Create an agentic chatbot profile - Fluid Topics - Latest

Use Agentic chatbot profiles for the Agentic Chatbot component.

To create an Agentic chatbot AI profile:

1. Select New profile, and select Agentic chatbot.

2. Enter or select:

   Field	Description
   Profile name	An AI profile name.
   Profile ID	A unique profile ID. The profile name and ID must be different from existing profiles.
   Provider	Choose one of Amazon Bedrock, Anthropic, Azure OpenAI, or OpenAI.
   Model	An LLM model from the selected provider. For Azure OpenAI, provide a host and model name. For Amazon Bedrock, provide a model name only. It is mandatory to select an agentic-ready model. For example, gpt-5 and up for OpenAI. Deployment of an agentic-ready model for Azure is only available worldwide yet. Consult the list of supported regions to make sure it is possible to use an agentic ready model in your region. The LLM model dropdown menu is not exhaustive. It is possible to enter any value, as long as it matches a valid model from the selected LLM provider. For example, for a refined model only known by the person configuring the profile. Use the Test connection button to check the profile configuration.
   Authentication	An API key from the provider.
   Agent instructions	Instructions for the agent, defining specific rules and the conversation scope. For optimal results, add specific instructions that are relevant to your context. Below are a few examples: - If the user is asking about product X, search for release notes X before answering. - Make sure you have properly identified the product the user is referring to. - Suggest to create a support ticket and provide a link to support.example.com if the user found a critical bug. - If the relevant documentation contains a topic named "Prerequisites" or "Before you begin", provide its content to the user.

3. Optional: Add inferred filters.

   Inferred filters allow the agent to use metadata filters for their queries. Administrators must enter a description for how and when the agent should use the metadata filter.

   If the agentic chatbot runs a query with filters and gets no response, it runs the query again.

4. Optional: Add cluster priority.

   Cluster priority uses metadata to indicate which variant of a document is the most relevant in a document cluster. For example: "version": "latest".

   • If the variant does not exist, the agentic chatbot ignores the rule.
   • Rules are applied in order.

5. Optional: Enter advanced settings.

6. Select Save.

Once created, ADMIN users can copy the agentic chatbot profile ID to use in AI features.

Agentic chatbot AI features include:

• The Agentic Chatbot component
• The Agentic retrieval-augmented generation (RAG) web service.