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Description

With a suite observability tools, you can confidently evaluate, test and ship LLM apps across your development and production lifecycle. Log traces and spans. Define and compute evaluation metrics. Score LLM outputs. Compare performance between app versions. Record, sort, find, and understand every step that your LLM app makes to generate a result. You can manually annotate and compare LLM results in a table. Log traces in development and production. Run experiments using different prompts, and evaluate them against a test collection. You can choose and run preconfigured evaluation metrics, or create your own using our SDK library. Consult the built-in LLM judges to help you with complex issues such as hallucination detection, factuality and moderation. Opik LLM unit tests built on PyTest provide reliable performance baselines. Build comprehensive test suites for every deployment to evaluate your entire LLM pipe-line.

Description

Traceloop is an all-encompassing observability platform tailored for the monitoring, debugging, and quality assessment of outputs generated by Large Language Models (LLMs). It features real-time notifications for any unexpected variations in output quality and provides execution tracing for each request, allowing for gradual implementation of changes to models and prompts. Developers can effectively troubleshoot and re-execute production issues directly within their Integrated Development Environment (IDE), streamlining the debugging process. The platform is designed to integrate smoothly with the OpenLLMetry SDK and supports a variety of programming languages, including Python, JavaScript/TypeScript, Go, and Ruby. To evaluate LLM outputs comprehensively, Traceloop offers an extensive array of metrics that encompass semantic, syntactic, safety, and structural dimensions. These metrics include QA relevance, faithfulness, overall text quality, grammatical accuracy, redundancy detection, focus evaluation, text length, word count, and the identification of sensitive information such as Personally Identifiable Information (PII), secrets, and toxic content. Additionally, it provides capabilities for validation through regex, SQL, and JSON schema, as well as code validation, ensuring a robust framework for the assessment of model performance. With such a diverse toolkit, Traceloop enhances the reliability and effectiveness of LLM outputs significantly.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

LiteLLM Yes 
Azure OpenAI Service Yes 
DeepEval Yes 
Flowise Yes 
Go No 
Hugging Face Yes 
JavaScript No 
Kong AI Gateway Yes 
LangChain Yes 
LlamaIndex Yes 
Microsoft Azure No 
OpenAI Yes 
Pinecone Yes 
Pinecone Rerank v0 No 
Python No 
Ragas Yes 
Ruby No 
SQL No 
TypeScript No 
VoltAgent No 

Integrations

LiteLLM Yes 
Azure OpenAI Service No 
DeepEval No 
Flowise No 
Go Yes 
Hugging Face No 
JavaScript Yes 
Kong AI Gateway No 
LangChain No 
LlamaIndex No 
Microsoft Azure Yes 
OpenAI No 
Pinecone No 
Pinecone Rerank v0 Yes 
Python Yes 
Ragas No 
Ruby Yes 
SQL Yes 
TypeScript Yes 
VoltAgent Yes 

Pricing Details

$39 per month
Free Trial Yes 
Free Version Yes 

Pricing Details

$59 per month
Free Trial Yes 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

Comet

Founded

2017

Country

United States

Website

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

Vendor Details

Company Name

Traceloop

Founded

2022

Country

Israel

Website

www.traceloop.com

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