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Dockerfile

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+FROM python:3.9
+
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+COPY . .
+
+CMD ["panel", "serve", "/code/app.py", "--address", "0.0.0.0", "--port", "7860", "--allow-websocket-origin", "moazzamdev-Chat_with_web_using_panel.hf.space",  "--allow-websocket-origin", "0.0.0.0:7860"]

app.py

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+import hvplot.pandas
+import numpy as np
+import panel as pn
+import pandas as pd
+import openai
+from llama_index import VectorStoreIndex, download_loader
+from langchain.agents import initialize_agent, Tool
+from langchain.llms import OpenAI
+from langchain.chains.conversation.memory import ConversationBufferMemory
+from panel.chat import ChatInterface
+import time
+pn.extension("perspective")
+
+def callback(contents: str, user: str, instance: pn.chat.ChatInterface):
+    message = f"Echoing {user}: {contents}"
+    return message
+chat_interface = pn.chat.ChatInterface(callback=callback)
+msg_panel = chat_interface.send(
+    "Enter a WEB link and ask anything!-\nNote: images in the link will be ignored!!!",
+    user="assistant",
+    respond=False,
+)
+website_url_input = pn.widgets.TextInput(name='Website URL', placeholder="https://www.google.com/")
+submit = pn.widgets.Button(name='Submit', button_type='primary')
+
+
+def on_submit(event, contents, ):
+
+    try:
+        SimpleWebPageReader = download_loader("SimpleWebPageReader")
+
+        # Set OpenAI API key
+        openai.api_key = "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"  # Replace with your actual API key
+
+        # Get the entered website URL
+        website_url = website_url_input.value
+
+        if website_url:
+            # Initialize SimpleWebPageReader with the provided website URL
+            loader = SimpleWebPageReader()
+            documents = loader.load_data(urls=[website_url])
+
+            # Create VectorStoreIndex from documents
+            index = VectorStoreIndex.from_documents(documents)
+
+            # Initialize LangChain OpenAI
+            index = VectorStoreIndex.from_documents(documents)
+            llm = OpenAI(openai_api_key="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", temperature=0, streaming = True
+                         )
+
+            # Initialize ConversationBufferMemory
+            memory = ConversationBufferMemory(memory_key="chat_history")
+
+            # Initialize agent chain
+            tools = [
+                Tool(
+                    name="Website Index",
+                    func=lambda q: index.as_query_engine(),
+                    description="Useful when you want to answer questions about the text on websites.",
+                ),
+            ]
+
+
+            query_engine = index.as_query_engine()
+            response = query_engine.query(contents)
+
+            return str(response),
+
+    except Exception as e:
+        print(f"Error: {e}")
+def even_or_odd(contents, user, instance):
+    response_tuple = on_submit(event='', contents=contents)
+
+    # Extracting the first element of the tuple and converting it to a string
+    response_string = str(response_tuple)
+
+    return response_string
+# Set the callback function for the button click event
+submit.on_click(on_submit)
+
+# Instantiate the template with widgets displayed in the sidebar
+template = pn.template.BootstrapTemplate(
+    title='Chat with Web',
+    sidebar=[website_url_input, submit,
+             msg_panel],
+    header=[],
+
+)
+
+ChatInterface(callback=even_or_odd)
+def callback(contents: str, user: str, instance: pn.chat.ChatInterface):
+    message = query_engine.query(contents)
+    return message
+
+template.main.append(
+
+    ChatInterface(
+        callback=even_or_odd,
+        user="User",
+        avatar="🧑",
+        callback_user="System",
+    ),
+)
+
+# Display the app
+template.servable()