mirror of
https://github.com/temporal-community/temporal-ai-agent.git
synced 2026-03-15 14:08:08 +01:00
activity init function to load llm client only once
This commit is contained in:
@@ -2,7 +2,7 @@ from temporalio import activity
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from ollama import chat, ChatResponse
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from openai import OpenAI
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import json
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from typing import Sequence
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from typing import Sequence, Optional
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from temporalio.common import RawValue
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import os
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from datetime import datetime
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@@ -14,16 +14,67 @@ from models.data_types import ValidationInput, ValidationResult, ToolPromptInput
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load_dotenv(override=True)
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print(
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"Using LLM: "
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+ os.environ.get("LLM_PROVIDER")
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"Using LLM provider: "
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+ os.environ.get("LLM_PROVIDER", "openai")
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+ " (set LLM_PROVIDER in .env to change)"
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)
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if os.environ.get("LLM_PROVIDER") == "ollama":
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print("Using Ollama (local) model: " + os.environ.get("OLLAMA_MODEL_NAME"))
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print("Using Ollama (local) model: " + os.environ.get("OLLAMA_MODEL_NAME", "qwen2.5:14b"))
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class ToolActivities:
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def __init__(self):
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"""Initialize LLM clients based on environment configuration."""
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self.llm_provider = os.environ.get("LLM_PROVIDER", "openai").lower()
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print(f"Initializing ToolActivities with LLM provider: {self.llm_provider}")
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# Initialize client variables (all set to None initially)
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self.openai_client: Optional[OpenAI] = None
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self.anthropic_client: Optional[anthropic.Anthropic] = None
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self.genai_configured: bool = False
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self.deepseek_client: Optional[deepseek.DeepSeekAPI] = None
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# Only initialize the client specified by LLM_PROVIDER
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if self.llm_provider == "openai":
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if os.environ.get("OPENAI_API_KEY"):
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self.openai_client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))
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print("Initialized OpenAI client")
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else:
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print("Warning: OPENAI_API_KEY not set but LLM_PROVIDER is 'openai'")
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elif self.llm_provider == "anthropic":
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if os.environ.get("ANTHROPIC_API_KEY"):
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self.anthropic_client = anthropic.Anthropic(api_key=os.environ.get("ANTHROPIC_API_KEY"))
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print("Initialized Anthropic client")
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else:
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print("Warning: ANTHROPIC_API_KEY not set but LLM_PROVIDER is 'anthropic'")
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elif self.llm_provider == "google":
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api_key = os.environ.get("GOOGLE_API_KEY")
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if api_key:
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genai.configure(api_key=api_key)
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self.genai_configured = True
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print("Configured Google Generative AI")
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else:
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print("Warning: GOOGLE_API_KEY not set but LLM_PROVIDER is 'google'")
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elif self.llm_provider == "deepseek":
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if os.environ.get("DEEPSEEK_API_KEY"):
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self.deepseek_client = deepseek.DeepSeekAPI(api_key=os.environ.get("DEEPSEEK_API_KEY"))
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print("Initialized DeepSeek client")
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else:
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print("Warning: DEEPSEEK_API_KEY not set but LLM_PROVIDER is 'deepseek'")
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# Ollama is initialized on-demand since it's a local API call
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elif self.llm_provider == "ollama":
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if not os.environ.get("OLLAMA_MODEL_NAME"):
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print("Warning: OLLAMA_MODEL_NAME not set, will use default 'qwen2.5:14b'")
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else:
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print(f"Using Ollama model: {os.environ.get('OLLAMA_MODEL_NAME')}")
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else:
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print(f"Warning: Unknown LLM_PROVIDER '{self.llm_provider}', defaulting to OpenAI")
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@activity.defn
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async def agent_validatePrompt(
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self, validation_input: ValidationInput
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@@ -87,17 +138,13 @@ class ToolActivities:
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@activity.defn
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def agent_toolPlanner(self, input: ToolPromptInput) -> dict:
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llm_provider = os.environ.get("LLM_PROVIDER", "openai").lower()
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print(f"LLM provider: {llm_provider}")
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if llm_provider == "ollama":
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if self.llm_provider == "ollama":
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return self.prompt_llm_ollama(input)
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elif llm_provider == "google":
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elif self.llm_provider == "google":
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return self.prompt_llm_google(input)
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elif llm_provider == "anthropic":
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elif self.llm_provider == "anthropic":
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return self.prompt_llm_anthropic(input)
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elif llm_provider == "deepseek":
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elif self.llm_provider == "deepseek":
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return self.prompt_llm_deepseek(input)
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else:
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return self.prompt_llm_openai(input)
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@@ -114,9 +161,12 @@ class ToolActivities:
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raise json.JSONDecodeError
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def prompt_llm_openai(self, input: ToolPromptInput) -> dict:
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client = OpenAI(
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api_key=os.environ.get("OPENAI_API_KEY"),
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)
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if not self.openai_client:
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api_key = os.environ.get("OPENAI_API_KEY")
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if not api_key:
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raise ValueError("OPENAI_API_KEY is not set in the environment variables but LLM_PROVIDER is 'openai'")
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self.openai_client = OpenAI(api_key=api_key)
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print("Initialized OpenAI client on demand")
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messages = [
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{
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@@ -131,7 +181,7 @@ class ToolActivities:
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},
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]
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chat_completion = client.chat.completions.create(
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chat_completion = self.openai_client.chat.completions.create(
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model="gpt-4o", messages=messages # was gpt-4-0613
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)
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@@ -168,11 +218,14 @@ class ToolActivities:
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return self.parse_json_response(response_content)
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def prompt_llm_google(self, input: ToolPromptInput) -> dict:
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api_key = os.environ.get("GOOGLE_API_KEY")
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if not api_key:
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raise ValueError("GOOGLE_API_KEY is not set in the environment variables.")
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if not self.genai_configured:
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api_key = os.environ.get("GOOGLE_API_KEY")
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if not api_key:
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raise ValueError("GOOGLE_API_KEY is not set in the environment variables but LLM_PROVIDER is 'google'")
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genai.configure(api_key=api_key)
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self.genai_configured = True
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print("Configured Google Generative AI on demand")
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genai.configure(api_key=api_key)
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model = genai.GenerativeModel(
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"models/gemini-1.5-flash",
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system_instruction=input.context_instructions
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@@ -189,15 +242,14 @@ class ToolActivities:
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return self.parse_json_response(response_content)
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def prompt_llm_anthropic(self, input: ToolPromptInput) -> dict:
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api_key = os.environ.get("ANTHROPIC_API_KEY")
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if not api_key:
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raise ValueError(
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"ANTHROPIC_API_KEY is not set in the environment variables."
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)
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if not self.anthropic_client:
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api_key = os.environ.get("ANTHROPIC_API_KEY")
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if not api_key:
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raise ValueError("ANTHROPIC_API_KEY is not set in the environment variables but LLM_PROVIDER is 'anthropic'")
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self.anthropic_client = anthropic.Anthropic(api_key=api_key)
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print("Initialized Anthropic client on demand")
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client = anthropic.Anthropic(api_key=api_key)
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response = client.messages.create(
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response = self.anthropic_client.messages.create(
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model="claude-3-5-sonnet-20241022", # todo try claude-3-7-sonnet-20250219
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max_tokens=1024,
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system=input.context_instructions
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@@ -220,7 +272,12 @@ class ToolActivities:
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return self.parse_json_response(response_content)
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def prompt_llm_deepseek(self, input: ToolPromptInput) -> dict:
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api_client = deepseek.DeepSeekAPI(api_key=os.environ.get("DEEPSEEK_API_KEY"))
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if not self.deepseek_client:
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api_key = os.environ.get("DEEPSEEK_API_KEY")
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if not api_key:
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raise ValueError("DEEPSEEK_API_KEY is not set in the environment variables but LLM_PROVIDER is 'deepseek'")
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self.deepseek_client = deepseek.DeepSeekAPI(api_key=api_key)
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print("Initialized DeepSeek client on demand")
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messages = [
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{
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@@ -235,7 +292,7 @@ class ToolActivities:
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},
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]
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response = api_client.chat_completion(prompt=messages)
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response = self.deepseek_client.chat_completion(prompt=messages)
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response_content = response
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print(f"DeepSeek response: {response_content}")
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