LLM Observability with OpenObserve and OpenLIT
Get your OpenObserve Credentials
Basic
)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"
)
YOUR_OPENOBSERVE_HTTP_ENDPOINT
with the Ingestion HTTP Endpoint value you copied in Step 1.http://127.0.0.1:5080/api/default
YOUR_OPENOBSERVE_AUTH_HEADER
with the Ingestion Authorization key value you copied in Step 1.Authorization=Basic%20<Ingestion Authorization key>
Import the pre-built Dashboard
Dashboard
below.Dashboard
{
"version": 4,
"dashboardId": "7232616793020301352",
"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",
"tabs": [
{
"tabId": "default",
"name": "GenAI",
"panels": [
{
"id": "Panel_ID4678610",
"type": "metric",
"title": "Total Successful GenAI Requests",
"description": "",
"config": {
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"legends_position": null,
"decimals": 2,
"axis_border_show": false,
"legend_width": {
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},
"base_map": {
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},
"map_view": {
"zoom": 1,
"lat": 0,
"lng": 0
},
"map_symbol_style": {
"size": "by Value",
"size_by_value": {
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"max": 100
},
"size_fixed": 2
},
"drilldown": [],
"mark_line": [],
"connect_nulls": false,
"no_value_replacement": "",
"wrap_table_cells": false
},
"queryType": "sql",
"queries": [
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"vrlFunctionQuery": "",
"customQuery": false,
"fields": {
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"stream_type": "metrics",
"x": [],
"y": [
{
"label": "Value",
"alias": "y_axis_1",
"column": "value",
"color": "#121969",
"aggregationFunction": "count",
"isDerived": false
}
],
"z": [],
"breakdown": [],
"filter": [
{
"type": "list",
"values": [
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],
"column": "telemetry_sdk_name",
"operator": null,
"value": null
}
]
},
"config": {
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"layer_type": "scatter",
"weight_fixed": 1,
"limit": 0,
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}
}
],
"layout": {
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"y": 0,
"w": 12,
"h": 4,
"i": 1
},
"htmlContent": "",
"markdownContent": ""
},
{
"id": "Panel_ID6880210",
"type": "markdown",
"title": "-",
"description": "",
"config": {
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"axis_border_show": false,
"legend_width": {
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"base_map": {
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"map_view": {
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"map_symbol_style": {
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"size_fixed": 2
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"no_value_replacement": "",
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},
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{
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"fields": {
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"stream_type": "logs",
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}
],
"layout": {
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"w": 24,
"h": 8,
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},
"htmlContent": "",
"markdownContent": "---\n#### GenAI Observability\n\nThis dashboard displays the usage stats of LLMs, Vector Databases and GPUs, tracking OpenTelemetry Traces and Metrics sent using [OpenLIT](https://github.com/openlit/openlit).\n\n---"
},
{
"id": "Panel_ID3159310",
"type": "metric",
"title": "Total Successful VectorDB Requests",
"description": "",
"config": {
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"legends_position": null,
"decimals": 2,
"axis_border_show": false,
"legend_width": {
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"map_view": {
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"map_symbol_style": {
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"max": 100
},
"size_fixed": 2
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"drilldown": [],
"mark_line": [],
"connect_nulls": false,
"no_value_replacement": "",
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},
"queryType": "sql",
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"fields": {
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"alias": "y_axis_1",
"column": "value",
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"aggregationFunction": "count",
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"z": [],
"breakdown": [],
"filter": [
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"column": "telemetry_sdk_name",
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"config": {
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"layer_type": "scatter",
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],
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"htmlContent": "",
"markdownContent": ""
},
{
"id": "Panel_ID3087510",
"type": "metric",
"title": "Total Usage Cost",
"description": "",
"config": {
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"h": 4,
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"htmlContent": "",
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},
{
"id": "Panel_ID6066010",
"type": "metric",
"title": "Avg Usage Cost",
"description": "",
"config": {
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"connect_nulls": false,
"no_value_replacement": "",
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"queryType": "sql",
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"vrlFunctionQuery": "",
"customQuery": false,
"fields": {
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{
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{
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