Building RAG AI Assistants with PhiData: A Comprehensive Guide

Building RAG AI Assistants with PhiData: A Comprehensive Guide

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Introduction

In the field of artificial intelligence, building an intelligent assistant that can understand and respond to user needs is a challenging task. PhiData, as an open-source framework, provides developers with the possibility to create AI assistants with long-term memory, rich knowledge, and powerful tools. This article will introduce the core advantages of PhiData, application examples, and how to use PhiData to build your own AI assistant.

The design philosophy of PhiData is as follows: an Assistant is centered around a Large Language Model (LLM), combined with long-term memory (Memory), knowledge (structured and unstructured), and tools (Tools, such as search, API calls, etc.), thus forming a complete Assistant.

Building RAG AI Assistants with PhiData: A Comprehensive Guide
Based on these design principles, PhiData can help users easily build assistant applications that not only have long-term memory to remember every conversation with users but also possess rich business knowledge and the ability to perform various actions.
Application Examples

PhiData is a powerful open-source framework specifically designed for building AI assistants with memory, knowledge, and tools. Here are some application examples of PhiData:

  • Web Search Assistant: With PhiData, you can create an AI assistant capable of performing web searches using search engines like DuckDuckGo or Google. Such an assistant can retrieve and process online information in real-time, providing users with the latest answers.

  • Financial Data Query Assistant: PhiData can be used to build an assistant that queries financial data, such as stock prices, analyst recommendations, and company information.

  • Data Analysis: Using PhiData, the AI assistant can perform data analysis using tools like SQL and DuckDb, suitable for tasks ranging from simple data retrieval to complex multi-step tasks.

  • Report Generation: PhiData can assist in research and report generation, which is very useful for scenarios requiring the integration of information from multiple sources to produce comprehensive reports.

  • Question and Answer System: An AI assistant can be built to answer questions from sources like PDFs and APIs, which is very helpful for information retrieval and knowledge management.

  • Article and Video Summarization: PhiData can also be used to create an AI assistant capable of summarizing article and video content, which is very useful for quickly obtaining key information.

  • Performing Specific Tasks: Tasks such as sending emails or querying databases can also be accomplished through an AI assistant built with PhiData.

The design philosophy of PhiData is to combine Large Language Models (LLMs) with long-term memory, rich business knowledge, and tools for performing various operations, thereby creating a powerful AI assistant that can accurately respond to user needs.

Building RAG AI Assistants with PhiData: A Comprehensive Guide

Developing Agents with PhiData

In the official repository’s cookbook directory, there is a demo agents program that uses Streamlit to develop an interactive interface. The default model used is OpenAI’s GPT-4. We made simple modifications to support Groq.

Building RAG AI Assistants with PhiData: A Comprehensive Guide

On the left, you can select models, choose tools, and select an assistant.

Draw a graph to illustrate the main content.

Building RAG AI Assistants with PhiData: A Comprehensive Guide
Then, for the assistants that can be delegated, prompts have been added with specific descriptions to facilitate LLM scheduling. Each assistant also has various tools that the LLM can choose from.
Building RAG AI Assistants with PhiData: A Comprehensive Guide

When we ask<span>NVIDIA's latest financial report</span>, the LLM recognizes the request, selects the<span>Investment Assistant</span> assistant, and then calls the<span>get_investment_report</span> tool.

Changing the question to <span>What happened in France today</span>, this successfully called DD search.

Application Scenarios

As an open-source framework for building AI assistants with memory, knowledge, and tools, PhiData has a very wide range of application scenarios. Here are some main application scenarios:

  • Customer Service: In the customer service field, PhiData can be used to build intelligent customer service robots that can understand customer questions and provide accurate answers or solutions. They can handle common issues, alleviating the burden on human customer service.

  • Personal Assistant: PhiData can be developed into personal assistant applications that help users manage schedules, set reminders, search for information, book restaurants or flights, etc.

  • Data Analysis and Reporting: In finance, consulting, and research fields, PhiData can be used to build data analysis tools that automatically collect data, perform analysis, and generate reports.

  • Educational Tutoring: In the education field, PhiData can be used to create intelligent educational assistants that provide personalized learning suggestions, answer student questions, and even assist in teaching.

  • Health Consultation: In the healthcare field, PhiData can be used to build health consultation robots that provide basic medical advice, medication information, symptom queries, and other services.

  • Technical Support: In the IT field, PhiData can be used to create technical support assistants that help users solve technical problems, providing troubleshooting and solutions.

  • Content Creation: PhiData can assist content creators, such as automatically generating article summaries, writing scripts, or providing creative inspiration.

  • Internal Business Tools: Within enterprises, PhiData can be used to build various tools, such as recruitment assistants for HR or report analysis tools for finance.

  • Market Research: In the market research field, PhiData can be used to collect market data, analyze consumer behavior, and generate market research reports.

  • Legal Consultation: In the legal field, PhiData can build legal consultation assistants that provide legal information queries, preliminary legal advice, and other services.

The application scenarios of PhiData mainly focus on fields that require intelligent interaction, data analysis, knowledge retrieval, and task automation. Through the integration of memory, knowledge, and tools it provides, PhiData can make AI assistants smarter and more efficient in serving various different scenarios.

Building RAG AI Assistants with PhiData: A Comprehensive Guide

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Building RAG AI Assistants with PhiData: A Comprehensive Guide

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