Update app.py

app.py

@@ -15,10 +15,10 @@ from typing import Iterator
 
 import streamlit as st
 import pandas as pd
-import PyPDF2  # For handling PDF files
+import PyPDF2                       # For handling PDF files
 from collections import Counter
 
-from openai import OpenAI  # OpenAI 라이브러리
+from openai import OpenAI, APIError, APITimeoutError   # ⬅️ OpenAI 오류형 포함
 from gradio_client import Client
 from kaggle.api.kaggle_api_extended import KaggleApi
 import tempfile
@@ -30,6 +30,11 @@ import pyarrow.parquet as pq
 from sklearn.feature_extraction.text import TfidfVectorizer
 from sklearn.metrics.pairwise import cosine_similarity
 
+# ─── NEW : 네트워크 안정화용 라이브러리 ──────────────────────────────
+import httpx
+from httpx import RemoteProtocolError
+import backoff                       # ⬅️ 자동 재시도 데코레이터
+
 # ─────────────────────────────── Environment Variables / Constants ─────────────────────────
 
 OPENAI_API_KEY   = os.getenv("OPENAI_API_KEY", "")
@@ -44,9 +49,12 @@ if not (KAGGLE_USERNAME and KAGGLE_KEY):
 os.environ["KAGGLE_USERNAME"] = KAGGLE_USERNAME
 os.environ["KAGGLE_KEY"]      = KAGGLE_KEY
 
+# ▶ 일부 프록시에서 HTTP/2 → 1.1 강제 전환이 필요할 때 활성화
+# os.environ["HTTPX_FORCE_HTTP1"] = "true"
+
 BRAVE_ENDPOINT   = "https://api.search.brave.com/res/v1/web/search"
 IMAGE_API_URL    = "http://211.233.58.201:7896"  # 예시 이미지 생성용 API
-MAX_TOKENS       = 7999
+MAX_TOKENS       = 7999       
 
 # ─────────────────────────────── Logging ───────────────────────────────
 logging.basicConfig(
@@ -54,6 +62,7 @@ logging.basicConfig(
     format="%(asctime)s - %(levelname)s - %(message)s"
 )
 
+
 # ─────────────────────────────── 군사(밀리터리) 전술 데이터셋 로드 ─────────────────
 @st.cache_resource
 def load_military_dataset():
@@ -2029,12 +2038,15 @@ def process_example(topic):
 def process_input(prompt: str, uploaded_files):
     """
     메인 채팅 입력을 받아 디자인/발명 아이디어를 생성한다.
+    스트리밍 중단(HTTPX RemoteProtocolError 등) 시 자동 재시도,
+    최종 실패 시 non-stream 호출로 폴백하도록 개선.
     """
     if not any(m["role"] == "user" and m["content"] == prompt for m in st.session_state.messages):
         st.session_state.messages.append({"role": "user", "content": prompt})
     with st.chat_message("user"):
         st.markdown(prompt)
 
+    # 동일 프롬프트-응답 중복 방지
     for i in range(len(st.session_state.messages) - 1):
         if (st.session_state.messages[i]["role"] == "user"
             and st.session_state.messages[i]["content"] == prompt
@@ -2050,7 +2062,7 @@ def process_input(prompt: str, uploaded_files):
             client = get_openai_client()
             status.update(label="Initializing model…")
 
-            selected_cat = st.session_state.get("category_focus", None)
+            selected_cat        = st.session_state.get("category_focus", None)
             selected_frameworks = st.session_state.get("selected_frameworks", [])
 
             # 목적이 "디자인/발명"이므로, system prompt 변경
@@ -2068,9 +2080,7 @@ def process_input(prompt: str, uploaded_files):
             use_kaggle     = st.session_state.kaggle_enabled
             has_uploaded   = bool(uploaded_files)
 
-            search_content  = None
-            kaggle_content  = None
-            file_content    = None
+            search_content = kaggle_content = file_content = mil_content = None  # 초기화
 
             # ① 웹검색
             if use_web_search:
@@ -2108,7 +2118,6 @@ def process_input(prompt: str, uploaded_files):
                     file_content = process_uploaded_files(uploaded_files)
 
             # ④ 군사 전술 데이터 (필요 시)
-            mil_content = None
             if is_military_query(prompt):
                 status.update(label="Searching military tactics dataset…")
                 with st.spinner("Loading military insights…"):
@@ -2123,15 +2132,11 @@ def process_input(prompt: str, uploaded_files):
                             f"**Defense Reasoning:** {row['defense_reasoning']}\n\n---\n"
                         )
 
+            # 사용자 프롬프트 + 참조자료 결합
             user_content = prompt
-            if search_content:
-                user_content += "\n\n" + search_content
-            if kaggle_content:
-                user_content += "\n\n" + kaggle_content
-            if file_content:
-                user_content += "\n\n" + file_content
-            if mil_content:
-                user_content += "\n\n" + mil_content
+            for _extra in (search_content, kaggle_content, file_content, mil_content):
+                if _extra:
+                    user_content += "\n\n" + _extra
 
             # 내부 분석
             status.update(label="분석 중…")
@@ -2168,22 +2173,22 @@ def process_input(prompt: str, uploaded_files):
                 for c, s in decision_purpose['constraints']:
                     purpose_info += f"- **{c}** (관련성: {s})\n"
 
-            # 프레임워크 적용 결과 (현재 목적이 디자인/발명 -> 선택적으로 표시)
+            # 기타 프레임워크
             framework_contents = []
             for fw in selected_frameworks:
                 if fw == "swot":
-                    swot_res = analyze_with_swot(prompt)
-                    framework_contents.append(format_business_framework_analysis("swot", swot_res))
+                    framework_contents.append(
+                        format_business_framework_analysis("swot", analyze_with_swot(prompt))
+                    )
                 elif fw == "porter":
-                    porter_res = analyze_with_porter(prompt)
-                    framework_contents.append(format_business_framework_analysis("porter", porter_res))
+                    framework_contents.append(
+                        format_business_framework_analysis("porter", analyze_with_porter(prompt))
+                    )
                 elif fw == "bcg":
-                    bcg_res = analyze_with_bcg(prompt)
-                    framework_contents.append(format_business_framework_analysis("bcg", bcg_res))
-                elif fw == "sunzi":
-                    # 손자병법 예시
-                    # (실제로는 별도 로직이 필요하나 여기선 생략)
-                    pass
+                    framework_contents.append(
+                        format_business_framework_analysis("bcg", analyze_with_bcg(prompt))
+                    )
+                # sunzi 등 필요 시 추가
 
             if framework_contents:
                 user_content += "\n\n## (Optional) 기타 프레임워크 분석\n\n" + "\n\n".join(framework_contents)
@@ -2191,29 +2196,54 @@ def process_input(prompt: str, uploaded_files):
             user_content += f"\n\n## 카테고리 매트릭스 분석{purpose_info}\n{combos_table}"
 
             status.update(label="Generating final design/invention ideas…")
+
             api_messages = [
                 {"role": "system", "content": sys_prompt},
                 {"role": "system", "name": "category_db", "content": category_context(selected_cat)},
                 {"role": "user",   "content": user_content},
             ]
-            stream = client.chat.completions.create(
-                model="gpt-4.1-mini",
-                messages=api_messages,
-                temperature=1,
-                max_tokens=MAX_TOKENS,
-                top_p=1,
-                stream=True
+
+            # ─────────────────────────────────────────────────────────────
+            # ⬇️ 1. 안전한 스트리밍 호출 (backoff 재시도)
+            @backoff.on_exception(
+                backoff.expo,
+                (RemoteProtocolError, APITimeoutError, APIError),
+                max_tries=3,
+                jitter=None
             )
+            def safe_stream_chat():
+                return client.chat.completions.create(
+                    model="gpt-4.1-mini",
+                    messages=api_messages,
+                    temperature=1,
+                    max_tokens=MAX_TOKENS,
+                    top_p=1,
+                    stream=True
+                )
 
-            for chunk in stream:
-                if chunk.choices and chunk.choices[0].delta.content:
-                    full_response += chunk.choices[0].delta.content
-                    stream_placeholder.markdown(full_response + "▌")
+            try:
+                stream = safe_stream_chat()
+                for chunk in stream:
+                    if chunk.choices and chunk.choices[0].delta.content:
+                        full_response += chunk.choices[0].delta.content
+                        stream_placeholder.markdown(full_response + "▌")
+            except (RemoteProtocolError, APITimeoutError, APIError) as stream_err:
+                logging.warning(f"💡 스트리밍 중단, non-stream으로 폴백: {stream_err}")
+                resp = client.chat.completions.create(
+                    model="gpt-4.1-mini",
+                    messages=api_messages,
+                    temperature=1,
+                    max_tokens=MAX_TOKENS,
+                    top_p=1,
+                    stream=False
+                )
+                full_response = resp.choices[0].message.content
+                stream_placeholder.markdown(full_response)
+            # ────────────────────────────────────────────────────────────���
 
-            stream_placeholder.markdown(full_response)
             status.update(label="Invention ideas created!", state="complete")
 
-            # 이미지 생성
+            # 자동 이미지 생성
             img_data = img_caption = None
             if st.session_state.generate_image and full_response:
                 match = re.search(r"###\s*이미지\s*프롬프트\s*\n+([^\n]+)", full_response, re.I)
@@ -2226,6 +2256,7 @@ def process_input(prompt: str, uploaded_files):
                     if img_data:
                         st.image(img_data, caption=f"Visualized Concept – {img_caption}")
 
+            # 세션 메시지 업데이트
             answer_msg = {"role": "assistant", "content": full_response}
             if img_data:
                 answer_msg["image"]         = img_data