Update app.py

app.py

@@ -2,27 +2,27 @@ import os
 import asyncio
 from typing import List, Dict
 
-# Protobuf C-extension 대신 pure-Python 구현
-os.environ["PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION"] = "python"
+# Protobuf C-extension 대신 pure-Python 구현 사용
+ios.environ["PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION"] = "python"
 
-# .env 및 Space Secrets 로드
+# .env 파일 및 Space Secrets 로드
 from dotenv import load_dotenv
 load_dotenv()
 
-# Gradio client 버그 우회용 패치
+# Gradio client 버그 우회 (OpenAPI 파싱)
 import gradio_client.utils as client_utils
-orig_json_to_python = client_utils.json_schema_to_python_type
-def safe_json_to_python(schema):
+orig = client_utils.json_schema_to_python_type
+def safe_json_type(schema, defs=None):
     try:
-        return orig_json_to_python(schema)
+        return orig(schema, defs)
     except Exception:
         return "Any"
-client_utils.json_schema_to_python_type = safe_json_to_python
+client_utils.json_schema_to_python_type = safe_json_type
 
 # Google API Key 검증
 api_key = os.getenv("GOOGLE_API_KEY")
 if not api_key:
-    raise EnvironmentError("GOOGLE_API_KEY를 Secrets에 추가해주세요.")
+    raise EnvironmentError("GOOGLE_API_KEY를 Settings→Secrets에 추가해주세요.")
 os.environ["GOOGLE_API_KEY"] = api_key
 
 # ChromaDB 경로 설정
@@ -42,46 +42,31 @@ from google.genai import types
 class SimpleRAGSystem:
     def __init__(self, db_path: str = None, collection: str = "KH_media_docs"):
         db_path = db_path or os.getenv("CHROMA_DB_DIR")
-        print(f"🔄 RAG 초기화: DB 경로={db_path}, 컬렉션={collection}")
-        # 임베딩 모델
-        print("📝 KR-SBERT 로드 중...")
         self.embedding_model = SentenceTransformer("snunlp/KR-SBERT-V40K-klueNLI-augSTS")
-        print("✅ 임베딩 준비 완료")
-        # ChromaDB 연결
-        print(f"🗄️ ChromaDB 연결: {db_path}")
         self.client = chromadb.PersistentClient(path=db_path)
         self.collection = self.client.get_collection(name=collection)
         count = self.collection.count()
-        print(f"✅ DB 준비됨: {collection} ({count}문서)")
         if count == 0:
-            raise RuntimeError("ChromaDB가 비어있습니다. 먼저 chromadb_builder.py를 실행하세요.")
+            raise RuntimeError("ChromaDB가 비어있습니다.")
 
     def search_similar_docs(self, query: str, top_k: int = 5) -> List[Dict]:
         emb = self.embedding_model.encode(query).tolist()
         res = self.collection.query(
-            query_embeddings=[emb],
-            n_results=top_k,
-            include=["documents","metadatas","distances"]
+            query_embeddings=[emb], n_results=top_k,
+            include=["documents", "metadatas"]
         )
         docs = []
-        for doc, meta, dist in zip(res["documents"][0], res["metadatas"][0], res.get("distances", [[]])[0]):
-            score = (2 - dist)/2 if dist is not None else None
-            docs.append({"content":doc, "metadata":meta, "similarity":score})
+        for doc, meta in zip(res["documents"][0], res["metadatas"][0]):
+            docs.append({"role": "system", "content": doc})
         return docs
 
-    def get_status(self) -> str:
-        return f"📊 '{self.collection.name}'에 {self.collection.count()}문서 준비"
-
-# RAG 시스템 인스턴스
 rag_system = SimpleRAGSystem()
 
 # === Google ADK 설정 ===
 session_svc = InMemorySessionService()
-agent = Agent(
-    model="gemini-2.0-flash-lite",
-    name="khu_media_advisor",
-    instruction="당신은 경희대 미디어학과 상담 AI입니다. 참고 문서를 바탕으로 답변하세요."
-)
+agent = Agent(model="gemini-2.0-flash-lite",
+              name="khu_media_advisor",
+              instruction="경희대 미디어학과 상담사로 답변하세요.")
 runner = Runner(agent=agent, app_name="khu_media_chatbot", session_service=session_svc)
 session_id = None
 
@@ -90,52 +75,42 @@ async def get_response(prompt: str) -> str:
     if session_id is None:
         sess = await session_svc.create_session(app_name="khu_media_chatbot", user_id="user")
         session_id = sess.id
-    response = ""
     content = types.Content(role="user", parts=[types.Part(text=prompt)])
+    response = ""
     for ev in runner.run(user_id="user", session_id=session_id, new_message=content):
         if ev.is_final_response():
             response = ev.content.parts[0].text
     return response
 
-# === Gradio Blocks UI ===
+# === Gradio UI ===
 with gr.Blocks(title="경희대 미디어학과 AI 상담사", theme="soft") as app:
     gr.Markdown("# 🎬 경희대 미디어학과 AI 상담사")
-    with gr.Row():
-        with gr.Column(scale=3):
-            chatbot = gr.Chatbot(type="messages", height=400, label="대화")
-            msg = gr.Textbox(show_label=False, placeholder="질문하세요...", lines=1)
-            send = gr.Button("전송")
-            gr.Markdown("### 💡 FAQ")
-            for q in ["전공 정보","주요 과목","취업 전망","학생 활동"]:
-                btn = gr.Button(q, size="sm")
-                btn.click(lambda x=q: x, outputs=[msg])
-        with gr.Column(scale=1):
-            status = gr.Textbox(label="시스템 상태", value=rag_system.get_status(), interactive=False)
-            gr.Button("🔄 새로고침").click(lambda: rag_system.get_status(), outputs=[status])
-            gr.Button("🗑️ 초기화").click(lambda: [], outputs=[chatbot])
+    chatbot = gr.Chatbot(type="messages", height=400)
+    msg = gr.Textbox(show_label=False, placeholder="질문을 입력하세요...")
+    send = gr.Button("전송")
+
     def chat_fn(user_input, history):
+        history = history or []
+        # RAG 컨텍스트
         docs = rag_system.search_similar_docs(user_input)
-        context = "\n".join(f"• {d['content']}" for d in docs)
-        prompt = f"질문: {user_input}\n\n===참고===\n{context}\n\n답변:"
+        # Combine existing history (dicts) with new user message
+        new_history = history + [{"role": "user", "content": user_input}]
+        # Insert docs as system messages
+        new_history += docs
+        # Build prompt text from history
+        prompt = "\n".join([f"{m['role']}: {m['content']}" for m in new_history])
         resp = asyncio.run(get_response(prompt))
-        history = history or []
-        history.append([user_input, resp])
-        return history, []
+        new_history.append({"role": "assistant", "content": resp})
+        return new_history, ""
+
     send.click(chat_fn, inputs=[msg, chatbot], outputs=[chatbot, msg])
     msg.submit(chat_fn, inputs=[msg, chatbot], outputs=[chatbot, msg])
+
     gr.Markdown(f"""
----
-**임베딩**: KR-SBERT  
-**DB**: ChromaDB  
-**LLM**: Gemini Flash-Lite  
-**상태**: {rag_system.get_status()}
-"""
+    ---
+    **상태**: ChromaDB에 준비된 문서 수 = {rag_system.collection.count()}
+    """
 )
 
 if __name__ == "__main__":
-    app.launch(
-        server_name="0.0.0.0",
-        server_port=int(os.environ.get("PORT", 7860)),
-        share=False,
-        show_api=False          # API 탭 숨기기
-    )
+    app.launch(server_name="0.0.0.0", server_port=int(os.environ.get("PORT",7860)), share=False, show_api=False)