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Connections
OpenObserve
LLM Observability with OpenObserve and OpenLIT
To directly send OpenTelemetry metrics and traces generated by OpenLIT from your AI Application to OpenObserve, Follow the below steps.
1
Get your OpenObserve Credentials
- Log into your OpenObserve instance.
- Click Ingestion in the side navigation and select Traces (OpenTelemetry) option.
- Under the OTLP HTTP section, Copy the Ingestion HTTP Endpoint and the Ingestion Authorization key (After
Basic)
2
Add the following two lines to your application code:
import openlit
openlit.init(
otlp_endpoint="YOUR_OPENOBSERVE_HTTP_ENDPOINT",
otlp_headers="YOUR_OPENOBSERVE_AUTH_HEADER"
)
Replace:
YOUR_OPENOBSERVE_HTTP_ENDPOINTwith the Ingestion HTTP Endpoint value you copied in Step 1.
- Example -
http://127.0.0.1:5080/api/default
YOUR_OPENOBSERVE_AUTH_HEADERwith the Ingestion Authorization key value you copied in Step 1.
- Example -
Authorization=Basic%20<Ingestion Authorization key>
Refer to the OpenLIT Python SDK repository for more advanced configurations and use cases.
3
Import the pre-built Dashboard
- Log into your OpenObserve Instance.
- Click Dashboards in the side navgivation menu.
- Click Import on the top right corner.
- Copy the dashboard JSON provided in the accordion named
Dashboardbelow. - Paste the dashboard JSON text directly under the Import Dashboard from JSON section
- Click Import.
- Save the dashboard.
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"title": "GenAI Observability",
"description": "This dashboard tracks the performance of LLM and VectorDB, recording metrics like latency, tokens used, and cost. It also logs input and output data, including request IDs, timestamps, user IDs, and model versions. This helps identify how well the systems are working and where improvements can be made.",
"role": "",
"owner": "",
"created": "2024-08-23T05:46:38.299Z",
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