Update app.py

app.py

@@ -33,6 +33,128 @@ from diffusers import FluxPipeline
 import torch
 from os import path  # 이 줄을 추가
 
+# 파일 업로드 관련 새로운 imports 추가
+from PIL import Image
+import pytesseract
+import fitz  # PyMuPDF for PDF processing
+import docx
+import io
+import mimetypes
+
+# 파일 처리를 위한 새로운 클래스 정의
+class FileProcessor:
+    ALLOWED_EXTENSIONS = {
+        'image': ['.jpg', '.jpeg', '.png', '.gif', '.bmp', '.webp'],
+        'text': ['.txt', '.pdf', '.docx', '.rtf'],
+    }
+    MAX_FILE_SIZE = 50 * 1024 * 1024  # 50MB
+    MAX_FILES = 5
+
+    @staticmethod
+    def is_allowed_file(filename):
+        ext = os.path.splitext(filename)[1].lower()
+        allowed = []
+        for extensions in FileProcessor.ALLOWED_EXTENSIONS.values():
+            allowed.extend(extensions)
+        return ext in allowed
+
+    @staticmethod
+    def get_file_type(filename):
+        ext = os.path.splitext(filename)[1].lower()
+        for file_type, extensions in FileProcessor.ALLOWED_EXTENSIONS.items():
+            if ext in extensions:
+                return file_type
+        return None
+
+    @staticmethod
+    async def process_file(file) -> str:
+        try:
+            file_type = FileProcessor.get_file_type(file.name)
+            
+            if file_type == 'image':
+                return await FileProcessor.process_image(file)
+            elif file_type == 'text':
+                return await FileProcessor.process_text(file)
+            else:
+                return "Unsupported file type"
+                
+        except Exception as e:
+            return f"Error processing file: {str(e)}"
+
+    @staticmethod
+    async def process_image(file):
+        try:
+            image = Image.open(file)
+            
+            # Claude API를 통한 이미지 분석
+            image_bytes = io.BytesIO()
+            image.save(image_bytes, format=image.format)
+            image_base64 = base64.b64encode(image_bytes.getvalue()).decode('utf-8')
+            
+            messages = [
+                {
+                    "role": "user",
+                    "content": [
+                        {
+                            "type": "image",
+                            "source": {
+                                "type": "base64",
+                                "media_type": f"image/{image.format.lower()}",
+                                "data": image_base64
+                            }
+                        },
+                        {
+                            "type": "text",
+                            "text": "Please analyze this image and provide a detailed description."
+                        }
+                    ]
+                }
+            ]
+
+            response = claude_client.messages.create(
+                model="claude-3-opus-20240229",
+                max_tokens=1000,
+                messages=messages
+            )
+
+            return response.content[0].text
+
+        except Exception as e:
+            return f"Error processing image: {str(e)}"
+
+    @staticmethod
+    async def process_text(file):
+        try:
+            text_content = ""
+            ext = os.path.splitext(file.name)[1].lower()
+            
+            if ext == '.pdf':
+                pdf = fitz.open(stream=file.read(), filetype="pdf")
+                for page in pdf:
+                    text_content += page.get_text()
+            elif ext == '.docx':
+                doc = docx.Document(file)
+                text_content = "\n".join([paragraph.text for paragraph in doc.paragraphs])
+            else:  # .txt, .rtf
+                text_content = file.read().decode('utf-8')
+
+            # Claude API를 통한 텍스트 분석
+            response = claude_client.messages.create(
+                model="claude-3-opus-20240229",
+                max_tokens=1000,
+                messages=[
+                    {
+                        "role": "user",
+                        "content": f"Please analyze this text and provide a summary and key insights:\n\n{text_content[:2000]}..."
+                    }
+                ]
+            )
+
+            return response.content[0].text
+
+        except Exception as e:
+            return f"Error processing text file: {str(e)}"
+            
 # 캐시 경로 설정
 cache_path = path.join(path.dirname(path.abspath(__file__)), "models")
 os.environ["TRANSFORMERS_CACHE"] = cache_path
@@ -691,6 +813,42 @@ def create_main_interface():
         .custom-button:hover {
             background: #0056b3;
         }
+
+
+.file-upload {
+    border: 2px dashed #007aff;
+    border-radius: 10px;
+    padding: 20px;
+    text-align: center;
+    background: #f8f9fa;
+    transition: all 0.3s ease;
+}
+
+.file-upload:hover {
+    border-color: #0056b3;
+    background: #e9ecef;
+}
+
+.analysis-result {
+    margin-top: 20px;
+    padding: 15px;
+    border-radius: 8px;
+    background: #fff;
+    border: 1px solid #e0e0e0;
+    max-height: 300px;
+    overflow-y: auto;
+}
+
+.analyze-btn {
+    margin-top: 10px;
+    background: #28c840 !important;
+    border-color: #28c840 !important;
+}
+
+.analyze-btn:hover {
+    background: #23a836 !important;
+    border-color: #23a836 !important;
+}        
     """, theme=theme)
 
 
@@ -860,6 +1018,9 @@ def create_main_interface():
                             # 좌측 패널
                             with antd.Col(span=24, md=8):
                                 with antd.Flex(vertical=True, gap="middle", wrap=True):
+
+
+        
                                     # macOS 스타일 윈도우 헤더
                                     header = gr.HTML("""
                                         <div class="window-frame">
@@ -885,16 +1046,37 @@ Use the "Generate" button for basic creation, "Enhance" button for prompt improv
                                         </div>
                                     """.format(get_image_base64('mouse.gif')))
 
-                                    # 입력 영역
+        # 파일 업로드 섹션
+                                    file_upload = gr.File(
+                                        label="Upload Files (Images/Documents)",
+                                        file_types=[".jpg", ".jpeg", ".png", ".gif", ".bmp", ".webp", 
+                                                  ".txt", ".pdf", ".docx", ".rtf"],
+                                        file_count="multiple",
+                                        elem_classes="file-upload"
+                                    )
+        
+                                    file_analysis = gr.Textbox(
+                                        label="File Analysis Result",
+                                        interactive=False,
+                                        elem_classes="analysis-result"
+                                    )
+        
+                                    analyze_btn = antd.Button(
+                                        "Analyze Files",
+                                        type="primary",
+                                        size="large",
+                                        elem_classes="analyze-btn"
+                                    )
+
+        # 입력 영역
                                     input = antd.InputTextarea(
                                         size="large", 
                                         allow_clear=True,
                                         placeholder=get_random_placeholder(),
-                                        elem_classes="custom-textarea"  # style 대신 class 사용
-
+                                        elem_classes="custom-textarea"
                                     )
- 
-                                    # 버튼 그룹
+
+        # 버튼 그룹
                                     with antd.Flex(gap="small", justify="flex-start"):
                                         btn = antd.Button(
                                             "Generate", 
@@ -915,11 +1097,63 @@ Use the "Generate" button for basic creation, "Enhance" button for prompt improv
                                             elem_classes="share-btn"
                                         )
 
+                                        deploy_result = gr.HTML(
+                                            label="Share Result",
+                                            elem_classes="deploy-result"
+                                        )
 
-                                    deploy_result = gr.HTML(
-                                        label="Share Result",
-                                        elem_classes="deploy-result"
-                                    )
+
+# 이벤트 핸들러들을 한 곳에 모아서 정의
+                        async def handle_file_upload(files):
+                            if not files:
+                                return "No files uploaded"
+    
+                            if len(files) > FileProcessor.MAX_FILES:
+                                return f"Maximum {FileProcessor.MAX_FILES} files allowed"
+    
+                            results = []
+                            for file in files:
+                                if not FileProcessor.is_allowed_file(file.name):
+                                    results.append(f"Unsupported file: {file.name}")
+                                    continue
+        
+                                if os.path.getsize(file.name) > FileProcessor.MAX_FILE_SIZE:
+                                    results.append(f"File too large: {file.name}")
+                                    continue
+        
+                                result = await FileProcessor.process_file(file)
+                                results.append(f"Analysis for {file.name}:\n{result}\n")
+    
+                            return "\n".join(results)
+
+# 이벤트 핸들러 연결
+                        analyze_btn.click(
+                            fn=handle_file_upload,
+                            inputs=[file_upload],
+                            outputs=[file_analysis]
+                        )
+
+                        btn.click(
+                            demo_instance.generation_code,
+                            inputs=[input, setting],
+                            outputs=[code_output, sandbox, state_tab, code_drawer]
+                        ).then(
+                            fn=update_placeholder,
+                            inputs=[],
+                            outputs=[input]
+                        )
+
+                        boost_btn.click(
+                            fn=handle_boost,
+                            inputs=[input],
+                            outputs=[input, state_tab]
+                        )
+
+                        deploy_btn.click(
+                            fn=lambda code: deploy_to_vercel(remove_code_block(code)) if code else "No code to share.",
+                            inputs=[code_output],
+                            outputs=[deploy_result]
+                        )
 
                             # 우측 패널
                             with antd.Col(span=24, md=16):