run_single_agent.py

import os

from smolagents import LiteLLMModel

from agents.single_agent import create_single_agent
from loguru import logger
from config import get_ollama_api_base, setup_logger, load_api_keys, get_model_id

setup_logger()
load_api_keys()

# Set environment variables for API keys if needed
os.environ["GEMINI_API_KEY"] = str(os.getenv("GEMINI_API_KEY"))

use_local = False

# If using Ollama, we need to specify the API base URL
# Initialize the LLM model based on configuration
if use_local:
    model_id = "openrouter/google/gemini-2.0-flash-lite-preview-02-05:free"
else:
    model_id = get_model_id(use_local=use_local)

logger.info(f"Initializing with model: {model_id}")

if use_local:
    api_base = get_ollama_api_base()
    logger.info(f"Using Ollama API base: {api_base}")
    model = LiteLLMModel(model_id=model_id, api_base=api_base)
else:
    model = LiteLLMModel(model_id=model_id)

# If the agent does not answer, the model is overloaded, please use another model or the following Hugging Face Endpoint that also contains qwen2.5 coder:
# model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud' 

# Prompt the user for the song name
song_data = "John Frusciante - Crowded"

agent = create_single_agent(model)

# Agent execution
agent.run(f"""
1. Find and extract the lyrics of the song, {song_data}. Don't try to scrape from azlyrics.com or genius.com, others are ok.
2. Perform deep lyrics analysis and return full lyrics and analysis results in a pretty human-readable format.
""")