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Personal Assistants (Agents)
We use "personal assistant" here in a very broad sense. Personal assistants have a few characteristics:
- They can interact with the outside world
- They have knowledge of your data
- They remember your interactions
Really all of the functionality in LangChain is relevant for building a personal assistant. Highlighting specific parts:
- Agent Documentation (for interacting with the outside world)
- Index Documentation (for giving them knowledge of your data)
- Memory (for helping them remember interactions)
Specific examples of this include:
- AI Plugins: an implementation of an agent that is designed to be able to use all AI Plugins.
- Plug-and-PlAI (Plugins Database): an implementation of an agent that is designed to be able to use all AI Plugins retrieved from PlugNPlAI.
- Wikibase Agent: an implementation of an agent that is designed to interact with Wikibase.
- Sales GPT: This notebook demonstrates an implementation of a Context-Aware AI Sales agent.