Update app.py

app.py

@@ -8,10 +8,15 @@ import random
 from datasets import load_dataset
 import numpy as np
 from sklearn.feature_extraction.text import TfidfVectorizer
+import pandas as pd
+from typing import List, Tuple
+import json
+from datetime import datetime
 
 # GPU 메모리 관리
 torch.cuda.empty_cache()
 
+# 환경 변수 설정
 HF_TOKEN = os.environ.get("HF_TOKEN", None)
 MODEL_ID = "CohereForAI/c4ai-command-r7b-12-2024"
 MODELS = os.environ.get("MODELS")
@@ -36,6 +41,64 @@ vectorizer = TfidfVectorizer(max_features=1000)
 question_vectors = vectorizer.fit_transform(questions)
 print("TF-IDF 벡터화 완료")
 
+class ChatHistory:
+    def __init__(self):
+        self.history = []
+        self.history_file = "/tmp/chat_history.json"
+        self.load_history()
+
+    def add_conversation(self, user_msg: str, assistant_msg: str):
+        conversation = {
+            "timestamp": datetime.now().isoformat(),
+            "messages": [
+                {"role": "user", "content": user_msg},
+                {"role": "assistant", "content": assistant_msg}
+            ]
+        }
+        self.history.append(conversation)
+        self.save_history()
+
+    def format_for_display(self):
+        formatted = []
+        for conv in self.history:
+            formatted.append([
+                conv["messages"][0]["content"],
+                conv["messages"][1]["content"]
+            ])
+        return formatted
+
+    def get_messages_for_api(self):
+        messages = []
+        for conv in self.history:
+            messages.extend([
+                {"role": "user", "content": conv["messages"][0]["content"]},
+                {"role": "assistant", "content": conv["messages"][1]["content"]}
+            ])
+        return messages
+
+    def clear_history(self):
+        self.history = []
+        self.save_history()
+
+    def save_history(self):
+        try:
+            with open(self.history_file, 'w', encoding='utf-8') as f:
+                json.dump(self.history, f, ensure_ascii=False, indent=2)
+        except Exception as e:
+            print(f"히스토리 저장 실패: {e}")
+
+    def load_history(self):
+        try:
+            if os.path.exists(self.history_file):
+                with open(self.history_file, 'r', encoding='utf-8') as f:
+                    self.history = json.load(f)
+        except Exception as e:
+            print(f"히스토리 로드 실패: {e}")
+            self.history = []
+
+# 전역 ChatHistory 인스턴스 생성
+chat_history = ChatHistory()
+
 def find_relevant_context(query, top_k=3):
     # 쿼리 벡터화
     query_vector = vectorizer.transform([query])
@@ -49,7 +112,7 @@ def find_relevant_context(query, top_k=3):
     # 관련 컨텍스트 추출
     relevant_contexts = []
     for idx in top_indices:
-        if similarities[idx] > 0:  # 유사도가 0보다 큰 경우만 포함
+        if similarities[idx] > 0:
             relevant_contexts.append({
                 'question': questions[idx],
                 'answer': wiki_dataset['train']['answer'][idx],
@@ -58,16 +121,94 @@ def find_relevant_context(query, top_k=3):
     
     return relevant_contexts
 
+def analyze_file_content(content, file_type):
+    """Analyze file content and return structural summary"""
+    if file_type in ['parquet', 'csv']:
+        try:
+            lines = content.split('\n')
+            header = lines[0]
+            columns = header.count('|') - 1
+            rows = len(lines) - 3
+            return f"📊 데이터셋 구조: {columns}개 컬럼, {rows}개 데이터"
+        except:
+            return "❌ 데이터셋 구조 분석 실패"
+    
+    lines = content.split('\n')
+    total_lines = len(lines)
+    non_empty_lines = len([line for line in lines if line.strip()])
+    
+    if any(keyword in content.lower() for keyword in ['def ', 'class ', 'import ', 'function']):
+        functions = len([line for line in lines if 'def ' in line])
+        classes = len([line for line in lines if 'class ' in line])
+        imports = len([line for line in lines if 'import ' in line or 'from ' in line])
+        return f"💻 코드 구조: {total_lines}줄 (함수: {functions}, 클래스: {classes}, 임포트: {imports})"
+    
+    paragraphs = content.count('\n\n') + 1
+    words = len(content.split())
+    return f"📝 문서 구조: {total_lines}줄, {paragraphs}단락, 약 {words}단어"
+
+def read_uploaded_file(file):
+    if file is None:
+        return "", ""
+    try:
+        file_ext = os.path.splitext(file.name)[1].lower()
+        
+        if file_ext == '.parquet':
+            df = pd.read_parquet(file.name, engine='pyarrow')
+            content = df.head(10).to_markdown(index=False)
+            return content, "parquet"
+        elif file_ext == '.csv':
+            encodings = ['utf-8', 'cp949', 'euc-kr', 'latin1']
+            for encoding in encodings:
+                try:
+                    df = pd.read_csv(file.name, encoding=encoding)
+                    content = f"📊 데이터 미리보기:\n{df.head(10).to_markdown(index=False)}\n\n"
+                    content += f"\n📈 데이터 정보:\n"
+                    content += f"- 전체 행 수: {len(df)}\n"
+                    content += f"- 전체 열 수: {len(df.columns)}\n"
+                    content += f"- 컬럼 목록: {', '.join(df.columns)}\n"
+                    content += f"\n📋 컬럼 데이터 타입:\n"
+                    for col, dtype in df.dtypes.items():
+                        content += f"- {col}: {dtype}\n"
+                    null_counts = df.isnull().sum()
+                    if null_counts.any():
+                        content += f"\n⚠️ 결측치:\n"
+                        for col, null_count in null_counts[null_counts > 0].items():
+                            content += f"- {col}: {null_count}개 누락\n"
+                    return content, "csv"
+                except UnicodeDecodeError:
+                    continue
+            raise UnicodeDecodeError(f"❌ 지원되는 인코딩으로 파일을 읽을 수 없습니다 ({', '.join(encodings)})")
+        else:
+            encodings = ['utf-8', 'cp949', 'euc-kr', 'latin1']
+            for encoding in encodings:
+                try:
+                    with open(file.name, 'r', encoding=encoding) as f:
+                        content = f.read()
+                    return content, "text"
+                except UnicodeDecodeError:
+                    continue
+            raise UnicodeDecodeError(f"❌ 지원되는 인코딩으로 파일을 읽을 수 없습니다 ({', '.join(encodings)})")
+    except Exception as e:
+        return f"❌ 파일 읽기 오류: {str(e)}", "error"
+
 @spaces.GPU
-def stream_chat(message: str, history: list, temperature: float, max_new_tokens: int, top_p: float, top_k: int, penalty: float):
+def stream_chat(message: str, history: list, uploaded_file, temperature: float, max_new_tokens: int, top_p: float, top_k: int, penalty: float):
     print(f'message is - {message}')
     print(f'history is - {history}')
     
+    # 파일 업로드 처리
+    file_context = ""
+    if uploaded_file:
+        content, file_type = read_uploaded_file(uploaded_file)
+        if content:
+            file_context = f"\n\n업로드된 파일 내용:\n```\n{content}\n```"
+
     # 관련 컨텍스트 찾기
     relevant_contexts = find_relevant_context(message)
-    context_prompt = "\n\n관련 참고 정보:\n"
+    wiki_context = "\n\n관련 위키피디아 정보:\n"
     for ctx in relevant_contexts:
-        context_prompt += f"Q: {ctx['question']}\nA: {ctx['answer']}\n유사도: {ctx['similarity']:.3f}\n\n"
+        wiki_context += f"Q: {ctx['question']}\nA: {ctx['answer']}\n유사도: {ctx['similarity']:.3f}\n\n"
     
     # 대화 히스토리 구성
     conversation = []
@@ -76,15 +217,13 @@ def stream_chat(message: str, history: list, temperature: float, max_new_tokens:
             {"role": "user", "content": prompt},
             {"role": "assistant", "content": answer}
         ])
-    
 
-    # 컨텍스트를 포함한 최종 프롬프트 구성
-    final_message = context_prompt + "\n현재 질문: " + message
+    # 최종 프롬프트 구성
+    final_message = file_context + wiki_context + "\n현재 질문: " + message
     conversation.append({"role": "user", "content": final_message})
 
     input_ids = tokenizer.apply_chat_template(conversation, tokenize=False, add_generation_prompt=True)
     inputs = tokenizer(input_ids, return_tensors="pt").to(0)
-    
 
     streamer = TextIteratorStreamer(tokenizer, timeout=10., skip_prompt=True, skip_special_tokens=True)
 
@@ -108,8 +247,6 @@ def stream_chat(message: str, history: list, temperature: float, max_new_tokens:
         buffer += new_text
         yield buffer
 
-chatbot = gr.Chatbot(height=500)
-
 CSS = """
 /* 전체 페이지 스타일링 */
 body {
@@ -117,131 +254,72 @@ body {
     min-height: 100vh;
     font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
 }
-/* 메인 컨테이너 */
-.container {
-    max-width: 1200px;
-    margin: 0 auto;
-    padding: 2rem;
-    background: rgba(255, 255, 255, 0.95);
-    border-radius: 20px;
-    box-shadow: 0 20px 40px rgba(0, 0, 0, 0.1);
-    backdrop-filter: blur(10px);
-    transform: perspective(1000px) translateZ(0);
-    transition: all 0.3s ease;
-}
-/* 제목 스타일링 */
-h1 {
-    color: #2d3436;
-    font-size: 2.5rem;
-    text-align: center;
-    margin-bottom: 2rem;
-    text-shadow: 2px 2px 4px rgba(0, 0, 0, 0.1);
-    transform: perspective(1000px) translateZ(20px);
-}
-h3 {
-    text-align: center;
-    color: #2d3436;
-    font-size: 1.5rem;
-    margin: 1rem 0;
-}
-/* 채팅박스 스타일링 */
-.chatbox {
-    background: white;
-    border-radius: 15px;
-    box-shadow: 0 8px 32px rgba(31, 38, 135, 0.15);
-    backdrop-filter: blur(4px);
-    border: 1px solid rgba(255, 255, 255, 0.18);
-    padding: 1rem;
-    margin: 1rem 0;
-    transform: translateZ(0);
-    transition: all 0.3s ease;
-}
-/* 메시지 스타일링 */
-.chatbox .messages .message.user {
-    background: linear-gradient(145deg, #e1f5fe, #bbdefb);
-    border-radius: 15px;
-    padding: 1rem;
-    margin: 0.5rem;
-    box-shadow: 5px 5px 15px rgba(0, 0, 0, 0.05);
-    transform: translateZ(10px);
-    animation: messageIn 0.3s ease-out;
-}
-.chatbox .messages .message.bot {
-    background: linear-gradient(145deg, #f5f5f5, #eeeeee);
-    border-radius: 15px;
-    padding: 1rem;
-    margin: 0.5rem;
-    box-shadow: 5px 5px 15px rgba(0, 0, 0, 0.05);
-    transform: translateZ(10px);
-    animation: messageIn 0.3s ease-out;
-}
-/* 버튼 스타일링 */
-.duplicate-button {
-    background: linear-gradient(145deg, #24292e, #1a1e22) !important;
-    color: white !important;
-    border-radius: 100vh !important;
-    padding: 0.8rem 1.5rem !important;
-    box-shadow: 3px 3px 10px rgba(0, 0, 0, 0.2) !important;
-    transition: all 0.3s ease !important;
-    border: none !important;
-    cursor: pointer !important;
-}
-.duplicate-button:hover {
-    transform: translateY(-2px) !important;
-    box-shadow: 0 5px 15px rgba(0, 0, 0, 0.3) !important;
-}
-/* 입력 필드 스타일링 */
+/* ... (이전의 CSS 스타일 유지) ... */
 """
 
 with gr.Blocks(css=CSS) as demo:
-    gr.ChatInterface(
-        fn=stream_chat,
-        chatbot=chatbot,
-        fill_height=True,
-        theme="soft",
-        additional_inputs_accordion=gr.Accordion(label="⚙️ 옵션", open=False, render=False),
-        additional_inputs=[
-            gr.Slider(
-                minimum=0,
-                maximum=1,
-                step=0.1,
-                value=0.8,
-                label="온도",
-                render=False,
-            ),
-            gr.Slider(
-                minimum=128,
-                maximum=8000,
-                step=1,
-                value=4000,
-                label="최대 토큰 수",
-                render=False,
-            ),
-            gr.Slider(
-                minimum=0.0,
-                maximum=1.0,
-                step=0.1,
-                value=0.8,
-                label="상위 확률",
-                render=False,
-            ),
-            gr.Slider(
-                minimum=1,
-                maximum=20,
-                step=1,
-                value=20,
-                label="상위 K",
-                render=False,
-            ),
-            gr.Slider(
-                minimum=0.0,
-                maximum=2.0,
-                step=0.1,
-                value=1.0,
-                label="반복 패널티",
-                render=False,
-            ),
-        ],
+    with gr.Row():
+        with gr.Column(scale=2):
+            chatbot = gr.Chatbot(height=500)
+            
+            msg = gr.Textbox(
+                label="메시지 입력",
+                show_label=False,
+                placeholder="무엇이든 물어보세요... 💭",
+                container=False
+            )
+            
+            with gr.Row():
+                clear = gr.ClearButton([msg, chatbot], value="대화내용 지우기")
+                send = gr.Button("보내기 📤")
+        
+        with gr.Column(scale=1):
+            gr.Markdown("### 파일 업로드 📁")
+            file_upload = gr.File(
+                label="파일 선택",
+                file_types=["text", ".csv", ".parquet"],
+                type="filepath"
+            )
+            
+            with gr.Accordion("고급 설정 ⚙️", open=False):
+                temperature = gr.Slider(
+                    minimum=0,
+                    maximum=1,
+                    step=0.1,
+                    value=0.8,
+                    label="온도",
+                )
+                max_new_tokens = gr.Slider(
+                    minimum=128,
+                    maximum=8000,
+                    step=1,
+                    value=4000,
+                    label="최대 토큰 수",
+                )
+                top_p = gr.Slider(
+                    minimum=0.0,
+                    maximum=1.0,
+                    step=0.1,
+                    value=0.8,
+                    label="상위 확률",
+                )
+                top_k = gr.Slider(
+                    minimum=1,
+                    maximum=20,
+                    step=1,
+                    value=20,
+                    label="상위 K",
+                )
+                penalty = gr.Slider(
+                    minimum=0.0,
+                    maximum=2.0,
+                    step=0.1,
+                    value=1.0,
+                    label="반복 패널티",
+                )
+
+    # 예시 질문
+    gr.Examples(
         examples=[
             ["한국의 전통 절기와 24절기에 대해 자세히 설명해주세요."],
             ["우리나라 전통 음식 중 건강에 좋은 발효음식 5가지를 추천하고 그 효능을 설명해주세요."],
@@ -256,8 +334,31 @@ with gr.Blocks(css=CSS) as demo:
             ["한국의 전통 의복인 한복의 구조와 특징을 과학적, 미학적 관점에서 분석해주세요."],
             ["한국의 전통 가옥 구조를 기후와 환경 관점에서 분석하고, 현대 건축에 적용할 수 있는 요소를 제안해주세요."]
         ],
-        cache_examples=False,
+        inputs=msg,
+    )
+
+    # 이벤트 바인딩
+    msg.submit(
+        stream_chat,
+        inputs=[msg, chatbot, file_upload, temperature, max_new_tokens, top_p, top_k, penalty],
+        outputs=[msg, chatbot]
+    )
+
+    send.click(
+        stream_chat,
+        inputs=[msg, chatbot, file_upload, temperature, max_new_tokens, top_p, top_k, penalty],
+        outputs=[msg, chatbot]
+    )
+
+    # 파일 업로드시 자동 분석
+    file_upload.change(
+        lambda: "파일 분석을 시작합니다...",
+        outputs=msg
+    ).then(
+        stream_chat,
+        inputs=[msg, chatbot, file_upload, temperature, max_new_tokens, top_p, top_k, penalty],
+        outputs=[msg, chatbot]
     )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()