Update app.py

app.py

@@ -1,20 +1,69 @@
 # LangChain version is pinned to 0.3.0 in requirements.txt.
-# We must use the 'initialize_agent' pattern and not the 'create_react_agent' pattern (which was introduced later).
+# We must use the 'initialize_agent' pattern.
 
-# Correct Imports for LangChain v0.3.0:
+# CORE IMPORTS
 from langchain.agents import AgentExecutor
 from langchain.agents import initialize_agent, AgentType
+from langchain.llms import GooglePalm  # Using a generic LLM wrapper for LangChain < 0.4.0
+from langchain.tools import Tool
+from typing import Optional, Type
+from pydantic import BaseModel, Field
 
-print("AgentExecutor and initialize_agent imported successfully for v0.3.0!")
-
-# NOTE: The old 'initialize_agent' method is the correct way to build agents
-# in the 0.3.0 version.
-# Example usage (assuming you define tools and an LLM):
-# def create_my_agent(llm, tools):
-#     agent = initialize_agent(
-#         tools, 
-#         llm, 
-#         agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, 
-#         verbose=True
-#     )
-#     return agent
+# --- TOOL DEFINITION ---
+# 1. Define the input schema for the tool (Pydantic is required for structured input)
+class CryptoPriceInput(BaseModel):
+    """Input for the Crypto Price Checker tool."""
+    cryptocurrency: str = Field(description="The name of the cryptocurrency (e.g., 'bitcoin', 'ethereum').")
+
+# 2. Define the tool function
+def get_crypto_price(cryptocurrency: str) -> str:
+    """
+    Returns the current price of a specified cryptocurrency.
+    Note: This is a placeholder function and returns a mock price.
+    """
+    crypto_prices = {
+        "bitcoin": "101,664.00",
+        "ethereum": "5,500.00",
+        "solana": "250.00",
+    }
+    
+    price = crypto_prices.get(cryptocurrency.lower())
+    if price:
+        return f"💰 {cryptocurrency.capitalize()} current price is ${price}"
+    else:
+        return f"Could not find the current price for {cryptocurrency}. Please try 'bitcoin', 'ethereum', or 'solana'."
+
+# 3. Create the LangChain Tool instance
+crypto_price_tool = Tool(
+    name="Crypto Price Checker",
+    func=get_crypto_price,
+    description="Useful for finding the current price of major cryptocurrencies like bitcoin or ethereum.",
+    args_schema=CryptoPriceInput # Attach Pydantic schema
+)
+
+# --- AGENT SETUP ---
+# 4. Initialize the LLM (Replace "YOUR_API_KEY" with an actual key or use environment variable)
+# NOTE: In v0.3.0, GooglePalm was often used for Google models.
+# If you intend to use the newer Gemini models, we would need to switch to a later version or use the specific community package import path.
+# For simplicity, we are using the generic placeholder LLM here.
+llm = GooglePalm(google_api_key="YOUR_API_KEY") # Replace with your actual key or load from env
+
+# 5. Define the list of tools the agent can use
+tools = [crypto_price_tool]
+
+# 6. Initialize the Agent Executor
+agent = initialize_agent(
+    tools, 
+    llm, 
+    agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, 
+    verbose=True # Set to True to see the Agent's thought process
+)
+
+# 7. Run the Agent
+print("\n--- Running Agent Test ---")
+response = agent.run("Check the current price of bitcoin.")
+
+print("\n--- Agent Final Response ---")
+print(response)
+
+print("\nAgentExecutor and initialize_agent imported successfully for v0.3.0!")