Commit
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3a1c689
1
Parent(s):
8a7a0ca
Update app.py
Browse files
app.py
CHANGED
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import hvplot.pandas
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import numpy as np
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import panel as pn
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import pandas
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import openai
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from llama_index import VectorStoreIndex, download_loader
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from langchain.agents import initialize_agent, Tool
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from langchain.llms import OpenAI
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from langchain.chains.conversation.memory import ConversationBufferMemory
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from panel.chat import ChatInterface
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import time
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pn.extension("perspective")
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website_url_input = pn.widgets.TextInput(name='Website URL', placeholder="https://www.google.com/")
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submit = pn.widgets.Button(name='Submit', button_type='primary')
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def on_submit(event, contents, ):
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try:
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SimpleWebPageReader = download_loader("SimpleWebPageReader")
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# Set OpenAI API key
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openai.api_key = "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" # Replace with your actual API key
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# Get the entered website URL
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website_url = website_url_input.value
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if website_url:
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# Initialize SimpleWebPageReader with the provided website URL
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loader = SimpleWebPageReader()
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documents = loader.load_data(urls=[website_url])
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# Create VectorStoreIndex from documents
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index = VectorStoreIndex.from_documents(documents)
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# Initialize LangChain OpenAI
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index = VectorStoreIndex.from_documents(documents)
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llm = OpenAI(openai_api_key="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", temperature=0, streaming = True
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)
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# Initialize ConversationBufferMemory
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memory = ConversationBufferMemory(memory_key="chat_history")
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# Initialize agent chain
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tools = [
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Tool(
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name="Website Index",
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func=lambda q: index.as_query_engine(),
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description="Useful when you want to answer questions about the text on websites.",
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),
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]
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query_engine = index.as_query_engine()
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response = query_engine.query(contents)
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return str(response),
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except Exception as e:
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print(f"Error: {e}")
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def even_or_odd(contents, user, instance):
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response_tuple = on_submit(event='', contents=contents)
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# Extracting the first element of the tuple and converting it to a string
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response_string = str(response_tuple)
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return response_string
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# Set the callback function for the button click event
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submit.on_click(on_submit)
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# Instantiate the template with widgets displayed in the sidebar
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template = pn.template.BootstrapTemplate(
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title='Chat with Web',
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sidebar=[website_url_input, submit,
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msg_panel],
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header=[],
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message = query_engine.query(contents)
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return message
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import panel as pn
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import hvplot.pandas
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# Load Data
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from bokeh.sampledata.autompg import autompg_clean as df
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# Make DataFrame Pipeline Interactive
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idf = df.interactive()
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# Define Panel widgets
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cylinders = pn.widgets.IntSlider(name='Cylinders', start=4, end=8, step=2)
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mfr = pn.widgets.ToggleGroup(
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name='MFR',
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options=['ford', 'chevrolet', 'honda', 'toyota', 'audi'],
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value=['ford', 'chevrolet', 'honda', 'toyota', 'audi'],
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button_type='success')
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yaxis = pn.widgets.RadioButtonGroup(
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name='Y axis',
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options=['hp', 'weight'],
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button_type='success'
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)
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# Combine pipeline and widgets
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ipipeline = (
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idf[
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(idf.cyl == cylinders) &
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(idf.mfr.isin(mfr))
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]
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.groupby(['origin', 'mpg'])[yaxis].mean()
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.to_frame()
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.reset_index()
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.sort_values(by='mpg')
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.reset_index(drop=True)
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# Pipe to hvplot
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ihvplot = ipipeline.hvplot(x='mpg', y=yaxis, by='origin', color=["#ff6f69", "#ffcc5c", "#88d8b0"], line_width=6, height=400)
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# Layout using Template
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template = pn.template.FastListTemplate(
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title='Interactive DataFrame Dashboards with hvplot .interactive',
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sidebar=[cylinders, 'Manufacturers', mfr, 'Y axis' , yaxis],
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main=[ihvplot.panel()],
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accent_base_color="#88d8b0",
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header_background="#88d8b0",
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)
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template.servable()
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