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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()
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