mirror of
https://github.com/RYDE-WORK/Langchain-Chatchat.git
synced 2026-01-29 02:03:37 +08:00
356 lines
16 KiB
Python
356 lines
16 KiB
Python
import base64
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import streamlit as st
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from streamlit_antd_components.utils import ParseItems
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from webui_pages.dialogue.utils import process_files
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from webui_pages.loom_view_client import build_plugins_name, find_menu_items_by_index, set_llm_select, \
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get_select_model_endpoint
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from webui_pages.utils import *
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from streamlit_chatbox import *
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from streamlit_modal import Modal
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from datetime import datetime
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import os
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import re
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import time
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from configs import (LLM_MODEL_CONFIG, SUPPORT_AGENT_MODELS, TOOL_CONFIG, OPENAI_KEY, OPENAI_PROXY)
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from server.callback_handler.agent_callback_handler import AgentStatus
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from server.utils import MsgType
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import uuid
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from typing import List, Dict
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import streamlit_antd_components as sac
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chat_box = ChatBox(
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assistant_avatar=os.path.join(
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"img",
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"chatchat_icon_blue_square_v2.png"
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)
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)
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def get_messages_history(history_len: int, content_in_expander: bool = False) -> List[Dict]:
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'''
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返回消息历史。
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content_in_expander控制是否返回expander元素中的内容，一般导出的时候可以选上，传入LLM的history不需要
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'''
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def filter(msg):
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content = [x for x in msg["elements"] if x._output_method in ["markdown", "text"]]
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if not content_in_expander:
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content = [x for x in content if not x._in_expander]
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content = [x.content for x in content]
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return {
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"role": msg["role"],
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"content": "\n\n".join(content),
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}
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return chat_box.filter_history(history_len=history_len, filter=filter)
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@st.cache_data
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def upload_temp_docs(files, _api: ApiRequest) -> str:
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'''
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将文件上传到临时目录，用于文件对话
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返回临时向量库ID
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'''
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return _api.upload_temp_docs(files).get("data", {}).get("id")
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def parse_command(text: str, modal: Modal) -> bool:
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'''
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检查用户是否输入了自定义命令，当前支持：
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/new {session_name}。如果未提供名称，默认为“会话X”
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/del {session_name}。如果未提供名称，在会话数量>1的情况下，删除当前会话。
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/clear {session_name}。如果未提供名称，默认清除当前会话
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/stop {session_name}。如果未提供名称，默认停止当前会话
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/help。查看命令帮助
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返回值：输入的是命令返回True，否则返回False
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'''
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if m := re.match(r"/([^\s]+)\s*(.*)", text):
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cmd, name = m.groups()
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name = name.strip()
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conv_names = chat_box.get_chat_names()
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if cmd == "help":
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modal.open()
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elif cmd == "new":
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if not name:
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i = 1
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while True:
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name = f"会话{i}"
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if name not in conv_names:
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break
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i += 1
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if name in st.session_state["conversation_ids"]:
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st.error(f"该会话名称 “{name}” 已存在")
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time.sleep(1)
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else:
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st.session_state["conversation_ids"][name] = uuid.uuid4().hex
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st.session_state["cur_conv_name"] = name
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elif cmd == "del":
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name = name or st.session_state.get("cur_conv_name")
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if len(conv_names) == 1:
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st.error("这是最后一个会话，无法删除")
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time.sleep(1)
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elif not name or name not in st.session_state["conversation_ids"]:
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st.error(f"无效的会话名称：“{name}”")
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time.sleep(1)
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else:
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st.session_state["conversation_ids"].pop(name, None)
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chat_box.del_chat_name(name)
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st.session_state["cur_conv_name"] = ""
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elif cmd == "clear":
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chat_box.reset_history(name=name or None)
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return True
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return False
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def dialogue_page(api: ApiRequest, is_lite: bool = False):
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st.session_state.setdefault("conversation_ids", {})
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st.session_state["conversation_ids"].setdefault(chat_box.cur_chat_name, uuid.uuid4().hex)
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st.session_state.setdefault("file_chat_id", None)
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st.session_state.setdefault("select_plugins_info", None)
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st.session_state.setdefault("select_model_worker", None)
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# 弹出自定义命令帮助信息
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modal = Modal("自定义命令", key="cmd_help", max_width="500")
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if modal.is_open():
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with modal.container():
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cmds = [x for x in parse_command.__doc__.split("\n") if x.strip().startswith("/")]
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st.write("\n\n".join(cmds))
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with st.sidebar:
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conv_names = list(st.session_state["conversation_ids"].keys())
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index = 0
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if st.session_state.get("cur_conv_name") in conv_names:
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index = conv_names.index(st.session_state.get("cur_conv_name"))
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conversation_name = st.selectbox("当前会话", conv_names, index=index)
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chat_box.use_chat_name(conversation_name)
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conversation_id = st.session_state["conversation_ids"][conversation_name]
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with st.expander("模型选择"):
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plugins_menu = build_plugins_name()
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items, _ = ParseItems(plugins_menu).multi()
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if len(plugins_menu) > 0:
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llm_model_index = sac.menu(plugins_menu, index=1, return_index=True)
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plugins_info, llm_model_worker = find_menu_items_by_index(items, llm_model_index)
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set_llm_select(plugins_info, llm_model_worker)
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else:
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st.info("没有可用的插件")
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# 传入后端的内容
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model_config = {key: {} for key in LLM_MODEL_CONFIG.keys()}
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tool_use = True
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for key in LLM_MODEL_CONFIG:
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if key == 'llm_model':
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continue
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if key == 'action_model':
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first_key = next(iter(LLM_MODEL_CONFIG[key]))
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if first_key not in SUPPORT_AGENT_MODELS:
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st.warning("不支持Agent的模型，无法执行任何工具调用")
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tool_use = False
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continue
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if LLM_MODEL_CONFIG[key]:
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first_key = next(iter(LLM_MODEL_CONFIG[key]))
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model_config[key][first_key] = LLM_MODEL_CONFIG[key][first_key]
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# 选择工具
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selected_tool_configs = {}
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if tool_use:
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from configs import model_config as model_config_py
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import importlib
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importlib.reload(model_config_py)
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tools = list(TOOL_CONFIG.keys())
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with st.expander("工具栏"):
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for tool in tools:
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is_selected = st.checkbox(tool, value=TOOL_CONFIG[tool]["use"], key=tool)
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if is_selected:
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selected_tool_configs[tool] = TOOL_CONFIG[tool]
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llm_model = None
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if st.session_state["select_model_worker"] is not None:
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llm_model = st.session_state["select_model_worker"]['label']
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if llm_model is not None:
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model_config['llm_model'][llm_model] = LLM_MODEL_CONFIG['llm_model'].get(llm_model, {})
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uploaded_file = st.file_uploader("上传附件", accept_multiple_files=False)
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files_upload = process_files(files=[uploaded_file]) if uploaded_file else None
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# print(len(files_upload["audios"])) if files_upload else None
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# if dialogue_mode == "文件对话":
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# with st.expander("文件对话配置", True):
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# files = st.file_uploader("上传知识文件：",
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# [i for ls in LOADER_DICT.values() for i in ls],
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# accept_multiple_files=True,
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# )
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# kb_top_k = st.number_input("匹配知识条数：", 1, 20, VECTOR_SEARCH_TOP_K)
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# score_threshold = st.slider("知识匹配分数阈值：", 0.0, 2.0, float(SCORE_THRESHOLD), 0.01)
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# if st.button("开始上传", disabled=len(files) == 0):
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# st.session_state["file_chat_id"] = upload_temp_docs(files, api)
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# Display chat messages from history on app rerun
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chat_box.output_messages()
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chat_input_placeholder = "请输入对话内容，换行请使用Shift+Enter。输入/help查看自定义命令 "
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def on_feedback(
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feedback,
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message_id: str = "",
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history_index: int = -1,
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):
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reason = feedback["text"]
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score_int = chat_box.set_feedback(feedback=feedback, history_index=history_index)
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api.chat_feedback(message_id=message_id,
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score=score_int,
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reason=reason)
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st.session_state["need_rerun"] = True
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feedback_kwargs = {
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"feedback_type": "thumbs",
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"optional_text_label": "欢迎反馈您打分的理由",
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}
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if prompt := st.chat_input(chat_input_placeholder, key="prompt"):
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if parse_command(text=prompt, modal=modal): # 用户输入自定义命令
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st.rerun()
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else:
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history = get_messages_history(
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model_config["llm_model"].get(next(iter(model_config["llm_model"])), {}).get("history_len", 1)
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)
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chat_box.user_say(prompt)
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if files_upload:
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if files_upload["images"]:
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st.markdown(f'<img src="data:image/jpeg;base64,{files_upload["images"][0]}" width="300">',
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unsafe_allow_html=True)
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elif files_upload["videos"]:
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st.markdown(
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f'<video width="400" height="300" controls><source src="data:video/mp4;base64,{files_upload["videos"][0]}" type="video/mp4"></video>',
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unsafe_allow_html=True)
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elif files_upload["audios"]:
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st.markdown(
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f'<audio controls><source src="data:audio/wav;base64,{files_upload["audios"][0]}" type="audio/wav"></audio>',
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unsafe_allow_html=True)
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chat_box.ai_say("正在思考...")
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text = ""
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text_action = ""
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element_index = 0
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openai_config = {}
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endpoint_host, select_model_name = get_select_model_endpoint()
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openai_config["endpoint_host"] = endpoint_host
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openai_config["model_name"] = select_model_name
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openai_config["endpoint_host_key"] = OPENAI_KEY
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openai_config["endpoint_host_proxy"] = OPENAI_PROXY
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for d in api.chat_chat(query=prompt,
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metadata=files_upload,
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history=history,
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model_config=model_config,
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openai_config=openai_config,
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conversation_id=conversation_id,
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tool_config=selected_tool_configs,
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):
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message_id = d.get("message_id", "")
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metadata = {
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"message_id": message_id,
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}
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print(d)
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if d["status"] == AgentStatus.error:
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st.error(d["text"])
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elif d["status"] == AgentStatus.agent_action:
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formatted_data = {
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"Function": d["tool_name"],
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"function_input": d["tool_input"]
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}
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element_index += 1
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formatted_json = json.dumps(formatted_data, indent=2, ensure_ascii=False)
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chat_box.insert_msg(
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Markdown(title="Function call", in_expander=True, expanded=True, state="running"))
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text = """\n```{}\n```\n""".format(formatted_json)
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chat_box.update_msg(Markdown(text), element_index=element_index)
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elif d["status"] == AgentStatus.tool_end:
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text += """\n```\nObservation:\n{}\n```\n""".format(d["tool_output"])
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chat_box.update_msg(Markdown(text), element_index=element_index, expanded=False, state="complete")
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elif d["status"] == AgentStatus.llm_new_token:
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text += d["text"]
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chat_box.update_msg(text, streaming=True, element_index=element_index, metadata=metadata)
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elif d["status"] == AgentStatus.llm_end:
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chat_box.update_msg(text, streaming=False, element_index=element_index, metadata=metadata)
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elif d["status"] == AgentStatus.agent_finish:
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if d["message_type"] == MsgType.IMAGE:
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for url in json.loads(d["text"]).get("images", []):
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url = f"{api.base_url}/media/{url}"
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chat_box.insert_msg(Image(url))
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chat_box.update_msg(element_index=element_index, expanded=False, state="complete")
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else:
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chat_box.insert_msg(Markdown(d["text"], expanded=True))
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if os.path.exists("tmp/image.jpg"):
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with open("tmp/image.jpg", "rb") as image_file:
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encoded_string = base64.b64encode(image_file.read()).decode()
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img_tag = f'<img src="data:image/jpeg;base64,{encoded_string}" width="300">'
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st.markdown(img_tag, unsafe_allow_html=True)
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os.remove("tmp/image.jpg")
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# chat_box.show_feedback(**feedback_kwargs,
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# key=message_id,
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# on_submit=on_feedback,
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# kwargs={"message_id": message_id, "history_index": len(chat_box.history) - 1})
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# elif dialogue_mode == "文件对话":
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# if st.session_state["file_chat_id"] is None:
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# st.error("请先上传文件再进行对话")
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# st.stop()
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# chat_box.ai_say([
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# f"正在查询文件 `{st.session_state['file_chat_id']}` ...",
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# Markdown("...", in_expander=True, title="文件匹配结果", state="complete"),
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# ])
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# text = ""
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# for d in api.file_chat(prompt,
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# knowledge_id=st.session_state["file_chat_id"],
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# top_k=kb_top_k,
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# score_threshold=score_threshold,
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# history=history,
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# model=llm_model,
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# prompt_name=prompt_template_name,
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# temperature=temperature):
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# if error_msg := check_error_msg(d):
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# st.error(error_msg)
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# elif chunk := d.get("answer"):
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# text += chunk
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# chat_box.update_msg(text, element_index=0)
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# chat_box.update_msg(text, element_index=0, streaming=False)
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# chat_box.update_msg("\n\n".join(d.get("docs", [])), element_index=1, streaming=False)
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if st.session_state.get("need_rerun"):
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st.session_state["need_rerun"] = False
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st.rerun()
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now = datetime.now()
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with st.sidebar:
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cols = st.columns(2)
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export_btn = cols[0]
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if cols[1].button(
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"清空对话",
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use_container_width=True,
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):
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chat_box.reset_history()
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st.rerun()
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warning_placeholder = st.empty()
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export_btn.download_button(
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"导出记录",
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"".join(chat_box.export2md()),
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file_name=f"{now:%Y-%m-%d %H.%M}_对话记录.md",
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mime="text/markdown",
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use_container_width=True,
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)
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