Langtrace AI Howto
Langtrace AI is an open-source observability tool that collects and analyzes traces and metrics to help monitor, evaluate, and improve LLM applications.
View MoreHow to Use Langtrace AI
Sign up for Langtrace: Go to https://langtrace.ai/signup to create an account and get an API key
Install the Langtrace SDK: Install the Langtrace SDK for your programming language (Python or TypeScript) using pip or npm
Initialize Langtrace in your code: Import and initialize Langtrace at the beginning of your script using: from langtrace_python_sdk import langtrace; langtrace.init(api_key='<YOUR_API_KEY>')
Integrate with your LLM application: Langtrace will automatically trace LLM, VectorDB and framework requests once initialized properly
View traces in the dashboard: Log into the Langtrace web dashboard to view and analyze the automatically generated traces and metrics for your LLM application
Annotate and evaluate: Use the dashboard to manually annotate traces, create golden datasets, and run automated evaluations on your LLM outputs
Use the prompt playground: Compare different prompts and models using the built-in prompt playground feature
Monitor metrics: Track cost, latency, and other key metrics at the project, model, and user levels using the metrics dashboard
Establish feedback loops: Use the insights gained to continuously improve your LLM application's performance and accuracy
Langtrace AI FAQs
Langtrace AI is an open-source observability tool that collects and analyzes traces and metrics to help monitor, evaluate, and improve LLM (Large Language Model) applications. It provides end-to-end visibility into ML pipelines, supports popular LLMs and frameworks, and offers features like tracing, annotations, evaluations, and a playground for comparing prompts.
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