R1 Crawler

examples/R1_web_crawler/R1_web_crawler.py

@@ -0,0 +1,173 @@
+import os
+import json
+import requests
+from dotenv import load_dotenv
+from openai import OpenAI
+from serpapi import GoogleSearch
+from firecrawl import FirecrawlApp
+
+# ANSI color codes
+class Colors:
+    CYAN = '\033[96m'
+    YELLOW = '\033[93m'
+    GREEN = '\033[92m'
+    RED = '\033[91m'
+    MAGENTA = '\033[95m'
+    BLUE = '\033[94m'
+    RESET = '\033[0m'
+
+# Load environment variables
+load_dotenv()
+
+# Initialize clients
+client = OpenAI(api_key=os.getenv("DEEPSEEK_API_KEY"), base_url="https://api.deepseek.com")
+firecrawl_api_key = os.getenv("FIRECRAWL_API_KEY")
+
+def search_google(query):
+    """Search Google using SerpAPI and return top results."""
+    print(f"{Colors.YELLOW}Searching Google for '{query}'...{Colors.RESET}")
+    search = GoogleSearch({"q": query, "api_key": os.getenv("SERP_API_KEY")})
+    return search.get_dict().get("organic_results", [])
+
+def select_urls_with_r1(company, objective, serp_results):
+    """
+    Use R1 to select the most relevant URLs from SERP results for the given company and objective.
+    Returns a JSON object with a "selected_urls" property that is an array of strings.
+    """
+    try:
+        # Prepare the data for R1
+        serp_data = [{"title": r.get("title"), "link": r.get("link"), "snippet": r.get("snippet")} 
+                     for r in serp_results if r.get("link")]
+
+        response = client.chat.completions.create(
+            model="deepseek-reasoner",
+            messages=[
+                {
+                    "role": "system",
+                    "content": "You select URLs from the SERP results relevant to the company and objective."
+                },
+                {
+                    "role": "user",
+                    "content": (
+                        f"Company: {company}\n"
+                        f"Objective: {objective}\n"
+                        f"SERP Results: {json.dumps(serp_data)}\n\n"
+                        "Return a JSON object with a property 'selected_urls' that contains an array "
+                        "of URLs most likely to help meet the objective. If you think the data might not be on the homepage, add a /* to the end of the URL. Do not return any social media links. For example: {\"selected_urls\": [\"https://example.com\", \"https://example2.com\"]}"
+                    )
+                }
+            ],
+        )
+
+        # The response is guaranteed to follow the specified JSON schema
+        result = json.loads(response.choices[0].message.content)
+        urls = result.get("selected_urls", [])
+        return urls
+
+    except Exception as e:
+        print(f"{Colors.RED}Error selecting URLs with R1: {e}{Colors.RESET}")
+        return []
+
+
+
+def extract_company_info(urls, prompt, company, api_key):
+    """Use requests to call Firecrawl's extract endpoint with selected URLs."""
+    print(f"{Colors.YELLOW}Extracting structured data from the provided URLs using Firecrawl's /extract endpoint...{Colors.RESET}")
+    app = FirecrawlApp(api_key=os.getenv("FIRECRAWL_API_KEY"))
+    try:
+        extract_prompt = prompt + " for " + company
+        response = app.extract(urls, {"prompt": extract_prompt, "enableWebSearch": True})
+        print(response)
+        return response
+    except Exception as e:
+        print(f"{Colors.RED}Failed to extract data: {e}{Colors.RESET}")
+        return None
+
+def deduplicate_with_r1(data, company, objective):
+    """Use R1 to deduplicate and consolidate extracted information."""
+    print(f"{Colors.YELLOW}Deduplicating and consolidating information using R1...{Colors.RESET}")
+    
+    try:
+        # Ensure data is valid JSON before sending
+        if not data:
+            return {}
+            
+        response = client.chat.completions.create(
+            model="deepseek-reasoner",
+            messages=[
+                {
+                    "role": "system",
+                    "content": "You are an expert at consolidating information and removing duplicates. Analyze the extracted data and provide a clean, consolidated response."
+                },
+                {
+                    "role": "user",
+                    "content": (
+                        f"Company: {company}\n"
+                        f"Objective: {objective}\n"
+                        f"Extracted Data: {json.dumps(data, indent=2)}\n\n"
+                        "Please analyze this data and:\n"
+                        "1. Remove any duplicate information\n"
+                        "2. Consolidate similar points\n"
+                        "3. Format the response as a clean JSON object\n"
+                        "4. Ensure all information is relevant to the objective\n"
+                        "Return only the JSON response."
+                    )
+                }
+            ],
+        )
+        
+        # Handle empty or invalid responses
+        response_text = response.choices[0].message.content.strip()
+        if not response_text:
+            return {}
+            
+        try:
+            consolidated_data = json.loads(response_text)
+            return consolidated_data
+        except json.JSONDecodeError:
+            # If JSON parsing fails, try to extract JSON from the response
+            # Look for content between curly braces
+            start = response_text.find('{')
+            end = response_text.rfind('}')
+            if start >= 0 and end >= 0:
+                json_str = response_text[start:end+1]
+                return json.loads(json_str)
+            return {}
+        
+    except Exception as e:
+        print(f"{Colors.RED}Error deduplicating data with R1: {e}{Colors.RESET}")
+        return data
+
+def main():
+    company = input(f"{Colors.BLUE}Enter the company name: {Colors.RESET}")
+    objective = input(f"{Colors.BLUE}Enter what information you want about the company: {Colors.RESET}")
+    
+    serp_results = search_google(f"{company}")
+    if not serp_results:
+        print(f"{Colors.RED}No search results found.{Colors.RESET}")
+        return
+    
+    # Ask R1 to select URLs
+    selected_urls = select_urls_with_r1(company, objective, serp_results)
+    
+    if not selected_urls:
+        print(f"{Colors.RED}R1 did not return any URLs.{Colors.RESET}")
+        return
+    
+    print(f"{Colors.CYAN}Selected URLs for extraction by R1:{Colors.RESET}")
+    for url in selected_urls:
+        print(f"- {url}")
+
+    data = extract_company_info(selected_urls, objective, company, firecrawl_api_key)
+    
+    if data and data.get('success') and data.get('data'):
+        # Deduplicate and consolidate the extracted data
+        consolidated_data = deduplicate_with_r1(data['data'], company, objective)
+        
+        print(f"\n{Colors.GREEN}Consolidated and deduplicated data:{Colors.RESET}")
+        print(json.dumps(consolidated_data, indent=2))
+    else:
+        print(f"{Colors.RED}Failed to extract the requested information. Try refining your prompt or choosing a different company.{Colors.RESET}")
+
+if __name__ == "__main__":
+    main()