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import os | |
import logging | |
from graph import agent_graph | |
# Configure logging | |
logging.basicConfig(level=logging.INFO) # Default to INFO level | |
logger = logging.getLogger(__name__) | |
# Enable LiteLLM debug logging only if environment variable is set | |
import litellm | |
if os.getenv('LITELLM_DEBUG', 'false').lower() == 'true': | |
litellm.set_verbose = True | |
logger.setLevel(logging.DEBUG) | |
else: | |
litellm.set_verbose = False | |
logger.setLevel(logging.INFO) | |
class AgentRunner: | |
def __init__(self): | |
logger.debug("Initializing AgentRunner") | |
logger.info("AgentRunner initialized.") | |
def __call__(self, question: str) -> str: | |
logger.debug(f"Processing question: {question[:50]}...") | |
logger.info(f"Agent received question (first 50 chars): {question[:50]}...") | |
try: | |
# Run the graph with the question | |
result = agent_graph.invoke({ | |
"messages": [], | |
"question": question, | |
"answer": None | |
}) | |
# Extract and return the answer | |
answer = result["answer"] | |
logger.debug(f"Successfully generated answer: {answer}") | |
logger.info(f"Agent returning answer: {answer}") | |
return answer | |
except Exception as e: | |
logger.error(f"Error in agent execution: {str(e)}", exc_info=True) | |
raise | |