fix(skills/py): align Python agent skill with official CloudBase docs

Based on https://docs.cloudbase.net/ai/agent/agent-adapter/agent-adapter-langgraph-python
and full cross-file audit of skill/cloudbase-agent/py/*.md

Fixes:
- adapter-langgraph.md: pip install cloudbase_agent[langgraph] → correct
  split package names (cloudbase-agent-langgraph + cloudbase-agent-server
  + langgraph + langchain-openai)
- authentication.md, adapter-development.md, adapter-coze.md,
  references/recipes.md: port=8000 → port=9000 (official default)
- adapter-coze.md: Docker port mapping 8000:8000 → 9000:9000

Why this matters: evaluation agents kept failing pip install because
the skill documented a non-existent package name, and port tests
failed because grader/case used the wrong default. This audit brings
all sub-files in line with skill.md's (already-correct) main entry.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: binggg

config/source/skills/cloudbase-agent/py/adapter-coze.md

@@ -30,7 +30,7 @@ def create_agent():
         api_key="your-api-key"
     )
 
-AgentServiceApp().run(create_agent, port=8000)
+AgentServiceApp().run(create_agent, port=9000)
 ```
 
 ## Configuration
@@ -99,7 +99,7 @@ def create_agent():
 
 app = AgentServiceApp()
 app.use(auth_middleware)
-app.run(create_agent, port=8000)
+app.run(create_agent, port=9000)
 ```
 
 ### User ID Extraction
@@ -314,7 +314,7 @@ CMD ["python", "app.py"]
 
 ```bash
 docker build -t coze-agent .
-docker run -p 8000:8000 \
+docker run -p 9000:9000 \
   -e COZE_BOT_ID=your-bot-id \
   -e COZE_API_KEY=your-api-key \
   -e JWT_SECRET_KEY=your-secret \

config/source/skills/cloudbase-agent/py/adapter-development.md

@@ -101,7 +101,7 @@ Deploy it:
 ```python
 from cloudbase_agent.server import AgentServiceApp
 
-AgentServiceApp().run(lambda: SimpleEchoAgent(), port=8000)
+AgentServiceApp().run(lambda: SimpleEchoAgent(), port=9000)
 ```
 
 ## Streaming Response Pattern

config/source/skills/cloudbase-agent/py/adapter-langgraph.md

@@ -22,7 +22,7 @@ The CloudBase Agent LangGraph adapter (`cloudbase_agent.langgraph`) provides sea
 ### 1. Install Dependencies
 
 ```bash
-pip install cloudbase_agent[langgraph]
+pip install cloudbase-agent-langgraph cloudbase-agent-server langgraph langchain-openai
 ```
 
 This installs:

config/source/skills/cloudbase-agent/py/authentication.md

@@ -91,7 +91,7 @@ from cloudbase_agent.server import AgentServiceApp
 
 app = AgentServiceApp()
 app.use(auth_middleware)  # Register before run()
-app.run(create_agent, port=8000)
+app.run(create_agent, port=9000)
 ```
 
 ### 3. Adapter/Agent (Read)
@@ -239,7 +239,7 @@ def create_agent():
 # Start server with auth middleware
 app = AgentServiceApp()
 app.use(jwt_auth_middleware)  # Register auth middleware
-app.run(create_agent, port=8000)
+app.run(create_agent, port=9000)
 ```
 
 ### Step 3: Coze Adapter Internal Logic

config/source/skills/cloudbase-agent/py/references/recipes.md

@@ -29,7 +29,7 @@ server = create_server()
 server.add_agent("/chat", agent)
 
 if __name__ == "__main__":
-    server.run(host="0.0.0.0", port=8000)
+    server.run(host="0.0.0.0", port=9000)
 ```
 
 ## Recipe 2: Multi-Agent System