Releases & Versioning
You can track the effect of changes to your LLM app on metrics in Langfuse. This allows you to:
- Run experiments (A/B tests) in production and measure the impact on costs, latencies and quality.
- Example: "What is the impact of switching to a new model?"
- Explain changes to metrics over time.
- Example: "Why did latency in this chain increase?"
Releases
A release tracks the overall version of your application. Commonly it is set to the semantic version or git commit hash of your application.
The SDKs look for a release in the following order:
- SDK initialization
- Environment variable
- Automatically set release identifiers on popular deployment platforms
Initialization
The Python SDK allows you to set the release when initializing the client:
from langfuse import Langfuse
# Set the release when initializing the client
langfuse = Langfuse(release="v2.1.24")The JS/TS SDK will look for a LANGFUSE_RELEASE environment variable. Use it to configure the release e.g. in your CI/CD pipeline.
LANGFUSE_RELEASE = "<release_tag>" # <- github sha or other identifierThe SDKs will look for a LANGFUSE_RELEASE environment variable. Use it to configure the release e.g. in your CI/CD pipeline.
LANGFUSE_RELEASE = "<release_tag>" # <- github sha or other identifierAutomatically on popular platforms
If no other release is set, the Langfuse SDKs default to a set of known release environment variables.
Supported platforms include: Vercel, Heroku, Netlify. See the full list of support environment variables for JS/TS and Python.
Versions
The version parameter can be added to all observation types (e.g., span, generation, event, and other observation types). Thereby, you can track the effect of a new version on the metrics of an object with a specific name using Langfuse analytics.
Set Version on all observations within a context:
from langfuse import observe, propagate_attributes
@observe()
def process_data():
# Propagate version to all child observations
with propagate_attributes(version="1.0"):
# All nested operations automatically inherit version
result = perform_processing()
return resultWhen creating observations directly:
from langfuse import get_client, propagate_attributes
langfuse = get_client()
with langfuse.start_as_current_observation(as_type="span", name="process-data") as span:
# Propagate version to all child observations
with propagate_attributes(version="1.0"):
# All observations created here automatically have version="1.0"
with span.start_as_current_observation(
as_type="generation",
name="guess-countries",
model="gpt-4o"
) as generation:
# This generation automatically has version="1.0"
passVersion on a specific observation:
from langfuse import get_client
langfuse = get_client()
with langfuse.start_as_current_observation(as_type="span", name="process-data", version="1.0") as span:
# This span has version="1.0"
passPropagating version to all observations within a context:
import { startActiveObservation, propagateAttributes } from "@langfuse/tracing";
await startActiveObservation("process-data", async (span) => {
// Propagate version to all child observations
await propagateAttributes(
{
version: "1.0",
},
async () => {
// All observations created here automatically have version="1.0"
const generation = startObservation(
"guess-countries",
{ model: "gpt-4" },
{ asType: "generation" }
);
// This generation automatically has version="1.0"
generation.end();
}
);
});Version on a specific observation:
import { startObservation } from "@langfuse/tracing";
const generation = startObservation(
"guess-countries",
{ model: "gpt-4" },
{ asType: "generation" }
);
generation.update({ version: "1.0" });
generation.end();from langfuse.callback import CallbackHandler
handler = CallbackHandler(version="1.0")import { CallbackHandler } from "langfuse-langchain";
const handler = new CallbackHandler({
version: "1.0",
});- Values must be strings ≤200 characters
- Call early in your trace to ensure all observations are covered. This way you make sure that all Metrics in Langfuse are accurate.
- Invalid values are dropped with a warning
Version parameter in Langfuse interface
