fix space in the folder name
This commit is contained in:
Harsha
GitHub
parent
a0189acbec
commit
d76cb6a6d2
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@ -1,152 +1,152 @@
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import os
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from firecrawl import FirecrawlApp
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import json
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from dotenv import load_dotenv
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from openai import OpenAI
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# ANSI color codes
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class Colors:
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CYAN = '\033[96m'
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YELLOW = '\033[93m'
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GREEN = '\033[92m'
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RED = '\033[91m'
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MAGENTA = '\033[95m'
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BLUE = '\033[94m'
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RESET = '\033[0m'
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# Load environment variables
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load_dotenv()
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# Retrieve API keys from environment variables
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firecrawl_api_key = os.getenv("FIRECRAWL_API_KEY")
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openai_api_key = os.getenv("OPENAI_API_KEY")
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# Initialize the FirecrawlApp and OpenAI client
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app = FirecrawlApp(api_key=firecrawl_api_key)
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client = OpenAI(api_key=openai_api_key)
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# Find the page that most likely contains the objective
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def find_relevant_page_via_map(objective, url, app, client):
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try:
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print(f"{Colors.CYAN}Understood. The objective is: {objective}{Colors.RESET}")
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print(f"{Colors.CYAN}Initiating search on the website: {url}{Colors.RESET}")
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map_prompt = f"""
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The map function generates a list of URLs from a website and it accepts a search parameter. Based on the objective of: {objective}, come up with a 1-2 word search parameter that will help us find the information we need. Only respond with 1-2 words nothing else.
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"""
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print(f"{Colors.YELLOW}Analyzing objective to determine optimal search parameter...{Colors.RESET}")
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completion = client.chat.completions.create(
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model="o1-preview",
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messages=[
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{
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"role": "user",
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"content": [
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{
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"type": "text",
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"text": map_prompt
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}
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]
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}
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]
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)
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map_search_parameter = completion.choices[0].message.content
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print(f"{Colors.GREEN}Optimal search parameter identified: {map_search_parameter}{Colors.RESET}")
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print(f"{Colors.YELLOW}Mapping website using the identified search parameter...{Colors.RESET}")
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map_website = app.map_url(url, params={"search": map_search_parameter})
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print(f"{Colors.GREEN}Website mapping completed successfully.{Colors.RESET}")
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print(f"{Colors.GREEN}Located {len(map_website)} relevant links.{Colors.RESET}")
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return map_website
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except Exception as e:
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print(f"{Colors.RED}Error encountered during relevant page identification: {str(e)}{Colors.RESET}")
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return None
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# Scrape the top 3 pages and see if the objective is met, if so return in json format else return None
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def find_objective_in_top_pages(map_website, objective, app, client):
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try:
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# Get top 3 links from the map result
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top_links = map_website[:3] if isinstance(map_website, list) else []
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print(f"{Colors.CYAN}Proceeding to analyze top {len(top_links)} links: {top_links}{Colors.RESET}")
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for link in top_links:
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print(f"{Colors.YELLOW}Initiating scrape of page: {link}{Colors.RESET}")
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# Scrape the page
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scrape_result = app.scrape_url(link, params={'formats': ['markdown']})
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print(f"{Colors.GREEN}Page scraping completed successfully.{Colors.RESET}")
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# Check if objective is met
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check_prompt = f"""
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Given the following scraped content and objective, determine if the objective is met.
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If it is, extract the relevant information in a simple and concise JSON format. Use only the necessary fields and avoid nested structures if possible.
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If the objective is not met with confidence, respond with 'Objective not met'.
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Objective: {objective}
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Scraped content: {scrape_result['markdown']}
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Remember:
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1. Only return JSON if you are confident the objective is fully met.
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2. Keep the JSON structure as simple and flat as possible.
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3. Do not include any explanations or markdown formatting in your response.
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"""
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completion = client.chat.completions.create(
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model="o1-preview",
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messages=[
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{
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"role": "user",
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"content": [
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{
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"type": "text",
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"text": check_prompt
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}
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]
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}
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]
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)
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result = completion.choices[0].message.content
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if result != "Objective not met":
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print(f"{Colors.GREEN}Objective potentially fulfilled. Relevant information identified.{Colors.RESET}")
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try:
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return json.loads(result)
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except json.JSONDecodeError:
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print(f"{Colors.RED}Error in parsing response. Proceeding to next page...{Colors.RESET}")
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else:
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print(f"{Colors.YELLOW}Objective not met on this page. Proceeding to next link...{Colors.RESET}")
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print(f"{Colors.RED}All available pages analyzed. Objective not fulfilled in examined content.{Colors.RESET}")
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return None
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except Exception as e:
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print(f"{Colors.RED}Error encountered during page analysis: {str(e)}{Colors.RESET}")
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return None
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# Main function to execute the process
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def main():
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# Get user input
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url = input(f"{Colors.BLUE}Enter the website to crawl: {Colors.RESET}")
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objective = input(f"{Colors.BLUE}Enter your objective: {Colors.RESET}")
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print(f"{Colors.YELLOW}Initiating web crawling process...{Colors.RESET}")
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# Find the relevant page
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map_website = find_relevant_page_via_map(objective, url, app, client)
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if map_website:
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print(f"{Colors.GREEN}Relevant pages identified. Proceeding with detailed analysis...{Colors.RESET}")
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# Find objective in top pages
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result = find_objective_in_top_pages(map_website, objective, app, client)
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if result:
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print(f"{Colors.GREEN}Objective successfully fulfilled. Extracted information:{Colors.RESET}")
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print(f"{Colors.MAGENTA}{json.dumps(result, indent=2)}{Colors.RESET}")
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else:
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print(f"{Colors.RED}Unable to fulfill the objective with the available content.{Colors.RESET}")
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else:
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print(f"{Colors.RED}No relevant pages identified. Consider refining the search parameters or trying a different website.{Colors.RESET}")
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if __name__ == "__main__":
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main()
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import os
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from firecrawl import FirecrawlApp
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import json
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from dotenv import load_dotenv
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from openai import OpenAI
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# ANSI color codes
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class Colors:
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CYAN = '\033[96m'
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YELLOW = '\033[93m'
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GREEN = '\033[92m'
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RED = '\033[91m'
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MAGENTA = '\033[95m'
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BLUE = '\033[94m'
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RESET = '\033[0m'
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# Load environment variables
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load_dotenv()
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# Retrieve API keys from environment variables
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firecrawl_api_key = os.getenv("FIRECRAWL_API_KEY")
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openai_api_key = os.getenv("OPENAI_API_KEY")
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# Initialize the FirecrawlApp and OpenAI client
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app = FirecrawlApp(api_key=firecrawl_api_key)
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client = OpenAI(api_key=openai_api_key)
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# Find the page that most likely contains the objective
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def find_relevant_page_via_map(objective, url, app, client):
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try:
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print(f"{Colors.CYAN}Understood. The objective is: {objective}{Colors.RESET}")
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print(f"{Colors.CYAN}Initiating search on the website: {url}{Colors.RESET}")
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map_prompt = f"""
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The map function generates a list of URLs from a website and it accepts a search parameter. Based on the objective of: {objective}, come up with a 1-2 word search parameter that will help us find the information we need. Only respond with 1-2 words nothing else.
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"""
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print(f"{Colors.YELLOW}Analyzing objective to determine optimal search parameter...{Colors.RESET}")
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completion = client.chat.completions.create(
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model="o1-preview",
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messages=[
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{
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"role": "user",
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"content": [
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{
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"type": "text",
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"text": map_prompt
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}
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]
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}
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]
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)
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map_search_parameter = completion.choices[0].message.content
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print(f"{Colors.GREEN}Optimal search parameter identified: {map_search_parameter}{Colors.RESET}")
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print(f"{Colors.YELLOW}Mapping website using the identified search parameter...{Colors.RESET}")
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map_website = app.map_url(url, params={"search": map_search_parameter})
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print(f"{Colors.GREEN}Website mapping completed successfully.{Colors.RESET}")
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print(f"{Colors.GREEN}Located {len(map_website)} relevant links.{Colors.RESET}")
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return map_website
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except Exception as e:
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print(f"{Colors.RED}Error encountered during relevant page identification: {str(e)}{Colors.RESET}")
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return None
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# Scrape the top 3 pages and see if the objective is met, if so return in json format else return None
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def find_objective_in_top_pages(map_website, objective, app, client):
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try:
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# Get top 3 links from the map result
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top_links = map_website[:3] if isinstance(map_website, list) else []
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print(f"{Colors.CYAN}Proceeding to analyze top {len(top_links)} links: {top_links}{Colors.RESET}")
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for link in top_links:
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print(f"{Colors.YELLOW}Initiating scrape of page: {link}{Colors.RESET}")
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# Scrape the page
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scrape_result = app.scrape_url(link, params={'formats': ['markdown']})
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print(f"{Colors.GREEN}Page scraping completed successfully.{Colors.RESET}")
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# Check if objective is met
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check_prompt = f"""
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Given the following scraped content and objective, determine if the objective is met.
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If it is, extract the relevant information in a simple and concise JSON format. Use only the necessary fields and avoid nested structures if possible.
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If the objective is not met with confidence, respond with 'Objective not met'.
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Objective: {objective}
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Scraped content: {scrape_result['markdown']}
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Remember:
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1. Only return JSON if you are confident the objective is fully met.
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2. Keep the JSON structure as simple and flat as possible.
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3. Do not include any explanations or markdown formatting in your response.
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"""
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completion = client.chat.completions.create(
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model="o1-preview",
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messages=[
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{
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"role": "user",
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"content": [
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{
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"type": "text",
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"text": check_prompt
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}
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]
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}
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]
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)
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result = completion.choices[0].message.content
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if result != "Objective not met":
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print(f"{Colors.GREEN}Objective potentially fulfilled. Relevant information identified.{Colors.RESET}")
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try:
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return json.loads(result)
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except json.JSONDecodeError:
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print(f"{Colors.RED}Error in parsing response. Proceeding to next page...{Colors.RESET}")
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else:
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print(f"{Colors.YELLOW}Objective not met on this page. Proceeding to next link...{Colors.RESET}")
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print(f"{Colors.RED}All available pages analyzed. Objective not fulfilled in examined content.{Colors.RESET}")
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return None
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except Exception as e:
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print(f"{Colors.RED}Error encountered during page analysis: {str(e)}{Colors.RESET}")
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return None
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# Main function to execute the process
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def main():
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# Get user input
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url = input(f"{Colors.BLUE}Enter the website to crawl: {Colors.RESET}")
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objective = input(f"{Colors.BLUE}Enter your objective: {Colors.RESET}")
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print(f"{Colors.YELLOW}Initiating web crawling process...{Colors.RESET}")
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# Find the relevant page
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map_website = find_relevant_page_via_map(objective, url, app, client)
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if map_website:
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print(f"{Colors.GREEN}Relevant pages identified. Proceeding with detailed analysis...{Colors.RESET}")
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# Find objective in top pages
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result = find_objective_in_top_pages(map_website, objective, app, client)
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if result:
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print(f"{Colors.GREEN}Objective successfully fulfilled. Extracted information:{Colors.RESET}")
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print(f"{Colors.MAGENTA}{json.dumps(result, indent=2)}{Colors.RESET}")
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else:
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print(f"{Colors.RED}Unable to fulfill the objective with the available content.{Colors.RESET}")
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else:
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print(f"{Colors.RED}No relevant pages identified. Consider refining the search parameters or trying a different website.{Colors.RESET}")
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if __name__ == "__main__":
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main()
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@ -1,3 +1,3 @@
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firecrawl-py
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python-dotenv
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firecrawl-py
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python-dotenv
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openai
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