import os import csv import json from dotenv import load_dotenv from firecrawl import FirecrawlApp from openai import OpenAI from serpapi import GoogleSearch load_dotenv() # Initialize FirecrawlApp and OpenAI app = FirecrawlApp(api_key=os.getenv("FIRECRAWL_API_KEY")) client = OpenAI(api_key=os.getenv("OPENAI_API_KEY")) def search_google(query, objective): """Search Google using SerpAPI.""" print(f"Parameters: query={query}, objective={objective}") search = GoogleSearch({"q": query, "api_key": os.getenv("SERP_API_KEY")}) results = search.get_dict().get("organic_results", []) return {"objective": objective, "results": results} def scrape_url(url, objective): """Scrape a website using Firecrawl.""" print(f"Parameters: url={url}, objective={objective}") scrape_status = app.scrape_url( url, params={'formats': ['markdown']} ) return {"objective": objective, "results": scrape_status} def crawl_url(url, objective): """Crawl a website using Firecrawl.""" print(f"Parameters: url={url}, objective={objective}") # If using a crawled url set, pass the ID in the function call below # scrape_status = app.check_crawl_status("c99c9598-5a21-46d3-bced-3444a8b1942d") # scrape_status['results'] = scrape_status['data'] scrape_status = app.crawl_url( url, params={'limit': 10, 'scrapeOptions': {'formats': ['markdown']}} ) return {"objective": objective, "results": scrape_status} def analyze_website_content(content, objective): """Analyze the scraped website content using OpenAI.""" print(f"Parameters: content={content[:50]}..., objective={objective}") analysis = generate_completion( "website data extractor", 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", "Objective: " + objective + "\nContent: " + content ) return {"objective": objective, "results": analysis} def generate_completion(role, task, content): """Generate a completion using OpenAI.""" print(f"Parameters: role={role}, task={task[:50]}..., content={content[:50]}...") response = client.chat.completions.create( model="gpt-4o", messages=[ {"role": "system", "content": f"You are a {role}. {task}"}, {"role": "user", "content": content} ] ) return response.choices[0].message.content def read_websites_from_csv(file_path): """Read websites from a CSV file.""" websites = [] with open(file_path, mode='r') as file: csv_reader = csv.DictReader(file) for row in csv_reader: websites.append(row['website']) return websites def write_results_to_json(results, file_path): """Write results to a JSON file.""" with open(file_path, mode='w') as file: json.dump(results, file, indent=4) def process_websites(file_path): """Process websites from a CSV file and write results to a new JSON file.""" results = [] websites = read_websites_from_csv(file_path) for website in websites: search_results = search_google(website, "Search website") if search_results['results']: top_result = search_results['results'][0] url = top_result['link'] crawl_results = crawl_url(url, "Crawl website") if crawl_results['results']: for each_result in crawl_results['results']['data'][:2]: analysis_results = analyze_website_content(each_result['markdown'], "Extract emails, names, and titles of the people found.") print(analysis_results['results']) results.append(json.loads(analysis_results['results'])) write_results_to_json(results, 'enriched_data.json') if __name__ == "__main__": # Process websites from the CSV file process_websites('websites.csv')