Pipeline class - Constructor

TypeScript

Python

The Pipeline class is the main entry point for passing observability data to Gentrace. This document focuses on the constructor. Learn more about using pipelines here.

Examples

typescript

typescript
import { Pipeline } from "@gentrace/core";
import { initPlugin } from "@gentrace/openai";
 
const openaiPlugin = await initPlugin({
  apiKey: process.env.OPENAI_KEY,
});
 
const pipeline = new Pipeline({
  slug: "my-pipeline",
  plugins: {
    openai: openaiPlugin
  }
});

python

python
import os
import gentrace
gentrace.init(
    api_key=os.getenv("GENTRACE_API_KEY"),
)
pipeline = gentrace.Pipeline(
    "my-pipeline",
    openai_config={
        "api_key": os.getenv("OPENAI_KEY"),
    },
)

Arguments

options: PipelineOptions

Types

🛠️ PipelineOptions

typescript

slug?

An optional slug for the pipeline.

logger?

An optional logger object with info and warn methods for logging messages and warnings.

typescript
import { Pipeline} from "@gentrace/core";
 
const pipeline = new Pipeline({
  slug: "my-pipeline",
  logger: {
    info: (message, context) => {
      console.log(message, context);
    },
    warn: (message, context) => {
      console.warn(message, context);
    }
  }  
});
 

plugins?

An optional object containing the plugins to be used within this pipeline.

typescript
import { Pipeline } from "@gentrace/core";
import { initPlugin } from "@gentrace/openai";
 
const openaiPlugin = await initPlugin({
  apiKey: process.env.OPENAI_KEY,
});
 
const pipeline = new Pipeline({
  slug: "my-pipeline",
  logger: {
    info: (message, context) => {
      console.log(message, context);
    },
    warn: (message, context) => {
      console.warn(message, context);
    }
  },
  plugins: {
    openai: openaiPlugin
  }
});

python

slug?

An optional slug for the pipeline.

openai_config?

The OpenAI configuration object, so the Pipeline can properly instantiate an OpenAI handle instance.

python
import os
import gentrace
gentrace.init(
    api_key=os.getenv("GENTRACE_API_KEY"),
)
pipeline = gentrace.Pipeline(
    "example-pipeline",
    # ✏️ Add your OpenAI configuration here
    openai_config={
        "api_key": os.getenv("OPENAI_KEY"),
    },
)
runner = pipeline.start()
# ✅ Defining the openai_config parameter allows you to access the OpenAI handle instance
openai = runner.get_openai()

pinecone_config?

The Pinecone configuration object, so the Pipeline can properly instantiate a Pinecone handle instance.

python
import os
import gentrace
gentrace.init(
    api_key=os.getenv("GENTRACE_API_KEY"),
)
pipeline = gentrace.Pipeline(
    "example-pipeline",
    # ✏️ Add your OpenAI configuration here
    pinecone_config={
        "api_key": os.getenv("PINECONE_API_KEY"),
        "environment: os.getenv("PINECONE_ENVIRONMENT"),
    },
)
runner = pipeline.start()
# ✅ Defining the openai_config parameter allows you to access the OpenAI handle instance
openai = runner.get_openai()