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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)
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