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A description of its purpose that will allow other AI agents to identify and collaborate with it.
Instructions indicating the context, the objectives of the AI agent, the data sources to query, the tasks to be performed, the examples to be used, the checks to be carried out, etc.
The use of a small or large multimodal generative model (
mainly called a Large Language Model or LLM) to interpret the instructions and generate the result.
The multimodal generative model will process an input that a human will produce in a conversational interaction.
Similarly, the generative model will produce an output that will be evaluated by the human in co-pilot mode. This output can also be shared with another AI agent.
The agent will rely on the short-term memory of the multimodal generative model and its long-term memory (this memory is persistent and can be used to personalize future interactions), as well as on planning, decision-making, and reasoning capabilities.
Access to tools, which may include access to enterprise applications and search engines. The multimodal generative model will decide which tools to use and in what sequence to achieve its objective.
Access to external data sources in addition to the training data of the model.
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To use an agent, you can either:
Type @ in the chat box or click the Invoke an Agent button and then select the agent you want to discuss with. Type your question and click the Start chatting Send button to start the conversation.
Select an agent from the provided list to open a new window where you can discuss with the selected agent. You can search any agents by name or category in the search field below the chat box.
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You can ask questions to several agents in the same conversation by selecting another agent.
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Discover our pre-built agents here. |
Manage previous conversations
You can view and even resume previous conversations by selecting a past conversation in the Discussions left panel.
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Tutorials
Coming soon!
What’s next?
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