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.env

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+GROQ_DEEPSEEK_API_KEY="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"
+GROQ_QWEN_API_KEY="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"

agent 2.py

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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)