import { Callout, Steps, Tabs, Cards } from "@/docs/components";

Knowledge Base

Enhance your agents with document-based knowledge using Retrieval-Augmented Generation (RAG).

<div className="status-badge status-stable">Stable</div>

Overview

The Knowledge Base allows you to:

Upload documents (PDF, TXT, MD, etc.)
Automatically chunk and index content
Query for relevant context
Connect to agents for enhanced responses

Quick Start

Dashboard

Navigate to Dashboard → Knowledge for the visual interface.

API

bash

# Upload a document
curl -X POST "https://elizacloud.ai/api/v1/documents/upload-file" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -F "[email protected]" \
  -F "characterId=agent_abc123"

</Tabs.Tab> <Tabs.Tab>

javascript

const formData = new FormData();
formData.append('files', file);
formData.append('characterId', 'agent_abc123');

const response = await fetch('https://elizacloud.ai/api/v1/documents/upload-file', {
method: 'POST',
headers: {
'Authorization': 'Bearer YOUR_API_KEY',
},
body: formData,
});

const result = await response.json();
console.log('Document uploaded:', result.id);

</Tabs.Tab> <Tabs.Tab>

python

import requests

with open('document.pdf', 'rb') as f:
    response = requests.post(
        'https://elizacloud.ai/api/v1/documents/upload-file',
        headers={'Authorization': 'Bearer YOUR_API_KEY'},
        files={'files': f},
        data={'characterId': 'agent_abc123'},
    )

result = response.json()
print(f'Document uploaded: {result["id"]}')

</Tabs.Tab> </Tabs>

Supported Formats

Format	Extension	Max Size
PDF	`.pdf`	5MB
Text	`.txt`	5MB
Markdown	`.md`	5MB
Word	`.docx`	5MB
JSON	`.json`	5MB
XML	`.xml`	5MB
YAML	`.yaml`	5MB
CSV	`.csv`	5MB

Note: Maximum 5MB per file and 5MB total per batch upload.

Upload Documents

<Steps> ### Prepare Your Documents Ensure documents are in a supported format and within size limits.

Upload via Dashboard or API

Use the Knowledge dashboard or the upload API endpoint.

Wait for Processing

Documents are stored as runtime documents and chunked for search.

Connect to Agent

Link the knowledge base to your agent for RAG.

</Steps>

Upload Response

json

{
  "id": "doc_abc123",
  "filename": "product-manual.pdf",
  "status": "processing",
  "chunks": null,
  "createdAt": "2024-01-15T10:30:00Z"
}

Check Processing Status

bash

curl -X GET "https://elizacloud.ai/api/v1/documents/check?documentId=doc_abc123" \
  -H "Authorization: Bearer YOUR_API_KEY"

json

{
  "id": "doc_abc123",
  "status": "completed",
  "chunks": 42,
  "tokensUsed": 15234
}

Query Knowledge

Search your knowledge base:

bash

curl -X POST "https://elizacloud.ai/api/v1/documents/query" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "How do I reset my password?",
    "agentId": "agent_abc123",
    "limit": 5
  }'

Response

json

{
  "results": [
    {
      "content": "To reset your password, navigate to Settings > Security > Reset Password...",
      "score": 0.92,
      "documentId": "doc_abc123",
      "metadata": {
        "page": 15,
        "section": "Account Settings"
      }
    },
    {
      "content": "Password requirements include at least 8 characters...",
      "score": 0.85,
      "documentId": "doc_abc123",
      "metadata": {
        "page": 16,
        "section": "Security"
      }
    }
  ]
}

Managing Documents

List Documents

bash

curl -X GET "https://elizacloud.ai/api/v1/documents?agentId=agent_abc123" \
  -H "Authorization: Bearer YOUR_API_KEY"

Get Document Details

bash

curl -X GET "https://elizacloud.ai/api/v1/documents/doc_abc123" \
  -H "Authorization: Bearer YOUR_API_KEY"

Delete Document

bash

curl -X DELETE "https://elizacloud.ai/api/v1/documents/doc_abc123" \
  -H "Authorization: Bearer YOUR_API_KEY"

RAG Configuration

Chunk Settings

Configure how documents are split:

Setting	Default	Description
`chunkSize`	1000	Characters per chunk
`chunkOverlap`	200	Overlap between chunks
`minChunkSize`	100	Minimum chunk size

Retrieval Settings

Configure query behavior:

Setting	Default	Description
`limit`	5	Number of results
`minScore`	0.7	Minimum relevance score
`rerank`	true	Re-rank results for relevance

Agent Integration

Automatic RAG

When knowledge is connected to an agent, relevant context is automatically retrieved:

javascript

// Agent with knowledge base
const response = await fetch("https://elizacloud.ai/api/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: "Bearer YOUR_API_KEY",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    model: "agent_abc123", // Agent with connected knowledge
    messages: [{ role: "user", content: "How do I reset my password?" }],
  }),
});

The agent automatically queries the knowledge base and includes relevant context in its response.

Manual RAG

Query knowledge and inject context manually:

javascript

// 1. Query knowledge
const knowledge = await fetch("https://elizacloud.ai/api/v1/documents/query", {
  method: "POST",
  headers: {
    Authorization: "Bearer YOUR_API_KEY",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    query: "password reset",
    limit: 3,
  }),
}).then((r) => r.json());

// 2. Include in chat
const context = knowledge.results.map((r) => r.content).join("\n\n");

const response = await fetch("https://elizacloud.ai/api/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: "Bearer YOUR_API_KEY",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    model: "gpt-4o",
    messages: [
      { role: "system", content: `Use this context:\n\n${context}` },
      { role: "user", content: "How do I reset my password?" },
    ],
  }),
});

Pricing

See Billing & Credits for current pricing on document uploads, embeddings, queries, and storage.

Best Practices

Quality Content — Use well-structured, accurate documents
Organize — Group related documents for better retrieval
Update Regularly — Keep knowledge current by refreshing documents
Test Queries — Verify retrieval quality before production

Next Steps

<Cards> <Cards.Card title="AI Agents" href="/docs/agents"> Create agents that use knowledge </Cards.Card> <Cards.Card title="Chat API" href="/docs/api"> Integrate RAG into your applications </Cards.Card> <Cards.Card title="Embeddings" href="/docs/api"> Learn about vector embeddings </Cards.Card> </Cards>