diff --git a/src/landppt/services/file_processor.py b/src/landppt/services/file_processor.py
new file mode 100644
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+++ b/src/landppt/services/file_processor.py
@@ -0,0 +1,493 @@
+"""
+File Processing Service for LandPPT
+Handles document upload and content extraction as specified in requires.md
+"""
+
+import os
+import re
+import logging
+from typing import List, Dict, Any, Optional, Tuple
+from pathlib import Path
+import tempfile
+
+# Document processing libraries
+try:
+    import docx
+    from docx import Document
+    DOCX_AVAILABLE = True
+except ImportError:
+    DOCX_AVAILABLE = False
+
+try:
+    import PyPDF2
+    PDF_AVAILABLE = True
+except ImportError:
+    PDF_AVAILABLE = False
+
+try:
+    from PIL import Image
+    import pytesseract
+    OCR_AVAILABLE = True
+except ImportError:
+    OCR_AVAILABLE = False
+
+from ..api.models import FileUploadResponse
+
+logger = logging.getLogger(__name__)
+
+
+class FileProcessor:
+    """Processes uploaded files and extracts content for PPT generation"""
+    
+    def __init__(self):
+        self.supported_formats = {
+            '.docx': self._process_docx,
+            '.pdf': self._process_pdf,
+            '.txt': self._process_txt,
+            '.md': self._process_markdown,
+            '.jpg': self._process_image,
+            '.jpeg': self._process_image,
+            '.png': self._process_image,
+        }
+        
+        # Keywords for scenario detection
+        self.scenario_keywords = {
+            'tourism': ['旅游', '景点', '行程', '旅行', '观光', '度假', '酒店', '机票', '导游'],
+            'education': ['教育', '学习', '课程', '培训', '知识', '科普', '儿童', '学生', '教学'],
+            'analysis': ['分析', '数据', '统计', '研究', '报告', '调查', '图表', '趋势', '结论'],
+            'history': ['历史', '古代', '文化', '传统', '遗产', '文物', '朝代', '事件', '人物'],
+            'technology': ['技术', '科技', '创新', '数字', '智能', '人工智能', '互联网', '软件', '硬件'],
+            'business': ['商业', '企业', '市场', '营销', '销售', '管理', '战略', '财务', '投资'],
+            'general': ['介绍', '概述', '总结', '说明', '展示', '汇报', '演示', '分享']
+        }
+    
+    async def process_file(self, file_path: str, filename: str) -> FileUploadResponse:
+        """Process uploaded file and extract content"""
+        try:
+            file_ext = Path(filename).suffix.lower()
+            file_size = os.path.getsize(file_path)
+            
+            if file_ext not in self.supported_formats:
+                raise ValueError(f"Unsupported file format: {file_ext}")
+            
+            # Process file based on type
+            processor = self.supported_formats[file_ext]
+            content = await processor(file_path)
+            
+            # Extract topics and suggest scenarios
+            topics = self._extract_topics(content)
+            scenarios = self._suggest_scenarios(content)
+            
+            return FileUploadResponse(
+                filename=filename,
+                size=file_size,
+                type=file_ext,
+                processed_content=content,
+                extracted_topics=topics,
+                suggested_scenarios=scenarios,
+                message=f"文件 {filename} 处理成功，提取了 {len(content)} 个字符的内容"
+            )
+            
+        except Exception as e:
+            logger.error(f"Error processing file {filename}: {e}")
+            raise ValueError(f"文件处理失败: {str(e)}")
+    
+    async def _process_docx(self, file_path: str) -> str:
+        """Process DOCX file"""
+        if not DOCX_AVAILABLE:
+            raise ValueError("DOCX processing not available. Please install python-docx.")
+
+        def _process_docx_sync(file_path: str) -> str:
+            """同步处理DOCX文件（在线程池中运行）"""
+            doc = Document(file_path)
+            content_parts = []
+
+            # Extract paragraphs
+            for paragraph in doc.paragraphs:
+                text = paragraph.text.strip()
+                if text:
+                    content_parts.append(text)
+
+            # Extract tables
+            for table in doc.tables:
+                for row in table.rows:
+                    row_text = []
+                    for cell in row.cells:
+                        cell_text = cell.text.strip()
+                        if cell_text:
+                            row_text.append(cell_text)
+                    if row_text:
+                        content_parts.append(" | ".join(row_text))
+
+            return "\n\n".join(content_parts)
+
+        try:
+            # 在线程池中执行文件处理以避免阻塞主服务
+            import asyncio
+            loop = asyncio.get_running_loop()
+            return await loop.run_in_executor(None, _process_docx_sync, file_path)
+
+        except Exception as e:
+            logger.error(f"Error processing DOCX file: {e}")
+            raise ValueError(f"DOCX 文件处理失败: {str(e)}")
+    
+    async def _process_pdf(self, file_path: str) -> str:
+        """Process PDF file"""
+        if not PDF_AVAILABLE:
+            raise ValueError("PDF processing not available. Please install PyPDF2.")
+
+        def _process_pdf_sync(file_path: str) -> str:
+            """同步处理PDF文件（在线程池中运行）"""
+            content_parts = []
+
+            with open(file_path, 'rb') as file:
+                pdf_reader = PyPDF2.PdfReader(file)
+
+                for page_num in range(len(pdf_reader.pages)):
+                    page = pdf_reader.pages[page_num]
+                    text = page.extract_text()
+
+                    if text.strip():
+                        content_parts.append(text.strip())
+
+            return "\n\n".join(content_parts)
+
+        try:
+            # 在线程池中执行文件处理以避免阻塞主服务
+            import asyncio
+            loop = asyncio.get_running_loop()
+            return await loop.run_in_executor(None, _process_pdf_sync, file_path)
+
+        except Exception as e:
+            logger.error(f"Error processing PDF file: {e}")
+            raise ValueError(f"PDF 文件处理失败: {str(e)}")
+    
+    async def _process_txt(self, file_path: str) -> str:
+        """Process TXT file"""
+        def _process_txt_sync(file_path: str) -> str:
+            """同步处理TXT文件（在线程池中运行）"""
+            try:
+                with open(file_path, 'r', encoding='utf-8') as file:
+                    content = file.read()
+
+                # Try different encodings if UTF-8 fails
+                if not content.strip():
+                    encodings = ['gbk', 'gb2312', 'latin1']
+                    for encoding in encodings:
+                        try:
+                            with open(file_path, 'r', encoding=encoding) as file:
+                                content = file.read()
+                            if content.strip():
+                                break
+                        except:
+                            continue
+
+                return content.strip()
+            except Exception as e:
+                raise e
+
+        try:
+            # 在线程池中执行文件处理以避免阻塞主服务
+            import asyncio
+            loop = asyncio.get_running_loop()
+            return await loop.run_in_executor(None, _process_txt_sync, file_path)
+
+        except Exception as e:
+            logger.error(f"Error processing TXT file: {e}")
+            raise ValueError(f"TXT 文件处理失败: {str(e)}")
+    
+    async def _process_markdown(self, file_path: str) -> str:
+        """Process Markdown file"""
+        def _process_markdown_sync(file_path: str) -> str:
+            """同步处理Markdown文件（在线程池中运行）"""
+            with open(file_path, 'r', encoding='utf-8') as file:
+                content = file.read()
+
+            # Remove markdown syntax for cleaner content
+            content = re.sub(r'#{1,6}\s+', '', content)  # Remove headers
+            content = re.sub(r'\*\*(.*?)\*\*', r'\1', content)  # Remove bold
+            content = re.sub(r'\*(.*?)\*', r'\1', content)  # Remove italic
+            content = re.sub(r'`(.*?)`', r'\1', content)  # Remove code
+            content = re.sub(r'\[(.*?)\]\(.*?\)', r'\1', content)  # Remove links
+
+            return content.strip()
+
+        try:
+            # 在线程池中执行文件处理以避免阻塞主服务
+            import asyncio
+            loop = asyncio.get_running_loop()
+            return await loop.run_in_executor(None, _process_markdown_sync, file_path)
+
+        except Exception as e:
+            logger.error(f"Error processing Markdown file: {e}")
+            raise ValueError(f"Markdown 文件处理失败: {str(e)}")
+    
+    async def _process_image(self, file_path: str) -> str:
+        """Process image file using OCR"""
+        if not OCR_AVAILABLE:
+            return "图片文件已上传，但 OCR 功能不可用。请安装 pytesseract 和 PIL 以启用文字识别。"
+
+        def _process_image_sync(file_path: str) -> str:
+            """同步处理图像文件（在线程池中运行）"""
+            image = Image.open(file_path)
+
+            # Perform OCR
+            text = pytesseract.image_to_string(image, lang='chi_sim+eng')
+
+            if not text.strip():
+                return "图片文件已处理，但未能识别出文字内容。"
+
+            return text.strip()
+
+        try:
+            # 在线程池中执行图像处理以避免阻塞主服务
+            import asyncio
+            loop = asyncio.get_running_loop()
+            return await loop.run_in_executor(None, _process_image_sync, file_path)
+
+        except Exception as e:
+            logger.error(f"Error processing image file: {e}")
+            return f"图片处理失败: {str(e)}"
+    
+    def _extract_topics(self, content: str) -> List[str]:
+        """Extract potential topics from content"""
+        if not content:
+            return []
+        
+        topics = []
+        
+        # Extract sentences that might be topics (short, descriptive)
+        sentences = re.split(r'[。！？\n]', content)
+        
+        for sentence in sentences:
+            sentence = sentence.strip()
+            # Look for topic-like sentences (10-50 characters, no common words)
+            if 10 <= len(sentence) <= 50:
+                # Avoid sentences with too many common words
+                common_words = ['的', '是', '在', '有', '和', '与', '或', '但', '而', '了', '着', '过']
+                common_count = sum(1 for word in common_words if word in sentence)
+                
+                if common_count <= 2:  # Not too many common words
+                    topics.append(sentence)
+        
+        # Also extract potential titles (lines that are short and at the beginning)
+        lines = content.split('\n')
+        for i, line in enumerate(lines[:10]):  # Check first 10 lines
+            line = line.strip()
+            if 5 <= len(line) <= 30 and not line.endswith('：'):
+                topics.append(line)
+        
+        # Remove duplicates and limit to top 10
+        topics = list(dict.fromkeys(topics))[:10]
+        
+        return topics
+    
+    def _suggest_scenarios(self, content: str) -> List[str]:
+        """Suggest appropriate scenarios based on content"""
+        if not content:
+            return ['general']
+        
+        content_lower = content.lower()
+        scenario_scores = {}
+        
+        # Score each scenario based on keyword matches
+        for scenario, keywords in self.scenario_keywords.items():
+            score = 0
+            for keyword in keywords:
+                score += content_lower.count(keyword)
+            
+            if score > 0:
+                scenario_scores[scenario] = score
+        
+        # Sort by score and return top scenarios
+        sorted_scenarios = sorted(scenario_scores.items(), key=lambda x: x[1], reverse=True)
+        
+        # Return top 3 scenarios, or 'general' if no matches
+        if sorted_scenarios:
+            return [scenario for scenario, score in sorted_scenarios[:3]]
+        else:
+            return ['general']
+    
+    def get_supported_formats(self) -> List[str]:
+        """Get list of supported file formats"""
+        return list(self.supported_formats.keys())
+    
+    def validate_file(self, filename: str, file_size: int, max_size_mb: int = 100) -> Tuple[bool, str]:
+        """Validate uploaded file"""
+        file_ext = Path(filename).suffix.lower()
+        
+        # Check file extension
+        if file_ext not in self.supported_formats:
+            return False, f"不支持的文件格式: {file_ext}。支持的格式: {', '.join(self.supported_formats.keys())}"
+        
+        # Check file size
+        max_size_bytes = max_size_mb * 1024 * 1024
+        if file_size > max_size_bytes:
+            return False, f"文件大小超过限制 ({max_size_mb}MB)。当前文件大小: {file_size / 1024 / 1024:.1f}MB"
+        
+        # Check specific format requirements
+        if file_ext == '.docx' and not DOCX_AVAILABLE:
+            return False, "DOCX 处理功能不可用，请联系管理员安装 python-docx"
+        
+        if file_ext == '.pdf' and not PDF_AVAILABLE:
+            return False, "PDF 处理功能不可用，请联系管理员安装 PyPDF2"
+        
+        if file_ext in ['.jpg', '.jpeg', '.png'] and not OCR_AVAILABLE:
+            return True, "图片文件可以上传，但文字识别功能不可用"
+        
+        return True, "文件验证通过"
+    
+    async def create_ppt_from_content(self, content: str, suggested_topic: str = None) -> Dict[str, Any]:
+        """Create PPT generation request from processed content"""
+        # Extract or suggest a topic
+        if not suggested_topic:
+            topics = self._extract_topics(content)
+            suggested_topic = topics[0] if topics else "文档内容展示"
+        
+        # Suggest scenarios
+        scenarios = self._suggest_scenarios(content)
+        primary_scenario = scenarios[0] if scenarios else 'general'
+        
+        # Create a structured outline from content
+        sections = self._create_content_sections(content)
+        
+        return {
+            'topic': suggested_topic,
+            'scenario': primary_scenario,
+            'requirements': f"基于上传文档内容生成PPT，包含以下要点：\n{content[:500]}...",
+            'uploaded_content': content,
+            'suggested_sections': sections,
+            'language': 'zh'
+        }
+    
+    def _create_content_sections(self, content: str) -> List[Dict[str, str]]:
+        """Create structured sections from content"""
+        sections = []
+
+        # Split content into logical sections
+        paragraphs = [p.strip() for p in content.split('\n\n') if p.strip()]
+
+        # Create title slide
+        sections.append({
+            'type': 'title',
+            'title': '文档内容展示',
+            'subtitle': '基于上传文档生成'
+        })
+
+        # Create content slides (max 10)
+        for i, paragraph in enumerate(paragraphs[:9]):
+            if len(paragraph) > 50:  # Only use substantial paragraphs
+                # Try to extract a title from the first sentence
+                sentences = paragraph.split('。')
+                title = sentences[0][:30] + '...' if len(sentences[0]) > 30 else sentences[0]
+
+                sections.append({
+                    'type': 'content',
+                    'title': title or f'内容 {i+1}',
+                    'content': paragraph[:300] + '...' if len(paragraph) > 300 else paragraph
+                })
+
+        # Add thank you slide
+        sections.append({
+            'type': 'thankyou',
+            'title': '谢谢观看',
+            'subtitle': '基于文档内容生成'
+        })
+
+        return sections
+
+    def merge_multiple_files_to_markdown(self, files_content: List[Dict[str, str]]) -> str:
+        """
+        将多个文件的内容合并为一个完整的Markdown文档
+
+        Args:
+            files_content: 文件内容列表，每项包含 filename 和 content
+
+        Returns:
+            合并后的Markdown格式内容
+        """
+        if not files_content:
+            return ""
+
+        # 如果只有一个文件，直接返回其内容
+        if len(files_content) == 1:
+            return files_content[0]["content"]
+
+        # 构建合并后的Markdown文档
+        merged_parts = []
+
+        # 添加文档标题
+        merged_parts.append("# 合并文档内容\n")
+        merged_parts.append(f"*本文档由 {len(files_content)} 个源文件合并生成*\n")
+        merged_parts.append("---\n")
+
+        # 添加目录
+        merged_parts.append("## 📋 文档目录\n")
+        for i, file_info in enumerate(files_content, 1):
+            filename = file_info["filename"]
+            merged_parts.append(f"{i}. [{filename}](#{self._sanitize_anchor(filename)})\n")
+        merged_parts.append("\n---\n")
+
+        # 添加每个文件的内容
+        for i, file_info in enumerate(files_content, 1):
+            filename = file_info["filename"]
+            content = file_info["content"]
+
+            # 添加文件标题（作为一级标题）
+            merged_parts.append(f"\n## {i}. {filename} {{#{self._sanitize_anchor(filename)}}}\n")
+
+            # 添加分隔线
+            merged_parts.append("---\n")
+
+            # 添加文件内容
+            # 如果内容已经包含Markdown格式，保持原样
+            # 否则将其格式化为段落
+            if content.strip():
+                # 检查是否已经是Markdown格式
+                if self._is_markdown_formatted(content):
+                    merged_parts.append(f"{content}\n")
+                else:
+                    # 将纯文本内容转换为段落
+                    paragraphs = [p.strip() for p in content.split('\n\n') if p.strip()]
+                    for paragraph in paragraphs:
+                        merged_parts.append(f"{paragraph}\n\n")
+            else:
+                merged_parts.append("*（此文件无内容或内容提取失败）*\n")
+
+            # 添加文件结束标记
+            merged_parts.append("\n")
+
+        # 添加文档结尾
+        merged_parts.append("\n---\n")
+        merged_parts.append("*文档结束*\n")
+
+        return "".join(merged_parts)
+
+    def _sanitize_anchor(self, text: str) -> str:
+        """将文本转换为合法的Markdown锚点"""
+        # 移除特殊字符，只保留字母数字和中文
+        sanitized = re.sub(r'[^\w\u4e00-\u9fff-]', '-', text)
+        # 移除多余的连字符
+        sanitized = re.sub(r'-+', '-', sanitized)
+        # 移除首尾的连字符
+        sanitized = sanitized.strip('-')
+        return sanitized.lower()
+
+    def _is_markdown_formatted(self, content: str) -> bool:
+        """检查内容是否已经是Markdown格式"""
+        # 简单检查是否包含常见的Markdown语法
+        markdown_indicators = [
+            r'^#{1,6}\s',  # 标题
+            r'\*\*.*\*\*',  # 粗体
+            r'\*.*\*',  # 斜体
+            r'^\s*[-*+]\s',  # 列表
+            r'^\s*\d+\.\s',  # 有序列表
+            r'\[.*\]\(.*\)',  # 链接
+            r'```',  # 代码块
+        ]
+
+        for indicator in markdown_indicators:
+            if re.search(indicator, content, re.MULTILINE):
+                return True
+
+        return False