activity init function to load llm client only once

activities/tool_activities.py

@@ -2,7 +2,7 @@ from temporalio import activity
 from ollama import chat, ChatResponse
 from openai import OpenAI
 import json
-from typing import Sequence
+from typing import Sequence, Optional
 from temporalio.common import RawValue
 import os
 from datetime import datetime
@@ -14,16 +14,67 @@ from models.data_types import ValidationInput, ValidationResult, ToolPromptInput
 
 load_dotenv(override=True)
 print(
-    "Using LLM: "
+    "Using LLM provider: "
-    + os.environ.get("LLM_PROVIDER")
+    + os.environ.get("LLM_PROVIDER", "openai")
     + " (set LLM_PROVIDER in .env to change)"
 )
 
 if os.environ.get("LLM_PROVIDER") == "ollama":
-    print("Using Ollama (local) model: " + os.environ.get("OLLAMA_MODEL_NAME"))
+    print("Using Ollama (local) model: " + os.environ.get("OLLAMA_MODEL_NAME", "qwen2.5:14b"))
 
 
 class ToolActivities:
+    def __init__(self):
+        """Initialize LLM clients based on environment configuration."""
+        self.llm_provider = os.environ.get("LLM_PROVIDER", "openai").lower()
+        print(f"Initializing ToolActivities with LLM provider: {self.llm_provider}")
+        
+        # Initialize client variables (all set to None initially)
+        self.openai_client: Optional[OpenAI] = None
+        self.anthropic_client: Optional[anthropic.Anthropic] = None
+        self.genai_configured: bool = False
+        self.deepseek_client: Optional[deepseek.DeepSeekAPI] = None
+        
+        # Only initialize the client specified by LLM_PROVIDER
+        if self.llm_provider == "openai":
+            if os.environ.get("OPENAI_API_KEY"):
+                self.openai_client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))
+                print("Initialized OpenAI client")
+            else:
+                print("Warning: OPENAI_API_KEY not set but LLM_PROVIDER is 'openai'")
+                
+        elif self.llm_provider == "anthropic":
+            if os.environ.get("ANTHROPIC_API_KEY"):
+                self.anthropic_client = anthropic.Anthropic(api_key=os.environ.get("ANTHROPIC_API_KEY"))
+                print("Initialized Anthropic client")
+            else:
+                print("Warning: ANTHROPIC_API_KEY not set but LLM_PROVIDER is 'anthropic'")
+                
+        elif self.llm_provider == "google":
+            api_key = os.environ.get("GOOGLE_API_KEY")
+            if api_key:
+                genai.configure(api_key=api_key)
+                self.genai_configured = True
+                print("Configured Google Generative AI")
+            else:
+                print("Warning: GOOGLE_API_KEY not set but LLM_PROVIDER is 'google'")
+                
+        elif self.llm_provider == "deepseek":
+            if os.environ.get("DEEPSEEK_API_KEY"):
+                self.deepseek_client = deepseek.DeepSeekAPI(api_key=os.environ.get("DEEPSEEK_API_KEY"))
+                print("Initialized DeepSeek client")
+            else:
+                print("Warning: DEEPSEEK_API_KEY not set but LLM_PROVIDER is 'deepseek'")
+        
+        # Ollama is initialized on-demand since it's a local API call
+        elif self.llm_provider == "ollama":
+            if not os.environ.get("OLLAMA_MODEL_NAME"):
+                print("Warning: OLLAMA_MODEL_NAME not set, will use default 'qwen2.5:14b'")
+            else:
+                print(f"Using Ollama model: {os.environ.get('OLLAMA_MODEL_NAME')}")
+        else:
+            print(f"Warning: Unknown LLM_PROVIDER '{self.llm_provider}', defaulting to OpenAI")
+
     @activity.defn
     async def agent_validatePrompt(
         self, validation_input: ValidationInput
@@ -87,17 +138,13 @@ class ToolActivities:
 
     @activity.defn
     def agent_toolPlanner(self, input: ToolPromptInput) -> dict:
-        llm_provider = os.environ.get("LLM_PROVIDER", "openai").lower()
+        if self.llm_provider == "ollama":
-
-        print(f"LLM provider: {llm_provider}")
-
-        if llm_provider == "ollama":
             return self.prompt_llm_ollama(input)
-        elif llm_provider == "google":
+        elif self.llm_provider == "google":
             return self.prompt_llm_google(input)
-        elif llm_provider == "anthropic":
+        elif self.llm_provider == "anthropic":
             return self.prompt_llm_anthropic(input)
-        elif llm_provider == "deepseek":
+        elif self.llm_provider == "deepseek":
             return self.prompt_llm_deepseek(input)
         else:
             return self.prompt_llm_openai(input)
@@ -114,9 +161,12 @@ class ToolActivities:
             raise json.JSONDecodeError
 
     def prompt_llm_openai(self, input: ToolPromptInput) -> dict:
-        client = OpenAI(
+        if not self.openai_client:
-            api_key=os.environ.get("OPENAI_API_KEY"),
+            api_key = os.environ.get("OPENAI_API_KEY")
-        )
+            if not api_key:
+                raise ValueError("OPENAI_API_KEY is not set in the environment variables but LLM_PROVIDER is 'openai'")
+            self.openai_client = OpenAI(api_key=api_key)
+            print("Initialized OpenAI client on demand")
 
         messages = [
             {
@@ -131,7 +181,7 @@ class ToolActivities:
             },
         ]
 
-        chat_completion = client.chat.completions.create(
+        chat_completion = self.openai_client.chat.completions.create(
             model="gpt-4o", messages=messages  # was gpt-4-0613
         )
 
@@ -168,11 +218,14 @@ class ToolActivities:
         return self.parse_json_response(response_content)
 
     def prompt_llm_google(self, input: ToolPromptInput) -> dict:
+        if not self.genai_configured:
             api_key = os.environ.get("GOOGLE_API_KEY")
             if not api_key:
-            raise ValueError("GOOGLE_API_KEY is not set in the environment variables.")
+                raise ValueError("GOOGLE_API_KEY is not set in the environment variables but LLM_PROVIDER is 'google'")
-
             genai.configure(api_key=api_key)
+            self.genai_configured = True
+            print("Configured Google Generative AI on demand")
+
         model = genai.GenerativeModel(
             "models/gemini-1.5-flash",
             system_instruction=input.context_instructions
@@ -189,15 +242,14 @@ class ToolActivities:
         return self.parse_json_response(response_content)
 
     def prompt_llm_anthropic(self, input: ToolPromptInput) -> dict:
+        if not self.anthropic_client:
             api_key = os.environ.get("ANTHROPIC_API_KEY")
             if not api_key:
-            raise ValueError(
+                raise ValueError("ANTHROPIC_API_KEY is not set in the environment variables but LLM_PROVIDER is 'anthropic'")
-                "ANTHROPIC_API_KEY is not set in the environment variables."
+            self.anthropic_client = anthropic.Anthropic(api_key=api_key)
-            )
+            print("Initialized Anthropic client on demand")
 
-        client = anthropic.Anthropic(api_key=api_key)
+        response = self.anthropic_client.messages.create(
-
-        response = client.messages.create(
             model="claude-3-5-sonnet-20241022",  # todo try claude-3-7-sonnet-20250219
             max_tokens=1024,
             system=input.context_instructions
@@ -220,7 +272,12 @@ class ToolActivities:
         return self.parse_json_response(response_content)
 
     def prompt_llm_deepseek(self, input: ToolPromptInput) -> dict:
-        api_client = deepseek.DeepSeekAPI(api_key=os.environ.get("DEEPSEEK_API_KEY"))
+        if not self.deepseek_client:
+            api_key = os.environ.get("DEEPSEEK_API_KEY")
+            if not api_key:
+                raise ValueError("DEEPSEEK_API_KEY is not set in the environment variables but LLM_PROVIDER is 'deepseek'")
+            self.deepseek_client = deepseek.DeepSeekAPI(api_key=api_key)
+            print("Initialized DeepSeek client on demand")
 
         messages = [
             {
@@ -235,7 +292,7 @@ class ToolActivities:
             },
         ]
 
-        response = api_client.chat_completion(prompt=messages)
+        response = self.deepseek_client.chat_completion(prompt=messages)
         response_content = response
         print(f"DeepSeek response: {response_content}")
 

scripts/run_worker.py

@@ -1,6 +1,7 @@
 import asyncio
-
 import concurrent.futures
+import os
+from dotenv import load_dotenv
 
 from temporalio.worker import Worker
 
@@ -11,10 +12,19 @@ from shared.config import get_temporal_client, TEMPORAL_TASK_QUEUE
 
 
 async def main():
+    # Load environment variables
+    load_dotenv(override=True)
+    
+    # Print LLM configuration info
+    llm_provider = os.environ.get("LLM_PROVIDER", "openai").lower()
+    print(f"Worker will use LLM provider: {llm_provider}")
+    
     # Create the client
     client = await get_temporal_client()
 
+    # Initialize the activities class once with the specified LLM provider
     activities = ToolActivities()
+    print(f"ToolActivities initialized with LLM provider: {llm_provider}")
 
     # Run the worker
     with concurrent.futures.ThreadPoolExecutor(max_workers=100) as activity_executor:

workflows/workflow_helpers.py

@@ -14,7 +14,7 @@ from shared.config import TEMPORAL_LEGACY_TASK_QUEUE
 # Constants from original file
 TOOL_ACTIVITY_START_TO_CLOSE_TIMEOUT = timedelta(seconds=12)
 TOOL_ACTIVITY_SCHEDULE_TO_CLOSE_TIMEOUT = timedelta(minutes=30)
-LLM_ACTIVITY_START_TO_CLOSE_TIMEOUT = timedelta(seconds=12)
+LLM_ACTIVITY_START_TO_CLOSE_TIMEOUT = timedelta(seconds=20)
 LLM_ACTIVITY_SCHEDULE_TO_CLOSE_TIMEOUT = timedelta(minutes=30)