Update chat_handler.py

chat_handler.py

@@ -17,6 +17,10 @@ from api_executor import call_api as execute_api
 from config_provider import ConfigProvider
 from validation_engine import validate
 from session import session_store, Session
+from llm_interface import LLMInterface, SparkLLM, GPT4oLLM
+
+# Global LLM instance
+llm_provider: Optional[LLMInterface] = None
 
 # ─────────────────────────  HELPERS ───────────────────────── #
 def _trim_response(raw: str) -> str:
@@ -52,6 +56,32 @@ cfg = ConfigProvider.get()
 SPARK_URL = str(cfg.global_config.spark_endpoint).rstrip("/")
 ALLOWED_INTENTS = {"flight-booking", "flight-info", "booking-cancel"}
 
+# ─────────────────────────  SPARK ───────────────────────── #
+def initialize_llm():
+    """Initialize LLM provider based on work_mode"""
+    global llm_provider
+    
+    work_mode = cfg.global_config.work_mode
+    
+    if cfg.global_config.is_gpt_mode():
+        # GPT mode
+        api_key = cfg.global_config.get_plain_token()
+        if not api_key:
+            raise ValueError("OpenAI API key not configured")
+        
+        model = cfg.global_config.get_gpt_model()
+        llm_provider = GPT4oLLM(api_key, model)
+        log(f"✅ Initialized {model} provider")
+    else:
+        # Spark mode
+        spark_token = _get_spark_token()
+        if not spark_token:
+            raise ValueError("Spark token not configured")
+            
+        spark_endpoint = str(cfg.global_config.spark_endpoint)
+        llm_provider = SparkLLM(spark_endpoint, spark_token)
+        log("✅ Initialized Spark provider")
+
 # ─────────────────────────  SPARK ───────────────────────── #
 def _get_spark_token() -> Optional[str]:
     """Get Spark token based on work_mode"""
@@ -68,65 +98,18 @@ def _get_spark_token() -> Optional[str]:
         return os.getenv("SPARK_TOKEN")
         
 async def spark_generate(s: Session, prompt: str, user_msg: str) -> str:
-    """Call Spark with proper error handling"""
+    """Call LLM provider with proper error handling"""
     try:
-        project = next((p for p in cfg.projects if p.name == s.project_name), None)
-        if not project:
-            raise ValueError(f"Project not found: {s.project_name}")
-        
-        version = next((v for v in project.versions if v.published), None)
-        if not version:
-            raise ValueError("No published version found")
-        
-        # Get Spark token
-        spark_token = _get_spark_token()
-        if not spark_token:
-            log("❌ SPARK_TOKEN not configured!")
-            raise ValueError("Spark authentication token not configured")
-        
-        # Prepare headers with authorization
-        headers = {
-            "Authorization": f"Bearer {spark_token}",
-            "Content-Type": "application/json"
-        }
-        
-        # Spark'a gönderilecek payload'ı hazırla
-        payload = {
-            "project_name": s.project_name,
-            "system_prompt": prompt,
-            "user_input": user_msg,
-            "context": s.chat_history[-10:]
-        }
+        if not llm_provider:
+            initialize_llm()
         
-        log(f"🚀 Calling Spark for session {s.session_id[:8]}...")
-        log(f"📋 Prompt preview (first 200 chars): {prompt[:200]}...")
+        # Use the abstract interface
+        raw = await llm_provider.generate(prompt, user_msg, s.chat_history)
+        log(f"🪄 LLM raw response: {raw[:120]!r}")
+        return raw
         
-        # Doğru endpoint'e istek at
-        spark_url = SPARK_URL + "/generate"
-        log(f"🌐 Spark URL: {spark_url}")
-        
-        async with httpx.AsyncClient(timeout=60) as client:
-            response = await client.post(spark_url, json=payload, headers=headers)
-            response.raise_for_status()
-            data = response.json()
-            
-            # Spark'tan gelen yanıtı parse et
-            raw = data.get("model_answer", "").strip()
-            if not raw:
-                # Fallback to other possible fields
-                raw = (data.get("assistant") or data.get("text", "")).strip()
-            
-            log(f"🪄 Spark raw: {raw[:120]!r}")
-            return raw
-            
-    except httpx.HTTPStatusError as e:
-        log(f"❌ Spark HTTP error: {e.response.status_code} - {e.response.text}")
-        raise
-    except httpx.TimeoutException:
-        log(f"⏱️ Spark timeout for session {s.session_id[:8]}")
-        raise
     except Exception as e:
-        log(f"❌ Spark error: {e}")
+        log(f"❌ LLM error: {e}")
         raise
 
 # ─────────────────────────  FASTAPI ───────────────────────── #