import os
from dotenv import load_dotenv
import gradio as gr
from crewai import Agent, Task, Crew
# Importing crewAI tools
from crewai_tools import (
    DirectoryReadTool,
    FileReadTool,
    SerperDevTool,
    WebsiteSearchTool
)

# Load environment variables
load_dotenv()

# Get API keys from environment variables
SERPER_API_KEY = os.getenv("SERPER_API_KEY")
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")

# Instantiate tools
file_tool = FileReadTool(file_path='plan2.txt')  # Adjusted to read plan.txt
search_tool = SerperDevTool()
web_rag_tool = WebsiteSearchTool()

# Create agents
analyst = Agent(
    role='Climate Strategy Analyst',
    goal='Analyze the climate strategy plan to identify key requirements and objectives.',
    backstory='An expert in climate strategy with experience in sustainable solutions.',
    tools=[file_tool],
    verbose=True
)

researcher = Agent(
    role='Climate Tech Researcher',
    goal='Find climate tech companies that provide solutions aligning with the strategy plan.',
    backstory='A researcher specialized in identifying and evaluating climate technology solutions.',
    tools=[search_tool, web_rag_tool],
    verbose=True
)

# Define tasks
analyze_strategy = Task(
    description='Analyze the climate strategy plan from plan.txt and extract key requirements.',
    expected_output='A detailed list of key requirements and objectives from the climate strategy plan.',
    agent=analyst
)

search_companies = Task(
    description='Search for climate tech companies that offer solutions meeting the extracted strategy requirements.',
    expected_output='A list of climate tech companies with brief descriptions of how their solutions align with the strategy needs.',
    agent=researcher,
    output_file='research_results/company_recommendations.md'  # The results will be saved here
)

# Assemble a crew with planning enabled
crew = Crew(
    agents=[analyst, researcher],
    tasks=[analyze_strategy, search_companies],
    verbose=True,
    planning=True,  # Enable planning feature
)

def run_crew():
    # Create crew and execute tasks
    crew = Crew(
        agents=[analyst, researcher],
        tasks=[analyze_strategy, search_companies],
        verbose=True,
        planning=True,
    )
    result = crew.kickoff()
    
    # Read and return the content of the output file
    with open('research_results/company_recommendations.md', 'r') as f:
        return f.read()

# Create Gradio interface
iface = gr.Interface(
    fn=run_crew,
    inputs=[],
    outputs=gr.Textbox(label="Results"),
    title="Climate Tech Company Finder",
    description="Click to analyze climate strategy and find relevant companies."
)

if __name__ == "__main__":
    iface.launch()