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codefuse-chatbot/dev_opsgpt/webui/dialogue.py

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import streamlit as st
from streamlit_chatbox import *
from typing import List, Dict
from datetime import datetime
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from random import randint
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from .utils import *
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from dev_opsgpt.utils import *
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from dev_opsgpt.tools import TOOL_SETS
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from dev_opsgpt.chat.search_chat import SEARCH_ENGINES
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from dev_opsgpt.connector import PHASE_LIST, PHASE_CONFIGS
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chat_box = ChatBox(
assistant_avatar="../sources/imgs/devops-chatbot2.png"
)
GLOBAL_EXE_CODE_TEXT = ""
def get_messages_history(history_len: int) -> List[Dict]:
def filter(msg):
'''
针对当前简单文本对话，只返回每条消息的第一个element的内容
'''
content = [x._content for x in msg["elements"] if x._output_method in ["markdown", "text"]]
return {
"role": msg["role"],
"content": content[0] if content else "",
}
history = chat_box.filter_history(100000, filter) # workaround before upgrading streamlit-chatbox.
user_count = 0
i = 1
for i in range(1, len(history) + 1):
if history[-i]["role"] == "user":
user_count += 1
if user_count >= history_len:
break
return history[-i:]
def dialogue_page(api: ApiRequest):
global GLOBAL_EXE_CODE_TEXT
chat_box.init_session()
with st.sidebar:
# TODO: 对话模型与会话绑定
def on_mode_change():
mode = st.session_state.dialogue_mode
text = f"已切换到 {mode} 模式。"
if mode == "知识库问答":
cur_kb = st.session_state.get("selected_kb")
if cur_kb:
text = f"{text} 当前知识库： `{cur_kb}`。"
st.toast(text)
# sac.alert(text, description="descp", type="success", closable=True, banner=True)
dialogue_mode = st.selectbox("请选择对话模式",
["LLM 对话",
"知识库问答",
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"代码知识库问答",
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"搜索引擎问答",
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"工具问答",
"数据分析",
"Agent问答"
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],
on_change=on_mode_change,
key="dialogue_mode",
)
history_len = st.number_input("历史对话轮数：", 0, 10, 3)
# todo: support history len
def on_kb_change():
st.toast(f"已加载知识库： {st.session_state.selected_kb}")
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def on_cb_change():
st.toast(f"已加载代码知识库： {st.session_state.selected_cb}")
not_agent_qa = True
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if dialogue_mode == "知识库问答":
with st.expander("知识库配置", True):
kb_list = api.list_knowledge_bases(no_remote_api=True)
selected_kb = st.selectbox(
"请选择知识库：",
kb_list,
on_change=on_kb_change,
key="selected_kb",
)
kb_top_k = st.number_input("匹配知识条数：", 1, 20, 3)
score_threshold = st.number_input("知识匹配分数阈值：", 0.0, float(SCORE_THRESHOLD), float(SCORE_THRESHOLD), float(SCORE_THRESHOLD//100))
# chunk_content = st.checkbox("关联上下文", False, disabled=True)
# chunk_size = st.slider("关联长度：", 0, 500, 250, disabled=True)
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elif dialogue_mode == '代码知识库问答':
with st.expander('代码知识库配置', True):
cb_list = api.list_cb(no_remote_api=True)
logger.debug('codebase_list={}'.format(cb_list))
selected_cb = st.selectbox(
"请选择代码知识库：",
cb_list,
on_change=on_cb_change,
key="selected_cb",
)
st.toast(f"已加载代码知识库： {st.session_state.selected_cb}")
cb_code_limit = st.number_input("匹配代码条数：", 1, 20, 1)
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elif dialogue_mode == "搜索引擎问答":
with st.expander("搜索引擎配置", True):
search_engine = st.selectbox("请选择搜索引擎", SEARCH_ENGINES.keys(), 0)
se_top_k = st.number_input("匹配搜索结果条数：", 1, 20, 3)
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elif dialogue_mode == "工具问答":
with st.expander("工具军火库", True):
tool_selects = st.multiselect(
'请选择待使用的工具', TOOL_SETS, ["WeatherInfo"])
elif dialogue_mode == "数据分析":
with st.expander("沙盒文件管理", False):
def _upload(upload_file):
res = api.web_sd_upload(upload_file)
logger.debug(res)
if res["msg"]:
st.success("上文件传成功")
else:
st.toast("文件上传失败")
interpreter_file = st.file_uploader(
"上传沙盒文件",
[i for ls in LOADER2EXT_DICT.values() for i in ls],
accept_multiple_files=False,
key="interpreter_file",
)
if interpreter_file:
_upload(interpreter_file)
interpreter_file = None
#
files = api.web_sd_list_files()
files = files["data"]
download_file = st.selectbox("选择要处理文件", files,
key="download_file",)
cols = st.columns(2)
file_url, file_name = api.web_sd_download(download_file)
cols[0].download_button("点击下载", file_url, file_name)
if cols[1].button("点击删除", ):
api.web_sd_delete(download_file)
elif dialogue_mode == "Agent问答":
not_agent_qa = False
with st.expander("Phase管理", True):
choose_phase = st.selectbox(
'请选择待使用的执行链路', PHASE_LIST, 0)
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is_detailed = st.toggle("返回明细的Agent交互", False)
tool_using_on = st.toggle("开启工具使用", PHASE_CONFIGS[choose_phase]["do_using_tool"])
tool_selects = []
if tool_using_on:
with st.expander("工具军火库", True):
tool_selects = st.multiselect(
'请选择待使用的工具', TOOL_SETS, ["WeatherInfo"])
search_on = st.toggle("开启搜索增强", PHASE_CONFIGS[choose_phase]["do_search"])
search_engine, top_k = None, 3
if search_on:
with st.expander("搜索引擎配置", True):
search_engine = st.selectbox("请选择搜索引擎", SEARCH_ENGINES.keys(), 0)
top_k = st.number_input("匹配搜索结果条数：", 1, 20, 3)
doc_retrieval_on = st.toggle("开启知识库检索增强", PHASE_CONFIGS[choose_phase]["do_doc_retrieval"])
selected_kb, top_k, score_threshold = None, 3, 1.0
if doc_retrieval_on:
with st.expander("知识库配置", True):
kb_list = api.list_knowledge_bases(no_remote_api=True)
selected_kb = st.selectbox(
"请选择知识库：",
kb_list,
on_change=on_kb_change,
key="selected_kb",
)
top_k = st.number_input("匹配知识条数：", 1, 20, 3)
score_threshold = st.number_input("知识匹配分数阈值：", 0.0, float(SCORE_THRESHOLD), float(SCORE_THRESHOLD), float(SCORE_THRESHOLD//100))
code_retrieval_on = st.toggle("开启代码检索增强", PHASE_CONFIGS[choose_phase]["do_code_retrieval"])
selected_cb, top_k = None, 1
if code_retrieval_on:
with st.expander('代码知识库配置', True):
cb_list = api.list_cb(no_remote_api=True)
logger.debug('codebase_list={}'.format(cb_list))
selected_cb = st.selectbox(
"请选择代码知识库：",
cb_list,
on_change=on_cb_change,
key="selected_cb",
)
st.toast(f"已加载代码知识库： {st.session_state.selected_cb}")
top_k = st.number_input("匹配代码条数：", 1, 20, 1)
with st.expander("沙盒文件管理", False):
def _upload(upload_file):
res = api.web_sd_upload(upload_file)
logger.debug(res)
if res["msg"]:
st.success("上文件传成功")
else:
st.toast("文件上传失败")
interpreter_file = st.file_uploader(
"上传沙盒文件",
[i for ls in LOADER2EXT_DICT.values() for i in ls],
accept_multiple_files=False,
key="interpreter_file",
)
if interpreter_file:
_upload(interpreter_file)
interpreter_file = None
#
files = api.web_sd_list_files()
files = files["data"]
download_file = st.selectbox("选择要处理文件", files,
key="download_file",)
cols = st.columns(2)
file_url, file_name = api.web_sd_download(download_file)
cols[0].download_button("点击下载", file_url, file_name)
if cols[1].button("点击删除", ):
api.web_sd_delete(download_file)
code_interpreter_on = st.toggle("开启代码解释器") and not_agent_qa
code_exec_on = st.toggle("自动执行代码") and not_agent_qa
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# Display chat messages from history on app rerun
chat_box.output_messages()
chat_input_placeholder = "请输入对话内容，换行请使用Ctrl+Enter "
code_text = "" or GLOBAL_EXE_CODE_TEXT
codebox_res = None
if prompt := st.chat_input(chat_input_placeholder, key="prompt"):
history = get_messages_history(history_len)
chat_box.user_say(prompt)
if dialogue_mode == "LLM 对话":
chat_box.ai_say("正在思考...")
text = ""
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r = api.chat_chat(prompt, history, no_remote_api=True)
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for t in r:
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if error_msg := check_error_msg(t): # check whether error occured
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st.error(error_msg)
break
text += t["answer"]
chat_box.update_msg(text)
logger.debug(f"text: {text}")
chat_box.update_msg(text, streaming=False) # 更新最终的字符串，去除光标
# 判断是否存在代码, 并提高编辑功能，执行功能
code_text = api.codebox.decode_code_from_text(text)
GLOBAL_EXE_CODE_TEXT = code_text
if code_text and code_exec_on:
codebox_res = api.codebox_chat("```"+code_text+"```", do_code_exe=True)
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elif dialogue_mode == "Agent问答":
display_infos = [f"正在思考..."]
if search_on:
display_infos.append(Markdown("...", in_expander=True, title="网络搜索结果"))
if doc_retrieval_on:
display_infos.append(Markdown("...", in_expander=True, title="知识库匹配结果"))
chat_box.ai_say(display_infos)
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if 'history_node_list' in st.session_state:
history_node_list: List[str] = st.session_state['history_node_list']
else:
history_node_list: List[str] = []
input_kargs = {"query": prompt,
"phase_name": choose_phase,
"history": history,
"doc_engine_name": selected_kb,
"search_engine_name": search_engine,
"code_engine_name": selected_cb,
"top_k": top_k,
"score_threshold": score_threshold,
"do_search": search_on,
"do_doc_retrieval": doc_retrieval_on,
"do_code_retrieval": code_retrieval_on,
"do_tool_retrieval": False,
"custom_phase_configs": {},
"custom_chain_configs": {},
"custom_role_configs": {},
"choose_tools": tool_selects,
"history_node_list": history_node_list,
"isDetailed": is_detailed,
}
text = ""
d = {"docs": []}
for idx_count, d in enumerate(api.agent_chat(**input_kargs)):
if error_msg := check_error_msg(d): # check whether error occured
st.error(error_msg)
text += d["answer"]
if idx_count%20 == 0:
chat_box.update_msg(text, element_index=0)
for k, v in d["figures"].items():
logger.debug(f"figure: {k}")
if k in text:
img_html = "\n<img src='data:image/png;base64,{}' class='img-fluid'>\n".format(v)
text = text.replace(k, img_html).replace(".png", "")
chat_box.update_msg(text, element_index=0, streaming=False, state="complete") # 更新最终的字符串，去除光标
if search_on:
chat_box.update_msg("搜索匹配结果:\n\n" + "\n\n".join(d["search_docs"]), element_index=search_on, streaming=False, state="complete")
if doc_retrieval_on:
chat_box.update_msg("知识库匹配结果:\n\n" + "\n\n".join(d["db_docs"]), element_index=search_on+doc_retrieval_on, streaming=False, state="complete")
history_node_list.extend([node[0] for node in d.get("related_nodes", [])])
history_node_list = list(set(history_node_list))
st.session_state['history_node_list'] = history_node_list
elif dialogue_mode == "工具问答":
chat_box.ai_say("正在思考...")
text = ""
r = api.tool_chat(prompt, history, tool_sets=tool_selects)
for t in r:
if error_msg := check_error_msg(t): # check whether error occured
st.error(error_msg)
break
text += t["answer"]
chat_box.update_msg(text)
logger.debug(f"text: {text}")
chat_box.update_msg(text, streaming=False) # 更新最终的字符串，去除光标
# 判断是否存在代码, 并提高编辑功能，执行功能
code_text = api.codebox.decode_code_from_text(text)
GLOBAL_EXE_CODE_TEXT = code_text
if code_text and code_exec_on:
codebox_res = api.codebox_chat("```"+code_text+"```", do_code_exe=True)
elif dialogue_mode == "数据分析":
chat_box.ai_say("正在思考...")
text = ""
r = api.data_chat(prompt, history)
for t in r:
if error_msg := check_error_msg(t): # check whether error occured
st.error(error_msg)
break
text += t["answer"]
chat_box.update_msg(text)
logger.debug(f"text: {text}")
chat_box.update_msg(text, streaming=False) # 更新最终的字符串，去除光标
# 判断是否存在代码, 并提高编辑功能，执行功能
code_text = api.codebox.decode_code_from_text(text)
GLOBAL_EXE_CODE_TEXT = code_text
if code_text and code_exec_on:
codebox_res = api.codebox_chat("```"+code_text+"```", do_code_exe=True)
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elif dialogue_mode == "知识库问答":
history = get_messages_history(history_len)
chat_box.ai_say([
f"正在查询知识库 `{selected_kb}` ...",
Markdown("...", in_expander=True, title="知识库匹配结果"),
])
text = ""
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d = {"docs": []}
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for idx_count, d in enumerate(api.knowledge_base_chat(prompt, selected_kb, kb_top_k, score_threshold, history)):
if error_msg := check_error_msg(d): # check whether error occured
st.error(error_msg)
text += d["answer"]
if idx_count%10 == 0:
chat_box.update_msg(text, element_index=0)
# chat_box.update_msg("知识库匹配结果: \n\n".join(d["docs"]), element_index=1, streaming=False, state="complete")
chat_box.update_msg(text, element_index=0, streaming=False) # 更新最终的字符串，去除光标
chat_box.update_msg("知识库匹配结果: \n\n".join(d["docs"]), element_index=1, streaming=False, state="complete")
# 判断是否存在代码, 并提高编辑功能，执行功能
code_text = api.codebox.decode_code_from_text(text)
GLOBAL_EXE_CODE_TEXT = code_text
if code_text and code_exec_on:
codebox_res = api.codebox_chat("```"+code_text+"```", do_code_exe=True)
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elif dialogue_mode == '代码知识库问答':
logger.info('prompt={}'.format(prompt))
logger.info('history={}'.format(history))
if 'history_node_list' in st.session_state:
api.codeChat.history_node_list = st.session_state['history_node_list']
chat_box.ai_say([
f"正在查询代码知识库 `{selected_cb}` ...",
Markdown("...", in_expander=True, title="代码库匹配结果"),
])
text = ""
d = {"codes": []}
for idx_count, d in enumerate(api.code_base_chat(query=prompt, code_base_name=selected_cb,
code_limit=cb_code_limit, history=history,
no_remote_api=True)):
if error_msg := check_error_msg(d):
st.error(error_msg)
text += d["answer"]
if idx_count % 10 == 0:
chat_box.update_msg(text, element_index=0)
chat_box.update_msg(text, element_index=0, streaming=False) # 更新最终的字符串，去除光标
chat_box.update_msg("\n".join(d["codes"]), element_index=1, streaming=False, state="complete")
# session state update
st.session_state['history_node_list'] = api.codeChat.history_node_list
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elif dialogue_mode == "搜索引擎问答":
chat_box.ai_say([
f"正在执行 `{search_engine}` 搜索...",
Markdown("...", in_expander=True, title="网络搜索结果"),
])
text = ""
d = {"docs": []}
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for idx_count, d in enumerate(api.search_engine_chat(prompt, search_engine, se_top_k)):
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if error_msg := check_error_msg(d): # check whether error occured
st.error(error_msg)
text += d["answer"]
if idx_count%10 == 0:
chat_box.update_msg(text, element_index=0)
# chat_box.update_msg("搜索匹配结果: \n\n".join(d["docs"]), element_index=1, streaming=False)
chat_box.update_msg(text, element_index=0, streaming=False) # 更新最终的字符串，去除光标
chat_box.update_msg("搜索匹配结果: \n\n".join(d["docs"]), element_index=1, streaming=False, state="complete")
# 判断是否存在代码, 并提高编辑功能，执行功能
code_text = api.codebox.decode_code_from_text(text)
GLOBAL_EXE_CODE_TEXT = code_text
if code_text and code_exec_on:
codebox_res = api.codebox_chat("```"+code_text+"```", do_code_exe=True)
if code_interpreter_on:
with st.expander("代码编辑执行器", False):
code_part = st.text_area("代码片段", code_text, key="code_text")
cols = st.columns(2)
if cols[0].button(
"修改对话",
use_container_width=True,
):
code_text = code_part
GLOBAL_EXE_CODE_TEXT = code_text
st.toast("修改对话成功")
if cols[1].button(
"执行代码",
use_container_width=True
):
if code_text:
codebox_res = api.codebox_chat("```"+code_text+"```", do_code_exe=True)
st.toast("正在执行代码")
else:
st.toast("code 不能为空")
#TODO 这段信息会被记录到history里
if codebox_res is not None and codebox_res.code_exe_status != 200:
st.toast(f"{codebox_res.code_exe_response}")
if codebox_res is not None and codebox_res.code_exe_status == 200:
st.toast(f"codebox_chajt {codebox_res}")
chat_box.ai_say(Markdown(code_text, in_expander=True, title="code interpreter", unsafe_allow_html=True), )
if codebox_res.code_exe_type == "image/png":
base_text = f"```\n{code_text}\n```\n\n"
img_html = "<img src='data:image/png;base64,{}' class='img-fluid'>".format(
codebox_res.code_exe_response
)
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chat_box.update_msg(img_html, streaming=False, state="complete")
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else:
chat_box.update_msg('```\n'+code_text+'\n```'+"\n\n"+'```\n'+codebox_res.code_exe_response+'\n```',
streaming=False, state="complete")
now = datetime.now()
with st.sidebar:
cols = st.columns(2)
export_btn = cols[0]
if cols[1].button(
"清空对话",
use_container_width=True,
):
chat_box.reset_history()
GLOBAL_EXE_CODE_TEXT = ""
st.experimental_rerun()
export_btn.download_button(
"导出记录",
"".join(chat_box.export2md()),
file_name=f"{now:%Y-%m-%d %H.%M}_对话记录.md",
mime="text/markdown",
use_container_width=True,
)