Hugging Face Transformers

pip install netra-sdk transformers torch

from netra import Netra
from transformers import pipeline
import os

# Initialize Netra with Hugging Face instrumentation
Netra.init(
    app_name="my-ai-app",
    headers=f"x-api-key={os.environ.get('NETRA_API_KEY')}",
    trace_content=True
)

# Use Transformers pipeline - all calls are automatically traced
generator = pipeline("text-generation", model="gpt2")

response = generator("What is observability?", max_length=50)
print(response[0]['generated_text'])

from transformers import TextStreamer

generator = pipeline(
    "text-generation",
    model="gpt2",
    streamer=TextStreamer(skip_prompt=True)
)

# Streaming output is automatically captured
generator("Tell me a story", max_length=100)

# Text Classification
classifier = pipeline("sentiment-analysis")
result = classifier("I love this product!")

# Summarization
summarizer = pipeline("summarization")
summary = summarizer("Long text to summarize...", max_length=50)

# Question Answering
qa = pipeline("question-answering")
answer = qa({
    "question": "What is AI?",
    "context": "Artificial Intelligence is..."
})

from netra import Netra
from netra.instrumentation.instruments import InstrumentSet

# Only enable Hugging Face instrumentation
Netra.init(
    headers=f"x-api-key={os.environ.get('NETRA_API_KEY')}",
    instruments={InstrumentSet.TRANSFORMERS}
)

# Or block specific instrumentations
Netra.init(
    headers=f"x-api-key={os.environ.get('NETRA_API_KEY')}",
    block_instruments={InstrumentSet.HTTPX}
)