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#: ../../source/development/xinference_internals.rst:3
msgid "The internals of Xinference"
msgstr "Estrutura interna do Xinference"

#: ../../source/development/xinference_internals.rst:6
msgid "Table of contents:"
msgstr "Índice"

#: ../../source/development/xinference_internals.rst:9
msgid "Overview"
msgstr "Visão geral"

#: ../../source/development/xinference_internals.rst:10
msgid ""
"Xinference leverages `Xoscar <https://github.com/xorbitsai/xoscar>`_, an "
"actor programming framework we designed, as its core component to manage "
"machines, devices, and model inference processes. Each actor serves as a "
"basic unit for model inference and various inference backends can be "
"integrate into the actor, enabling us to support multiple inference engines "
"and hardware. These actors are hosted and scheduled within actor pools, "
"which are designed to be asynchronous and non-blocking and function as "
"resource pools."
msgstr ""
"Xinference utiliza o framework de programação actor `Xoscar "
"<https://github.com/xorbitsai/xoscar>`_, que projetamos, como seu componente"
" principal para gerenciar máquinas, dispositivos e processos de inferência "
"de modelos. Cada actor é uma unidade básica de inferência de modelos, e "
"vários backends de inferência podem ser integrados nos actors, permitindo-"
"nos suportar múltiplos mecanismos de inferência e hardwares. Esses actors "
"são hospedados e escalonados em um pool de actors, que funciona como um pool"
" de recursos. O design dos actors é assíncrono e não bloqueante."

#: ../../source/development/xinference_internals.rst:22
msgid ""
"Both supervisor and worker are actor instances. Initially, an actor pool, "
"serving as a resource pool, needs to be created on each server; and each "
"actor can utilize a CPU core or a GPU device. Each server has its own "
"address (IP address or hostname), so actors on different computing nodes can"
" communicate with each other through these addresses. See `Actor`_ for more "
"information."
msgstr ""
"O `supervisor` e o `worker` são instâncias de atores. Primeiro, é necessário"
" criar um pool de atores em cada servidor, que funciona como um pool de "
"recursos; cada ator pode utilizar um núcleo de CPU ou um dispositivo GPU. "
"Cada servidor possui seu próprio endereço (endereço IP ou nome de host), "
"portanto, atores em diferentes nós de computação podem se comunicar entre si"
" por meio desses endereços. Para mais informações, consulte `Actor`_."

#: ../../source/development/xinference_internals.rst:27
msgid "RESTful API"
msgstr "RESTful API"

#: ../../source/development/xinference_internals.rst:28
msgid ""
"The RESTful API is implemented using `FastAPI "
"<https://github.com/tiangolo/fastapi>`_, as specified in `api/restful_api.py"
" "
"<https://github.com/xorbitsai/inference/tree/main/xinference/api/restful_api.py>`_."
msgstr ""
"A API RESTful é implementada utilizando `FastAPI "
"<https://github.com/tiangolo/fastapi>`_, e o código específico está em "
"`api/restful_api.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/api/restful_api.py>`_."

#: ../../source/development/xinference_internals.rst:35
msgid ""
"This is an example of the API ``/status``, it's corresponding function is "
"``get_status``. You can add connection between RESTful API and the backend "
"function you want in `api/restful_api.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/api/restful_api.py>`_."
msgstr ""
"Este é um exemplo de API. A API ``/status`` corresponde à função "
"``get_status``. Você pode adicionar a relação entre a API RESTful e a função"
" de backend correspondente em `api/restful_api.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/api/restful_api.py>`_."

#: ../../source/development/xinference_internals.rst:39
msgid "Command Line"
msgstr "Linha de comando"

#: ../../source/development/xinference_internals.rst:40
msgid ""
"The Command Line is implemented using `Click "
"<https://click.palletsprojects.com/>`_, as specified in `deploy/cmdline.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/deploy/cmdline.py>`_,"
" allowing users to interact with the Xinference deployment features directly"
" from the terminal."
msgstr ""
"A interface de linha de comando é implementada através do `Click "
"<https://click.palletsprojects.com/>`_, com o código específico em "
"`deploy/cmdline.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/deploy/cmdline.py>`_."
" A linha de comando permite que os usuários interajam diretamente com o "
"Xinference pelo terminal."

#: ../../source/development/xinference_internals.rst:45
msgid "Entry Points"
msgstr "Entrada"

#: ../../source/development/xinference_internals.rst:46
msgid "Take the command-lines we implemented as examples:"
msgstr "Com o exemplo da linha de comando que implementamos:"

#: ../../source/development/xinference_internals.rst:48
msgid ""
"``xinference``: Provides commands for model management, including "
"registering/unregistering models, listing all registered/running models, and"
" launching or terminating specific models. It also features interactive "
"commands like generate and chat for testing and interacting with deployed "
"models in real-time."
msgstr ""
"``xinference``: fornece comandos para gerenciamento de modelos, incluindo "
"registrar/cancelar registro de modelos, listar todos os modelos "
"registrados/em execução, além de iniciar ou encerrar modelos específicos. "
"Também oferece comandos interativos, como geração de linguagem e bate-papo, "
"para testar ou interagir com modelos implantados."

#: ../../source/development/xinference_internals.rst:52
msgid "``xinference-local``: Starts a local Xinference service."
msgstr "``xinference-local``: inicie um serviço local do Xinference."

#: ../../source/development/xinference_internals.rst:54
msgid ""
"``xinference-supervisor``: Initiates a supervisor process that manages and "
"monitors worker actors within a distributed setup."
msgstr ""
"``xinference-supervisor``: Inicia o processo supervisor, que gerencia e "
"monitora os workers actors em um ambiente distribuído."

#: ../../source/development/xinference_internals.rst:56
msgid ""
"``xinference-worker``: Starts a worker process that executes tasks assigned "
"by the supervisor, utilizing available computational resources effectively."
msgstr ""
"``xinference-worker``: inicia o processo worker, utilizando os recursos "
"computacionais disponíveis para executar as tarefas atribuídas pelo "
"supervisor."

#: ../../source/development/xinference_internals.rst:59
msgid ""
"Each command is equipped with ``options`` and ``flags`` to customize its "
"behavior, such as specifying log levels, host addresses, port numbers, and "
"other relevant settings."
msgstr ""
"Cada comando é acompanhado por ``option`` e ``flag``, que permitem "
"personalizar seu comportamento, como especificar o nível de log, endereço do"
" host, número da porta e outras configurações relacionadas."

#: ../../source/development/xinference_internals.rst:62
msgid ""
"Python projects define command-line console entry points in "
"``pyproject.toml``."
msgstr ""
"Os projetos Python definem pontos de entrada de console de linha de comando "
"em ``pyproject.toml``."

#: ../../source/development/xinference_internals.rst:72
msgid ""
"The command-line ``xinference`` can be referred to code in "
"``xinference.deploy.cmdline:cli``."
msgstr ""
"A linha de comando ``xinference`` pode ser consultada no código em "
"``xinference.deploy.cmdline:cli``."

#: ../../source/development/xinference_internals.rst:75
msgid "Click"
msgstr "Click"

#: ../../source/development/xinference_internals.rst:76
msgid "We use Click to implement a specific command-line:"
msgstr "Usamos o Click para implementar uma linha de comando específica:"

#: ../../source/development/xinference_internals.rst:95
msgid ""
"For example, the ``xinference-local`` command allows you to define the host "
"address and port."
msgstr ""
"Por exemplo, o comando ``xinference-local`` permite que você defina o "
"endereço do host e a porta."

#: ../../source/development/xinference_internals.rst:98
msgid "Actor"
msgstr "Actor"

#: ../../source/development/xinference_internals.rst:99
msgid ""
"Xinference is fundamentally based on `Xoscar "
"<https://github.com/xorbitsai/xoscar>`_, our actor framework, which can "
"manage computational resources and Python processes to support scalable and "
"concurrent programming. The following is a pseudocode demonstrating how our "
"Worker Actor works, the actual Worker Actor is more complex than this."
msgstr ""
"Xinference é baseado no `Xoscar <https://github.com/xorbitsai/xoscar>`_, que"
" é nosso framework de atores, capaz de gerenciar recursos computacionais e "
"processos Python, suportando programação concorrente escalável. O "
"pseudocódigo abaixo demonstra o princípio de funcionamento do Worker Actor, "
"sendo que o Worker Actor real é muito mais complexo que isso."

#: ../../source/development/xinference_internals.rst:126
msgid ""
"We use the ``WorkerActor`` as an example to illustrate how we build the "
"Xinference. Each actor class is a standard Python class that inherits from "
"``xoscar.Actor``. An instance of this class is a specific actor within the "
"actor pool."
msgstr ""
"Tomamos ``WorkerActor`` como exemplo para explicar como construir o "
"Xinference. Cada classe de actor é uma classe Python padrão que herda de "
"``xoscar.Actor``. A instância dessa classe é um actor específico dentro do "
"pool de actors."

#: ../../source/development/xinference_internals.rst:130
msgid ""
"**Define Actor Actions**: Each actor needs to define certain actions or "
"behaviors to accomplish specific tasks. For instance, the model inference "
"``WorkerActor`` needs to launch the model (``launch_model``), list the "
"models in this actor (``list_models``), terminate a model "
"(``terminate_model``). There are two special methods worth noting. The "
"``__post_create__`` is invoked before the actor is created, allowing for "
"necessary initializations. The ``__pre_destroy__`` is called after the actor"
" is destroyed, allowing for cleanup or finalization tasks."
msgstr ""
"**Definindo o comportamento do Actor**: cada actor precisa definir "
"determinadas ações ou comportamentos para concluir tarefas específicas. Por "
"exemplo, o `WorkerActor` de inferência de modelo precisa iniciar o modelo "
"(`launch_model`), listar os modelos neste actor (`list_models`) e encerrar o"
" modelo (`terminate_model`). Dois métodos especiais merecem atenção. O "
"`__post_create__` é chamado antes da criação do actor para realizar a "
"inicialização necessária. Já o `__pre_destroy__` é chamado após a destruição"
" do actor para executar tarefas de limpeza."

#: ../../source/development/xinference_internals.rst:136
msgid ""
"**Reference Actor and Invoke Methods**: When an actor is created, it yields "
"a reference variable so that other actors can reference it. The actor "
"reference can also be referenced with the address. Suppose the "
"``WorkerActor`` is created and the reference variable is ``worker_ref``,  "
"the ``launch_model`` method of this actor class can be invoked by calling "
"``worker_ref.launch_model()``. Even if the actor's method is originally a "
"synchronized method, when called with an actor reference, it will become as "
"an asynchronous method."
msgstr ""
"**Referenciando um Actor e chamando métodos**: ao criar um Actor, uma "
"variável de referência é gerada para que outros Actors possam referenciá-lo."
" Actors também podem ser referenciados por endereço IP. Supondo que "
"``WorkerActor`` seja criado e a variável de referência seja ``worker_ref``, "
"é possível chamar o método ``launch_model`` dessa classe Actor através de "
"``worker_ref.launch_model()``. Mesmo que o método dentro do actor fosse "
"originalmente um método bloqueante tradicional, ao chamá-lo usando a "
"variável de referência, ele se torna um método assíncrono."

#: ../../source/development/xinference_internals.rst:143
msgid ""
"**Inference Engine**: The actor can manage the process, and the inference "
"engine is also a process. In the launch model part of the ``WorkerActor``, "
"we can initialize different inference engines according to the user's need. "
"Therefore, Xinference can support multiple inference engines and can easily "
"adapt to new inference engines in the future."
msgstr ""
"**Motor de Inferência**: O Actor pode gerenciar processos, e o motor de "
"inferência também é um tipo de processo. Na parte do modelo de inicialização"
" do ``WorkerActor``, podemos inicializar diferentes motores de inferência de"
" acordo com as necessidades do usuário. Portanto, o Xinference pode suportar"
" vários motores de inferência e se adaptar facilmente a novos motores de "
"inferência no futuro."

#: ../../source/development/xinference_internals.rst:148
msgid ""
"See `Xoscar document <https://xoscar.dev/en/latest/getting_started/llm-"
"inference.html>`_ for more actor use cases."
msgstr ""
"Consulte a `documentação do Xoscar "
"<https://xoscar.dev/en/latest/getting_started/llm-inference.html>`_ para "
"mais exemplos de uso de Actors."

#: ../../source/development/xinference_internals.rst:151
msgid "Asynchronous Programming"
msgstr "Programação assíncrona"

#: ../../source/development/xinference_internals.rst:153
msgid ""
"Both Xinference and Xoscar highly utilize asynchronous programming of "
"``asyncio``. Asynchronous programming is a programming paradigm that does "
"not block. Instead, requests and function calls are issued and executed in "
"the background and results are returned in the future. This enables us to "
"perform activities concurrently."
msgstr ""
"Xinference e Xoscar dependem fortemente da biblioteca de programação "
"assíncrona ``asyncio``. A programação assíncrona é um paradigma de "
"programação não bloqueante. Em comparação com chamadas de função bloqueantes"
" tradicionais, as requisições ou chamadas de função na programação "
"assíncrona são executadas em segundo plano, com os resultados retornados em "
"algum momento futuro. A vantagem da programação assíncrona é permitir que "
"muitas atividades ou tarefas diferentes sejam realizadas simultaneamente de "
"forma concorrente."

#: ../../source/development/xinference_internals.rst:159
msgid ""
"If you're not familiar with Pythons's ``asyncio``, you can see more "
"tutorials for help:"
msgstr ""
"Se você não está familiarizado com o ``asyncio`` do Python, pode consultar "
"mais tutoriais para obter ajuda:"

#: ../../source/development/xinference_internals.rst:161
msgid ""
"`Python Asyncio Tutorial <https://bbc.github.io/cloudfit-public-"
"docs/asyncio/asyncio-part-1.html>`__"
msgstr ""
"`Tutorial Python Asyncio <https://bbc.github.io/cloudfit-public-"
"docs/asyncio/asyncio-part-1.html>`__"

#: ../../source/development/xinference_internals.rst:163
msgid ""
"`Real Python's asyncio Tutorial <https://realpython.com/async-io-python/>`__"
msgstr ""
"`Tutorial asyncio do Real Python <https://realpython.com/async-io-"
"python/>`__"

#: ../../source/development/xinference_internals.rst:165
msgid ""
"`Python Official Documentation "
"<https://docs.python.org/3/library/asyncio.html>`__"
msgstr ""
"`Documentação Oficial do Python "
"<https://docs.python.org/3/library/asyncio.html>`__"

#: ../../source/development/xinference_internals.rst:169
msgid "Model"
msgstr "model"

#: ../../source/development/xinference_internals.rst:171
msgid ""
"Xinference supports different types of models including large language "
"models (LLMs), image models, audio models, embedding models, etc. All models"
" are implemented in `model/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference/model>`_."
msgstr ""
"Xinference suporta diferentes tipos de modelos, incluindo modelos de "
"linguagem de grande escala (LLM), modelos de imagem, modelos de áudio, "
"modelos de incorporação, entre outros. Todos os modelos são implementados na"
" pasta `model/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference/model>`_."

#: ../../source/development/xinference_internals.rst:175
msgid "LLM"
msgstr ""

#: ../../source/development/xinference_internals.rst:177
msgid ""
"Take `model/llm/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference/model/llm>`_ "
"for example, it focuses on the management and instantiation of LLMs. It "
"includes detailed implementations for loading, configuring, and deploying "
"LLMs."
msgstr ""
"Usando `model/llm/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference/model/llm>`_ "
"como exemplo, ele gerencia e inicia principalmente o LLM, incluindo "
"carregamento, configuração e execução de modelos de linguagem de grande "
"porte."

#: ../../source/development/xinference_internals.rst:181
msgid ""
"We support many backends such as GGML, PyTorch, and vLLM. Our generated "
"content is compatible with the format of OpenAI, supporting features such as"
" streaming output and returning chat completion format (for chat models "
"only). Therefore, there is a lot of adaptation work to be done after the "
"model generate content. These tasks are not difficult, but they do require "
"some time. When writing this part of the code, please refer to the `OpenAI "
"API documentation <https://platform.openai.com/docs/introduction>`_ and the "
"documentation of various inference backends, and make the necessary "
"adaptations."
msgstr ""
"Damos suporte a diferentes backends de inferência, como GGML, PyTorch e "
"vLLM. O conteúdo gerado é compatível com o formato da OpenAI, como suporte a"
" saída em streaming (stream) e modelos de diálogo retornados no formato chat"
" completion. Portanto, após a saída do modelo, é necessário realizar muitas "
"adaptações. Essas tarefas não são difíceis, mas exigem algum tempo. Ao "
"escrever essa parte do código, consulte a `documentação da API da OpenAI "
"<https://platform.openai.com/docs/introduction>`_ e a documentação de cada "
"backend de inferência para fazer as adaptações necessárias."

#: ../../source/development/xinference_internals.rst:185
msgid "JSON"
msgstr ""

#: ../../source/development/xinference_internals.rst:187
msgid ""
"In `model/llm/llm_family.json "
"<https://github.com/xorbitsai/inference/blob/main/xinference/model/llm/llm_family.json>`_,"
" we utilize JSON files to manage the metadata of emerging open-source "
"models. Adding a new model does not necessitate writing new code, it merely "
"requires appending new metadata to the existing JSON file."
msgstr ""
"Em `model/llm/llm_family.json "
"<https://github.com/xorbitsai/inference/blob/main/xinference/model/llm/llm_family.json>`_,"
" utilizamos um arquivo JSON para gerenciar os metadados de novos modelos de "
"código aberto que surgem. Adicionar um novo modelo não requer escrever novo "
"código, basta adicionar os novos metadados ao arquivo JSON existente."

#: ../../source/development/xinference_internals.rst:214
msgid ""
"This is an example of how to define the Llama-2 chat model. The "
"``model_specs`` define the information of the model, as one model family "
"usually comes with various sizes, quantization methods, and file formats. "
"For instance, the ``model_format`` could be ``pytorch`` (using Hugging Face "
"Transformers or vLLM as backend), ``ggmlv3`` (a tensor library associated "
"with llama.cpp), or ``gptq`` (a post-training quantization framework). The "
"``model_id`` defines the repository of the model hub from which Xinference "
"downloads the checkpoint files. Furthermore, due to distinct instruction-"
"tuning processes, different model families have varying prompt styles. The "
"``prompt_style`` in the JSON file specifies how to format prompts for this "
"particular model. For example, ``system_prompt`` and ``roles`` are used to "
"specify the instructions and personality of the model."
msgstr ""
"Aqui está um exemplo de como definir um modelo Llama-2 para chat. O "
"`model_specs` define as informações do modelo, pois uma família de modelos "
"geralmente possui diferentes tamanhos, métodos de quantização e formatos de "
"arquivo. Por exemplo, `model_format` pode ser `pytorch` (usando Hugging Face"
" Transformers ou vLLM como backend), `ggmlv3` (biblioteca de tensores "
"relacionada ao llama.cpp) ou `gptq` (framework de quantização pós-"
"treinamento). O `model_id` define o repositório do hub de modelos, onde o "
"Xinference baixa os arquivos de checkpoint. Além disso, devido a diferentes "
"processos de ajuste de instruções, diferentes famílias de modelos têm "
"estilos de prompt distintos. O `prompt_style` no arquivo JSON especifica o "
"formato de prompt para aquele modelo específico. Por exemplo, "
"`system_prompt` e `roles` são usados para especificar as instruções e a "
"personalidade do modelo."

#: ../../source/development/xinference_internals.rst:224
msgid "Code Walkthrough"
msgstr "Guia de Código"

#: ../../source/development/xinference_internals.rst:226
msgid ""
"The main code is located in the `xinference/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference>`_:"
msgstr ""
"O código principal está localizado em `xinference/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference>`_:"

#: ../../source/development/xinference_internals.rst:228
msgid ""
"`api/ <https://github.com/xorbitsai/inference/tree/main/xinference/api>`_: "
"`restful_api.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/api/restful_api.py>`_"
" is the core part that sets up and runs the RESTful APIs. It integrates an "
"authentication service (the specific code is located in `oauth2/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference/api/oauth2>`_),"
" as some or all endpointsrequire user authentication."
msgstr ""
"`api/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference/api>`_：`restful_api.py"
" "
"<https://github.com/xorbitsai/inference/tree/main/xinference/api/restful_api.py>`_"
" é a parte principal para configurar e executar a API RESTful. Ela integra "
"um serviço de autenticação (com o código específico localizado em `oauth2/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference/api/oauth2>`_),"
" pois algumas ou todas as portas exigem autenticação do usuário."

#: ../../source/development/xinference_internals.rst:233
msgid ""
"`client/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference/client>`_: This"
" is the client of Xinference."
msgstr ""
"`client/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference/client>`_：Este "
"é o cliente do Xinference."

#: ../../source/development/xinference_internals.rst:235
msgid ""
"`oscar/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference/client/oscar>`_"
" defines the Actor Client which acts as a client interface for interacting "
"with models deployed in a Xinference cluster."
msgstr ""
"`oscar/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference/client/oscar>`_"
" define o cliente Actor, que é uma interface cliente para interagir com "
"modelos no Xinference."

#: ../../source/development/xinference_internals.rst:238
msgid ""
"`restful/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference/client/restful>`_"
" implements a RESTful client for interacting with a Xinference service."
msgstr ""
"`restful/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference/client/restful>`_"
" implementa o cliente RESTful para interagir com o serviço Xinference."

#: ../../source/development/xinference_internals.rst:241
msgid ""
"`core/ <https://github.com/xorbitsai/inference/tree/main/xinference/core>`_:"
" This is the core part of Xinference."
msgstr ""
"`core/ <https://github.com/xorbitsai/inference/tree/main/xinference/core>`_:"
" Esta é a parte central do Xinference."

#: ../../source/development/xinference_internals.rst:243
msgid ""
"`metrics.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/core/metrics.py>`_"
" and `resource.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/core/resource.py>`_"
" defines a set of tools for collecting and reporting metrics and the status "
"of node resources, including model throughput, latency, the usage of CPU and"
" GPU, memory usage, and more."
msgstr ""
"`metrics.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/core/metrics.py>`_"
" e `resource.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/core/resource.py>`_"
" definem um conjunto de ferramentas para coletar e relatar métricas e o "
"estado dos recursos do nó, incluindo vazão do modelo, latência, uso de CPU e"
" GPU, uso de memória, entre outros."

#: ../../source/development/xinference_internals.rst:248
msgid ""
"`image_interface.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/core/image_interface.py>`_"
" and `chat_interface.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/core/chat_interface.py>`_"
" implement `Gradio <https://github.com/gradio-app/gradio>`_ interfaces for "
"image and chat models, respectively. These interfaces allow users to "
"interact with models through a Web UI, such as generating images or engaging"
" in chat. They build user interfaces using the gradio package and "
"communicate with backend models through our RESTful APIs."
msgstr ""
"`image_interface.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/core/image_interface.py>`_"
" e `chat_interface.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/core/chat_interface.py>`_"
" implementam a interface `Gradio <https://github.com/gradio-app/gradio>`_ "
"para modelos de imagem e chat, respectivamente. Essas interfaces permitem "
"que os usuários interajam com os modelos por meio de uma interface web, como"
" gerar imagens ou realizar conversas. O código utiliza o pacote Gradio para "
"construir a interface do usuário e se comunica com os modelos de backend por"
" meio de nossa API RESTful."

#: ../../source/development/xinference_internals.rst:254
msgid ""
"`worker.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/core/worker.py>`_"
" and `supervisor.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/core/supervisor.py>`_"
" respectively define the logic for worker actors and supervisor actor. "
"Worker actors are responsible for carrying out specific model computation "
"tasks, while supervisor actors manage the lifecycle of worker nodes, "
"schedule tasks, and monitor system states."
msgstr ""
"`worker.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/core/worker.py>`_"
" e `supervisor.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/core/supervisor.py>`_"
" definem, respectivamente, a lógica do worker actor e do supervisor actor. O"
" worker actor é responsável por executar tarefas específicas de computação "
"de modelos, enquanto o supervisor actor gerencia o ciclo de vida dos nós "
"Worker e a programação de tarefas, além de monitorar o estado do sistema."

#: ../../source/development/xinference_internals.rst:259
msgid ""
"`status_guard.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/core/status_guard.py>`_"
" implements a status monitor to track the status of models (like creating, "
"updating, terminating, etc.). It allows querying status information of model"
" instances and managing these statuses based on the model's UID."
msgstr ""
"`status_guard.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/core/status_guard.py>`_"
" implementa um monitor de status para rastrear o estado do modelo (como "
"criação, atualização, término, etc.). Ele permite consultar as informações "
"de status de uma instância de modelo com base no UID do modelo."

#: ../../source/development/xinference_internals.rst:263
msgid ""
"`cache_tracker.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/core/cache_tracker.py>`_"
" defines a cache tracker for recording and managing cache status and "
"information of model versions. It supports recording cache locations and "
"statuses of model versions and querying model version information based on "
"model names."
msgstr ""
"`cache_tracker.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/core/cache_tracker.py>`_"
" define um rastreador de cache, usado para registrar e gerenciar o status do"
" cache e as informações de versão do modelo. Ele suporta o registro do local"
" do cache e do status da versão do modelo, além de consultar informações de "
"versão do modelo com base no nome do modelo."

#: ../../source/development/xinference_internals.rst:267
msgid ""
"`event.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/core/event.py>`_"
" defines an event collector for gathering and reporting various runtime "
"events of models, such as information, warnings, and errors. `model.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/core/model.py>`_"
" defines a Model Actor, the core component for direct model interactions. "
"The Model Actor is responsible for executing model inference requests, "
"handling input and output data streams, and supports various types of model "
"operations."
msgstr ""
"`event.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/core/event.py>`_"
" define um coletor de eventos, usado para coletar e relatar vários eventos "
"de modelos em execução, como informações, avisos e erros. `model.py "
"<https://github.com/xorbitsai/inference/tree/main/xinference/core/model.py>`_"
" define um ator de modelo, que é o componente central para interagir "
"diretamente com o modelo. O ator de modelo é responsável por executar "
"requisições de inferência do modelo, processar fluxos de dados de entrada e "
"saída, e oferecer suporte a várias operações do modelo. Ambas as partes "
"utilizam `Xoscar <https://github.com/xorbitsai/xoscar>`_ para execução "
"concorrente e distribuída."

#: ../../source/development/xinference_internals.rst:273
msgid ""
"`deploy/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference/deploy>`_: It "
"provides a command-line interface (CLI) for interacting with the Xinference "
"framework, allowing users to perform operations by command line. See "
"`Command Line`_ for more information."
msgstr ""
"`deploy/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference/deploy>`_: "
"fornece uma interface de linha de comando (CLI) para interagir com o "
"framework Xinference, permitindo que os usuários executem operações via "
"linha de comando. Para mais informações, consulte `Command Line`_."

#: ../../source/development/xinference_internals.rst:276
msgid ""
"`locale/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference/locale>`_: It "
"supports multi-language localization. By simply adding and updating JSON "
"translation files, it becomes possible to support more languages, improving "
"user experience."
msgstr ""
"`locale/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference/locale>`_: "
"suporta localização multilíngue. Basta adicionar e atualizar os arquivos de "
"tradução JSON para oferecer suporte a mais idiomas, melhorando a experiência"
" do usuário."

#: ../../source/development/xinference_internals.rst:279
msgid ""
"`model/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference/model>`_: It "
"provides a structure for model descriptions, creation, and caching. See "
"`Model`_ for more information."
msgstr ""
"`model/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference/model>`_: Ele "
"fornece uma estrutura para descrição, criação e cache de modelos. Consulte "
"`Model`_ para obter mais informações."

#: ../../source/development/xinference_internals.rst:282
msgid ""
"`web/ui/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference/web/ui>`_: The "
"js code of the frontend (Web UI)."
msgstr ""
"`web/ui/ "
"<https://github.com/xorbitsai/inference/tree/main/xinference/web/ui>`_：código"
" JS do frontend (interface do usuário)."

#~ msgid ""
#~ "Xinference supports different types of models including large language "
#~ "models (LLMs), image models, audio models, embedding models, etc"
#~ msgstr ""
#~ "Xinference suporta diferentes tipos de modelos, incluindo modelos de "
#~ "linguagem de grande escala (LLM), modelos de imagem, modelos de áudio, "
#~ "modelos de incorporação, entre outros. Todos os modelos são implementados em"
#~ " `model/ "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model>`_. "
#~ "Tomando `llm/ "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model/llm>`_ "
#~ "como exemplo, ele foca no gerenciamento e instanciação de LLMs. Inclui "
#~ "implementações detalhadas para carregar, configurar e implantar LLMs, "
#~ "incluindo o tratamento de diferentes tipos de quantização e formatos de "
#~ "modelo. Em `llm/ "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model/llm>`_, "
#~ "ele oferece suporte a vários back-ends, como `GGML "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model/llm/ggml>`_,"
#~ " `PyTorch "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model/llm/pytorch>`_,"
#~ " `SGLang "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model/llm/sglang>`_"
#~ " e `vLLM "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model/llm/vllm>`_."

#~ msgid ""
#~ "Take `llm/ "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model/llm>`_ "
#~ "for example, it focuses on the management and instantiation of LLMs. It "
#~ "includes detailed implementations for loading, configuring, and deploying "
#~ "LLMs, including handling different types of quantization and model formats. "
#~ "In `llm/ "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model/llm>`_, "
#~ "it supports many backends such as `GGML "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model/llm/ggml>`_,"
#~ " `PyTorch "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model/llm/pytorch>`_,"
#~ " `SGLang "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model/llm/sglang>`_"
#~ " and `vLLM "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model/llm/vllm>`_."
#~ msgstr ""
#~ "Todos os modelos estão implementados em `model/ "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model>`_. "
#~ "Tomando `llm/ "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model/llm>`_ "
#~ "como exemplo, ele foca no gerenciamento e instanciação de LLMs. Inclui "
#~ "implementações detalhadas para carregamento, configuração e implantação de "
#~ "LLMs, incluindo o tratamento de diferentes tipos de quantização e formatos "
#~ "de modelo. Em `llm/ "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model/llm>`_, "
#~ "ele suporta diversos backends, como `GGML "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model/llm/ggml>`_,"
#~ " `PyTorch "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model/llm/pytorch>`_,"
#~ " `SGLang "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model/llm/sglang>`_"
#~ " e `vLLM "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model/llm/vllm>`_."

#~ msgid ""
#~ "All models are implemented in `model/ "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model>`_."
#~ msgstr ""
#~ "Todos os modelos estão implementados em `model/ "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/model>`_."

#~ msgid ""
#~ "In ``model/llm/``, it supports many backends such as GGML, PyTorch, and "
#~ "vLLM."
#~ msgstr ""
#~ "Em ``model/llm/``, oferecemos suporte a vários backends, como GGML, PyTorch "
#~ "e vLLM."

#~ msgid ""
#~ "`oscar/ "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/client/oscar>`_"
#~ " defines the Actor Client which acts as a client interface for interacting "
#~ "with models deployed in a server environment. It includes functionalities to"
#~ " register/unregister models, launch/terminate models, and interact with "
#~ "different types of models. This part heavily utilizes ``asyncio`` for "
#~ "asynchronous operations. See `Concurrency`_ for more information."
#~ msgstr ""
#~ "`oscar/ "
#~ "<https://github.com/xorbitsai/inference/tree/main/xinference/client/oscar>`_"
#~ " define o cliente Actor, que é uma interface cliente utilizada para "
#~ "interagir com modelos implantados em ambiente de servidor. Ele inclui "
#~ "funcionalidades para registrar/cancelar registro de modelos, "
#~ "iniciar/terminar modelos e interagir com diferentes tipos de modelos. Esta "
#~ "parte utiliza principalmente ``asyncio`` para operações assíncronas. Para "
#~ "mais informações, consulte `Concurrency`_."

#~ msgid "Concurrency"
#~ msgstr "Concorrência"

#~ msgid ""
#~ "Both Xinference and Xoscar highly utilize coroutine programming of "
#~ "``asyncio``."
#~ msgstr ""
#~ "O Xinference e o Xoscar utilizam amplamente o ``asyncio`` para programação "
#~ "de corrotinas."
