Langtrace AI

WebsiteLarge Language Models (LLMs)AI Analytics Assistant
Langtrace AI is an open-source observability tool that collects and analyzes traces and metrics to help monitor, evaluate, and improve LLM applications.
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Langtrace AI

Product Information

Updated:09/09/2024

What is Langtrace AI

Langtrace AI is a comprehensive tool designed for monitoring, evaluating, and optimizing large language models (LLMs). It provides real-time insights and detailed performance metrics to enhance AI applications. Built on open telemetry standards, Langtrace offers end-to-end observability for LLM applications, supporting popular LLMs, frameworks, and vector databases. The tool can be self-hosted and integrates seamlessly with existing observability stacks, ensuring no vendor lock-in.

Key Features of Langtrace AI

Langtrace AI is an open-source observability tool for monitoring, evaluating, and optimizing large language model (LLM) applications. It provides end-to-end visibility through real-time tracing, performance metrics, and automated evaluations. Langtrace offers seamless integration with popular LLMs and frameworks, supports self-hosting, and adheres to OpenTelemetry standards for flexibility and security.
End-to-end Observability: Gain visibility into the entire ML pipeline with traces and logs across frameworks, vector databases, and LLM requests.
Automated Evaluations: Run LLM-based automated evaluations to track performance over time and continuously improve AI applications.
Prompt Playground: Compare prompt performance across different models to optimize LLM interactions.
Annotation and Dataset Creation: Annotate LLM interactions and create golden datasets for testing and enhancing AI applications.
Comprehensive Metrics: Track costs, latency, and performance at project, model, and user levels.

Use Cases of Langtrace AI

LLM Application Development: Monitor and optimize performance of AI applications during development and production stages.
AI Model Evaluation: Conduct automated evaluations to assess and compare different LLM models for specific tasks.
RAG System Optimization: Improve retrieval-augmented generation systems by analyzing end-to-end performance and identifying bottlenecks.
AI Cost Management: Track and manage costs associated with LLM usage across projects and users.

Pros

Open-source and self-hostable for flexibility and control
Comprehensive observability across the entire LLM pipeline
Integration with popular LLMs, frameworks, and vector databases
Advanced security with SOC 2 Type II certification

Cons

May require technical expertise to set up and fully utilize all features
As a relatively new tool, it may have a smaller community compared to more established solutions

How 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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Analytics of Langtrace AI Website

Langtrace AI Traffic & Rankings
12.7K
Monthly Visits
#2022820
Global Rank
-
Category Rank
Traffic Trends: Jun 2024-Aug 2024
Langtrace AI User Insights
00:01:09
Avg. Visit DTabsNavuration
2.27
Pages Per Visit
54.04%
User Bounce Rate
Top Regions of Langtrace AI

  1. US: 37.23%

  2. VN: 23.91%

  3. FR: 11.21%

  4. GB: 7.84%

  5. IN: 7.48%

  6. Others: 12.33%

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