Refactor code structure for improved readability and maintainability

services/graphiti_client.py

@@ -2,6 +2,19 @@
 
 Wird von ingest_episode_event_step und query_graph_step genutzt.
 Lazy-initialisiert beim ersten Aufruf.
+
+Umgebungsvariablen:
+    GRAPHITI_LLM_PROVIDER    – 'gemini' (default) oder 'xai'
+    GOOGLE_API_KEY           – Google AI Studio Key (für gemini)
+    GRAPHITI_LLM_MODEL       – LLM-Hauptmodell (default: gemini-3-flash-preview)
+    GRAPHITI_LLM_SMALL_MODEL – LLM-Hilfsmodell  (default: gemini-2.5-flash-lite)
+    XAI_API_KEY              – xAI-Key (für xai-Provider)
+    XAI_BASE_URL             – optional, Standard: https://api.x.ai/v1
+    XAI_MODEL                – optional, Standard: grok-4-1-fast-reasoning
+    XAI_SMALL_MODEL          – optional, Standard: grok-3-mini-fast
+    OPENAI_API_KEY           – OpenAI-Key für Embeddings
+    GRAPHITI_EMBED_BASE_URL  – optional, Standard: https://api.openai.com/v1
+    GRAPHITI_EMBED_MODEL     – optional, Standard: text-embedding-3-small
 """
 import asyncio
 import os
@@ -9,7 +22,6 @@ from typing import Any, Optional
 
 from graphiti_core import Graphiti
 from graphiti_core.llm_client import LLMConfig
-from graphiti_core.llm_client.openai_generic_client import OpenAIGenericClient
 from graphiti_core.embedder import OpenAIEmbedder, OpenAIEmbedderConfig
 
 from services.graphiti_tracer import build_langfuse_tracer
@@ -24,22 +36,7 @@ _graphiti_init_lock = asyncio.Lock()
 
 
 async def get_graphiti(ctx: Optional[Any] = None) -> Graphiti:
-    """Gibt den gecachten Graphiti-Client zurück (Singleton).
-
-    Args:
-        ctx: Optionaler Motia-Context für Logging während der Initialisierung.
-
-    Benötigte Umgebungsvariablen:
-        NEO4J_URI            – bolt://host:7687
-        NEO4J_USER           – neo4j
-        NEO4J_PASSWORD       – Pflicht
-        XAI_API_KEY          – xAI-Key für LLM (grok)
-        XAI_BASE_URL         – optional, Standard: https://api.x.ai/v1
-        XAI_MODEL            – optional, Standard: grok-4-1-fast-reasoning
-        OPENAI_API_KEY       – OpenAI-Key für Embeddings
-        GRAPHITI_EMBED_BASE_URL  – optional, Standard: https://api.openai.com/v1
-        GRAPHITI_EMBED_MODEL     – optional, Standard: text-embedding-3-small
-    """
+    """Gibt den gecachten Graphiti-Client zurück (Singleton)."""
     global _graphiti_client
     if _graphiti_client is None:
         async with _graphiti_init_lock:
@@ -61,26 +58,40 @@ def _log(ctx: Optional[Any], message: str, level: str = "info") -> None:
         print(f"[GraphitiClient] {message}")
 
 
+def _build_llm_client():
+    provider = os.environ.get("GRAPHITI_LLM_PROVIDER", "gemini").lower()
+
+    if provider == "gemini":
+        from graphiti_core.llm_client.gemini_client import GeminiClient
+        return GeminiClient(
+            config=LLMConfig(
+                api_key=os.environ["GOOGLE_API_KEY"],
+                model=os.environ.get("GRAPHITI_LLM_MODEL", "gemini-3-flash-preview"),
+                small_model=os.environ.get("GRAPHITI_LLM_SMALL_MODEL", "gemini-2.5-flash-lite"),
+            )
+        )
+    else:  # xai
+        from graphiti_core.llm_client.openai_generic_client import OpenAIGenericClient
+        return OpenAIGenericClient(
+            config=LLMConfig(
+                api_key=os.environ["XAI_API_KEY"],
+                base_url=os.environ.get("XAI_BASE_URL", "https://api.x.ai/v1"),
+                model=os.environ.get("XAI_MODEL", "grok-4-1-fast-reasoning"),
+                small_model=os.environ.get("XAI_SMALL_MODEL", "grok-3-mini-fast"),
+            )
+        )
+
+
 async def _build_graphiti() -> Graphiti:
     neo4j_uri = os.environ["NEO4J_URI"]
     neo4j_user = os.environ.get("NEO4J_USER", "neo4j")
     neo4j_password = os.environ["NEO4J_PASSWORD"]
 
-    xai_base_url = os.environ.get("XAI_BASE_URL", "https://api.x.ai/v1")
-    xai_api_key = os.environ["XAI_API_KEY"]
-    xai_model = os.environ.get("XAI_MODEL", "grok-4-1-fast-reasoning")
-
-    embed_api_key = os.environ.get("OPENAI_API_KEY") or os.environ.get("GRAPHITI_EMBED_API_KEY", xai_api_key)
+    embed_api_key = os.environ.get("OPENAI_API_KEY") or os.environ["GRAPHITI_EMBED_API_KEY"]
     embed_base_url = os.environ.get("GRAPHITI_EMBED_BASE_URL", "https://api.openai.com/v1")
     embed_model = os.environ.get("GRAPHITI_EMBED_MODEL", "text-embedding-3-small")
 
-    llm_client = OpenAIGenericClient(
-        config=LLMConfig(
-            api_key=xai_api_key,
-            base_url=xai_base_url,
-            model=xai_model,
-        )
-    )
+    llm_client = _build_llm_client()
 
     embedder = OpenAIEmbedder(
         config=OpenAIEmbedderConfig(