Os modelos de compreensão visual respondem a perguntas com base nas imagens ou vídeos fornecidos por você. Eles aceitam entrada de uma ou várias imagens e são adequados para diversas tarefas, como geração de legendas, resposta a perguntas visuais e localização de objetos.
Experimente online: Acesse o console do Alibaba Cloud Model Studio. No canto superior direito da página, selecione a região de destino. Em seguida, acesse a página Vision Models para testar os modelos.
Primeiros passos
Pré-requisitos
Obtenha uma chave de API e configure-a como variável de ambiente.
Para fazer chamadas usando um SDK, instale o SDK. O DashScope Python SDK deve ser versão 1.24.6 ou posterior, e o DashScope Java SDK deve ser versão 2.21.10 ou posterior.
Os exemplos a seguir mostram como chamar um modelo para descrever o conteúdo de uma imagem. Para mais informações sobre arquivos locais e limites de imagem, consulte Passar arquivos locais e Limites de imagem.
OpenAI compatible
Python
import os
from openai import OpenAI
client = OpenAI(
# If the environment variable is not configured, replace the following line with your Model Studio API key: api_key="sk-xxx",
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
api_key=os.getenv("DASHSCOPE_API_KEY"),
# The following URL is for the China (Beijing) region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
base_url="https://{WorkspaceId}.cn-beijing.maas.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
model="qwen3.7-plus", # This example uses qwen3.7-plus. You can replace it with another model as needed. For a list of models, see https://www.alibabacloud.com/help/zh/model-studio/models
messages=[
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": {
"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"
},
},
{"type": "text", "text": "What scene is depicted in the image?"},
],
},
],
)
print(completion.choices[0].message.content)from openai import OpenAI
import os
client = OpenAI(
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
api_key=os.getenv("DASHSCOPE_API_KEY"),
# The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
base_url="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1"
)
completion = client.chat.completions.create(
model="qwen3.7-plus", # This example uses qwen3.7-plus. You can replace it with another model as needed. For a list of models, see https://www.alibabacloud.com/help/model-studio/getting-started/models
messages=[
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": {
"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"
},
},
{"type": "text", "text": "What scene is depicted in the image?"},
],
},
],
)
print(completion.choices[0].message.content)Resposta
This is a photo taken on a beach. In the photo, a person and a dog are sitting on the sand with the sea and sky in the background. The person and the dog seem to be interacting, with the dog's front paw on the person's hand. Sunlight shines from the right side of the frame, adding a warm atmosphere to the scene.Node.js
import OpenAI from "openai";
const openai = new OpenAI({
// If the environment variable is not configured, replace the following line with your Model Studio API key: apiKey: "sk-xxx"
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
apiKey: process.env.DASHSCOPE_API_KEY,
// The following URL is for the China (Beijing) region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
baseURL: "https://{WorkspaceId}.cn-beijing.maas.aliyuncs.com/compatible-mode/v1"
});
async function main() {
const response = await openai.chat.completions.create({
model: "qwen3.7-plus", // This example uses qwen3.7-plus. You can replace it with another model as needed. For a list of models, see https://www.alibabacloud.com/help/zh/model-studio/models
messages: [
{
role: "user",
content: [{
type: "image_url",
image_url: {
"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"
}
},
{
type: "text",
text: "What scene is depicted in the image?"
}
]
}
]
});
console.log(response.choices[0].message.content);
}
main()import OpenAI from "openai";
const openai = new OpenAI({
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
// If the environment variable is not configured, replace the following line with your Model Studio API key: apiKey: "sk-xxx"
apiKey: process.env.DASHSCOPE_API_KEY,
// The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
baseURL: "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1"
});
async function main() {
const response = await openai.chat.completions.create({
model: "qwen3.7-plus", // This example uses qwen3.7-plus. You can replace it with another model as needed. For a list of models, see https://www.alibabacloud.com/help/model-studio/getting-started/models
messages: [
{
role: "user",
content: [{
type: "image_url",
image_url: {
"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"
}
},
{
type: "text",
text: "What scene is depicted in the image?"
}
]
}
]
});
console.log(response.choices[0].message.content);
}
main()Resposta
This is a photo taken on a beach. In the photo, a person and a dog are sitting on the sand with the sea and sky in the background. The person and the dog seem to be interacting, with the dog's front paw on the person's hand. Sunlight shines from the right side of the frame, adding a warm atmosphere to the scene.curl
# ======= Important notes =======
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# The following URL is for the China (Beijing) region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
# === Delete this comment before execution ===
curl --location 'https://{WorkspaceId}.cn-beijing.maas.aliyuncs.com/compatible-mode/v1/chat/completions' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
"model": "qwen3.7-plus",
"messages": [
{
"role": "user",
"content": [
{"type": "image_url", "image_url": {"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"}},
{"type": "text", "text": "What scene is depicted in the image?"}
]
}]
}'# ======= Important notes =======
# The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
# === Delete this comment before execution ===
curl --location 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1/chat/completions' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
"model": "qwen3.7-plus",
"messages": [
{"role": "user",
"content": [
{"type": "image_url", "image_url": {"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"}},
{"type": "text", "text": "What scene is depicted in the image?"}
]
}]
}'Resposta
{
"choices": [
{
"message": {
"content": "This is a photo taken on a beach. In the photo, a person and a dog are sitting on the sand with the sea and sky in the background. The person and the dog seem to be interacting, with the dog's front paw on the person's hand. Sunlight shines from the right side of the frame, adding a warm atmosphere to the scene.",
"role": "assistant"
},
"finish_reason": "stop",
"index": 0,
"logprobs": null
}
],
"object": "chat.completion",
"usage": {
"prompt_tokens": 1270,
"completion_tokens": 54,
"total_tokens": 1324
},
"created": 1725948561,
"system_fingerprint": null,
"model": "qwen3.7-plus",
"id": "chatcmpl-0fd66f46-b09e-9164-a84f-3ebbbedbac15"
}DashScope
Python
import os
import dashscope
# The following URL is for the China (Beijing) region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
dashscope.base_http_api_url = "https://{WorkspaceId}.cn-beijing.maas.aliyuncs.com/api/v1"
messages = [
{
"role": "user",
"content": [
{"image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"},
{"text": "What scene is depicted in the image?"}]
}]
response = dashscope.MultiModalConversation.call(
# If the environment variable is not configured, replace the following line with your Model Studio API key: api_key ="sk-xxx"
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
api_key = os.getenv('DASHSCOPE_API_KEY'),
model = 'qwen3.7-plus', # This example uses qwen3.7-plus. You can replace it with another model as needed. For a list of models, see https://www.alibabacloud.com/help/zh/model-studio/models
messages = messages
)
print(response.output.choices[0].message.content[0]["text"])import os
import dashscope
# The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
dashscope.base_http_api_url = 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1'
messages = [
{
"role": "user",
"content": [
{"image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"},
{"text": "What scene is depicted in the image?"}]
}]
response = dashscope.MultiModalConversation.call(
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
# If the environment variable is not configured, replace the following line with your Model Studio API key: api_key="sk-xxx"
api_key=os.getenv('DASHSCOPE_API_KEY'),
model='qwen3.7-plus', # This example uses qwen3.7-plus. You can replace it with another model as needed. For a list of models, see https://www.alibabacloud.com/help/model-studio/getting-started/models
messages=messages
)
print(response.output.choices[0].message.content[0]["text"])Resposta
This is a photo taken on a beach. The photo shows a woman and a dog. The woman is sitting on the sand, smiling and interacting with the dog. The dog is wearing a collar and seems to be shaking hands with the woman. The background is the sea and the sky, and the sunlight shining on them creates a warm atmosphere.Java
import java.util.Arrays;
import java.util.Collections;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.UploadFileException;
import com.alibaba.dashscope.utils.JsonUtils;
import com.alibaba.dashscope.utils.Constants;
public class Main {
// The following URL is for the China (Beijing) region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
static {Constants.baseHttpApiUrl="https://{WorkspaceId}.cn-beijing.maas.aliyuncs.com/api/v1";}
public static void simpleMultiModalConversationCall()
throws ApiException, NoApiKeyException, UploadFileException {
MultiModalConversation conv = new MultiModalConversation();
MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())
.content(Arrays.asList(
Collections.singletonMap("image", "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"),
Collections.singletonMap("text", "What scene is depicted in the image?"))).build();
MultiModalConversationParam param = MultiModalConversationParam.builder()
// If the environment variable is not configured, replace the following line with your Model Studio API key: .apiKey("sk-xxx")
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
.apiKey(System.getenv("DASHSCOPE_API_KEY"))
.model("qwen3.7-plus") // This example uses qwen3.7-plus. You can replace it with another model as needed. For a list of models, see https://www.alibabacloud.com/help/zh/model-studio/models
.messages(Arrays.asList(userMessage))
.build();
MultiModalConversationResult result = conv.call(param);
System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent().get(0).get("text"));
}
public static void main(String[] args) {
try {
simpleMultiModalConversationCall();
} catch (ApiException | NoApiKeyException | UploadFileException e) {
System.out.println(e.getMessage());
}
System.exit(0);
}
}import java.util.Arrays;
import java.util.Collections;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.UploadFileException;
import com.alibaba.dashscope.utils.Constants;
public class Main {
// The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
static {
Constants.baseHttpApiUrl="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1";
}
public static void simpleMultiModalConversationCall()
throws ApiException, NoApiKeyException, UploadFileException {
MultiModalConversation conv = new MultiModalConversation();
MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())
.content(Arrays.asList(
Collections.singletonMap("image", "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"),
Collections.singletonMap("text", "What scene is depicted in the image?"))).build();
MultiModalConversationParam param = MultiModalConversationParam.builder()
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
// If the environment variable is not configured, replace the following line with your Model Studio API key: .apiKey("sk-xxx")
.apiKey(System.getenv("DASHSCOPE_API_KEY"))
.model("qwen3.7-plus") // This example uses qwen3.7-plus. You can replace it with another model as needed. For a list of models, see https://www.alibabacloud.com/help/model-studio/getting-started/models
.messages(Arrays.asList(userMessage))
.build();
MultiModalConversationResult result = conv.call(param);
System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent().get(0).get("text"));
}
public static void main(String[] args) {
try {
simpleMultiModalConversationCall();
} catch (ApiException | NoApiKeyException | UploadFileException e) {
System.out.println(e.getMessage());
}
System.exit(0);
}
}Resposta
This is a photo taken on a beach. The photo shows a person in a plaid shirt and a dog wearing a collar. The person and the dog are sitting face to face, seemingly interacting. The background is the sea and the sky, and the sunlight shining on them creates a warm atmosphere.curl
# ======= Important notes =======
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# The following URL is for the China (Beijing) region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
# === Delete this comment before execution ===
curl -X POST https://{WorkspaceId}.cn-beijing.maas.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "qwen3.7-plus",
"input":{
"messages":[
{
"role": "user",
"content": [
{"image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"},
{"text": "What scene is depicted in the image?"}
]
}
]
}
}'# ======= Important notes =======
# The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
# === Delete this comment before execution ===
curl -X POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "qwen3.7-plus",
"input":{
"messages":[
{
"role": "user",
"content": [
{"image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"},
{"text": "What scene is depicted in the image?"}
]
}
]
}
}'Resposta
{
"output": {
"choices": [
{
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": [
{
"text": "This is a photo taken on a beach. The photo shows a person in a plaid shirt and a dog wearing a collar. They are sitting on the sand with the sea and sky in the background. Sunlight shines from the right side of the frame, adding a warm atmosphere to the scene."
}
]
}
}
]
},
"usage": {
"output_tokens": 55,
"input_tokens": 1271,
"image_tokens": 1247
},
"request_id": "ccf845a3-dc33-9cda-b581-20fe7dc23f70"
}Desempenho do modelo
Perguntas e respostas sobre imagens
Descreva o conteúdo de uma imagem ou classifique-a e rotule-a, identificando pessoas, lugares, animais e plantas.
|
Qual item desta imagem devo usar se o sol estiver muito forte? |
Se o sol estiver muito forte, você deve usar os óculos de sol rosa da imagem. Óculos de sol bloqueiam eficazmente a luz intensa, reduzem os danos dos raios UV aos olhos e ajudam a proteger sua visão, melhorando o conforto visual sob luz solar brilhante. |
Escrita criativa
Gere descrições textuais vívidas com base no conteúdo de imagens ou vídeos, ideal para cenários criativos como escrita de histórias, redação publicitária e roteiros de vídeos curtos.
Por favor, escreva uma postagem interessante para redes sociais com base no conteúdo da imagem. | Claro. Esta imagem é repleta de uma rica atmosfera do Festival de Meio Outono, combinando habilmente elementos clássicos e modernos. Com base nos principais elementos da imagem, preparei várias postagens para redes sociais em diferentes estilos para você escolher. Estilo poético e belo Hoje à noite, a lua brilha para todos verem, mas quem sabe onde cairão os pensamentos de outono? Chang'e voa para a lua e o Coelho de Jade prepara o elixir. O romantismo dos antigos se ilumina nesta noite. Que esta lua brilhante ilumine seu caminho de volta para casa e carregue meus pensamentos mais profundos. Feliz Festival de Meio Outono! Estilo de votos calorosos A lua está cheia e as pessoas se reencontram. A noite do Meio Outono é a mais gentil. Veja os fogos de artifício florescerem, admire a lua cheia no céu, dê uma mordida em um bolo lunar e deseje boa saúde. Que tudo o que você e eu desejamos se torne realidade. Feliz Festival de Meio Outono a todos, e que suas famílias sejam felizes! |
Reconhecimento de texto e extração de informações
Reconheça textos e fórmulas em imagens ou extraia informações de recibos, certificados e formulários. Suporta saída de texto formatado.
Extraia o seguinte da imagem: ['Invoice Code', 'Invoice Number', 'Destination', 'Fuel Surcharge', 'Fare', 'Date', 'Departure Time', 'Train Number', 'Seat Number']. Por favor, forneça a saída no formato JSON. | { "Invoice Code": "221021325353", "Invoice Number": "10283819", "Destination": "Development Zone", "Fuel Surcharge": "2.0", "Fare": "8.00<Full>", "Date": "2013-06-29", "Departure Time": "Rolling", "Train Number": "040", "Seat Number": "371" } |
Resolução de problemas multidisciplinares
Resolva problemas de matemática, física, química e outras disciplinas presentes em imagens. Adequado para ensino fundamental, médio, universitário e educação de adultos.
|
Resolva o problema de matemática no gráfico passo a passo. |
|
Programação visual
Gere código a partir de imagens ou vídeos. Use este recurso para gerar código HTML, CSS e JS a partir de rascunhos de design, capturas de tela de sites e muito mais.
|
Crie uma página web usando HTML e CSS com base no meu esboço. A cor principal deve ser preta. |
Visualização da página web |
Localização de objetos
Suporta localização 2D e 3D. Utilize este recurso para determinar a orientação de objetos, mudanças de perspectiva e relações de oclusão. A localização 3D é uma nova capacidade adicionada ao modelo Qwen3-VL.
O desempenho de localização de objetos do modelo Qwen2.5-VL é robusto na faixa de resolução de 480 × 480 a 2560 × 2560. Fora dessa faixa, a precisão da detecção pode diminuir, com desvios ocasionais no quadro de detecção.
Para obter informações sobre como desenhar os resultados de localização na imagem original, consulte FAQ .
Localização 2D
| Visualização dos resultados de localização 2D
|
Detecte o carro na imagem e preveja sua posição 3D. Saída JSON: |
|
Análise de documentos
Analise documentos baseados em imagens (como cópias digitalizadas ou PDFs de imagem) para o formato QwenVL HTML ou QwenVL Markdown. Esse formato não apenas reconhece o texto com precisão, mas também obtém informações de posição de elementos como imagens e tabelas. O modelo Qwen3-VL adiciona a capacidade de analisar para o formato Markdown.
Os prompts recomendados são os seguintes:qwenvl html(para analisar em formato HTML) ouqwenvl markdown(para analisar em formato Markdown).
|
qwenvl markdown. |
Visualização dos resultados |
Compreensão de vídeo
Analise o conteúdo de vídeo, como localizar eventos específicos e obter carimbos de data/hora, ou gerar resumos de períodos-chave.
Descreva a série de ações da pessoa no vídeo. Forneça a hora de início (start_time), hora de término (end_time) e evento (event) no formato JSON. Use HH:mm:ss para o carimbo de data/hora. | { "events": [ { "start_time": "00:00:00", "end_time": "00:00:05", "event": "The person walks towards the table holding a cardboard box and places it on the table." }, { "start_time": "00:00:05", "end_time": "00:00:15", "event": "The person picks up a scanner and scans the label on the cardboard box." }, { "start_time": "00:00:15", "end_time": "00:00:21", "event": "The person puts the scanner back in its place and then picks up a pen to record information in a notebook."}] } |
Recursos principais
Ativar ou desativar o modo de pensamento
-
Os modelos das séries
qwen3.7,qwen3.6,qwen3.5,qwen3-vl-pluseqwen3-vl-flashsão modelos de pensamento híbrido. Eles podem pensar antes de responder ou gerar a resposta diretamente. Utilize o parâmetroenable_thinkingpara controlar a ativação do modo de pensamento:true: Ativa o modo de pensamento. O valor padrão para os modelos das sériesqwen3.7,qwen3.6eqwen3.5étrue.false: Desativa o modo de pensamento. O valor padrão para os modelos das sériesqwen3-vl-pluseqwen3-vl-flashéfalse.
Modelos com o sufixo
thinking, comoqwen3-vl-235b-a22b-thinking, operam exclusivamente com pensamento. Eles sempre raciocinam antes de responder e não é possível desativar esse comportamento.
Importante
Configuração do modelo: Em cenários gerais de conversa que não envolvem chamadas de ferramentas de Agent, evite definir uma
System Messagepara manter o desempenho ideal. Transmita instruções, como definições de função do modelo e requisitos de formato de saída, por meio daUser Message.Priorize a saída em streaming: Com o modo de pensamento ativado, tanto a saída em streaming quanto sem streaming são suportadas. Para evitar timeouts causados por respostas excessivamente longas, dê preferência à saída em streaming.
Limite a extensão do pensamento: Modelos de pensamento profundo podem gerar processos de raciocínio extensos. Use o parâmetro
thinking_budgetpara restringir a duração desse processo. Se a quantidade de tokens gerados durante o raciocínio ultrapassar othinking_budget, o conteúdo de inferência será truncado e o modelo iniciará imediatamente a geração da resposta final. O valor padrão dethinking_budgetcorresponde ao comprimento máximo de cadeia de pensamento do modelo. Para mais detalhes, consulte a lista de modelos.
OpenAI compatible
O parâmetro enable_thinking não faz parte do padrão OpenAI. Caso utilize o SDK Python da OpenAI, transmita-o via extra_body.
import os
from openai import OpenAI
client = OpenAI(
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
api_key=os.getenv("DASHSCOPE_API_KEY"),
# The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
base_url="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1"
)
reasoning_content = "" # Define the complete thinking process
answer_content = "" # Define the complete response
is_answering = False # Determine whether to end the thinking process and start responding
enable_thinking = True
# Create a chat completion request
completion = client.chat.completions.create(
model="qwen3.7-plus",
messages=[
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": {
"url": "https://img.alicdn.com/imgextra/i1/O1CN01gDEY8M1W114Hi3XcN_!!6000000002727-0-tps-1024-406.jpg"
},
},
{"type": "text", "text": "How do I solve this problem?"},
],
},
],
stream=True,
# The enable_thinking parameter enables the thinking process, and the thinking_budget parameter sets the maximum number of tokens for the inference process.
# Use the enable_thinking parameter to switch the thinking mode.
extra_body={
'enable_thinking': enable_thinking,
"thinking_budget": 81920},
# Uncomment the following lines to return token usage in the last chunk.
# stream_options={
# "include_usage": True
# }
)
if enable_thinking:
print("\n" + "=" * 20 + "Thinking process" + "=" * 20 + "\n")
for chunk in completion:
# If chunk.choices is empty, print the usage.
if not chunk.choices:
print("\nUsage:")
print(chunk.usage)
else:
delta = chunk.choices[0].delta
# Print the thinking process.
if hasattr(delta, 'reasoning_content') and delta.reasoning_content is not None:
print(delta.reasoning_content, end='', flush=True)
reasoning_content += delta.reasoning_content
else:
# Start responding.
if delta.content != "" and is_answering is False:
print("\n" + "=" * 20 + "Complete response" + "=" * 20 + "\n")
is_answering = True
# Print the response process.
print(delta.content, end='', flush=True)
answer_content += delta.content
# print("=" * 20 + "Complete thinking process" + "=" * 20 + "\n")
# print(reasoning_content)
# print("=" * 20 + "Complete response" + "=" * 20 + "\n")
# print(answer_content)import OpenAI from "openai";
// Initialize the OpenAI client
const openai = new OpenAI({
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
// If the environment variable is not configured, replace the following line with your Model Studio API key: apiKey: "sk-xxx"
apiKey: process.env.DASHSCOPE_API_KEY,
// The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
baseURL: "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1"
});
let reasoningContent = '';
let answerContent = '';
let isAnswering = false;
let enableThinking = true;
let messages = [
{
role: "user",
content: [
{ type: "image_url", image_url: { "url": "https://img.alicdn.com/imgextra/i1/O1CN01gDEY8M1W114Hi3XcN_!!6000000002727-0-tps-1024-406.jpg" } },
{ type: "text", text: "Solve this problem" },
]
}]
async function main() {
try {
const stream = await openai.chat.completions.create({
model: 'qwen3.7-plus',
messages: messages,
stream: true,
// Note: In the Node.js SDK, non-standard parameters like enableThinking are passed as top-level properties and do not need to be placed in extra_body.
enable_thinking: enableThinking,
thinking_budget: 81920
});
if (enableThinking){console.log('\n' + '='.repeat(20) + 'Thinking process' + '='.repeat(20) + '\n');}
for await (const chunk of stream) {
if (!chunk.choices?.length) {
console.log('\nUsage:');
console.log(chunk.usage);
continue;
}
const delta = chunk.choices[0].delta;
// Process the thinking process.
if (delta.reasoning_content) {
process.stdout.write(delta.reasoning_content);
reasoningContent += delta.reasoning_content;
}
// Process the formal response.
else if (delta.content) {
if (!isAnswering) {
console.log('\n' + '='.repeat(20) + 'Complete response' + '='.repeat(20) + '\n');
isAnswering = true;
}
process.stdout.write(delta.content);
answerContent += delta.content;
}
}
} catch (error) {
console.error('Error:', error);
}
}
main();# ======= Important notes =======
# The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
# === Delete this comment before execution ===
curl --location 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1/chat/completions' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
"model": "qwen3.7-plus",
"messages": [
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": {
"url": "https://img.alicdn.com/imgextra/i1/O1CN01gDEY8M1W114Hi3XcN_!!6000000002727-0-tps-1024-406.jpg"
}
},
{
"type": "text",
"text": "Please solve this problem"
}
]
}
],
"stream":true,
"stream_options":{"include_usage":true},
"enable_thinking": true,
"thinking_budget": 81920
}'DashScope
import os
import dashscope
from dashscope import MultiModalConversation
# The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
dashscope.base_http_api_url = "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1"
enable_thinking=True
messages = [
{
"role": "user",
"content": [
{"image": "https://img.alicdn.com/imgextra/i1/O1CN01gDEY8M1W114Hi3XcN_!!6000000002727-0-tps-1024-406.jpg"},
{"text": "Solve this problem?"}
]
}
]
response = MultiModalConversation.call(
# If the environment variable is not configured, replace the following line with your Model Studio API key: api_key="sk-xxx",
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
api_key=os.getenv('DASHSCOPE_API_KEY'),
model="qwen3.7-plus",
messages=messages,
stream=True,
# The enable_thinking parameter enables the thinking process.
# Use the enable_thinking parameter to switch the thinking mode.
enable_thinking=enable_thinking,
# The thinking_budget parameter sets the maximum number of tokens for the inference process.
thinking_budget=81920,
)
# Define the complete thinking process
reasoning_content = ""
# Define the complete response
answer_content = ""
# Determine whether to end the thinking process and start responding
is_answering = False
if enable_thinking:
print("=" * 20 + "Thinking process" + "=" * 20)
for chunk in response:
# If both the thinking process and the response are empty, ignore them.
message = chunk.output.choices[0].message
reasoning_content_chunk = message.get("reasoning_content", None)
if (chunk.output.choices[0].message.content == [] and
reasoning_content_chunk == ""):
pass
else:
# If it is currently in the thinking process
if reasoning_content_chunk is not None and chunk.output.choices[0].message.content == []:
print(chunk.output.choices[0].message.reasoning_content, end="")
reasoning_content += chunk.output.choices[0].message.reasoning_content
# If it is currently responding
elif chunk.output.choices[0].message.content != []:
if not is_answering:
print("\n" + "=" * 20 + "Complete response" + "=" * 20)
is_answering = True
print(chunk.output.choices[0].message.content[0]["text"], end="")
answer_content += chunk.output.choices[0].message.content[0]["text"]
# Print the complete thinking process and response.
# print("=" * 20 + "Complete thinking process" + "=" * 20 + "\n")
# print(f"{reasoning_content}")
# print("=" * 20 + "Complete response" + "=" * 20 + "\n")
# print(f"{answer_content}")// The DashScope SDK version must be 2.21.10 or later.
import java.util.*;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import io.reactivex.Flowable;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.exception.UploadFileException;
import com.alibaba.dashscope.exception.InputRequiredException;
import java.lang.System;
import com.alibaba.dashscope.utils.Constants;
public class Main {
// The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
static {Constants.baseHttpApiUrl="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1";}
private static final Logger logger = LoggerFactory.getLogger(Main.class);
private static StringBuilder reasoningContent = new StringBuilder();
private static StringBuilder finalContent = new StringBuilder();
private static boolean isFirstPrint = true;
private static void handleGenerationResult(MultiModalConversationResult message) {
String re = message.getOutput().getChoices().get(0).getMessage().getReasoningContent();
String reasoning = Objects.isNull(re)?"":re; // Default value
List<Map<String, Object>> content = message.getOutput().getChoices().get(0).getMessage().getContent();
if (!reasoning.isEmpty()) {
reasoningContent.append(reasoning);
if (isFirstPrint) {
System.out.println("====================Thinking process====================");
isFirstPrint = false;
}
System.out.print(reasoning);
}
if (Objects.nonNull(content) && !content.isEmpty()) {
Object text = content.get(0).get("text");
finalContent.append(content.get(0).get("text"));
if (!isFirstPrint) {
System.out.println("\n====================Complete response====================");
isFirstPrint = true;
}
System.out.print(text);
}
}
public static MultiModalConversationParam buildMultiModalConversationParam(MultiModalMessage Msg) {
return MultiModalConversationParam.builder()
// If the environment variable is not configured, replace the following line with your Model Studio API key: .apiKey("sk-xxx")
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
.apiKey(System.getenv("DASHSCOPE_API_KEY"))
.model("qwen3.7-plus")
.messages(Arrays.asList(Msg))
.enableThinking(true)
.thinkingBudget(81920)
.incrementalOutput(true)
.build();
}
public static void streamCallWithMessage(MultiModalConversation conv, MultiModalMessage Msg)
throws NoApiKeyException, ApiException, InputRequiredException, UploadFileException {
MultiModalConversationParam param = buildMultiModalConversationParam(Msg);
Flowable<MultiModalConversationResult> result = conv.streamCall(param);
result.blockingForEach(message -> {
handleGenerationResult(message);
});
}
public static void main(String[] args) {
try {
MultiModalConversation conv = new MultiModalConversation();
MultiModalMessage userMsg = MultiModalMessage.builder()
.role(Role.USER.getValue())
.content(Arrays.asList(Collections.singletonMap("image", "https://img.alicdn.com/imgextra/i1/O1CN01gDEY8M1W114Hi3XcN_!!6000000002727-0-tps-1024-406.jpg"),
Collections.singletonMap("text", "Please solve this problem")))
.build();
streamCallWithMessage(conv, userMsg);
// Print the final result.
// if (reasoningContent.length() > 0) {
// System.out.println("\n====================Complete response====================");
// System.out.println(finalContent.toString());
// }
} catch (ApiException | NoApiKeyException | UploadFileException | InputRequiredException e) {
logger.error("An exception occurred: {}", e.getMessage());
}
System.exit(0);
}
}# ======= Important notes =======
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
# The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
# === Delete this comment before execution ===
curl -X POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-H 'X-DashScope-SSE: enable' \
-d '{
"model": "qwen3.7-plus",
"input":{
"messages":[
{
"role": "user",
"content": [
{"image": "https://img.alicdn.com/imgextra/i1/O1CN01gDEY8M1W114Hi3XcN_!!6000000002727-0-tps-1024-406.jpg"},
{"text": "Please solve this problem"}
]
}
]
},
"parameters":{
"enable_thinking": true,
"incremental_output": true,
"thinking_budget": 81920
}
}'Entrada de múltiplas imagens
Os modelos de compreensão visual aceitam o envio de várias imagens em uma única requisição, permitindo tarefas como comparação de produtos e processamento de documentos multipáginas. Para isso, basta incluir múltiplos objetos de imagem no array content da user message.
Importante
A quantidade de imagens está sujeita ao limite total de tokens do modelo para imagens e texto. A soma dos tokens de todas as imagens e textos não deve exceder a capacidade máxima de entrada do modelo.
OpenAI compatible
Python
import os
from openai import OpenAI
client = OpenAI(
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
api_key=os.getenv("DASHSCOPE_API_KEY"),
# The following URL is for the China (Beijing) region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
base_url="https://{WorkspaceId}.cn-beijing.maas.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
model="qwen3.7-plus", # This example uses qwen3.7-plus. You can replace it with another model as needed. For a list of models, see https://www.alibabacloud.com/help/zh/model-studio/models
messages=[
{"role": "user","content": [
{"type": "image_url","image_url": {"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"},},
{"type": "image_url","image_url": {"url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/tiger.png"},},
{"type": "text", "text": "What content do these images depict?"},
],
}
],
)
print(completion.choices[0].message.content)import os
from openai import OpenAI
client = OpenAI(
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
api_key=os.getenv("DASHSCOPE_API_KEY"),
# The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
base_url="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
model="qwen3.7-plus", # This example uses qwen3.7-plus. You can replace it with another model as needed. For a list of models, see https://www.alibabacloud.com/help/model-studio/getting-started/models
messages=[
{"role": "user","content": [
{"type": "image_url","image_url": {"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"},},
{"type": "image_url","image_url": {"url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/tiger.png"},},
{"type": "text", "text": "What content do these images depict?"},
],
}
],
)
print(completion.choices[0].message.content)Resposta
Image 1 shows a scene of a woman and a Labrador retriever interacting on a beach. The woman is wearing a plaid shirt and sitting on the sand, shaking hands with the dog. The background is the ocean waves and the sky, and the whole picture is full of warmth and joy.
Image 2 shows a scene of a tiger walking in a forest. The tiger's coat is orange with black stripes. It is stepping forward, surrounded by dense trees and vegetation, and the ground is covered with fallen leaves. The whole picture gives a feeling of wild nature.Node.js
import OpenAI from "openai";
const openai = new OpenAI(
{
// If the environment variable is not configured, replace the following line with your Model Studio API key: apiKey: "sk-xxx"
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
apiKey: process.env.DASHSCOPE_API_KEY,
// The following URL is for the China (Beijing) region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
baseURL: "https://{WorkspaceId}.cn-beijing.maas.aliyuncs.com/compatible-mode/v1"
}
);
async function main() {
const response = await openai.chat.completions.create({
model: "qwen3.7-plus", // This example uses qwen3.7-plus. You can replace it with another model as needed. For a list of models, see https://www.alibabacloud.com/help/zh/model-studio/models
messages: [
{role: "user",content: [
{type: "image_url",image_url: {"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"}},
{type: "image_url",image_url: {"url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/tiger.png"}},
{type: "text", text: "What content do these images depict?" },
]}]
});
console.log(response.choices[0].message.content);
}
main()import OpenAI from "openai";
const openai = new OpenAI(
{
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
// If the environment variable is not configured, replace the following line with your Model Studio API key: apiKey: "sk-xxx"
apiKey: process.env.DASHSCOPE_API_KEY,
// The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
baseURL: "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1"
}
);
async function main() {
const response = await openai.chat.completions.create({
model: "qwen3.7-plus", // This example uses qwen3.7-plus. You can replace it with another model as needed. For a list of models, see https://www.alibabacloud.com/help/model-studio/getting-started/models
messages: [
{role: "user",content: [
{type: "image_url",image_url: {"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"}},
{type: "image_url",image_url: {"url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/tiger.png"}},
{type: "text", text: "What content do these images depict?" },
]}]
});
console.log(response.choices[0].message.content);
}
main()Resposta
In the first image, a person and a dog are interacting on a beach. The person is wearing a plaid shirt, and the dog is wearing a collar. They seem to be shaking hands or giving a high-five.
In the second image, a tiger is walking in a forest. The tiger's coat is orange with black stripes, and the background is green trees and vegetation.curl
# ======= Important notes =======
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# The following URL is for the China (Beijing) region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
# === Delete this comment before execution ===
curl -X POST https://{WorkspaceId}.cn-beijing.maas.aliyuncs.com/compatible-mode/v1/chat/completions \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "qwen3.7-plus",
"messages": [
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": {
"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"
}
},
{
"type": "image_url",
"image_url": {
"url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/tiger.png"
}
},
{
"type": "text",
"text": "What content do these images depict?"
}
]
}
]
}'# ======= Important notes =======
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
# The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
# === Delete this comment before execution ===
curl -X POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1/chat/completions \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "qwen3.7-plus",
"messages": [
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": {
"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"
}
},
{
"type": "image_url",
"image_url": {
"url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/tiger.png"
}
},
{
"type": "text",
"text": "What content do these images depict?"
}
]
}
]
}'Resposta
{
"choices": [
{
"message": {
"content": "Image 1 shows a scene of a woman and a Labrador retriever interacting on a beach. The woman is wearing a plaid shirt and sitting on the sand, shaking hands with the dog. The background is a sea view and a sunset sky, making the whole scene look very warm and harmonious.\n\nImage 2 shows a scene of a tiger walking in a forest. The tiger's coat is orange with black stripes. It is stepping forward, surrounded by dense trees and vegetation, and the ground is covered with fallen leaves. The whole picture is full of natural wildness and vitality.",
"role": "assistant"
},
"finish_reason": "stop",
"index": 0,
"logprobs": null
}
],
"object": "chat.completion",
"usage": {
"prompt_tokens": 2497,
"completion_tokens": 109,
"total_tokens": 2606
},
"created": 1725948561,
"system_fingerprint": null,
"model": "qwen3.7-plus",
"id": "chatcmpl-0fd66f46-b09e-9164-a84f-3ebbbedbac15"
}DashScope
Python
import os
import dashscope
# The following URL is for the China (Beijing) region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
dashscope.base_http_api_url = "https://{WorkspaceId}.cn-beijing.maas.aliyuncs.com/api/v1"
messages = [
{
"role": "user",
"content": [
{"image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"},
{"image": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/tiger.png"},
{"text": "What content do these images depict?"}
]
}
]
response = dashscope.MultiModalConversation.call(
# If the environment variable is not configured, replace the following line with your Model Studio API key: api_key="sk-xxx"
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
api_key=os.getenv('DASHSCOPE_API_KEY'),
model='qwen3.7-plus', # This example uses qwen3.7-plus. You can replace it with another model as needed. For a list of models, see https://www.alibabacloud.com/help/zh/model-studio/models
messages=messages
)
print(response.output.choices[0].message.content[0]["text"])import os
import dashscope
# The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
dashscope.base_http_api_url = 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1'
messages = [
{
"role": "user",
"content": [
{"image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"},
{"image": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/tiger.png"},
{"text": "What content do these images depict?"}
]
}
]
response = dashscope.MultiModalConversation.call(
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
# If the environment variable is not configured, replace the following line with your Model Studio API key: api_key="sk-xxx"
api_key=os.getenv('DASHSCOPE_API_KEY'),
model='qwen3.7-plus', # This example uses qwen3.7-plus. You can replace it with another model as needed. For a list of models, see https://www.alibabacloud.com/help/model-studio/getting-started/models
messages=messages
)
print(response.output.choices[0].message.content[0]["text"])Resposta
These images show some animals and natural scenes. In the first image, a person and a dog are interacting on a beach. The second image is of a tiger walking in a forest.Java
import java.util.Arrays;
import java.util.Collections;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.UploadFileException;
import java.util.HashMap;
import com.alibaba.dashscope.utils.Constants;
public class Main {
// The following URL is for the China (Beijing) region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
static {Constants.baseHttpApiUrl="https://{WorkspaceId}.cn-beijing.maas.aliyuncs.com/api/v1";}
public static void simpleMultiModalConversationCall()
throws ApiException, NoApiKeyException, UploadFileException {
MultiModalConversation conv = new MultiModalConversation();
MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())
.content(Arrays.asList(
Collections.singletonMap("image", "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"),
Collections.singletonMap("image", "https://dashscope.oss-cn-beijing.aliyuncs.com/images/tiger.png"),
Collections.singletonMap("text", "What content do these images depict?"))).build();
MultiModalConversationParam param = MultiModalConversationParam.builder()
// If the environment variable is not configured, replace the following line with your Model Studio API key: .apiKey("sk-xxx")
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
.apiKey(System.getenv("DASHSCOPE_API_KEY"))
.model("qwen3.7-plus") // This example uses qwen3.7-plus. You can replace it with another model as needed. For a list of models, see https://www.alibabacloud.com/help/zh/model-studio/models
.messages(Arrays.asList(userMessage))
.build();
MultiModalConversationResult result = conv.call(param);
System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent().get(0).get("text")); }
public static void main(String[] args) {
try {
simpleMultiModalConversationCall();
} catch (ApiException | NoApiKeyException | UploadFileException e) {
System.out.println(e.getMessage());
}
System.exit(0);
}
}import java.util.Arrays;
import java.util.Collections;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.UploadFileException;
import com.alibaba.dashscope.utils.Constants;
public class Main {
static {
// The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
Constants.baseHttpApiUrl="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1";
}
public static void simpleMultiModalConversationCall()
throws ApiException, NoApiKeyException, UploadFileException {
MultiModalConversation conv = new MultiModalConversation();
MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())
.content(Arrays.asList(
Collections.singletonMap("image", "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"),
Collections.singletonMap("image", "https://dashscope.oss-cn-beijing.aliyuncs.com/images/tiger.png"),
Collections.singletonMap("text", "What content do these images depict?"))).build();
MultiModalConversationParam param = MultiModalConversationParam.builder()
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
.apiKey(System.getenv("DASHSCOPE_API_KEY"))
.model("qwen3.7-plus") // This example uses qwen3.7-plus. You can replace it with another model as needed. For a list of models, see https://www.alibabacloud.com/help/model-studio/getting-started/models
.messages(Arrays.asList(userMessage))
.build();
MultiModalConversationResult result = conv.call(param);
System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent().get(0).get("text")); }
public static void main(String[] args) {
try {
simpleMultiModalConversationCall();
} catch (ApiException | NoApiKeyException | UploadFileException e) {
System.out.println(e.getMessage());
}
System.exit(0);
}
}Resposta
These images show some animals and natural scenes.
1. First image: A woman and a dog are interacting on a beach. The woman is wearing a plaid shirt and sitting on the sand, and the dog is wearing a collar and extending its paw to shake hands with the woman.
2. Second image: A tiger is walking in a forest. The tiger's coat is orange with black stripes, and the background is trees and leaves.curl
# ======= Important notes =======
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# The following URL is for the China (Beijing) region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
# === Delete this comment before execution ===
curl --location 'https://{WorkspaceId}.cn-beijing.maas.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
"model": "qwen3.7-plus",
"input":{
"messages":[
{
"role": "user",
"content": [
{"image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"},
{"image": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/tiger.png"},
{"text": "What content do these images show?"}
]
}
]
}
}'# ======= Important notes =======
# The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
# === Delete this comment before execution ===
curl --location 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
"model": "qwen3.7-plus",
"input":{
"messages":[
{
"role": "user",
"content": [
{"image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"},
{"image": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/tiger.png"},
{"text": "What content do these images show?"}
]
}
]
}
}'Resposta
{
"output": {
"choices": [
{
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": [
{
"text": "These images show some animals and natural scenes. In the first image, a person and a dog are interacting on a beach. The second image is of a tiger walking in a forest."
}
]
}
}
]
},
"usage": {
"output_tokens": 81,
"input_tokens": 1277,
"image_tokens": 2497
},
"request_id": "ccf845a3-dc33-9cda-b581-20fe7dc23f70"
}Compreensão de vídeo
Os modelos de compreensão visual analisam o conteúdo de vídeo fornecido como uma lista de imagens (frames de vídeo) ou um arquivo de vídeo. Os exemplos a seguir mostram como compreender vídeos online ou listas de imagens especificadas por uma URL. Para obter mais informações sobre os limites de vídeo ou o número de imagens que podem ser passadas em uma lista de imagens, consulte Limites de vídeo.
Para obter melhor desempenho ao analisar arquivos de vídeo, utilize as versões de snapshot mais recentes ou atuais dos modelos.
Arquivos de vídeo
Os modelos de compreensão visual analisam o conteúdo do vídeo extraindo uma sequência de frames. É possível controlar a estratégia de extração de frames com os dois parâmetros a seguir:
-
fps: Controla a frequência de extração de frames. Um frame é extraído a cada
\frac 1 {fps} segundos. O intervalo de valores é [0.1, 10], e o valor padrão é 2.0.Para cenas com movimento rápido, defina um valor de fps mais alto para capturar mais detalhes.
Em cenas estáticas ou vídeos longos, defina um valor de fps mais baixo para melhorar o desempenho.
max_frames: Número máximo de frames a serem extraídos de um vídeo. O sistema calcula o total de frames com base no fps do vídeo. Se o número total de frames exceder esse limite, o sistema amostra automaticamente os frames de maneira uniforme para atender ao limite. Este parâmetro está disponível apenas ao usar o DashScope SDK.
Compatível com OpenAI
Ao enviar um arquivo de vídeo diretamente para o modelo de compreensão visual usando o OpenAI SDK ou HTTP, defina o parâmetro"type"na mensagem do usuário como"video_url".
Python
import os
from openai import OpenAI
client = OpenAI(
# API keys vary by region. To get an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# If you have not configured the environment variable, replace the following line with your Model Studio API key: api_key="sk-xxx",
api_key=os.getenv("DASHSCOPE_API_KEY"),
# The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your workspace ID. URLs vary by region.
base_url="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
model="qwen3.7-plus",
messages=[
{
"role": "user",
"content": [
# When you pass a video file directly, set the value of type to video_url.
{
"type": "video_url",
"video_url": {
"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241115/cqqkru/1.mp4"
},
"fps": 2
},
{
"type": "text",
"text": "What is the content of this video?"
}
]
}
]
)
print(completion.choices[0].message.content)Node.js
import OpenAI from "openai";
const openai = new OpenAI(
{
// API keys vary by region. To get an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
// If you have not configured the environment variable, replace the following line with your Model Studio API key: apiKey: "sk-xxx"
apiKey: process.env.DASHSCOPE_API_KEY,
// The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your workspace ID. URLs vary by region.
baseURL: "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1"
}
);
async function main() {
const response = await openai.chat.completions.create({
model: "qwen3.7-plus",
messages: [
{
role: "user",
content: [
// When you pass a video file directly, set the value of type to video_url.
{
type: "video_url",
video_url: {
"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241115/cqqkru/1.mp4"
},
"fps": 2
},
{
type: "text",
text: "What is the content of this video?"
}
]
}
]
});
console.log(response.choices[0].message.content);
}
main();curl
# ======= Important =======
# API keys vary by region. To get an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your workspace ID. URLs vary by region.
# === Delete this comment before execution. ===
curl -X POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1/chat/completions \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "qwen3.7-plus",
"messages": [
{
"role": "user",
"content": [
{
"type": "video_url",
"video_url": {
"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241115/cqqkru/1.mp4"
},
"fps":2
},
{
"type": "text",
"text": "What is the content of this video?"
}
]
}
]
}'DashScope
Python
import dashscope
import os
# The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your workspace ID. URLs vary by region.
dashscope.base_http_api_url = 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1'
messages = [
{"role": "user",
"content": [
# The fps parameter controls the video frame extraction frequency. It indicates that one frame is extracted every 1/fps seconds. For complete usage, see: https://www.alibabacloud.com/help/zh/model-studio/use-qwen-by-calling-api?#2ed5ee7377fum
{"video": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241115/cqqkru/1.mp4","fps":2},
{"text": "What is the content of this video?"}
]
}
]
response = dashscope.MultiModalConversation.call(
# API keys vary by region. To get an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# If you have not configured the environment variable, replace the following line with your Model Studio API key: api_key ="sk-xxx"
api_key=os.getenv('DASHSCOPE_API_KEY'),
model='qwen3.7-plus',
messages=messages
)
print(response.output.choices[0].message.content[0]["text"])Java
import java.util.Arrays;
import java.util.Collections;
import java.util.HashMap;
import java.util.Map;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.UploadFileException;
import com.alibaba.dashscope.utils.Constants;
public class Main {
static {
// The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your workspace ID. URLs vary by region.
Constants.baseHttpApiUrl="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1";
}
public static void simpleMultiModalConversationCall()
throws ApiException, NoApiKeyException, UploadFileException {
MultiModalConversation conv = new MultiModalConversation();
// The fps parameter controls the video frame extraction frequency. It indicates that one frame is extracted every 1/fps seconds. For complete usage, see: https://www.alibabacloud.com/help/zh/model-studio/use-qwen-by-calling-api?#2ed5ee7377fum
Map<String, Object> params = new HashMap<>();
params.put("video", "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241115/cqqkru/1.mp4");
params.put("fps", 2);
MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())
.content(Arrays.asList(
params,
Collections.singletonMap("text", "What is the content of this video?"))).build();
MultiModalConversationParam param = MultiModalConversationParam.builder()
// If you use a model in the China (Beijing) region, you must use an API key for that region. To get an API key, see: https://www.alibabacloud.com/help/zh/model-studio/get-api-key
// If you have not configured the environment variable, replace the following line with your Model Studio API key: .apiKey("sk-xxx")
.apiKey(System.getenv("DASHSCOPE_API_KEY"))
.model("qwen3.7-plus")
.messages(Arrays.asList(userMessage))
.build();
MultiModalConversationResult result = conv.call(param);
System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent().get(0).get("text"));
}
public static void main(String[] args) {
try {
simpleMultiModalConversationCall();
} catch (ApiException | NoApiKeyException | UploadFileException e) {
System.out.println(e.getMessage());
}
System.exit(0);
}
}curl
# ======= Important =======
# The following URL is for the Singapore region. When you make a call, replace {WorkspaceId} with your workspace ID. URLs vary by region.
# API keys vary by region. To get an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# === Delete this comment before execution. ===
curl -X POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "qwen3.7-plus",
"input":{
"messages":[
{"role": "user","content": [{"video": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241115/cqqkru/1.mp4","fps":2},
{"text": "What is the content of this video?"}]}]}
}'Lista de imagens
Ao fornecer um vídeo como uma lista de frames pré-extraídos, use o parâmetro fps para especificar o intervalo de tempo entre os frames. Isso ajuda o modelo a compreender melhor a sequência, a duração e as mudanças dinâmicas dos eventos. O parâmetro fps indica que os frames foram extraídos do vídeo original a cada
Compatível com OpenAI
Ao usar o OpenAI SDK ou HTTP para inserir um vídeo como uma lista de imagens no modelo de compreensão visual, defina o parâmetro"type"na mensagem do usuário como"video".
Python
import os
from openai import OpenAI
client = OpenAI(
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# If you have not configured the environment variable, replace the following line with your Model Studio API key: api_key="sk-xxx",
api_key=os.getenv("DASHSCOPE_API_KEY"),
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
base_url="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
model="qwen3.7-plus", # This example uses qwen3.7-plus. You can replace it with another model name as needed. For a list of models, see https://www.alibabacloud.com/help/zh/model-studio/models
messages=[{"role": "user","content": [
# When you input a list of images, the "type" parameter in the user message is "video"
{"type": "video","video": [
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/xzsgiz/football1.jpg",
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/tdescd/football2.jpg",
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/zefdja/football3.jpg",
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/aedbqh/football4.jpg"],
"fps":2},
{"type": "text","text": "Describe the specific process in this video"},
]}]
)
print(completion.choices[0].message.content)Node.js
// Make sure you have specified "type": "module" in your package.json file.
import OpenAI from "openai";
const openai = new OpenAI({
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
// If you have not configured the environment variable, replace the following line with your Model Studio API key: apiKey: "sk-xxx",
apiKey: process.env.DASHSCOPE_API_KEY,
// The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
baseURL: "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1"
});
async function main() {
const response = await openai.chat.completions.create({
model: "qwen3.7-plus", // This example uses qwen3.7-plus. You can replace it with another model name as needed. For a list of models, see https://www.alibabacloud.com/help/zh/model-studio/models
messages: [{
role: "user",
content: [
{
// When you input a list of images, the "type" parameter in the user message is "video"
type: "video",
video: [
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/xzsgiz/football1.jpg",
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/tdescd/football2.jpg",
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/zefdja/football3.jpg",
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/aedbqh/football4.jpg"],
"fps": 2
},
{
type: "text",
text: "Describe the specific process in this video"
}
]
}]
});
console.log(response.choices[0].message.content);
}
main();curl
# ======= Important =======
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
# === Delete this comment before execution ===
curl -X POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1/chat/completions \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "qwen3.7-plus",
"messages": [{"role": "user","content": [{"type": "video","video": [
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/xzsgiz/football1.jpg",
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/tdescd/football2.jpg",
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/zefdja/football3.jpg",
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/aedbqh/football4.jpg"],
"fps":2},
{"type": "text","text": "Describe the specific process in this video"}]}]
}'DashScope
Python
import os
import dashscope
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
dashscope.base_http_api_url = 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1'
messages = [{"role": "user",
"content": [
# When you input a list of images, the fps parameter applies to the Qwen3.6, Qwen3-VL, and Qwen2.5-VL series models.
{"video":["https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/xzsgiz/football1.jpg",
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/tdescd/football2.jpg",
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/zefdja/football3.jpg",
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/aedbqh/football4.jpg"],
"fps":2},
{"text": "Describe the specific process in this video"}]}]
response = dashscope.MultiModalConversation.call(
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# If you have not configured the environment variable, replace the following line with your Model Studio API key: api_key="sk-xxx",
api_key=os.getenv("DASHSCOPE_API_KEY"),
model='qwen3.7-plus', # This example uses qwen3.7-plus. You can replace it with another model name as needed. For a list of models, see https://www.alibabacloud.com/help/model-studio/getting-started/models
messages=messages
)
print(response.output.choices[0].message.content[0]["text"])Java
// The DashScope SDK version must be 2.21.10 or later.
import java.util.Arrays;
import java.util.Collections;
import java.util.Map;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.UploadFileException;
import com.alibaba.dashscope.utils.Constants;
public class Main {
static {
// The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
Constants.baseHttpApiUrl="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1";
}
private static final String MODEL_NAME = "qwen3.7-plus"; // This example uses qwen3.7-plus. You can replace it with another model name as needed. For a list of models, see https://www.alibabacloud.com/help/model-studio/getting-started/models
public static void videoImageListSample() throws ApiException, NoApiKeyException, UploadFileException {
MultiModalConversation conv = new MultiModalConversation();
// When you input a list of images, the fps parameter applies to the Qwen3.6, Qwen3-VL, and Qwen2.5-VL series models.
Map<String, Object> params = new HashMap<>();
params.put("video", Arrays.asList("https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/xzsgiz/football1.jpg",
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/tdescd/football2.jpg",
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/zefdja/football3.jpg",
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/aedbqh/football4.jpg"));
params.put("fps", 2);
MultiModalMessage userMessage = MultiModalMessage.builder()
.role(Role.USER.getValue())
.content(Arrays.asList(
params,
Collections.singletonMap("text", "Describe the specific process in this video")))
.build();
MultiModalConversationParam param = MultiModalConversationParam.builder()
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
// If you have not configured the environment variable, replace the following line with your Model Studio API key: .apiKey("sk-xxx")
.apiKey(System.getenv("DASHSCOPE_API_KEY"))
.model(MODEL_NAME)
.messages(Arrays.asList(userMessage)).build();
MultiModalConversationResult result = conv.call(param);
System.out.print(result.getOutput().getChoices().get(0).getMessage().getContent().get(0).get("text"));
}
public static void main(String[] args) {
try {
videoImageListSample();
} catch (ApiException | NoApiKeyException | UploadFileException e) {
System.out.println(e.getMessage());
}
System.exit(0);
}
}curl
# ======= Important =======
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# === Delete this comment before execution ===
curl -X POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "qwen3.7-plus",
"input": {
"messages": [
{
"role": "user",
"content": [
{
"video": [
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/xzsgiz/football1.jpg",
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/tdescd/football2.jpg",
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/zefdja/football3.jpg",
"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/aedbqh/football4.jpg"
],
"fps":2
},
{
"text": "Describe the specific process in this video"
}
]
}
]
}
}'Passar um arquivo local (codificação Base64 ou caminho do arquivo)
Os modelos de compreensão visual aceitam dois métodos para upload de arquivos locais: codificação Base64 e upload direto pelo caminho do arquivo. Escolha o método de upload conforme o tamanho do arquivo e o tipo de SDK. Para recomendações, consulte Como escolher um método de upload de arquivo. Ambos os métodos devem atender aos requisitos de arquivo descritos em Limitações de imagem.
Upload usando codificação Base64
Converta o arquivo para uma string codificada em Base64 e passe-a ao modelo. Este método é aplicável aos SDKs OpenAI e DashScope, além de requisições HTTP.
Upload usando caminho de arquivo
Passe diretamente o caminho do arquivo local para o modelo. Apenas os SDKs Python e Java do DashScope oferecem suporte a este método. Ele não é compatível com requisições HTTP do DashScope nem com o modo compatível com OpenAI.
Consulte a tabela a seguir para especificar o caminho do arquivo de acordo com sua linguagem de programação e sistema operacional.
Imagem
Passar usando um caminho de arquivo
Python
import os
import dashscope
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
dashscope.base_http_api_url = 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1'
# Replace xxx/eagle.png with the absolute path of your local image
local_path = "xxx/eagle.png"
image_path = f"file://{local_path}"
messages = [
{'role':'user',
'content': [{'image': image_path},
{'text': 'What scene is depicted in the image?'}]}]
response = dashscope.MultiModalConversation.call(
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# If you have not configured the environment variable, replace the following line with your Model Studio API key: api_key="sk-xxx"
api_key=os.getenv('DASHSCOPE_API_KEY'),
model='qwen3.7-plus', # This example uses qwen3.7-plus. You can change the model name as needed. For a list of models, see https://www.alibabacloud.com/help/model-studio/getting-started/models
messages=messages)
print(response.output.choices[0].message.content[0]["text"])Java
import java.util.Arrays;
import java.util.Collections;
import java.util.HashMap;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.UploadFileException;
import com.alibaba.dashscope.utils.Constants;
public class Main {
static {
// The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
Constants.baseHttpApiUrl="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1";
}
public static void callWithLocalFile(String localPath)
throws ApiException, NoApiKeyException, UploadFileException {
String filePath = "file://"+localPath;
MultiModalConversation conv = new MultiModalConversation();
MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())
.content(Arrays.asList(new HashMap<String, Object>(){{put("image", filePath);}},
new HashMap<String, Object>(){{put("text", "What scene is depicted in the image?");}})).build();
MultiModalConversationParam param = MultiModalConversationParam.builder()
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
// If you have not configured the environment variable, replace the following line with your Model Studio API key: .apiKey("sk-xxx")
.apiKey(System.getenv("DASHSCOPE_API_KEY"))
.model("qwen3.7-plus") // This example uses qwen3.7-plus. You can change the model name as needed. For a list of models, see https://www.alibabacloud.com/help/model-studio/getting-started/models
.messages(Arrays.asList(userMessage))
.build();
MultiModalConversationResult result = conv.call(param);
System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent().get(0).get("text"));}
public static void main(String[] args) {
try {
// Replace xxx/eagle.png with the absolute path of your local image
callWithLocalFile("xxx/eagle.png");
} catch (ApiException | NoApiKeyException | UploadFileException e) {
System.out.println(e.getMessage());
}
System.exit(0);
}
}Entrada codificada em Base64
Compatível com OpenAI
Python
from openai import OpenAI
import os
import base64
# Encoding function: Converts a local file to a Base64-encoded string
def encode_image(image_path):
with open(image_path, "rb") as image_file:
return base64.b64encode(image_file.read()).decode("utf-8")
# Replace xxxx/eagle.png with the absolute path of your local image
base64_image = encode_image("xxx/eagle.png")
client = OpenAI(
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# If you have not configured the environment variable, replace the following line with your Model Studio API key: api_key="sk-xxx"
api_key=os.getenv('DASHSCOPE_API_KEY'),
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
base_url="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
model="qwen3.7-plus", # This example uses qwen3.7-plus. You can change the model name as needed. For a list of models, see https://www.alibabacloud.com/help/model-studio/getting-started/models
messages=[
{
"role": "user",
"content": [
{
"type": "image_url",
# When passing Base64 image data, note that the image format (image/{format}) must match the Content Type in the list of supported images. "f" is a method for string formatting.
# PNG image: f"data:image/png;base64,{base64_image}"
# JPEG image: f"data:image/jpeg;base64,{base64_image}"
# WEBP image: f"data:image/webp;base64,{base64_image}"
"image_url": {"url": f"data:image/png;base64,{base64_image}"},
},
{"type": "text", "text": "What scene is depicted in the image?"},
],
}
],
)
print(completion.choices[0].message.content)Node.js
import OpenAI from "openai";
import { readFileSync } from 'fs';
const openai = new OpenAI(
{
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
// If you have not configured the environment variable, replace the following line with your Model Studio API key: apiKey: "sk-xxx"
apiKey: process.env.DASHSCOPE_API_KEY,
// The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
baseURL: "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1"
}
);
const encodeImage = (imagePath) => {
const imageFile = readFileSync(imagePath);
return imageFile.toString('base64');
};
// Replace xxx/eagle.png with the absolute path of your local image
const base64Image = encodeImage("xxx/eagle.png")
async function main() {
const completion = await openai.chat.completions.create({
model: "qwen3.7-plus", // This example uses qwen3.7-plus. You can change the model name as needed. For a list of models, see https://www.alibabacloud.com/help/model-studio/getting-started/models
messages: [
{"role": "user",
"content": [{"type": "image_url",
// Note: When passing Base64 data, the image format (image/{format}) must match the Content Type in the list of supported images.
// PNG image: data:image/png;base64,${base64Image}
// JPEG image: data:image/jpeg;base64,${base64Image}
// WEBP image: data:image/webp;base64,${base64Image}
"image_url": {"url": `data:image/png;base64,${base64Image}`},},
{"type": "text", "text": "What scene is depicted in the image?"}]}]
});
console.log(completion.choices[0].message.content);
}
main();curl
Para obter informações sobre como converter um arquivo em uma string codificada em Base64, consulte o código de exemplo.
Para fins de demonstração, a string codificada em Base64
"data:image/jpg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAA..."no código está truncada. Em uso real, certifique-se de passar a string codificada completa.
# ======= Important =======
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
# === Delete this comment before execution ===
curl --location 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1/chat/completions' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
"model": "qwen3.7-plus",
"messages": [
{
"role": "user",
"content": [
{"type": "image_url", "image_url": {"url": "data:image/jpg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAA"}},
{"type": "text", "text": "What scene is depicted in the image?"}
]
}]
}'DashScope
Python
import base64
import os
import dashscope
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
dashscope.base_http_api_url = 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1'
# Encoding function: Converts a local file to a Base64-encoded string
def encode_image(image_path):
with open(image_path, "rb") as image_file:
return base64.b64encode(image_file.read()).decode("utf-8")
# Replace xxxx/eagle.png with the absolute path of your local image
base64_image = encode_image("xxxx/eagle.png")
messages = [
{
"role": "user",
"content": [
# Note: When passing Base64 data, the image format (image/{format}) must match the Content Type in the list of supported images. "f" is a method for string formatting.
# PNG image: f"data:image/png;base64,{base64_image}"
# JPEG image: f"data:image/jpeg;base64,{base64_image}"
# WEBP image: f"data:image/webp;base64,{base64_image}"
{"image": f"data:image/png;base64,{base64_image}"},
{"text": "What scene is depicted in the image?"},
],
},
]
response = dashscope.MultiModalConversation.call(
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# If you have not configured the environment variable, replace the following line with your Model Studio API key: api_key="sk-xxx"
api_key=os.getenv("DASHSCOPE_API_KEY"),
model="qwen3.7-plus", # This example uses qwen3.7-plus. You can change the model name as needed. For a list of models, see https://www.alibabacloud.com/help/model-studio/getting-started/models
messages=messages,
)
print(response.output.choices[0].message.content[0]["text"])Java
import java.io.IOException;
import java.util.Arrays;
import java.util.Collections;
import java.util.HashMap;
import java.util.Base64;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.Paths;
import com.alibaba.dashscope.aigc.multimodalconversation.*;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.UploadFileException;
import com.alibaba.dashscope.utils.Constants;
public class Main {
static {
// The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
Constants.baseHttpApiUrl="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1";
}
private static String encodeImageToBase64(String imagePath) throws IOException {
Path path = Paths.get(imagePath);
byte[] imageBytes = Files.readAllBytes(path);
return Base64.getEncoder().encodeToString(imageBytes);
}
public static void callWithLocalFile(String localPath) throws ApiException, NoApiKeyException, UploadFileException, IOException {
String base64Image = encodeImageToBase64(localPath); // Base64 encoding
MultiModalConversation conv = new MultiModalConversation();
MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())
.content(Arrays.asList(
new HashMap<String, Object>() {{ put("image", "data:image/png;base64," + base64Image); }},
new HashMap<String, Object>() {{ put("text", "What scene is depicted in the image?"); }}
)).build();
MultiModalConversationParam param = MultiModalConversationParam.builder()
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
.apiKey(System.getenv("DASHSCOPE_API_KEY"))
.model("qwen3.7-plus")
.messages(Arrays.asList(userMessage))
.build();
MultiModalConversationResult result = conv.call(param);
System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent().get(0).get("text"));
}
public static void main(String[] args) {
try {
// Replace xxx/eagle.png with the absolute path of your local image
callWithLocalFile("xxx/eagle.png");
} catch (ApiException | NoApiKeyException | UploadFileException | IOException e) {
System.out.println(e.getMessage());
}
System.exit(0);
}
}curl
Para saber como converter um arquivo em uma string codificada em Base64, veja o código de exemplo.
Como demonstração, a string codificada em Base64
"data:image/jpg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAA..."no código aparece truncada. Ao utilizar em produção, passe sempre a string codificada completa.
# ======= Important =======
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# === Delete this comment before execution ===
curl -X POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "qwen3.7-plus",
"input":{
"messages":[
{
"role": "user",
"content": [
{"image": "data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAA..."},
{"text": "What scene is depicted in the image?"}
]
}
]
}
}'Arquivo de vídeo
Esta seção utiliza como exemplo um arquivo test.mp4 salvo localmente.
Passagem usando um caminho de arquivo
Python
import os
import dashscope
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
dashscope.base_http_api_url = 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1'
# Replace xxxx/test.mp4 with the absolute path of your local video
local_path = "xxx/test.mp4"
video_path = f"file://{local_path}"
messages = [
{'role':'user',
# The fps parameter controls the number of frames extracted from the video. It indicates that one frame is extracted every 1/fps seconds.
'content': [{'video': video_path,"fps":2},
{'text': 'What scene does this video depict?'}]}]
response = MultiModalConversation.call(
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# If you have not configured the environment variable, replace the following line with your Model Studio API key: api_key="sk-xxx"
api_key=os.getenv('DASHSCOPE_API_KEY'),
model='qwen3.7-plus',
messages=messages)
print(response.output.choices[0].message.content[0]["text"])Java
import java.util.Arrays;
import java.util.Collections;
import java.util.HashMap;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.UploadFileException;
import com.alibaba.dashscope.utils.Constants;
public class Main {
static {
// The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
Constants.baseHttpApiUrl="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1";
}
public static void callWithLocalFile(String localPath)
throws ApiException, NoApiKeyException, UploadFileException {
String filePath = "file://"+localPath;
MultiModalConversation conv = new MultiModalConversation();
MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())
.content(Arrays.asList(new HashMap<String, Object>()
{{
put("video", filePath);// The fps parameter controls the number of frames extracted from the video. It indicates that one frame is extracted every 1/fps seconds.
put("fps", 2);
}},
new HashMap<String, Object>(){{put("text", "What scene does this video depict?");}})).build();
MultiModalConversationParam param = MultiModalConversationParam.builder()
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
// If you have not configured the environment variable, replace the following line with your Model Studio API key: .apiKey("sk-xxx")
.apiKey(System.getenv("DASHSCOPE_API_KEY"))
.model("qwen3.7-plus")
.messages(Arrays.asList(userMessage))
.build();
MultiModalConversationResult result = conv.call(param);
System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent().get(0).get("text"));}
public static void main(String[] args) {
try {
// Replace xxxx/test.mp4 with the absolute path of your local video
callWithLocalFile("xxx/test.mp4");
} catch (ApiException | NoApiKeyException | UploadFileException e) {
System.out.println(e.getMessage());
}
System.exit(0);
}
}Entrada codificada em Base64
Compatível com OpenAI
Python
from openai import OpenAI
import os
import base64
# Encoding function: Converts a local file to a Base64-encoded string
def encode_video(video_path):
with open(video_path, "rb") as video_file:
return base64.b64encode(video_file.read()).decode("utf-8")
# Replace xxxx/test.mp4 with the absolute path of your local video
base64_video = encode_video("xxx/test.mp4")
client = OpenAI(
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# If you have not configured the environment variable, replace the following line with your Model Studio API key: api_key="sk-xxx"
api_key=os.getenv('DASHSCOPE_API_KEY'),
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
base_url="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
model="qwen3.7-plus",
messages=[
{
"role": "user",
"content": [
{
# When passing a video file directly, set the value of type to video_url
"type": "video_url",
"video_url": {"url": f"data:video/mp4;base64,{base64_video}"},
"fps":2
},
{"type": "text", "text": "What scene does this video depict?"},
],
}
],
)
print(completion.choices[0].message.content)Node.js
import OpenAI from "openai";
import { readFileSync } from 'fs';
const openai = new OpenAI(
{
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
// If you have not configured the environment variable, replace the following line with your Model Studio API key: apiKey: "sk-xxx"
apiKey: process.env.DASHSCOPE_API_KEY,
// The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
baseURL: "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1"
}
);
const encodeVideo = (videoPath) => {
const videoFile = readFileSync(videoPath);
return videoFile.toString('base64');
};
// Replace xxxx/test.mp4 with the absolute path of your local video
const base64Video = encodeVideo("xxx/test.mp4")
async function main() {
const completion = await openai.chat.completions.create({
model: "qwen3.7-plus",
messages: [
{"role": "user",
"content": [{
// When passing a video file directly, set the value of type to video_url
"type": "video_url",
"video_url": {"url": `data:video/mp4;base64,${base64Video}`},
"fps":2},
{"type": "text", "text": "What scene does this video depict?"}]}]
});
console.log(completion.choices[0].message.content);
}
main();
curl
Para obter informações sobre como converter um arquivo em uma string codificada em Base64, consulte o código de exemplo.
Para fins de demonstração, a string codificada em Base64
"data:video/mp4;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAA..."no código está truncada. Em uso real, certifique-se de passar a string codificada completa.
# ======= Important =======
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
# === Delete this comment before execution ===
curl --location 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1/chat/completions' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
"model": "qwen3.7-plus",
"messages": [
{
"role": "user",
"content": [
{"type": "video_url", "video_url": {"url": "data:video/mp4;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAA..."},"fps":2},
{"type": "text", "text": "What scene is depicted in the image?"}
]
}]
}'DashScope
Python
import base64
import os
import dashscope
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
dashscope.base_http_api_url = 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1'
# Encoding function: Converts a local file to a Base64-encoded string
def encode_video(video_path):
with open(video_path, "rb") as video_file:
return base64.b64encode(video_file.read()).decode("utf-8")
# Replace xxxx/test.mp4 with the absolute path of your local video
base64_video = encode_video("xxxx/test.mp4")
messages = [{'role':'user',
# The fps parameter controls the number of frames extracted from the video. It indicates that one frame is extracted every 1/fps seconds.
'content': [{'video': f"data:video/mp4;base64,{base64_video}","fps":2},
{'text': 'What scene does this video depict?'}]}]
response = dashscope.MultiModalConversation.call(
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# If you have not configured the environment variable, replace the following line with your Model Studio API key: api_key="sk-xxx"
api_key=os.getenv('DASHSCOPE_API_KEY'),
model='qwen3.7-plus',
messages=messages)
print(response.output.choices[0].message.content[0]["text"])Java
import java.io.IOException;
import java.util.*;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.Paths;
import com.alibaba.dashscope.aigc.multimodalconversation.*;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.UploadFileException;
import com.alibaba.dashscope.utils.Constants;
public class Main {
static {
// The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
Constants.baseHttpApiUrl="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1";
}
private static String encodeVideoToBase64(String videoPath) throws IOException {
Path path = Paths.get(videoPath);
byte[] videoBytes = Files.readAllBytes(path);
return Base64.getEncoder().encodeToString(videoBytes);
}
public static void callWithLocalFile(String localPath)
throws ApiException, NoApiKeyException, UploadFileException, IOException {
String base64Video = encodeVideoToBase64(localPath); // Base64 encoding
MultiModalConversation conv = new MultiModalConversation();
MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())
.content(Arrays.asList(new HashMap<String, Object>()
{{
put("video", "data:video/mp4;base64," + base64Video);// The fps parameter controls the number of frames extracted from the video. It indicates that one frame is extracted every 1/fps seconds.
put("fps", 2);
}},
new HashMap<String, Object>(){{put("text", "What scene does this video depict?");}})).build();
MultiModalConversationParam param = MultiModalConversationParam.builder()
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
// If you have not configured the environment variable, replace the following line with your Model Studio API key: .apiKey("sk-xxx")
.apiKey(System.getenv("DASHSCOPE_API_KEY"))
.model("qwen3.7-plus")
.messages(Arrays.asList(userMessage))
.build();
MultiModalConversationResult result = conv.call(param);
System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent().get(0).get("text"));
}
public static void main(String[] args) {
try {
// Replace xxx/test.mp4 with the absolute path of your local video
callWithLocalFile("xxx/test.mp4");
} catch (ApiException | NoApiKeyException | UploadFileException | IOException e) {
System.out.println(e.getMessage());
}
System.exit(0);
}
}curl
Para obter informações sobre como converter um arquivo em uma string codificada em Base64, consulte o código de exemplo.
Para fins de demonstração, a string codificada em Base64
"f"data:video/mp4;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAA..."no código está truncada. Em uso real, certifique-se de passar a string codificada completa.
# ======= Important =======
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# === Delete this comment before execution ===
curl -X POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "qwen3.7-plus",
"input":{
"messages":[
{
"role": "user",
"content": [
{"video": "data:video/mp4;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAA..."},
{"text": "What scene does this video depict? "}
]
}
]
}
}'Lista de imagens
Esta seção utiliza como exemplo os arquivos salvos localmente football1.jpg, football2.jpg, football3.jpg e football4.jpg.
Passagem de caminhos de arquivo
Python
import os
import dashscope
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
dashscope.base_http_api_url = 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1'
local_path1 = "football1.jpg"
local_path2 = "football2.jpg"
local_path3 = "football3.jpg"
local_path4 = "football4.jpg"
image_path1 = f"file://{local_path1}"
image_path2 = f"file://{local_path2}"
image_path3 = f"file://{local_path3}"
image_path4 = f"file://{local_path4}"
messages = [{'role':'user',
# When you pass an image list, the fps parameter applies to the Qwen3.6, Qwen3-VL, and Qwen2.5-VL series models.
'content': [{'video': [image_path1,image_path2,image_path3,image_path4],"fps":2},
{'text': 'What scene does this video depict?'}]}]
response = MultiModalConversation.call(
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# If you have not configured the environment variable, replace the following line with your Model Studio API key: api_key="sk-xxx"
api_key=os.getenv('DASHSCOPE_API_KEY'),
model='qwen3.7-plus', # This example uses qwen3.7-plus. You can change the model name as needed. For a list of models, see https://www.alibabacloud.com/help/model-studio/getting-started/models
messages=messages)
print(response.output.choices[0].message.content[0]["text"])Java
// The DashScope SDK version must be 2.21.10 or later.
import java.util.Arrays;
import java.util.Map;
import java.util.Collections;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.UploadFileException;
import com.alibaba.dashscope.utils.Constants;
public class Main {
static {
// The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
Constants.baseHttpApiUrl="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1";
}
private static final String MODEL_NAME = "qwen3.7-plus"; // This example uses qwen3.7-plus. You can change the model name as needed. For a list of models, see https://www.alibabacloud.com/help/model-studio/getting-started/models
public static void videoImageListSample(String localPath1, String localPath2, String localPath3, String localPath4)
throws ApiException, NoApiKeyException, UploadFileException {
MultiModalConversation conv = new MultiModalConversation();
String filePath1 = "file://" + localPath1;
String filePath2 = "file://" + localPath2;
String filePath3 = "file://" + localPath3;
String filePath4 = "file://" + localPath4;
Map<String, Object> params = new HashMap<>();
params.put("video", Arrays.asList(filePath1,filePath2,filePath3,filePath4));
// When you pass an image list, the fps parameter applies to the Qwen3.6, Qwen3-VL, and Qwen2.5-VL series models.
params.put("fps", 2);
MultiModalMessage userMessage = MultiModalMessage.builder()
.role(Role.USER.getValue())
.content(Arrays.asList(params,
Collections.singletonMap("text", "Describe the specific process in this video")))
.build();
MultiModalConversationParam param = MultiModalConversationParam.builder()
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
// If you have not configured the environment variable, replace the following line with your Model Studio API key: .apiKey("sk-xxx")
.apiKey(System.getenv("DASHSCOPE_API_KEY"))
.model(MODEL_NAME)
.messages(Arrays.asList(userMessage)).build();
MultiModalConversationResult result = conv.call(param);
System.out.print(result.getOutput().getChoices().get(0).getMessage().getContent().get(0).get("text"));
}
public static void main(String[] args) {
try {
videoImageListSample(
"xxx/football1.jpg",
"xxx/football2.jpg",
"xxx/football3.jpg",
"xxx/football4.jpg");
} catch (ApiException | NoApiKeyException | UploadFileException e) {
System.out.println(e.getMessage());
}
System.exit(0);
}
}Envio via codificação Base64
Compatível com OpenAI
Python
import os
from openai import OpenAI
import base64
# Encoding function: Converts a local file to a Base64-encoded string
def encode_image(image_path):
with open(image_path, "rb") as image_file:
return base64.b64encode(image_file.read()).decode("utf-8")
base64_image1 = encode_image("football1.jpg")
base64_image2 = encode_image("football2.jpg")
base64_image3 = encode_image("football3.jpg")
base64_image4 = encode_image("football4.jpg")
client = OpenAI(
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# If you have not configured the environment variable, replace the following line with your Model Studio API key: api_key="sk-xxx",
api_key=os.getenv("DASHSCOPE_API_KEY"),
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
base_url="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
model="qwen3.7-plus", # This example uses qwen3.7-plus. You can change the model name as needed. For a list of models, see https://www.alibabacloud.com/help/model-studio/getting-started/models
messages=[
{"role": "user","content": [
{"type": "video","video": [
f"data:image/jpeg;base64,{base64_image1}",
f"data:image/jpeg;base64,{base64_image2}",
f"data:image/jpeg;base64,{base64_image3}",
f"data:image/jpeg;base64,{base64_image4}",]},
{"type": "text","text": "Describe the specific process in this video"},
]}]
)
print(completion.choices[0].message.content)Node.js
import OpenAI from "openai";
import { readFileSync } from 'fs';
const openai = new OpenAI(
{
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
// If you have not configured the environment variable, replace the following line with your Model Studio API key: apiKey: "sk-xxx"
apiKey: process.env.DASHSCOPE_API_KEY,
// The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
baseURL: "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1"
}
);
const encodeImage = (imagePath) => {
const imageFile = readFileSync(imagePath);
return imageFile.toString('base64');
};
const base64Image1 = encodeImage("football1.jpg")
const base64Image2 = encodeImage("football2.jpg")
const base64Image3 = encodeImage("football3.jpg")
const base64Image4 = encodeImage("football4.jpg")
async function main() {
const completion = await openai.chat.completions.create({
model: "qwen3.7-plus", // This example uses qwen3.7-plus. You can change the model name as needed. For a list of models, see https://www.alibabacloud.com/help/model-studio/getting-started/models
messages: [
{"role": "user",
"content": [{"type": "video",
"video": [
`data:image/jpeg;base64,${base64Image1}`,
`data:image/jpeg;base64,${base64Image2}`,
`data:image/jpeg;base64,${base64Image3}`,
`data:image/jpeg;base64,${base64Image4}`]},
{"type": "text", "text": "What scene does this video depict?"}]}]
});
console.log(completion.choices[0].message.content);
}
main();curl
Para obter informações sobre como converter um arquivo em uma string codificada em Base64, consulte o código de exemplo.
Para fins de demonstração, a string codificada em Base64
"data:image/jpg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAA..."no código está truncada. Em uso real, certifique-se de passar a string codificada completa.
# ======= Important =======
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# === Delete this comment before execution ===
curl -X POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1/chat/completions \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "qwen3.7-plus",
"messages": [{"role": "user",
"content": [{"type": "video",
"video": [
"data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAA...",
"data:image/jpeg;base64,nEpp6jpnP57MoWSyOWwrkXMJhHRCWYeFYb...",
"data:image/jpeg;base64,JHWQnJPc40GwQ7zERAtRMK6iIhnWw4080s...",
"data:image/jpeg;base64,adB6QOU5HP7dAYBBOg/Fb7KIptlbyEOu58..."
]},
{"type": "text",
"text": "Describe the specific process in this video"}]}]
}'DashScope
Python
import base64
import os
import dashscope
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
dashscope.base_http_api_url = 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1'
# Encoding function: Converts a local file to a Base64-encoded string
def encode_image(image_path):
with open(image_path, "rb") as image_file:
return base64.b64encode(image_file.read()).decode("utf-8")
base64_image1 = encode_image("football1.jpg")
base64_image2 = encode_image("football2.jpg")
base64_image3 = encode_image("football3.jpg")
base64_image4 = encode_image("football4.jpg")
messages = [{'role':'user',
'content': [
{'video':
[f"data:image/jpeg;base64,{base64_image1}",
f"data:image/jpeg;base64,{base64_image2}",
f"data:image/jpeg;base64,{base64_image3}",
f"data:image/jpeg;base64,{base64_image4}"
]
},
{'text': 'Please describe the specific process of this video?'}]}]
response = dashscope.MultiModalConversation.call(
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
api_key=os.getenv("DASHSCOPE_API_KEY"),
model='qwen3.7-plus', # This example uses qwen3.7-plus. You can change the model name as needed. For a list of models, see https://www.alibabacloud.com/help/model-studio/getting-started/models
messages=messages)
print(response.output.choices[0].message.content[0]["text"])Java
import java.io.IOException;
import java.util.*;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.Paths;
import com.alibaba.dashscope.aigc.multimodalconversation.*;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.UploadFileException;
import com.alibaba.dashscope.utils.Constants;
public class Main {
static {
// The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
Constants.baseHttpApiUrl="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1";
}
private static String encodeImageToBase64(String imagePath) throws IOException {
Path path = Paths.get(imagePath);
byte[] imageBytes = Files.readAllBytes(path);
return Base64.getEncoder().encodeToString(imageBytes);
}
public static void videoImageListSample(String localPath1,String localPath2,String localPath3,String localPath4)
throws ApiException, NoApiKeyException, UploadFileException, IOException {
String base64Image1 = encodeImageToBase64(localPath1); // Base64 encoding
String base64Image2 = encodeImageToBase64(localPath2);
String base64Image3 = encodeImageToBase64(localPath3);
String base64Image4 = encodeImageToBase64(localPath4);
MultiModalConversation conv = new MultiModalConversation();
Map<String, Object> params = new HashMap<>();
params.put("video", Arrays.asList(
"data:image/jpeg;base64," + base64Image1,
"data:image/jpeg;base64," + base64Image2,
"data:image/jpeg;base64," + base64Image3,
"data:image/jpeg;base64," + base64Image4));
// When you pass an image list, the fps parameter applies to the Qwen3.6, Qwen3-VL, and Qwen2.5-VL series models.
params.put("fps", 2);
MultiModalMessage userMessage = MultiModalMessage.builder()
.role(Role.USER.getValue())
.content(Arrays.asList(params,
Collections.singletonMap("text", "Describe the specific process in this video")))
.build();
MultiModalConversationParam param = MultiModalConversationParam.builder()
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
.apiKey(System.getenv("DASHSCOPE_API_KEY"))
.model("qwen3.7-plus")
.messages(Arrays.asList(userMessage))
.build();
MultiModalConversationResult result = conv.call(param);
System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent().get(0).get("text"));
}
public static void main(String[] args) {
try {
// Replace xxx/football1.png and other files with the absolute paths of your local images
videoImageListSample(
"xxx/football1.jpg",
"xxx/football2.jpg",
"xxx/football3.jpg",
"xxx/football4.jpg"
);
} catch (ApiException | NoApiKeyException | UploadFileException | IOException e) {
System.out.println(e.getMessage());
}
System.exit(0);
}
}curl
Para obter informações sobre como converter um arquivo em uma string codificada em Base64, consulte o código de exemplo.
Para fins de demonstração, a string codificada em Base64
"data:image/jpg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAA..."no código está truncada. Em uso real, certifique-se de passar a string codificada completa.
# ======= Important =======
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# === Delete this comment before execution ===
curl -X POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "qwen3.7-plus",
"input": {
"messages": [
{
"role": "user",
"content": [
{
"video": [
"data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAA...",
"data:image/jpeg;base64,nEpp6jpnP57MoWSyOWwrkXMJhHRCWYeFYb...",
"data:image/jpeg;base64,JHWQnJPc40GwQ7zERAtRMK6iIhnWw4080s...",
"data:image/jpeg;base64,adB6QOU5HP7dAYBBOg/Fb7KIptlbyEOu58..."
],
"fps":2
},
{
"text": "Describe the specific process in this video"
}
]
}
]
}
}'Processamento de imagens de alta resolução
A API do modelo de compreensão visual possui um limite de tokens visuais para cada imagem codificada. Nas configurações padrão, imagens de alta resolução são compactadas, o que pode causar perda de detalhes e afetar a precisão da compreensão. Ative vl_high_resolution_images ou ajuste max_pixels para aumentar o número de tokens visuais. Essa alteração preserva mais detalhes da imagem e melhora a compreensão.
Quando
vl_high_resolution_images=true, a API utiliza uma política de resolução fixa e ignora a configuraçãomax_pixels. Essa opção é adequada para reconhecer textos finos, objetos pequenos ou detalhes complexos em imagens.-
Quando
vl_high_resolution_images=false, o limite final de pixels depende do valor do parâmetromax_pixels.Para cenários que exigem alta velocidade de processamento ou são sensíveis a custos: Utilize o valor padrão de
max_pixelsou defina um valor menor.Caso precise focar em detalhes específicos e possa aceitar uma velocidade de processamento menor, aumente o valor de
max_pixelsconforme necessário.
OpenAI compatible
O parâmetro vl_high_resolution_images não faz parte do padrão OpenAI. A forma de passá-lo varia entre os diferentes SDKs de linguagem:
Python SDK: Deve ser passado por meio do dicionário
extra_body.Node.js SDK: Pode ser passado diretamente como um parâmetro de nível superior.
Python
import os
from openai import OpenAI
client = OpenAI(
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
api_key=os.getenv("DASHSCOPE_API_KEY"),
# The following URL is for the China (Beijing) region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
base_url="https://{WorkspaceId}.cn-beijing.maas.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
model="qwen3.7-plus",
messages=[
{"role": "user","content": [
{"type": "image_url","image_url": {"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250212/earbrt/vcg_VCG211286867973_RF.jpg"},
# max_pixels represents the maximum pixel threshold for the input image. It is invalid when vl_high_resolution_images=True. When vl_high_resolution_images=False, it is customizable, and the maximum value varies by model.
# "max_pixels": 16384 * 32 * 32
},
{"type": "text", "text": "What festival atmosphere does this image convey?"},
],
}
],
extra_body={"vl_high_resolution_images":True}
)
print(f"Model output: {completion.choices[0].message.content}")
print(f"Total input tokens: {completion.usage.prompt_tokens}")import os
import time
from openai import OpenAI
client = OpenAI(
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
api_key=os.getenv("DASHSCOPE_API_KEY"),
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
base_url="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
model="qwen3.7-plus",
messages=[
{"role": "user","content": [
{"type": "image_url","image_url": {"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250212/earbrt/vcg_VCG211286867973_RF.jpg"},
# max_pixels represents the maximum pixel threshold for the input image. It is invalid when vl_high_resolution_images=True. When vl_high_resolution_images=False, it is customizable, and the maximum value varies by model.
# "max_pixels": 16384 * 32 * 32
},
{"type": "text", "text": "What festival atmosphere does this image convey"},
],
}
],
extra_body={"vl_high_resolution_images":True}
)
print(f"Model output: {completion.choices[0].message.content}")
print(f"Total input tokens: {completion.usage.prompt_tokens}")Node.js
import OpenAI from "openai";
const openai = new OpenAI(
{
// If you have not configured the environment variable, replace the following line with your Model Studio API key: apiKey: "sk-xxx"
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
apiKey: process.env.DASHSCOPE_API_KEY,
// The following URL is for the China (Beijing) region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
baseURL: "https://{WorkspaceId}.cn-beijing.maas.aliyuncs.com/compatible-mode/v1"
}
);
const response = await openai.chat.completions.create({
model: "qwen3.7-plus",
messages: [
{role: "user",content: [
{type: "image_url",
image_url: {"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250212/earbrt/vcg_VCG211286867973_RF.jpg"},
// max_pixels represents the maximum pixel threshold for the input image. It has no effect when vl_high_resolution_images=True. When vl_high_resolution_images=False, it is customizable, and the maximum value varies by model.
// "max_pixels": 2560 * 32 * 32
},
{type: "text", text: "What festival atmosphere does this image convey?" },
]}],
vl_high_resolution_images:true
})
console.log("Model output:",response.choices[0].message.content);
console.log("Total input tokens",response.usage.prompt_tokens);import OpenAI from "openai";
const openai = new OpenAI(
{
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
// If you have not configured the environment variable, replace the following line with your Model Studio API key: apiKey: "sk-xxx"
apiKey: process.env.DASHSCOPE_API_KEY,
// The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
baseURL: "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1"
}
);
const response = await openai.chat.completions.create({
model: "qwen3.7-plus",
messages: [
{role: "user",content: [
{type: "image_url",
image_url: {"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250212/earbrt/vcg_VCG211286867973_RF.jpg"},
// max_pixels represents the maximum pixel threshold for the input image. It has no effect when vl_high_resolution_images=True. When vl_high_resolution_images=False, it is customizable, and the maximum value varies by model.
// "max_pixels": 2560 * 32 * 32
},
{type: "text", text: "What festival atmosphere does this image convey?" },
]}],
vl_high_resolution_images:true
})
console.log("Model output:",response.choices[0].message.content);
console.log("Total input tokens",response.usage.prompt_tokens);
curl
# ======= Important =======
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# The following URL is for the China (Beijing) region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
# === Delete this comment before execution ===
curl -X POST https://{WorkspaceId}.cn-beijing.maas.aliyuncs.com/compatible-mode/v1/chat/completions \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "qwen3.7-plus",
"messages": [
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": {
"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250212/earbrt/vcg_VCG211286867973_RF.jpg"
}
},
{
"type": "text",
"text": "What festival atmosphere does this image convey?"
}
]
}
],
"vl_high_resolution_images":true
}'# ======= Important =======
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
# === Delete this comment before execution ===
curl -X POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1/chat/completions \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "qwen3.7-plus",
"messages": [
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": {
"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250212/earbrt/vcg_VCG211286867973_RF.jpg"
}
},
{
"type": "text",
"text": "What festival atmosphere does this image convey?"
}
]
}
],
"vl_high_resolution_images":true
}'DashScope
Python
import os
import time
import dashscope
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
dashscope.base_http_api_url = 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1'
messages = [
{
"role": "user",
"content": [
{"image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250212/earbrt/vcg_VCG211286867973_RF.jpg",
# max_pixels represents the maximum pixel threshold for the input image. It is invalid when vl_high_resolution_images=True. When vl_high_resolution_images=False, it is customizable, and the maximum value varies by model.
# "max_pixels": 16384 * 32 * 32
},
{"text": "What festival atmosphere does this image convey?"}
]
}
]
response = dashscope.MultiModalConversation.call(
# If you have not configured the environment variable, replace the following line with your Model Studio API key: api_key="sk-xxx"
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
api_key=os.getenv('DASHSCOPE_API_KEY'),
model='qwen3.7-plus',
messages=messages,
vl_high_resolution_images=True
)
print("Model output",response.output.choices[0].message.content[0]["text"])
print("Total input tokens:",response.usage.input_tokens)Java
import java.util.Arrays;
import java.util.Collections;
import java.util.Map;
import java.util.HashMap;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.UploadFileException;
import com.alibaba.dashscope.utils.Constants;
public class Main {
static {
// The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
Constants.baseHttpApiUrl="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1";
}
public static void simpleMultiModalConversationCall()
throws ApiException, NoApiKeyException, UploadFileException {
MultiModalConversation conv = new MultiModalConversation();
Map<String, Object> map = new HashMap<>();
map.put("image", "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250212/earbrt/vcg_VCG211286867973_RF.jpg");
// max_pixels represents the maximum pixel threshold for the input image. It is invalid when vl_high_resolution_images=True. When vl_high_resolution_images=False, it is customizable, and the maximum value varies by model.
// map.put("max_pixels", 2621440);
MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())
.content(Arrays.asList(
map,
Collections.singletonMap("text", "What festival atmosphere does this image convey?"))).build();
MultiModalConversationParam param = MultiModalConversationParam.builder()
// If you have not configured the environment variable, replace the following line with your Model Studio API key: .apiKey("sk-xxx")
.apiKey(System.getenv("DASHSCOPE_API_KEY"))
.model("qwen3.7-plus")
.message(userMessage)
.vlHighResolutionImages(true)
.build();
MultiModalConversationResult result = conv.call(param);
System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent().get(0).get("text"));
System.out.println(result.getUsage().getInputTokens());
}
public static void main(String[] args) {
try {
simpleMultiModalConversationCall();
} catch (ApiException | NoApiKeyException | UploadFileException e) {
System.out.println(e.getMessage());
}
System.exit(0);
}
}curl
# ======= Important =======
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# The following URL is for the Singapore region. When you call the API, replace {WorkspaceId} with your actual workspace ID. The URL varies by region.
# === Delete this comment before execution ===
curl -X POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "qwen3.7-plus",
"input":{
"messages":[
{
"role": "user",
"content": [
{"image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250212/earbrt/vcg_VCG211286867973_RF.jpg"},
{"text": "What festival atmosphere does this image convey?"}
]
}
]
},
"parameters": {
"vl_high_resolution_images": true
}
}'Mais casos de uso
Limites
Limites de arquivos de entrada
Image limits
-
Resolução da imagem:
Tamanho mínimo: A largura e a altura da imagem devem ser ambas maiores que
10pixels.-
Proporção: A razão entre o lado longo e o lado curto, tanto para imagens originais quanto redimensionadas, não deve exceder
200:1.Para obter informações sobre a lógica de redimensionamento de imagens, consulte a função
smart_resizeem Calcular tokens de imagem -
Máximo de pixels:
Mantenha a resolução da imagem dentro de
8K (7680x4320). Imagens com resolução superior podem causar timeouts na chamada da API devido ao tamanho grande dos arquivos e ao tempo prolongado de transmissão pela rede.Redimensionamento automático: O modelo ajusta o tamanho da imagem usando
max_pixelsemin_pixels. Fornecer imagens de alta resolução não melhora a precisão da detecção; pelo contrário, aumenta o risco de falhas nas chamadas. Redimensione as imagens para um tamanho adequado no cliente antes de fazer o upload.
-
Formatos de imagem suportados
-
Para resoluções abaixo de 4K
(3840x2160), os seguintes formatos de imagem são suportados:Formato de imagem
Extensões comuns
Tipo MIME
BMP
.bmp
image/bmp
JPEG
.jpe, .jpeg, .jpg
image/jpeg
PNG
.png
image/png
TIFF
.tif, .tiff
image/tiff
WEBP
.webp
image/webp
HEIC
.heic
image/heic
Para resoluções entre
4K (3840x2160)e8K (7680x4320), apenas os formatos JPEG, JPG e PNG são suportados.
-
-
Tamanho da imagem:
Quando passada como URL pública: Uma única imagem não pode exceder
20 MBpara modelos das séries Qwen3.7, Qwen3.6 e Qwen3.5. Para outros modelos, uma única imagem não pode exceder10 MB.Quando passada como caminho local: Uma única imagem não pode exceder
10 MB.Quando passada como string codificada em Base64: A string codificada não pode exceder
10 MB.
Para compactar um arquivo, consulte Como compactar uma imagem ou vídeo para o tamanho necessário .
-
Limite de quantidade de imagens: O número máximo de imagens suportado para entrada de múltiplas imagens varia conforme o método de entrada:
-
Quando passadas como URLs públicas ou caminhos locais:
Série Qwen3.7: Até 2.048 imagens
Séries Qwen3.6-Plus, Qwen3.6-Flash, Qwen3.5-Plus, Qwen3.5-Flash, Qwen3-VL, Qwen-VL, QVQ: Até 256 imagens
Para a série Qwen-Omni, consulte Omni-modal.
Quando passadas como strings codificadas em Base64: Até 250 imagens
-
O número total de tokens para todas as imagens também é limitado pelo limite máximo de tokens de entrada do modelo. A contagem total de tokens para todas as imagens e textos não deve exceder o máximo de entrada do modelo.
Video limits
-
Quando passado como uma lista de imagens, o número de imagens na lista é limitado da seguinte forma:
Séries
qwen3.6eqwen3.5: Mínimo de 4 imagens e máximo de 8.000 imagensSéries
qwen3-vl-plus,qwen3-vl-flash,qwen3-vl-235b-a22b-thinkingeqwen3-vl-235b-a22b-instruct: Mínimo de 4 imagens e máximo de 2.000 imagensOutros modelos open source
Qwen3-VL,Qwen2.5-VL(incluindo versões comerciais e open source) e modelos da sérieQVQ: Mínimo de 4 imagens e máximo de 512 imagensDemais modelos: Mínimo de 4 imagens e máximo de 80 imagens
-
Quando passado como um arquivo de vídeo:
-
Tamanho do vídeo:
-
Quando passado como URL pública:
Séries
qwen3.6,qwen3.5,Qwen3-VLeqwen-vl-max(incluindo todas as versões posteriores ae): Não pode exceder 2 GB.Série
qwen-vl-plus, outros modelosqwen-vl-max, série open sourceQwen2.5-VLe modelos da sérieQVQ: Não pode exceder 1 GB.Demais modelos: Não pode exceder 150 MB.
Quando passado como string codificada em Base64: A string codificada deve ter menos de 10 MB.
Quando passado como caminho de arquivo local: O arquivo de vídeo não pode exceder 100 MB.
Para compactar um arquivo, consulte Como compactar uma imagem ou vídeo para o tamanho necessário .
-
-
Duração do vídeo:
Séries
qwen3.6eqwen3.5: De 2 segundos a 2 horas.Séries
qwen3-vl-plus,qwen3-vl-flash,qwen3-vl-235b-a22b-thinkingeqwen3-vl-235b-a22b-instruct: De 2 segundos a 1 hora.Outras séries open source
Qwen3-VLeqwen-vl-max(incluindo todas as versões atualizadas apóse): De 2 segundos a 20 minutos.Série
qwen-vl-plus, outros modelosqwen-vl-max, série open sourceQwen2.5-VLe modelos da sérieQVQ: De 2 segundos a 10 minutos.Demais modelos: De 2 segundos a 40 segundos.
Formato de vídeo: MP4, AVI, MKV, MOV, FLV, WMV, entre outros.
Dimensões do vídeo: Não há limites específicos. O modelo ajusta automaticamente as dimensões do vídeo usando
max_pixelsemin_pixels. Arquivos de vídeo maiores não resultam em melhor compreensão.Limite de quantidade de vídeos: É possível passar até 64 vídeos.
Compreensão de áudio: O modelo não suporta a compreensão da faixa de áudio de arquivos de vídeo.
-
Métodos de entrada de arquivos
-
URL pública: Forneça um endereço de arquivo acessível publicamente que suporte o protocolo HTTP ou HTTPS. Para garantir estabilidade e desempenho ideais, faça o upload do arquivo para o OSS para obter uma URL pública.
ImportantePara garantir que o modelo consiga baixar o arquivo com sucesso, o cabeçalho de resposta da URL pública deve incluir Content-Length (tamanho do arquivo) e Content-Type (tipo de mídia, como image/jpeg). Se algum desses campos estiver ausente ou incorreto, o download do arquivo falhará.
Codificação Base64: Converta o arquivo para uma string codificada em Base64 e passe-o em seguida.
Caminho de arquivo local (apenas DashScope SDK): Passe o caminho de um arquivo local.
Para recomendações sobre como escolher um método de entrada de arquivo, consulte Como escolher um método de upload de arquivo?
Uso em ambiente de produção
Pré-processamento de imagens e vídeos: Os modelos de compreensão visual possuem limites de tamanho para arquivos de entrada. Para compactar arquivos, consulte Métodos de compactação de imagem ou vídeo.
-
Processamento de arquivos de texto: Os modelos de compreensão visual suportam apenas arquivos de imagem e vídeo. Eles não processam TXT, Word (.doc/.docx), PDF ou outros arquivos baseados em texto. Utilize uma das seguintes soluções alternativas:
Converta o arquivo de texto para um formato de imagem. Use uma biblioteca de processamento de imagens, como pdf2image para Python, para converter o arquivo página por página em várias imagens de alta qualidade. Em seguida, passe as imagens para o modelo usando o método de entrada de múltiplas imagens.
Utilize o Qwen-Long, que suporta o upload de documentos e a realização de conversas passando informações por meio de
file-id.
-
Tolerância a falhas e estabilidade
Tratamento de timeout: Em chamadas sem streaming, ocorre um erro de timeout se o modelo não terminar de gerar a saída dentro de 300 segundos. Quando isso acontece, o conteúdo gerado é retornado no corpo da resposta. Um cabeçalho de resposta contendo
x-dashscope-partialresponse: trueindica que a resposta atingiu o tempo limite. Utilize o recurso de modo parcial, suportado por alguns modelos. Adicione o conteúdo gerado ao arraymessagese envie a solicitação novamente. Isso permite que o Large Language Model (LLM) continue gerando conteúdo. Para mais informações, consulte Continuar a geração a partir de uma saída incompleta.Mecanismo de nova tentativa: Projete uma lógica adequada de novas tentativas para chamadas de API, como backoff exponencial, para lidar com flutuações de rede ou indisponibilidade temporária do serviço.
Faturamento e limitação de taxa
-
Faturamento: O custo total é calculado com base no número total de tokens de entrada e saída. Os preços de entrada e saída estão disponíveis no console do Model Studio.
Composição de tokens: Os tokens de entrada incluem tokens de texto e tokens convertidos a partir de imagens ou vídeos. Os tokens de saída correspondem ao texto gerado pelo modelo. No modo de raciocínio, o processo de pensamento do modelo também conta como tokens de saída. Caso o processo de pensamento não seja retornado nesse modo, o faturamento segue a tabela de preços do modo sem raciocínio.
-
Cálculo de tokens para imagens e vídeos: Utilize o código abaixo para estimar o consumo de tokens de imagens ou vídeos. O resultado é apenas uma referência; o uso real consta na resposta da API.
Visualizar faturas: Consulte suas faturas ou recarregue sua conta na página Expenses and Costs do Alibaba Cloud Management Console.
Limitação de taxa: Para detalhes sobre as condições de limitação de taxa dos modelos de compreensão visual, consulte Limitação de taxa.
Cota gratuita(apenas região Singapore): Uma cota gratuita de 1 milhão de tokens está disponível para modelos de compreensão visual. O período de validade de 90 dias começa na data em que você ativa o Model Studio ou quando sua solicitação de modelo é aprovada.
Instruções
Leia o conteúdo em inglês para compreender O QUE precisa ser comunicado
Escreva o português brasileiro DO ZERO — esqueça a estrutura das frases em inglês
Preserve toda a formatação markdown, blocos de código, links e imagens exatamente como estão
Tags xref (
<a data-tag="xref" ...>text</a>) — preserve A TAG INTEIRA com todos os atributos na ordem e caixa originais, traduza APENAS o texto visível entre > eAplique todas as regras específicas do idioma rigorosamente
Aplique as regras de stopwords com tolerância zero
Use o modo imperativo em passos numerados e listas de procedimentos
Garanta a consistência terminológica — o mesmo termo deve ter a mesma tradução em todo o documento
Varie os inícios de frase em listas e tabelas — nenhum início deve se repetir mais de 3 vezes
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Retorne APENAS o documento markdown em português brasileiro, sem explicações
Referência da API
Para obter mais informações sobre os parâmetros de entrada e saída do modelo de compreensão visual, consulte geração de texto.
Perguntas frequentes
Como escolher um método de upload de arquivo?
Como comprimir uma imagem ou vídeo para o tamanho necessário?
Após o modelo gerar resultados de localização de objetos, como desenhar quadros de detecção na imagem original?
Códigos de erro
Se uma chamada de modelo falhar, uma mensagem de erro será retornada. Para obter informações sobre como resolver o erro, consulte Códigos de erro.