Registro públicoBueno
Informe de salud del softwareesquema 0.27.0 · métricas 1.13.0 · 2026-07-28 09:52 UTC
vllm-project / tpu-inference
TPU inference for vLLM, with unified JAX and PyTorch support.
vllm-project/tpu-inference tiene un índice de salud de 75 sobre 100, lo que lo sitúa en la banda Bueno. Su puntuación más alta es Vitality (100/100) y la más baja, Security (21/100). Se actualizó por última vez hoy. 5 personas concentran la mayor parte del trabajo reciente.
75
global / 100Índice de salud del software
Las métricas se agrupan en categorías ponderadas sobre una escala de 1 a 100. El resultado global parte de su media; cuando la evidencia pública activa la Política de Jurisdicciones de Alto Riesgo, la calificación se ajusta y recibe el límite 49 (En riesgo). Preparación para IA queda fuera.
75
Excelente85-100Ejemplar; cumple prácticamente todos los criterios evaluados
Bueno70-84Saludable; carencias menores
Moderado50-69Aceptable con carencias notables; se recomienda revisión
En riesgo30-49Debilidades significativas; su adopción exige cautela
Crítico1-29Problemas graves (proyecto abandonado, un solo mantenedor, sin higiene)
Perfil de puntuación
Cada eje es una categoría. La forma importa más que la media: un proyecto sano llena toda la figura, mientras que un perfil de picos y cráteres indica que la fortaleza en una dimensión enmascara el riesgo en otra.
Titularidad
vLLMOrganización
3772 seguidores46 repositorios públicosdesde jun 2023
Este repositorio está respaldado por una organización: una custodia compartida y responsable que puede sobrevivir a cualquier mantenedor individual.
Ecosistemas de paquetes
| Registro | Paquete | Versión | Descargas / mes | Versiones | Última publicación |
|---|---|---|---|---|---|
| PyPI | tpu_inference | 0.25.0 | 43.373 | 284 | hace 6 días |
Métricas por categoría
Vitalidad
¿Está vivo el proyecto: se escribe código y se publican versiones?
100
Actividad de desarrollo
100Excelente
Cómo se puntúa
| 36/36 | Recencia de push — último push hace 0 días |
| 36/36 | Cadencia de commits — 52/52 semanas con commits |
| 18/18 | Volumen de commits — 3251 commits en el último año |
| 0/10 | OpenSSF Scorecard: Maintained — sin datos |
Datos de entrada utilizados
| commits_last_year | 3251 |
| human_commit_share | 1 |
| days_since_last_push | 0 |
| active_weeks_last_year | 52 |
Disciplina de publicación
100Excelente
Cómo se puntúa
| 27/27 | Publica versiones — 10 versiones publicadas |
| 36/36 | Recencia de las versiones — última versión hace 6 días |
| 27/27 | Cadencia de publicación — una versión cada ~24,6 días |
| 0/10 | OpenSSF Scorecard: Signed-Releases — sin datos |
Datos de entrada utilizados
| releases_count | 10 |
| latest_release_tag | v0.25.0 |
| releases_from_tags | no |
| days_since_latest_release | 6 |
| mean_days_between_releases | 24,6 |
Comunidad y Adopción
¿Tiene el proyecto usuarios, descargas, atención y unas condiciones acogedoras para quienes contribuyen?
73
Popularidad y adopción
68Moderado
Cómo se puntúa
| 42.1/60 | Estrellas — 393 estrellas |
| 20.3/25 | Forks — 271 forks |
| 5.6/15 | Observadores — 11 observadores |
Datos de entrada utilizados
| forks | 271 |
| stars | 393 |
| watchers | 11 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Salud de la comunidad
77Bueno
Cómo se puntúa
| 22.5/22.5 | README |
| 22.5/22.5 | Licencia — licencia reconocida (Apache-2.0) |
| 18/18 | Guía CONTRIBUTING |
| 0/13.5 | Código de conducta |
| 0/7.2 | Plantilla de issues |
| 6.3/6.3 | Plantilla de PR |
Datos de entrada utilizados
| has_readme | sí |
| has_license | sí |
| has_contributing | sí |
| has_issue_template | no |
| has_code_of_conduct | no |
| has_pull_request_template | sí |
Cómo se puntúa
| 61.8/80 | Descargas mensuales — 43.373 descargas/mes en pypi |
| 0/20 | Dependientes en el registro — no lo informa este ecosistema |
Datos de entrada utilizados
| packages | tpu_inference |
| dependents | — |
| ecosystems | pypi |
| total_downloads | — |
| monthly_downloads | 43.373 |
Excluidos de la puntuación (sin datos o no aplicable): Dependientes en el registro. Los pesos restantes se han renormalizado.
Sostenibilidad y Gobernanza
¿Sobrevivirá el proyecto a sus personas: factor bus, capacidad de respuesta, quién lo respalda y mantenimiento del paquete?
80
Cómo se puntúa
| 45.9/54 | Factor bus — la mitad de los commits recae en 5 contribuyente(s) |
| 14.8/22.5 | Distribución de commits — el principal contribuyente firma el 34% de los commits |
| 13.5/13.5 | Amplitud de contribuyentes — 100 contribuyentes |
| 0/10 | OpenSSF Scorecard: Contributors — sin datos |
Datos de entrada utilizados
| bus_factor | 5 |
| contributors_sampled | 100 |
| top_contributor_share | 0,343 |
Cómo se puntúa
| 25.6/46.8 | Resolución de issues — 55% de issues cerradas |
| 33.5/38.3 | Aceptación de PR — 2452/2803 PR decididos fusionados |
| 0/15 | OpenSSF Scorecard: Code-Review — sin datos |
Datos de entrada utilizados
| merged_prs | 2452 |
| open_issues | 72 |
| closed_issues | 87 |
| issue_closed_ratio | 0,547 |
| closed_unmerged_prs | 351 |
Propiedad y custodia
73Bueno
Cómo se puntúa
| 30/30 | Respaldo de la propiedad — propiedad de una organización |
| 0/20 | Dominio verificado |
| 25/25 | Alcance del propietario — 3772 seguidores de vllm-project |
| 18.4/25 | Trayectoria — 46 repos públicos, cuenta de ~3 años |
Datos de entrada utilizados
| followers | 3772 |
| owner_type | Organization |
| is_verified | — |
| owner_login | vllm-project |
| public_repos | 46 |
| account_age_days | 1135 |
Mantenimiento de paquetes
100Excelente
Cómo se puntúa
| 25/25 | Publicado y resoluble — 1 paquete(s) en pypi |
| 35/35 | Recencia de publicación — última publicación hace 6 días |
| 20/20 | Historial de versiones — 284 versiones en el registro |
| 20/20 | No obsoleto — activo, ni obsoleto ni retirado |
Datos de entrada utilizados
| packages | tpu_inference |
| ecosystems | pypi |
| any_deprecated | no |
| min_days_since_publish | 6 |
Calidad de Ingeniería
¿Existen unas prácticas mínimas de ingeniería y documentación?
87
Prácticas de ingeniería
92Excelente
Cómo se puntúa
| 24/24 | Flujos de trabajo de CI — 5 flujo(s) de trabajo |
| 24/24 | Pruebas presentes |
| 16/16 | Configuración de linter |
| 9.6/9.6 | Hooks de pre-commit |
| 0/6.4 | .editorconfig |
| 0/20 | OpenSSF Scorecard: CI-Tests — sin datos |
Datos de entrada utilizados
| has_ci | sí |
| has_tests | sí |
| has_editorconfig | no |
| has_linter_config | sí |
| has_precommit_config | sí |
Documentación
80Bueno
Cómo se puntúa
| 30/30 | README |
| 25/25 | Directorio de documentación |
| 15/15 | Sitio de documentación / página del proyecto — https://docs.vllm.ai/projects/tpu |
| 10/10 | Descripción del repositorio |
| 0/10 | Topics |
| 0/10 | Wiki |
Datos de entrada utilizados
| topics | — |
| has_wiki | no |
| homepage | https://docs.vllm.ai/projects/tpu |
| has_readme | sí |
| has_docs_dir | sí |
| has_description | sí |
Seguridad
¿Son sólidas las prácticas visibles de seguridad y de cadena de suministro, sin exposición jurisdiccional de alto riesgo sin resolver?
21
Postura de seguridad
1Crítico
Cómo se puntúa
| 0/30 | Política de seguridad (SECURITY.md) |
| 0/25 | Configuración de Dependabot |
| 0/25 | Lockfiles de dependencias — biblioteca publicada — los lockfiles son cosa de las aplicaciones, no se esperan aquí |
| 0/20 | Flujo de trabajo de CodeQL |
Datos de entrada utilizados
| source | file_signals |
| lockfiles | — |
| manifests | docs/requirements.txt, pyproject.toml, requirements.txt, requirements_benchmarking.txt, requirements_test.txt, setup.py |
| has_codeql_workflow | no |
| has_security_policy | no |
| has_dependabot_config | no |
Excluidos de la puntuación (sin datos o no aplicable): Lockfiles de dependencias. Los pesos restantes se han renormalizado.
Avisos de dependencias
100Excelente
Cómo se puntúa
| 35/35 | Dependencias directas libres de avisos conocidos — ninguna dependencia directa tiene un aviso conocido |
| 25/25 | Dependencias indirectas libres de avisos conocidos — ninguna dependencia indirecta tiene un aviso conocido |
| 0/40 | Sin avisos pendientes — ningún aviso tiene fecha de publicación |
Datos de entrada utilizados
| source | osv |
| advisories | 0 |
| affected_packages | 0 |
| assessed_packages | 141 |
| unassessed_packages | 0 |
| affected_by_severity | none |
| direct_affected_packages | 0 |
Excluidos de la puntuación (sin datos o no aplicable): Sin avisos pendientes. Los pesos restantes se han renormalizado. Se cotejó el cierre de dependencias en tiempo de ejecución de pypi:tpu_inference@0.25.0 —lo que arrastra la instalación del paquete publicado—: 141 paquetes. No se analiza la alcanzabilidad.
Preparación para IA
¿Hasta qué punto está el repositorio preparado para desarrollarse y mantenerse con agentes de codificación de IA? Es una insignia independiente y experimental — peso 0,0, de modo que se presenta por separado y no afecta a la puntuación de salud global.
41
Contexto y guía para agentes
25Crítico
Cómo se puntúa
| 0/45 | Instrucciones para agentes — sin CLAUDE.md / AGENTS.md / reglas de editor |
| 0/15 | Documentación legible por máquinas (llms.txt) |
| 25.1/40 | Historial de commits legible — 47 de 100 commits humanos declaran su intención (asunto estructurado o cuerpo explicativo) |
Datos de entrada utilizados
| has_llms_txt | no |
| legible_history_share | 0,47 |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
Cómo se puntúa
| 0/18 | Arranque con un solo comando |
| 22/22 | Pruebas automatizadas |
| 11/11 | Configuración de lint / formato |
| 0/11 | Verificación estática de tipos |
| 10/10 | Entorno reproducible — Dockerfile |
| 0/10 | Práctica demostrada con agentes — ningún commit con autoría de agente entre los últimos 100 |
| 0/8 | Mantenimiento automatizado — no se observan actualizaciones automáticas de dependencias |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — sin datos |
Datos de entrada utilizados
| has_nix | no |
| has_tests | sí |
| lockfiles | — |
| has_dockerfile | sí |
| typed_language | no |
| bootstrap_files | — |
| has_devcontainer | no |
| has_linter_config | sí |
| typecheck_configs | — |
| agent_commit_share | 0 |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0 |
Legibilidad del código para modelos
54Moderado
Cómo se puntúa
| 0/45 | Código verificable por tipos — Python sin configuración de verificación de tipos |
| 53.5/55 | Tamaños de archivo manejables — 16/601 archivos fuente de más de 60 KB |
Datos de entrada utilizados
| primary_language | Python |
| largest_source_bytes | 231.672 |
| source_files_sampled | 601 |
| oversized_source_files | 16 |
Interfaces legibles por máquina
40En riesgo
Cómo se puntúa
| 0/40 | Esquema de API (OpenAPI/GraphQL/proto) |
| 0/20 | Servidor MCP |
| 40/40 | Ejemplos ejecutables — examples, sample |
Datos de entrada utilizados
| example_dirs | examples, sample |
| has_mcp_signal | no |
| api_schema_files | — |
Datos clave
393estrellas de GitHub
100contribuidores
3251commits en los últimos 12 meses
0días desde el último push
10versiones publicadas
5factor bus
72issues abiertas
PyPIecosistemas de paquetes
Advertencias de recopilación de datos
- Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
- GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
- OpenSSF Scorecard did not return a usable result (exit code -9); skipping Scorecard checks
Más detalle
Historial de estrellas y forks 0 ★ / 271 ⇿
0Estrellas
271Forks
10Versiones
Cuándo se añadió cada estrella y fork, recopilado de GitHub y agrupado por día. El crecimiento acumulado se sitúa justo encima de las adiciones diarias que lo componen, de modo que ambos se leen en conjunto: la acumulación orgánica sostenida no se parece en nada a un pico abrupto y efímero. Cuando esa diferencia es medible, se informa como autenticidad del crecimiento.
Mayor 0Menor 8Parche 2
Todas las dependencias no recopilado
No fue posible recopilar el conjunto de dependencias resuelto para este informe: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
Avisos de dependencias 0
Instalar pypi:tpu_inference@0.25.0 arrastra 141 paquetes, directos y transitivos: 0 tienen avisos conocidos, de los cuales 0 son dependencias directas.
Ningún aviso conocido afecta a las dependencias evaluadas.
Un aviso significa que la versión registrada en el grafo de dependencias cae dentro del rango afectado de un aviso. No se analiza la alcanzabilidad, y el grafo incluye fijaciones de desarrollo y prueba: un hallazgo puede referirse al utillaje y no al software distribuido.
Informe JSON sin procesar legible por máquina
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"description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
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],
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},
"warnings": [
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"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/v/vllm-project/tpu-inference.svg",
"full_name": "vllm-project/tpu-inference",
"license_state": "standard",
"license_spdx": "Apache-2.0"
}Las puntuaciones son señales, no garantías. Reflejan prácticas públicamente visibles en GitHub; no son una auditoría de código ni una garantía de seguridad.
Los datos ausentes se excluyen y los pesos se renormalizan; nunca se puntúan como cero. La metodología es versionada y abierta: métricas v1.13.0, esquema v0.27.0 — metodología completa · wiki de métricas.
Cómo se sitúa un resultado dentro del registro general: estadísticas agregadas — PyPI.