Knowledge Bases

Knowledge bases are collections of content sources that power AI agents with contextual information. They index content, generate vector embeddings, and provide intelligent retrieval capabilities.

What are Knowledge Bases?

A knowledge base is an organized collection of content sources that provides:

Interactive Chat — Ask questions and have conversations with your indexed content using built-in RAG
Vector Embeddings — AI-powered content representations for similarity matching
Agent Context — Provide agents with relevant information automatically
Content Triggers — Automatically run agents when content changes
Multi-Source Indexing — Combine multiple sources into one searchable collection

Knowledge bases act as the "memory" for your AI agents, allowing them to access and reason about your content intelligently.

Creating a Knowledge Base

Navigate to the Knowledge Bases page
Click Create Knowledge Base
Give it a name and optional description
Select one or more content sources to include
Configure retrieval settings (or keep the defaults)

You can add or remove sources at any time after creation.

Retrieval Settings

Each knowledge base has configurable retrieval settings that control how content is returned to agents:

Setting	Description	Default
Reranker Model	Model used to rerank search results for relevance	—
Top N	Maximum number of results returned from the initial vector search	20
Top K	Number of results kept after reranking	5
Score Threshold	Minimum relevance score (0–1) a result must meet to be included	0.0

Chat

Every knowledge base has a built-in chat interface that lets you have interactive conversations with your indexed content. The chat uses RAG under the hood — each message triggers a retrieval against the knowledge base, then feeds the relevant content to an LLM to generate a grounded response.

Starting a conversation

Open a knowledge base and switch to the Chat tab. Type a question and press Enter. A new conversation is created automatically, and the response streams back in real time.

Key capabilities:

Multiple conversations — Create as many conversations as you need. Each one maintains its own message history and can be renamed, archived, or deleted.
Model selection — Choose between Fast (Nova Lite), Balanced (Claude Sonnet), and Thorough (Claude Opus) tiers per message. You can also select a specific model from the full model catalogue.
Streaming responses — Responses stream token-by-token so you see results immediately.
Conversation management — Rename conversations for easy reference, archive old ones to keep the sidebar clean, or bulk-delete conversations you no longer need.
Regenerate responses — If a response isn't satisfactory, regenerate it to get a fresh answer.
Copy and feedback — Copy any message to your clipboard, and use the thumbs-up/down feedback buttons to rate response quality.

How it works

When you send a message, Seclai:

Retrieves relevant content chunks from the knowledge base using the configured retrieval settings (Top N, Top K, reranker, score threshold)
Constructs a RAG prompt with the retrieved context and your conversation history
Sends the prompt to the selected model and streams the response back

Conversations persist across sessions — come back any time to continue where you left off.

API Access

Knowledge bases can be managed programmatically via the Public API using your API key:

# List knowledge bases
curl "https://api.seclai.com/knowledge_bases?page=1&limit=20" \
  -H "X-API-Key: $SECLAI_API_KEY"

# Create a knowledge base
curl -X POST https://api.seclai.com/knowledge_bases \
  -H "X-API-Key: $SECLAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Tech News KB",
    "description": "Aggregated tech news sources",
    "source_ids": ["source-id-1", "source-id-2"]
  }'

# Get a knowledge base
curl "https://api.seclai.com/knowledge_bases/$KNOWLEDGE_BASE_ID" \
  -H "X-API-Key: $SECLAI_API_KEY"

# Update a knowledge base
curl -X PUT "https://api.seclai.com/knowledge_bases/$KNOWLEDGE_BASE_ID" \
  -H "X-API-Key: $SECLAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"name": "Renamed KB", "top_k": 10}'

# Delete a knowledge base
curl -X DELETE "https://api.seclai.com/knowledge_bases/$KNOWLEDGE_BASE_ID" \
  -H "X-API-Key: $SECLAI_API_KEY"

See API Examples for more examples in multiple languages.

MCP Tools

Knowledge base operations are available as MCP tools for AI coding assistants:

Tool	Description
`list_knowledge_bases`	List knowledge bases with pagination and sorting
`get_knowledge_base`	Get full details of a knowledge base
`create_knowledge_base`	Create a new knowledge base
`update_knowledge_base`	Update a knowledge base's configuration
`delete_knowledge_base`	Delete a knowledge base
`chat_with_knowledge_base`	Send a message and get a RAG-powered response
`list_kb_conversations`	List conversations for a knowledge base
`load_kb_chat_messages`	Load messages from a conversation
`rename_kb_conversation`	Rename a conversation
`delete_kb_conversation`	Delete a conversation

See MCP Server → Knowledge Base Tools for setup instructions.

Exporting

Export a knowledge base's full content — sources, metadata, and indexed items — as a downloadable JSON file.

UI: Open the knowledge base detail page and click the Export button. You'll see an estimate of the export size before confirming.
API: POST /authenticated/resource-exports with resource_type: "knowledge_base" and the knowledge base ID.
MCP: Use the create_resource_export tool with resource_type: "knowledge_base".

See Export Formats → Knowledge Base for the full file schema and available filter options.

Next Steps

Content Sources — Learn about content sources
Contents — Inspect, replace, and delete indexed content items
Agents — Build agents that use knowledge bases
API Examples — Code samples for the API
API Reference — Complete API documentation
MCP Server — Use knowledge base tools from AI coding assistants