Deep Search Agent

from src.services.agents.deep_search_agent import AutogenDeepSearchAgent
from configs.oai_config import get_llm_config
import asyncio

# Initialize the agent
llm_config = get_llm_config(service_type="deepsearch")
agent = AutogenDeepSearchAgent(llm_config=llm_config)

# Perform a search
query = "What are the latest developments in quantum computing?"
result = asyncio.run(agent.deep_search(query))
print(result)

async def deep_search(self, query: str) -> str:
    """
    Execute deep search and return results
    
    Args:
        query: User's query question
        
    Returns:
        Search results and answer
    """

def web_agent_answer(self, query: str) -> str:
    """Execute deep search and return results (sync version)"""
    return asyncio.run(self.deep_search(query))

async def run(self, query: str) -> str:
    """Execute deep search with full trajectory"""
    final_answer, chat_result = await self.deep_search(query)
    return {
        "final_answer": final_answer,
        "trajectory": chat_result
    }

agent = AutogenDeepSearchAgent(
    llm_config=custom_llm_config,
    code_execution_config={"work_dir": "./search_workspace"},
    return_chat_history=True,  # Get full conversation history
    save_log=True  # Save logs for debugging
)

# Configure context management
agent.max_tool_messages_before_summary = 3  # Summarize every 3 tool calls
agent.token_limit = 3000  # Maximum tokens before summarization

try:
    result = await agent.a_web_agent_answer(query)
except Exception as e:
    # Errors are logged to search_error_log.txt
    print(f"Search error: {e}")