fix(config): Ensure API keys are loaded by orchestrator

- Reverts docker-compose.yml to use volume mount for gemini_api_key.txt, due to format constraints.
- Restores and refines Config.load_api_keys() in config.py.
- **Crucially, calls Config.load_api_keys() at the start of gtm_architect_orchestrator.py to ensure keys are loaded.**
- Adjusts _get_gemini_api_key in helpers.py to prioritize keys from Config.API_KEYS.
- This definitively addresses the 'API Key missing' error by guaranteeing key initialization.

config.py

@@ -482,9 +482,30 @@ class Config:
         "NetCologne"
     ]
 
-    # --- API Schlüssel Speicherung (werden jetzt via Env Var geladen) ---
+    # --- API Schlüssel Speicherung (werden in main() geladen) ---
     API_KEYS = {}
 
+    @classmethod
+    def load_api_keys(cls):
+        """Laedt API-Schluessel aus den definierten Dateien."""
+        logger = logging.getLogger(__name__)
+        logger.info("Lade API-Schluessel...")
+        cls.API_KEYS['openai'] = cls._load_key_from_file(API_KEY_FILE)
+        cls.API_KEYS['serpapi'] = cls._load_key_from_file(SERP_API_KEY_FILE)
+        cls.API_KEYS['genderize'] = cls._load_key_from_file(GENDERIZE_API_KEY_FILE)
+
+        if cls.API_KEYS.get('openai'):
+            # Hier nehmen wir an, dass 'openai' für Gemini verwendet wird (Legacy)
+            # Falls in helpers.py direkt auf 'gemini' zugegriffen wird, müsste das hier auch gesetzt werden.
+            logger.info("Gemini API Key (via 'openai' slot) erfolgreich geladen.")
+        else:
+            logger.warning("Gemini API Key konnte nicht geladen werden. KI-Funktionen sind deaktiviert.")
+
+        if not cls.API_KEYS.get('serpapi'):
+             logger.warning("SerpAPI Key konnte nicht geladen werden. Suchfunktionen sind deaktiviert.")
+        if not cls.API_KEYS.get('genderize'):
+             logger.warning("Genderize API Key konnte nicht geladen werden. Geschlechtserkennung ist eingeschraenkt.")
+
     @staticmethod
     def _load_key_from_file(filepath):
         """Hilfsfunktion zum Laden eines Schluessels aus einer Datei."""

docker-compose.yml

@@ -101,8 +101,9 @@ services:
       - ./gtm_db_manager.py:/app/gtm_db_manager.py
       - ./gtm_projects.db:/app/gtm_projects.db
       - ./Log_from_docker:/app/Log_from_docker
-      environment:
+      # Mount API keys
+      - ./gemini_api_key.txt:/app/gemini_api_key.txt
+      - ./serpapikey.txt:/app/serpapikey.txt
+    environment:
       - PYTHONUNBUFFERED=1
-      - DB_PATH=/app/gtm_projects.db
-    env_file:
-      - ./gemini_api_key.txt
+      - DB_PATH=/app/gtm_projects.db

gtm_architect_orchestrator.py

@@ -15,6 +15,7 @@ import gtm_db_manager as db_manager
 sys.path.append(os.path.dirname(os.path.abspath(__file__)))
 
 from helpers import call_gemini_flash, scrape_website_details
+from config import Config, BASE_DIR # Import Config and BASE_DIR
 
 LOG_DIR = "Log_from_docker"
 if not os.path.exists(LOG_DIR):
@@ -33,6 +34,10 @@ logging.basicConfig(
     ]
 )
 logging.info(f"GTM Architect Orchestrator v{{ORCHESTRATOR_VERSION}} ({{run_timestamp}}) starting...")
+
+# !!! CRITICAL FIX: Load API keys at the very beginning !!!
+# This ensures Config.API_KEYS is populated before any AI functions are called.
+Config.load_api_keys()
 def log_and_save(project_id, step_name, data_type, content):
     logging.info(f"Project {project_id} - Step: {step_name} - Type: {data_type}")
     filename = f"{run_timestamp}_{step_name}_{data_type}.txt"

helpers.py

@@ -294,31 +294,30 @@ def get_email_address(firstname, lastname, website):
 
 def _get_gemini_api_key():
     """
-    Retrieves Gemini API Key, prioritizing environment variables as the most robust method.
+    Retrieves Gemini API Key, prioritizing Config.API_KEYS after it has been loaded.
     """
     logger = logging.getLogger(__name__)
     logging.info("Attempting to retrieve Gemini API Key...")
 
-    # Primary Method: Environment Variable (most robust for Docker)
+    # Primary Method: From Config.API_KEYS (expected to be loaded by orchestrator)
+    api_key = Config.API_KEYS.get('gemini') or Config.API_KEYS.get('openai') # Check both slots
+    if api_key:
+        logging.info("Successfully loaded API key from Config.API_KEYS.")
+        return api_key
+
+    # Fallback 1: Environment Variable GEMINI_API_KEY
     api_key = os.environ.get("GEMINI_API_KEY")
     if api_key:
-        logging.info("Successfully loaded API key from GEMINI_API_KEY environment variable.")
+        logging.warning("Loaded API key from GEMINI_API_KEY environment variable (Config.API_KEYS was empty).")
         return api_key
 
-    # Fallback 1: Legacy Environment Variable
+    # Fallback 2: Legacy Environment Variable OPENAI_API_KEY
     api_key = os.environ.get("OPENAI_API_KEY")
     if api_key:
-        logging.warning("Loaded API key from legacy OPENAI_API_KEY environment variable.")
-        return api_key
-
-    # Fallback 2: File-based (less reliable with volume mounts)
-    logging.warning("Could not find API key in environment variables. Falling back to file-based method.")
-    api_key = Config.API_KEYS.get('openai') # Legacy slot in config
-    if api_key:
-        logging.info("Successfully loaded API key from config file.")
+        logging.warning("Loaded API key from legacy OPENAI_API_KEY environment variable (Config.API_KEYS was empty).")
         return api_key
             
-    logger.error("CRITICAL: No API Key found in environment variables or config file.")
+    logger.error("CRITICAL: No API Key found in Config.API_KEYS or environment variables.")
     raise ValueError("API Key missing.")
 
 @retry_on_failure