import os
from dotenv import load_dotenv
from crewai import Agent, Task, Crew
from crewai_tools import BaseTool
import requests

# Load environment variables from .env file
load_dotenv()

class VerboseSearchTool(BaseTool):
    name: str = "VerboseSearchTool"
    description: str = "A tool for searching web data with verbose output for debugging."

    def _run(self, query: str) -> dict:
        api_key = os.getenv("SERPER_API_KEY")
        base_url = os.getenv("SERPER_API_BASE")
        headers = {'Authorization': f'Bearer {api_key}'}
        params = {'q': query}
        
        # Log the URL and headers for debugging
        print(f"Attempting to hit URL: {base_url} with query: {params} using API Key: {api_key}")
        
        try:
            response = requests.get(base_url, headers=headers, params=params)
            response.raise_for_status()  # This will raise an exception for HTTP errors
            return response.json()
        except requests.exceptions.HTTPError as e:
            print(f"HTTP error occurred: {e} - Status code: {response.status_code}")
            return {"error": str(e), "status_code": response.status_code}
        except Exception as e:
            print(f"An error occurred: {e}")
            return {"error": str(e)}

# Initialize the search tool
search_tool = VerboseSearchTool()

# Define your agents with roles, goals, tools, and additional attributes
researcher = Agent(
    role='Senior Research Analyst',
    goal='Uncover cutting-edge developments in AI and data science',
    backstory=(
        "You are a Senior Research Analyst at a leading tech think tank. "
        "Your expertise lies in identifying emerging trends and technologies in AI and data science. "
        "You have a knack for dissecting complex data and presenting actionable insights."
    ),
    verbose=True,
    allow_delegation=False,
    tools=[search_tool],
    max_rpm=1000
)

writer = Agent(
    role='Tech Content Strategist',
    goal='Craft compelling content on tech advancements',
    backstory=(
        "You are a renowned Tech Content Strategist, known for your insightful and engaging articles on technology and innovation. "
        "With a deep understanding of the tech industry, you transform complex concepts into compelling narratives."
    ),
    verbose=True,
    allow_delegation=True,
    tools=[search_tool],
    cache=False  # Disable cache for this agent
)

# Create tasks for your agents
task1 = Task(
    description=(
        "Perform an in-depth review of the most recent progress in open-source large language models (LLMs) for business applications and custom solution integrations in 2024. "
        "Highlight pivotal trends, innovative technologies, and their prospective implications for various industries."
        "Compile your findings in a detailed report."
        "Make sure to check with a human if the draft is good before finalizing your answer."
    ),
    expected_output='A comprehensive full report on the latest AI advancements in 2024, leave nothing out',
    agent=researcher,
    human_input=True,
)

task2 = Task(
    description=(
        "Using the insights from the researcher's report, develop an engaging blog post that highlights the most significant AI advancements. "
        "Your post should be informative yet accessible, catering to an investor audience. "
        "Aim for a narrative that captures the essence of these breakthroughs and their implications for the future."
    ),
    expected_output='A detailed and engaging three-paragraph blog post, formatted in Markdown, discussing the newest developments in open-source large language models (LLMs) for business applications and custom solution integrations in 2024',
    agent=writer
)

# Instantiate your crew with a sequential process
crew = Crew(
    agents=[researcher, writer],
    tasks=[task1, task2],
    verbose=2
)

# Get your crew to work!
result = crew.kickoff()

print("######################")
print(result)