refactor(ai): Migrate to google-genai Client API

- Rewrites  and  in helpers.py to use the new  and  syntax.
- Removes the deprecated  calls which were causing AttributeError.
- Updates parameter handling to use .
- This change ensures full compatibility with the  library version 1.0+.

helpers.py

@@ -324,37 +324,47 @@ def _get_gemini_api_key():
 def call_gemini_flash(prompt, system_instruction=None, temperature=0.3, json_mode=False):
     """
     Spezifische Funktion für Gemini 1.5 Flash Aufrufe mit System-Instruction Support.
-    Wird vom GTM Architect Orchestrator verwendet.
+    Aktualisiert für die neue 'google-genai' Bibliothek (v1.0+).
     """
+    logger = logging.getLogger(__name__)
+    
     if not HAS_GEMINI:
         logger.error("Fehler: google-genai Bibliothek fehlt.")
         raise ImportError("google-genai not installed.")
 
     api_key = _get_gemini_api_key()
-    genai.configure(api_key=api_key)
     
-    model_name = "gemini-1.5-flash"
-    
-    generation_config = {
-        "temperature": temperature,
-        "top_p": 0.95,
-        "top_k": 40,
-        "max_output_tokens": 8192,
-    }
-    
-    if json_mode:
-        generation_config["response_mime_type"] = "application/json"
-
     try:
-        # Pass system_instruction if provided
-        model_instance = genai.GenerativeModel(
-            model_name=model_name,
-            generation_config=generation_config,
-            system_instruction=system_instruction
+        # NEU: Client-basierte Instanziierung für google-genai v1.0+
+        client = genai.Client(api_key=api_key)
+        
+        # Konfiguration für den Aufruf
+        config = {
+            "temperature": temperature,
+            "top_p": 0.95,
+            "top_k": 40,
+            "max_output_tokens": 8192,
+        }
+        
+        if json_mode:
+            config["response_mime_type"] = "application/json"
+
+        # Der Modell-Name muss oft explizit sein, 'gemini-1.5-flash' ist Standard
+        model_id = "gemini-1.5-flash"
+
+        response = client.models.generate_content(
+            model=model_id,
+            contents=prompt,
+            config=genai.types.GenerateContentConfig(
+                temperature=temperature,
+                top_p=0.95,
+                top_k=40,
+                max_output_tokens=8192,
+                response_mime_type="application/json" if json_mode else "text/plain",
+                system_instruction=system_instruction
+            )
         )
         
-        # generate_content is stateless and cleaner for this use case than start_chat
-        response = model_instance.generate_content(prompt)
         return response.text.strip()
 
     except Exception as e:
@@ -366,9 +376,7 @@ def call_gemini_flash(prompt, system_instruction=None, temperature=0.3, json_mod
 @retry_on_failure
 def call_openai_chat(prompt, temperature=0.3, model=None, response_format_json=False):
     """
-    Zentrale Funktion fuer KI API Aufrufe.
-    Wurde umgebaut auf Google Gemini (generativeai), behält aber den Namen 'call_openai_chat'
-    aus Kompatibilitätsgründen mit dem Rest des Codes bei.
+    Zentrale Funktion fuer KI API Aufrufe (jetzt Gemini via google-genai Client).
     """
     logger = logging.getLogger(__name__)
     
@@ -379,33 +387,23 @@ def call_openai_chat(prompt, temperature=0.3, model=None, response_format_json=F
         logger.error("Fehler: google-genai Bibliothek fehlt.")
         raise ImportError("google-genai not installed.")
 
-    # Konfiguriere Gemini
-    genai.configure(api_key=api_key)
-    
-    # Wähle Modell (Standard auf Flash für Speed/Kosten)
-    model_name = "gemini-1.5-flash" 
-    
-    generation_config = {
-        "temperature": temperature,
-        "top_p": 0.95,
-        "top_k": 40,
-        "max_output_tokens": 8192,
-    }
-    
-    if response_format_json:
-        generation_config["response_mime_type"] = "application/json"
-
     try:
-        model_instance = genai.GenerativeModel(
-            model_name=model_name,
-            generation_config=generation_config,
-        )
+        # NEU: Client Instanziierung
+        client = genai.Client(api_key=api_key)
         
-        chat_session = model_instance.start_chat(
-            history=[]
-        )
+        model_id = "gemini-1.5-flash" 
         
-        response = chat_session.send_message(prompt)
+        response = client.models.generate_content(
+            model=model_id,
+            contents=prompt,
+            config=genai.types.GenerateContentConfig(
+                temperature=temperature,
+                top_p=0.95,
+                top_k=40,
+                max_output_tokens=8192,
+                response_mime_type="application/json" if response_format_json else "text/plain"
+            )
+        )
         return response.text.strip()
 
     except Exception as e: