feat: 修复 H5 底部导航覆盖 + 更新项目进度文档

## H5 底部导航修复 (Bug #10)
- 精简 App.vue，移除重复 tabbar，仅保留全局样式
- uni-page 设置 height: calc(100% - 50px) + overflow-y: auto
- 内容区域精确停在底部导航上方，独立滚动不再叠加
- 恢复 custom-tab-bar 组件

## 项目进度文档
- PROGRESS.md 更新至 10 个 Bug 修复
- 新增 H5 底部导航修复记录
- 新增历史变更条目

backend/app/ai/providers/openai.py

@@ -19,8 +19,11 @@ SYSTEM_PROMPTS = {
 
 
 class OpenAIProvider(AIProvider):
-    def __init__(self, api_key: str, model: str = "gpt-4o"):
-        self.client = AsyncOpenAI(api_key=api_key)
+    def __init__(self, api_key: str, model: str = "gpt-4o", base_url: Optional[str] = None):
+        kwargs = {"api_key": api_key}
+        if base_url:
+            kwargs["base_url"] = base_url
+        self.client = AsyncOpenAI(**kwargs)
         self.model = model
         self._name = f"openai-{model}"
         self._pricing = {
@@ -39,8 +42,10 @@ class OpenAIProvider(AIProvider):
         content = await self._call(system, f"Translate to {target_lang}:\n\n{text}", model=self._cheap_model)
         return {"translated_text": content, "provider": self.name, "model": self.model}
 
-    async def reply(self, inquiry: str, context: Optional[Dict[str, Any]] = None, tone: str = "professional") -> Dict[str, Any]:
+    async def reply(self, inquiry: str, context: Optional[Dict[str, Any]] = None, tone: str = "professional", preference_context: Optional[str] = None) -> Dict[str, Any]:
         system = SYSTEM_PROMPTS["reply"] + f"\nTone: {tone}"
+        if preference_context:
+            system += f"\nUser preference: {preference_context}"
 
         context_str = ""
         if context:
@@ -57,8 +62,10 @@ class OpenAIProvider(AIProvider):
         content = await self._call(system, prompt)
         return {"reply": content, "provider": self.name, "model": self.model}
 
-    async def generate_marketing(self, product_info: Dict[str, Any], target: str, style: str = "professional", language: str = "en") -> Dict[str, Any]:
+    async def generate_marketing(self, product_info: Dict[str, Any], target: str, style: str = "professional", language: str = "en", preference_context: Optional[str] = None) -> Dict[str, Any]:
         system = SYSTEM_PROMPTS["marketing"] + f"\nStyle: {style}\nTarget audience: {target}\nLanguage: {language}"
+        if preference_context:
+            system += f"\nUser preference: {preference_context}"
 
         product_str = json.dumps(product_info, ensure_ascii=False, indent=2)
         prompt = f"Product information:\n{product_str}\n\nGenerate marketing copy:"
@@ -76,7 +83,7 @@ class OpenAIProvider(AIProvider):
         except json.JSONDecodeError:
             return {"data": {}, "confidence": 0.0, "provider": self.name, "error": "parse_failed"}
 
-    async def _call(self, system: str, prompt: str, max_tokens: int = 1000, response_format: Optional[Dict] = None, model: Optional[str] = None) -> str:
+    async def _call(self, system: str, prompt: str, max_tokens: int = 3000, response_format: Optional[Dict] = None, model: Optional[str] = None) -> str:
         kwargs = {
             "model": model or self.model,
             "messages": [
@@ -90,7 +97,46 @@ class OpenAIProvider(AIProvider):
             kwargs["response_format"] = response_format
 
         resp = await self.client.chat.completions.create(**kwargs)
-        return resp.choices[0].message.content
+        content = resp.choices[0].message.content
+        
+        if content is None and hasattr(resp.choices[0].message, 'reasoning'):
+            reasoning = resp.choices[0].message.reasoning
+            if reasoning:
+                import re
+                final_output_patterns = [
+                    r'Final Output Generation[:：]\s*(.+?)(?:\n\n|$)',
+                    r'Final Output[:：]\s*(.+?)(?:\n\n|$)',
+                    r'7\.\s*Final Output Generation[:：]\s*(.+?)(?:\n\n|$)',
+                    r'翻译结果[：:]\s*(.+?)(?:\n\n|$)',
+                    r'最终输出[：:]\s*(.+?)(?:\n\n|$)',
+                ]
+                for pattern in final_output_patterns:
+                    match = re.search(pattern, reasoning, re.DOTALL)
+                    if match:
+                        content = match.group(1).strip()
+                        break
+                
+                if content is None:
+                    paragraphs = re.split(r'\n\n+', reasoning.strip())
+                    if paragraphs:
+                        for p in reversed(paragraphs):
+                            p = p.strip()
+                            if p and len(p) > 10:
+                                if not p.startswith('步骤') and not p.startswith('Step'):
+                                    content = p
+                                    break
+        
+        if content is None and hasattr(resp.choices[0].message, 'reasoning'):
+            reasoning = resp.choices[0].message.reasoning
+            if reasoning:
+                import re
+                cleaned = re.sub(r'^步骤\d+[：:].*$', '', reasoning, flags=re.MULTILINE)
+                cleaned = re.sub(r'^Step \d+[：:].*$', '', cleaned, flags=re.MULTILINE)
+                cleaned = re.sub(r'\n+', '\n', cleaned).strip()
+                if cleaned:
+                    content = cleaned
+        
+        return content
 
     @property
     def name(self) -> str: