@@ -82,6 +82,8 @@ Generate SQL and code to query data, clean datasets, compute metrics, and produc
### 3. Multi-source data access
Work across structured and unstructured sources, including databases, spreadsheets, documents, and knowledge bases.
+
+
### 4. Skills-driven extensibility
Package domain knowledge, analysis methods, and execution workflows into reusable skills.
@@ -91,7 +93,6 @@ Package domain knowledge, analysis methods, and execution workflows into reusabl
-
### 5. Sandboxed execution
Run code and tools in isolated environments for safer, more reliable analysis.
@@ -250,24 +251,6 @@ For Docker, local GPU models (vLLM, llama.cpp), or manual source-code setup, see
- controlled tool use
- reproducible outputs and artifacts
-## Platform & Ecosystem
-
-DB-GPT is also a platform for building AI-native data systems.
-
-- **AWEL** for agentic workflow orchestration
-- **Agents** for autonomous task execution
-- **RAG** for knowledge-enhanced reasoning
-- **SMMF** for multi-model management
-- **DB-GPT-Hub** for Text2SQL and finetuning workflows
-- **dbgpts** for apps, workflows, operators, and templates
-- [DB-GPT-Plugins](https://github.com/eosphoros-ai/DB-GPT-Plugins) for plugin-based extension
-- [GPT-Vis](https://github.com/eosphoros-ai/GPT-Vis) for visualization protocols
-
-#### DeepWiki
-- [DB-GPT](https://deepwiki.com/eosphoros-ai/DB-GPT)
-- [DB-GPT-HUB](https://deepwiki.com/eosphoros-ai/DB-GPT-Hub)
-- [dbgpts](https://deepwiki.com/eosphoros-ai/dbgpts)
-
#### Text2SQL Finetune
| LLM | Supported |
@@ -418,10 +401,6 @@ The next generation of **AI + Data** products will be:
DB-GPT aims to help developers and enterprises build that future.
-## Image
-🌐 [AutoDL Image](https://www.codewithgpu.com/i/eosphoros-ai/DB-GPT/dbgpt)
-
-
## Contribution
diff --git a/README.ta.md b/README.ta.md
index bce97a3ec..11e0096b3 100644
--- a/README.ta.md
+++ b/README.ta.md
@@ -2,7 +2,7 @@
@@ -317,8 +317,6 @@ LLaMA/LLaMA2, Baichuan, ChatGLM, Wenxin, Tongyi, Zhipu மற்றும் ப
- ஆதரவு தரவுமூலங்கள்
- [தரவுமூலங்கள்](http://docs.dbgpt.cn/docs/modules/connections)
-## படம்
-🌐 [AutoDL படம்](https://www.codewithgpu.com/i/eosphoros-ai/DB-GPT/dbgpt)
## பங்களிப்பு
diff --git a/README.zh.md b/README.zh.md
index ff4b8b37f..b3a67a36b 100644
--- a/README.zh.md
+++ b/README.zh.md
@@ -1,7 +1,7 @@
#
DB-GPT：开源 Agentic AI 数据分析智能助手
- 
+ 
@@ -79,14 +79,13 @@ DB-GPT 不只是一个助手界面，它同时也是一个平台，用于构建
### 3. 多数据源分析
同时处理结构化与非结构化数据，包括数据库、表格文件、文档和知识库。
+
### 4. Skills 驱动的可扩展能力
将领域知识、分析方法和执行流程沉淀为 skills，实现复用与扩展。
-
-
### 5. 沙箱安全执行
在隔离环境中运行代码和工具，让分析过程更安全、更可控。
@@ -250,18 +249,6 @@ cd ~/.dbgpt/DB-GPT && uv run dbgpt start webserver --config ~/.dbgpt/configs/
DB-GPT: AI Native Data App Development framework with AWEL and Agents
-
+
diff --git a/assets/datasources.png b/assets/datasources.png
new file mode 100644
index 000000000..ff7d6f45b
Binary files /dev/null and b/assets/datasources.png differ
diff --git a/assets/dbgpt_vision.png b/assets/dbgpt_vision.png
new file mode 100644
index 000000000..03950d07b
Binary files /dev/null and b/assets/dbgpt_vision.png differ
diff --git a/docs/docs/getting-started/concepts/architecture.md b/docs/docs/getting-started/concepts/architecture.md
deleted file mode 100644
index 27847c743..000000000
--- a/docs/docs/getting-started/concepts/architecture.md
+++ /dev/null
@@ -1,172 +0,0 @@
----
-sidebar_position: 0
-title: Architecture
-summary: "High-level map of DB-GPT packages, subsystems, and request flow"
-read_when:
- - You want to understand how DB-GPT is split across packages and runtime layers
- - You need the shortest mental model before diving into AWEL, agents, or RAG
----
-
-# Architecture
-
-An overview of how DB-GPT is structured and how its components fit together.
-
-## High-level view
-
-```mermaid
-flowchart TB
- subgraph Client["Client Layer"]
- WebUI["Web UI"]
- CLI["CLI"]
- API["REST API"]
- end
-
- subgraph App["Application Layer"]
- AppMgr["App Manager"]
- ChatMgr["Chat Manager"]
- FlowMgr["AWEL Flow Manager"]
- end
-
- subgraph Core["Core Layer"]
- Agent["Agent Framework"]
- AWEL["AWEL Engine"]
- RAG["RAG Framework"]
- SMMF["SMMF (Model Management)"]
- end
-
- subgraph Data["Data Layer"]
- DS["Data Sources"]
- KB["Knowledge Base"]
- VectorDB["Vector Store"]
- MetaDB["Metadata Store"]
- end
-
- Client --> App
- App --> Core
- Core --> Data
- SMMF --> LLM["LLM Providers"]
-```
-
-## Package structure
-
-DB-GPT is a Python monorepo organized into multiple packages under `packages/`:
-
-| Package | Purpose |
-|---|---|
-| **dbgpt-core** | Core abstractions: agent, AWEL, RAG, model interfaces, storage |
-| **dbgpt-app** | Application server, chat logic, Web API endpoints |
-| **dbgpt-serve** | Service modules (knowledge, flow, app, datasource management) |
-| **dbgpt-ext** | Extensions: datasource connectors, storage backends, model providers |
-| **dbgpt-client** | Python client SDK for the DB-GPT REST API |
-| **dbgpt-accelerator** | GPU acceleration utilities (quantization, inference optimization) |
-
-```
-DB-GPT/
-├── packages/
-│ ├── dbgpt-core/ # Core abstractions
-│ ├── dbgpt-app/ # Application server
-│ ├── dbgpt-serve/ # Service modules
-│ ├── dbgpt-ext/ # Extensions
-│ ├── dbgpt-client/ # Python client SDK
-│ └── dbgpt-accelerator/ # GPU acceleration
-├── web/ # Next.js Web UI
-├── configs/ # TOML configuration files
-└── docs/ # Documentation (Docusaurus)
-```
-
-## Core subsystems
-
-### SMMF (Service-oriented Multi-Model Management Framework)
-
-Manages multiple LLM and embedding model instances. Supports:
-
-- API proxy models (OpenAI, DeepSeek, Qwen, etc.)
-- Local models via HuggingFace Transformers, vLLM, llama.cpp
-- Model switching and failover
-- Standalone and cluster deployment modes
-
-Learn more: [SMMF Concept](/docs/getting-started/concepts/smmf) | [SMMF Module](/docs/modules/smmf)
-
-### AWEL (Agentic Workflow Expression Language)
-
-A domain-specific language for building AI application workflows as directed acyclic graphs (DAGs). AWEL provides:
-
-- Operators: Map, Reduce, Join, Branch, Stream transformers
-- Triggers: HTTP, scheduler-based
-- Visual editor: AWEL Flow in the Web UI
-
-Learn more: [AWEL Concept](/docs/getting-started/concepts/awel) | [AWEL Tutorial](/docs/awel/tutorial)
-
-### Agent Framework
-
-Data-driven multi-agent system with:
-
-- **Profile**: Agent identity and role definition
-- **Memory**: Sensory, short-term, long-term, and hybrid memory
-- **Planning**: Task decomposition and execution strategies
-- **Action**: Tool invocation and result processing
-- **Resource**: Tools, databases, knowledge bases, and resource packs
-
-Learn more: [Agents Concept](/docs/getting-started/concepts/agents) | [Agent Guide](/docs/agents/introduction/)
-
-### RAG Framework
-
-Retrieval-Augmented Generation with multiple retrieval strategies:
-
-- Vector similarity search (ChromaDB, Milvus, OceanBase)
-- Knowledge graph retrieval (Graph RAG)
-- Keyword-based retrieval (BM25)
-- Hybrid retrieval combining multiple strategies
-
-Learn more: [RAG Concept](/docs/getting-started/concepts/rag) | [RAG Module](/docs/modules/rag)
-
-## Configuration
-
-DB-GPT uses TOML configuration files in the `configs/` directory:
-
-```toml
-# configs/dbgpt-proxy-openai.toml
-[models]
-[[models.llms]]
-name = "chatgpt_proxyllm"
-provider = "proxy/openai"
-api_key = "your-api-key"
-
-[[models.embeddings]]
-name = "text-embedding-3-small"
-provider = "proxy/openai"
-api_key = "your-api-key"
-```
-
-Full reference: [Config Reference](/docs/config/config-reference)
-
-## Data flow
-
-A typical chat request flows through DB-GPT like this:
-
-```mermaid
-sequenceDiagram
- participant User
- participant WebUI
- participant Server
- participant Agent
- participant LLM
- participant DataSource
-
- User->>WebUI: Send message
- WebUI->>Server: POST /api/v2/chat/completions
- Server->>Agent: Route to agent
- Agent->>DataSource: Query data (if needed)
- DataSource-->>Agent: Data results
- Agent->>LLM: Generate response
- LLM-->>Agent: Model output
- Agent-->>Server: Formatted response
- Server-->>WebUI: Stream response
- WebUI-->>User: Display answer
-```
-
-## What's next
-
-- [AWEL](/docs/getting-started/concepts/awel) — Understand workflow orchestration
-- [Agents](/docs/getting-started/concepts/agents) — Learn about the agent framework
-- [Model Providers](/docs/getting-started/providers/) — Configure your preferred LLM