pip install pixelagent
# Install provider-specific dependencies
pip install anthropic  # For Claude models
pip install openai     # For GPT models

from pixelagent.anthropic import Agent  # Or from pixelagent.openai import Agent

# Create a simple agent
agent = Agent(
    agent_name="my_assistant",
    system_prompt="You are a helpful assistant."
)

# Chat with your agent
response = agent.chat("Hello, who are you?")
print(response)

import pixeltable as pxt
from pixelagent.anthropic import Agent
import yfinance as yf

# Define a tool as a UDF
@pxt.udf
def stock_price(ticker: str) -> dict:
    """Get stock information for a ticker symbol"""
    stock = yf.Ticker(ticker)
    return stock.info

# Create agent with tool
agent = Agent(
    agent_name="financial_assistant",
    system_prompt="You are a financial analyst assistant.",
    tools=pxt.tools(stock_price)
)

# Use tool calling
result = agent.tool_call("What's the current price of NVDA?")
print(result)

import pixeltable as pxt

# Agent memory is automatically persisted
memory = pxt.get_table("my_assistant.memory")
conversations = memory.collect()

# Access tool call history
tools_log = pxt.get_table("financial_assistant.tools")
tool_history = tools_log.collect()

# Unlimited memory
infinite_agent = Agent(
    agent_name="historian",
    system_prompt="You remember everything.",
    n_latest_messages=None  # No limit on conversation history
)

import re
from datetime import datetime
from pixelagent.openai import Agent
import pixeltable as pxt

# Define a tool
@pxt.udf
def stock_info(ticker: str) -> dict:
    """Get stock information for analysis"""
    import yfinance as yf
    stock = yf.Ticker(ticker)
    return stock.info

# ReAct system prompt with structured reasoning pattern
REACT_PROMPT = """
Today is {date}

IMPORTANT: You have {max_steps} maximum steps. You are on step {step}.

Follow this EXACT step-by-step reasoning and action pattern:

1. THOUGHT: Think about what information you need to answer the question.
2. ACTION: Either use a tool OR write "FINAL" if you're ready to give your final answer.

Available tools:
{tools}

Always structure your response with these exact headings:

THOUGHT: [your reasoning]
ACTION: [tool_name] OR simply write "FINAL"
"""

# Helper function to extract sections from responses
def extract_section(text, section_name):
    pattern = rf'{section_name}:?\s*(.*?)(?=\n\s*(?:THOUGHT|ACTION):|$)'
    match = re.search(pattern, text, re.DOTALL | re.IGNORECASE)
    return match.group(1).strip() if match else ""

# Execute ReAct planning loop
def run_react_loop(question, max_steps=5):
    step = 1
    while step <= max_steps:
        # Dynamic system prompt with current step
        react_system_prompt = REACT_PROMPT.format(
            date=datetime.now().strftime("%Y-%m-%d"),
            tools=["stock_info"],
            step=step,
            max_steps=max_steps,
        )
        
        # Agent with updated system prompt
        agent = Agent(
            agent_name="financial_planner",
            system_prompt=react_system_prompt,
            reset=False,  # Maintain memory between steps
        )
        
        # Get agent's response for current step
        response = agent.chat(question)
        
        # Extract action to determine next step
        action = extract_section(response, "ACTION")
        
        # Check if agent is ready for final answer
        if "FINAL" in action.upper():
            break
            
        # Call tool if needed
        if "stock_info" in action.lower():
            tool_agent = Agent(
                agent_name="financial_planner",
                tools=pxt.tools(stock_info)
            )
            tool_agent.tool_call(question)
            
        step += 1
    
    # Generate final recommendation
    return Agent(agent_name="financial_planner").chat(question)

# Run the planning loop
recommendation = run_react_loop("Create an investment recommendation for AAPL")