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戒酒的李白
6244d116 1 parent 4d90f56b

The single-multi-agent framework has been initially completed.

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Showing 4 changed files with 6 additions and 407 deletions
... ... @@ -168,7 +168,8 @@ def start_streamlit_app(app_name, script_path, port):
'--server.port', str(port),
'--server.headless', 'true',
'--browser.gatherUsageStats', 'false',
'--logger.level', 'debug', # 增加日志详细程度
# '--logger.level', 'debug', # 增加日志详细程度
'--logger.level', 'info',
'--server.enableCORS', 'false'
]
... ...
"""
Streamlit Web界面
为DInsight Agent提供友好的Web界面
"""
import os
import sys
import streamlit as st
from datetime import datetime
import json
# 添加src目录到Python路径
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..'))
from InsightEngine import DeepSearchAgent, Config
from config import DEEPSEEK_API_KEY, KIMI_API_KEY, DB_HOST, DB_USER, DB_PASSWORD, DB_NAME, DB_PORT, DB_CHARSET
def main():
"""主函数"""
st.set_page_config(
page_title="Insight Agent",
page_icon="",
layout="wide"
)
st.title("Insight Engine")
st.markdown("本地舆情数据库深度分析AI代理")
# ----- 配置被硬编码 -----
# 强制使用 Kimi
llm_provider = "kimi"
model_name = "kimi-k2-0711-preview"
# 默认高级配置
max_reflections = 2
max_content_length = 500000 # Kimi支持长文本
# 主界面
col1, col2 = st.columns([2, 1])
with col1:
st.header("研究查询")
query = st.text_area(
"请输入您要研究的问题",
placeholder="例如：2025年人工智能发展趋势",
height=100
)
with col2:
st.header("状态信息")
if 'agent' in st.session_state and hasattr(st.session_state.agent, 'state'):
progress = st.session_state.agent.get_progress_summary()
st.metric("总段落数", progress['total_paragraphs'])
st.metric("已完成", progress['completed_paragraphs'])
st.progress(progress['progress_percentage'] / 100)
else:
st.info("尚未开始研究")
# 执行按钮
col1_btn, col2_btn, col3_btn = st.columns([1, 1, 1])
with col2_btn:
start_research = st.button("开始研究", type="primary", use_container_width=True)
# 验证配置
if start_research:
if not query.strip():
st.error("请输入研究查询")
return
# 由于强制使用Kimi，只检查KIMI_API_KEY
if not KIMI_API_KEY:
st.error("请在您的配置文件(config.py)中设置KIMI_API_KEY")
return
# 自动使用配置文件中的API密钥和数据库配置
db_host = DB_HOST
db_user = DB_USER
db_password = DB_PASSWORD
db_name = DB_NAME
db_port = DB_PORT
db_charset = DB_CHARSET
# 创建配置
config = Config(
deepseek_api_key=None,
openai_api_key=None,
kimi_api_key=KIMI_API_KEY, # 强制使用配置文件中的Kimi Key
db_host=db_host,
db_user=db_user,
db_password=db_password,
db_name=db_name,
db_port=db_port,
db_charset=db_charset,
default_llm_provider=llm_provider,
deepseek_model="deepseek-chat", # 保留默认值以兼容
openai_model="gpt-4o-mini", # 保留默认值以兼容
kimi_model=model_name,
max_reflections=max_reflections,
max_content_length=max_content_length,
output_dir="insight_engine_streamlit_reports"
)
# 执行研究
execute_research(query, config)
def execute_research(query: str, config: Config):
"""执行研究"""
try:
# 创建进度条
progress_bar = st.progress(0)
status_text = st.empty()
# 初始化Agent
status_text.text("正在初始化Agent...")
agent = DeepSearchAgent(config)
st.session_state.agent = agent
progress_bar.progress(10)
# 生成报告结构
status_text.text("正在生成报告结构...")
agent._generate_report_structure(query)
progress_bar.progress(20)
# 处理段落
total_paragraphs = len(agent.state.paragraphs)
for i in range(total_paragraphs):
status_text.text(f"正在处理段落 {i + 1}/{total_paragraphs}: {agent.state.paragraphs[i].title}")
# 初始搜索和总结
agent._initial_search_and_summary(i)
progress_value = 20 + (i + 0.5) / total_paragraphs * 60
progress_bar.progress(int(progress_value))
# 反思循环
agent._reflection_loop(i)
agent.state.paragraphs[i].research.mark_completed()
progress_value = 20 + (i + 1) / total_paragraphs * 60
progress_bar.progress(int(progress_value))
# 生成最终报告
status_text.text("正在生成最终报告...")
final_report = agent._generate_final_report()
progress_bar.progress(90)
# 保存报告
status_text.text("正在保存报告...")
agent._save_report(final_report)
progress_bar.progress(100)
status_text.text("研究完成！")
# 显示结果
display_results(agent, final_report)
except Exception as e:
st.error(f"研究过程中发生错误: {str(e)}")
def display_results(agent: DeepSearchAgent, final_report: str):
"""显示研究结果"""
st.header("研究结果")
# 结果标签页（已移除下载选项）
tab1, tab2 = st.tabs(["最终报告", "详细信息"])
with tab1:
st.markdown(final_report)
with tab2:
# 段落详情
st.subheader("段落详情")
for i, paragraph in enumerate(agent.state.paragraphs):
with st.expander(f"段落 {i + 1}: {paragraph.title}"):
st.write("**预期内容:**", paragraph.content)
st.write("**最终内容:**", paragraph.research.latest_summary[:300] + "..."
if len(paragraph.research.latest_summary) > 300
else paragraph.research.latest_summary)
st.write("**搜索次数:**", paragraph.research.get_search_count())
st.write("**反思次数:**", paragraph.research.reflection_iteration)
# 搜索历史
st.subheader("搜索历史")
all_searches = []
for paragraph in agent.state.paragraphs:
all_searches.extend(paragraph.research.search_history)
if all_searches:
for i, search in enumerate(all_searches):
with st.expander(f"搜索 {i + 1}: {search.query}"):
st.write("**URL:**", search.url)
st.write("**标题:**", search.title)
st.write("**内容预览:**",
search.content[:200] + "..." if len(search.content) > 200 else search.content)
if search.score:
st.write("**相关度评分:**", search.score)
if __name__ == "__main__":
main()
\ No newline at end of file
"""
Streamlit Web界面
为DInsight Agent提供友好的Web界面
"""
import os
import sys
import streamlit as st
from datetime import datetime
import json
# 添加src目录到Python路径
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..'))
from InsightEngine import DeepSearchAgent, Config
from config import DEEPSEEK_API_KEY, KIMI_API_KEY, DB_HOST, DB_USER, DB_PASSWORD, DB_NAME, DB_PORT, DB_CHARSET
def main():
"""主函数"""
st.set_page_config(
page_title="Insight Agent",
page_icon="",
layout="wide"
)
st.title("Insight Engine")
st.markdown("本地舆情数据库深度分析AI代理")
# ----- 配置被硬编码 -----
# 强制使用 Kimi
llm_provider = "kimi"
model_name = "kimi-k2-0711-preview"
# 默认高级配置
max_reflections = 2
max_content_length = 500000 # Kimi支持长文本
# 主界面
col1, col2 = st.columns([2, 1])
with col1:
st.header("研究查询")
query = st.text_area(
"请输入您要研究的问题",
placeholder="例如：2025年人工智能发展趋势",
height=100
)
with col2:
st.header("状态信息")
if 'agent' in st.session_state and hasattr(st.session_state.agent, 'state'):
progress = st.session_state.agent.get_progress_summary()
st.metric("总段落数", progress['total_paragraphs'])
st.metric("已完成", progress['completed_paragraphs'])
st.progress(progress['progress_percentage'] / 100)
else:
st.info("尚未开始研究")
# 执行按钮
col1_btn, col2_btn, col3_btn = st.columns([1, 1, 1])
with col2_btn:
start_research = st.button("开始研究", type="primary", use_container_width=True)
# 验证配置
if start_research:
if not query.strip():
st.error("请输入研究查询")
return
# 由于强制使用Kimi，只检查KIMI_API_KEY
if not KIMI_API_KEY:
st.error("请在您的配置文件(config.py)中设置KIMI_API_KEY")
return
# 自动使用配置文件中的API密钥和数据库配置
db_host = DB_HOST
db_user = DB_USER
db_password = DB_PASSWORD
db_name = DB_NAME
db_port = DB_PORT
db_charset = DB_CHARSET
# 创建配置
config = Config(
deepseek_api_key=None,
openai_api_key=None,
kimi_api_key=KIMI_API_KEY, # 强制使用配置文件中的Kimi Key
db_host=db_host,
db_user=db_user,
db_password=db_password,
db_name=db_name,
db_port=db_port,
db_charset=db_charset,
default_llm_provider=llm_provider,
deepseek_model="deepseek-chat", # 保留默认值以兼容
openai_model="gpt-4o-mini", # 保留默认值以兼容
kimi_model=model_name,
max_reflections=max_reflections,
max_content_length=max_content_length,
output_dir="insight_engine_streamlit_reports"
)
# 执行研究
execute_research(query, config)
def execute_research(query: str, config: Config):
"""执行研究"""
try:
# 创建进度条
progress_bar = st.progress(0)
status_text = st.empty()
# 初始化Agent
status_text.text("正在初始化Agent...")
agent = DeepSearchAgent(config)
st.session_state.agent = agent
progress_bar.progress(10)
# 生成报告结构
status_text.text("正在生成报告结构...")
agent._generate_report_structure(query)
progress_bar.progress(20)
# 处理段落
total_paragraphs = len(agent.state.paragraphs)
for i in range(total_paragraphs):
status_text.text(f"正在处理段落 {i + 1}/{total_paragraphs}: {agent.state.paragraphs[i].title}")
# 初始搜索和总结
agent._initial_search_and_summary(i)
progress_value = 20 + (i + 0.5) / total_paragraphs * 60
progress_bar.progress(int(progress_value))
# 反思循环
agent._reflection_loop(i)
agent.state.paragraphs[i].research.mark_completed()
progress_value = 20 + (i + 1) / total_paragraphs * 60
progress_bar.progress(int(progress_value))
# 生成最终报告
status_text.text("正在生成最终报告...")
final_report = agent._generate_final_report()
progress_bar.progress(90)
# 保存报告
status_text.text("正在保存报告...")
agent._save_report(final_report)
progress_bar.progress(100)
status_text.text("研究完成！")
# 显示结果
display_results(agent, final_report)
except Exception as e:
st.error(f"研究过程中发生错误: {str(e)}")
def display_results(agent: DeepSearchAgent, final_report: str):
"""显示研究结果"""
st.header("研究结果")
# 结果标签页（已移除下载选项）
tab1, tab2 = st.tabs(["最终报告", "详细信息"])
with tab1:
st.markdown(final_report)
with tab2:
# 段落详情
st.subheader("段落详情")
for i, paragraph in enumerate(agent.state.paragraphs):
with st.expander(f"段落 {i + 1}: {paragraph.title}"):
st.write("**预期内容:**", paragraph.content)
st.write("**最终内容:**", paragraph.research.latest_summary[:300] + "..."
if len(paragraph.research.latest_summary) > 300
else paragraph.research.latest_summary)
st.write("**搜索次数:**", paragraph.research.get_search_count())
st.write("**反思次数:**", paragraph.research.reflection_iteration)
# 搜索历史
st.subheader("搜索历史")
all_searches = []
for paragraph in agent.state.paragraphs:
all_searches.extend(paragraph.research.search_history)
if all_searches:
for i, search in enumerate(all_searches):
with st.expander(f"搜索 {i + 1}: {search.query}"):
st.write("**URL:**", search.url)
st.write("**标题:**", search.title)
st.write("**内容预览:**",
search.content[:200] + "..." if len(search.content) > 200 else search.content)
if search.score:
st.write("**相关度评分:**", search.score)
if __name__ == "__main__":
main()
\ No newline at end of file
... ... @@ -22,10 +22,11 @@
.container {
max-width: 100vw;
min-height: 100vh;
height: 100vh; /* 固定高度为视口高度 */
display: flex;
flex-direction: column;
border: 2px solid #000000;
overflow: hidden; /* 防止整体滚动 */
}
/* 搜索框区域 */
... ... @@ -117,6 +118,7 @@
flex-direction: column;
background-color: #ffffff;
min-height: 0; /* 允许子元素缩小 */
overflow: hidden; /* 防止内容溢出 */
}
/* 应用切换按钮 */
... ... @@ -178,10 +180,10 @@
font-family: 'Courier New', monospace;
font-size: 12px;
overflow-y: auto;
overflow-x: hidden;
white-space: pre-wrap;
word-break: break-all;
min-height: 0; /* 允许内容缩小 */
max-height: 100%; /* 限制最大高度 */
}
.console-line {
... ...