基于 Amazon Nova 和 TEN 框架的实时音视频交互解决方案

    async def _on_video(self, ten_env: AsyncTenEnv):        """Process video frames from the queue."""        while True:            try:                [image_data, image_width, image_height] = await self.image_queue.get()                                frame_buffer = rgb2base64jpeg(image_data, image_width, image_height)                                self.image_buffers.append(frame_buffer)                                               while len(self.image_buffers) > MAX_IMAGE_COUNT:                    self.image_buffers.pop(0)                                # Skip remaining frames for the interval                while not self.image_queue.empty():                    await self.image_queue.get()                                    await asyncio.sleep(VIDEO_FRAME_INTERVAL)                            except Exception as e:                traceback.print_exc()                ten_env.log_error(f"Error processing video frame: {e}")

def resize_image_keep_aspect(image: Image.Image, max_size: int = 512) -> Image.Image:    """Resize an image while maintaining its aspect ratio."""    width, height = image.size
    if width <= max_size and height <= max_size:        return image
    aspect_ratio = width / height
    if width > height:        new_width = max_size        new_height = int(max_size / aspect_ratio)    else:        new_height = max_size        new_width = int(max_size * aspect_ratio)
    return image.resize((new_width, new_height))

    async def handle_transcript_event(self, transcript_event: TranscriptEvent) -> None:        results = transcript_event.transcript.results        text_result = ""
        is_final = True
        for result in results:            if result.is_partial:                is_final = False                # continue
            for alt in result.alternatives:                text_result += alt.transcript
        if not text_result:            return
        self.ten.log_info(f"got transcript: [{text_result}], is_final: [{is_final}]")
        create_and_send_data(ten=self.ten, text_result=text_result, is_final=is_final, stream_id=self.stream_id)

# 登陆dockeraws ecr get-login-password --region region_id | docker login --username AWS --password-stdin your_accountid.dkr.ecr.us-east-1.amazonaws.com
# 代码仓库https://github.com/zhuermu/TEN-Agent.git
# 在本地构建镜像  在目录TEN-Agent/Dockerfiledocker build -t dev/ten_agent_build .
# 打tagdocker tag dev/ten_agent_build:latest your_accountid.dkr.ecr.us-east-1.amazonaws.com/dev/ten_agent_build:latest# 推送镜像docker push your_accountid.dkr.ecr.us-east-1.amazonaws.com/dev/ten_agent_build:latest

# 部署集群eksctl create cluster -f cluster-config.yaml
# 创建命名空间kubectl create namespace ten-framework --save-config
# 创建部署deploymentkubectl apply -n ten-framework -f deployment.k8s.yaml
# 创建服务service 和 ingresskubectl apply -n ten-framework -f service.k8s.yaml

apiVersion: eksctl.io/v1alpha5kind: ClusterConfig
metadata:  name: ten-framework  region: us-east-1
autoModeConfig:  enabled: true

apiVersion: apps/v1kind: Deploymentmetadata:  name: ten-agent-demo  namespace: ten-frameworkspec:  replicas: 1  selector:    matchLabels:      app: ten-agent-demo  template:    metadata:      labels:        app: ten-agent-demo    spec:      containers:        - env:            - name: AGENT_SERVER_URL              value: http://ten-agent-build-service:8080          image: xxxxx.dkr.ecr.us-east-1.amazonaws.com/dev/ten_agent_demo:latest # 替换你的镜像地址,部署palyground          name: ten-agent-demo          ports:            - containerPort: 3000          resources:            requests:                          cpu: "1"                        memory: "2Gi"                 limits:                          cpu: "2"                       memory: "4Gi"   ---apiVersion: apps/v1kind: Deploymentmetadata:  name: ten-agent-build  namespace: ten-frameworkspec:  replicas: 1  selector:    matchLabels:      app: ten-agent-build  template:    metadata:      labels:        app: ten-agent-build    spec:      containers:          - env:            - name: LOG_PATH              value: /tmp/ten_agent            - name: LOG_STDOUT              value: "true"            - name: GRAPH_DESIGNER_SERVER_PORT              value: "49483"            - name: SERVER_PORT              value: "8080"            - name: WORKERS_MAX              value: "100"            - name: WORKER_QUIT_TIMEOUT_SECONDES              value: "60"            - name: AGORA_APP_ID              value: {{AGORA_APP_ID}} # 替换你的 agora app id            - name: AGORA_APP_CERTIFICATE              value: {{AGORA_APP_CERTIFICATE}} # 替换你的 agora app certificate            - name: AWS_ACCESS_KEY_ID              value: {{AWS_ACCESS_KEY_ID}} # 替换你的 aws access key id            - name: AWS_SECRET_ACCESS_KEY              value: {{AWS_SECRET_ACCESS_KEY}} # 替换你的 aws secret access key                      image: xxxx.dkr.ecr.us-east-1.amazonaws.com/dev/ten_agent_build:latest # 替换你的镜像地址,部署agent          name: ten-agent-build          ports:            - containerPort: 8080          resources:            requests:                          cpu: "2"                        memory: "4Gi"            limits:                          cpu: "3"                       memory: "6Gi"

apiVersion: v1kind: Servicemetadata:  name: service-ten-agent-demo  namespace: ten-frameworkspec:  ports:    - port: 3000      targetPort: 3000  selector:    app: ten-agent-demo  type: LoadBalancer---apiVersion: v1kind: Servicemetadata:  name: ten-agent-build-service  # 这个名称将用于服务发现  namespace: ten-framework   # 你的命名空间名称spec:  selector:    app: ten-agent-build        # 要匹配 ten-agent-build 的标签  ports:    - protocol: TCP      port: 8080               # Service 端口      targetPort: 8080         # 容器端口
---apiVersion: networking.k8s.io/v1kind: Ingressmetadata:  namespace: ten-framework  name: ingress-ten-agent-demo  annotations:    alb.ingress.kubernetes.io/scheme: internet-facing    alb.ingress.kubernetes.io/target-type: ip
spec:  ingressClassName: alb  rules:    - http:        paths:        - path: /          pathType: Prefix          backend:            service:              name: service-ten-agent-demo              port:                number: 3000