7. Scrape the website and display the result • Add a "Scrape" button using 'st.button()'
• When the button is clicked, run the SmartScraperGraph and display the result using 'st.write()'
@saboo_shubham_
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Web Scraping with SmartScraperGraph and Streamlit Button
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Initializing SmartScraperGraph with Prompt URL and Config
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6. Initialize the SmartScraperGraph • Create an instance of SmartScraperGraph with the user prompt, website URL, and graph configuration
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Building a Web Scraper with Streamlit URL and Prompt Inputs
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5. Get the website URL and user prompt • Use 'st.text_input()' to get the URL of the website to scrape
• Use 'st.text_input()' to get the user prompt specifying what to scrape from the website -
Configuring SmartScraperGraph with OpenAI API and Model Selection
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4. Configure the SmartScraperGraph • If the OpenAI API key is provided, create a 'graph_config' dictionary with the API key and selected model
• Allow the user to select the model using '
http://
st.radio()' -
Building Streamlit App with OpenAI API Integration
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3. Set up the Streamlit App Streamlit lets you create user interface with just python code, for this app we will: • Add a title to the app using 'st.title()'
• Create a text input box for the user to enter their OpenAI API key using 'st.text_input()' -
Building AI Web Apps with Streamlit and ScrapegraphAI
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2. Import necessary libraries • Streamlit for building the web app
• Scrapegraph AI for creating scrapping pipelines with LLMs -
ScrapeGraphAI: LLM-Powered Web Scraping Pipeline Library
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We'll use ScrapeGraphAI, a Python library that uses LLMs to create smart scraping pipelines. It involves four main steps:
1. Fetch: Retrieve the data
2. Parse: Analyze and structure the data
3. RAG: Processes the parsed data to find relevant information
4. Generate Answer -
Build Web Scraping AI Agent with RAG in 30 Lines Python
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Build a Web Scrapping AI Agent with RAG in just 30 lines of Python Code (step-by-step instructions):
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LLM Tips and Tutorials from Shubham Saboo
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If you find this useful, RT to share it with your friends.
— Shubham Saboo (@Saboo_Shubham_) 11 mai 2024
Don't forget to follow me @Saboo_Shubham_ for more such LLMs tips and tutorials. https://t.co/gVhaqgZNBuIf you find this useful, RT to share it with your friends. Don't forget to follow me @Saboo_Shubham_ for more such LLMs tips and tutorials.
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Service Optimizes Multiple LLM API Access at Discounted Rates
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I tried the service and it works. Not sure how they are providing access to all these models at such discounted rates. Only thing I can think of is that they figured out some optimized way of using various LLM APIs.