app.py

import os
import requests
import gradio as gr

# --- CORRECTED LANGCHAIN IMPORTS ---
# create_react_agent and AgentExecutor are now imported directly from langchain.agents
from langchain.agents import AgentExecutor, create_react_agent
from langchain.tools import Tool
# We need to import the specific ReAct prompt template from the hub
from langchain import hub 
from langchain_google_genai import ChatGoogleGenerativeAI
from typing import List, Dict # Added for Gradio ChatInterface typing

# --- Configuration and Environment Setup ---

# IMPORTANT: Do NOT hardcode your API key.
# Define GEMINI_API_KEY as a Space Secret in your Hugging Face Space Settings.
GEMINI_API_KEY = os.environ.get("GEMINI_API_KEY")

if not GEMINI_API_KEY:
    # This message helps the user set up their Hugging Face Space correctly
    print("WARNING: GEMINI_API_KEY environment variable not set. Running without API key.")
    # We will raise a value error later during LLM initialization if it's actually needed.

# Initialize Gemini LLM
try:
    llm = ChatGoogleGenerativeAI(
        model="gemini-2.5-flash",
        temperature=0.3,
        google_api_key=GEMINI_API_KEY
    )
except Exception as e:
    # Graceful exit if API key is missing during initialization
    raise RuntimeError(
        "Could not initialize ChatGoogleGenerativeAI. "
        "Ensure GEMINI_API_KEY is set as a Space Secret."
    ) from e

# --- Tool Definition ---

def get_crypto_price(symbol: str) -> str:
    """Fetches the current price of a cryptocurrency symbol."""
    try:
        # Use lowercase symbol for CoinGecko API lookup
        lookup_symbol = symbol.lower()
        url = f"https://api.coingecko.com/api/v3/simple/price?ids={lookup_symbol}&vs_currencies=usd"
        res = requests.get(url).json()
        
        # Check if the symbol exists in the response
        price = res.get(lookup_symbol, {}).get('usd')
        
        if price:
            return f"💰 The current price of {symbol.capitalize()} is ${price:,.2f}"
        else:
            # Check for common partial matches as suggestions
            if not res and len(lookup_symbol) > 3:
                 return f"❌ Could not find price for symbol '{symbol}'. Try the full name (e.g., 'bitcoin', 'ethereum')."
            return f"❌ Could not find price for symbol '{symbol}'."
            
    except Exception as e:
        return f"⚠️ Error fetching price: {str(e)}"

# Create a Tool for the Agent
crypto_tool = Tool(
    name="Crypto Price Checker",
    func=get_crypto_price,
    description="Fetches the current cryptocurrency price using CoinGecko. Use this tool ONLY when the user asks for a specific crypto price (e.g., 'bitcoin', 'ethereum')."
)

# List of tools
tools = [crypto_tool]

# --- Agent Initialization (CORRECTED) ---

# 1. CORRECTED PROMPT: Pull the standard ReAct prompt from LangChain Hub.
# This prompt is guaranteed to have the required '{tools}' and '{tool_names}' variables.
prompt = hub.pull("hwchase17/react")

# 2. Create the Agent
# This uses the corrected 'create_react_agent' import
agent = create_react_agent(llm, tools, prompt)

# 3. Create the Agent Executor
# This uses the corrected 'AgentExecutor' import
agent_executor = AgentExecutor(
    agent=agent, 
    tools=tools, 
    verbose=True,
    handle_parsing_errors=True # Good practice for ReAct agents
)

# --- Gradio Interface Function ---

# Added 'history' for ChatInterface compatibility
def run_agent(user_query: str, history: List[List[str]]) -> str:
    """The main function called by Gradio to run the agent."""
    if not user_query:
        return "Please enter a question for the agent."

    try:
        # Use the AgentExecutor's invoke method
        # The input must be a dictionary
        response: Dict = agent_executor.invoke({"input": user_query})
        
        # Extract the final answer text
        return response.get("output", "Agent could not find a clear answer.")
        
    except Exception as e:
        # Catch and report any runtime errors gracefully
        return f"An error occurred while running the agent: {str(e)}"

# --- Gradio App Setup (Using ChatInterface for better UX) ---

gr.ChatInterface(
    fn=run_agent,
    title="💰 Gemini Crypto Price Agent (ReAct Pattern)",
    description="Ask the agent to check the current price of cryptocurrencies (e.g., bitcoin, ethereum). This agent uses the modern LangChain ReAct pattern (v0.1.0+).",
    examples=[
        ["What is the current price of Bitcoin?"],
        ["How much is Ethereum?"],
        ["What about solana?"]
    ]
).launch()