Skip to main content

Documentation Index

Fetch the complete documentation index at: https://docs.baserun.ai/llms.txt

Use this file to discover all available pages before exploring further.

A Tag object includes the tag’s key, and its value. You can use tags to add extra information to a trace or request. 
client.tag(key: str, value: str, metadata: Dict, tag_type: str) -> Tag:

​
Arguments

​
key
string
required
​
value
string/numeric/boolean/object/array
required
​
metadata
object
​
tag_type
string
The type of tag. Default tag types are tag, log, variable, and feedback.

​
Instructions

With a traced OpenAI client, after it is created: 
client.tag (key="project", value="customer support")

​
Adding tags to a completed trace or completion

After a trace or completion has completed, you may want to add extra tags based on feedback collected later. To do this, store the trace_id and, for completions, the completion_id. Use the tag, log, or feedback functions to add tags, specifying trace_id and completion_id as needed. 
from baserun import OpenAI, log, feedback

client = OpenAI(name="trace to be resumed")
completion = client.chat.completions.create(
    name="completion to be resumed",
    model="gpt-4o",
    messages=[{"role": "user", "content": "What are three activities to do in Paris?"}],
)

# Store these values
trace_id = client.trace_id
completion_id = completion.completion_id

# A few moments later...
log("Tagging resumed", trace_id=trace_id, completion_id=completion_id)
feedback("User satisfaction", 0.9, trace_id=trace_id, completion_id=completion_id)