rw-integrate-documents

★ 55

by runwayml · part of runwayml/skills

Help users add knowledge base documents to Runway Characters for domain-specific conversations

🔥🔥🔥✓ VerifiedFreeQuick setup

#automation #database #ai-video #git #customer-support

🧩 One of 7 skills in the runwayml/skills package — works on its own, and pairs well with its siblings.

Help users add knowledge base documents to Runway Characters for domain-specific conversations

Inspect the full instructions your agent will receiveExpand

This is the exact playbook injected into your agent when the skill activates — shown here so you can audit it before installing. You don't need to read it to use the skill.

by runwayml

Help users add knowledge base documents to Runway Characters for domain-specific conversations npx skills add https://github.com/runwayml/skills --skill rw-integrate-documents Download ZIP GitHub55

Integrate Documents (Knowledge Base)

PREREQUISITE: Run +rw-check-compatibility first. Run +rw-fetch-api-reference to load the latest API reference before integrating. +rw-setup-api-key — API credentials must be configured

USED BY: +rw-integrate-characters — Documents are linked to Avatars to give them domain-specific knowledge

Give your Characters access to domain-specific knowledge. Upload content that your Avatar can reference during conversations for accurate, contextual responses.

When to Use Documents

Use Case Example Content Customer support FAQs, product info, company policies, return procedures Quizzes & games Question banks, correct answers, scoring rules Education Course material, reference content, learning objectives Brand experiences Brand guidelines, messaging, product catalogs

Constraints

Each Avatar supports up to 50,000 tokens of knowledge
Supported formats: plain text and Markdown
More formats planned for future releases

Flow

The flow is: Create a Document → Link it to an Avatar

Step 1: Create a Document

Node.js

Copy & paste — that's it

import RunwayML from '@runwayml/sdk';

const client = new RunwayML();

const document = await client.documents.create({
 name: 'Product FAQ',
 content: `# Product FAQ

## What is your return policy?

We offer a 30-day return policy for all unused items in original packaging.

## How do I track my order?

Log in to your account and visit the Orders page. You'll find tracking information for all shipped orders.

## Do you offer international shipping?

Yes, we ship to over 50 countries. Shipping costs and delivery times vary by destination.`,
});

console.log('Document created:', document.id);

Python

Copy & paste — that's it

from runwayml import RunwayML

client = RunwayML()

document = client.documents.create(
 name='Product FAQ',
 content="""# Product FAQ

## What is your return policy?

We offer a 30-day return policy for all unused items in original packaging.

## How do I track my order?

Log in to your account and visit the Orders page.

## Do you offer international shipping?

Yes, we ship to over 50 countries.""",
)

print('Document created:', document.id)

Step 2: Link the Document to an Avatar

Update your Avatar to attach the document. This replaces any existing document attachments — pass all document IDs you want linked.

Node.js

Copy & paste — that's it

await client.avatars.update(avatarId, {
 documentIds: [document.id],
});

Python

Copy & paste — that's it

client.avatars.update(
 avatar_id,
 document_ids=[document.id],
)

Multiple Documents

You can link multiple documents to a single avatar (total must stay under 50,000 tokens):

Copy & paste — that's it

const faq = await client.documents.create({
 name: 'FAQ',
 content: '...',
});

const policies = await client.documents.create({
 name: 'Company Policies',
 content: '...',
});

await client.avatars.update(avatarId, {
 documentIds: [faq.id, policies.id],
});

Step 3: Start a Session

Once documents are linked, the Avatar automatically has access to the knowledge during conversations. Start a session as usual — no additional configuration needed:

Copy & paste — that's it

const session = await client.realtimeSessions.create({
 model: 'gwm1_avatars',
 avatar: {
 type: 'custom',
 avatarId: avatarId,
 },
});

Copy & paste — that's it

session = client.realtime_sessions.create(
 model='gwm1_avatars',
 avatar={
 'type': 'custom',
 'avatar_id': avatar_id,
 },
)

See +rw-integrate-characters for the full session creation, polling, and WebRTC flow.

Integration Patterns

Load Documents from Files

Read content from local files and create documents:

Copy & paste — that's it

import fs from 'fs';
import RunwayML from '@runwayml/sdk';

const client = new RunwayML();

// Read a local markdown file
const content = fs.readFileSync('./knowledge/product-faq.md', 'utf-8');

const document = await client.documents.create({
 name: 'Product FAQ',
 content,
});

Copy & paste — that's it

from pathlib import Path
from runwayml import RunwayML

client = RunwayML()

content = Path('./knowledge/product-faq.md').read_text()

document = client.documents.create(
 name='Product FAQ',
 content=content,
)

Dynamic Knowledge Updates

Update documents programmatically — useful for syncing with a CMS or database:

Copy & paste — that's it

// Example: API endpoint to update character knowledge
app.post('/api/avatar/update-knowledge', async (req, res) => {
 const { avatarId, documents } = req.body;

 // Create new documents
 const docIds = [];
 for (const doc of documents) {
 const created = await client.documents.create({
 name: doc.name,
 content: doc.content,
 });
 docIds.push(created.id);
 }

 // Link all documents to the avatar (replaces existing)
 await client.avatars.update(avatarId, {
 documentIds: docIds,
 });

 res.json({ success: true, documentCount: docIds.length });
});

Tips

Use Markdown for structured content — headings help the Avatar navigate the knowledge.
Be concise — stay well under the 50,000 token limit for best retrieval quality.
Organize by topic — multiple focused documents work better than one giant document.
Update regularly — keep knowledge current by re-creating documents when content changes.
Documents can also be managed via the Developer Portal UI.