TinyCodeAgent

import asyncio
import os
from tinyagent.code_agent import TinyCodeAgent

async def main():
    # AI-powered code editor alternative
    agent = TinyCodeAgent(
        model="o4-mini",
        api_key=os.environ['OPENAI_API_KEY'],
        provider="modal",
        pip_packages=["black", "mypy", "flake8"],
        default_workdir=os.getcwd()
    )
    
    try:
        # Intelligent code editing and refactoring
        result = await agent.run("""
        I have a Python Flask API in 'app.py' that needs improvement:
        
        1. Read the current file and analyze its structure
        2. Add proper type hints to all functions
        3. Implement error handling for database operations
        4. Add input validation for API endpoints
        5. Format with black and check with flake8
        6. Create comprehensive docstrings
        7. Save the improved version
        
        Show me a summary of changes made.
        """)
        print(result)
    finally:
        await agent.close()

asyncio.run(main())

import asyncio
import os
import pandas as pd
from tinyagent.code_agent import TinyCodeAgent
from tinyagent.hooks.gradio_callback import GradioCallback
from tinyagent.hooks.logging_manager import LoggingManager
import logging

async def main():
    # Configure for accounting data analysis
    agent = TinyCodeAgent(
        model="o4-mini",
        api_key=os.environ['OPENAI_API_KEY'],
        pip_packages=["pandas"],
        provider_config={
            "pip_packages": ["gradio"]
        }
    )
    
    # Setup Gradio UI with logging
    log_manager = LoggingManager(default_level=logging.INFO)
    gradio_ui = GradioCallback(
        show_thinking=True,
        show_tool_calls=True
    )
    agent.add_callback(gradio_ui)
    
    # Load bank account data
    df = pd.read_csv("Corporate_account_2022-04-15-2025-06-15.csv", 
                     encoding='latin1', delimiter=';')
    
    # Pass dataframe to Python environment
    agent.set_user_variables(dict(df=df))
    
    try:
        result = await agent.run("""
        df is an export of a bank account for my company.
        I need to extract all payments to AWS (Amazon Web Services):
        - Total amount of payments to AWS
        - Total payments to AWS in each year
        - List transactions that might be typos or worth reviewing
        
        You have access to df variable in your python environment.
        """, max_turns=20)
        print(result)
    finally:
        await agent.close()

asyncio.run(main())

# Real-world example: Restaurant research automation
# Extract data from website + Google Maps API analysis in 10 lines
from tinyagent import TinyCodeAgent
import os
import asyncio

agent = TinyCodeAgent(
    model="o4-mini",
    api_key=os.environ.get("OPENAI_API_KEY"),
    ui="jupyter",
    authorized_imports=["json","pandas","requests"],
    local_execution=True,
)

async def run_example(page_content):
    GOOGLE_MAPS_API_KEY = os.environ.get("GOOGLE_MAPS_API_KEY")

    response = await agent.run(f"""
    Extract restaurant data from this Toronto website source:
    1. Get names, addresses, phone numbers
    2. Use Google Maps API for reviews/ratings  
    3. Sort by quality (reviews + rating combination)
    4. Export to CSV
    
    API Key: {GOOGLE_MAPS_API_KEY}
    
    <page_source>
    Restaurant Name | Address | Telephone
    1 Kitchen | 550 Wellington St W | 416-601-3533
    12 Tables | 1552 Avenue Rd | 416-590-7819
    612 Harlowe | 612 Richmond St W | 416-637-9998
    # ... more restaurants
    </page_source>
    """)
    
    # Agent automatically creates 'df' variable with results
    df = agent.code_provider._globals_dict['df']
    df.to_csv("restaurants_analyzed.csv")
    
asyncio.run(run_example(page_content))