mirror of
https://github.com/linyqh/NarratoAI.git
synced 2025-12-11 18:42:49 +00:00
eaa8ceb7e3
- 优化了基本设置中的文本生成模型提供商选择 - 重新设计了脚本生成器的架构，提高了可扩展性和维护性 - 为 OpenAI、Gemini、Qwen 和 Moonshot 生成器实现了统一的接口和流程 - 移除了字数控制要求，简化了生成逻辑
237 lines
8.9 KiB
Python
237 lines
8.9 KiB
Python
import streamlit as st
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import os
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from app.config import config
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from app.utils import utils
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def render_basic_settings(tr):
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"""渲染基础设置面板"""
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with st.expander(tr("Basic Settings"), expanded=False):
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config_panels = st.columns(3)
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left_config_panel = config_panels[0]
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middle_config_panel = config_panels[1]
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right_config_panel = config_panels[2]
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with left_config_panel:
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render_language_settings(tr)
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render_proxy_settings(tr)
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with middle_config_panel:
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render_vision_llm_settings(tr) # 视频分析模型设置
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with right_config_panel:
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render_text_llm_settings(tr) # 文案生成模型设置
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def render_language_settings(tr):
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st.subheader(tr("Proxy Settings"))
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"""渲染语言设置"""
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system_locale = utils.get_system_locale()
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i18n_dir = os.path.join(os.path.dirname(os.path.dirname(__file__)), "i18n")
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locales = utils.load_locales(i18n_dir)
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display_languages = []
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selected_index = 0
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for i, code in enumerate(locales.keys()):
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display_languages.append(f"{code} - {locales[code].get('Language')}")
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if code == st.session_state.get('ui_language', system_locale):
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selected_index = i
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selected_language = st.selectbox(
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tr("Language"),
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options=display_languages,
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index=selected_index
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)
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if selected_language:
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code = selected_language.split(" - ")[0].strip()
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st.session_state['ui_language'] = code
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config.ui['language'] = code
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def render_proxy_settings(tr):
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"""渲染代理设置"""
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proxy_url_http = config.proxy.get("http", "") or os.getenv("VPN_PROXY_URL", "")
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proxy_url_https = config.proxy.get("https", "") or os.getenv("VPN_PROXY_URL", "")
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HTTP_PROXY = st.text_input(tr("HTTP_PROXY"), value=proxy_url_http)
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HTTPS_PROXY = st.text_input(tr("HTTPs_PROXY"), value=proxy_url_https)
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if HTTP_PROXY:
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config.proxy["http"] = HTTP_PROXY
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os.environ["HTTP_PROXY"] = HTTP_PROXY
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if HTTPS_PROXY:
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config.proxy["https"] = HTTPS_PROXY
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os.environ["HTTPS_PROXY"] = HTTPS_PROXY
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def render_vision_llm_settings(tr):
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"""渲染视频分析模型设置"""
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st.subheader(tr("Vision Model Settings"))
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# 视频分析模型提供商选择
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vision_providers = ['Gemini', 'NarratoAPI']
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saved_vision_provider = config.app.get("vision_llm_provider", "Gemini").lower()
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saved_provider_index = 0
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for i, provider in enumerate(vision_providers):
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if provider.lower() == saved_vision_provider:
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saved_provider_index = i
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break
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vision_provider = st.selectbox(
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tr("Vision Model Provider"),
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options=vision_providers,
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index=saved_provider_index
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)
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vision_provider = vision_provider.lower()
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config.app["vision_llm_provider"] = vision_provider
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st.session_state['vision_llm_providers'] = vision_provider
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# 获取已保存的视觉模型配置
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vision_api_key = config.app.get(f"vision_{vision_provider}_api_key", "")
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vision_base_url = config.app.get(f"vision_{vision_provider}_base_url", "")
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vision_model_name = config.app.get(f"vision_{vision_provider}_model_name", "")
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# 渲染视觉模型配置输入框
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st_vision_api_key = st.text_input(tr("Vision API Key"), value=vision_api_key, type="password")
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st_vision_base_url = st.text_input(tr("Vision Base URL"), value=vision_base_url)
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st_vision_model_name = st.text_input(tr("Vision Model Name"), value=vision_model_name)
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# 保存视觉模型配置
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if st_vision_api_key:
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config.app[f"vision_{vision_provider}_api_key"] = st_vision_api_key
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st.session_state[f"vision_{vision_provider}_api_key"] = st_vision_api_key # 用于script_settings.py
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if st_vision_base_url:
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config.app[f"vision_{vision_provider}_base_url"] = st_vision_base_url
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st.session_state[f"vision_{vision_provider}_base_url"] = st_vision_base_url
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if st_vision_model_name:
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config.app[f"vision_{vision_provider}_model_name"] = st_vision_model_name
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st.session_state[f"vision_{vision_provider}_model_name"] = st_vision_model_name
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# NarratoAPI 特殊配置
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if vision_provider == 'narratoapi':
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st.subheader(tr("Narrato Additional Settings"))
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# Narrato API 基础配置
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narrato_api_key = st.text_input(
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tr("Narrato API Key"),
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value=config.app.get("narrato_api_key", ""),
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type="password",
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help="用于访问 Narrato API 的密钥"
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)
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if narrato_api_key:
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config.app["narrato_api_key"] = narrato_api_key
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st.session_state['narrato_api_key'] = narrato_api_key
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narrato_api_url = st.text_input(
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tr("Narrato API URL"),
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value=config.app.get("narrato_api_url", "http://127.0.0.1:8000/api/v1/video/analyze")
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)
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if narrato_api_url:
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config.app["narrato_api_url"] = narrato_api_url
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st.session_state['narrato_api_url'] = narrato_api_url
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# 视频分析模型配置
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st.markdown("##### " + tr("Vision Model Settings"))
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narrato_vision_model = st.text_input(
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tr("Vision Model Name"),
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value=config.app.get("narrato_vision_model", "gemini-1.5-flash")
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)
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narrato_vision_key = st.text_input(
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tr("Vision Model API Key"),
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value=config.app.get("narrato_vision_key", ""),
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type="password",
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help="用于视频分析的模型 API Key"
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)
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if narrato_vision_model:
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config.app["narrato_vision_model"] = narrato_vision_model
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st.session_state['narrato_vision_model'] = narrato_vision_model
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if narrato_vision_key:
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config.app["narrato_vision_key"] = narrato_vision_key
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st.session_state['narrato_vision_key'] = narrato_vision_key
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# 文案生成模型配置
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st.markdown("##### " + tr("Text Generation Model Settings"))
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narrato_llm_model = st.text_input(
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tr("LLM Model Name"),
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value=config.app.get("narrato_llm_model", "qwen-plus")
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)
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narrato_llm_key = st.text_input(
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tr("LLM Model API Key"),
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value=config.app.get("narrato_llm_key", ""),
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type="password",
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help="用于文案生成的模型 API Key"
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)
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if narrato_llm_model:
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config.app["narrato_llm_model"] = narrato_llm_model
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st.session_state['narrato_llm_model'] = narrato_llm_model
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if narrato_llm_key:
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config.app["narrato_llm_key"] = narrato_llm_key
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st.session_state['narrato_llm_key'] = narrato_llm_key
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# 批处理配置
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narrato_batch_size = st.number_input(
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tr("Batch Size"),
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min_value=1,
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max_value=50,
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value=config.app.get("narrato_batch_size", 10),
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help="每批处理的图片数量"
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)
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if narrato_batch_size:
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config.app["narrato_batch_size"] = narrato_batch_size
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st.session_state['narrato_batch_size'] = narrato_batch_size
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def render_text_llm_settings(tr):
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"""渲染文案生成模型设置"""
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st.subheader(tr("Text Generation Model Settings"))
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# 文案生成模型提供商选择
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text_providers = ['OpenAI', 'Qwen', 'Moonshot', 'Gemini']
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saved_text_provider = config.app.get("text_llm_provider", "OpenAI").lower()
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saved_provider_index = 0
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for i, provider in enumerate(text_providers):
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if provider.lower() == saved_text_provider:
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saved_provider_index = i
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break
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text_provider = st.selectbox(
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tr("Text Model Provider"),
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options=text_providers,
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index=saved_provider_index
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)
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text_provider = text_provider.lower()
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config.app["text_llm_provider"] = text_provider
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# 获取已保存的文本模型配置
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text_api_key = config.app.get(f"text_{text_provider}_api_key", "")
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text_base_url = config.app.get(f"text_{text_provider}_base_url", "")
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text_model_name = config.app.get(f"text_{text_provider}_model_name", "")
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# 渲染文本模型配置输入框
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st_text_api_key = st.text_input(tr("Text API Key"), value=text_api_key, type="password")
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st_text_base_url = st.text_input(tr("Text Base URL"), value=text_base_url)
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st_text_model_name = st.text_input(tr("Text Model Name"), value=text_model_name)
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# 保存文本模型配置
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if st_text_api_key:
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config.app[f"text_{text_provider}_api_key"] = st_text_api_key
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if st_text_base_url:
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config.app[f"text_{text_provider}_base_url"] = st_text_base_url
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if st_text_model_name:
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config.app[f"text_{text_provider}_model_name"] = st_text_model_name
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# Cloudflare 特殊配置
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if text_provider == 'cloudflare':
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st_account_id = st.text_input(
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tr("Account ID"),
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value=config.app.get(f"text_{text_provider}_account_id", "")
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)
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if st_account_id:
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config.app[f"text_{text_provider}_account_id"] = st_account_id
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