mirror of
https://github.com/linyqh/NarratoAI.git
synced 2025-12-10 18:02:51 +00:00
f44d56110e
- 新增 QwenVL 视觉分析器类，实现对阿里云 Qwen 模型的支持 - 更新基础设置界面，增加代理配置和 QwenVL 模型可用性检测 - 修改脚本生成逻辑，支持 QwenVL 模型的图像分析 - 重构视觉分析器初始化和调用接口，提高代码复用性和可维护性
374 lines
13 KiB
Python
374 lines
13 KiB
Python
import streamlit as st
|
||
import os
|
||
from app.config import config
|
||
from app.utils import utils
|
||
|
||
|
||
def render_basic_settings(tr):
|
||
"""渲染基础设置面板"""
|
||
with st.expander(tr("Basic Settings"), expanded=False):
|
||
config_panels = st.columns(3)
|
||
left_config_panel = config_panels[0]
|
||
middle_config_panel = config_panels[1]
|
||
right_config_panel = config_panels[2]
|
||
|
||
with left_config_panel:
|
||
render_language_settings(tr)
|
||
render_proxy_settings(tr)
|
||
|
||
with middle_config_panel:
|
||
render_vision_llm_settings(tr) # 视频分析模型设置
|
||
|
||
with right_config_panel:
|
||
render_text_llm_settings(tr) # 文案生成模型设置
|
||
|
||
|
||
def render_language_settings(tr):
|
||
st.subheader(tr("Proxy Settings"))
|
||
|
||
"""渲染语言设置"""
|
||
system_locale = utils.get_system_locale()
|
||
i18n_dir = os.path.join(os.path.dirname(os.path.dirname(__file__)), "i18n")
|
||
locales = utils.load_locales(i18n_dir)
|
||
|
||
display_languages = []
|
||
selected_index = 0
|
||
for i, code in enumerate(locales.keys()):
|
||
display_languages.append(f"{code} - {locales[code].get('Language')}")
|
||
if code == st.session_state.get('ui_language', system_locale):
|
||
selected_index = i
|
||
|
||
selected_language = st.selectbox(
|
||
tr("Language"),
|
||
options=display_languages,
|
||
index=selected_index
|
||
)
|
||
|
||
if selected_language:
|
||
code = selected_language.split(" - ")[0].strip()
|
||
st.session_state['ui_language'] = code
|
||
config.ui['language'] = code
|
||
|
||
|
||
def render_proxy_settings(tr):
|
||
"""渲染代理设置"""
|
||
# 获取当前代理状态
|
||
proxy_enabled = config.proxy.get("enabled", True)
|
||
proxy_url_http = config.proxy.get("http")
|
||
proxy_url_https = config.proxy.get("https")
|
||
|
||
# 添加代理开关
|
||
proxy_enabled = st.checkbox(tr("Enable Proxy"), value=proxy_enabled)
|
||
|
||
# 保存代理开关状态
|
||
config.proxy["enabled"] = proxy_enabled
|
||
|
||
# 只有在代理启用时才显示代理设置输入框
|
||
if proxy_enabled:
|
||
HTTP_PROXY = st.text_input(tr("HTTP_PROXY"), value=proxy_url_http)
|
||
HTTPS_PROXY = st.text_input(tr("HTTPs_PROXY"), value=proxy_url_https)
|
||
|
||
if HTTP_PROXY:
|
||
config.proxy["http"] = HTTP_PROXY
|
||
os.environ["HTTP_PROXY"] = HTTP_PROXY
|
||
if HTTPS_PROXY:
|
||
config.proxy["https"] = HTTPS_PROXY
|
||
os.environ["HTTPS_PROXY"] = HTTPS_PROXY
|
||
else:
|
||
# 当代理被禁用时，清除环境变量和配置
|
||
os.environ.pop("HTTP_PROXY", None)
|
||
os.environ.pop("HTTPS_PROXY", None)
|
||
config.proxy["http"] = ""
|
||
config.proxy["https"] = ""
|
||
|
||
|
||
def test_vision_model_connection(api_key, base_url, model_name, provider, tr):
|
||
"""测试视觉模型连接
|
||
|
||
Args:
|
||
api_key: API密钥
|
||
base_url: 基础URL
|
||
model_name: 模型名称
|
||
provider: 提供商名称
|
||
|
||
Returns:
|
||
bool: 连接是否成功
|
||
str: 测试结果消息
|
||
"""
|
||
if provider.lower() == 'gemini':
|
||
import google.generativeai as genai
|
||
|
||
try:
|
||
genai.configure(api_key=api_key)
|
||
model = genai.GenerativeModel(model_name)
|
||
model.generate_content("直接回复我文本'当前网络可用'")
|
||
return True, tr("gemini model is available")
|
||
except Exception as e:
|
||
return False, f"{tr('gemini model is not available')}: {str(e)}"
|
||
|
||
elif provider.lower() == 'qwenvl':
|
||
from openai import OpenAI
|
||
try:
|
||
client = OpenAI(
|
||
api_key=api_key,
|
||
base_url=base_url or "https://dashscope.aliyuncs.com/compatible-mode/v1"
|
||
)
|
||
|
||
# 发送一个简单的测试请求
|
||
response = client.chat.completions.create(
|
||
model=model_name or "qwen-vl-max-latest",
|
||
messages=[{"role": "user", "content": "直接回复我文本'当前网络可用'"}]
|
||
)
|
||
|
||
if response and response.choices:
|
||
return True, tr("QwenVL model is available")
|
||
else:
|
||
return False, tr("QwenVL model returned invalid response")
|
||
|
||
except Exception as e:
|
||
return False, f"{tr('QwenVL model is not available')}: {str(e)}"
|
||
|
||
elif provider.lower() == 'narratoapi':
|
||
import requests
|
||
try:
|
||
# 构建测试请求
|
||
headers = {
|
||
"Authorization": f"Bearer {api_key}"
|
||
}
|
||
|
||
test_url = f"{base_url.rstrip('/')}/health"
|
||
response = requests.get(test_url, headers=headers, timeout=10)
|
||
|
||
if response.status_code == 200:
|
||
return True, tr("NarratoAPI is available")
|
||
else:
|
||
return False, f"{tr('NarratoAPI is not available')}: HTTP {response.status_code}"
|
||
except Exception as e:
|
||
return False, f"{tr('NarratoAPI is not available')}: {str(e)}"
|
||
|
||
else:
|
||
return False, f"{tr('Unsupported provider')}: {provider}"
|
||
|
||
def render_vision_llm_settings(tr):
|
||
"""渲染视频分析模型设置"""
|
||
st.subheader(tr("Vision Model Settings"))
|
||
|
||
# 视频分析模型提供商选择
|
||
vision_providers = ['Gemini', 'QwenVL', 'NarratoAPI(待发布)']
|
||
saved_vision_provider = config.app.get("vision_llm_provider", "Gemini").lower()
|
||
saved_provider_index = 0
|
||
|
||
for i, provider in enumerate(vision_providers):
|
||
if provider.lower() == saved_vision_provider:
|
||
saved_provider_index = i
|
||
break
|
||
|
||
vision_provider = st.selectbox(
|
||
tr("Vision Model Provider"),
|
||
options=vision_providers,
|
||
index=saved_provider_index
|
||
)
|
||
vision_provider = vision_provider.lower()
|
||
config.app["vision_llm_provider"] = vision_provider
|
||
st.session_state['vision_llm_providers'] = vision_provider
|
||
|
||
# 获取已保存的视觉模型配置
|
||
vision_api_key = config.app.get(f"vision_{vision_provider}_api_key", "")
|
||
vision_base_url = config.app.get(f"vision_{vision_provider}_base_url", "")
|
||
vision_model_name = config.app.get(f"vision_{vision_provider}_model_name", "")
|
||
|
||
# 渲染视觉模型配置输入框
|
||
st_vision_api_key = st.text_input(tr("Vision API Key"), value=vision_api_key, type="password")
|
||
|
||
# 根据不同提供商设置默认值和帮助信息
|
||
if vision_provider == 'gemini':
|
||
st_vision_base_url = st.text_input(
|
||
tr("Vision Base URL"),
|
||
value=vision_base_url,
|
||
disabled=True,
|
||
help=tr("Gemini API does not require a base URL")
|
||
)
|
||
st_vision_model_name = st.text_input(
|
||
tr("Vision Model Name"),
|
||
value=vision_model_name or "gemini-1.5-flash",
|
||
help=tr("Default: gemini-1.5-flash")
|
||
)
|
||
elif vision_provider == 'qwenvl':
|
||
st_vision_base_url = st.text_input(
|
||
tr("Vision Base URL"),
|
||
value=vision_base_url or "https://dashscope.aliyuncs.com/compatible-mode/v1",
|
||
help=tr("Default: https://dashscope.aliyuncs.com/compatible-mode/v1")
|
||
)
|
||
st_vision_model_name = st.text_input(
|
||
tr("Vision Model Name"),
|
||
value=vision_model_name or "qwen-vl-max-latest",
|
||
help=tr("Default: qwen-vl-max-latest")
|
||
)
|
||
else:
|
||
st_vision_base_url = st.text_input(tr("Vision Base URL"), value=vision_base_url)
|
||
st_vision_model_name = st.text_input(tr("Vision Model Name"), value=vision_model_name)
|
||
|
||
# 在配置输入框后添加测试按钮
|
||
if st.button(tr("Test Connection"), key="test_vision_connection"):
|
||
with st.spinner(tr("Testing connection...")):
|
||
success, message = test_vision_model_connection(
|
||
api_key=st_vision_api_key,
|
||
base_url=st_vision_base_url,
|
||
model_name=st_vision_model_name,
|
||
provider=vision_provider,
|
||
tr=tr
|
||
)
|
||
|
||
if success:
|
||
st.success(tr(message))
|
||
else:
|
||
st.error(tr(message))
|
||
|
||
# 保存视觉模型配置
|
||
if st_vision_api_key:
|
||
config.app[f"vision_{vision_provider}_api_key"] = st_vision_api_key
|
||
st.session_state[f"vision_{vision_provider}_api_key"] = st_vision_api_key
|
||
if st_vision_base_url:
|
||
config.app[f"vision_{vision_provider}_base_url"] = st_vision_base_url
|
||
st.session_state[f"vision_{vision_provider}_base_url"] = st_vision_base_url
|
||
if st_vision_model_name:
|
||
config.app[f"vision_{vision_provider}_model_name"] = st_vision_model_name
|
||
st.session_state[f"vision_{vision_provider}_model_name"] = st_vision_model_name
|
||
|
||
|
||
def test_text_model_connection(api_key, base_url, model_name, provider, tr):
|
||
"""测试文本模型连接
|
||
|
||
Args:
|
||
api_key: API密钥
|
||
base_url: 基础URL
|
||
model_name: 模型名称
|
||
provider: 提供商名称
|
||
|
||
Returns:
|
||
bool: 连接是否成功
|
||
str: 测试结果消息
|
||
"""
|
||
import requests
|
||
|
||
try:
|
||
# 构建统一的测试请求（遵循OpenAI格式）
|
||
headers = {
|
||
"Authorization": f"Bearer {api_key}",
|
||
"Content-Type": "application/json"
|
||
}
|
||
|
||
# 如果没有指定base_url，使用默认值
|
||
if not base_url:
|
||
if provider.lower() == 'openai':
|
||
base_url = "https://api.openai.com/v1"
|
||
elif provider.lower() == 'moonshot':
|
||
base_url = "https://api.moonshot.cn/v1"
|
||
elif provider.lower() == 'deepseek':
|
||
base_url = "https://api.deepseek.com/v1"
|
||
|
||
# 构建测试URL
|
||
test_url = f"{base_url.rstrip('/')}/chat/completions"
|
||
|
||
# 特殊处理Gemini
|
||
if provider.lower() == 'gemini':
|
||
import google.generativeai as genai
|
||
try:
|
||
genai.configure(api_key=api_key)
|
||
model = genai.GenerativeModel(model_name or 'gemini-pro')
|
||
model.generate_content("直接回复我文本'当前网络可用'")
|
||
return True, tr("Gemini model is available")
|
||
except Exception as e:
|
||
return False, f"{tr('Gemini model is not available')}: {str(e)}"
|
||
|
||
# 构建测试消息
|
||
test_data = {
|
||
"model": model_name,
|
||
"messages": [
|
||
{"role": "user", "content": "直接回复我文本'当前网络可用'"}
|
||
],
|
||
"max_tokens": 10
|
||
}
|
||
|
||
# 发送测试请求
|
||
response = requests.post(
|
||
test_url,
|
||
headers=headers,
|
||
json=test_data,
|
||
timeout=10
|
||
)
|
||
|
||
if response.status_code == 200:
|
||
return True, tr("Text model is available")
|
||
else:
|
||
return False, f"{tr('Text model is not available')}: HTTP {response.status_code}"
|
||
|
||
except Exception as e:
|
||
return False, f"{tr('Connection failed')}: {str(e)}"
|
||
|
||
|
||
def render_text_llm_settings(tr):
|
||
"""渲染文案生成模型设置"""
|
||
st.subheader(tr("Text Generation Model Settings"))
|
||
|
||
# 文案生成模型提供商选择
|
||
text_providers = ['OpenAI', 'Qwen', 'Moonshot', 'DeepSeek', 'Gemini']
|
||
saved_text_provider = config.app.get("text_llm_provider", "OpenAI").lower()
|
||
saved_provider_index = 0
|
||
|
||
for i, provider in enumerate(text_providers):
|
||
if provider.lower() == saved_text_provider:
|
||
saved_provider_index = i
|
||
break
|
||
|
||
text_provider = st.selectbox(
|
||
tr("Text Model Provider"),
|
||
options=text_providers,
|
||
index=saved_provider_index
|
||
)
|
||
text_provider = text_provider.lower()
|
||
config.app["text_llm_provider"] = text_provider
|
||
|
||
# 获取已保存的文本模型配置
|
||
text_api_key = config.app.get(f"text_{text_provider}_api_key", "")
|
||
text_base_url = config.app.get(f"text_{text_provider}_base_url", "")
|
||
text_model_name = config.app.get(f"text_{text_provider}_model_name", "")
|
||
|
||
# 渲染文本模型配置输入框
|
||
st_text_api_key = st.text_input(tr("Text API Key"), value=text_api_key, type="password")
|
||
st_text_base_url = st.text_input(tr("Text Base URL"), value=text_base_url)
|
||
st_text_model_name = st.text_input(tr("Text Model Name"), value=text_model_name)
|
||
|
||
# 添加测试按钮
|
||
if st.button(tr("Test Connection"), key="test_text_connection"):
|
||
with st.spinner(tr("Testing connection...")):
|
||
success, message = test_text_model_connection(
|
||
api_key=st_text_api_key,
|
||
base_url=st_text_base_url,
|
||
model_name=st_text_model_name,
|
||
provider=text_provider,
|
||
tr=tr
|
||
)
|
||
|
||
if success:
|
||
st.success(message)
|
||
else:
|
||
st.error(message)
|
||
|
||
# 保存文本模型配置
|
||
if st_text_api_key:
|
||
config.app[f"text_{text_provider}_api_key"] = st_text_api_key
|
||
if st_text_base_url:
|
||
config.app[f"text_{text_provider}_base_url"] = st_text_base_url
|
||
if st_text_model_name:
|
||
config.app[f"text_{text_provider}_model_name"] = st_text_model_name
|
||
|
||
# Cloudflare 特殊配置
|
||
if text_provider == 'cloudflare':
|
||
st_account_id = st.text_input(
|
||
tr("Account ID"),
|
||
value=config.app.get(f"text_{text_provider}_account_id", "")
|
||
)
|
||
if st_account_id:
|
||
config.app[f"text_{text_provider}_account_id"] = st_account_id
|