feat: implement ERP AI Assistant Phase 1

Backend (FastAPI + SQLAlchemy + Claude API + RAG):
- Config management with Pydantic v2
- Database engine with connection pooling and SQL injection prevention
- AI engine with Claude API integration (support custom base URL)
- RAG engine with ChromaDB and sentence-transformers
- Requirement analysis service
- Config generation service
- Executor engine with SQL validation
- REST API endpoints: /analyze, /generate, /execute

Frontend (Vue 3 + Element Plus + Pinia):
- Complete 3-step workflow: analyze → generate → execute
- Step indicator with progress visualization
- Analysis result display with field table
- SQL preview with monospace font
- Execute confirmation dialog with safety warning
- Execution result display
- State management with Pinia
- API service integration

Security:
- SQL injection prevention with parameterized queries
- Dangerous SQL operation blocking
- Database password URL encoding
- Transaction auto-rollback
- Pydantic config validation

Features:
- Natural language requirement analysis
- Automated SQL configuration generation
- Safe execution with human review
- LAN access support
- Custom Claude API endpoint support

Documentation:
- README with quick start guide
- Quick start guide
- LAN access configuration
- Dependency fixes guide
- Claude API configuration
- Git operation guide
- Implementation report

Dependencies fixed:
- numpy<2.0.0 for chromadb compatibility
- sentence-transformers==2.7.0 for huggingface_hub compatibility

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

backend/app/models/request.py

@@ -0,0 +1,89 @@
+"""Request models for ERP AI Assistant API.
+
+This module defines Pydantic models for API request validation.
+"""
+
+from typing import Optional
+
+from pydantic import BaseModel, Field
+
+
+class AnalyzeRequest(BaseModel):
+    """Request model for requirement analysis.
+
+    Attributes:
+        input_type: Type of input - 'natural_language' or 'structured'
+        content: Requirement content text
+        session_id: Optional session ID for context continuity
+    """
+
+    input_type: str = Field(
+        ...,
+        description="输入类型: natural_language | structured"
+    )
+    content: str = Field(..., description="需求内容")
+    session_id: Optional[str] = Field(None, description="会话ID")
+
+    model_config = {
+        "json_schema_extra": {
+            "examples": [
+                {
+                    "input_type": "natural_language",
+                    "content": "创建一个销售订单管理页面",
+                    "session_id": "session-123"
+                }
+            ]
+        }
+    }
+
+
+class GenerateRequest(BaseModel):
+    """Request model for config generation.
+
+    Attributes:
+        session_id: Session ID from previous analysis
+        requirements: Structured requirements from analysis
+    """
+
+    session_id: str = Field(..., description="会话ID")
+    requirements: dict = Field(..., description="结构化需求")
+
+    model_config = {
+        "json_schema_extra": {
+            "examples": [
+                {
+                    "session_id": "session-123",
+                    "requirements": {
+                        "功能名称": "销售订单管理",
+                        "功能类型": "列表页面"
+                    }
+                }
+            ]
+        }
+    }
+
+
+class ExecuteRequest(BaseModel):
+    """Request model for config execution.
+
+    Attributes:
+        session_id: Session ID for tracking
+        confirmed: User confirmation flag
+        backup_enabled: Whether to create backup before execution
+    """
+
+    session_id: str = Field(..., description="会话ID")
+    confirmed: bool = Field(False, description="用户确认标识")
+    backup_enabled: bool = Field(True, description="是否启用备份")
+
+    model_config = {
+        "json_schema_extra": {
+            "examples": [
+                {
+                    "session_id": "session-123",
+                    "confirmed": True,
+                    "backup_enabled": True
+                }
+            ]
+        }
+    }