Engage with an intelligent RAG-powered conversational agent for complex information retrieval and analysis.
This advanced endpoint combines retrieval-augmented generation (RAG) with a conversational AI agent to provide detailed, context-aware responses based on your document collection. The agent can:
Key Features:
Common Use Cases:
The agent uses both vector search and knowledge graph capabilities to find and synthesize information, providing detailed, factual responses with proper attribution to source documents.
Current message to process
Default value of custom
allows full control over search settings.
Pre-configured search modes:
basic
: A simple semantic-based search.
advanced
: A more powerful hybrid search combining semantic and full-text.
custom
: Full control via search_settings
.
If filters
or limit
are provided alongside basic
or advanced
, they will override the default settings for that mode.
The search configuration object. If search_mode
is custom
, these settings are used as-is. For basic
or advanced
, these settings will override the default mode configuration.
Common overrides include filters
to narrow results and limit
to control how many results are returned.
Configuration for RAG generation
Optional custom prompt to override default
Include document titles in responses when available
ID of the conversation
ID of the conversation branch
List of messages (deprecated, use message instead)
Successful Response