Refactor orchestrator: add LLM fallbacks and Temporal workflow integration

src/agent.py

@@ -109,7 +109,9 @@ def run_agent_activity(payload: dict) -> str:
     target_jid = payload.get("targetJid", "default")
     sender = payload.get("sender", "Unknown")
 
-    llm = ChatGoogleGenerativeAI(model="gemini-1.5-flash")
+    primary_llm = ChatGoogleGenerativeAI(model="gemini-1.5-flash")
+    fallback_llm = ChatGoogleGenerativeAI(model="gemini-1.5-pro")
+    llm = primary_llm.with_fallbacks([fallback_llm])
     
     system_prompt = f"""You are a highly capable AI assistant operating as an orchestrator.
     

src/api.py

@@ -15,11 +15,16 @@ from src.agent import run_agent_activity
 
 async def trigger_workflow(payload: dict):
     try:
-        # Bypass Temporal for now since it's not deployed in the cluster
-        print(f"Directly invoking agent for payload: {payload}")
-        # run_agent_activity is a synchronous function, so run in thread or just call it directly
-        result = await asyncio.to_thread(run_agent_activity, payload)
-        print(f"Agent finished. Result: {result}")
+        print(f"Connecting to Temporal and dispatching workflow for payload: {payload}")
+        client = await Client.connect("temporal-frontend.ai-core.svc.cluster.local:7233")
+        
+        result = await client.execute_workflow(
+            CentralOrchestratorWorkflow.run,
+            payload,
+            id=f"orchestrator-workflow-{payload.get('sender', 'unknown')}-{asyncio.get_event_loop().time()}",
+            task_queue="agents-orchestrator",
+        )
+        print(f"Workflow finished. Result: {result}")
     except Exception as e:
         import traceback
         print(f"Failed to trigger workflow: {e}")

src/worker.py

@@ -5,10 +5,10 @@ from src.orchestrator import CentralOrchestratorWorkflow
 from src.agent import run_agent_activity
 
 async def main():
-    client = await Client.connect("localhost:7233")
+    client = await Client.connect("temporal-frontend.ai-core.svc.cluster.local:7233")
     worker = Worker(
         client,
-        task_queue="agent-task-queue",
+        task_queue="agents-orchestrator",
         workflows=[CentralOrchestratorWorkflow],
         activities=[run_agent_activity],
     )