Prerequisite Please see here to get and set your API Key environment variable. Integration
Express Integration
Lytix provides an out of the box middleware that you can use to collect data from your NodeJS (Express) project.
To get started, simply add the middleware to your Express app.
import { LytixRequestWrapper } from "@lytix/client";
....
const app = express();
...
/**
* Pass the logger in as the 4th argument here
* @note The 4th argument is a boolean that can be set to true to collect metrics
* related to your server
*/
app.use((req, res, next) => {
return LytixRequestWrapper(req, res, next, false);
});
Note: If you enable request metrics, data will be published with the requestDuration metric name
Manual Integration
You can always wrap your entrypoint to get access to all of Lytix log tracing features (for example if you are running a cron job and have a main entrypoint)
import { LLogger } from "@lytix/client";
const logger = new LLogger("mainEntrypoint");
const main = async () => {
logger.info(`Log from the main process`);
await someBackgroundProcess();
};
/**
* All we need to do is wrap our entrypoint and everything will
* be accessable
*/
logger.runInAsyncContext(main);
Error Capturing
Error Class
You can now just replace all your throw new Error calls with throw new LError. For example:
...
app.get("/test", async (req, res) => {
const logger = new LLogger('testRoute');
/**
* Lets pretend an error happend
*/
try {
logger.info("Some process is starting");
throw new LError("An unexpeted error", { env: "prod" });
} catch (err) {
logger.error("crazy unexpeted error with this user: 123", err);
res.sendStatus(500);
return;
}
/**
* Magically if we ended here, we'd reply with a 200
*/
res.send("Hello World");
});
...
Error Increment
You can also send an error along with related logs without throwing an error by using the increment method.
import { LErrorIncrement, LLogger } from "@lytix/client";
/**
* An example background process
*/
const backgroundProcess = async () => {
const logger = new LLogger("backgroundProcessExample", { userId: "123" });
try {
logger.info("Background process started for user!");
throw new Error("Unexpected error!");
} catch (err) {
/**
* Just increment to get the logs as well as the error
*/
logger.error(`Unexpected error happened`, err);
LErrorIncrement("Unexpected error");
}
};
Examples
To see all examples please check the Github repo here
Lytix supports automatically collecting the input and output of LLM models. To do this you can use the following
import { MetricCollector } from "@lytix/client";
await MetricCollector.captureModelIO({
modelName: "testModelName",
modelInput: "Some user input",
modelOutput: "Some model output",
metricMetadata: {
/**
* Optional extra data
*/
env: "prod",
}
);
LLM Model Trace Collection
Lytix also supports capturing trace information (e.g. duration) for the LLM model. To do this you can use the following
import { MetricCollector } from "@lytix/client";
const response = await MetricCollector.captureModelTrace({
modelName: "testModelName",
modelInput: "Some user input",
generateModelOutput: async () => {
const openai = new OpenAI();
...
/**
* This callback is expecting the model output to be returned
*/
return response;
}
});
Manual Metric Collection
You always have the option to manually push metrics to the Lytix platform with custom names and metadata.
The following example pushes a metric to the Lytix platform with the name testMetic and the value 1 along with the env: prod metadata.
import { MetricCollector } from "@lytix/client";
await MetricCollector.increment("testMetic", 1, { env: "prod" });
