> ## Documentation Index
> Fetch the complete documentation index at: https://docs.getnetra.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Claude
> Trace Anthropic Claude API calls with Netra auto-instrumentation. Monitor prompts, completions, token usage, and response latency automatically.
The Netra SDK automatically instruments Anthropic Claude API calls, capturing prompts, completions, token usage, and performance metrics through OpenTelemetry tracing.
# Installation
Install the Netra SDK and the Anthropic client library:
```bash Python theme={null}
pip install netra-sdk anthropic
```
```bash TypeScript theme={null}
npm install netra-sdk @anthropic-ai/sdk
```
# Usage
Initialize the Netra SDK with your API key to automatically trace all Anthropic Claude API calls.
## Basic Setup
```python Python theme={null}
from netra import Netra
import anthropic
import os
# Initialize Netra with your API key
Netra.init(headers=f"x-api-key={os.getenv('NETRA_API_KEY')}")
# Use Anthropic client as normal
client = anthropic.Anthropic(api_key=os.getenv("ANTHROPIC_API_KEY"))
message = client.messages.create(
model="claude-3-5-sonnet-20241022",
max_tokens=1024,
messages=[
{"role": "user", "content": "Hello, Claude"}
]
)
print(message.content)
```
```typescript TypeScript theme={null}
import { Netra } from "netra-sdk";
import Anthropic from "@anthropic-ai/sdk";
async function main() {
// Initialize Netra with your API key (must await)
await Netra.init({
headers: `x-api-key=${process.env.NETRA_API_KEY}`
});
// Use Anthropic client as normal
const client = new Anthropic({
apiKey: process.env.ANTHROPIC_API_KEY
});
const message = await client.messages.create({
model: "claude-3-5-sonnet-20241022",
max_tokens: 1024,
messages: [
{ role: "user", content: "Hello, Claude" }
]
});
console.log(message.content);
}
main();
```
## Streaming Responses
The SDK automatically traces streaming responses from Claude.
```python Python theme={null}
from netra import Netra
import anthropic
import os
Netra.init(headers=f"x-api-key={os.getenv('NETRA_API_KEY')}")
client = anthropic.Anthropic(api_key=os.getenv("ANTHROPIC_API_KEY"))
with client.messages.stream(
model="claude-3-5-sonnet-20241022",
max_tokens=1024,
messages=[{"role": "user", "content": "Tell me a story"}]
) as stream:
for text in stream.text_stream:
print(text, end="", flush=True)
```
```typescript TypeScript theme={null}
import { Netra } from "netra-sdk";
import Anthropic from "@anthropic-ai/sdk";
async function main() {
await Netra.init({
headers: `x-api-key=${process.env.NETRA_API_KEY}`
});
const client = new Anthropic({
apiKey: process.env.ANTHROPIC_API_KEY
});
const stream = await client.messages.create({
model: "claude-3-5-sonnet-20241022",
max_tokens: 1024,
messages: [{ role: "user", content: "Tell me a story" }],
stream: true
});
for await (const chunk of stream) {
if (chunk.type === 'content_block_delta') {
process.stdout.write(chunk.delta.text);
}
}
}
main();
```
## Session Tracking
Track user sessions and conversations across multiple Claude API calls.
```python Python theme={null}
from netra import Netra, ConversationType
import anthropic
import os
Netra.init(headers=f"x-api-key={os.getenv('NETRA_API_KEY')}")
# Set session and user context
Netra.set_session_id("session-123")
Netra.set_user_id("user-456")
client = anthropic.Anthropic(api_key=os.getenv("ANTHROPIC_API_KEY"))
# Track conversation
Netra.add_conversation(
content="What is machine learning?",
conversation_type=ConversationType.INPUT
)
response = client.messages.create(
model="claude-3-5-sonnet-20241022",
max_tokens=1024,
messages=[{"role": "user", "content": "What is machine learning?"}]
)
Netra.add_conversation(
content=response.content[0].text,
conversation_type=ConversationType.OUTPUT
)
```
```typescript TypeScript theme={null}
import { Netra } from "netra-sdk";
import Anthropic from "@anthropic-ai/sdk";
async function main() {
await Netra.init({
headers: `x-api-key=${process.env.NETRA_API_KEY}`
});
// Set session and user context
Netra.setSessionId("session-123");
Netra.setUserId("user-456");
const client = new Anthropic({
apiKey: process.env.ANTHROPIC_API_KEY
});
// API calls are automatically traced with session context
const message = await client.messages.create({
model: "claude-3-5-sonnet-20241022",
max_tokens: 1024,
messages: [
{ role: "user", content: "What is machine learning?" }
]
});
}
main();
```
## Custom Attributes
Add custom metadata to your Claude API traces for filtering and analysis.
```python Python theme={null}
from netra import Netra
import anthropic
import os
Netra.init(headers=f"x-api-key={os.getenv('NETRA_API_KEY')}")
# Set custom attributes
Netra.set_custom_attributes({
"environment": "production",
"feature": "chat-assistant",
"model_version": "v2"
})
client = anthropic.Anthropic(api_key=os.getenv("ANTHROPIC_API_KEY"))
message = client.messages.create(
model="claude-3-5-sonnet-20241022",
max_tokens=1024,
messages=[{"role": "user", "content": "Hello"}]
)
```
```typescript TypeScript theme={null}
import { Netra } from "netra-sdk";
import Anthropic from "@anthropic-ai/sdk";
async function main() {
await Netra.init({
headers: `x-api-key=${process.env.NETRA_API_KEY}`
});
// Set custom attributes
Netra.setCustomAttributes({
environment: "production",
feature: "chat-assistant",
modelVersion: "v2"
});
const client = new Anthropic({
apiKey: process.env.ANTHROPIC_API_KEY
});
const message = await client.messages.create({
model: "claude-3-5-sonnet-20241022",
max_tokens: 1024,
messages: [{ role: "user", content: "Hello" }]
});
}
main();
```
# Next Steps
* [Auto-instrumentation Guide](https://docs.getnetra.ai/tracing/auto-instrumentation) - Learn about automatic tracing capabilities
* [Session Tracking](https://docs.getnetra.ai/tracing/session) - Track user sessions and conversations
* [Analytics Dashboard](https://docs.getnetra.ai/Dashboard/Custom-dashboard) - Query and visualize your Claude API usage
* [Anthropic Claude Documentation](https://docs.anthropic.com/en/home) - Official Anthropic Claude API documentation