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chore: import upstream snapshot with attribution
2026-07-13 13:25:44 +08:00

91 lines
2.4 KiB
ReStructuredText

distributed_headers
===================
.. autofunction:: opik.decorator.context_manager.distributed_headers
Examples
--------
Basic usage in a server endpoint
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. code-block:: python
from opik.decorator.context_manager import distributed_headers
from fastapi import FastAPI, Request
app = FastAPI()
@app.post("/generate_response")
def generate_llm_response(request: Request) -> str:
# Extract distributed headers from the incoming request
headers = {
"opik_trace_id": request.headers.get("opik_trace_id"),
"opik_parent_span_id": request.headers.get("opik_parent_span_id"),
}
# Use the context manager to handle distributed headers
with distributed_headers(headers):
result = my_llm_application()
return result
With flush enabled
~~~~~~~~~~~~~~~~~~
.. code-block:: python
from opik.decorator.context_manager import distributed_headers
def process_request(headers_dict):
# Flush data immediately after the root span is processed
with distributed_headers(headers_dict, flush=True):
# Your processing logic here
pass
Using with the track decorator
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. code-block:: python
from opik import track
from opik.decorator.context_manager import distributed_headers
from flask import Flask, request
app = Flask(__name__)
@track()
def my_llm_function(prompt: str) -> str:
# Your LLM logic here
return "response"
@app.route("/api/generate", methods=["POST"])
def api_endpoint():
# Extract headers from the request
headers = {
"opik_trace_id": request.headers.get("opik_trace_id"),
"opik_parent_span_id": request.headers.get("opik_parent_span_id"),
}
# Create distributed trace context
with distributed_headers(headers):
result = my_llm_function(prompt=request.json.get("prompt"))
return {"result": result}
Error handling
~~~~~~~~~~~~~~
.. code-block:: python
from opik.decorator.context_manager import distributed_headers
try:
with distributed_headers(incoming_headers):
# Code that might fail
result = risky_operation()
except Exception as e:
# The context manager automatically logs the error
# and attaches error information to the root span
print(f"Operation failed: {e}")