phidata

Introduction to Phidata

Phidata is a comprehensive framework designed for creating sophisticated systems known as agentic systems. These systems empower users to construct digital agents that can harness memory, knowledge, tools, and reasoning to perform various tasks.

Features of Phidata

1. Construction of Intelligent Agents: Phidata enables users to build agents that possess memory, knowledge, tools, and reasoning abilities. These agents can perform tasks such as web searches and data analysis.

2. Collaborative Agent Teams: Users can develop teams of agents that work collaboratively. This feature allows for complex tasks to be tackled by leveraging the shared capabilities of multiple agents.

3. Interactive Agent Interface: Phidata offers a user-friendly interface for interaction with agents. This interface allows users to issue commands and receive responses in a streamlined manner.

4. Monitoring and Optimization: The framework includes tools for monitoring the performance of agents, evaluating their efficiency, and optimizing their operations for improved outcomes.

5. Built-In Infrastructure: Phidata provides essential infrastructure elements such as APIs, databases, and vectorized databases to support the functioning and scalability of agentic systems.

Getting Started with Phidata

To install Phidata, use the following command:

pip install -U phidata

Examples of Phidata in Action

Web Search Agent

Phidata allows users to develop a web search agent capable of retrieving information from the internet. By using tools like DuckDuckGo, users can instruct the agent to perform searches and provide detailed responses.

from phi.agent import Agent
from phi.model.openai import OpenAIChat
from phi.tools.duckduckgo import DuckDuckGo

web_agent = Agent(
    name="Web Agent",
    model=OpenAIChat(id="gpt-4o"),
    tools=[DuckDuckGo()],
    instructions=["Always include sources"],
    show_tool_calls=True,
    markdown=True,
)
web_agent.print_response("Whats happening in France?", stream=True)

Finance Agent

Another practical application is in finance, where users can create agents to gather and summarize financial data and insights using services like YFinance.

from phi.agent import Agent
from phi.model.openai import OpenAIChat
from phi.tools.yfinance import YFinanceTools

finance_agent = Agent(
    name="Finance Agent",
    model=OpenAIChat(id="gpt-4o"),
    tools=[YFinanceTools(stock_price=True, analyst_recommendations=True, company_info=True, company_news=True)],
    instructions=["Use tables to display data"],
    show_tool_calls=True,
    markdown=True,
)
finance_agent.print_response("Summarize analyst recommendations for NVDA", stream=True)

Teams and Reasoning

Phidata supports creating teams of agents to combine their functionalities for more complex tasks. Moreover, it offers experimental features like reasoning, enabling agents to solve problems step by step and adjust their approach as needed.

Advanced Features

Phidata includes advanced capabilities like the RAG Agent, which optimizes resource usage by searching its knowledge base instead of constantly requiring external context. Additionally, it supports building reasoning agents that can work through complex tasks with iterative problem-solving techniques.

Agent Interaction UI

Phidata offers a Playground UI for seamless interaction with agents. This visual interface simplifies command input and result viewing, enhancing the overall user experience.

Conclusion

Phidata is a robust platform suited for developing intelligent, collaborative agents capable of accessing vast amounts of information and performing tasks with improved efficiency. Through its versatile tools and intuitive interface, Phidata empowers users to bring their agentic systems to life.