chore: update 0.8.0 version (#3004)

Author: chenliang15405

README.md

@@ -189,6 +189,36 @@ Then open [http://localhost:5670](http://localhost:5670).
 > bash install.sh --profile openai
 > ```
 
+### Install via PyPI
+
+Install DB-GPT from PyPI and start it with a single command — no source checkout required.
+
+> **Prerequisites:** Python **3.10+** and [uv](https://docs.astral.sh/uv/getting-started/installation/) (recommended) or pip.
+
+**1. Install**
+
+```bash
+# Recommended: use uv
+uv pip install dbgpt-app
+
+# Or with pip
+pip install dbgpt-app
+```
+
+The default installation includes the core framework (CLI, FastAPI, Agent), OpenAI-compatible LLM support, DashScope / Tongyi support, RAG document parsing, and ChromaDB vector store.
+
+**2. Start**
+
+```bash
+dbgpt start
+```
+
+On first run, an interactive setup wizard will guide you through choosing an LLM provider and entering your API key. Once complete, the web server starts automatically.
+
+**3. Open the Web UI**
+
+Visit [http://localhost:5670](http://localhost:5670) — you're all set! 🎉
+
 ### Advanced Installation
 
 ![Docker](https://img.shields.io/badge/docker-%230db7ed.svg?style=for-the-badge&logo=docker&logoColor=white)

README.zh.md

@@ -180,6 +180,36 @@ cd ~/.dbgpt/DB-GPT && uv run dbgpt start webserver --profile <profile>
 > bash install.sh --profile openai
 > ```
 
+### 通过 PyPI 安装
+
+从 PyPI 安装 DB-GPT，一条命令即可启动，无需克隆源码仓库。
+
+> **前置条件：** Python **3.10+**，推荐使用 [uv](https://docs.astral.sh/uv/getting-started/installation/) 包管理器，也支持 pip。
+
+**1. 安装**
+
+```bash
+# 推荐使用 uv
+uv pip install dbgpt-app
+
+# 或使用 pip
+pip install dbgpt-app
+```
+
+默认安装包含核心框架（CLI、FastAPI、Agent）、OpenAI 兼容 LLM 支持、DashScope / 通义支持、RAG 文档解析和 ChromaDB 向量存储。
+
+**2. 启动**
+
+```bash
+dbgpt start
+```
+
+首次运行时，交互式向导会引导你选择 LLM 提供商并输入 API Key，配置完成后服务自动启动。
+
+**3. 打开 Web 界面**
+
+访问 [http://localhost:5670](http://localhost:5670) — 开始使用！🎉
+
 ![Docker](https://img.shields.io/badge/docker-%230db7ed.svg?style=for-the-badge&logo=docker&logoColor=white)
 ![Linux](https://img.shields.io/badge/Linux-FCC624?style=for-the-badge&logo=linux&logoColor=black)
 ![macOS](https://img.shields.io/badge/mac%20os-000000?style=for-the-badge&logo=macos&logoColor=F0F0F0)

assets/schema/dbgpt.sql

@@ -567,6 +567,19 @@ CREATE TABLE `benchmark_summary` (
   PRIMARY KEY (`id`)
 ) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;
 
+-- share_links, Store conversation share link tokens
+CREATE TABLE `share_links` (
+  `id` int NOT NULL AUTO_INCREMENT COMMENT 'Primary key',
+  `token` varchar(64) NOT NULL COMMENT 'Unique random share token',
+  `conv_uid` varchar(255) NOT NULL COMMENT 'The conversation uid being shared',
+  `created_by` varchar(255) DEFAULT NULL COMMENT 'User who created the share link',
+  `gmt_created` TIMESTAMP DEFAULT CURRENT_TIMESTAMP COMMENT 'Creation time',
+  PRIMARY KEY (`id`),
+  UNIQUE KEY `uk_share_token` (`token`),
+  KEY `ix_share_links_token` (`token`),
+  KEY `ix_share_links_conv_uid` (`conv_uid`)
+) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci COMMENT='Conversation share link table';
+
 
 CREATE
 DATABASE IF NOT EXISTS EXAMPLE_1;

docs/docs/changelog/Released_V0.8.0.md

@@ -0,0 +1,163 @@
+# DB-GPT V0.8.0 — Paradigm Shift: AI + Data Driven Analytics Experience
+
+A paradigm shift from "conversational Q&A" to "task delivery" — from passive answering to autonomous analysis, exploring true Agentic productivity.
+
+## Introduction
+
+DB-GPT V0.8.0 introduces a self-driven AI Data Assistant that autonomously handles the entire analytics pipeline:
+
+🎯 Business Goal → 🧠 Task Decomposition → 🧩 Skill Invocation → 💻 Code Generation (SQL/Python) → 🛡️ Sandbox Execution → 📊 Chart Generation → 📝 Report Delivery
+
+You no longer need to know which table your data lives in, nor write Python scripts for intermediate data cleaning. Simply state your business objective, and the **DB-GPT AI Data Assistant** will take care of everything.
+
+### Key Highlights
+
+- 🌟 **Autonomous Data Analytics** — A brand-new autonomous data analytics experience, orchestrating AI-driven analysis through Skills
+- 🤖 **Agent Skills** — Support for Agent Skills, enabling more powerful and flexible agent capabilities
+- 📊 **Autonomous SQL Generation** — AI agents can now autonomously write SQL queries for data analysis
+- 💻 **Autonomous Code Execution** — AI agents can automatically generate and execute Python code for data analysis tasks
+- 🛡️ **Sandbox Environment** — A secure, isolated sandbox environment for executing untrusted code
+- 💬 **Conversation Sharing & Replay** — View not only the final polished HTML reports, but also replay the entire reasoning process
+- 🚀 **One-Click Setup Script** — A new streamlined installation script to get DB-GPT up and running faster than ever
+
+## Features
+
+### ✨ Agentic Data Analytics Engine
+
+The DB-GPT AI Data Assistant can now autonomously orchestrate an entire execution pipeline around your analysis goals, moving beyond the limitations of traditional single-turn conversations to deliver a brand-new autonomous data analytics experience:
+
+- **Multi-Source Data Integration**: Seamlessly connect to relational databases, CSV/Excel files, data warehouses, knowledge bases, documents, and more.
+- **Autonomous Reasoning & Exploration**: For complex problems, the AI Data Assistant automatically analyzes database schemas or data files and plans multi-step execution strategies.
+- **Execution Capabilities**: Autonomously generates and executes SQL / Python code.
+- **Out-of-the-Box Experience**: A newly designed Welcome Page with rich analysis examples, reducing the learning curve for new users to nearly zero.
+
+#### CSV/Excel Autonomous Data Analysis
+
+Upload local spreadsheet files with one click, and the AI automatically understands the data structure, autonomously performs data cleaning, multi-dimensional calculations, and chart visualization — making routine report processing easier than ever.
+
+<img src="/img/agentic_data/csv_data_analysis.jpg" width="720px" />
+
+#### Intelligent Database Insights & Analysis Reports
+
+Built on the new Agentic architecture, the engine autonomously performs data diagnostics, feature extraction, and multi-dimensional analysis, generating dedicated analysis reports with beautiful charts and deep insights — making data value crystal clear.
+
+<img src="/img/agentic_data/agentic_db_data.jpg" width="720px" />
+
+#### Deep Financial Report Analysis
+
+Purpose-built for financial scenarios, precisely extracting core metrics such as revenue and profit. Automatically performs year-over-year / quarter-over-quarter calculations and trend forecasting, generating professional financial health diagnostic reports with one click.
+
+<img src="/img/skill/financial_report_analysis_skill.jpg" width="720px" />
+
+#### Autonomous SQL Generation & Code Execution
+
+Powered by advanced large language models, the system not only accurately translates natural language into complex SQL queries, but also supports autonomous Python code execution in a secure sandbox — handling even the most demanding computational requirements.
+
+<img src="/img/agentic_data/agentic_sql_query.png" width="720px" />
+
+<img src="/img/agentic_data/agentic_gen_code.png" width="720px" />
+
+### 🤖 Agent Skill Ecosystem
+
+The LLM determines the intelligence baseline, but ecosystem extensibility determines the business ceiling. Different business scenarios require vastly different analysis approaches. V0.8.0 officially introduces the **Agent Skill** system — a new way to codify team expertise into reusable assets:
+
+- 📦 **Custom Skill Packaging**: Encapsulate your unique data cleaning logic, business analysis models, and more into standalone Skills — write once, reuse across the entire team.
+- 🔗 **One-Click GitHub Import**: Import high-quality Skills directly from community or enterprise private repositories, breaking down information silos.
+- 📊 **Built-in Skills**: Ships with CSV/Excel deep analysis Skill, financial report analysis Skill, Agent Browser Skill, and more. Create business-specific Skills with one click using the Skill Creator.
+
+<img src="/img/skill/skill_list.png" width="720px" />
+
+### 🛡️ Sandbox Secure Execution Environment
+
+Granting AI the power to execute code often comes with system-level risks. To address this, we introduce the isolated **Sandbox**:
+
+- 🛡️ **Isolated Sandbox Execution**: All shell code generated by Agents that hasn't been manually reviewed runs in isolated containers. Supports strict resource threshold limits and execution timeout controls — protecting the host system while balancing agent execution power with enterprise-grade data security.
+- ⚙️ **Resource Configuration**: Session-level sandbox resource limits and execution timeout guarantees, making analysis artifacts more reproducible and auditable.
+
+<img src="/img/agentic_data/sanbox_running.png" width="720px" />
+
+### 💬 Collaboration & Product Experience Upgrades
+
+Great tools need to flow smoothly, transforming analysis reports and processes from "personal use" to "team reuse":
+
+- 💬 **Conversation Sharing & Execution Replay**: Generate share links with one click. Your team members can not only view the final polished HTML reports, but also replay every step of the Agent's thinking and reasoning process — making retrospectives and knowledge sharing simpler.
+- 📝 **Conversation Task List**: Search historical conversation records at any time, facilitating review and documentation.
+- 🔗 **Native App & Agent Modes**: Retains native application, Agent, AWEL, and other capabilities, supporting diverse product enhancements and feature usage.
+
+<img src="/img/agentic_data/agentic_playback.jpg" width="720px" />
+
+### 🚀 One-Click Setup Script
+
+We provide multiple new streamlined installation scripts to get DB-GPT up and running faster.
+
+**Option 1: Install via PyPI**
+
+```bash
+# Step 1: Install dbgpt-app
+pip install dbgpt-app
+
+# Step 2: Start DB-GPT
+dbgpt start
+```
+
+**Option 2: Install via Shell Script**
+
+```bash
+# Using OpenAI as an example, quickly initialize the environment
+curl -fsSL https://raw.githubusercontent.com/eosphoros-ai/DB-GPT/main/scripts/install/install.sh \
+  | OPENAI_API_KEY=sk-xxx bash -s -- --profile openai
+
+# Start DB-GPT
+cd ~/.dbgpt/DB-GPT && uv run dbgpt start webserver --config ~/.dbgpt/configs/<profile>.toml
+```
+
+**Option 3: Install from Source (same as previous versions)**
+
+```bash
+uv sync --all-packages \
+  --extra "base" \
+  --extra "proxy_openai" \
+  --extra "rag" \
+  --extra "storage_chromadb" \
+  --extra "dbgpts"
+
+uv run dbgpt start webserver --config configs/dbgpt-proxy-openai.toml
+```
+
+🚀 Open your browser and visit [http://localhost:5670](http://localhost:5670)
+
+For detailed installation instructions, see the [Installation Guide](http://docs.dbgpt.cn/docs/next/installation/).
+
+### 📖 Documentation Overhaul with Multi-Language Support
+
+The official documentation has been completely revamped and now officially supports multiple languages! A fresh UI design, clearer directory structure, and one-click language switching deliver a better reading and development experience.
+
+👉 [Browse the New Documentation](http://docs.dbgpt.cn/docs/next/overview/)
+
+## Other Improvements
+
+- Add MiniMax Provider support ([#2989](https://github.com/eosphoros-ai/DB-GPT/pull/2989))
+- Fix React parser handling of vis-thinking blocks ([#2996](https://github.com/eosphoros-ai/DB-GPT/pull/2996))
+- README and documentation updates ([#2991](https://github.com/eosphoros-ai/DB-GPT/pull/2991))
+
+## How to Upgrade
+
+[Upgrade to v0.8.0](../upgrade/v0.8.0.md)
+
+## Acknowledgements
+
+### 🎉 New Contributors
+
+V0.8.0 welcomes **2 new contributors**:
+
+- @octo-patch
+- @LXW2019124
+
+🔥🔥 Thank you to all our contributors for making this release possible!
+
+@Aries-ckt, @Copilot, @LXW2019124, @chenliang15405, @copilot-swe-agent, @fangyinc and @octo-patch
+
+## Reference
+
+- [Quick Start](http://docs.dbgpt.cn/docs/overview/)
+- [Docker Quick Deploy](http://docs.dbgpt.cn/docs/next/installation/docker/)

docs/docs/upgrade/v0.8.0.md

@@ -0,0 +1,66 @@
+# Upgrade To v0.8.0
+
+## Overview
+
+This guide walks you through upgrading from **v0.7.x** to **v0.8.0**.
+
+- **SQLite users**: No database migration is required.
+- **MySQL users**: A database migration is required — see [Upgrade Database](#upgrade-database) below.
+
+## Prepare
+
+### Backup Your Database
+
+:::warning
+To prevent data loss, **always back up your database** before performing an upgrade. Choose the backup method that matches your database type (e.g., `mysqldump` for MySQL, file copy for SQLite).
+:::
+
+## Upgrade
+
+### Step 1 — Stop DB-GPT Service
+
+Stop the running DB-GPT service using the same method you used to start it.
+
+### Step 2 — Upgrade Database
+
+Execute the following SQL statements against your MySQL database to apply the v0.8.0 schema changes.
+
+:::tip
+All upgrade SQL scripts are maintained in the repository under [`assets/schema/upgrade/`](https://github.com/eosphoros-ai/DB-GPT/tree/main/assets/schema/upgrade).
+:::
+
+**New Tables**
+
+| Table | Description |
+|-------|-------------|
+| `share_links` | Stores conversation share-link tokens, enabling users to share conversations via unique URLs. |
+
+```sql
+USE dbgpt;
+
+-- share_links: Store conversation share link tokens
+CREATE TABLE `share_links` (
+  `id` int NOT NULL AUTO_INCREMENT COMMENT 'Primary key',
+  `token` varchar(64) NOT NULL COMMENT 'Unique random share token',
+  `conv_uid` varchar(255) NOT NULL COMMENT 'The conversation uid being shared',
+  `created_by` varchar(255) DEFAULT NULL COMMENT 'User who created the share link',
+  `gmt_created` TIMESTAMP DEFAULT CURRENT_TIMESTAMP COMMENT 'Creation time',
+  PRIMARY KEY (`id`),
+  UNIQUE KEY `uk_share_token` (`token`),
+  KEY `ix_share_links_token` (`token`),
+  KEY `ix_share_links_conv_uid` (`conv_uid`)
+) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci COMMENT='Conversation share link table';
+```
+
+### Step 3 — Install Dependencies
+
+Install or update dependencies according to your installation method. If you installed from source using the default setup, run:
+
+```bash
+uv sync --all-packages
+```
+
+
+### Step 4 — Start DB-GPT Service
+
+Restart the DB-GPT service using your preferred start method. Verify that the service is running correctly and the new share-link feature is available.