Update spark_startup.py

spark_startup.py

@@ -1,29 +1,15 @@
 """
-Flare – Spark startup notifier
+Flare – LLM startup notifier
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-Projeler açılırken Spark'a /startup çağrısı yapar.
+Projeler açılırken LLM provider'a startup çağrısı yapar.
 """
 
 from __future__ import annotations
-import threading, requests
-from typing import Dict, Any, Optional
+import threading, requests, os
+from typing import Dict, Any
 from utils import log
 from config_provider import ConfigProvider, ProjectConfig, VersionConfig
-import os
-
-def _get_spark_token() -> Optional[str]:
-    """Get Spark token based on work_mode"""
-    if cfg.global_config.is_cloud_mode():
-        # Cloud mode - use HuggingFace Secrets
-        token = os.getenv("SPARK_TOKEN")
-        if not token:
-            log("❌ SPARK_TOKEN not found in HuggingFace Secrets!")
-        return token
-    else:
-        # On-premise mode - use .env file
-        from dotenv import load_dotenv
-        load_dotenv()
-        return os.getenv("SPARK_TOKEN")
+from llm_factory import LLMFactory
 
 def _select_live_version(p: ProjectConfig) -> VersionConfig | None:
     """Yayınlanmış en güncel versiyonu getir."""
@@ -31,44 +17,67 @@ def _select_live_version(p: ProjectConfig) -> VersionConfig | None:
     return max(published, key=lambda v: v.id) if published else None
 
 def notify_startup():
-    # Fresh config al
-    from config_provider import ConfigProvider
+    """Notify LLM provider about project startups"""
     cfg = ConfigProvider.get()
-
-    # GPT mode kontrolü
-    if cfg.global_config.is_gpt_mode():
-        log("🤖 GPT mode detected, skipping Spark startup notification")
+    
+    # Check if current provider needs startup notification
+    llm_config = cfg.global_config.llm_provider
+    if not llm_config:
+        log("⚠️ No LLM provider configured")
         return
-        
-    spark_base = str(cfg.global_config.spark_endpoint).rstrip("/")
-    spark_token = _get_spark_token()
     
-    if not spark_token:
-        log("⚠️ SPARK_TOKEN not configured. Skipping Spark startup notification.")
+    provider_def = cfg.global_config.get_provider_config("llm", llm_config.name)
+    if not provider_def:
+        log(f"⚠️ Unknown LLM provider: {llm_config.name}")
         return
-
-    enabled_projects = [p for p in cfg.projects if p.enabled]
     
-    if not enabled_projects:
-        log("ℹ️ No enabled projects found for startup notification.")
+    # Currently only Spark variants need startup
+    if llm_config.name not in ("spark", "spark_cloud", "spark_onpremise"):
+        log(f"ℹ️ {llm_config.name} doesn't require startup notification")
         return
+    
+    # Check if provider requires repo info
+    if not provider_def.requires_repo_info:
+        log(f"ℹ️ {llm_config.name} doesn't require repo info for startup")
+        return
+    
+    # Get endpoint and API key
+    endpoint = llm_config.endpoint
+    if not endpoint:
+        log("⚠️ No LLM endpoint configured for startup")
+        return
+    
+    api_key = cfg.global_config.get_plain_api_key("llm")
+    if not api_key:
+        # Try environment
+        env_var = "SPARK_TOKEN"
+        if os.environ.get("SPACE_ID"):
+            api_key = os.environ.get(env_var)
+        else:
+            from dotenv import load_dotenv
+            load_dotenv()
+            api_key = os.getenv(env_var)
+        
+        if not api_key:
+            log("⚠️ No API key available for startup")
+            return
+    
+    spark_base = str(endpoint).rstrip("/")
 
-    for p in enabled_projects:
+    for p in cfg.projects:
         if not p.enabled:
             continue
-            
         v = _select_live_version(p)
         if not v:
-            log(f"⚠️ No published version found for project '{p.name}', skipping startup.")
             continue
-
-        plain = cfg.global_config.get_plain_token()
-        log(f"🔑 Cloud-token starts with {plain[:6]}… (len={len(plain)})")
         
+        # Check if version has LLM config (required for Spark)
+        if not v.llm:
+            log(f"⚠️ No LLM config in version {v.id} for project '{p.name}'")
+            continue
+
         body: Dict[str, Any] = {
-            # ----- zorunlu alanlar -----
-            "work_mode": cfg.global_config.work_mode,
-            "cloud_token": plain,
+            # Required fields for Spark startup
             "project_name": p.name,
             "project_version": v.id,
             "repo_id": v.llm.repo_id,
@@ -78,26 +87,20 @@ def notify_startup():
         }
 
         headers = {
-            "Authorization": f"Bearer {spark_token}",
+            "Authorization": f"Bearer {api_key}",
             "Content-Type": "application/json"
         }
-        
+
         try:
-            log(f"🚀 Notifying Spark /startup for project '{p.name}' …")
+            log(f"🚀 Notifying {llm_config.name} /startup for project '{p.name}' …")
             r = requests.post(f"{spark_base}/startup", json=body, headers=headers, timeout=10)
             if r.status_code >= 400:
-                log(f"❌ Spark responded {r.status_code}: {r.text}")
+                log(f"❌ LLM provider responded {r.status_code}: {r.text}")
                 r.raise_for_status()
-            log(f"✅ Spark acknowledged startup ({r.status_code})")
+            log(f"✅ LLM provider acknowledged startup ({r.status_code})")
         except Exception as e:
-            log(f"⚠️ Spark startup failed: {e}")
+            log(f"⚠️ LLM startup failed: {e}")
 
 def run_in_thread():
-    cfg = ConfigProvider.get()
-    
-    # GPT mode'da thread başlatmaya gerek yok
-    if cfg.global_config.is_gpt_mode():
-        log("🤖 GPT mode - Spark startup thread not started")
-        return
-
-    threading.Thread(target=notify_startup, daemon=True).start()
+    """Run startup notification in background thread"""
+    threading.Thread(target=notify_startup, daemon=True).start()