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Description

FastReport Mono is compatible with Windows, Linux and macOS. With FastReport Mono, you can create application-independent .NET and Mono reports. FastReport Mono can also be used as a standalone reporting tool. - You can connect any database, use any table or create your own queries using SQL. - To request parameters before running the report, you can add one or more dialog form to the report. - You can use the built-in script to control the interaction between dialog form controls and perform complex data processing. - You can view the result in the preview window. You can also print the report or save it to one of many popular formats. FastReport Mono is written entirely in C#. It contains no managed code. It is compatible with Mono Framework 4.0 or higher. Full source code is available. FastReport Mono can be customized to meet your needs. License policy and price are reasonable.

Description

RankLLM is a comprehensive Python toolkit designed to enhance reproducibility in information retrieval research, particularly focusing on listwise reranking techniques. This toolkit provides an extensive array of rerankers, including pointwise models such as MonoT5, pairwise models like DuoT5, and listwise models that work seamlessly with platforms like vLLM, SGLang, or TensorRT-LLM. Furthermore, it features specialized variants like RankGPT and RankGemini, which are proprietary listwise rerankers tailored for enhanced performance. The toolkit comprises essential modules for retrieval, reranking, evaluation, and response analysis, thereby enabling streamlined end-to-end workflows. RankLLM's integration with Pyserini allows for efficient retrieval processes and ensures integrated evaluation for complex multi-stage pipelines. Additionally, it offers a dedicated module for in-depth analysis of input prompts and LLM responses, which mitigates reliability issues associated with LLM APIs and the unpredictable nature of Mixture-of-Experts (MoE) models. Supporting a variety of backends, including SGLang and TensorRT-LLM, it ensures compatibility with an extensive range of LLMs, making it a versatile choice for researchers in the field. This flexibility allows researchers to experiment with different model configurations and methodologies, ultimately advancing the capabilities of information retrieval systems.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

ClickHouse
Elasticsearch
FastReport .NET
FastReport Desktop
Firebird
Gemini
Gemini Enterprise
IBM Db2
Llama
Mistral AI
MongoDB
MySQL
NVIDIA TensorRT
OpenAI
Python
Qwen
RankGPT
RavenDB
SQLite

Integrations

ClickHouse
Elasticsearch
FastReport .NET
FastReport Desktop
Firebird
Gemini
Gemini Enterprise
IBM Db2
Llama
Mistral AI
MongoDB
MySQL
NVIDIA TensorRT
OpenAI
Python
Qwen
RankGPT
RavenDB
SQLite

Pricing Details

$399.00/developer
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Fast Reports

Founded

1998

Country

United States

Website

www.fast-report.com/en/product/fast-report-mono/

Vendor Details

Company Name

Castorini

Country

Canada

Website

github.com/castorini/rank_llm/

Product Features

Reporting

Customizable Dashboard
Data Source Connectors
Drag & Drop
Drill Down
Email Reports
Financial Reports
Forecasting
Marketing Reports
OLAP
Report Export
Sales Reports
Scheduled / Automated Reports

Product Features

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