RankLLM

RankLLM

Castorini
RankLLM Vectara

Related Products

  • Gemini platform
    4.3 out of 5 stars 1,178 Ratings
    Visit Website for Gemini platform
  • QA Wolf
    4.8 out of 5 stars 284 Ratings
    Visit Website for QA Wolf
  • LTX
    4.4 out of 5 stars 182 Ratings
    Visit Website for LTX
  • SearchUnify
    4.5 out of 5 stars 150 Ratings
    Visit Website for SearchUnify
  • LM-Kit.NET
    4.8 out of 5 stars 29 Ratings
    Visit Website for LM-Kit.NET
  • AddSearch
    4.6 out of 5 stars 145 Ratings
    Visit Website for AddSearch
  • RallyFuel
    5.0 out of 5 stars 1 Rating
    Visit Website for RallyFuel
  • kama.ai
    4.8 out of 5 stars 9 Ratings
    Visit Website for kama.ai
  • LogicalDOC
    4.5 out of 5 stars 151 Ratings
    Visit Website for LogicalDOC
  • Buildium
    4.5 out of 5 stars 2,563 Ratings
    Visit Website for Buildium
RankLLM:

About

RankLLM is a Python toolkit for reproducible information retrieval research using rerankers, with a focus on listwise reranking. It offers a suite of rerankers, pointwise models like MonoT5, pairwise models like DuoT5, and listwise models compatible with vLLM, SGLang, or TensorRT-LLM. Additionally, it supports RankGPT and RankGemini variants, which are proprietary listwise rerankers. It includes modules for retrieval, reranking, evaluation, and response analysis, facilitating end-to-end workflows. RankLLM integrates with Pyserini for retrieval and provides integrated evaluation for multi-stage pipelines. It also includes a module for detailed analysis of input prompts and LLM responses, addressing reliability concerns with LLM APIs and non-deterministic behavior in Mixture-of-Experts (MoE) models. The toolkit supports various backends, including SGLang and TensorRT-LLM, and is compatible with a wide range of LLMs.
Vectara:

About

Vectara is LLM-powered search-as-a-service. The platform provides a complete ML search pipeline from extraction and indexing to retrieval, re-ranking and calibration. Every element of the platform is API-addressable. Developers can embed the most advanced NLP models for app and site search in minutes. Vectara automatically extracts text from PDF and Office to JSON, HTML, XML, CommonMark, and many more. Encode at scale with cutting edge zero-shot models using deep neural networks optimized for language understanding. Segment data into any number of indexes storing vector encodings optimized for low latency and high recall. Recall candidate results from millions of documents using cutting-edge, zero-shot neural network models. Increase the precision of retrieved results with cross-attentional neural networks to merge and reorder results. Zero in on the true likelihoods that the retrieved response represents a probable answer to the query.
RankLLM:

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported
Vectara:

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported
RankLLM:

Audience

Academic researchers and developers seeking a solution offering tools for implementing and evaluating listwise reranking with large language models
Vectara:

Audience

Companies interested in a powerful AI neural search solution for sites, documents, and apps
RankLLM:

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported
Vectara:

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported
RankLLM:

API

Offers API Supported
Vectara:

API

Offers API Not Supported
RankLLM:

Screenshots and Videos

Vectara:

Screenshots and Videos

RankLLM:

Pricing

Free
Free Version Supported
Free Trial Not Supported
Vectara:

Pricing

Free
Free Version Supported
Free Trial Not Supported
RankLLM:

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software
Vectara:

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software
RankLLM:

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported
Vectara:

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported
RankLLM:

Company Information

Castorini
Canada
github.com/castorini/rank_llm/
Vectara:

Company Information

Vectara
Founded: 2020
United States
vectara.com
RankLLM:

Alternatives

RankGPT

RankGPT

Weiwei Sun
Vectara:

Alternatives

RankLLM:
ColBERT

ColBERT

Future Data Systems
Vectara:
Semantee

Semantee

Semantee.AI
RankLLM:
Vectara:
RankLLM:
Vectara:
INTERGATOR

INTERGATOR

interface projects
RankLLM:
Vectara:
RankLLM:

Categories

Reranking Models Supported
Vectara:

Categories

Enterprise Search Supported
Neural Search Supported
Reranking Models Supported
Site Search Supported
RankLLM:

Integrations

Datavolo Not Supported
Gemini Supported
Gemini Enterprise Supported
IBM watsonx.data Not Supported
Langflow Not Supported
Llama Supported
Mistral AI Supported
Model Context Protocol (MCP) Not Supported
NVIDIA TensorRT Supported
OpenAI Supported
Python Supported
Qwen Supported
RankGPT Supported
Vectara:

Integrations

Datavolo Supported
Gemini Not Supported
Gemini Enterprise Not Supported
IBM watsonx.data Supported
Langflow Supported
Llama Not Supported
Mistral AI Not Supported
Model Context Protocol (MCP) Supported
NVIDIA TensorRT Not Supported
OpenAI Not Supported
Python Not Supported
Qwen Not Supported
RankGPT Not Supported
RankLLM:
Claim RankLLM and update features and information
Claim RankLLM and update features and information
Vectara:
Claim Vectara and update features and information
Claim Vectara and update features and information