import gradio as gr from langchain.chains import LLMChain from langchain.chat_models import ChatOpenAI from langchain.document_loaders import TextLoader from agents.tools.python_code_tool import generate_and_excute_python_code from chains import HumanFeedBackChain, contextRewriteChain from embedding import CustomEmbedding from memories import HumenFeedbackBufferMemory from langchain.memory import ConversationBufferMemory from promopts import FEEDBACK, FEEDBACK_PROMPT from agents.code_generate_agent import code_agent_executor, code_agent_tools # llm = ChatOpenAI(temperature=0.7) baMemory = HumenFeedbackBufferMemory( input_key="input", human_prefix="Answer", ai_prefix="AI") baChain = HumanFeedBackChain(verbose=True, memory=baMemory) """读取document/business_context.py文件内容作为context""" context_path = "./documents/bussiness_context/business_context.md" def sendMessage(chatbot, input): chatbot.append(( (None if len(input) == 0 else input), None)) return chatbot def clearMemory(chatbot): chatbot.clear() if baMemory != None: baMemory.clear() return chatbot, "" def loadContext(): textloader = TextLoader(context_path) return textloader.load()[0].page_content def saveContext(context): with open(context_path, 'w') as f: f.write(context) def feedBack(context, story, chatbot=[], input=""): if len(input) > 0: context += (f"\n\n {input}") saveContext(context) response = baChain.run( input=(input if len(input) == 0 else input), context=context, story=story, stop="\nAnswer:") chatbot[-1][1] = response return chatbot, "", context customerEmbedding = CustomEmbedding() faqChain = customerEmbedding.getFAQChain() code_agent_executor = code_agent_executor() def faqFromLocal(input, chatbot=[]): response = faqChain({"question": f"{input}"}) chatbot.append((input, response["answer"])) return chatbot, "" def generateEmbeddings(chatbot=[]): response = customerEmbedding.calculateEmbedding() chatbot.append((None, response)) return chatbot def generateCode(input: str, chatbot=[], returnCode=False): if len(input) <=0: chatbot[-1][1] = None return chatbot, "" response = code_agent_executor.run( input=(input if len(input) == 0 else input)) chatbot[-1][1] = response return chatbot, "" def generateCodeByMultiPart(context: str, relateCode: str, toolName: str, chatbot=[]): input = f"请根据如下信息{toolName}:\n{context}\n\n{relateCode}" return generateCode(input, chatbot) def sendMessageByMultiPart(chatbot, context: str, relateCode: str, toolName: str): input = f"请根据如下信息{toolName}:\n{context}\n\n{relateCode}" chatbot.append((input, None)) return chatbot def rewriteContext(input, chatbot): response = contextRewriteChain.run(input=input, verbose=True) chatbot.append((input, response)) return chatbot, response def generateCodeAndExcute(input, chatbot=[]): result = generate_and_excute_python_code.run(input) chatbot.append((input, result)) return chatbot toolTextBox = [] with gr.Blocks() as demo: with gr.Row(): with gr.Tab("Business"): with gr.Row(): with gr.Column(): chatbot = gr.Chatbot().style() with gr.Row(): txt = gr.Textbox(show_label=False, placeholder="Enter text and press enter").style( container=False) with gr.Column(): with gr.Row(): context = gr.Textbox(show_label=True, label="Context", placeholder="Enter Context").style( container=False) with gr.Row(): story = gr.Textbox(show_label=True, label="User Story", placeholder="Enter User Story").style( container=False) with gr.Row(): gr.Button("Generate Scenarios").click(clearMemory, [chatbot], [chatbot, txt]).then(sendMessage, [chatbot, txt], [chatbot]).then( feedBack, [context, story, chatbot], [chatbot, txt]) with gr.Row(): with gr.Column(scale=5): gr.Button("Rewrite Context").click(rewriteContext, [context, chatbot], [chatbot, context]) with gr.Column(scale=1): gr.Button("Revert").click(loadContext, [], [context]) with gr.Row(): gr.Button("Save Context").click(saveContext, [context], []) with gr.Tab("Tech"): with gr.Row(): with gr.Column(): code_chatbot = gr.Chatbot().style() with gr.Row(): code = gr.Textbox(show_label=False, label="Code Generate", placeholder="Enter text and press enter").style( container=False) with gr.Column(): with gr.Row(): code_context = gr.Textbox(show_label=True, label="Context", placeholder="Enter Context").style( container=False) with gr.Row(): relateCode = gr.Textbox(show_label=True, label="Relate Code", placeholder="Enter Relate Code").style( container=False) for index, tool in enumerate(code_agent_tools): with gr.Row(): toolTextBox.append(gr.Textbox(show_label=False, visible=False, label=tool.name, value=tool.name).style()) gr.Button(tool.name).click( sendMessageByMultiPart, [code_chatbot, code_context, relateCode, toolTextBox[index]], [code_chatbot]).then( generateCodeByMultiPart, [code_context, relateCode, toolTextBox[index], code_chatbot], [code_chatbot, code]) with gr.Tab("FAQ"): faq_chatbot = gr.Chatbot().style() with gr.Row(): faq = gr.Textbox(show_label=False, placeholder="Enter text and press enter").style( container=False) with gr.Row(): gr.Button("Regenerate embedding").click(generateEmbeddings,[faq_chatbot], [faq_chatbot]) with gr.Tab("TOOL"): with gr.Row(): with gr.Column(): tool_request = gr.Textbox(show_label=False, placeholder="Enter your tool Request").style( container=False, show_copy_button=True) tool_button = gr.Button("Generate Code and Execute") with gr.Column(): tool_chatbot = gr.Chatbot(elem_id="chatbot").style(container=False) tool_button.click(generateCodeAndExcute,[tool_request, tool_chatbot], [tool_chatbot]) txt.submit(sendMessage, [chatbot, txt], [chatbot]).then( feedBack, [context, story, chatbot, txt], [chatbot, txt, context]) code.submit(sendMessage, [code_chatbot, code], [code_chatbot]).then( generateCode, [code, code_chatbot], [code_chatbot, code]) faq.submit(faqFromLocal, [faq, faq_chatbot], [faq_chatbot, faq]) demo.load(loadContext, [], [context]) demo.launch()