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