Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,62 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
-
-"""
-# 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])),
-    ))
+import requests
+import base64
+from PIL import Image
+from io import BytesIO
+
+# ───────────────────────────────
+# CONFIG
+# ───────────────────────────────
+st.set_page_config(page_title="동화 삽화 생성기", layout="wide")
+API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-Kontext-dev"
+headers = {"Authorization": f"Bearer {st.secrets['HF_TOKEN']}"}
+
+# ───────────────────────────────
+# UTILS
+# ───────────────────────────────
+def query_flux(prompt, image_bytes=None):
+    inputs = {"prompt": prompt}
+    if image_bytes:
+        inputs["image"] = base64.b64encode(image_bytes).decode("utf-8")
+
+    response = requests.post(API_URL, headers=headers, json=inputs)
+    if response.status_code == 200:
+        image_data = base64.b64decode(response.json()["image"])
+        return Image.open(BytesIO(image_data))
+    else:
+        st.error(f"Error: {response.status_code} - {response.text}")
+        return None
+
+# ───────────────────────────────
+# UI
+# ───────────────────────────────
+st.title("📚 동화 삽화 생성기 (FLUX.1 Kontext)")
+st.markdown("각 장면의 설명을 입력하면, 이야기 흐름에 맞는 삽화를 자동으로 생성합니다.")
+
+with st.expander("등장인물 및 스타일 정보 (선택)"):
+    character_prompt = st.text_area("등장인물 설명 (ex. 빨간 망토를 쓴 소녀, 회색 늑대 등)", height=100)
+    reference_image = st.file_uploader("참조 이미지 업로드 (선택)", type=["jpg", "png"])
+
+st.markdown("### 📝 동화 내용을 5개 장면으로 나누어 입력하세요")
+
+scene_prompts = []
+for i in range(5):
+    text = st.text_area(f"장면 {i+1} 설명", key=f"scene_{i}", height=80)
+    scene_prompts.append(text)
+
+if st.button("🎨 삽화 생성하기"):
+    if not any(scene_prompts):
+        st.warning("최소 하나 이상의 장면 설명이 필요합니다.")
+    else:
+        ref_bytes = reference_image.read() if reference_image else None
+
+        with st.spinner("이미지를 생성 중입니다..."):
+            cols = st.columns(5)
+            for i, prompt in enumerate(scene_prompts):
+                if not prompt.strip():
+                    continue
+
+                full_prompt = f"{character_prompt}. {prompt}" if character_prompt else prompt
+                img = query_flux(full_prompt, ref_bytes)
+                if img:
+                    cols[i].image(img, caption=f"장면 {i+1}")