ChatGPT Retrieval Plugin: Difference between revisions
(Created page with "==Background Information== The introduction of ChatGPT plugins by OpenAI has significantly expanded the capabilities of the popular chatbot. Plugins allow ChatGPT to interact with a variety of apps and services, enabling it to do more than just provide conversation. With this added functionality, ChatGPT can now perform tasks in the real world, such as ordering groceries or booking vacations. One particularly exciting plugin is the ChatGPT Retrieval Plugin, which all...") |
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Revision as of 19:41, 8 April 2023
Background Information
The introduction of ChatGPT plugins by OpenAI has significantly expanded the capabilities of the popular chatbot. Plugins allow ChatGPT to interact with a variety of apps and services, enabling it to do more than just provide conversation. With this added functionality, ChatGPT can now perform tasks in the real world, such as ordering groceries or booking vacations. One particularly exciting plugin is the ChatGPT Retrieval Plugin, which allows users to connect ChatGPT to a vector database like Weaviate in order to address its limitations related to long-term memory and provide responses based on internal documents and data.
ChatGPT Plugins
ChatGPT plugins act as a bridge between the chatbot and a range of third-party resources, enabling it to leverage these resources to perform tasks based on user conversations. These plugins can also help ChatGPT compensate for its own shortcomings, making it more adaptable and effective. The Retrieval Plugin, specifically, has the potential to be widely used, as it allows users to create customized versions of ChatGPT tailored to their own data.
Introduction to ChatGPT Retrieval Plugin
Connecting to a Vector Database
The ChatGPT Retrieval Plugin allows users to connect ChatGPT to an instance of a vector database. By doing so, any information stored in the connected vector database can be used to answer questions and provide responses based on the details stored in the database. Additionally, the vector database can be utilized as a long-term storage solution for ChatGPT, allowing it to persist and store portions of user conversations beyond the short-lived memory of a browser tab.
The retrieval plugin enables ChatGPT to accomplish tasks grounded in the context of knowledge stored in a connected vector database, such as Weaviate. The process consists of two steps: prompting ChatGPT with a question to craft a query that can be sent to the vector database, and then receiving relevant information and context from the database to formulate an appropriate response.
Plugin Functionality
The main functions of the ChatGPT Retrieval Plugin include:
- Connecting a vector database with proprietary data to ChatGPT, allowing it to answer specific questions based on that data
- Persisting personal documents and details to provide a personalized touch to ChatGPT's responses
- Storing conversations with ChatGPT in the attached vector database, enabling continued conversations across multiple sessions
This functionality allows for regular updates to content stored in connected vector databases, giving the model awareness of new information without the need for costly and time-consuming retraining of the large language model (LLM).
Weaviate Retrieval Plugin in Action
Using ChatGPT on Proprietary Company Documents
The Weaviate Retrieval Plugin can be used to create a customized version of ChatGPT trained on a company's internal documents, enabling it to act as a human resources chatbot. This can provide employees with easy access to information about onboarding processes, health benefits, and more.
Personalizing ChatGPT
The plugin also enables the customization of ChatGPT around personal details, such as information about friends or languages spoken by the user. By storing these details in Weaviate, ChatGPT can provide more tailored and personalized responses.
Helping ChatGPT Remember
One of the most powerful applications of the Weaviate Retrieval Plugin is its ability to store and reference previous conversations with ChatGPT. By persisting these conversations in Weaviate, ChatGPT can recall past interactions and provide more contextually relevant responses.
While still in its Alpha stage, the ChatGPT Retrieval Plugin offers a promising solution toenhancing ChatGPT's capabilities, overcoming its memory limitations, and creating a more personalized and engaging user experience. As the plugin continues to develop and becomes more accessible, it will likely play a significant role in the evolution of ChatGPT and its real-world applications. The potential use cases for this technology are vast, from customized customer service chatbots to more efficient knowledge management systems. By leveraging the power of vector databases like Weaviate, the ChatGPT Retrieval Plugin is poised to bring a new level of versatility and utility to the world of generative AI.