Application List¶

In the Application List, you can view the application information created under the integration of various application frameworks.

Concepts¶

Create Application¶

Enter the Create Application page, which currently supports accessing Langfuse by default:

1. Define the application name and application ID;

2. The system automatically generates configuration parameters;

3. A Client Token is generated by default, which you can replace as needed;

4. Select the access configuration;

5. Click "Create".

After successful creation, you can go to the "Application List" page to view it.

Access Configuration¶

Generally, three types are supported here:

Access Python

Access JS/TS

Access Other Models/Frameworks

Access Python¶

1. Install Dependencies:

pip install langfuse

2. Initialize the Client:

LANGFUSE_PUBLIC_KEY="app_id"
LANGFUSE_SECRET_KEY="llm_bb0f30d.....66eec"
LANGFUSE_HOST="https://llm-openway.guance.com"

from langfuse import Langfuse
langfuse = Langfuse()

from langfuse import Langfuse
langfuse = Langfuse(
  public_key="app_id",
  secret_key="llm_bb0f30d.....66eec",
  host="https://llm-openway.guance.com"
)

3. Verify Connection:

You can use langfuse.auth_check() to verify if the access is successful. It is not recommended to use it in production as it increases the application's latency.

from langfuse import Langfuse
# Initialize (via parameter construction)
langfuse = Langfuse(
  public_key="app_id",
  secret_key="llm_bb0f30d.....66eec",
  host="https://llm-openway.guance.com"
)
# Verify connection, this is a synchronous call, not recommended for production, this method is only for verifying configuration
if langfuse.auth_check():
  print("Langfuse client is authenticated and ready!")

If the access fails, you may encounter the following error:

langfuse.api.resources.commons.errors.unauthorized_error.UnauthorizedError: status_code: 401, body: {}

This error usually indicates that the App ID or Client Token is incorrect, please check your parameter configuration.

For more details and end-to-end examples, refer to Python.

Access JS/TS¶

1. Install Dependencies:

npm install @langfuse/tracing @langfuse/otel @opentelemetry/sdk-node

Click to view more package information.

2. Register Credentials

Set the following environment variables in your application environment. Ensure that your project root directory has a .env file and a package like dotenv to load the variables.

LANGFUSE_SECRET_KEY="llm_122f6b85d0c7454fa0f9*****d360"
LANGFUSE_PUBLIC_KEY="pk-lf-..."
LANGFUSE_BASE_URL="http://testing-openway.dataflux.cn",

**3. Initialize OpenTelemetry"

The tracing of Langfuse SDK is built on OpenTelemetry, so you need to set up the OpenTelemetry SDK. LangfuseSpanProcessor is the key component for sending traces to Langfuse.

import { NodeSDK } from "@opentelemetry/sdk-node";
import { LangfuseSpanProcessor } from "@langfuse/otel";
const sdk = new NodeSDK({
  spanProcessors: [new LangfuseSpanProcessor()],
});
sdk.start();

Click to view Ollama Access Example.

For more details and end-to-end examples, refer to JS/TS.

Access Others¶

If you need to integrate with other models/frameworks, such as DeepSeek, Ollama, LangChain, Dify, etc., refer to Langfuse Official Documentation for Configuration.

Application List¶

In the Application List, you can view the application name, call count, error rate, total token count, P50/P75 duration, and other information.

You can manage the list through the following operations:

• Search and locate by application name;

• Filter by time range using the Time Widget;

• Edit/Delete applications;

• Click on a single application to directly jump to the Explorer page with that application as the query condition.

Further Reading¶