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This video demonstrates how to use the AI Web scraper template.
import logging
from fastapi import FastAPI, Form, Request
from fastapi.responses import HTMLResponse, RedirectResponse
from fastapi.responses import HTMLResponse
from fastapi.templating import Jinja2Templates
# Removed WebFetcher import as it's no longer needed with the new Google CSE integration
import uvicorn
from typing import List
from abilities import llm_prompt
app = FastAPI()
templates = Jinja2Templates(directory="templates")
# Removed SolutionFinder class as it's no longer needed with the new Google CSE integration
import json
@app.get("/", response_class=HTMLResponse)
async def read_index(request: Request):
return templates.TemplateResponse("index.html", {"request": request})
@app.get("/solutions", response_class=HTMLResponse)
async def solutions(request: Request):
solutions = request.app.state.solutionsFrequently Asked Questions
How can the AI Web Scraper benefit businesses in customer support?
The AI Web Scraper can significantly enhance customer support by providing a quick and efficient way to find solutions to common problems. When customers reach out with issues, support agents can use the AI Web Scraper to quickly search for relevant solutions from a curated list of websites. This can lead to faster resolution times, improved customer satisfaction, and reduced workload on support teams.
What industries could benefit most from implementing the AI Web Scraper?
The AI Web Scraper is versatile and can be beneficial across various industries. However, it could be particularly valuable in: - Tech industry: For troubleshooting software and hardware issues - E-commerce: Addressing common customer queries and product-related problems - Healthcare: Providing general health information and answering common medical questions - Education: Helping students and educators find resources for various subjects - Manufacturing: Assisting with troubleshooting equipment issues and maintenance procedures
How can the AI Web Scraper be customized for specific business needs?
The AI Web Scraper can be tailored to meet specific business needs by: - Customizing the Google Custom Search Engine (CSE) to focus on industry-specific websites - Modifying the HTML templates to match the company's branding - Integrating the tool with existing customer support systems - Implementing additional filters or categorization of search results based on business-specific criteria
How can I modify the AI Web Scraper to display search results directly on the page instead of using the Google CSE widget?
To display search results directly on the page, you can modify the main.py file to handle a search request and render the results. Here's an example of how you could implement this:
```python from googleapiclient.discovery import build
@app.post("/search", response_class=HTMLResponse) async def search(request: Request, query: str = Form(...)): service = build("customsearch", "v1", developerKey="YOUR_API_KEY") res = service.cse().list(q=query, cx="YOUR_CSE_ID").execute()
search_results = [
{"title": item["title"], "link": item["link"]}
for item in res.get("items", [])
]
return templates.TemplateResponse(
"search_results.html",
{"request": request, "results": search_results}
)
```
You'll also need to create a new search_results.html template to display the results.
How can I extend the AI Web Scraper to include a summary of each search result?
To include summaries, you can use the snippet field provided by the Google Custom Search API. Modify the search function in main.py as follows:
```python @app.post("/search", response_class=HTMLResponse) async def search(request: Request, query: str = Form(...)): service = build("customsearch", "v1", developerKey="YOUR_API_KEY") res = service.cse().list(q=query, cx="YOUR_CSE_ID").execute()
search_results = [
{
"title": item["title"],
"link": item["link"],
"summary": item.get("snippet", "No summary available")
}
for item in res.get("items", [])
]
return templates.TemplateResponse(
"search_results.html",
{"request": request, "results": search_results}
)
```
Then, update your search_results.html template to display the summary for each result. This enhancement will provide users with more context about each search result, making the AI Web Scraper even more useful for finding relevant solutions quickly.
Created: | Last Updated:
Introduction to the AI Web Scraper Template
Welcome to the AI Web Scraper template! This template is designed to help you build a web application that leverages Google's Custom Search Engine to generate a curated list of websites. These websites can provide solutions to specific problems or situations you may encounter. This step-by-step guide will walk you through the process of using this template on the Lazy platform, ensuring you can deploy your application with ease.
Getting Started
To begin using the AI Web Scraper template, simply click on "Start with this Template" within the Lazy Builder interface. This will pre-populate the code in the Lazy Builder, so you won't need to copy, paste, or delete any code manually.
Test: Deploying the App
Once you have started with the template, the next step is to deploy your application. Press the "Test" button to initiate the deployment process. The Lazy CLI will handle the deployment, and you won't need to worry about installing libraries or setting up your environment.
Entering Input
If the template requires user input, the Lazy App's CLI interface will prompt you for it after you press the "Test" button. Provide the necessary input as prompted to ensure the app functions correctly.
Using the App
After deployment, if the template includes a frontend, you will be able to interact with the user interface. The AI Web Scraper app provides an interface where you can search for solutions using Google's Custom Search Engine. You can access this interface through a dedicated server link that Lazy will print out for you.
If the code uses FastAPI, Lazy will also provide you with a documentation link, which you can use to understand and interact with the API endpoints.
Integrating the App
If you need to integrate the AI Web Scraper app into an external service or frontend, you may need to add the app's server link or API endpoints to the external tool. Follow the specific instructions provided by the external tool to complete this integration.
For example, if you need to add API endpoints to an external tool, ensure you have the correct scopes and know where to add the code. If the template includes sample code that is helpful for integration, make sure to use it as a reference.
Remember, this guide is here to help you through the mandatory steps to run and integrate the AI Web Scraper template. If you encounter any issues or have questions, refer to the documentation links provided in the code or reach out for support through the Lazy platform.
Happy building!
Here are 5 key business benefits for this AI Web Scraper template:
Template Benefits
-
Efficient Problem Solving: Quickly generates curated lists of relevant websites to help solve specific business problems or challenges, saving time and effort in research.
-
Enhanced Customer Support: Can be integrated into customer service platforms to provide rapid, AI-assisted solutions to common customer inquiries or issues.
-
Market Research Tool: Helps businesses gather competitive intelligence and stay updated on industry trends by efficiently aggregating relevant online resources.
-
Training and Development Aid: Supports employee learning and development by providing targeted resources for skill improvement and knowledge acquisition.
-
Product Ideation Assistant: Assists in the ideation phase of product development by aggregating diverse solutions and innovations related to specific problems or needs in the market.
Technologies
Python App Templates for Scraping, Machine Learning, Data Science and More
