Graphlit

Graphlit can accelerate your Generative AI app development by providing an API-first platform that offers intelligent text extraction, vector-based search, and RAG conversations, along with audio and video transcription support.

Langtrace integrates directly with Graphlit, providing comprehensive tracing and monitoring capabilities for your RAG (Retrieval-Augmented Generation) applications. Track everything from data ingestion to conversation completion with detailed performance metrics.

​

Prerequisites

Before you begin, ensure you have the following:

• An active account on the Graphlit Platform with access to the API Settings page.
• An API key from Langtrace. Sign up for Langtrace if you haven’t done so already.

​

Setup

1. Install the Graphlit client and Langtrace’s SDK and initialize the SDK in your code.

# Install the SDK
pip install langtrace-python-sdk graphlit-client

2. Setup environment variables:

export LANGTRACE_API_KEY=YOUR_LANGTRACE_API_KEY
export GRAPHLIT_ORGANIZATION_ID=YOUR_GRAPHLIT_ORGANIZATION_ID
export GRAPHLIT_ENVIRONMENT_ID=YOUR_GRAPHLIT_ENVIRONMENT_ID
export GRAPHLIT_JWT_SECRET=YOUR_GRAPHLIT_JWT_SECRET

​

Usage

Initialize Langtrace and Graphlit:

Ingest content and create a specification:

Create and interact with a conversation:

Run the complete RAG pipeline:

You can now view your traces on the Langtrace dashboard, including:

• Data ingestion metrics
• Specification creation details
• Conversation flow and completion times
• Error tracking and diagnostics

​

Additional Resources

• Langtrace Documentation
• Graphlit Documentation