Update app.py

app.py

@@ -7,14 +7,15 @@ import sqlite3
 import gc
 import time
 import re
-import traceback # <-- 추가: 에러 상세 출력을 위해 임포트
+import traceback # <-- 에러 상세 출력을 위해 임포트
+import requests # <-- Pydantic v1 환경을 위해 Together SDK 대신 requests 사용
 
 # --- 외부 모듈 임포트 ---
 import reg_embedding_system
 import leximind_prompts
 
-# --- Together AI SDK ---
-from together import Together
+# --- Together AI SDK (제거됨) ---
+# from together import Together
 
 # --- eventlet monkey patch (Gunicorn + SocketIO 필수!) ---
 import eventlet
@@ -48,11 +49,11 @@ lexi_prompts = leximind_prompts.PromptLibrary()
 # --- RAG 객체 ---
 region_rag_objects = {}
 
-# --- Together AI 클라이언트 ---
+# --- Together AI 설정 (SDK 대신 API 호출에 사용) ---
 TOGETHER_API_KEY = os.getenv("TOGETHER_API_KEY")
 if not TOGETHER_API_KEY:
     raise EnvironmentError("TOGETHER_API_KEY가 설정되지 않았습니다. Hugging Face Secrets에 추가하세요.")
-client = Together(api_key=TOGETHER_API_KEY)
+# client = Together(api_key=TOGETHER_API_KEY) # <--- Together SDK 클라이언트 제거
 
 # --- RAG 로딩 ---
 def load_rag_objects():
@@ -168,32 +169,60 @@ def cleanup_connections():
         except:
             pass
 
-# --- Together AI 분석 ---
+# --- Together AI 분석 (SDK -> requests 직접 호출로 변경) ---
 def Gemma3_AI_analysis(query_txt, content_txt):
     content_txt = "\n".join(doc.page_content for doc in content_txt) if isinstance(content_txt, list) else str(content_txt)
     query_txt = str(query_txt)
     prompt = lexi_prompts.use_prompt(lexi_prompts.AI_system_prompt, query_txt=query_txt, content_txt=content_txt)
 
-    response = client.chat.completions.create(
-        model="meta-llama/Llama-3.3-70B-Instruct-Turbo",
-        messages=[{"role": "user", "content": prompt}],
-        max_tokens=1024,
-        temperature=0.7
-    )
-    return response.choices[0].message.content
-
-# --- Together AI 번역 ---
+    headers = {
+        "Authorization": f"Bearer {TOGETHER_API_KEY}",
+        "Content-Type": "application/json"
+    }
+    payload = {
+        "model": "meta-llama/Llama-3.3-70B-Instruct-Turbo",
+        "messages": [{"role": "user", "content": prompt}],
+        "max_tokens": 1024,
+        "temperature": 0.7
+    }
+
+    try:
+        response = requests.post("https://api.together.xyz/v1/chat/completions", headers=headers, json=payload, timeout=120)
+        response.raise_for_status() # HTTP 오류가 발생하면 예외 발생
+        
+        data = response.json()
+        return data["choices"][0]["message"]["content"]
+    except requests.exceptions.RequestException as e:
+        print(f"Together AI 분석 API 호출 실패: {e}")
+        traceback.print_exc()
+        return f"AI 분석 중 오류가 발생했습니다: {e}"
+
+# --- Together AI 번역 (SDK -> requests 직접 호출로 변경) ---
 def Gemma3_AI_Translate(query_txt):
     query_txt = str(query_txt)
     prompt = lexi_prompts.use_prompt(lexi_prompts.query_translator, query_txt=query_txt)
 
-    response = client.chat.completions.create(
-        model="meta-llama/Llama-3.2-3B-Instruct-Turbo",
-        messages=[{"role": "user", "content": prompt}],
-        max_tokens=512,
-        temperature=0.3
-    )
-    return response.choices[0].message.content
+    headers = {
+        "Authorization": f"Bearer {TOGETHER_API_KEY}",
+        "Content-Type": "application/json"
+    }
+    payload = {
+        "model": "meta-llama/Llama-3.2-3B-Instruct-Turbo",
+        "messages": [{"role": "user", "content": prompt}],
+        "max_tokens": 512,
+        "temperature": 0.3
+    }
+    
+    try:
+        response = requests.post("https://api.together.xyz/v1/chat/completions", headers=headers, json=payload, timeout=60)
+        response.raise_for_status() # HTTP 오류가 발생하면 예외 발생
+
+        data = response.json()
+        return data["choices"][0]["message"]["content"]
+    except requests.exceptions.RequestException as e:
+        print(f"Together AI 번역 API 호출 실패: {e}")
+        traceback.print_exc()
+        return query_txt # 번역 실패 시 원래 쿼리를 사용 (최소한의 기능 유지)
 
 # --- 검색 ---
 def search_DB_from_multiple_regions(query, selected_regions, region_rag_objects):