from agents import build_reader_agent, build_search_agent, writer_chain, critic_chain
import time

def extract_text(content) -> str:
    if isinstance(content, str):
        return content
    elif isinstance(content, list):
        return "".join(item.get("text", "") for item in content if isinstance(item, dict) and "text" in item)
    return str(content)

def run_research_pipeline(topic: str) -> dict:
    
    state={}

    #Search Agent working

    print("\n" + "="*50 )
    print("step 1 - search agent is wokring ...")
    print("=" *50)

    search_agent= build_search_agent()
    search_result= search_agent.invoke({ 
        "messages": [("user", f"Find recent, reliable and detailed information about: {topic}")]
    })

    state["search_results"]= extract_text(search_result['messages'][-1].content)
    print("\n search result", state['search_results'])

    # Introduce delay to prevent rate limits
    time.sleep(5)

    #Step 2 - reader agent
    print("\n" + "="*50)
    print("step 2- reader agent is scrapping top respurces ...")
    print("="*50)

    reader_agent= build_reader_agent()
    reader_result = reader_agent.invoke({ 
        "messages": [("user",
        f"Based on the following search results about '{topic}',"
        f"pick the most relevant URL and scrape it for deeper content.\n\n"
        f"Search Results: \n{state['search_results'][:800]}"
        )]
    }) 

    state['scraped_content']= extract_text(reader_result['messages'][-1].content)
    print("\nScraped content\n", state['scraped_content'])

    # Introduce delay to prevent rate limits
    time.sleep(5)

    #Step 3- writer chain

    print("\n" + "="*50)
    print("step 3- Writer is drafting the report ...")
    print("="*50)

    research_combined= ( 
        f"Search Results: \n {state['search_results']}\n\n"
        f"Detailed Scraped Content: \n {state['scraped_content']}"
    
    )

    state['report']= writer_chain.invoke({
        "topic":topic,
        "research": research_combined
    })

    print("\n final report\n", state['report'])

    #Critic Report
    print("\n" + "="*50)
    print("step 3- Critic is reviewing the report ...")
    print("="*50)

    # Introduce delay to prevent rate limits
    time.sleep(5)

    state['feedback']=critic_chain.invoke({
        "report": state['report']
    })

    print("\n critic report \n", state['feedback'])

    return state

if __name__ == "__main__":
    topic= input("\n Enter a research topic: " )
    run_research_pipeline(topic)