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What is Opik?

Utilizing a comprehensive set of observability tools enables you to thoroughly assess, test, and deploy LLM applications throughout both development and production phases. You can efficiently log traces and spans, while also defining and computing evaluation metrics to gauge performance. Scoring LLM outputs and comparing the efficiencies of different app versions becomes a seamless process. Furthermore, you have the capability to document, categorize, locate, and understand each action your LLM application undertakes to produce a result. For deeper analysis, you can manually annotate and juxtapose LLM results within a table. Both development and production logging are essential, and you can conduct experiments using various prompts, measuring them against a curated test collection. The flexibility to select and implement preconfigured evaluation metrics, or even develop custom ones through our SDK library, is another significant advantage. In addition, the built-in LLM judges are invaluable for addressing intricate challenges like hallucination detection, factual accuracy, and content moderation. The Opik LLM unit tests, designed with PyTest, ensure that you maintain robust performance baselines. In essence, building extensive test suites for each deployment allows for a thorough evaluation of your entire LLM pipeline, fostering continuous improvement and reliability. This level of scrutiny ultimately enhances the overall quality and trustworthiness of your LLM applications.

What is LangSmith?

In software development, unforeseen results frequently arise, and having complete visibility into the entire call sequence allows developers to accurately identify the sources of errors and anomalies in real-time. By leveraging unit testing, software engineering plays a crucial role in delivering efficient solutions that are ready for production. Tailored specifically for large language model (LLM) applications, LangSmith provides similar functionalities, allowing users to swiftly create test datasets, run their applications, and assess the outcomes without leaving the platform. This tool is designed to deliver vital observability for critical applications with minimal coding requirements. LangSmith aims to empower developers by simplifying the complexities associated with LLMs, and our mission extends beyond merely providing tools; we strive to foster dependable best practices for developers. As you build and deploy LLM applications, you can rely on comprehensive usage statistics that encompass feedback collection, trace filtering, performance measurement, dataset curation, chain efficiency comparisons, AI-assisted evaluations, and adherence to industry-leading practices, all aimed at refining your development workflow. This all-encompassing strategy ensures that developers are fully prepared to tackle the challenges presented by LLM integrations while continuously improving their processes. With LangSmith, you can enhance your development experience and achieve greater success in your projects.

Media

Media

Integrations Supported

LangChain
Azure OpenAI Service
Claude Duet
Claude for Legal
DeepEval
Flowise
Hugging Face
Kong AI Gateway
LiteLLM
LlamaIndex
OpenAI
OpenAI o1
Predibase

Integrations Supported

LangChain
Noma
Overmind
Reflexio
TierZero
Voker
dcode
evalship

API Availability

Has API

API Availability

Pricing Information

$39 per month
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Comet

Date Founded

2017

Company Location

United States

Company Website

www.comet.com/site/products/opik/

Company Facts

Organization Name

LangChain

Company Location

United States

Company Website

www.langchain.com/langsmith

Categories and Features

LLM Evaluation

Not specified

Categories and Features

AI Development

Not specified

Context Engineering

Not specified

Debugging

Not specified

Software Testing

Not specified

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