Using ChatGPT with YOUR OWN Data. This is magical. (LangChain OpenAI API)

The video script details a fascinating method to integrate personal data with Chat GPT, enabling the AI to organize and structure one's documents. This allows users to interact with their data through natural language queries. The video demonstrates how to describe companies of past internships, summarize Twitter feeds, and even use the AI for personal scheduling. It introduces the LangChain library for easy setup and emphasizes the importance of Python as a versatile language for coding. The script also discusses privacy concerns with OpenAI's API, contrasting it with Azure's version, and suggests direct coding as a more secure alternative to third-party plugins. The video concludes with potential applications of the technology, such as generating summaries from large datasets, and encourages viewers to explore the possibilities of personalizing AI interactions.

Takeaways

• 🤖 The user has discovered a method to integrate personal data with Chat GPT, enabling the AI to organize and structure their documents and interact with the data through natural language queries.
• 📄 The AI can describe companies of the user's internships, format information in bullet points, and recall specific events like a last dentist appointment from the user's personal data.
• 🗓 The AI can access the user's calendar data to answer questions about future plans, such as the user's parents' trip dates.
• 📰 The AI can summarize the user's Twitter feed or long articles by analyzing the provided text and generating concise summaries.
• 📝 Users can create custom applications, like a calendaring app, and ask the AI to analyze and manipulate the data, such as changing an appointment date.
• 💡 The user highlights the potential of using AI to analyze various types of personal data, including books, novels, diaries, blogs, PDFs, and research papers.
• 🔍 By using the LangChain library, users can set up their own personal bot to ingest custom data with minimal coding.
• 🔗 The process involves installing necessary libraries, using an OpenAI API key, and creating a vector store index to query against the personal data.
• 📚 The AI can be trained on the user's email responses, showcasing its ability to learn and mimic the user's communication style.
• 🔒 OpenAI's privacy policy ensures that data submitted via their API is not used to train or improve their models, and is retained for a maximum of 30 days for monitoring purposes before being deleted.
• 🛡 For users concerned about privacy, the Azure OpenAI service is an alternative that keeps data within Microsoft and is encrypted, with a smaller group of employees having access for debugging within a 30-day period.

Q & A

What is the main feature discussed in the transcript that allows personal data to be integrated with Chat GPT?

The main feature discussed is the ability to feed personal custom data into Chat GPT, enabling it to organize and structure documents, and interact with the data through natural language queries.

How does the LangChain library help in setting up a personal bot for Chat GPT?

LangChain simplifies the process by providing a pip installable package that allows users to load, vectorize, and query against their own personal data with just a few lines of code.

What is the significance of using Python in the context of this transcript?

Python is used as it is a widely known and versatile programming language, suitable for scripting and interacting with APIs like OpenAI. It is also emphasized for its simplicity and the fact that it is a standard language in the tech industry.

What are the privacy concerns associated with using OpenAI's API?

The privacy concerns include the potential use of submitted data for training or improving models, and the retention of data for up to 30 days for abuse and misuse monitoring purposes, as stated in OpenAI's privacy policy.

How does the Azure Open AI API differ from the Open AI API in terms of data privacy?

The Azure Open AI API is said to keep data submitted to its service within Microsoft, encrypted, and not used for training purposes, offering a higher level of privacy compared to the Open AI API.

What is the potential risk of using third-party plugins with Chat GPT?

The risk includes potential prompt injection hacking, where plugins may modify search queries and block out certain results, leading to unreliable or biased information.

How can Chat GPT be used to summarize long articles or social media feeds?

By feeding the text of long articles or social media feeds into Chat GPT, it can process the information and provide concise summaries, making it easier to digest large amounts of content.

What is the process of setting up a personal bot with Chat GPT using LangChain?

The process involves installing LangChain and Open AI packages via pip, obtaining an Open AI API key, and using the LangChain library to load, vectorize, and create an index for querying against personal data.

What are the benefits of merging custom data with external data when using Chat GPT?

Merging custom data with external data provides a more cohesive world model, allowing Chat GPT to have context about the outside world in addition to the user's personal data.

How can Chat GPT assist in debugging code?

Chat GPT can analyze code provided to it, identify typos or logical errors, and suggest corrections, making it a useful tool for programmers.

What is an example of an innovative use case for Chat GPT discussed in the transcript?

An example given is the use of Chat GPT to analyze customer reviews and generate short review summaries for car listings, showcasing its potential for data analysis and content creation.

Outlines

00:00

😀 Custom Data Ingestion with Chat GPT

The speaker demonstrates a method to feed personal data into Chat GPT, which then organizes and structures the documents. This allows for interactive querying of personal data, such as internship companies, dentist appointment dates, and parental travel plans. The process involves using a GitHub library called Lang Chain and an Open AI API key to create a vector store index that can be queried. The speaker also discusses the potential for summarizing Twitter feeds and web pages, and the possibility of creating personalized apps using this data.

05:01

📚 Setting Up a Personal Chat GPT Bot

The video script outlines the steps to set up a personal Chat GPT bot using the Lang Chain library and an Open AI API key. The process includes installing necessary packages, creating a file to store the API key, and writing a Python script to query the bot. The speaker emphasizes the importance of learning Python and uses the bot to answer a question about the language's relevance. The script involves using a text loader for data ingestion and a vector store index creator for data structurization. The speaker also touches on the topic of data privacy and the use of Azure Open AI as an alternative for potentially better privacy.

10:03

🔍 Merging Personal and External Data

The speaker explains how to merge personal data with external data using the LLM model to provide context about the outside world. This process involves modifying the query function to include an LLM model, which can enhance the bot's understanding of entities like companies and historical figures. The video also addresses privacy concerns related to using Open AI's API, noting that as of March 1st, Open AI will not use API-submitted data to train or improve their models. The speaker raises concerns about prompt injection hacking with plugins and suggests that writing code personally could be safer and more reliable.

15:04

🚀 Advanced Usage Cases of Chat GPT

The video concludes with advanced usage cases of Chat GPT, such as generating code for a partition function in quicksort, identifying bugs in code, and creating review summaries from large datasets. The speaker shares an example of how Azure Open AI was used to analyze customer reviews and generate summaries for car listings. They also demonstrate the bot's ability to recognize patterns in sequences and extend them, suggesting that the bot could potentially learn an individual's coding style from their samples.

Keywords

Chat GPT

Chat GPT, as mentioned in the video, refers to a chatbot model developed by OpenAI that can interact with users in a conversational manner. In the context of the video, it is used to demonstrate how personal custom data can be fed into the model to allow it to organize and structure documents, thereby enabling users to interact with their own data through natural language queries.

LangChain

LangChain is a GitHub library that facilitates the interaction between users and AI models like Chat GPT. It is highlighted in the video as a tool that simplifies the process of ingesting custom personal data into Chat GPT, allowing users to query their own data. The library does much of the heavy lifting in terms of data structurization and querying.

Personal Custom Data

Personal custom data refers to an individual's unique and specific information, which could include documents, schedules, notes, and more. The video emphasizes how Chat GPT can be used to organize and provide insights from this data after it has been fed into the system, thereby offering personalized experiences and responses.

Data Structurization

Data structurization is the process of organizing raw data into a structured format that can be easily interpreted and analyzed. In the video, the speaker discusses how Chat GPT, with the help of LangChain, can take unstructured personal data and make it accessible for querying and gaining insights.

Natural Language Queries

Natural language queries are questions or commands that are phrased in the form of everyday human language, rather than in a formal, computer-friendly format. The video demonstrates how users can ask Chat GPT questions using natural language and receive responses based on their personal custom data.

Microsoft

Microsoft is a leading technology company known for its software and hardware products. In the video, it is mentioned as one of the companies where the speaker had internships. The video also uses Microsoft as an example to illustrate how Chat GPT can provide information about companies when given personal custom data.

Vector Store Index Creator

A vector store index creator is a component used to analyze and vectorize data, essentially transforming it into a format that can be searched and queried efficiently. In the context of the video, it is part of the process of preparing personal data for interaction with Chat GPT.

API Key

An API key is a unique identifier used to authenticate a user, device, or application when interacting with an API (Application Programming Interface). In the video, the speaker mentions the need for an OpenAI API key to use their services, including the Chat GPT model.

Data Privacy

Data privacy refers to the appropriate handling, protection, and sharing of personal data to ensure it is not misused or accessed without permission. The video discusses concerns about data privacy when using OpenAI's API, noting that as of March 1st, OpenAI will not use data submitted via their API for training or improving their models.

Plugins

Plugins, in the context of the video, are add-ons or extensions that can enhance the functionality of a base application, such as Chat GPT. The video mentions the use of plugins for specific tasks, but also raises concerns about their authenticity and potential for prompt injection hacking.

Code Analysis

Code analysis involves examining source code to identify potential errors, bugs, or areas for improvement. In the video, the speaker demonstrates how Chat GPT can be used to analyze code, identify typos, and even write specific functions based on provided context.

Highlights

Discovered a method to integrate personal custom data with Chat GPT.

Chat GPT can organize and structure documents from personal data.

Interact with your data by talking to it and asking for information.

Example: Chat GPT describes companies of past internships using personal data.

Chat GPT can format information, such as company descriptions, in bullet points.

Personal data integration allows for new use cases, such as summarizing Twitter feeds.

Chat GPT can analyze and summarize web pages when provided with the content.

The LangChain GitHub Library simplifies the process of ingesting custom data.

Only 10 lines of code needed to set up a personal Chat GPT bot.

OpenAI API key is required and offers a free budget for basic usage.

The tool LangChain does the heavy lifting for data analysis and querying.

Custom data ingestion is called retrieval, which can be combined with LLM model data.

Privacy concerns are addressed with OpenAI's policy update from March 1st.

Azure OpenAI API ensures data remains within Microsoft and is encrypted.

Chat GPT can identify and fix bugs in code snippets provided to it.

Potential application: Generating customer review summaries from large databases.

Chat GPT can learn and mimic your coding style from provided code samples.