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import os
import streamlit as st
from dotenv import load_dotenv
from phi.agent import Agent
from phi.model.groq import Groq
from phi.tools.duckduckgo import DuckDuckGo
from phi.tools.yfinance import YFinanceTools
# Load environment variables
load_dotenv()
# Retrieve API keys from the environment
deepseek_api_key = os.getenv("GROQ_DEEPSEEK_API_KEY")
qwen_api_key = os.getenv("GROQ_QWEN_API_KEY")
# Debugging API key loading
if not deepseek_api_key or not qwen_api_key:
raise ValueError("Missing API keys. Check your .env file.")
print("DeepSeek API Key Loaded")
print("Qwen API Key Loaded")
# Define the Web Agent using Groq's QWEN model
web_agent = Agent(
name="Web Agent",
model=Groq(id="qwen-2.5-coder-32b", api_key=qwen_api_key),
tools=[DuckDuckGo()],
instructions=["Always include sources"],
show_tool_calls=True,
markdown=True,
)
# Define the Finance Agent using Groq's DeepSeek model
finance_agent = Agent(
name="Finance Agent",
role="Get financial data",
model=Groq(id="qwen-2.5-coder-32b", api_key=qwen_api_key),
tools=[YFinanceTools(stock_price=True, analyst_recommendations=True, company_info=True)],
instructions=["Use tables to display data"],
show_tool_calls=True,
markdown=True,
)
# Combine agents into a team
agent_team = Agent(
model=Groq(id="deepseek-r1-distill-llama-70b", api_key=deepseek_api_key),
team=[web_agent, finance_agent],
instructions=["Always include sources", "Use tables to display data"],
show_tool_calls=True,
markdown=True,
)
# Debugging agent_team initialization
if not agent_team:
raise ValueError("Agent team failed to initialize.")
print("Agent team initialized successfully")
# Streamlit UI
st.set_page_config(page_title="AI Chat Assistant", layout="wide")
st.title("🤖 AI Chat Assistant")
# User input
if prompt := st.chat_input("Ask me anything..."):
with st.chat_message("user"):
st.markdown(prompt)
with st.chat_message("assistant"):
response_container = st.empty()
response_text = ""
# Ensure agent_team has a valid method to generate responses
if hasattr(agent_team, "respond") and callable(agent_team.respond):
try:
response_text = web_agent.respond(prompt) # Try this instead
response_container.markdown(response_text if response_text else "No response received.")
except Exception as e:
error_message = f"Error during response: {str(e)}"
print(error_message)
response_container.markdown(error_message)
else:
error_message = "Error: Agent does not support valid response methods."
print(error_message)
response_container.markdown(error_message)
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