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| from langchain_huggingface import HuggingFaceEndpoint as HF | |
| from subprocess import Popen, PIPE as P | |
| from langchain_experimental.tools.python.tool import PythonREPLTool as PYT | |
| from langchain.agents import load_tools, initialize_agent Agent,AgentExecutor as Ex, AgentType as Type | |
| from langchain.agents.agent_toolkits import create_retriever_tool as crt | |
| from langchain_community.agent_toolkits import FileManagementToolkit as FMT | |
| from langchain.tools import Tool,YoutubeSearchTool as YTS | |
| from langchain.memory import ConversationalBufferMomory as MEM,RedisChatHistory as HIS | |
| from langchain.schema import SystemMessage as SM,HumanMessage as HM | |
| from langchain import hub | |
| import os | |
| from langchain.retrievers import WikipediaRetriever as Wiki | |
| import gradio as gr | |
| chatbot = gr.Chatbot( | |
| label="SYAI4.1", | |
| show_copy_button=True, | |
| likeable=True, | |
| layout="panel" | |
| ) | |
| def terminal(c): | |
| a=Popen(c,shell=True,stdin=P,stdout=P,stderr=P) | |
| return a.stdout.read()+a.stderr.read() | |
| tools=FMT().get_tools() | |
| tools.append(PYT()) | |
| tools.append(YTS()) | |
| tools.extend(load_tools(["requests"])) | |
| tools.extend(load_tools(["llm-math","ddg-search"])) | |
| tools.append(Tool.from_function(func=terminal,name="terminal")) | |
| tools.append(crt(name="wiki",description="위키 백과를 검색하여 정보를 가져온다",retriever=Wiki(lang="ko",top_k_results=1))) | |
| llm=HF(repo_id="peterpeter8585/syai4.0") | |
| prompt=hub.pull("hwchase17/structed-chat-agent") | |
| def chat(message, | |
| history: list[tuple[str, str]], | |
| system_message, | |
| max_tokens, | |
| temperature, | |
| top_p, chat_session=""): | |
| messages=[SM(content=system_message+"And, Your name is Chatchat")] | |
| for val in history: | |
| if val[0]: | |
| messages.append(HM(content=val[0])) | |
| if val[1]: | |
| messages.append(AM(content=val[1])) | |
| messages.append(HM(content=message)) | |
| history1=HIS(session_id=chat_session, url=os.environ["URL"]) | |
| memory=MEM(chat_memory=history1,memory_key="history") | |
| agent=EX(agent=Agent(tools=tools,llm=llm,memory=memory,agent=Type.STRUCTED_CHAT_ZERO_SHOT_REACT_DESCRIPTION),tools=tools,verbose=True,handle_parsing_errors=True) | |
| yield agent.invoke(messages) | |
| ai1=gr.ChatInterface( | |
| chat, | |
| chatbot=chatbot, | |
| additional_inputs=[ | |
| gr.Textbox(value="You are a helpful assistant.", label="System message", interactive=True), | |
| gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"), | |
| gr.Slider(minimum=0.1, maximum=4.0, value=0.1, step=0.1, label="Temperature"), | |
| gr.Slider( | |
| minimum=0.1, | |
| maximum=1.0, | |
| value=0.1, | |
| step=0.05, | |
| label="Top-p (nucleus sampling)", | |
| ), | |
| gr.Textbox(label="chat_id(please enter the chat id!)") | |
| ], | |
| ) | |
| with gr.Blocks(theme="shivi/calm_seafoam") as ai: | |
| gr.TabbedInterface([ai1],["Chatchat"]) | |
| ai.launch() |