jeecgboot/jimureport

Overview

JimuReport is a Java-based reporting and BI suite that runs inside a Spring Boot application. It combines three modules: JimuReport for traditional tabular and print-oriented reports, JimuBI for big screens and dashboards, and JimuChatBI for conversational data analysis driven by a built-in AI assistant. The report designer works in the browser with an Excel-like grid, so teams can build grouped, cross-tab, master-detail, and multi-sheet reports without installing a desktop client.

The project targets enterprise reporting scenarios: complex multi-header tables, conditional queries, data entry back to the database, invoice or certificate printing, and around 30 data sources including MySQL, Oracle, PostgreSQL, ClickHouse, Doris, Elasticsearch, and domestic databases such as Dameng and Kingbase. AI features are optional and route through any OpenAI-compatible chat completion API; the assistant can generate reports, big screens, dashboards, and ChatBI views from a natural-language prompt or a screenshot.

Getting started

JimuReport is consumed as a Maven dependency rather than a standalone binary. Prerequisites for the example application are JDK 17+, MySQL 5.7+, and optionally Redis; the SQL initialization script is included. Detailed configuration steps reference the official quick integration guide quick integration guide.

1. Add the starter for your Spring Boot line to the project’s pom.xml. For Spring Boot 3 this is jimureport-spring-boot3-starter version 2.5.6.1; Spring Boot 4 uses jimureport-spring-boot4-starter; Spring Boot 2 uses jimureport-spring-boot-starter but does not support the AI assistant dependency examples.
2. Add jimubi-spring-boot3-starter (or the matching jimubi starter) at the same version to enable big screens and dashboards JimuBI dependencies.
3. Add jimuchatbi-spring-boot3-starter version 1.2.0 for conversational BI ChatBI dependencies.
4. Initialize the database with the provided MySQL script and adjust application-dev.yml deployment requirements.

To enable the AI assistant, add the following under jeecg.jmreport.ai in application.yml, using your own credentials:

jeecg:
  jmreport:
    ai:
      base-url: https://api.deepseek.com
      api-key: sk-xxxxxxxxxxxxxxxxxxxx
      model: deepseek-v4-pro
      temperature: 0
      autoTableEnabled: false

The AI panel then appears in the report designer. The example project builds one with Maven dependencies and the default admin account receives a random password printed to the startup log unless JIMU_ADMIN_PASSWORD or spring.security.user.password is set example notes. A hosted online demo is also available for trying the designer before integrating it.

Constraints and licensing

• The Spring Boot 4 starter requires JDK 17+; Spring Boot 2 is limited to JDK 8+ and lacks the AI assistant integration notes.
• Since version 2.5.4, JimuReport, JimuBI, and JimuChatBI must be upgraded together because their signature and encryption schemes are linked; version mismatches cause signature verification and data-source connection failures version compatibility.
• AI functionality requires an external OpenAI-compatible endpoint and a customer-supplied API key; the autoTableEnabled switch allows the AI to execute DDL/DML against a configured data source and should stay disabled in production AI configuration.
• The repository states a GPL-3.0 license with supplementary terms; keeping the “Powered by JimuReport” mark and brand links generally requires a commercial license license section.
• The README also advertises a Windows PowerShell irm ... | iex bootstrap and a macOS/Linux curl ... | bash script to install Claude Code and the project’s skills. Those scripts live on a third-party domain and their contents are not described in the repository; inspect them before running.

HotRepo's take

On 2026-11-04 the repository recorded 8,563 stars and 1,893 forks, with a third-place daily gain of 3 stars on the Java daily list, where it reached 16th. That is the only snapshot available, so it supports a single-day observation rather than a trend. The recent README centers on AI generation and the ChatBI product, while the dependency structure shows a mature Spring Boot reporting stack. The project is a reasonable fit for Java teams that need an embeddable report designer plus optional AI-assisted authoring; small standalone use cases will still need a host application and database.