feat(webui): 添加视觉模型连接测试功能

- 新增 test_vision_model_connection 函数,用于测试视觉模型连接
- 在视觉模型设置界面添加测试连接按钮
- 实现对 Gemini 和 NarratoAPI 两种提供商的连接测试
- 优化界面布局,注释掉部分冗余代码
This commit is contained in:
linyq 2024-11-18 11:55:11 +08:00
parent 9b3a8f845a
commit 07c3d540c5

View File

@ -66,6 +66,51 @@ def render_proxy_settings(tr):
os.environ["HTTPS_PROXY"] = HTTPS_PROXY
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() == '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"))
@ -99,6 +144,22 @@ def render_vision_llm_settings(tr):
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
@ -110,80 +171,80 @@ def render_vision_llm_settings(tr):
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
# NarratoAPI 特殊配置
if vision_provider == 'narratoapi':
st.subheader(tr("Narrato Additional Settings"))
# Narrato API 基础配置
narrato_api_key = st.text_input(
tr("Narrato API Key"),
value=config.app.get("narrato_api_key", ""),
type="password",
help="用于访问 Narrato API 的密钥"
)
if narrato_api_key:
config.app["narrato_api_key"] = narrato_api_key
st.session_state['narrato_api_key'] = narrato_api_key
narrato_api_url = st.text_input(
tr("Narrato API URL"),
value=config.app.get("narrato_api_url", "http://127.0.0.1:8000/api/v1/video/analyze")
)
if narrato_api_url:
config.app["narrato_api_url"] = narrato_api_url
st.session_state['narrato_api_url'] = narrato_api_url
# 视频分析模型配置
st.markdown("##### " + tr("Vision Model Settings"))
narrato_vision_model = st.text_input(
tr("Vision Model Name"),
value=config.app.get("narrato_vision_model", "gemini-1.5-flash")
)
narrato_vision_key = st.text_input(
tr("Vision Model API Key"),
value=config.app.get("narrato_vision_key", ""),
type="password",
help="用于视频分析的模型 API Key"
)
if narrato_vision_model:
config.app["narrato_vision_model"] = narrato_vision_model
st.session_state['narrato_vision_model'] = narrato_vision_model
if narrato_vision_key:
config.app["narrato_vision_key"] = narrato_vision_key
st.session_state['narrato_vision_key'] = narrato_vision_key
# 文案生成模型配置
st.markdown("##### " + tr("Text Generation Model Settings"))
narrato_llm_model = st.text_input(
tr("LLM Model Name"),
value=config.app.get("narrato_llm_model", "qwen-plus")
)
narrato_llm_key = st.text_input(
tr("LLM Model API Key"),
value=config.app.get("narrato_llm_key", ""),
type="password",
help="用于文案生成的模型 API Key"
)
if narrato_llm_model:
config.app["narrato_llm_model"] = narrato_llm_model
st.session_state['narrato_llm_model'] = narrato_llm_model
if narrato_llm_key:
config.app["narrato_llm_key"] = narrato_llm_key
st.session_state['narrato_llm_key'] = narrato_llm_key
# 批处理配置
narrato_batch_size = st.number_input(
tr("Batch Size"),
min_value=1,
max_value=50,
value=config.app.get("narrato_batch_size", 10),
help="每批处理的图片数量"
)
if narrato_batch_size:
config.app["narrato_batch_size"] = narrato_batch_size
st.session_state['narrato_batch_size'] = narrato_batch_size
# # NarratoAPI 特殊配置
# if vision_provider == 'narratoapi':
# st.subheader(tr("Narrato Additional Settings"))
#
# # Narrato API 基础配置
# narrato_api_key = st.text_input(
# tr("Narrato API Key"),
# value=config.app.get("narrato_api_key", ""),
# type="password",
# help="用于访问 Narrato API 的密钥"
# )
# if narrato_api_key:
# config.app["narrato_api_key"] = narrato_api_key
# st.session_state['narrato_api_key'] = narrato_api_key
#
# narrato_api_url = st.text_input(
# tr("Narrato API URL"),
# value=config.app.get("narrato_api_url", "http://127.0.0.1:8000/api/v1/video/analyze")
# )
# if narrato_api_url:
# config.app["narrato_api_url"] = narrato_api_url
# st.session_state['narrato_api_url'] = narrato_api_url
#
# # 视频分析模型配置
# st.markdown("##### " + tr("Vision Model Settings"))
# narrato_vision_model = st.text_input(
# tr("Vision Model Name"),
# value=config.app.get("narrato_vision_model", "gemini-1.5-flash")
# )
# narrato_vision_key = st.text_input(
# tr("Vision Model API Key"),
# value=config.app.get("narrato_vision_key", ""),
# type="password",
# help="用于视频分析的模型 API Key"
# )
#
# if narrato_vision_model:
# config.app["narrato_vision_model"] = narrato_vision_model
# st.session_state['narrato_vision_model'] = narrato_vision_model
# if narrato_vision_key:
# config.app["narrato_vision_key"] = narrato_vision_key
# st.session_state['narrato_vision_key'] = narrato_vision_key
#
# # 文案生成模型配置
# st.markdown("##### " + tr("Text Generation Model Settings"))
# narrato_llm_model = st.text_input(
# tr("LLM Model Name"),
# value=config.app.get("narrato_llm_model", "qwen-plus")
# )
# narrato_llm_key = st.text_input(
# tr("LLM Model API Key"),
# value=config.app.get("narrato_llm_key", ""),
# type="password",
# help="用于文案生成的模型 API Key"
# )
#
# if narrato_llm_model:
# config.app["narrato_llm_model"] = narrato_llm_model
# st.session_state['narrato_llm_model'] = narrato_llm_model
# if narrato_llm_key:
# config.app["narrato_llm_key"] = narrato_llm_key
# st.session_state['narrato_llm_key'] = narrato_llm_key
#
# # 批处理配置
# narrato_batch_size = st.number_input(
# tr("Batch Size"),
# min_value=1,
# max_value=50,
# value=config.app.get("narrato_batch_size", 10),
# help="每批处理的图片数量"
# )
# if narrato_batch_size:
# config.app["narrato_batch_size"] = narrato_batch_size
# st.session_state['narrato_batch_size'] = narrato_batch_size
def render_text_llm_settings(tr):