[2f988f42] fix(company-explorer): Implement robust quantitative potential and atomic opener generation\n\n- Refactored ClassificationService for two-stage metric extraction (direct area and proxy).- Enhanced MetricParser for targeted value matching and robust number parsing.- Implemented persona-specific 'Atomic Opener' generation using segmented pains.- Fixed logging configuration and Pydantic response models.- Added dedicated debugging script and updated documentation (GEMINI.md, MIGRATION_PLAN.md).

company-explorer/backend/scripts/debug_single_company.py

@@ -0,0 +1,72 @@
+import os
+import sys
+import argparse
+import logging
+
+# Add the backend directory to the Python path
+sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
+
+from backend.database import get_db, Company
+from backend.services.classification import ClassificationService
+from backend.lib.logging_setup import setup_logging
+
+# --- CONFIGURATION ---
+# Setup logging to be very verbose for this script
+setup_logging()
+logger = logging.getLogger(__name__)
+logger.setLevel(logging.DEBUG)
+logger = logging.getLogger(__name__)
+
+def run_debug_analysis(company_id: int):
+    """
+    Runs the full classification and enrichment process for a single company
+    in the foreground and prints detailed results.
+    """
+    logger.info(f"--- Starting Interactive Debug for Company ID: {company_id} ---")
+    
+    db_session = next(get_db())
+    
+    try:
+        # 1. Fetch the company
+        company = db_session.query(Company).filter(Company.id == company_id).first()
+        if not company:
+            logger.error(f"Company with ID {company_id} not found.")
+            return
+
+        logger.info(f"Found Company: {company.name}")
+        
+        # --- PRE-ANALYSIS STATE ---
+        print("\n--- METRICS BEFORE ---")
+        print(f"Calculated: {company.calculated_metric_value} {company.calculated_metric_unit}")
+        print(f"Standardized: {company.standardized_metric_value} {company.standardized_metric_unit}")
+        print("----------------------\n")
+        
+        # 2. Instantiate the service
+        classifier = ClassificationService()
+        
+        # 3. RUN THE CORE LOGIC
+        # This will now print all the detailed logs we added
+        updated_company = classifier.classify_company_potential(company, db_session)
+        
+        # --- POST-ANALYSIS STATE ---
+        print("\n--- METRICS AFTER ---")
+        print(f"Industry (AI): {updated_company.industry_ai}")
+        print(f"Metric Source: {updated_company.metric_source}")
+        print(f"Proof Text: {updated_company.metric_proof_text}")
+        print(f"Calculated: {updated_company.calculated_metric_value} {updated_company.calculated_metric_unit}")
+        print(f"Standardized: {updated_company.standardized_metric_value} {updated_company.standardized_metric_unit}")
+        print(f"\nOpener 1 (Infra): {updated_company.ai_opener}")
+        print(f"Opener 2 (Ops): {updated_company.ai_opener_secondary}")
+        print("---------------------")
+        
+        logger.info(f"--- Interactive Debug Finished for Company ID: {company_id} ---")
+
+    finally:
+        db_session.close()
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Run a single company analysis for debugging.")
+    parser.add_argument("--id", type=int, default=1, help="The ID of the company to analyze.")
+    args = parser.parse_args()
+    
+    run_debug_analysis(args.id)

company-explorer/backend/scripts/trigger_analysis.py

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+import requests
+import os
+import time
+import argparse
+import sys
+import logging
+
+# Add the backend directory to the Python path for relative imports to work
+sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
+
+# --- Configuration ---
+def load_env_manual(path):
+    if not os.path.exists(path):
+        # print(f"⚠️  Warning: .env file not found at {path}") # Suppress for cleaner output in container
+        return
+    with open(path) as f:
+        for line in f:
+            line = line.strip()
+            if line and not line.startswith('#') and '=' in line:
+                key, val = line.split('=', 1)
+                os.environ.setdefault(key.strip(), val.strip())
+
+# Load .env (assuming it's in /app) - this needs to be run from /app or adjusted
+# For docker-compose exec from project root, /app is the container's WORKDIR
+load_env_manual('/app/.env')
+
+API_USER = os.getenv("API_USER")
+API_PASS = os.getenv("API_PASSWORD")
+# When run INSIDE the container, the service is reachable via localhost
+CE_URL = "http://localhost:8000"
+ANALYZE_ENDPOINT = f"{CE_URL}/api/enrich/analyze"
+
+def trigger_analysis(company_id: int):
+    print("="*60)
+    print(f"🚀 Triggering REAL analysis for Company ID: {company_id}")
+    print("="*60)
+
+    payload = {"company_id": company_id}
+
+    try:
+        # Added logging for API user/pass (debug only, remove in prod)
+        logger.debug(f"API Call to {ANALYZE_ENDPOINT} with user {API_USER}")
+        response = requests.post(ANALYZE_ENDPOINT, json=payload, auth=(API_USER, API_PASS), timeout=30) # Increased timeout
+        
+        if response.status_code == 200 and response.json().get("status") == "queued":
+            print("   ✅ SUCCESS: Analysis task has been queued on the server.")
+            print("   The result will be available in the database and UI shortly.")
+            return True
+        else:
+            print(f"   ❌ FAILURE: Server responded with status {response.status_code}")
+            print(f"   Response: {response.text}")
+            return False
+
+    except requests.exceptions.RequestException as e:
+        print(f"   ❌ FATAL: Could not connect to the server: {e}")
+        return False
+
+if __name__ == "__main__":
+    # Add a basic logger to the script itself for clearer output
+    logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+    logger = logging.getLogger(__name__)
+
+    parser = argparse.ArgumentParser(description="Trigger Company Explorer Analysis Task")
+    parser.add_argument("--company-id", type=int, required=True, help="ID of the company to analyze")
+    args = parser.parse_args()
+    
+    trigger_analysis(args.company_id)