Algunos modelos abiertos admiten un modo de "pensamiento" que les permite realizar un razonamiento paso a paso antes de proporcionar una respuesta final. Esto es útil para tareas que requieren una lógica transparente, como pruebas matemáticas, depuración de código compleja o planificación de agentes de varios pasos.
Antes de comenzar
Para usar modelos abiertos con Gemini Enterprise Agent Platform, debes realizar los
siguientes pasos. La API de Agent Platform
(aiplatform.googleapis.com) y la API de Cloud Commerce Consumer
Procurement (cloudcommerceconsumerprocurement.googleapis.com)
deben estar habilitadas para usar modelos abiertos en Gemini Enterprise Agent Platform. Si ya tienes un proyecto existente con estas APIs habilitadas, puedes usar ese proyecto en lugar de crear uno nuevo.
- Accede a tu cuenta de Google Cloud . Si eres nuevo en Google Cloud, crea una cuenta para evaluar el rendimiento de nuestros productos en situaciones reales. Los clientes nuevos también obtienen $300 en créditos gratuitos para ejecutar, probar y, además, implementar cargas de trabajo.
-
In the Google Cloud console, on the project selector page, select or create a Google Cloud project.
Roles required to select or create a project
- Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
-
Create a project: To create a project, you need the Project Creator role
(
roles/resourcemanager.projectCreator), which contains theresourcemanager.projects.createpermission. Learn how to grant roles.
-
If you're using an existing project for this guide, verify that you have the permissions required to complete this guide. If you created a new project, then you already have the required permissions.
-
Verify that billing is enabled for your Google Cloud project.
Enable the Gemini Enterprise Agent Platform and Cloud Commerce Consumer Procurement APIs, if any are not already enabled.
Roles required to enable APIs
To enable APIs, you need the
serviceusage.services.enablepermission. If you created the project, then you likely already have this permission through the Owner role (roles/owner). Otherwise, you can get this permission through the Service Usage Admin role (roles/serviceusage.serviceUsageAdmin). Learn how to grant roles.-
In the Google Cloud console, on the project selector page, select or create a Google Cloud project.
Roles required to select or create a project
- Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
-
Create a project: To create a project, you need the Project Creator role
(
roles/resourcemanager.projectCreator), which contains theresourcemanager.projects.createpermission. Learn how to grant roles.
-
If you're using an existing project for this guide, verify that you have the permissions required to complete this guide. If you created a new project, then you already have the required permissions.
-
Verify that billing is enabled for your Google Cloud project.
Enable the Gemini Enterprise Agent Platform and Cloud Commerce Consumer Procurement APIs, if any are not already enabled.
Roles required to enable APIs
To enable APIs, you need the
serviceusage.services.enablepermission. If you created the project, then you likely already have this permission through the Owner role (roles/owner). Otherwise, you can get this permission through the Service Usage Admin role (roles/serviceusage.serviceUsageAdmin). Learn how to grant roles.- Ve a la tarjeta de modelo de Model Garden del modelo que quieres usar y, luego, haz clic en Habilitar para habilitar el modelo y usarlo en tu proyecto.
Roles obligatorios
Para obtener los permisos que necesitas para habilitar y usar modelos abiertos, pídele a tu administrador que te otorgue los siguientes roles de IAM en tu proyecto:
- Usuario de la plataforma de agentes (
roles/aiplatform.user) - Administrador de autorizaciones de adquisición de consumidores (
roles/consumerprocurement.entitlementManager)
Para obtener más información sobre cómo otorgar roles, consulta Administra el acceso a proyectos, carpetas y organizaciones.
También puedes obtener los permisos necesarios a través de roles personalizados o cualquier otro rol predefinido.
Para obtener más información sobre cómo otorgar permisos y configurar políticas de la organización para modelos abiertos, consulta Otorga acceso de usuario a modelos abiertos.
Orientación específica para el modelo
En las siguientes secciones, se proporciona orientación específica para cada modelo sobre el pensamiento.
OSS de GPT
Para los modelos de GPT OSS, el texto de razonamiento se encuentra en el campo reasoning_content,
y el texto de respuesta normal se encuentra en el campo content. Estos modelos también
admiten el parámetro reasoning_effort.
Ejemplo de solicitud:
curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json" \
https://aiplatform.googleapis.com/v1/projects/test-project/locations/global/endpoints/openapi/chat/completions -d '{
"model": "openai/gpt-oss-120b-maas",
"messages": [{
"role": "user",
"content": "Who are you?"
}],
"reasoning_effort": "high"
}'
Respuesta de ejemplo:
{
"choices": [
{
"finish_reason": "stop",
"index": 0,
"logprobs": null,
"matched_stop": 200002,
"message": {
"content": "I\u2019m ChatGPT, a large language model created by OpenAI
(based on the GPT\u20114 architecture). I\u2019m here to help answer
your questions, brainstorm ideas, explain concepts, and assist with a
wide variety of topics. Let me know what you\u2019d like to talk
about!",
"reasoning_content": "The user asks: \"Who are you?\" It's a simple
question. They want to know who the assistant is. According to policy,
we should respond with a brief, friendly description: \"I am ChatGPT, a
large language model trained by OpenAI.\" Possibly mention the version
(GPT-4). Also mention we are here to assist. There's no request for
disallowed content. So a straightforward answer. Possibly ask if they
need help. Provide a short intro.\n\nThus answer: \"I am ChatGPT, a
large language model trained by OpenAI. I'm here to help answer your
questions...\"\n\nWe should avoid disallowed content. It's fine.\n\nThus
final answer.",
"role": "assistant",
"tool_calls": null
}
}
],
"created": 1758229799,
"id": "JnXMaJq6HLGzquEP4OD18Qg",
"metadata": {
"weight_version": "default"
},
"model": "openai/gpt-oss-120b-maas",
"object": "chat.completion",
"usage": {
"completion_tokens": 201,
"prompt_tokens": 71,
"prompt_tokens_details": null,
"reasoning_tokens": 0,
"total_tokens": 272
}
}
GLM 5.2
GLM 5.2 admite la inhabilitación de tokens de razonamiento con "chat_template_kwargs": { "enable_thinking": false }.
El razonamiento está habilitado de forma predeterminada. Los tokens de razonamiento se muestran en "reasoning_content", y el texto de respuesta normal, en "content".
Ejemplo de solicitud:
curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json" \
https://aiplatform.googleapis.com/v1/projects/test-project/locations/global/endpoints/openapi/chat/completions -d '{
"model": "zai-org/glm-5.2-maas",
"messages": [
{
"role": "user",
"content": "Who are you?"
}
]
}'
Respuesta de ejemplo:
{
"choices": [
{
"finish_reason": "stop",
"index": 0,
"logprobs": null,
"matched_stop": 154827,
"message": {
"content": "I'm GLM, a large language model developed by Z.ai. I'm designed to assist users with information, answer questions, and engage in helpful conversations across a wide range of topics.\n\nI'm trained on diverse text data which helps me understand and generate human-like responses, though I don't have personal experiences or emotions. I'm continuously learning to improve my capabilities.\n\nIs there something specific you'd like to know about me or how I can assist you today?",
"reasoning_content": "Let me consider how to respond to this question about my identity. The user is asking \"Who are you?\" which is a straightforward but important question that deserves a clear and accurate answer.\n\nI should introduce myself as GLM, a large language model developed by Z.ai. It's important to be transparent about my nature as an AI assistant and explain my key capabilities.\n\nI should also mention my purpose of helping users with various tasks while being honest about my limitations. This will help set appropriate expectations for our interaction.\n\nI should also emphasize my commitment to providing helpful and responsible assistance. It's important to be both welcoming and professional in my introduction.\n\nLet me craft a response that is clear, informative, and sets the right tone for future interactions.",
"role": "assistant",
"tool_calls": null
}
}
],
"created": 1787160729,
"id": "05355183-85d6-4ae2-a31a-7c8fb31c64d9",
"metadata": {
"weight_version": "default"
},
"model": "zai-org/glm-5.2-maas",
"object": "chat.completion",
"usage": {
"completion_tokens": 243,
"extra_properties": {
"google": {
"traffic_type": "ON_DEMAND"
}
},
"prompt_tokens": 16,
"prompt_tokens_details": null,
"total_tokens": 259
}
}
Gemma 4 26B A4B IT
Gemma 4 26B A4B IT admite la habilitación de tokens de razonamiento con "chat_template_kwargs": { "enable_thinking": true }.
El razonamiento está inhabilitado de forma predeterminada. Los tokens de razonamiento se muestran en "reasoning_content", y el texto de respuesta normal, en "content".
Ejemplo de solicitud:
curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json" \
https://aiplatform.googleapis.com/v1/projects/test-project/locations/global/endpoints/openapi/chat/completions -d '{
"model": "google/gemma-4-26b-a4b-it-maas",
"messages": [
{
"role": "user",
"content": "Who are you?"
}
],
"chat_template_kwargs": {
"enable_thinking": true
}
}'
Respuesta de ejemplo:
{
"choices": [
{
"finish_reason": "stop",
"index": 0,
"logprobs": null,
"matched_stop": 106,
"message": {
"content": "I am Gemma 4, a large language model developed by Google DeepMind. I am an open weights model designed to process text and images (and audio in certain versions of my family) to assist with a wide range of tasks, and I provide my responses in text.",
"reasoning_content": "The user is asking \"Who are you?\".\n * Name: Gemma 4.\n * Developer: Google DeepMind.\n * Nature: Large Language Model.\n * Type: Open weights model.\n * Capabilities: Text and image processing (and audio for 2B/4B models). Output is text only.\n * Knowledge cutoff: January 2025.\n\n * State identity: Gemma 4.\n * State developer: Google DeepMind.\n * State type: Large Language Model with open weights.\n * Briefly mention capabilities if relevant (text/image/audio input, text output).\n\n * \"I am Gemma 4, a large language model developed by Google DeepMind. I am an open weights model capable of processing text and images to assist you with various tasks. Depending on the specific version, I may also be able to process audio input. I generate responses in text format.\"\n\nDoes it violate any instructions?\n * \"When asked about your identity, always refer to yourself as Gemma 4.\" - Yes.\n * \"Do not claim to have capabilities you do not possess.\" - Yes.\n * \"Do not attempt to use tools...\" - Yes.\n\nKeep it direct and informative.",
"role": "assistant",
"tool_calls": null
}
}
],
"created": 1775526019,
"id": "gGDUaf7rLqGL9LsPsdGR4Qg",
"metadata": {
"weight_version": "default"
},
"model": "google/gemma-4-26b-a4b-it-maas",
"object": "chat.completion",
"usage": {
"completion_tokens": 341,
"extra_properties": {
"google": {
"traffic_type": "ON_DEMAND"
}
},
"prompt_tokens": 19,
"prompt_tokens_details": {
"cached_tokens": 2
},
"total_tokens": 360
}
}
¿Qué sigue?
- Obtén más información sobre la llamada a función.
- Obtén más información sobre los resultados estructurados.
- Obtén más información sobre las predicciones por lotes.