[] {CODE
LOW…ponents/pages/token-router/router-config-normalizer.ts230export function normalizeTokenRouterRuntimeInstance(CODE
LOW…ponents/pages/token-router/router-config-normalizer.ts271export function normalizeTokenRouterAssignments(value: unknown): TokenRouterAssignment[] {CODE
LOW…s/pages/token-router/tokenizer-asset-binding-status.ts13export function getBindingDesiredStateLabel(t: TFunc, state: BindingDesiredState): string {CODE
LOW…s/pages/token-router/tokenizer-asset-binding-status.ts17export function getBindingObservedStateLabel(t: TFunc, state: string): string {CODE
LOW…s/pages/token-router/tokenizer-asset-binding-status.ts43export function getBindingObservedStateBadgeVariant(state: string): BadgeVariant {CODE
LOWxinference/conftest.py165def run_test_cluster_in_subprocess(CODE
LOWxinference/constants.py122def _parse_virtual_env_find_links_allowed_roots(CODE
LOWxinference/constants.py186def _get_or_create_persisted_secret(env_name: str, file_name: str) -> str:CODE
LOWxinference/types.py369def get_pydantic_model_from_method(CODE
LOWxinference/device_utils.py53def _count_with_visible_devices(env_name: str, device_count: int) -> int:CODE
LOWxinference/device_utils.py273def _collect_gpu_info_with_env(CODE
LOWxinference/device_utils.py583def move_model_to_available_device(model):CODE
LOWxinference/device_utils.py590def get_device_preferred_dtype(device: str) -> Union[torch.dtype, None]:CODE
LOWxinference/device_utils.py599def is_hf_accelerate_supported(device: str) -> bool:CODE
LOWxinference/device_utils.py609def get_available_device_env_name():CODE
LOWxinference/device_utils.py635def get_per_process_gpu_memory() -> Dict[int, Dict[int, int]]:CODE
LOWxinference/core/worker.py391def _snapshot_gpu_occupying_pids(device_indices: list) -> set:CODE
LOWxinference/core/worker.py484def _process_or_ancestor_has_uid(proc: Any, uid_lower: str) -> bool:CODE
LOWxinference/core/worker.py1722 def _load_persisted_launch_args(self) -> dict:CODE
LOWxinference/core/worker.py242def _wait_for_metrics_export_server(CODE
LOWxinference/core/worker.py259def _exclusive_venv_path_lock(env_path: str):CODE
LOWxinference/core/worker.py595async def _kill_gpu_orphans_by_ppid(CODE
LOWxinference/core/worker.py997 async def _evict_replica_from_supervisor(self, model_uid: str) -> None:CODE
LOWxinference/core/worker.py1036 def _get_spec_dicts_with_cache_status(CODE
LOWxinference/core/worker.py1108 async def _cleanup_gpu_orphans_on_startup(self) -> None:CODE
LOWxinference/core/worker.py1386 async def _get_supervisor_ref_with_generation(CODE
LOWxinference/core/worker.py1410 async def _get_supervisor_ref_on_actor_loop(CODE
LOWxinference/core/worker.py1526 async def _record_model_versions_best_effort(self, cache_tracker_ref):CODE
LOWxinference/core/worker.py1562 def _clear_unregistered_supervisor_refs(self) -> bool:CODE
LOWxinference/core/worker.py1578 def _get_supervisor_ref_generation(CODE
LOWxinference/core/worker.py1615 async def _refresh_supervisor_address(self):CODE
LOWxinference/core/worker.py1632 def _get_running_replica_states(self) -> List[Dict[str, Any]]:CODE
LOWxinference/core/worker.py1705 def _remove_persisted_launch_args(self, model_uid: str):CODE
LOWxinference/core/worker.py1913 async def allocate_devices_with_gpu_idx(CODE
LOWxinference/core/worker.py1951 async def get_gpu_allocation_status(self) -> Dict[str, Any]:CODE
LOWxinference/core/worker.py1999 async def _append_sub_pool_protected(CODE
LOWxinference/core/worker.py2063 async def _allocate_subpool_devices(CODE
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Cross-File Repetition228 hits · 1140 pts
SeverityFileLineSnippetContext
HIGHxinference/model/video/__init__.py0load downloaded json configurations from the builtin directory.STRING
HIGHxinference/model/llm/__init__.py0load downloaded json configurations from the builtin directory.STRING
HIGHxinference/model/embedding/__init__.py0load downloaded json configurations from the builtin directory.STRING
HIGHxinference/model/image/__init__.py0load downloaded json configurations from the builtin directory.STRING
HIGHxinference/model/audio/__init__.py0load downloaded json configurations from the builtin directory.STRING
HIGHxinference/model/rerank/__init__.py0load downloaded json configurations from the builtin directory.STRING
HIGHxinference/model/video/engine_family.py0whether the engine implements the model, ignoring host constraints.STRING
HIGHxinference/model/audio/engine_family.py0whether the engine implements the model, ignoring host constraints.STRING
HIGHxinference/model/world/engine_family.py0whether the engine implements the model, ignoring host constraints.STRING
HIGH…ence/model/llm/tool_parsers/deepseek_v3_tool_parser.py0extract tool calls from complete model output. parses the model output to find json code blocks containing tool calls anSTRING
HIGHxinference/model/llm/tool_parsers/glm5_tool_parser.py0extract tool calls from complete model output. parses the model output to find json code blocks containing tool calls anSTRING
HIGH…ce/model/llm/tool_parsers/deepseek_v3_1_tool_parser.py0extract tool calls from complete model output. parses the model output to find json code blocks containing tool calls anSTRING
HIGHxinference/model/llm/tool_parsers/glm4_tool_parser.py0extract tool calls from complete model output. parses the model output to find json code blocks containing tool calls anSTRING
HIGHxinference/thirdparty/cosyvoice/tokenizer/tokenizer.py0's|'t|'re|'ve|'m|'ll|'d| ?\p{l}+| ?\p{n}+| ?[^\s\p{l}\p{n}]+|\s+(?!\s)|\s+STRING
HIGHxinference/thirdparty/indextts/utils/tokenizer.py0's|'t|'re|'ve|'m|'ll|'d| ?\p{l}+| ?\p{n}+| ?[^\s\p{l}\p{n}]+|\s+(?!\s)|\s+STRING
HIGHxinference/thirdparty/whisper/tokenizer.py0's|'t|'re|'ve|'m|'ll|'d| ?\p{l}+| ?\p{n}+| ?[^\s\p{l}\p{n}]+|\s+(?!\s)|\s+STRING
HIGH…ference/thirdparty/cosyvoice/transformer/activation.py0implementation of a sine-based periodic activation function shape: - input: (b, c, t) - output: (b, c, t), same shape asSTRING
HIGHxinference/thirdparty/indextts/BigVGAN/activations.py0implementation of a sine-based periodic activation function shape: - input: (b, c, t) - output: (b, c, t), same shape asSTRING
HIGH…thirdparty/indextts/s2mel/modules/hifigan/generator.py0implementation of a sine-based periodic activation function shape: - input: (b, c, t) - output: (b, c, t), same shape asSTRING
HIGH…irdparty/indextts/s2mel/modules/bigvgan/activations.py0implementation of a sine-based periodic activation function shape: - input: (b, c, t) - output: (b, c, t), same shape asSTRING
HIGH…ference/thirdparty/cosyvoice/transformer/activation.py0initialization. input: - in_features: shape of the input - alpha: trainable parameter alpha is initialized to 1 by defauSTRING
HIGHxinference/thirdparty/indextts/BigVGAN/activations.py0initialization. input: - in_features: shape of the input - alpha: trainable parameter alpha is initialized to 1 by defauSTRING
HIGH…thirdparty/indextts/s2mel/modules/hifigan/generator.py0initialization. input: - in_features: shape of the input - alpha: trainable parameter alpha is initialized to 1 by defauSTRING
HIGH…irdparty/indextts/s2mel/modules/bigvgan/activations.py0initialization. input: - in_features: shape of the input - alpha: trainable parameter alpha is initialized to 1 by defauSTRING
HIGH…ference/thirdparty/cosyvoice/transformer/activation.py0forward pass of the function. applies the function to the input elementwise. snake ∶= x + 1/a * sin^2 (xa)STRING
HIGHxinference/thirdparty/indextts/BigVGAN/activations.py0forward pass of the function. applies the function to the input elementwise. snake ∶= x + 1/a * sin^2 (xa)STRING
HIGH…thirdparty/indextts/s2mel/modules/hifigan/generator.py0forward pass of the function. applies the function to the input elementwise. snake ∶= x + 1/a * sin^2 (xa)STRING
HIGH…irdparty/indextts/s2mel/modules/bigvgan/activations.py0forward pass of the function. applies the function to the input elementwise. snake ∶= x + 1/a * sin^2 (xa)STRING
HIGHxinference/thirdparty/cosyvoice/utils/mask.py0make mask tensor containing indices of padded part. see description of make_non_pad_mask. args: lengths (torch.tensor): STRING
HIGHxinference/thirdparty/indextts/utils/common.py0make mask tensor containing indices of padded part. see description of make_non_pad_mask. args: lengths (torch.tensor): STRING
HIGHxinference/thirdparty/indextts/utils/utils.py0make mask tensor containing indices of padded part. see description of make_non_pad_mask. args: lengths (torch.tensor): STRING
HIGH…ference/thirdparty/deepseek_vl2/models/conversation.py0a class that manages prompt templates and keeps all conversation history.STRING
HIGH…irdparty/sensenova_u1/models/neo_unify/conversation.py0a class that manages prompt templates and keeps all conversation history.STRING
HIGHxinference/thirdparty/deepseek_vl/utils/conversation.py0a class that manages prompt templates and keeps all conversation history.STRING
HIGHxinference/thirdparty/internvl/conversation.py0a class that manages prompt templates and keeps all conversation history.STRING
HIGH…ference/thirdparty/deepseek_vl2/models/conversation.py0update the last output. the last message is typically set to be none when constructing the prompt, so we need to update STRING
HIGH…irdparty/sensenova_u1/models/neo_unify/conversation.py0update the last output. the last message is typically set to be none when constructing the prompt, so we need to update STRING
HIGHxinference/thirdparty/deepseek_vl/utils/conversation.py0update the last output. the last message is typically set to be none when constructing the prompt, so we need to update STRING
HIGHxinference/thirdparty/internvl/conversation.py0update the last output. the last message is typically set to be none when constructing the prompt, so we need to update STRING
HIGH…ference/thirdparty/deepseek_vl2/models/conversation.py0convert the conversation to openai chat completion format.STRING
HIGH…irdparty/sensenova_u1/models/neo_unify/conversation.py0convert the conversation to openai chat completion format.STRING
HIGHxinference/thirdparty/deepseek_vl/utils/conversation.py0convert the conversation to openai chat completion format.STRING
HIGHxinference/thirdparty/internvl/conversation.py0convert the conversation to openai chat completion format.STRING
HIGH…ce/thirdparty/deepseek_vl2/models/modeling_deepseek.py0this is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). the hidden states go from (batch, num_key_vaSTRING
HIGH…dparty/sensenova_u1/models/neo_unify/modeling_qwen3.py0this is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). the hidden states go from (batch, num_key_vaSTRING
HIGH…ference/thirdparty/hidream_o1/qwen3_vl_transformers.py0this is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). the hidden states go from (batch, num_key_vaSTRING
HIGH…ce/thirdparty/deepseek_vl2/models/modeling_deepseek.py0multi-headed attention from 'attention is all you need' paperSTRING
HIGH…dparty/sensenova_u1/models/neo_unify/modeling_qwen3.py0multi-headed attention from 'attention is all you need' paperSTRING
HIGH…ference/thirdparty/hidream_o1/qwen3_vl_transformers.py0multi-headed attention from 'attention is all you need' paperSTRING
HIGH…ish_speech/fish_speech/models/vqgan/modules/firefly.py0remove padding from x, handling properly zero padding. only for 1d!STRING
HIGH…s/maskgct/models/codec/speechtokenizer/modules/conv.py0remove padding from x, handling properly zero padding. only for 1d!STRING
HIGH…ference/thirdparty/indextts/s2mel/dac/model/encodec.py0remove padding from x, handling properly zero padding. only for 1d!STRING
HIGHxinference/thirdparty/indextts/s2mel/modules/encodec.py0remove padding from x, handling properly zero padding. only for 1d!STRING
HIGH…ish_speech/fish_speech/models/vqgan/modules/firefly.py0tiny wrapper around f.pad, just to allow for reflect padding on small input. if this is the case, we insert extra 0 paddSTRING
HIGH…s/maskgct/models/codec/speechtokenizer/modules/conv.py0tiny wrapper around f.pad, just to allow for reflect padding on small input. if this is the case, we insert extra 0 paddSTRING
HIGH…ference/thirdparty/indextts/s2mel/dac/model/encodec.py0tiny wrapper around f.pad, just to allow for reflect padding on small input. if this is the case, we insert extra 0 paddSTRING
HIGHxinference/thirdparty/indextts/s2mel/modules/encodec.py0tiny wrapper around f.pad, just to allow for reflect padding on small input. if this is the case, we insert extra 0 paddSTRING
HIGH…y/sensenova_u1/models/neo_unify/modeling_fm_modules.py0embeds scalar timesteps into vector representations.STRING
HIGH…ference/thirdparty/hidream_o1/qwen3_vl_transformers.py0embeds scalar timesteps into vector representations.STRING
HIGH…dparty/indextts/s2mel/modules/diffusion_transformer.py0embeds scalar timesteps into vector representations.STRING
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Unused Imports1024 hits · 976 pts
SeverityFileLineSnippetContext
LOWbuild_backend.py35CODE
LOWbenchmark/utils.py29CODE
LOWxinference/__init__.py37CODE
LOWxinference/device_utils.py131CODE
LOWxinference/device_utils.py140CODE
LOWxinference/device_utils.py149CODE
LOWxinference/device_utils.py158CODE
LOWxinference/device_utils.py159CODE
LOWxinference/device_utils.py168CODE
LOWxinference/_compat.py22CODE
LOWxinference/_compat.py22CODE
LOWxinference/_compat.py22CODE
LOWxinference/_compat.py22CODE
LOWxinference/_compat.py22CODE
LOWxinference/_compat.py22CODE
LOWxinference/_compat.py22CODE
LOWxinference/_compat.py34CODE
LOWxinference/_compat.py35CODE
LOWxinference/_compat.py36CODE
LOWxinference/_compat.py37CODE
LOWxinference/_compat.py39CODE
LOWxinference/_compat.py39CODE
LOWxinference/_compat.py39CODE
LOWxinference/_compat.py39CODE
LOWxinference/_compat.py39CODE
LOWxinference/_compat.py39CODE
LOWxinference/_compat.py39CODE
LOWxinference/_compat.py51CODE
LOWxinference/_compat.py52CODE
LOWxinference/_compat.py53CODE
LOWxinference/_compat.py54CODE
LOWxinference/core/tokenizer_asset_store.py4CODE
LOWxinference/core/router_orchestration.py4CODE
LOWxinference/core/router_config_store.py10CODE
LOWxinference/core/supervisor.py64CODE
LOWxinference/core/supervisor.py90CODE
LOWxinference/core/supervisor.py91CODE
LOWxinference/core/supervisor.py93CODE
LOWxinference/core/supervisor.py94CODE
LOWxinference/core/supervisor.py95CODE
LOWxinference/core/supervisor.py96CODE
LOWxinference/core/launch_strategy.py22CODE
LOWxinference/core/router_scheduler.py4CODE
LOWxinference/core/router_node_store.py4CODE
LOWxinference/core/http_protocol.py131CODE
LOWxinference/core/router_assignment_store.py4CODE
LOWxinference/core/model.py49CODE
LOWxinference/core/model.py50CODE
LOWxinference/core/tokenizer_asset_registry.py4CODE
LOWxinference/core/router_deployment_store.py4CODE
LOWxinference/core/system_settings_store.py17CODE
LOWxinference/core/router_registry.py4CODE
LOWxinference/core/tests/test_monitoring_v2.py1CODE
LOWxinference/core/tests/test_router_orchestration.py3CODE
LOWxinference/core/tests/test_tokenizer_asset_store.py3CODE
LOWxinference/deploy/cmdline.py57CODE
LOWxinference/deploy/router_agent.py4CODE
LOWxinference/deploy/router_agent.py6CODE
LOWxinference/deploy/utils.py43CODE
LOWxinference/deploy/router.py4CODE
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Decorative Section Separators230 hits · 762 pts
SeverityFileLineSnippetContext
MEDIUMxinference/device_utils.py29# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/device_utils.py31# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/device_utils.py48# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/device_utils.py50# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/device_utils.py268# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/device_utils.py270# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/device_utils.py90# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/device_utils.py92# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/device_utils.py175# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/device_utils.py177# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/device_utils.py449# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/device_utils.py451# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/device_utils.py558# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/device_utils.py560# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/metrics.py37# ===========================================================================COMMENT
MEDIUMxinference/core/metrics.py39# ===========================================================================COMMENT
MEDIUMxinference/core/metrics.py58# ===========================================================================COMMENT
MEDIUMxinference/core/metrics.py60# ===========================================================================COMMENT
MEDIUMxinference/core/metrics.py102# ===========================================================================COMMENT
MEDIUMxinference/core/metrics.py104# ===========================================================================COMMENT
MEDIUMxinference/core/metrics.py338# ===========================================================================COMMENT
MEDIUMxinference/core/metrics.py340# ===========================================================================COMMENT
MEDIUMxinference/core/metrics.py367# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/metrics.py369# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/metrics.py434# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/metrics.py436# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/metrics.py450# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/metrics.py452# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/otel.py161# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/otel.py163# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/otel.py316# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/otel.py318# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/tests/test_model.py302# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/tests/test_model.py308# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/tests/test_utils.py682# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/tests/test_utils.py684# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/tests/test_subpool_hardening.py114# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/tests/test_subpool_hardening.py116# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/tests/test_subpool_hardening.py153# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/tests/test_subpool_hardening.py155# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/tests/test_subpool_hardening.py187# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/tests/test_subpool_hardening.py189# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/tests/test_subpool_hardening.py211# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/tests/test_subpool_hardening.py213# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/tests/test_subpool_hardening.py253# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/tests/test_subpool_hardening.py258# ---------------------------------------------------------------------------COMMENT
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MEDIUMxinference/core/tests/test_subpool_hardening.py358# ---------------------------------------------------------------------------COMMENT
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MEDIUMxinference/core/tests/test_subpool_hardening.py419# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/tests/test_subpool_hardening.py505# ---------------------------------------------------------------------------COMMENT
MEDIUMxinference/core/tests/test_subpool_hardening.py507# ---------------------------------------------------------------------------COMMENT
MEDIUM…nference/deploy/docker/pypiserver/download_packages.py357 # ------------------------------------------------------------------COMMENT
MEDIUM…nference/deploy/docker/pypiserver/download_packages.py359 # ------------------------------------------------------------------COMMENT
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MEDIUM…nference/deploy/docker/pypiserver/download_packages.py396 # ------------------------------------------------------------------COMMENT
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MEDIUM…nference/deploy/docker/pypiserver/download_packages.py460 # ------------------------------------------------------------------COMMENT
MEDIUM…nference/deploy/docker/pypiserver/download_packages.py498 # ------------------------------------------------------------------COMMENT
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Excessive Try-Catch Wrapping756 hits · 713 pts
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MEDIUMxinference/device_utils.py313def get_nvidia_gpu_info() -> Dict[str, Any]:CODE
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LOWxinference/core/worker.py1440 except Exception:CODE
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Over-Commented Block601 hits · 576 pts
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LOWbuild_backend.py1# Copyright 2022-2026 Xinference Holdings Pte. LtdCOMMENT
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LOWxinference/core/worker.py3301 f"[DEBUG] CUDA version check passed: cuda_version={cuda_version}, keeping settings.extra_index_url={settCOMMENT
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LOWxinference/core/resource.py1# Copyright 2022-2026 Xinference Holdings Pte. LtdCOMMENT
LOWxinference/core/__init__.py1# Copyright 2022-2026 Xinference Holdings Pte. LtdCOMMENT
LOWxinference/core/cache_tracker.py1# Copyright 2022-2026 Xinference Holdings Pte. LtdCOMMENT
LOWxinference/core/autostart.py1# Copyright 2022-2026 Xinference Holdings Pte. LtdCOMMENT
LOWxinference/core/http_protocol.py1# Copyright 2022-2026 Xinference Holdings Pte. LtdCOMMENT
LOWxinference/core/replica_config.py1# Copyright 2022-2026 Xinference Holdings Pte. LtdCOMMENT
LOWxinference/core/model.py1# Copyright 2022-2026 Xinference Holdings Pte. LtdCOMMENT
LOWxinference/core/utils.py1# Copyright 2022-2026 Xinference Holdings Pte. LtdCOMMENT
LOWxinference/core/status_guard.py1# Copyright 2022-2026 Xinference Holdings Pte. LtdCOMMENT
LOWxinference/core/exceptions.py1# Copyright 2022-2026 Xinference Holdings Pte. LtdCOMMENT
LOWxinference/core/launch_history_store.py1# Copyright 2022-2026 Xinference Holdings Pte. LtdCOMMENT
LOWxinference/core/otel.py1# Copyright 2022-2026 Xinference Holdings Pte. LtdCOMMENT
LOWxinference/core/system_settings_store.py1# Copyright 2022-2026 Xinference Holdings Pte. LtdCOMMENT
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LOWxinference/core/tests/test_model.py1# Copyright 2022-2026 Xinference Holdings Pte. LtdCOMMENT
LOWxinference/core/tests/test_continuous_batching.py1# Copyright 2022-2026 XProbe Inc.COMMENT
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LOWxinference/core/tests/test_metrics.py1# Copyright 2022-2026 Xinference Holdings Pte. LtdCOMMENT
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Deep Nesting649 hits · 542 pts
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AI Structural Patterns304 hits · 284 pts
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Modern Structural Boilerplate253 hits · 256 pts
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Dead Code125 hits · 181 pts
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Docstring Block Structure36 hits · 180 pts
SeverityFileLineSnippetContext
HIGHxinference/utils.py87 Recursively convert an object into a hashable form. This function is useful for creating deterministic cache kSTRING
HIGHxinference/deploy/utils.py1072Convert CLI string arguments to appropriate Python types. Handles type conversion for Click command arguments with STRING
HIGH…ence/model/llm/tool_parsers/deepseek_v4_tool_parser.py102 Extract tool calls from complete model output. Args: model_output: The complete output strSTRING
HIGH…ce/model/llm/tool_parsers/deepseek_v3_2_tool_parser.py95 Extract tool calls from complete model output. Args: model_output: The complete output strSTRING
HIGHxinference/model/embedding/core.py362 Extract the 'sentences' argument and remaining kwargs from (*args, **kwargs) for a given function. STRING
HIGHxinference/model/rerank/sentence_transformers/core.py781 Extract the 'documents' and 'query' argument and remaining kwargs from (*args, **kwargs) for a given fuSTRING
HIGHxinference/model/rerank/vllm/core.py303 Extract the 'documents' and 'query' argument and remaining kwargs from (*args, **kwargs) for a given fuSTRING
HIGHxinference/api/utils.py101 Get a model with standardized error handling. Replaces the repeated pattern: ```python try: moSTRING
HIGHxinference/thirdparty/cosyvoice/utils/mask.py18 def subsequent_mask( size: int, device: torch.device = torch.device("cpu"), ) -> torch.Tensor: """CSTRING
HIGHxinference/thirdparty/cosyvoice/utils/mask.py57Create mask for subsequent steps (size, size). This mask is used only in decoder which works in an auto-regressive STRING
HIGHxinference/thirdparty/cosyvoice/utils/mask.py95Create mask for subsequent steps (size, size) with chunk size, this is for streaming encoder Args: sSTRING
HIGHxinference/thirdparty/cosyvoice/utils/mask.py133Create mask for subsequent steps (size, size) with chunk size, this is for streaming encoder Args: sSTRING
HIGHxinference/thirdparty/cosyvoice/utils/mask.py240Make mask tensor containing indices of padded part. See description of make_non_pad_mask. Args: lengthSTRING
HIGHxinference/thirdparty/cosyvoice/utils/common.py30Perform padding for the list of tensors. Args: xs (List): List of Tensors [(T_1, `*`), (T_2, `*`), ..., (T_STRING
HIGHxinference/thirdparty/cosyvoice/flow/decoder.py211Forward pass of the UNet1DConditional model. Args: x (torch.Tensor): shape (batch_size, in_channelsSTRING
HIGHxinference/thirdparty/cosyvoice/flow/decoder.py406Forward pass of the UNet1DConditional model. Args: x (torch.Tensor): shape (batch_size, in_channelsSTRING
HIGH…u1/prompt_enhance/adapters/chat_completions_adapter.py154Extract the assistant message text from a chat/completions response. Handles both plain-string and list-of-contSTRING
HIGH…u1/prompt_enhance/adapters/chat_completions_adapter.py191Call the ``/chat/completions`` endpoint with vision content. Args: user_prompt: User-facing text inSTRING
HIGH…irdparty/sensenova_u1/prompt_enhance/adapters/utils.py13Read raw image bytes from a path or return bytes unchanged. Args: image: File path to an image, or raw imagSTRING
HIGH…senova_u1/prompt_enhance/adapters/anthropic_adapter.py160Extract the assistant message text from Anthropic Messages response. Handles responses with or without content STRING
HIGH…senova_u1/prompt_enhance/adapters/anthropic_adapter.py193Call the ``/v1/messages`` endpoint with vision content. Args: user_prompt: User-facing text instrucSTRING
HIGH…ce/thirdparty/ace_step_1_5/acestep/model_downloader.py711Resolve a VAE variant id (or absolute path) to its on-disk directory. Args: checkpoint_dir: Root checkpointSTRING
HIGH…/third_parts/nano-vllm/nanovllm/engine/model_runner.py30Encode IPC arguments to UTF-8 JSON bytes for shared-memory transport. Replaces ``pickle`` to avoid arbitrary code eSTRING
HIGH…/third_parts/nano-vllm/nanovllm/engine/model_runner.py84Find an available port starting from start_port. Args: start_port: The starting port number to check STRING
HIGH…1_5/acestep/core/generation/handler/lyric_timestamp.py28Generate LRC timestamps by aligning decoder cross-attention to lyric tokens. Args: pred_latent (torSTRING
HIGH…estep/core/generation/handler/generate_music_decode.py27Collect decode inputs and validate raw diffusion latents. Args: outputs: ``service_generate`` outpuSTRING
HIGH…e/generation/handler/init_service_loader_components.py27Load the VAE checkpoint and return its resolved path. Args: checkpoint_dir: Root checkpoint directoSTRING
HIGH…e/generation/handler/init_service_loader_components.py69Load the text tokenizer and embedding model, then return its path. Args: checkpoint_dir: Root checkSTRING
HIGH…tep_1_5/acestep/core/generation/handler/lyric_score.py27Calculate lyric alignment scores for pure-noise and regressed-latent inputs. Args: pred_latent (torSTRING
HIGH…e_step_1_5/acestep/core/generation/handler/io_audio.py14Read an audio file, with torchaudio fallback for formats unsupported by soundfile. soundfile (libsndfile) supports STRING
HIGH…_1_5/acestep/core/generation/handler/generate_music.py252Generate audio from text/reference inputs and return response payload. Args: captions: Text prompt STRING
HIGH…party/megatts3/tts/modules/ar_dur/commons/seq_utils.py113Make mask tensor containing indices of padded part. Args: lengths (LongTensor or List): Batch of lengths (B,STRING
HIGH…party/megatts3/tts/modules/ar_dur/commons/seq_utils.py219Make mask tensor containing indices of non-padded part. Args: lengths (LongTensor or List): Batch of lengthsSTRING
HIGH…ference/thirdparty/matcha/models/components/decoder.py364Forward pass of the UNet1DConditional model. Args: x (torch.Tensor): shape (batch_size, in_channelsSTRING
HIGHxinference/thirdparty/indextts/utils/common.py86Make mask tensor containing indices of padded part. See description of make_non_pad_mask. Args: lengthSTRING
HIGHxinference/thirdparty/indextts/utils/utils.py54Make mask tensor containing indices of padded part. See description of make_non_pad_mask. Args: lengthSTRING
Self-Referential Comments47 hits · 142 pts
SeverityFileLineSnippetContext
MEDIUMxinference/core/virtual_env_manager.py813 # This method is deprecated and no longer neededCOMMENT
MEDIUMxinference/core/tests/test_restful_api.py1645 # Create a mock handler with the conversion methodCOMMENT
MEDIUMxinference/core/tests/test_restful_api.py1652 # Create a temporary RESTfulAPI instance to access the methodCOMMENT
MEDIUMxinference/deploy/test/test_log_rotation.py211 # Create a file dated 100 days agoCOMMENT
MEDIUMxinference/model/utils.py3068 # Create a mapping of updated_at to model for comparisonCOMMENT
MEDIUMxinference/model/utils.py3143 # Create a copy of built-in models for mergingCOMMENT
MEDIUMxinference/model/llm/__init__.py297 # Create a copy of built-in models for mergingCOMMENT
MEDIUMxinference/model/llm/vllm/distributed_executor_v1.py101 # Create the parallel GPU workers.COMMENT
MEDIUMxinference/model/llm/vllm/distributed_executor.py146 # Create the parallel GPU workers.COMMENT
MEDIUMxinference/model/llm/transformers/chatglm.py126 # This method is adapted from https://github.com/THUDM/GLM-4/blob/main/basic_demo/openai_api_server.pyCOMMENT
MEDIUMxinference/model/llm/transformers/core.py64# Define the decorator to support multiple names registrationCOMMENT
MEDIUM…erence/model/llm/transformers/tests/test_tensorizer.py100 # Create a dummy cache file to simulate cache existenceCOMMENT
MEDIUM…ence/model/embedding/vllm/tests/test_vllm_embedding.py104 # Create a long text that exceeds 512 tokensCOMMENT
MEDIUMxinference/model/audio/utils.py178 # Create the file, close our handle immediately, and clean it upCOMMENT
MEDIUMxinference/model/rerank/sentence_transformers/core.py311 # Create a simple wrapper for return value conversion only.COMMENT
MEDIUMxinference/thirdparty/audiotools/ml/accelerator.py14 """This class is used to prepare models and dataloaders forSTRING
MEDIUMxinference/thirdparty/fish_speech/tools/run_webui.py73 # Create the inference engineCOMMENT
MEDIUM…rence/thirdparty/fish_speech/tools/vqgan/extract_vq.py24# This file is used to convert the audio files to text files using the Whisper model.COMMENT
MEDIUM…fish_speech/tools/server/agent/pre_generation_utils.py39 # Create a conversation object and encode it for inferenceCOMMENT
MEDIUM…fish_speech/tools/inference_engine/reference_loader.py29 # Define the torchaudio backendCOMMENT
MEDIUM…rdparty/fish_speech/tools/inference_engine/__init__.py166 # Create a queue to get the responseCOMMENT
MEDIUM…erence/thirdparty/fish_speech/fish_speech/i18n/scan.py55# Define the standard file nameCOMMENT
MEDIUM…erence/thirdparty/fish_speech/fish_speech/i18n/scan.py78# Define the standard file nameCOMMENT
MEDIUM…arty/sensenova_u1/models/neo_unify/modeling_neo_vit.py38 # Create the batch index for each patch (B x patch count)COMMENT
MEDIUM…rty/sensenova_u1/models/neo_unify/modeling_neo_chat.py134 # Create the batch index for each patch (B x patch count)COMMENT
MEDIUM…dparty/sensenova_u1/models/neo_unify/modeling_qwen3.py1147 # Create the masksCOMMENT
MEDIUMxinference/thirdparty/melo/text/japanese.py540# Initialize kakasi objectCOMMENT
MEDIUMxinference/thirdparty/melo/text/japanese.py636# # Initialize kakasi objectCOMMENT
MEDIUMxinference/thirdparty/melo/text/korean.py181# # Initialize kakasi objectCOMMENT
MEDIUM…ference/thirdparty/ace_step_1_5/acestep/audio_utils.py83 # Create a copy to avoid modifying original in-placeCOMMENT
MEDIUMxinference/thirdparty/ace_step_1_5/acestep/inference.py960 # Create a copy of params dict for this audioCOMMENT
MEDIUMxinference/thirdparty/f5_tts/infer/utils_infer.py509 # Create a combined spectrogramCOMMENT
MEDIUMxinference/thirdparty/deepseek_vl/serve/app_deepseek.py96 # Create a copy of the conversation to avoid history truncation in the UICOMMENT
MEDIUMxinference/thirdparty/megatts3/tts/infer_cli.py49 # Define the output path with a .wav extensionCOMMENT
MEDIUM…erence/thirdparty/megatts3/tts/utils/audio_utils/io.py63 # Define the output path with a .wav extensionCOMMENT
MEDIUMxinference/thirdparty/mlx/flux/flux.py142 # Create the latent variablesCOMMENT
MEDIUMxinference/thirdparty/matcha/onnx/export.py164 # Create the output directory (if not exists)COMMENT
MEDIUMxinference/thirdparty/indextts/infer_v2.py1134 # Create a temporary file for the complete audioCOMMENT
MEDIUM…irdparty/indextts/gpt/transformers_generation_utils.py431 # Create the causal mask with fixed shape in advance, to reduce recompilations. If the function to createCOMMENT
MEDIUMxinference/thirdparty/indextts/BigVGAN/ECAPA_TDNN.py246 """This class implements an attentive statistic pooling layer for each channel.STRING
MEDIUMxinference/thirdparty/indextts/BigVGAN/ECAPA_TDNN.py585 """This class implements the cosine similarity on the top of features.STRING
MEDIUMxinference/thirdparty/indextts/BigVGAN/nnet/CNN.py24 """This function implements SincConv (SincNet).STRING
MEDIUMxinference/thirdparty/indextts/BigVGAN/nnet/CNN.py306 """This function implements 1d convolution.STRING
MEDIUM…/utils/maskgct/models/codec/facodec/facodec_trainer.py521 # Create the normalized F0 sequence with unvoiced framesCOMMENT
MEDIUMxinference/thirdparty/indextts/s2mel/modules/commons.py382 # Create the normalized F0 sequence with unvoiced framesCOMMENT
MEDIUMdoc/source/gen_docs.py67 # Create a proper ModuleSpec that importlib.util.find_spec can findCOMMENT
MEDIUMdoc/source/norm_zh.py15# This file is derived from https://github.com/mars-project/mars/blob/master/docs/source/norm_zh.pyCOMMENT
Cross-Language Confusion25 hits · 141 pts
SeverityFileLineSnippetContext
HIGHbenchmark/benchmark_runner.py142 # "finish_reason": null,COMMENT
HIGHxinference/deploy/docker/pypiserver/selfcheck.py80 # live in a writable directory (not /dev/null).COMMENT
HIGHxinference/deploy/test/test_utils.py218 arg = '{"int_val": 10, "float_val": 1.5, "bool_val": false, "null_val": null}'CODE
HIGHxinference/deploy/test/test_utils.py324 result = handle_click_args_type('[1, "two", null, true, {"key": "value"}]')CODE
HIGHxinference/model/llm/tool_parsers/llama3_tool_parser.py53 # (e.g., True/False/None instead of true/false/null).COMMENT
HIGH…odel/llm/tool_parsers/tests/test_llama3_tool_parser.py41 model_output = '{"name": "test_func", "parameters": {"value": null}}'CODE
HIGHxinference/model/llm/tests/test_utils.py2614 "arguments": None, # null, left as-isCODE
HIGHxinference/model/llm/tests/test_utils.py2632 "arguments": "null", # valid JSON null, left as-isCODE
HIGHxinference/model/image/ocr/tests/test_deepdoc_parse.py167 # The field is omitted rather than set to null, so clients can relyCOMMENT
HIGHxinference/model/audio/minimax_music3.py170 "MiniMax-Music3 only accepts `voice` as null, an empty string, "CODE
HIGHxinference/model/audio/ace_step.py349 "ACE-Step 1.5 only accepts `voice` as null, an empty string, "CODE
HIGHxinference/api/restful_api.py955 "npm ci && npm run build" (this stages the export at the directoryCODE
HIGH…nference/api/tests/test_frontend_static_real_export.py18(``cd frontend && npm run build``) and runs this module againstSTRING
HIGHxinference/api/tests/test_anthropic_messages.py145 '"finish_reason":null}]}\n\n'CODE
HIGHxinference/api/tests/test_token_router_dispatch.py1272 yield b'data: {"choices":[{"delta":{"content":"hello"},"finish_reason":null}]}\n\n'CODE
HIGHxinference/thirdparty/audiotools/preference.py179 if (region != null) {CODE
HIGH…ference/thirdparty/fish_speech/tools/webui/__init__.py18 js="() => {const params = new URLSearchParams(window.location.search);if (!params.has('__theme')) {params.seCODE
HIGH…rence/thirdparty/ace_step_1_5/acestep/llm_inference.py800 logger.error("nano-vllm is not installed. Please install it using 'cd acestep/third_parts/nano-vllm && pip iCODE
HIGH…rence/thirdparty/ace_step_1_5/acestep/llm_inference.py801 return "❌ nano-vllm is not installed. Please install it using 'cd acestep/third_parts/nano-vllm && pip instaCODE
HIGH…ce_step_1_5/acestep/models/common/flow_edit_helpers.py50 """Reduce a ``(cond, null)``-packed prediction to a guided velocity.STRING
HIGH…ce_step_1_5/acestep/models/common/flow_edit_helpers.py184 torch.cat([enc_hs, null], dim=0),CODE
HIGH…odels/codec/speechtokenizer/modules/quantization/ac.py138 self.packer.push(b1)CODE
HIGH…odels/codec/speechtokenizer/modules/quantization/ac.py185 self.packer.push(b1)CODE
HIGH…odels/codec/speechtokenizer/modules/quantization/ac.py304 encoder.push(symbol, q_cdf)CODE
HIGH…nce/thirdparty/indextts/s2mel/modules/flow_matching.py88 # Stack original and CFG (null) inputs for batched processingCOMMENT
Redundant / Tautological Comments95 hits · 128 pts
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LOWxinference/core/worker.py3223 # Check if packages contain PyTorch system markers (#system_torch#, etc.)COMMENT
LOWxinference/core/worker.py3784 # Check if cancelled while waiting in queueCOMMENT
LOWxinference/model/utils.py2909 # Check if flash_attn is installedCOMMENT
LOWxinference/model/utils.py2917 # Check if CUDA is availableCOMMENT
LOWxinference/model/llm/reasoning_parser.py55 # Check if <think> is present in previous or delta.COMMENT
LOWxinference/model/llm/llm_family.py407 # Append the class to the list of transformer classesCOMMENT
LOWxinference/model/llm/harmony.py60 # Check if buffer ends with partial 'assistantfinal'COMMENT
LOWxinference/model/llm/harmony.py76 # Check if this is actually a new message starting with 'analysis'COMMENT
LOWxinference/model/llm/harmony.py102 # Check if buffer ends with partial 'assistantfinal'COMMENT
LOWxinference/model/llm/tool_parsers/qwen_tool_parser.py360 # Check if current output contains tool_call start tokenCOMMENT
LOW…ence/model/llm/tool_parsers/deepseek_r1_tool_parser.py86 # Check if this block is a tool callCOMMENT
LOWxinference/model/llm/tests/test_llm_model.py311 # Check if tool_calls is present and is a listCOMMENT
LOWxinference/model/llm/tests/test_llm_model.py325 # Check if arguments is a valid JSON stringCOMMENT
LOWxinference/model/llm/vllm/xavier/engine.py125 # Check if we have a cached last_output from the previous iteration.COMMENT
LOW…ce/model/llm/vllm/patches/hybrid_kv_cache_page_size.py107 # Check if the original problematic code existsCOMMENT
LOW…ce/model/llm/vllm/patches/hybrid_kv_cache_page_size.py119 # Check if all smaller pages divide max evenlyCOMMENT
LOWxinference/model/llm/transformers/core.py469 # Check if streamingCOMMENT
LOWxinference/model/llm/transformers/core.py1060 # Check if streamingCOMMENT
LOW…erence/model/llm/transformers/tests/test_tensorizer.py118 # Check if the logger.info was called with the expected message, indicating early return due to cache existenceCOMMENT
LOWxinference/model/llm/mlx/core.py179 # Check if next_generated method exists (new API)COMMENT
LOWxinference/model/llm/mlx/core.py440 # Check if there are any pending results (early results that arrived before queue was ready)COMMENT
LOWxinference/model/llm/mlx/core.py492 # Check if generation is finishedCOMMENT
LOWxinference/model/llm/mlx/core.py517 # Check if request is still in active setCOMMENT
LOWxinference/model/llm/mlx/core.py2102 # Check if processor supports audio to avoid feature_extractor errorsCOMMENT
LOWxinference/model/embedding/core.py216 # Check if sentences is a two-dimensional list of integersCOMMENT
LOWxinference/model/image/stable_diffusion/core.py916 # Check if we have a cancel callback for this requestCOMMENT
LOWxinference/thirdparty/fish_speech/tools/run_webui.py48 # Check if MPS or CUDA is availableCOMMENT
LOW…e/thirdparty/fish_speech/tools/server/model_manager.py37 # Check if MPS or CUDA is availableCOMMENT
LOWxinference/thirdparty/fish_speech/tools/server/views.py159 # Check if the text is too longCOMMENT
LOWxinference/thirdparty/fish_speech/tools/server/views.py166 # Check if streaming is enabledCOMMENT
LOW…/thirdparty/fish_speech/tools/server/agent/generate.py64 # Check if all samples are finishedCOMMENT
LOW…rty/fish_speech/tools/server/agent/generation_utils.py102 # Check if the token is semanticCOMMENT
LOW…nference/thirdparty/ace_step_1_5/acestep/gpu_config.py1217 # Check if a per-process memory fraction has been setCOMMENT
LOW…nference/thirdparty/ace_step_1_5/acestep/gpu_config.py1400 # Check if model size is in available modelsCOMMENT
LOW…rence/thirdparty/ace_step_1_5/acestep/llm_inference.py1688 # Check if user provided a meaningful negative prompt (not the default)COMMENT
LOW…rence/thirdparty/ace_step_1_5/acestep/llm_inference.py2889 # Check if this is a new field (no leading spaces and contains ':')COMMENT
LOW…rence/thirdparty/ace_step_1_5/acestep/llm_inference.py2979 # Check if keys need "model." prefix by inspecting first keyCOMMENT
LOW…rence/thirdparty/ace_step_1_5/acestep/llm_inference.py3287 # Check if all items are doneCOMMENT
LOW…ce/thirdparty/ace_step_1_5/acestep/model_downloader.py646 # Check if this is a known LM modelCOMMENT
LOW…ce/thirdparty/ace_step_1_5/acestep/model_downloader.py648 # Check if it might be a variant nameCOMMENT
LOW…ce/thirdparty/ace_step_1_5/acestep/model_downloader.py689 # Check if this is the default turbo model (part of main)COMMENT
LOW…ce/thirdparty/ace_step_1_5/acestep/model_downloader.py693 # Check if it's a known sub-modelCOMMENT
LOWxinference/thirdparty/ace_step_1_5/acestep/inference.py742 # Check if LM generation failedCOMMENT
LOWxinference/thirdparty/ace_step_1_5/acestep/inference.py913 # Check if generation failedCOMMENT
LOWxinference/thirdparty/ace_step_1_5/acestep/inference.py1154 # Check if LLM is initializedCOMMENT
LOWxinference/thirdparty/ace_step_1_5/acestep/inference.py1178 # Check if LLM returned empty metadata (error case)COMMENT
LOWxinference/thirdparty/ace_step_1_5/acestep/inference.py1331 # Check if LLM is initializedCOMMENT
LOWxinference/thirdparty/ace_step_1_5/acestep/inference.py1353 # Check if LLM returned empty metadata (error case)COMMENT
LOWxinference/thirdparty/ace_step_1_5/acestep/inference.py1505 # Check if LLM is initializedCOMMENT
LOWxinference/thirdparty/ace_step_1_5/acestep/inference.py1527 # Check if LLM returned empty metadata (error case)COMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py751 # Check if first token starts with a note (A-G, case insensitive, with optional leading space)COMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py1804 # Check if field is user-provided and we haven't started injecting yetCOMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py1260 # Check if new_prefix is a valid prefix in the active trieCOMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py1389 # Check if decoded token matches the prefix start (allowing for space prefixes)COMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py1424 # Check if this digit could lead to a valid final valueCOMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py1433 # Check if we can still reach min_valCOMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py1597 # Check if input contains </think> token sequenceCOMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py1750 # Check if we have tokens in queue for user-provided fieldCOMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py1763 # Check if we should stop at reasoning (after </think> tag)COMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py1766 # Check if the next token would complete the fixed stringCOMMENT
35 more matches not shown…
Modern AI Meta-Vocabulary15 hits · 52 pts
SeverityFileLineSnippetContext
MEDIUMxinference/core/tests/test_model.py276 # rerank/embedding model must run del + empty_cache so its VRAM isCOMMENT
MEDIUMxinference/core/tests/test_worker.py2074 # test terminate LLM model, then launch embedding modelCOMMENT
MEDIUMxinference/model/embedding/embed_family.py115# { embedding model name -> { engine name -> engine params } }COMMENT
MEDIUMxinference/model/embedding/core.py90# this class define the basic info of embedding modelCOMMENT
MEDIUM…nference/model/embedding/sentence_transformers/core.py528 # seems already support prompt in embedding modelCOMMENT
MEDIUMxinference/api/restful_api.py845 # Attach API instance for dependency injection (Depends(get_api), etc.)COMMENT
MEDIUMxinference/api/schemas/requests.py33 # <0 = cap at the model's max_tokens. Honored by the embedding model baseCOMMENT
MEDIUM…ference/thirdparty/deepseek_vl2/models/conversation.py33 # The number of few shot examplesCOMMENT
MEDIUM…irdparty/sensenova_u1/models/neo_unify/conversation.py52 # The number of few shot examplesCOMMENT
MEDIUMxinference/thirdparty/deepseek_vl/utils/conversation.py65 # The number of few shot examplesCOMMENT
MEDIUMxinference/thirdparty/internvl/conversation.py50 # The number of few shot examplesCOMMENT
MEDIUMxinference/thirdparty/whisper/transcribe.py402 # skip silence before possible hallucinationsCOMMENT
MEDIUMxinference/thirdparty/whisper/transcribe.py414 # if first segment might be a hallucination, skip leading silenceCOMMENT
MEDIUMxinference/thirdparty/whisper/transcribe.py422 # skip silence before any possible hallucination that is surroundedCOMMENT
MEDIUMxinference/thirdparty/whisper/transcribe.py423 # by silence or more hallucinationsCOMMENT
AI Slop Vocabulary22 hits · 45 pts
SeverityFileLineSnippetContext
LOWxinference/core/supervisor.py3403 # Not launched perhaps, just return 0.0 to prevent errorCOMMENT
LOWxinference/model/utils.py3062 # New model from user, just add itCOMMENT
LOWxinference/model/llm/llm_family.py633 # TODO: If user does not specify quantization, just use the first oneCOMMENT
MEDIUMxinference/model/llm/core.py252 # Use model_specs from huggingface, as HuggingFace is the most comprehensive.COMMENT
LOWxinference/model/embedding/embed_family.py105 # TODO: If user does not specify quantization, just use the first oneCOMMENT
LOWxinference/model/rerank/rerank_family.py104 # TODO: If user does not specify quantization, just use the first oneCOMMENT
LOW…erence/thirdparty/cosyvoice/transformer/convolution.py124 # It's better we just return None if no cache is required,COMMENT
MEDIUMxinference/thirdparty/cosyvoice/utils/executor.py45 # A context manager to be used in conjunction with an instance ofCOMMENT
MEDIUMxinference/thirdparty/cosyvoice/utils/executor.py97 # A context manager to be used in conjunction with an instance ofCOMMENT
MEDIUMxinference/thirdparty/sensenova_u1/utils/param_count.py166 # parameter, which is robust to mixed-dtype checkpoints (e.g. normsCOMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py1793 # Avoid infinite recursion: if we're still in a fixed_strings state, just return scoresCOMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py1795 # This shouldn't happen, but if it does, just return scores to avoid recursionCOMMENT
LOW…ep/third_parts/nano-vllm/nanovllm/engine/llm_engine.py65 # For now, just use the same prompt (user should provide unconditional_prompt)COMMENT
MEDIUM…irdparty/ace_step_1_5/acestep/core/scoring/lm_score.py339 # Calculate recall using the robust logicCOMMENT
LOWxinference/thirdparty/f5_tts/model/cfm.py136 duration = torch.maximum(lens + 1, duration) # just add one token so something is generatedCODE
LOWxinference/thirdparty/f5_tts/model/dataset.py214 # if want to have different batches between epochs, may just set a seed and log it in ckptCOMMENT
MEDIUMxinference/thirdparty/f5_tts/infer/speech_edit.py54# [leverage https://github.com/MahmoudAshraf97/ctc-forced-aligner to get char level alignment]COMMENT
MEDIUM…irdparty/indextts/gpt/transformers_generation_utils.py372 # (this alternative is not as robust as calling `generate` and letting it create `cache_position`)COMMENT
MEDIUM…irdparty/indextts/gpt/transformers_generation_utils.py648 # 1. Check whether the user has defined `decoder_input_ids` manually. To facilitate in terms of input naming,COMMENT
LOW…ce/thirdparty/indextts/gpt/transformers_beam_search.py854 # generation. In these cases we simply return the highest scoring outputs.STRING
LOW…thirdparty/indextts/gpt/transformers_modeling_utils.py5402 # We can probably just use the multi-head attention module of PyTorch >=1.1.0STRING
LOWxinference/thirdparty/indextts/gpt/conformer_encoder.py146 # It's better we just return None if no cache is required,COMMENT
Structural Annotation Overuse28 hits · 43 pts
SeverityFileLineSnippetContext
LOW…m/tool_parsers/tests/test_deepseek_v3_1_tool_parser.py281 # Step 1: Part 1 of end tokenCOMMENT
LOW…m/tool_parsers/tests/test_deepseek_v3_1_tool_parser.py288 # Step 2: Part 2 of end tokenCOMMENT
LOWxinference/model/llm/tests/test_stream_options.py1015 # Step 1: Get the initial response with stream=TrueCOMMENT
LOWxinference/model/llm/tests/test_stream_options.py1033 # Step 2: Get the final response after tool calls with stream=TrueCOMMENT
LOWxinference/model/llm/tests/test_stream_options.py1051 # Step 3: Get the initial response with stream=FalseCOMMENT
LOWxinference/model/llm/tests/test_stream_options.py1068 # Step 4: Get the final response after tool calls with stream=FalseCOMMENT
LOWxinference/thirdparty/fish_speech/tools/fish_e2e.py106 # Step 1: Encode audio using VQGANCOMMENT
LOWxinference/thirdparty/fish_speech/tools/fish_e2e.py135 # Step 2: Prepare LLM requestCOMMENT
LOWxinference/thirdparty/fish_speech/tools/fish_e2e.py182 # Step 3: Stream LLM response and decode audioCOMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py719 # Step 1: Encode full string "keyscale: {keyscale}" (with space, as tokenizer sees it)COMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py723 # Step 2: Find where context ends in full_token_idsCOMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py738 # Step 3: Extract keyscale value tokens (everything after context)COMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py741 # Step 4: Verify we extracted some tokens (sanity check)COMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py747 # Step 5: Verify first token is a note (A-G)COMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py759 # Step 6: Build prefix mappings from keyscale value tokensCOMMENT
LOW…1_5/acestep/models/turbo/modeling_acestep_v15_turbo.py156 # Step 1: Concatenate hidden states and masks along sequence dimensionCOMMENT
LOW…1_5/acestep/models/turbo/modeling_acestep_v15_turbo.py162 # Step 2: Sort indices so that mask values of 1 come before 0COMMENT
LOW…1_5/acestep/models/turbo/modeling_acestep_v15_turbo.py165 # Step 3: Reorder hidden states using sorted indicesCOMMENT
LOW…1_5/acestep/models/turbo/modeling_acestep_v15_turbo.py168 # Step 4: Create new mask based on valid sequence lengthsCOMMENT
LOW…1_5/acestep/models/turbo/modeling_acestep_v15_turbo.py500 # Step 1: Self-attention with adaptive layer norm (AdaLN)COMMENT
LOW…1_5/acestep/models/turbo/modeling_acestep_v15_turbo.py516 # Step 2: Cross-attention (if enabled) for conditioning on encoder outputsCOMMENT
LOW…1_5/acestep/models/turbo/modeling_acestep_v15_turbo.py531 # Step 3: Feed-forward (MLP) with adaptive layer normCOMMENT
LOW…hirdparty/ace_step_1_5/acestep/models/mlx/dit_model.py329 # Step 1: Self-attention with AdaLNCOMMENT
LOW…hirdparty/ace_step_1_5/acestep/models/mlx/dit_model.py339 # Step 2: Cross-attentionCOMMENT
LOW…hirdparty/ace_step_1_5/acestep/models/mlx/dit_model.py350 # Step 3: MLP with AdaLNCOMMENT
LOW…irdparty/indextts/gpt/transformers_generation_utils.py3549 # IMPORTANT: Note that this should appear BEFORE the call to _reorder_cache() to save the maximum memorySTRING
LOW…irdparty/indextts/gpt/transformers_generation_utils.py3842 # IMPORTANT: Note that this should appear BEFORE the call to _reorder_cache() to save the maximum memorySTRING
LOW…irdparty/indextts/gpt/transformers_generation_utils.py4080 # IMPORTANT: Note that this should appear BEFORE the call to _reorder_cache() to save the maximum memorySTRING
Verbosity Indicators25 hits · 42 pts
SeverityFileLineSnippetContext
LOW…m/tool_parsers/tests/test_deepseek_v3_1_tool_parser.py281 # Step 1: Part 1 of end tokenCOMMENT
LOW…m/tool_parsers/tests/test_deepseek_v3_1_tool_parser.py288 # Step 2: Part 2 of end tokenCOMMENT
LOWxinference/model/llm/tests/test_stream_options.py1015 # Step 1: Get the initial response with stream=TrueCOMMENT
LOWxinference/model/llm/tests/test_stream_options.py1033 # Step 2: Get the final response after tool calls with stream=TrueCOMMENT
LOWxinference/model/llm/tests/test_stream_options.py1051 # Step 3: Get the initial response with stream=FalseCOMMENT
LOWxinference/model/llm/tests/test_stream_options.py1068 # Step 4: Get the final response after tool calls with stream=FalseCOMMENT
LOWxinference/thirdparty/fish_speech/tools/fish_e2e.py106 # Step 1: Encode audio using VQGANCOMMENT
LOWxinference/thirdparty/fish_speech/tools/fish_e2e.py135 # Step 2: Prepare LLM requestCOMMENT
LOWxinference/thirdparty/fish_speech/tools/fish_e2e.py182 # Step 3: Stream LLM response and decode audioCOMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py719 # Step 1: Encode full string "keyscale: {keyscale}" (with space, as tokenizer sees it)COMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py723 # Step 2: Find where context ends in full_token_idsCOMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py738 # Step 3: Extract keyscale value tokens (everything after context)COMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py741 # Step 4: Verify we extracted some tokens (sanity check)COMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py747 # Step 5: Verify first token is a note (A-G)COMMENT
LOW…y/ace_step_1_5/acestep/constrained_logits_processor.py759 # Step 6: Build prefix mappings from keyscale value tokensCOMMENT
LOW…1_5/acestep/models/turbo/modeling_acestep_v15_turbo.py156 # Step 1: Concatenate hidden states and masks along sequence dimensionCOMMENT
LOW…1_5/acestep/models/turbo/modeling_acestep_v15_turbo.py162 # Step 2: Sort indices so that mask values of 1 come before 0COMMENT
LOW…1_5/acestep/models/turbo/modeling_acestep_v15_turbo.py165 # Step 3: Reorder hidden states using sorted indicesCOMMENT
LOW…1_5/acestep/models/turbo/modeling_acestep_v15_turbo.py168 # Step 4: Create new mask based on valid sequence lengthsCOMMENT
LOW…1_5/acestep/models/turbo/modeling_acestep_v15_turbo.py500 # Step 1: Self-attention with adaptive layer norm (AdaLN)COMMENT
LOW…1_5/acestep/models/turbo/modeling_acestep_v15_turbo.py516 # Step 2: Cross-attention (if enabled) for conditioning on encoder outputsCOMMENT
LOW…1_5/acestep/models/turbo/modeling_acestep_v15_turbo.py531 # Step 3: Feed-forward (MLP) with adaptive layer normCOMMENT
LOW…hirdparty/ace_step_1_5/acestep/models/mlx/dit_model.py329 # Step 1: Self-attention with AdaLNCOMMENT
LOW…hirdparty/ace_step_1_5/acestep/models/mlx/dit_model.py339 # Step 2: Cross-attentionCOMMENT
LOW…hirdparty/ace_step_1_5/acestep/models/mlx/dit_model.py350 # Step 3: MLP with AdaLNCOMMENT
Synthetic Comment Markers1 hit · 11 pts
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HIGHxinference/api/tests/test_ocr_pdf.py531 # 200 A4 pages at zoomin 3 is only 0.902 G px as requested, so theCOMMENT
Slop Phrases4 hits · 10 pts
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MEDIUMxinference/thirdparty/melo/text/chinese.py73 assert len(word2ph) == len(text) # Sometimes it will crash,you can add a try-catch.CODE
MEDIUMxinference/thirdparty/melo/text/chinese_mix.py80 # assert len(word2ph) == len(text) # Sometimes it will crash,you can add a try-catch.COMMENT
LOW…rence/thirdparty/ace_step_1_5/acestep/llm_inference.py2907 # Don't forget to save the last fieldCOMMENT
MEDIUM…nce/thirdparty/f5_tts/train/datasets/prepare_emilia.py2# if use updated new version, i.e. WebDataset, feel free to modify / draft your own scriptCOMMENT
Hallucination Indicators1 hit · 10 pts
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CRITICALxinference/thirdparty/audiotools/core/util.py475 batch[k] = torch.utils.data._utils.collate.default_collate(v)CODE
Magic Placeholder Names1 hit · 5 pts
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HIGHxinference/thirdparty/fish_speech/tools/api_client.py176 "authorization": "Bearer YOUR_API_KEY",CODE
Fake / Example Data3 hits · 4 pts
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LOWdoc/source/norm_zh.py62 ... "Lorem ipsum dolor sit amet, consectetur adipisicing elit, "CODE
LOWdoc/source/norm_zh.py62 ... "Lorem ipsum dolor sit amet, consectetur adipisicing elit, "CODE
LOWdoc/source/norm_zh.py66 " \"Lorem ipsum dolor sit "CODE
Example Usage Blocks2 hits · 2 pts
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LOWxinference/thirdparty/fish_speech/tools/fish_e2e.py263# Example usage:COMMENT
LOW…party/matcha/utils/get_durations_from_trained_model.py192 # Example usage:STRING
Overly Generic Function Names1 hit · 1 pts
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LOW…ce/thirdparty/fish_speech/tools/llama/build_dataset.py65def run_task(task):CODE