Update readme (#849)

Co-authored-by: 班扬 <xingjun.wxj@alibaba-inc.com>

Author: vinci-grape

README.md

@@ -263,58 +263,6 @@ asyncio.run(main())
 </details>
 
 
-### Agent Skills
-
-**MS-Agent Skills** is an **Implementation** of the [**Anthropic-Agent-Skills**](https://docs.claude.com/en/docs/agents-and-tools/agent-skills) protocol, enabling agents to autonomously explore and execute complex tasks by leveraging predefined or custom "skills".
-
-
-#### Key Features
-
-- 📜 **Standard Skill Protocol**: Fully compatible with the [Anthropic Skills](https://github.com/anthropics/skills) protocol
-- 🧠 **Heuristic Context Loading**: Loads only necessary context—such as `References`, `Resources`, and `Scripts` on demand
-- 🤖 **Autonomous Execution**: Agents autonomously analyze, plan, and decide which scripts and resources to execute based on skill definitions
-- 🔍 **Skill Management**: Supports batch loading of skills and can automatically retrieve and discover relevant skills based on user input
-- 🛡️ **Code Execution Environment**: Optional local direct code execution or secure sandboxed execution via [**ms-enclave**](https://github.com/modelscope/ms-enclave), with automatic dependency installation and environment isolation
-- 📁 **Multi-file Type Support**: Supports documentation, scripts, and resource files
-- 🧩 **Extensible Design**: The skill data structure is modularized, with implementations such as `SkillSchema` and `SkillContext` provided for easy extension and customization
-
-
-#### Quick Start
-
-> 💡 Note:
-> 1. Before running the following examples, ensure that you have set the `OPENAI_API_KEY` and `OPENAI_BASE_URL` environment variables to access the required model APIs.
-> 2. Agent Skills requires ms-agent >= 1.4.0
-
-
-**Installation**:
-
-```shell
-pip install ms-agent
-```
-
-**Usage**:
-
-> This example demonstrates how to configure and run an Agent Skill that generates generative art code based on p5.js flow fields.
-
-
-Refer to: [Run Skills](projects/agent_skills/run.py)
-
-
-**Result**:
-
-<div align="center">
-  <img src="https://github.com/user-attachments/assets/9d5d78bf-c2db-4280-b780-324eab74a41e" alt="FlowFieldParticles" width="750">
-  <p><em>Agent-Skills: Flow Field Particles</em></p>
-</div>
-
-
-#### References
-- **README**: [MS-Agent Skills](projects/agent_skills/README.md)
-- **Anthropic Agent Skills Official Docs**: [Anthropic-Agent-Skills](https://docs.claude.com/en/docs/agents-and-tools/agent-skills)
-- **Anthropic Skills GitHub Repo**: [Skills](https://github.com/anthropics/skills)
-
-
-
 ### Agentic Insight
 
 #### - Lightweight, Efficient, and Extensible Multi-modal Deep Research Framework

ms_agent/agent/agent.yaml

@@ -32,7 +32,7 @@ prompt:
 
     7. Respond in the same language the user uses. If the user switches, switch accordingly.
 
-    For requests that require performing a specific task or retrieving information, using the following format **in user language**:
+    For requests that require performing a specific task or retrieving information, using the following format:
     ```
     The user needs to ...
     I have analyzed this request in detail and broken it down into the following steps:
@@ -48,6 +48,8 @@ prompt:
     I have carefully reviewed the tool's output. The result does/does not fully meet my expectations. Next, I need to ...
     ```
 
+    **Important: Always respond in the same language the user is using.**
+
 max_chat_round: 9999
 
 callbacks:

projects/code_genesis/PR_ARTICLE.md

@@ -29,7 +29,7 @@ Code Genesis is built on three foundational pillars:
 Code Genesis provides **two configurable workflow modes** to balance between generation quality and execution speed, enabling users to select the optimal strategy based on project complexity:
 
 #### Standard Workflow (Production-Grade)
-<img alt="Simple Workflow Diagram" src="asset/workflow_code_genesis.png" />
+<img alt="Workflow Diagram" src="asset/workflow.jpg" />
 
 The standard pipeline implements a rigorous 7-stage process optimized for complex, production-ready projects:
 
@@ -49,7 +49,7 @@ User Story → Architect → File Design → File Order → Install → Coding 
 This workflow guarantees architectural coherence, eliminates reference errors through explicit dependency modeling, and produces enterprise-grade codebases with comprehensive documentation.
 
 #### Simple Workflow (Rapid Prototyping)
-<img alt="Simple Workflow Diagram" src="asset/simple_workflow_code_genesis.png" />
+<img alt="Simple Workflow Diagram" src="asset/simple_workflow.jpg" />
 
 For lightweight projects or quick iterations, the simple workflow condenses the pipeline into 4 core stages:
 

projects/code_genesis/asset/simple_workflow.jpg

@@ -2,3 +2,4 @@ aiohttp
 fastapi
 pandas
 uvicorn
+uvicorn[standard]

projects/code_genesis/asset/simple_workflow.png

@@ -237,9 +237,11 @@ def _build_and_copy_webui(self):
     extra_requires['research'], _ = parse_requirements(
         'requirements/research.txt')
     extra_requires['code'], _ = parse_requirements('requirements/code.txt')
+    extra_requires['webui'], _ = parse_requirements('requirements/webui.txt')
     all_requires.extend(install_requires)
     all_requires.extend(extra_requires['research'])
     all_requires.extend(extra_requires['code'])
+    all_requires.extend(extra_requires['webui'])
     extra_requires['all'] = all_requires
 
     setup(