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import os
from phi.agent import Agent
from phi.tools.duckduckgo import DuckDuckGo
from phi.tools.exa import ExaTools
from phi.model.openai import OpenAIChat
from dotenv import load_dotenv
# Load environment variables (API keys, etc.)
load_dotenv()
#####################################################################################
# PHASE 2 #
#####################################################################################
##############################
# 1️⃣ Industry Trends Agent #
##############################
industry_trends_agent = Agent(
name="Industry Trends Agent",
model=OpenAIChat(id="gpt-4o"),
tools=[ExaTools(include_domains=["cnbc.com", "reuters.com", "bloomberg.com"])],
description="Finds the latest AI advancements in a given industry.",
show_tool_calls=True,
markdown=True,
)
def get_industry_trends(industry: str) -> dict:
""" Fetches the latest AI advancements, trends, and emerging technologies in a given industry. """
query = f"Find recent AI advancements in the {industry} sector, including major breakthroughs and adoption trends."
response = industry_trends_agent.run(query)
return {"industry": industry, "trends": response.content}
##################################
# 2️⃣ AI Use Case Discovery Agent #
##################################
ai_use_case_agent = Agent(
name="AI Use Case Discovery Agent",
model=OpenAIChat(id="gpt-4o"),
tools=[DuckDuckGo()],
description="Identifies AI applications relevant to a given industry.",
show_tool_calls=True,
markdown=True,
)
def get_ai_use_cases(industry: str) -> dict:
""" Identifies key AI use cases, automation improvements, and cost-saving innovations for an industry. """
query = f"Identify the most impactful AI use cases in the {industry} sector. Include real-world examples and benefits."
response = ai_use_case_agent.run(query)
return {"industry": industry, "use_cases": response.content}
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