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Create app.py
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examples/sales_web_crawler/app.py
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examples/sales_web_crawler/app.py
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import os
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import csv
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import json
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from dotenv import load_dotenv
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from firecrawl import FirecrawlApp
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from openai import OpenAI
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from serpapi import GoogleSearch
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load_dotenv()
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# Initialize FirecrawlApp and OpenAI
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app = FirecrawlApp(api_key=os.getenv("FIRECRAWL_API_KEY"))
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client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
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def search_google(query, objective):
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"""Search Google using SerpAPI."""
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print(f"Parameters: query={query}, objective={objective}")
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search = GoogleSearch({"q": query, "api_key": os.getenv("SERP_API_KEY")})
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results = search.get_dict().get("organic_results", [])
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return {"objective": objective, "results": results}
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def scrape_url(url, objective):
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"""Scrape a website using Firecrawl."""
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print(f"Parameters: url={url}, objective={objective}")
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scrape_status = app.scrape_url(
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url,
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params={'formats': ['markdown']}
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)
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return {"objective": objective, "results": scrape_status}
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def crawl_url(url, objective):
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"""Crawl a website using Firecrawl."""
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print(f"Parameters: url={url}, objective={objective}")
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# If using a crawled url set, pass the ID in the function call below
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# scrape_status = app.check_crawl_status("c99c9598-5a21-46d3-bced-3444a8b1942d")
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# scrape_status['results'] = scrape_status['data']
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scrape_status = app.crawl_url(
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url,
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params={'limit': 10, 'scrapeOptions': {'formats': ['markdown']}}
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)
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return {"objective": objective, "results": scrape_status}
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def analyze_website_content(content, objective):
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"""Analyze the scraped website content using OpenAI."""
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print(f"Parameters: content={content[:50]}..., objective={objective}")
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analysis = generate_completion(
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"website data extractor",
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f"Analyze the following website content and extract a JSON object based on the objective. Do not write the ```json and ``` to denote a JSON when returning a response",
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"Objective: " + objective + "\nContent: " + content
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)
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return {"objective": objective, "results": analysis}
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def generate_completion(role, task, content):
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"""Generate a completion using OpenAI."""
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print(f"Parameters: role={role}, task={task[:50]}..., content={content[:50]}...")
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response = client.chat.completions.create(
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model="gpt-4o",
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messages=[
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{"role": "system", "content": f"You are a {role}. {task}"},
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{"role": "user", "content": content}
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]
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)
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return response.choices[0].message.content
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def read_websites_from_csv(file_path):
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"""Read websites from a CSV file."""
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websites = []
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with open(file_path, mode='r') as file:
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csv_reader = csv.DictReader(file)
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for row in csv_reader:
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websites.append(row['website'])
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return websites
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def write_results_to_json(results, file_path):
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"""Write results to a JSON file."""
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with open(file_path, mode='w') as file:
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json.dump(results, file, indent=4)
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def process_websites(file_path):
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"""Process websites from a CSV file and write results to a new JSON file."""
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results = []
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websites = read_websites_from_csv(file_path)
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for website in websites:
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search_results = search_google(website, "Search website")
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if search_results['results']:
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top_result = search_results['results'][0]
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url = top_result['link']
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crawl_results = crawl_url(url, "Crawl website")
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if crawl_results['results']:
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for each_result in crawl_results['results']['data'][:2]:
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analysis_results = analyze_website_content(each_result['markdown'], "Extract emails, names, and titles of the people found.")
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print(analysis_results['results'])
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results.append(json.loads(analysis_results['results']))
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write_results_to_json(results, 'enriched_data.json')
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if __name__ == "__main__":
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# Process websites from the CSV file
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process_websites('websites.csv')
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