594 lines
24 KiB
Python
594 lines
24 KiB
Python
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import base64
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import hashlib
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import io
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import os
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import uuid
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from datetime import datetime
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from PIL import Image as PILImage
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from typing import Dict, List
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from urllib.parse import urlencode
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# from audio_recorder_streamlit import audio_recorder
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import openai
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import streamlit as st
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import streamlit_antd_components as sac
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from streamlit_chatbox import *
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from streamlit_extras.bottom_container import bottom
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from streamlit_paste_button import paste_image_button
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from chatchat.settings import Settings
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from chatchat.server.callback_handler.agent_callback_handler import AgentStatus
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from chatchat.server.knowledge_base.model.kb_document_model import DocumentWithVSId
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from chatchat.server.knowledge_base.utils import format_reference
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from chatchat.server.utils import MsgType, get_config_models, get_config_platforms, get_default_llm
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from chatchat.webui_pages.utils import *
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chat_box = ChatBox(assistant_avatar=get_img_base64("chatchat_icon_blue_square_v2.png"))
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def save_session(conv_name: str = None):
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"""save session state to chat context"""
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chat_box.context_from_session(
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conv_name, exclude=["selected_page", "prompt", "cur_conv_name", "upload_image"]
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)
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def restore_session(conv_name: str = None):
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"""restore sesstion state from chat context"""
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chat_box.context_to_session(
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conv_name, exclude=["selected_page", "prompt", "cur_conv_name", "upload_image"]
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)
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def rerun():
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"""
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save chat context before rerun
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"""
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save_session()
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st.rerun()
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def get_messages_history(
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history_len: int, content_in_expander: bool = False
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) -> 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 = [
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x for x in msg["elements"] if x._output_method in ["markdown", "text"]
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]
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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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messages = chat_box.filter_history(history_len=history_len, filter=filter)
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if sys_msg := chat_box.context.get("system_message"):
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messages = [{"role": "system", "content": sys_msg}] + messages
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return messages
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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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@st.cache_data
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def upload_image_file(file_name: str, content: bytes) -> dict:
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'''upload image for vision model using openai sdk'''
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client = openai.Client(base_url=f"{api_address()}/v1", api_key="NONE")
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return client.files.create(file=(file_name, content), purpose="assistants").to_dict()
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def get_image_file_url(upload_file: dict) -> str:
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file_id = upload_file.get("id")
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return f"{api_address(True)}/v1/files/{file_id}/content"
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def add_conv(name: str = ""):
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conv_names = chat_box.get_chat_names()
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if not name:
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i = len(conv_names) + 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 conv_names:
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sac.alert(
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"创建新会话出错",
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f"该会话名称 “{name}” 已存在",
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color="error",
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closable=True,
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)
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else:
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chat_box.use_chat_name(name)
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st.session_state["cur_conv_name"] = name
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def del_conv(name: str = None):
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conv_names = chat_box.get_chat_names()
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name = name or chat_box.cur_chat_name
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if len(conv_names) == 1:
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sac.alert(
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"删除会话出错", f"这是最后一个会话，无法删除", color="error", closable=True
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)
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elif not name or name not in conv_names:
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sac.alert(
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"删除会话出错", f"无效的会话名称：“{name}”", color="error", closable=True
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)
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else:
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chat_box.del_chat_name(name)
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# restore_session()
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st.session_state["cur_conv_name"] = chat_box.cur_chat_name
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def clear_conv(name: str = None):
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chat_box.reset_history(name=name or None)
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# @st.cache_data
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def list_tools(_api: ApiRequest):
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return _api.list_tools() or {}
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def dialogue_page(
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api: ApiRequest,
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is_lite: bool = False,
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):
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ctx = chat_box.context
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ctx.setdefault("uid", uuid.uuid4().hex)
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ctx.setdefault("file_chat_id", None)
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ctx.setdefault("llm_model", get_default_llm())
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ctx.setdefault("temperature", Settings.model_settings.TEMPERATURE)
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st.session_state.setdefault("cur_conv_name", chat_box.cur_chat_name)
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st.session_state.setdefault("last_conv_name", chat_box.cur_chat_name)
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# sac on_change callbacks not working since st>=1.34
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if st.session_state.cur_conv_name != st.session_state.last_conv_name:
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save_session(st.session_state.last_conv_name)
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restore_session(st.session_state.cur_conv_name)
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st.session_state.last_conv_name = st.session_state.cur_conv_name
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# st.write(chat_box.cur_chat_name)
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# st.write(st.session_state)
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# st.write(chat_box.context)
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@st.experimental_dialog("模型配置", width="large")
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def llm_model_setting():
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# 模型
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cols = st.columns(3)
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platforms = ["所有"] + list(get_config_platforms())
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platform = cols[0].selectbox("选择模型平台", platforms, key="platform")
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llm_models = list(
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get_config_models(
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model_type="llm", platform_name=None if platform == "所有" else platform
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)
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)
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llm_models += list(
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get_config_models(
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model_type="image2text", platform_name=None if platform == "所有" else platform
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)
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)
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llm_model = cols[1].selectbox("选择LLM模型", llm_models, key="llm_model")
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temperature = cols[2].slider("Temperature", 0.0, 1.0, key="temperature")
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system_message = st.text_area("System Message:", key="system_message")
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if st.button("OK"):
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rerun()
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@st.experimental_dialog("重命名会话")
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def rename_conversation():
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name = st.text_input("会话名称")
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if st.button("OK"):
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chat_box.change_chat_name(name)
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restore_session()
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st.session_state["cur_conv_name"] = name
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rerun()
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with st.sidebar:
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tab1, tab2 = st.tabs(["工具设置", "会话设置"])
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with tab1:
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use_agent = st.checkbox(
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"启用Agent", help="请确保选择的模型具备Agent能力", key="use_agent"
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)
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output_agent = st.checkbox("显示 Agent 过程", key="output_agent")
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# 选择工具
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tools = list_tools(api)
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tool_names = ["None"] + list(tools)
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if use_agent:
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# selected_tools = sac.checkbox(list(tools), format_func=lambda x: tools[x]["title"], label="选择工具",
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# check_all=True, key="selected_tools")
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selected_tools = st.multiselect(
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"选择工具",
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list(tools),
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format_func=lambda x: tools[x]["title"],
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key="selected_tools",
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)
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else:
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# selected_tool = sac.buttons(list(tools), format_func=lambda x: tools[x]["title"], label="选择工具",
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# key="selected_tool")
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selected_tool = st.selectbox(
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"选择工具",
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tool_names,
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format_func=lambda x: tools.get(x, {"title": "None"})["title"],
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key="selected_tool",
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)
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selected_tools = [selected_tool]
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selected_tool_configs = {
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name: tool["config"]
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for name, tool in tools.items()
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if name in selected_tools
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}
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if "None" in selected_tools:
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selected_tools.remove("None")
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# 当不启用Agent时，手动生成工具参数
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# TODO: 需要更精细的控制控件
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tool_input = {}
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if not use_agent and len(selected_tools) == 1:
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with st.expander("工具参数", True):
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for k, v in tools[selected_tools[0]]["args"].items():
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if choices := v.get("choices", v.get("enum")):
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tool_input[k] = st.selectbox(v["title"], choices)
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else:
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if v["type"] == "integer":
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tool_input[k] = st.slider(
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v["title"], value=v.get("default")
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)
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elif v["type"] == "number":
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tool_input[k] = st.slider(
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v["title"], value=v.get("default"), step=0.1
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)
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else:
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tool_input[k] = st.text_input(
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v["title"], v.get("default")
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)
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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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files_upload = None
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# 用于图片对话、文生图的图片
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upload_image = None
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def on_upload_file_change():
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if f := st.session_state.get("upload_image"):
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name = ".".join(f.name.split(".")[:-1]) + ".png"
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st.session_state["cur_image"] = (name, PILImage.open(f))
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else:
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st.session_state["cur_image"] = (None, None)
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st.session_state.pop("paste_image", None)
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st.file_uploader("上传图片", ["bmp", "jpg", "jpeg", "png"],
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accept_multiple_files=False,
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key="upload_image",
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on_change=on_upload_file_change)
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paste_image = paste_image_button("黏贴图像", key="paste_image")
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cur_image = st.session_state.get("cur_image", (None, None))
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if cur_image[1] is None and paste_image.image_data is not None:
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name = hashlib.md5(paste_image.image_data.tobytes()).hexdigest()+".png"
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cur_image = (name, paste_image.image_data)
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if cur_image[1] is not None:
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st.image(cur_image[1])
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buffer = io.BytesIO()
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cur_image[1].save(buffer, format="png")
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upload_image = upload_image_file(cur_image[0], buffer.getvalue())
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with tab2:
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# 会话
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cols = st.columns(3)
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conv_names = chat_box.get_chat_names()
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def on_conv_change():
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print(conversation_name, st.session_state.cur_conv_name)
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save_session(conversation_name)
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restore_session(st.session_state.cur_conv_name)
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conversation_name = sac.buttons(
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conv_names,
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label="当前会话：",
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key="cur_conv_name",
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# on_change=on_conv_change, # not work
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)
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chat_box.use_chat_name(conversation_name)
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conversation_id = chat_box.context["uid"]
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if cols[0].button("新建", on_click=add_conv):
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...
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if cols[1].button("重命名"):
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rename_conversation()
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if cols[2].button("删除", on_click=del_conv):
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...
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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。"
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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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|||
|
|
|
|||
|
|
# TODO: 这里的内容有点奇怪，从后端导入Settings.model_settings.LLM_MODEL_CONFIG，然后又从前端传到后端。需要优化
|
|||
|
|
# 传入后端的内容
|
|||
|
|
llm_model_config = Settings.model_settings.LLM_MODEL_CONFIG
|
|||
|
|
chat_model_config = {key: {} for key in llm_model_config.keys()}
|
|||
|
|
for key in llm_model_config:
|
|||
|
|
if c := llm_model_config[key]:
|
|||
|
|
model = c.get("model", "").strip() or get_default_llm()
|
|||
|
|
chat_model_config[key][model] = llm_model_config[key]
|
|||
|
|
llm_model = ctx.get("llm_model")
|
|||
|
|
if llm_model is not None:
|
|||
|
|
chat_model_config["llm_model"][llm_model] = llm_model_config["llm_model"].get(
|
|||
|
|
llm_model, {}
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
# chat input
|
|||
|
|
with bottom():
|
|||
|
|
cols = st.columns([1, 0.2, 15, 1])
|
|||
|
|
if cols[0].button(":gear:", help="模型配置"):
|
|||
|
|
widget_keys = ["platform", "llm_model", "temperature", "system_message"]
|
|||
|
|
chat_box.context_to_session(include=widget_keys)
|
|||
|
|
llm_model_setting()
|
|||
|
|
if cols[-1].button(":wastebasket:", help="清空对话"):
|
|||
|
|
chat_box.reset_history()
|
|||
|
|
rerun()
|
|||
|
|
# with cols[1]:
|
|||
|
|
# mic_audio = audio_recorder("", icon_size="2x", key="mic_audio")
|
|||
|
|
prompt = cols[2].chat_input(chat_input_placeholder, key="prompt")
|
|||
|
|
if prompt:
|
|||
|
|
history = get_messages_history(
|
|||
|
|
chat_model_config["llm_model"]
|
|||
|
|
.get(next(iter(chat_model_config["llm_model"])), {})
|
|||
|
|
.get("history_len", 1)
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
is_vision_chat = upload_image and not selected_tools
|
|||
|
|
|
|||
|
|
if is_vision_chat: # multimodal chat
|
|||
|
|
chat_box.user_say([Image(get_image_file_url(upload_image), width=100), Markdown(prompt)])
|
|||
|
|
else:
|
|||
|
|
chat_box.user_say(prompt)
|
|||
|
|
if files_upload:
|
|||
|
|
if files_upload["images"]:
|
|||
|
|
st.markdown(
|
|||
|
|
f'<img src="data:image/jpeg;base64,{files_upload["images"][0]}" width="300">',
|
|||
|
|
unsafe_allow_html=True,
|
|||
|
|
)
|
|||
|
|
elif files_upload["videos"]:
|
|||
|
|
st.markdown(
|
|||
|
|
f'<video width="400" height="300" controls><source src="data:video/mp4;base64,{files_upload["videos"][0]}" type="video/mp4"></video>',
|
|||
|
|
unsafe_allow_html=True,
|
|||
|
|
)
|
|||
|
|
elif files_upload["audios"]:
|
|||
|
|
st.markdown(
|
|||
|
|
f'<audio controls><source src="data:audio/wav;base64,{files_upload["audios"][0]}" type="audio/wav"></audio>',
|
|||
|
|
unsafe_allow_html=True,
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
chat_box.ai_say("正在思考...")
|
|||
|
|
text = ""
|
|||
|
|
started = False
|
|||
|
|
|
|||
|
|
client = openai.Client(base_url=f"{api_address()}/chat", api_key="NONE")
|
|||
|
|
if is_vision_chat: # multimodal chat
|
|||
|
|
content = [
|
|||
|
|
{"type": "text", "text": prompt},
|
|||
|
|
{"type": "image_url", "image_url": {"url": get_image_file_url(upload_image)}}
|
|||
|
|
]
|
|||
|
|
messages = [{"role": "user", "content": content}]
|
|||
|
|
else:
|
|||
|
|
messages = history + [{"role": "user", "content": prompt}]
|
|||
|
|
tools = list(selected_tool_configs)
|
|||
|
|
if len(selected_tools) == 1:
|
|||
|
|
tool_choice = selected_tools[0]
|
|||
|
|
else:
|
|||
|
|
tool_choice = None
|
|||
|
|
# 如果 tool_input 中有空的字段，设为用户输入
|
|||
|
|
for k in tool_input:
|
|||
|
|
if tool_input[k] in [None, ""]:
|
|||
|
|
tool_input[k] = prompt
|
|||
|
|
|
|||
|
|
extra_body = dict(
|
|||
|
|
metadata=files_upload,
|
|||
|
|
chat_model_config=chat_model_config,
|
|||
|
|
conversation_id=conversation_id,
|
|||
|
|
tool_input=tool_input,
|
|||
|
|
upload_image=upload_image,
|
|||
|
|
)
|
|||
|
|
stream = not is_vision_chat
|
|||
|
|
params = dict(
|
|||
|
|
messages=messages,
|
|||
|
|
model=llm_model,
|
|||
|
|
stream=stream, # TODO：xinference qwen-vl-chat 流式输出会出错，后续看更新
|
|||
|
|
extra_body=extra_body,
|
|||
|
|
)
|
|||
|
|
if tools:
|
|||
|
|
params["tools"] = tools
|
|||
|
|
if tool_choice:
|
|||
|
|
params["tool_choice"] = tool_choice
|
|||
|
|
if Settings.model_settings.MAX_TOKENS:
|
|||
|
|
params["max_tokens"] = Settings.model_settings.MAX_TOKENS
|
|||
|
|
|
|||
|
|
if stream:
|
|||
|
|
try:
|
|||
|
|
for d in client.chat.completions.create(**params):
|
|||
|
|
# import rich
|
|||
|
|
# rich.print(d)
|
|||
|
|
message_id = d.message_id
|
|||
|
|
metadata = {
|
|||
|
|
"message_id": message_id,
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
# clear initial message
|
|||
|
|
if not started:
|
|||
|
|
chat_box.update_msg("", streaming=False)
|
|||
|
|
started = True
|
|||
|
|
|
|||
|
|
if d.status == AgentStatus.error:
|
|||
|
|
st.error(d.choices[0].delta.content)
|
|||
|
|
elif d.status == AgentStatus.llm_start:
|
|||
|
|
if not output_agent:
|
|||
|
|
continue
|
|||
|
|
chat_box.insert_msg("正在解读工具输出结果...")
|
|||
|
|
text = d.choices[0].delta.content or ""
|
|||
|
|
elif d.status == AgentStatus.llm_new_token:
|
|||
|
|
if not output_agent:
|
|||
|
|
continue
|
|||
|
|
text += d.choices[0].delta.content or ""
|
|||
|
|
chat_box.update_msg(
|
|||
|
|
text.replace("\n", "\n\n"), streaming=True, metadata=metadata
|
|||
|
|
)
|
|||
|
|
elif d.status == AgentStatus.llm_end:
|
|||
|
|
if not output_agent:
|
|||
|
|
continue
|
|||
|
|
text += d.choices[0].delta.content or ""
|
|||
|
|
chat_box.update_msg(
|
|||
|
|
text.replace("\n", "\n\n"), streaming=False, metadata=metadata
|
|||
|
|
)
|
|||
|
|
# tool 的输出与 llm 输出重复了
|
|||
|
|
# elif d.status == AgentStatus.tool_start:
|
|||
|
|
# formatted_data = {
|
|||
|
|
# "Function": d.choices[0].delta.tool_calls[0].function.name,
|
|||
|
|
# "function_input": d.choices[0].delta.tool_calls[0].function.arguments,
|
|||
|
|
# }
|
|||
|
|
# formatted_json = json.dumps(formatted_data, indent=2, ensure_ascii=False)
|
|||
|
|
# text = """\n```{}\n```\n""".format(formatted_json)
|
|||
|
|
# chat_box.insert_msg( # TODO: insert text directly not shown
|
|||
|
|
# Markdown(text, title="Function call", in_expander=True, expanded=True, state="running"))
|
|||
|
|
# elif d.status == AgentStatus.tool_end:
|
|||
|
|
# tool_output = d.choices[0].delta.tool_calls[0].tool_output
|
|||
|
|
# if d.message_type == MsgType.IMAGE:
|
|||
|
|
# for url in json.loads(tool_output).get("images", []):
|
|||
|
|
# url = f"{api.base_url}/media/{url}"
|
|||
|
|
# chat_box.insert_msg(Image(url))
|
|||
|
|
# chat_box.update_msg(expanded=False, state="complete")
|
|||
|
|
# else:
|
|||
|
|
# text += """\n```\nObservation:\n{}\n```\n""".format(tool_output)
|
|||
|
|
# chat_box.update_msg(text, streaming=False, expanded=False, state="complete")
|
|||
|
|
elif d.status == AgentStatus.agent_finish:
|
|||
|
|
text = d.choices[0].delta.content or ""
|
|||
|
|
chat_box.update_msg(text.replace("\n", "\n\n"))
|
|||
|
|
elif d.status is None: # not agent chat
|
|||
|
|
if getattr(d, "is_ref", False):
|
|||
|
|
context = str(d.tool_output)
|
|||
|
|
if isinstance(d.tool_output, dict):
|
|||
|
|
docs = d.tool_output.get("docs", [])
|
|||
|
|
source_documents = format_reference(kb_name=d.tool_output.get("knowledge_base"),
|
|||
|
|
docs=docs,
|
|||
|
|
api_base_url=api_address(is_public=True))
|
|||
|
|
context = "\n".join(source_documents)
|
|||
|
|
|
|||
|
|
chat_box.insert_msg(
|
|||
|
|
Markdown(
|
|||
|
|
context,
|
|||
|
|
in_expander=True,
|
|||
|
|
state="complete",
|
|||
|
|
title="参考资料",
|
|||
|
|
)
|
|||
|
|
)
|
|||
|
|
chat_box.insert_msg("")
|
|||
|
|
elif getattr(d, "tool_call", None) == "text2images": # TODO：特定工具特别处理，需要更通用的处理方式
|
|||
|
|
for img in d.tool_output.get("images", []):
|
|||
|
|
chat_box.insert_msg(Image(f"{api.base_url}/media/{img}"), pos=-2)
|
|||
|
|
else:
|
|||
|
|
text += d.choices[0].delta.content or ""
|
|||
|
|
chat_box.update_msg(
|
|||
|
|
text.replace("\n", "\n\n"), streaming=True, metadata=metadata
|
|||
|
|
)
|
|||
|
|
chat_box.update_msg(text, streaming=False, metadata=metadata)
|
|||
|
|
except Exception as e:
|
|||
|
|
st.error(e.body)
|
|||
|
|
else:
|
|||
|
|
try:
|
|||
|
|
d =client.chat.completions.create(**params)
|
|||
|
|
chat_box.update_msg(d.choices[0].message.content or "", streaming=False)
|
|||
|
|
except Exception as e:
|
|||
|
|
st.error(e.body)
|
|||
|
|
|
|||
|
|
# if os.path.exists("tmp/image.jpg"):
|
|||
|
|
# with open("tmp/image.jpg", "rb") as image_file:
|
|||
|
|
# encoded_string = base64.b64encode(image_file.read()).decode()
|
|||
|
|
# img_tag = (
|
|||
|
|
# f'<img src="data:image/jpeg;base64,{encoded_string}" width="300">'
|
|||
|
|
# )
|
|||
|
|
# st.markdown(img_tag, unsafe_allow_html=True)
|
|||
|
|
# os.remove("tmp/image.jpg")
|
|||
|
|
# chat_box.show_feedback(**feedback_kwargs,
|
|||
|
|
# key=message_id,
|
|||
|
|
# on_submit=on_feedback,
|
|||
|
|
# kwargs={"message_id": message_id, "history_index": len(chat_box.history) - 1})
|
|||
|
|
|
|||
|
|
# elif dialogue_mode == "文件对话":
|
|||
|
|
# if st.session_state["file_chat_id"] is None:
|
|||
|
|
# st.error("请先上传文件再进行对话")
|
|||
|
|
# st.stop()
|
|||
|
|
# chat_box.ai_say([
|
|||
|
|
# f"正在查询文件 `{st.session_state['file_chat_id']}` ...",
|
|||
|
|
# Markdown("...", in_expander=True, title="文件匹配结果", state="complete"),
|
|||
|
|
# ])
|
|||
|
|
# text = ""
|
|||
|
|
# for d in api.file_chat(prompt,
|
|||
|
|
# knowledge_id=st.session_state["file_chat_id"],
|
|||
|
|
# top_k=kb_top_k,
|
|||
|
|
# score_threshold=score_threshold,
|
|||
|
|
# history=history,
|
|||
|
|
# model=llm_model,
|
|||
|
|
# prompt_name=prompt_template_name,
|
|||
|
|
# temperature=temperature):
|
|||
|
|
# if error_msg := check_error_msg(d):
|
|||
|
|
# st.error(error_msg)
|
|||
|
|
# elif chunk := d.get("answer"):
|
|||
|
|
# text += chunk
|
|||
|
|
# chat_box.update_msg(text, element_index=0)
|
|||
|
|
# chat_box.update_msg(text, element_index=0, streaming=False)
|
|||
|
|
# chat_box.update_msg("\n\n".join(d.get("docs", [])), element_index=1, streaming=False)
|
|||
|
|
|
|||
|
|
now = datetime.now()
|
|||
|
|
with tab2:
|
|||
|
|
cols = st.columns(2)
|
|||
|
|
export_btn = cols[0]
|
|||
|
|
if cols[1].button(
|
|||
|
|
"清空对话",
|
|||
|
|
use_container_width=True,
|
|||
|
|
):
|
|||
|
|
chat_box.reset_history()
|
|||
|
|
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,
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
# st.write(chat_box.history)
|