import streamlit as st from streamlit_chatbox import * from typing import List, Dict from datetime import datetime from .utils import * from dev_opsgpt.utils import * from dev_opsgpt.chat.search_chat import SEARCH_ENGINES 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", "搜索引擎问答", ], 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}") 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) 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) code_interpreter_on = st.toggle("开启代码解释器") code_exec_on = st.toggle("自动执行代码") # 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 = "" r = api.chat_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) 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 = "" 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) 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": []} for d in api.search_engine_chat(prompt, search_engine, se_top_k): 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 = "".format( codebox_res.code_exe_response ) chat_box.update_msg(base_text + img_html, streaming=False, state="complete") 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, )