import os
from crewai import Agent, Task, Crew, Process, LLM
from crewai_tools import SerperDevTool

# 1. Setup Environment Variables
# Gemini provides the reasoning LLM engine; Serper provides live Google Search access
os.environ["GEMINI_API_KEY"] = "YOUR_GEMINI_API_KEY"
os.environ["SERPER_API_KEY"] = "YOUR_SERPER_API_KEY"

# 2. Define the Brain (LLM)
gemini_brain = LLM(
    model="gemini/gemini-1.5-flash",
    temperature=0.3  # Lower temperature ensures factual adherence during web research
)

# 3. Initialize the Web Search Tool
search_tool = SerperDevTool()

# 4. Define the Research Agent with Tools attached
research_agent = Agent(
    role="Senior Market Research Analyst",
    goal="Uncover cutting-edge industry trends, technical advancements, and live market data.",
    backstory=(
        "You are a relentless tech researcher. You don't rely on old knowledge; "
        "you use search engines to cross-reference multiple modern sources, weed out "
        "marketing fluff, and isolate hard, technical facts."
    ),
    verbose=True,
    allow_delegation=False,
    llm=gemini_brain,
    tools=[search_tool]  # <-- Attaching web search capability directly to the Agent
)

# 5. Define the Research Task
topic = "Mahindra electric vehicle platforms like INGLO and competition comparison"

research_task = Task(
    description=(
        f"Conduct a thorough online search regarding: '{topic}'. "
        "Find the key technical specs, target launch timeline, and architecture benefits. "
        "Filter out generic press release fluff and synthesize the core technical details."
    ),
    expected_output="A structured markdown report with key technical bullet points and clear headings.",
    agent=research_agent
)

# 6. Assemble the Crew and Kick off
crew = Crew(
    agents=[research_agent],
    tasks=[research_task],
    process=Process.sequential
)

print(f"--- Starting Live Web Research on '{topic}' ---")
result = crew.kickoff()

print("\n--- Final Result ---")
print(result)