Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,149 @@
-import altair as alt
-import numpy as np
-import pandas as pd
+import os, io, time, json, re, requests
+from io import BytesIO
+from PIL import Image
 import streamlit as st
+from google import genai
 
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+st.set_page_config(page_title="멀티모달 LLM 데모 (Gemma 3 27B)", page_icon="🤖", layout="wide")
+
+# ===== Sidebar: 설정 =====
+st.sidebar.title("🔧 설정")
+api_key = st.sidebar.text_input("GOOGLE_API_KEY", value=os.getenv("GOOGLE_API_KEY", ""), type="password")
+model_name = st.sidebar.selectbox("모델", ["gemma-3-27b-it"], index=0)
+rate_delay = st.sidebar.number_input("호출간 대기(초)", value=1.0, step=0.5, min_value=0.0)
+
+if not api_key:
+    st.warning("사이드바에 GOOGLE_API_KEY를 입력하거나 환경변수로 설정해 주세요.")
+    st.stop()
+
+client = genai.Client(api_key=api_key)
+
+# ===== 유틸 =====
+RETRY_LIMIT = 3
+
+def load_image(source: str) -> Image.Image:
+    """URL/로컬 모두 지원 + 투명 배경 보정."""
+    session = requests.Session()
+    session.headers.update({"User-Agent": "Mozilla/5.0"})
+    last_err = None
+    for _ in range(RETRY_LIMIT):
+        try:
+            if source.startswith(("http://", "https://")):
+                resp = session.get(source, timeout=10)
+                resp.raise_for_status()
+                img = Image.open(BytesIO(resp.content))
+            else:
+                img = Image.open(source)
+
+            if img.mode in ("RGBA", "LA", "P"):
+                bg = Image.new("RGB", img.size, (255, 255, 255))
+                img = img.convert("RGBA")
+                bg.paste(img, mask=img.split()[-1] if len(img.split()) > 3 else None)
+                img = bg
+            else:
+                img = img.convert("RGB")
+            return img
+        except Exception as e:
+            last_err = e
+            time.sleep(0.5)
+    raise RuntimeError(f"이미지 로드 실패: {last_err}")
+
+RESET_PROMPT = "이전 대화는 무시하고, 아래 지시에만 응답하세요.\n\n"
+
+def try_parse_json(raw_text: str):
+    """응답에서 JSON 추출 시도."""
+    pattern = r'```(?:json)?\s*(\{[\s\S]*?\})\s*```|(\{[\s\S]*?\})'
+    for g1, g2 in re.findall(pattern, raw_text):
+        cand = (g1 or g2).strip()
+        try:
+            return json.loads(cand)
+        except json.JSONDecodeError:
+            pass
+    cleaned = re.sub(r'```json|```', '', raw_text).strip()
+    try:
+        return json.loads(cleaned)
+    except json.JSONDecodeError:
+        return None
+
+def infer_text(article: str, prompt: str):
+    contents = [RESET_PROMPT + prompt.strip() + "\n\n" + article.strip()]
+    resp = client.models.generate_content(model=model_name, contents=contents)
+    time.sleep(rate_delay)
+    text = (resp.text or "").strip()
+    parsed = try_parse_json(text)
+    return parsed if parsed is not None else {"text": text}
+
+def infer_image(image: Image.Image, prompt: str):
+    contents = [RESET_PROMPT + prompt.strip(), image]
+    resp = client.models.generate_content(model=model_name, contents=contents)
+    time.sleep(rate_delay)
+    text = (resp.text or "").strip()
+    parsed = try_parse_json(text)
+    return parsed if parsed is not None else {"text": text}
+
+# ===== 기본 프롬프트(간결 버전) =====
+TEXT_PROMPT = (
+    "당신은 기사 정보원 분석 전문가입니다. 다음 기사에서 정보원을 추출하고, "
+    "정보원별 묘사 프레임을 긍정/중립/부정으로 판정해 JSON으로만 출력하세요.\n"
+    '예시: {"sources": ["정보원A","정보원B"], "frames": ["중립","부정"]}'
+)
+
+IMAGE_PROMPT = (
+    "당신은 보도사진 분석 전문가입니다. 제공된 사진에서 Donald Trump 존재 여부를 판단하고 "
+    "감정(emotion: positive/negative/neutral)과 역동성(dynamism: high/medium/low)을 평가해 "
+    'JSON으로만 출력하세요. Trump가 없으면 {"trump_present": false}만 반환하세요.'
+)
+
+# ===== UI =====
+st.title("🤖 멀티모달 LLM 데모 (Gemma 3 27B)")
+tab_text, tab_img = st.tabs(["📝 텍스트 분석", "🖼️ 이미지 분석"])
+
+with tab_text:
+    st.subheader("기사 텍스트 → 정보원 & 프레임 판정")
+    article = st.text_area(
+        "기사 본문", height=180,
+        value="Donald Trump와 Nancy Pelosi가 회의장에서 격렬히 논쟁을 벌였다..."
+    )
+    user_prompt = st.text_area("프롬프트(옵션)", value=TEXT_PROMPT, height=120)
+    if st.button("텍스트 분석 실행", type="primary", use_container_width=True):
+        if not article.strip():
+            st.error("기사 본문을 입력해 주세요.")
+        else:
+            with st.spinner("분석 중..."):
+                try:
+                    result = infer_text(article, user_prompt or TEXT_PROMPT)
+                    st.success("완료")
+                    st.json(result)
+                    st.download_button("결과 JSON 다운로드", data=json.dumps(result, ensure_ascii=False, indent=2),
+                                       file_name="text_result.json", mime="application/json")
+                except Exception as e:
+                    st.error(f"오류: {e}")
+
+with tab_img:
+    st.subheader("보도사진 → 인물 존재·감정·역동성 분석")
+    col1, col2 = st.columns(2)
+    with col1:
+        img_url = st.text_input("이미지 URL")
+    with col2:
+        file = st.file_uploader("이미지 업로드", type=["jpg","jpeg","png","webp","gif","bmp"])
+
+    img_prompt = st.text_area("프롬프트(옵션)", value=IMAGE_PROMPT, height=120)
+    if st.button("이미지 분석 실행", type="primary", use_container_width=True):
+        try:
+            if file is not None:
+                image = Image.open(io.BytesIO(file.read())).convert("RGB")
+            elif img_url.strip():
+                image = load_image(img_url.strip())
+            else:
+                st.error("이미지 URL을 입력하거나 파일을 업로드해 주세요.")
+                st.stop()
+
+            st.image(image, caption="입력 이미지", use_container_width=True)
+            with st.spinner("분석 중..."):
+                result = infer_image(image, img_prompt or IMAGE_PROMPT)
+            st.success("완료")
+            st.json(result)
+            st.download_button("결과 JSON 다운로드", data=json.dumps(result, ensure_ascii=False, indent=2),
+                               file_name="image_result.json", mime="application/json")
+        except Exception as e:
+            st.error(f"오류: {e}")