Create app.py

src/app.py

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+# app.py
+import streamlit as st
+from cerebras.cloud.sdk import Cerebras
+import openai
+import os
+from dotenv import load_dotenv
+
+# --- Assuming config.py and utils.py exist ---
+import config
+import utils
+
+# --- BASE_PROMPT のインポート ---
+try:
+    from prompt import BASE_PROMPT
+except ImportError:
+    st.error(
+        "Error: 'prompt.py' not found or 'BASE_PROMPT' is not defined within it.")
+    st.stop()
+
+# --- Import column rendering functions ---
+from chat_column import render_chat_column
+
+# --- 環境変数読み込み ---
+load_dotenv()
+
+# --- Streamlit ページ設定 ---
+st.set_page_config(page_icon="🤖x🎬", layout="wide",
+                   page_title="Veo3 JSON Creator")
+
+# --- UI 表示 ---
+utils.display_icon("🤖x🎬")
+st.title("Veo3 JSON Creator")
+st.subheader("Generate json for Veo3",
+             divider="blue", anchor=False)
+
+# --- APIキーの処理 ---
+# (API Key logic remains the same)
+api_key_from_env = os.getenv("CEREBRAS_API_KEY")
+show_api_key_input = not bool(api_key_from_env)
+cerebras_api_key = None
+
+# --- サイドバーの設定 ---
+# (Sidebar logic remains the same)
+with st.sidebar:
+    st.title("Settings")
+    # Cerebras Key Input
+    if show_api_key_input:
+        st.markdown("### :red[Enter your Cerebras API Key below]")
+        api_key_input = st.text_input(
+            "Cerebras API Key:", type="password", key="cerebras_api_key_input_field")
+        if api_key_input:
+            cerebras_api_key = api_key_input
+    else:
+        cerebras_api_key = api_key_from_env
+        st.success("✓ Cerebras API Key loaded from environment")
+
+    # Model selection
+    model_option = st.selectbox(
+        "Choose a LLM model:",
+        options=list(config.MODELS.keys()),
+        format_func=lambda x: config.MODELS[x]["name"],
+        key="model_select"
+    )
+    # Max tokens slider
+    max_tokens_range = config.MODELS[model_option]["tokens"]
+    default_tokens = min(2048, max_tokens_range)
+    max_tokens = st.slider(
+        "Max Tokens (LLM):",
+        min_value=512,
+        max_value=max_tokens_range,
+        value=default_tokens,
+        step=512,
+        help="Max tokens for the LLM's text prompt response."
+    )
+
+
+# --- メインアプリケーションロジック ---
+# Re-check Cerebras API key
+if not cerebras_api_key and show_api_key_input and 'cerebras_api_key_input_field' in st.session_state and st.session_state.cerebras_api_key_input_field:
+    cerebras_api_key = st.session_state.cerebras_api_key_input_field
+
+if not cerebras_api_key:
+    st.error("Cerebras API Key is required. Please enter it in the sidebar or set the CEREBRAS_API_KEY environment variable.", icon="🚨")
+    st.stop()
+
+# APIクライアント初期化
+# (Client initialization remains the same)
+llm_client = None
+image_client = None
+try:
+    llm_client = Cerebras(api_key=cerebras_api_key)
+except Exception as e:
+    st.error(f"Failed to initialize API client(s): {str(e)}", icon="🚨")
+    st.stop()
+
+
+# --- Session State Initialization ---
+# Initialize state variables if they don't exist
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+if "current_image_prompt_text" not in st.session_state:
+    st.session_state.current_image_prompt_text = ""
+# --- MODIFICATION START ---
+# Replace single image state with a list to store multiple images and their prompts
+if "generated_images_list" not in st.session_state:
+    st.session_state.generated_images_list = []  # Initialize as empty list
+# Remove old state variable if it exists (optional cleanup)
+if "latest_generated_image" in st.session_state:
+    del st.session_state["latest_generated_image"]
+# --- MODIFICATION END ---
+if "selected_model" not in st.session_state:
+    st.session_state.selected_model = None
+
+
+# --- Track selected model, but do not clear chat or image state on model change ---
+if st.session_state.selected_model != model_option:
+    st.session_state.selected_model = model_option
+    # Optionally rerun to update UI, but do not clear messages or images
+    st.rerun()
+
+# --- Define Main Columns ---
+chat_col, image_col = st.columns([2, 1])
+
+# --- Render Columns using imported functions ---
+with chat_col:
+    render_chat_column(st, llm_client, model_option, max_tokens, BASE_PROMPT)
+
+# --- Footer ---
+st.markdown('<div style="text-align: center; margin-top: 2em; color: #888; font-size: 1.1em;">made with 💙 by baxin</div>', unsafe_allow_html=True)