Phidata: Easily Build Autonomous AI Agents with GPT-4o!
TLDRThe video tutorial introduces Phidata, a framework for building autonomous AI agents with GPT-4o. It demonstrates how to create agents with long-term memory and the ability to perform actions through function calling. The creator, Sash PR, guides viewers through building various agents, such as a web search agent and a finance agent, by integrating tools like web searching and querying APIs. The tutorial also covers creating custom tools for internal APIs and showcases examples of data analysis and research assistants. The framework's extensibility allows for personalized AI solutions, making it an invaluable resource for developers interested in AI.
Takeaways
- ๐ Phidata is a framework that simplifies the creation of autonomous AI agents with function calling.
- ๐ง The video demonstrates the new upgrades of Phidata, focusing on building AI systems with long-term memory and contextual knowledge.
- ๐ ๏ธ The creator of Phidata, Sash PR, shows step-by-step how to build agents with GPT 40, including web search and finance agents.
- ๐ The code for building these agents is available in the Phidata repository, which can be forked and cloned for use.
- ๐ The assistant built with Phidata can utilize tools like web search, email sending, and querying cloud APIs to solve problems autonomously.
- ๐ The video includes a demonstration of creating a finance assistant using Yahoo Finance tool and GPT 40 to retrieve stock prices and write comparisons.
- ๐ป The ability to build custom tools for internal APIs is highlighted, showcasing the flexibility of Phidata for various applications.
- ๐ The use of DuckDB for data analysis within the assistant is demonstrated, showing how it can process and visualize data from CSV files.
- ๐ The video also covers creating a research assistant that uses EXA to search the web and generate reports in a specified format, including saving to a markdown file.
- ๐ The framework is extensible, allowing users to build upon the base examples and add personalized features and code.
- ๐ The video encourages viewers to explore the framework, follow the creator on Patreon and Twitter for updates, and subscribe for the latest AI news.
Q & A
What is Phidata and how is it used in creating autonomous AI assistance?
-Phidata is a framework that simplifies the creation of autonomous AI assistance through function calling. It allows users to build AI agents with long-term memory, contextual knowledge, and the ability to take actions from function calling.
What are the new upgrades in the Phidata framework that are being explored in the video?
-The new upgrades in the Phidata framework enable the building of intricate autonomous AI systems with enhanced capabilities such as long-term memory, contextual knowledge, and the ability to perform actions like web searches and querying cloud APIs.
How does one get started with building an autonomous assistant using Phidata?
-To get started, one needs to fork and clone the Phidata repository, open it in a code editor, and set up a Python virtual environment. The basic steps are outlined in the readme file of the repository.
What is the role of GPT-40 in the context of building autonomous AI agents with Phidata?
-GPT-40 is used as the language model in Phidata to create autonomous assistants. It is integrated with various tools to enable problem-solving capabilities for the AI agents.
Can the basic assistant built with Phidata perform tasks without any additional tools?
-Yes, a basic assistant built with Phidata can take an LLM, follow given descriptions and instructions, and perform tasks such as printing a response to the CLI or running a query if it's part of an application.
How is the web search capability integrated into the Phidata framework?
-The web search capability is integrated by importing the 'Duco' tool from 'fire tools' and adding it to the assistant. This allows the assistant to perform tasks like searching for news and writing about it.
What is the significance of the finance assistant example shown in the video?
-The finance assistant example demonstrates how to build a more complex AI agent using Phidata with specific tools like Yahoo Finance. It shows how the assistant can perform tasks such as getting stock prices and writing comparisons between companies.
How can users build their own tools for use with Phidata?
-Users can build their own tools by writing custom Python code and describing the function, its arguments, and return values. Phidata will then format this information in a way that the LLM can understand and use it within the assistant.
What is the purpose of the 'debug mode' in Phidata?
-The 'debug mode' in Phidata, when set to true, prints all the debug logs. This feature is useful for developers to understand what's happening behind the scenes and to troubleshoot any issues.
Can the assistants built with Phidata generate reports and save them to files?
-Yes, the assistants built with Phidata can generate reports and save them to files. The script demonstrates this with a research assistant that writes a report on a given topic and saves it in a markdown file.
Outlines
๐ Introduction to Building Autonomous AI Assistants with Fi Data
The video script introduces the concept of building autonomous AI assistants using the Fi Data framework. It highlights the ease of creating AI systems with long-term memory, contextual knowledge, and the ability to take actions from function calling. The creator, Sash PR, demonstrates how to construct agents using GPT 40, including a web search agent and a finance agent. The process involves forking and cloning the F data repository, setting up a Python virtual environment, and utilizing tools to enhance the AI's capabilities. The script emphasizes the use of GPT 40 for its speed and quality, and showcases a basic assistant's functionality before integrating additional tools like web search and finance analysis.
๐ ๏ธ Enhancing AI Assistants with Tools and Custom APIs
This section delves into the process of enhancing basic AI assistants with various tools to make them autonomous. It discusses the integration of tools like Duco for web search, Yahoo Finance for stock information, and the creation of custom APIs, such as the Hacker News API. The script explains how these tools are added to the AI system and how they can be utilized to perform tasks like fetching news, generating reports, and summarizing data. It also touches on the importance of not overloading the AI model with too many functions to maintain efficiency. The video demonstrates the process of building a finance assistant, creating a histogram with DuckDB, and using EXA to perform web searches and generate reports.
๐ Building a Research Assistant and Personalized AI Tools
The final paragraph focuses on the creation of a research assistant that uses EXA to search the web and generate a formatted report. It details the process of instructing the AI to write an article about a specific topic, save the output to a file, and format the response in Markdown. The script also mentions the importance of personalizing AI tools for specific use cases, such as integrating internal APIs for company products. The video concludes by emphasizing the extensibility of the Fi Data framework and encourages viewers to explore the examples provided. It wraps up with a call to action for viewers to follow the creator on Patreon and Twitter for access to free subscriptions and the latest AI news.
Mindmap
Keywords
๐กAutonomous AI Agents
๐กFunction Calling
๐กLong-term Memory
๐กContextual Knowledge
๐กGPT-4o
๐กWeb Search Agent
๐กFinance Agent
๐กTool Integration
๐กPython Virtual Environments
๐กDebug Mode
Highlights
Introduction to Phidata, a framework for creating autonomous AI assistants with function calling.
Exploration of new upgrades in the Phidata framework for building AI systems with long-term memory and contextual knowledge.
Demonstration of building agents with GPT 4.0 from scratch by the creator of Phidata.
Building an assistant using Phidata with tools like web search and email sending.
Instructions on cloning the Phidata repository and setting up the environment.
Creating a basic assistant with the GPT 4 model and generating a simple breakfast recipe.
Adding web search functionality to the assistant using the Duco tool.
Benefits of Patreon membership including access to AI tools and community collaboration.
Building a finance assistant with Yahoo Finance tool for stock price checks and company information.
Creating custom tools for internal APIs to enhance the capabilities of AI assistants.
Debug mode feature to understand what happens behind the scenes in the assistant's operation.
Using DuckDB for data analysis in CSV and Parquet files with the assistant.
Creating a research assistant that uses EXA to search the web and generate reports.
Saving the output of the research assistant's report to a markdown file.
The extendability of the Phidata framework allowing for personalized AI agent development.
Encouragement to watch previous videos for more understanding of the Phidata framework.
Invitation to join Patreon for access to free subscriptions and stay updated with AI news.