IBM Watsonx.ai

from dotenv import load_dotenv
import os

# Load environment variables from .env file
load_dotenv()

# Set up environment variables with fallback values
os.environ["IBM_WATSONX_API_KEY"] = os.getenv("IBM_WATSONX_API_KEY")
os.environ["IBM_WATSONX_URL"] = os.getenv("IBM_WATSONX_URL")
os.environ["IBM_WATSONX_PROJECT_ID"] = os.getenv("IBM_WATSONX_PROJECT_ID")
os.environ["AGENTOPS_API_KEY"] = os.getenv("AGENTOPS_API_KEY")

import agentops
from ibm_watsonx_ai import Credentials
from ibm_watsonx_ai.foundation_models import ModelInference

# Initialize AgentOps
agentops.init(api_key="")

# Initialize credentials
credentials = Credentials(
    url=os.getenv("IBM_WATSONX_URL"),
    api_key=os.getenv("IBM_WATSONX_API_KEY"),
)

# Project ID
project_id = os.getenv("IBM_WATSONX_PROJECT_ID")

# Create a model instance
model = ModelInference(
    model_id="meta-llama/llama-3-3-70b-instruct",
    credentials=credentials,
    project_id=project_id
)

# Make a completion request
response = model.generate_text("What is artificial intelligence?")
print(f"Generated Text:\n{response}")

# Don't forget to close connection when done
model.close_persistent_connection()