Update R1_web_crawler.py

examples/R1_web_crawler/R1_web_crawler.py

@@ -1,10 +1,10 @@
 import os
 import json
+import time
 import requests
 from dotenv import load_dotenv
 from openai import OpenAI
-from serpapi import GoogleSearch
+from serpapi.google_search import GoogleSearch
-from firecrawl import FirecrawlApp
 
 # ANSI color codes
 class Colors:
@@ -22,17 +22,18 @@ 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")
+serp_api_key = os.getenv("SERP_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")})
+    search = GoogleSearch({"q": query, "api_key": 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.
+    Returns a list of URLs.
     """
     try:
         # Prepare the data for R1
@@ -44,7 +45,7 @@ def select_urls_with_r1(company, objective, serp_results):
             messages=[
                 {
                     "role": "system",
-                    "content": "You select URLs from the SERP results relevant to the company and objective."
+                    "content": "You are a URL selector that always responds with valid JSON. You select URLs from the SERP results relevant to the company and objective. Your response must be a JSON object with a 'selected_urls' array property containing strings."
                 },
                 {
                     "role": "user",
@@ -53,90 +54,127 @@ def select_urls_with_r1(company, objective, serp_results):
                         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\"]}"
+                        "of URLs most likely to help meet the objective. Add a /* to the end of the URL if you think it should search all of the pages in the site. 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
+        try:
-        result = json.loads(response.choices[0].message.content)
+            # First try to parse as JSON
-        urls = result.get("selected_urls", [])
+            result = json.loads(response.choices[0].message.content)
-        return urls
+            if isinstance(result, dict) and "selected_urls" in result:
+                urls = result["selected_urls"]
+            else:
+                # If JSON doesn't have the expected structure, fall back to text parsing
+                response_text = response.choices[0].message.content
+                urls = [line.strip() for line in response_text.split('\n') 
+                       if line.strip().startswith(('http://', 'https://'))]
+        except json.JSONDecodeError:
+            # If JSON parsing fails, fall back to text parsing
+            response_text = response.choices[0].message.content
+            urls = [line.strip() for line in response_text.split('\n') 
+                   if line.strip().startswith(('http://', 'https://'))]
+
+        # Clean up URLs - remove wildcards and trailing slashes
+        cleaned_urls = [url.replace('/*', '').rstrip('/') for url in urls]
+        cleaned_urls = [url for url in cleaned_urls if url]
+
+        if not cleaned_urls:
+            print(f"{Colors.YELLOW}No valid URLs found.{Colors.RESET}")
+            return []
+
+        print(f"{Colors.CYAN}Selected URLs for extraction by R1:{Colors.RESET}")
+        for url in cleaned_urls:
+            print(f"- {url}")
+
+        return cleaned_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}")
+    print(f"{Colors.YELLOW}Extracting structured data from the provided URLs using Firecrawl...{Colors.RESET}")
-    app = FirecrawlApp(api_key=os.getenv("FIRECRAWL_API_KEY"))
+    
+    headers = {
+        'Content-Type': 'application/json',
+        'Authorization': f'Bearer {api_key}'
+    }
+    
+    payload = {
+        "urls": urls,
+        "prompt": prompt + " for " + company,
+        "enableWebSearch": True
+    }
+    
     try:
-        extract_prompt = prompt + " for " + company
+        response = requests.post(
-        response = app.extract(urls, {"prompt": extract_prompt, "enableWebSearch": True})
+            "https://api.firecrawl.dev/v1/extract",
-        print(response)
+            headers=headers,
-        return response
+            json=payload,
+            timeout=30
+        )
+        
+        data = response.json()
+        
+        if not data.get('success'):
+            print(f"{Colors.RED}API returned error: {data.get('error', 'No error message')}{Colors.RESET}")
+            return None
+        
+        # Assuming Firecrawl provides a way to retrieve data with 'id'
+        extraction_id = data.get('id')
+        if not extraction_id:
+            print(f"{Colors.RED}No extraction ID found in response.{Colors.RESET}")
+            return None
+
+        # Polling for the extraction result
+        return poll_firecrawl_result(extraction_id, api_key)
+
+    except requests.exceptions.RequestException as e:
+        print(f"{Colors.RED}Request failed: {e}{Colors.RESET}")
+        return None
+    except json.JSONDecodeError as e:
+        print(f"{Colors.RED}Failed to parse response: {e}{Colors.RESET}")
+        return None
     except Exception as e:
         print(f"{Colors.RED}Failed to extract data: {e}{Colors.RESET}")
         return None
 
-def deduplicate_with_r1(data, company, objective):
+def poll_firecrawl_result(extraction_id, api_key, interval=5, max_attempts=12):
-    """Use R1 to deduplicate and consolidate extracted information."""
+    """Poll Firecrawl API to get the extraction result."""
-    print(f"{Colors.YELLOW}Deduplicating and consolidating information using R1...{Colors.RESET}")
+    url = f"https://api.firecrawl.dev/v1/extract/{extraction_id}"
-    
+    headers = {
-    try:
+        'Authorization': f'Bearer {api_key}'
-        # Ensure data is valid JSON before sending
+    }
-        if not data:
+
-            return {}
+    for attempt in range(1, max_attempts + 1):
-            
-        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)
+            # print(f"{Colors.YELLOW}Polling for extraction result (Attempt {attempt}/{max_attempts})...{Colors.RESET}")
-            return consolidated_data
+            response = requests.get(url, headers=headers, timeout=30)
+            response.raise_for_status()
+            data = response.json()
+
+            if data.get('success') and data.get('data'):
+                print(f"{Colors.GREEN}Data successfully extracted:{Colors.RESET}")
+                print(json.dumps(data['data'], indent=2))
+                return data['data']
+            elif data.get('success') and not data.get('data'):
+                time.sleep(interval)
+            else:
+                print(f"{Colors.RED}API Error: {data.get('error', 'No error message provided')}{Colors.RESET}")
+                return None
+
+        except requests.exceptions.RequestException:
+            return None
         except json.JSONDecodeError:
-            # If JSON parsing fails, try to extract JSON from the response
+            return None
-            # Look for content between curly braces
+        except Exception:
-            start = response_text.find('{')
+            return None
-            end = response_text.rfind('}')
+
-            if start >= 0 and end >= 0:
+    print(f"{Colors.RED}Max polling attempts reached. Extraction did not complete in time.{Colors.RESET}")
-                json_str = response_text[start:end+1]
+    return None
-                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}")
@@ -154,20 +192,12 @@ def main():
         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'):
+    if data:
-        # Deduplicate and consolidate the extracted data
+        print(f"{Colors.GREEN}Extraction completed successfully.{Colors.RESET}")
-        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()
+        main()