firecrawl/examples/sales_web_crawler/app.py
2024-10-19 02:27:39 +05:30

107 lines
4.2 KiB
Python

import csv
import json
import os
import uuid
from dotenv import load_dotenv
from firecrawl import FirecrawlApp
from openai import OpenAI
from serpapi import GoogleSearch
from tqdm import tqdm
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': 5, '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']
unique_filename = f'output_{uuid.uuid4()}.json'
crawl_results = crawl_url(url, "Crawl website")
if crawl_results['results']:
for each_result in tqdm(crawl_results['results']['data'], desc="Analyzing crawl results"):
analysis_results = analyze_website_content(each_result['markdown'], "Extract emails, names, and titles of the people and companies found.")
try:
result = json.loads(analysis_results['results'])
if result:
results.append(result)
write_results_to_json(results, unique_filename)
except:
continue
if __name__ == "__main__":
# Process websites from the CSV file
process_websites('websites.csv')