AWS Bedrock

pip install netra-sdk boto3

npm install netra-sdk @aws-sdk/client-bedrock-runtime

from netra import Netra
import boto3
import os

# Initialize Netra SDK
Netra.init(
    headers=f"x-api-key={os.environ.get('NETRA_API_KEY')}",
    app_name="bedrock-app"
)

# Create Bedrock client - automatically instrumented
bedrock = boto3.client(
    service_name='bedrock-runtime',
    region_name='us-east-1'
)

# Make Bedrock calls - automatically traced
response = bedrock.invoke_model(
    modelId='anthropic.claude-v2',
    body='{"prompt": "Hello, world!"}'
)

import { Netra } from "netra-sdk";
import { BedrockRuntimeClient, InvokeModelCommand } from "@aws-sdk/client-bedrock-runtime";

// Initialize Netra SDK (must await)
await Netra.init({
    headers: `x-api-key=${process.env.NETRA_API_KEY}`,
    appName: "bedrock-app"
});

// Create Bedrock client - automatically instrumented
const client = new BedrockRuntimeClient({
    region: "us-east-1"
});

// Make Bedrock calls - automatically traced
const command = new InvokeModelCommand({
    modelId: "anthropic.claude-v2",
    body: JSON.stringify({ prompt: "Hello, world!" })
});

const response = await client.send(command);

from netra import Netra
import boto3
import json
import os

Netra.init(headers=f"x-api-key={os.environ.get('NETRA_API_KEY')}")

bedrock = boto3.client('bedrock-runtime', region_name='us-east-1')

# Text generation
response = bedrock.invoke_model(
    modelId='anthropic.claude-v2',
    body=json.dumps({
        "prompt": "Explain AI observability",
        "max_tokens_to_sample": 300
    })
)

import { Netra } from "netra-sdk";
import { BedrockRuntimeClient, InvokeModelCommand } from "@aws-sdk/client-bedrock-runtime";

await Netra.init({
    headers: `x-api-key=${process.env.NETRA_API_KEY}`
});

const client = new BedrockRuntimeClient({ region: "us-east-1" });

const command = new InvokeModelCommand({
    modelId: "anthropic.claude-v2",
    body: JSON.stringify({
        prompt: "Explain AI observability",
        max_tokens_to_sample: 300
    })
});

await client.send(command);

from netra import Netra
import boto3
import json
import os

Netra.init(headers=f"x-api-key={os.environ.get('NETRA_API_KEY')}")

bedrock = boto3.client('bedrock-runtime', region_name='us-east-1')

response = bedrock.invoke_model_with_response_stream(
    modelId='anthropic.claude-v2',
    body=json.dumps({
        "prompt": "Write a story",
        "max_tokens_to_sample": 500
    })
)

# Stream automatically traced
for event in response['body']:
    chunk = json.loads(event['chunk']['bytes'])
    print(chunk.get('completion', ''))

import { Netra } from "netra-sdk";
import { BedrockRuntimeClient, InvokeModelWithResponseStreamCommand } from "@aws-sdk/client-bedrock-runtime";

await Netra.init({
    headers: `x-api-key=${process.env.NETRA_API_KEY}`
});

const client = new BedrockRuntimeClient({ region: "us-east-1" });

const command = new InvokeModelWithResponseStreamCommand({
    modelId: "anthropic.claude-v2",
    body: JSON.stringify({
        prompt: "Write a story",
        max_tokens_to_sample: 500
    })
});

const response = await client.send(command);

// Stream automatically traced
for await (const event of response.body) {
    console.log(event.chunk?.bytes);
}

from netra import Netra
import boto3
import json

Netra.init(api_key="your-api-key")
Netra.set_session_id("session-123")
Netra.set_user_id("user-456")

bedrock = boto3.client('bedrock-runtime', region_name='us-east-1')

# All calls automatically tagged with session context
response = bedrock.invoke_model(
    modelId='anthropic.claude-v2',
    body=json.dumps({"prompt": "Hello"})
)

import { Netra } from "netra-sdk";
import { BedrockRuntimeClient, InvokeModelCommand } from "@aws-sdk/client-bedrock-runtime";

await Netra.init({
    headers: `x-api-key=${process.env.NETRA_API_KEY}`
});

Netra.setSessionId("session-123");
Netra.setUserId("user-456");

const client = new BedrockRuntimeClient({ region: "us-east-1" });

// All calls automatically tagged with session context
const command = new InvokeModelCommand({
    modelId: "anthropic.claude-v2",
    body: JSON.stringify({ prompt: "Hello" })
});

await client.send(command);