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.
Installation
Install both the Netra SDK and Google Generative AI SDK:
pip install netra-sdk google-generativeai
Usage
Initialize the Netra SDK with Gemini instrumentation enabled. The SDK automatically traces all Gemini API calls once initialized.
from netra import Netra
import google.generativeai as genai
import os
# Initialize Netra with Gemini instrumentation
Netra.init(
app_name="my-ai-app",
headers=f"x-api-key={os.environ.get('NETRA_API_KEY')}",
trace_content=True
)
# Use Gemini client as usual - all calls are automatically traced
genai.configure(api_key=os.environ.get("GOOGLE_API_KEY"))
model = genai.GenerativeModel('gemini-pro')
response = model.generate_content("What is observability?")
print(response.text)
Streaming Responses
The SDK automatically handles streaming responses and captures the complete output:
model = genai.GenerativeModel('gemini-pro')
response = model.generate_content("Tell me a story", stream=True)
for chunk in response:
print(chunk.text, end="")
Chat Sessions
Chat operations are also automatically instrumented:
model = genai.GenerativeModel('gemini-pro')
chat = model.start_chat(history=[
{"role": "user", "parts": ["Hello"]},
{"role": "model", "parts": ["Great to meet you. What would you like to know?"]},
])
response = chat.send_message("I have 2 dogs in my house.")
print(response.text)
Selective Instrumentation
Control which integrations are enabled using the instruments or blockInstruments configuration:
from netra import Netra
from netra.instrumentation.instruments import InstrumentSet
# Only enable Gemini instrumentation
Netra.init(
headers=f"x-api-key={os.environ.get('NETRA_API_KEY')}",
instruments={InstrumentSet.GOOGLE_GENERATIVEAI}
)
# Or block specific instrumentations
Netra.init(
headers=f"x-api-key={os.environ.get('NETRA_API_KEY')}",
block_instruments={InstrumentSet.HTTPX}
)
Next Steps
