interactor-agents

name	interactor-agents
description	Create LLM-powered AI assistants with tools and data sources through Interactor. Use when building conversational AI, chatbots, tool-calling assistants, or agents that need to query databases and external APIs.
author	Interactor Integration Guide

Interactor AI Agents Skill

Build LLM-powered assistants that can have conversations, use tools, and access your data sources.

When to Use

• Conversational AI: Building chat interfaces with AI assistants
• Tool-Calling Agents: Creating assistants that can invoke custom functions
• Data-Connected AI: Connecting AI to databases for natural language queries
• Customer Support Bots: Building support assistants with domain knowledge
• Internal Tools: Creating AI assistants for internal operations

Prerequisites

• Interactor authentication configured (see interactor-auth skill)
• Understanding of LLM concepts (prompts, tools, context)
• Webhook endpoint for tool callbacks (optional, for custom tools)
• Database with network access from Interactor (optional, for data sources)
• jq command-line tool (for bash examples)

Overview

The AI Agents system consists of:

Component	Description
Assistants	Configured AI agents with specific behaviors and capabilities
Rooms	Chat sessions between users and assistants
Messages	Individual messages in a conversation
Tools	Custom functions that assistants can invoke
Data Sources	Databases and APIs that assistants can query

---

Quick Start

The typical implementation flow:

1. Create an Assistant    → Define behavior with instructions and model config
         ↓
2. Register Tools         → (Optional) Add custom functions the assistant can call
         ↓
3. Connect Data Sources   → (Optional) Connect databases for natural language queries
         ↓
4. Create a Room          → Start a conversation session for a user
         ↓
5. Send/Receive Messages  → Exchange messages, handle tool calls
         ↓
6. Close Room             → End the conversation when complete

Minimal Example:

Prerequisites: This example requires jq for JSON parsing and a valid $TOKEN. See interactor-auth skill for authentication setup.

# Get your token first (see interactor-auth skill)
# export TOKEN="your_access_token_here"

# 1. Create assistant
ASSISTANT_ID=$(curl -s -X POST https://core.interactor.com/api/v1/agents/assistants \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"name": "helper", "title": "Helper", "instructions": "You are a helpful assistant."}' \
  | jq -r '.data.id')

echo "Created assistant: $ASSISTANT_ID"

# 2. Create room
ROOM_ID=$(curl -s -X POST https://core.interactor.com/api/v1/agents/$ASSISTANT_ID/rooms \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"namespace": "user_123"}' \
  | jq -r '.data.id')

echo "Created room: $ROOM_ID"

# 3. Send message
curl -X POST https://core.interactor.com/api/v1/agents/rooms/$ROOM_ID/messages \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"content": "Hello!", "role": "user"}'

---

Instructions

API Version Note: This skill documents the standard AI Agents API. Some operations (DELETE endpoints, advanced pagination options) may vary by Interactor version. Always verify endpoint availability against your specific API documentation or test in a development environment first.

Step 1: Create an Assistant

curl -X POST https://core.interactor.com/api/v1/agents/assistants \
  -H "Authorization: Bearer <token>" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "support_assistant",
    "title": "Support Assistant",
    "description": "Helps users with support questions",
    "model_config": {
      "provider": "openai",
      "model": "gpt-4o",
      "temperature": 0.7
    },
    "instructions": "You are a helpful support assistant. Be concise and friendly. Always try to resolve issues on the first response.",
    "enabled_tools": ["search_knowledge_base", "create_ticket"]
  }'

Response:

{
  "data": {
    "id": "asst_abc",
    "name": "support_assistant",
    "title": "Support Assistant",
    "description": "Helps users with support questions",
    "model_config": {
      "provider": "openai",
      "model": "gpt-4o",
      "temperature": 0.7
    },
    "enabled_tools": ["search_knowledge_base", "create_ticket"],
    "created_at": "2026-01-20T12:00:00Z"
  }
}

Assistant Configuration Options

Field	Type	Required	Description
name	string	Yes	Unique identifier (lowercase, underscores only)
title	string	Yes	Display name for users
description	string	No	What the assistant does
model_config.provider	string	No	openai (default: openai)
model_config.model	string	No	Model identifier (default: gpt-4o)
model_config.temperature	number	No	Response randomness 0.0-1.0 (default: 0.7)
instructions	string	Yes	System prompt defining behavior
enabled_tools	array	No	Tool names the assistant can use

List Assistants

curl https://core.interactor.com/api/v1/agents/assistants \
  -H "Authorization: Bearer <token>"

Get Assistant

curl https://core.interactor.com/api/v1/agents/assistants/asst_abc \
  -H "Authorization: Bearer <token>"

Update Assistant

curl -X PUT https://core.interactor.com/api/v1/agents/assistants/asst_abc \
  -H "Authorization: Bearer <token>" \
  -H "Content-Type: application/json" \
  -d '{
    "instructions": "Updated instructions with more detail...",
    "model_config": {
      "temperature": 0.5
    }
  }'

Delete Assistant

curl -X DELETE https://core.interactor.com/api/v1/agents/assistants/asst_abc \
  -H "Authorization: Bearer <token>"

---

Chat Rooms

Rooms are conversations between a user and an assistant.

Create a Room

curl -X POST https://core.interactor.com/api/v1/agents/asst_abc/rooms \
  -H "Authorization: Bearer <token>" \
  -H "Content-Type: application/json" \
  -d '{
    "namespace": "user_123",
    "metadata": {
      "user_name": "John",
      "context": "billing_question",
      "plan": "premium"
    }
  }'

Response:

{
  "data": {
    "id": "room_xyz",
    "assistant_id": "asst_abc",
    "namespace": "user_123",
    "status": "active",
    "metadata": {
      "user_name": "John",
      "context": "billing_question",
      "plan": "premium"
    },
    "created_at": "2026-01-20T12:00:00Z"
  }
}

List Rooms

curl https://core.interactor.com/api/v1/agents/rooms \
  -H "Authorization: Bearer <token>"

Query Parameters:

Parameter	Type	Description
namespace	string	Filter by namespace
assistant_id	string	Filter by assistant
status	string	active or closed

Example - List active rooms for a user:

curl "https://core.interactor.com/api/v1/agents/rooms?namespace=user_123&status=active" \
  -H "Authorization: Bearer <token>"

Get Room

curl https://core.interactor.com/api/v1/agents/rooms/room_xyz \
  -H "Authorization: Bearer <token>"

Response includes conversation history:

{
  "data": {
    "id": "room_xyz",
    "assistant_id": "asst_abc",
    "status": "active",
    "metadata": {...},
    "message_count": 5,
    "created_at": "2026-01-20T12:00:00Z",
    "last_message_at": "2026-01-20T12:05:00Z"
  }
}

Close Room

curl -X POST https://core.interactor.com/api/v1/agents/rooms/room_xyz/close \
  -H "Authorization: Bearer <token>"

---

Messages

Send a Message

curl -X POST https://core.interactor.com/api/v1/agents/rooms/room_xyz/messages \
  -H "Authorization: Bearer <token>" \
  -H "Content-Type: application/json" \
  -d '{
    "content": "How do I update my billing information?",
    "role": "user"
  }'

Response:

{
  "data": {
    "id": "msg_123",
    "role": "user",
    "content": "How do I update my billing information?",
    "created_at": "2026-01-20T12:00:00Z"
  }
}

The assistant's response is generated asynchronously. Use streaming or webhooks to receive it.

List Messages

curl https://core.interactor.com/api/v1/agents/rooms/room_xyz/messages \
  -H "Authorization: Bearer <token>"

Query Parameters:

Parameter	Type	Description
limit	integer	Max messages to return (default: 50, max: 100)
cursor	string	Opaque cursor for pagination (from next_cursor)
order	string	Sort order: asc (oldest first) or desc (newest first, default)

Response:

{
  "data": {
    "messages": [
      {
        "id": "msg_123",
        "role": "user",
        "content": "How do I update my billing information?",
        "created_at": "2026-01-20T12:00:00Z"
      },
      {
        "id": "msg_124",
        "role": "assistant",
        "content": "To update your billing information, go to Settings > Billing...",
        "tool_calls": [],
        "created_at": "2026-01-20T12:00:05Z"
      }
    ],
    "has_more": true,
    "next_cursor": 
  

Pagination Pattern

The API uses cursor-based pagination for stable, consistent results:

// Fetch all messages in a room
async function getAllMessages(roomId: string): Promise<Message[]> {
  const allMessages: Message[] = [];
  let cursor: string | undefined;

  do {
    const params = new URLSearchParams({ limit: '100' });
    if (cursor) params.set('cursor', cursor);

    const response = await fetch(
      `https://core.interactor.com/api/v1/agents/rooms/${roomId}/messages?${params}`,
      { headers: { 'Authorization': `Bearer ${token}` } }
    );

    const { data } = await response.json();
    allMessages.push(...data.messages);
    cursor = data.has_more ? data.next_cursor : undefined;

  } while (cursor);

  return allMessages;
}

Pagination Best Practices:

• Always use next_cursor from the response; never construct cursors manually
• Cursors are opaque and may change format between API versions
• Cursors expire after 24 hours; for long-running jobs, re-fetch from the beginning
• Results are stable within a cursor session (new messages won't appear mid-pagination)

Message Roles

Role	Description
user	Message from the user
assistant	Response from the AI assistant
system	System message (internal use)
tool	Tool execution result

Real-Time Responses

Assistant responses are generated asynchronously after you send a user message. To receive responses in real-time, you have three options:

API Note: Verify streaming endpoint availability with your Interactor version. The SSE endpoint pattern shown below (/rooms/{id}/stream) is a common convention but may differ in your deployment. Check your API documentation or contact support.

Option 1: Server-Sent Events (SSE)

Subscribe to room events for streaming tokens as they're generated.

Note: The standard browser EventSource API doesn't support custom headers. Use the eventsource npm package for Node.js, or pass the token as a query parameter if your API supports it.

Node.js with eventsource package:

import EventSource from 'eventsource';

// Node.js: Use eventsource package which supports headers
const eventSource = new EventSource(
  `https://core.interactor.com/api/v1/agents/rooms/${roomId}/stream`,
  { headers: { 'Authorization': `Bearer ${token}` } }
);

eventSource.onmessage = (event) => {
  const data = JSON.parse(event.data);

  if (data.type === 'token') {
    // Append token to response
    process.stdout.write(data.token);
  } else if (data.type === 'message_complete') {
    // Full message available
    console.log('\nComplete:', data.message);
  } else if (data.type === 'tool_call') {
    // Tool is being invoked
    console.log('Tool call:', data.tool_name);
  }
};

eventSource.onerror = (error) => {
  console.(, error);
  eventSource.();
};

Browser with Fetch API (alternative):

// Browser: Use fetch with ReadableStream for SSE with auth
async function streamMessages(roomId: string, token: string) {
  const response = await fetch(
    `https://core.interactor.com/api/v1/agents/rooms/${roomId}/stream`,
    { headers: { 'Authorization': `Bearer ${token}` } }
  );

  const reader = response.body?.getReader();
  const decoder = new TextDecoder();

  while (reader) {
    const { done, value } = await reader.read();
    if (done) break;

    const chunk = decoder.decode(value);
    // Parse SSE format: "data: {...}\n\n"
    const lines = chunk.split('\n');
    for (const line of lines) {
      if (line.startsWith('data: ')) {
        const data = JSON.parse(line.slice(6));
        console.log('Received:', data);
      }
    }
  }
}

Option 2: Webhooks

Configure a webhook to receive agent.room.message events at your endpoint. See the interactor-webhooks skill for complete webhook setup and payload handling.

Option 3: Polling (Not Recommended)

Poll the messages endpoint for new messages. Use only as a fallback:

async function pollForResponse(roomId: string, lastKnownMessageId: string) {
  const maxAttempts = 30;
  const delayMs = 1000;

  for (let i = 0; i < maxAttempts; i++) {
    // Fetch recent messages and check for new assistant response
    const { messages } = await getMessages(roomId, { limit: 10 });
    const newMessages = messages.filter(m =>
      m.role === 'assistant' && m.id !== lastKnownMessageId
    );

    if (newMessages.length > 0) return newMessages[0];
    await new Promise(resolve => setTimeout(resolve, delayMs));
  }

  throw new Error('Response timeout');
}

---

Tools

Tools are custom functions that assistants can invoke during conversations.

Register a Tool

curl -X POST https://core.interactor.com/api/v1/tools \
  -H "Authorization: Bearer <token>" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "search_products",
    "description": "Search the product catalog by query and optional category",
    "parameters": {
      "type": "object",
      "properties": {
        "query": {
          "type": "string",
          "description": "Search query for product names or descriptions"
        },
        "category": {
          "type": "string",
          "description": "Product category to filter by",
          "enum": ["electronics", "clothing", "home", "sports"]
        },
        "max_results": {
          "type": "integer",
          "description": "Maximum number of results to return",
          "default": 10
        }
      },
      "required": ["query"]
    },
    "callback_url": "https://yourapp.com/api/tools/search_products",
    "callback_secret": "your_webhook_secret_here"
  }'

Response:

{
  "data": {
    "id": "tool_abc",
    "name": "search_products",
    "description": "Search the product catalog by query and optional category",
    "created_at": "2026-01-20T12:00:00Z"
  }
}

Tool Callback

When the assistant invokes your tool, Interactor POSTs to your callback_url:

Request Headers:

POST /api/tools/search_products HTTP/1.1
Content-Type: application/json
X-Interactor-Signature: sha256=abc123def456...
X-Interactor-Timestamp: 2026-01-20T12:00:00Z

Request Body:

{
  "tool_name": "search_products",
  "parameters": {
    "query": "laptop",
    "category": "electronics",
    "max_results": 5
  },
  "execution_id": "exec_xyz",
  "room_id": "room_xyz",
  "assistant_id": "asst_abc",
  "timestamp": "2026-01-20T12:00:00Z"
}

Security Note: The X-Interactor-Signature header contains an HMAC-SHA256 signature of the raw request body, signed with your callback_secret. Always verify this signature before processing the request.

Your response:

{
  "result": {
    "products": [
      {
        "id": "prod_1",
        "name": "MacBook Pro 14\"",
        "price": 1999,
        "in_stock": true
      },
      {
        "id": "prod_2",
        "name": "Dell XPS 15",
        "price": 1499,
        "in_stock": true
      }
    ],
    "total_count": 2
  }
}

The assistant will use this result to formulate its response.

Verify Tool Callback Signature

Tool callbacks include three security headers for verification:

Header	Description
X-Interactor-Signature	HMAC-SHA256 signature of the raw request body
X-Interactor-Timestamp	ISO 8601 timestamp when request was signed
X-Interactor-Request-Id	Unique request ID (same as execution_id in body)

Security Requirements:

1. Verify HMAC signature matches
2. Check timestamp is within acceptable window (recommended: 300 seconds)
3. Use execution_id as idempotency key to prevent replay attacks

TypeScript (with replay protection):

import crypto from 'crypto';

interface VerificationResult {
  valid: boolean;
  error?: string;
}

function verifyToolCallback(
  payload: string,
  signature: string,
  timestamp: string,
  secret: string,
  maxAgeSeconds: number = 300
): VerificationResult {
  // 1. Check timestamp is not too old (replay protection)
  const requestTime = Date.parse(timestamp);
  const now = Date.now();
  const ageSeconds = Math.abs(now - requestTime) / 1000;

  if (ageSeconds > maxAgeSeconds) {
    return { valid: false, error: `Request too old: ${ageSeconds}s > ${maxAgeSeconds}s` };
  }

  // 2. Verify HMAC signature
  const expected = crypto
    .createHmac('sha256', secret)
    .update(payload)
    .digest('hex');

   signatureValid = crypto.(
    .(signature.(, )),
    .(expected)
  );

   (!signatureValid) {
     { : , :  };
  }

   { :  };
}


app.(, express.({ :  }),  (req, res) => {
   signature = req.[]  ;
   timestamp = req.[]  ;
   requestId = req.[]  ;
   payload = req..();

  
   verification = (
    payload,
    signature,
    timestamp,
    process..!
  );

   (!verification.) {
    .(, verification., { requestId });
     res.().({ : verification. });
  }

   data = .(payload);

  
   alreadyProcessed =  (data.);
   (alreadyProcessed) {
    .(, data.);
     res.().({ :  (data.) });
  }

  
   result =  (data.);

  
   (data., result,  *  *  * );

  res.({ result });
});


  (): <> {
  
   ; 
}

  (): <> {
  
   ; 
}

  (): <> {
  
  
}

Python (with replay protection):

import os
import hmac
import hashlib
import time
from datetime import datetime
from flask import Flask, request, jsonify

app = Flask(__name__)

def verify_tool_callback(
    payload: bytes,
    signature: str,
    timestamp: str,
    secret: str,
    max_age_seconds: int = 300
) -> tuple[bool, str | None]:
    """
    Verify callback with replay protection.
    Returns (is_valid, error_message).
    """
    # 1. Check timestamp is not too old
    try:
        request_time = datetime.fromisoformat(timestamp.replace('Z', '+00:00'))
        age_seconds = abs((datetime.now(request_time.tzinfo) - request_time).total_seconds())

        if age_seconds > max_age_seconds:
            return False, f'Request too old: {age_seconds}s > {max_age_seconds}s'
    except ValueError as e:
        return False, f'Invalid timestamp: {e}'

    # 2. Verify HMAC signature
    expected = hmac.new(
        secret.encode(),
        payload,
        hashlib.sha256
    ).hexdigest()

    signature_value = signature.replace('sha256=', '')
    if not hmac.compare_digest(signature_value, expected):
         , 

     , 


 ():
    signature = request.headers.get(, )
    timestamp = request.headers.get(, )
    request_id = request.headers.get(, )
    payload = request.get_data()

    
    is_valid, error = verify_tool_callback(
        payload,
        signature,
        timestamp,
        os.environ[]
    )

      is_valid:
        app.logger.error(, extra={: request_id})
         jsonify({: error}), 

    data = request.get_json()

    
     is_duplicate_execution(data[]):
         jsonify({: get_cached_result(data[])}), 

    
    result = search_products(data[])

    
    store_execution_result(data[], result)

     jsonify({: result})

List Tools

curl https://core.interactor.com/api/v1/tools \
  -H "Authorization: Bearer <token>"

Get Tool

curl https://core.interactor.com/api/v1/tools/tool_abc \
  -H "Authorization: Bearer <token>"

Update Tool

curl -X PUT https://core.interactor.com/api/v1/tools/tool_abc \
  -H "Authorization: Bearer <token>" \
  -H "Content-Type: application/json" \
  -d '{
    "description": "Updated description with more detail",
    "callback_url": "https://yourapp.com/api/v2/tools/search_products"
  }'

Delete Tool

curl -X DELETE https://core.interactor.com/api/v1/tools/tool_abc \
  -H "Authorization: Bearer <token>"

---

Webhook & Callback Contract

This section defines the canonical contract for all Interactor webhooks and tool callbacks.

Request Headers

All webhook/callback requests include these headers:

Header	Format	Description
X-Interactor-Signature	sha256=<hex>	HMAC-SHA256 of raw body
X-Interactor-Timestamp	ISO 8601	When request was signed
X-Interactor-Request-Id	exec_<id>	Unique request identifier
Content-Type	application/json	Always JSON

Response Requirements

Status	Meaning	Interactor Behavior
200	Success	Process result, no retry
201	Created	Same as 200
202	Accepted	Async processing (see below)
400	Bad Request	Permanent failure, no retry
401	Unauthorized	Permanent failure, no retry
404	Not Found	Permanent failure, no retry
429	Rate Limited	Retry with backoff
500	Server Error	Retry with backoff
502-504	Gateway Error	Retry with backoff

Expected Response Format:

{
  "result": { ... }
}

Timeout Policy

Operation	Timeout	Behavior on Timeout
Tool callback	30 seconds	Retry with backoff
Webhook delivery	10 seconds	Retry with backoff
Async callback (202)	5 minutes	Poll for completion

Important: Your callback must respond within the timeout window. For long-running operations, return 202 Accepted with a status URL, and Interactor will poll for completion.

Retry Policy

When a callback fails (5xx, timeout, network error), Interactor retries with exponential backoff:

Attempt	Delay	Cumulative Time
1	Immediate	0s
2	1s	1s
3	2s	3s
4	4s	7s
5	8s	15s
6 (final)	16s	31s

After 6 failed attempts:

• Request is marked as permanently failed
• tool.callback.failed event is emitted (if webhooks configured)
• Assistant receives an error and may retry or inform the user

Idempotency Requirements

You MUST implement idempotent handlers. Use execution_id as the idempotency key.

Idempotency Implementation:

// Redis-based idempotency example
import Redis from 'ioredis';
const redis = new Redis();

const IDEMPOTENCY_TTL = 7 * 24 * 60 * 60; // 7 days

async function handleWithIdempotency(
  executionId: string,
  handler: () => Promise<any>
): Promise<{ result: any; isDuplicate: boolean }> {
  const cacheKey = `idempotency:${executionId}`;

  // Check for existing result
  const cached = await redis.get(cacheKey);
  if (cached) {
    return { result: JSON.parse(cached), isDuplicate: true };
  }

  // Execute handler
  const result = await handler();

  // Store result with TTL
  await redis.setex(cacheKey, IDEMPOTENCY_TTL, JSON.(result));

   { result, :  };
}

Recommended idempotency window: 7 days minimum. This covers retry scenarios and delayed processing.

Dead Letter Handling

If all retries are exhausted:

1. Interactor emits a tool.callback.dead_letter event (if webhooks configured)
2. The failed request is logged in your Interactor dashboard
3. You can manually retry from the dashboard or via API

Dead Letter Event Payload:

{
  "event": "tool.callback.dead_letter",
  "data": {
    "execution_id": "exec_xyz",
    "tool_name": "search_products",
    "assistant_id": "asst_abc",
    "room_id": "room_xyz",
    "attempts": 6,
    "last_error": "Connection timeout",
    "first_attempt_at": "2026-01-20T12:00:00Z",
    "last_attempt_at": "2026-01-20T12:00:31Z"
  }
}

---

Streaming Contract

This section defines the canonical contract for Server-Sent Events (SSE) streaming.

Event Types

The streaming endpoint emits these event types:

Event Type	Description	When Emitted
token	Incremental response token	During response generation
message_complete	Full message available	When response finishes
tool_call	Tool is being invoked	When assistant calls a tool
tool_result	Tool execution completed	After tool callback returns
error	Error occurred	On any error
done	Stream complete	End of stream

Event Schemas

token Event:

{
  "type": "token",
  "token": "Hello",
  "index": 0,
  "message_id": "msg_123"
}

Field	Type	Description
type	string	Always "token"
token	string	The text token (1-4 characters typically)
index	integer	Token position in the response
message_id	string	ID of the message being generated

message_complete Event:

{
  "type": "message_complete",
  "message": {
    "id": "msg_123",
    "role": "assistant",
    "content": "Hello! How can I help you today?",
    "tool_calls": [],
    "created_at": "2026-01-20T12:00:05Z"
  }
}

tool_call Event:

{
  "type": "tool_call",
  "tool_call": {
    "id": "tc_456",
    "tool_name": "search_products",
    "parameters": {
      "query": "laptop"
    },
    "status": "pending"
  },
  "message_id": "msg_123"
}

tool_result Event:

{
  "type": "tool_result",
  "tool_call": {
    "id": "tc_456",
    "tool_name": "search_products",
    "status": "completed",
    "result": {
      "products": [...]
    }
  },
  "message_id": "msg_123"
}

error Event:

{
  "type": "error",
  "error": {
    "code": "tool_callback_failed",
    "message": "Tool callback timed out",
    "tool_call_id": "tc_456"
  },
  "message_id": "msg_123"
}

done Event:

{
  "type": "done",
  "message_id": "msg_123"
}

SSE Wire Format

Events follow the standard SSE format:

event: token
data: {"type":"token","token":"Hello","index":0,"message_id":"msg_123"}

event: token
data: {"type":"token","token":" world","index":1,"message_id":"msg_123"}

event: message_complete
data: {"type":"message_complete","message":{...}}

event: done
data: {"type":"done","message_id":"msg_123"}

Important: Each event has an event: line followed by a data: line, then a blank line.

Authentication for Streaming

The standard browser EventSource API does not support custom headers. Use one of these approaches:

Option 1: Short-Lived Token in Query Parameter (Recommended for Browsers)

// 1. Get a short-lived streaming token (valid 60 seconds)
const { streaming_token } = await fetch('/api/v1/agents/rooms/{room_id}/stream-token', {
  method: 'POST',
  headers: { 'Authorization': `Bearer ${accessToken}` }
}).then(r => r.json());

// 2. Connect with token in query string
const eventSource = new EventSource(
  `https://core.interactor.com/api/v1/agents/rooms/${roomId}/stream?token=${streaming_token}`
);

Option 2: Fetch API with ReadableStream

async function streamWithAuth(roomId: string, accessToken: string) {
  const response = await fetch(
    `https://core.interactor.com/api/v1/agents/rooms/${roomId}/stream`,
    {
      headers: { 'Authorization': `Bearer ${accessToken}` }
    }
  );

  const reader = response.body?.getReader();
  const decoder = new TextDecoder();
  let buffer = '';

  while (reader) {
    const { done, value } = await reader.read();
    if (done) break;

    buffer += decoder.decode(value, { stream: true });

    // Parse complete events from buffer
    const events = buffer.split('\n\n');
    buffer = events.pop() || ''; // Keep incomplete event in buffer

    for (const eventBlock of events) {
      if (!eventBlock.trim()) continue;

      const lines = eventBlock.split();
       eventType = ;
       data = ;

       ( line  lines) {
         (line.()) {
          eventType = line.();
        }   (line.()) {
          data = line.();
        }
      }

       (data) {
         parsed = .(data);
        (eventType, parsed);
      }
    }
  }
}

 () {
   (data.) {
     :
      process..(data.);
      ;
     :
      .(, data..);
      ;
     :
      .(, data..);
      ;
     :
      .(, data..);
      ;
     :
      .();
      ;
  }
}

Option 3: Node.js with eventsource Package

import EventSource from 'eventsource';

const eventSource = new EventSource(
  `https://core.interactor.com/api/v1/agents/rooms/${roomId}/stream`,
  { headers: { 'Authorization': `Bearer ${accessToken}` } }
);

eventSource.addEventListener('token', (e) => {
  const data = JSON.parse(e.data);
  process.stdout.write(data.token);
});

eventSource.addEventListener('error', (e) => {
  console.error('Stream error:', e);
  eventSource.close();
});

Reconnection Handling

If the stream disconnects, reconnect with a Last-Event-ID header (if supported):

let lastEventId: string | null = null;

eventSource.onmessage = (e) => {
  lastEventId = e.lastEventId;
  // ... handle event
};

eventSource.onerror = () => {
  eventSource.close();

  // Reconnect after delay
  setTimeout(() => {
    const newSource = new EventSource(
      `${streamUrl}?last_event_id=${lastEventId}`,
      { headers: { 'Authorization': `Bearer ${token}` } }
    );
    // ... set up handlers
  }, 1000);
};

---

Data Sources

Connect databases and APIs that assistants can query directly using natural language.

Register a Data Source

curl -X POST https://core.interactor.com/api/v1/data-sources \
  -H "Authorization: Bearer <token>" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "sales_database",
    "type": "postgresql",
    "connection": {
      "host": "db.yourcompany.com",
      "port": 5432,
      "database": "sales",
      "username": "readonly_user",
      "password": "secure_password"
    },
    "description": "Sales and customer data including orders, products, and customer information"
  }'

Response:

{
  "data": {
    "id": "ds_abc",
    "name": "sales_database",
    "type": "postgresql",
    "status": "connected",
    "schema_status": "extracting",
    "created_at": "2026-01-20T12:00:00Z"
  }
}

Interactor automatically extracts the database schema for the assistant to understand.

Supported Data Source Types

Type	Description
postgresql	PostgreSQL database
mysql	MySQL database
mssql	Microsoft SQL Server
mongodb	MongoDB database
rest_api	REST API endpoint

List Data Sources

curl https://core.interactor.com/api/v1/data-sources \
  -H "Authorization: Bearer <token>"

Get Data Source

curl https://core.interactor.com/api/v1/data-sources/ds_abc \
  -H "Authorization: Bearer <token>"

Response includes schema information:

{
  "data": {
    "id": "ds_abc",
    "name": "sales_database",
    "type": "postgresql",
    "status": "connected",
    "schema_status": "ready",
    "tables": [
      {
        "name": "customers",
        "columns": [
          {"name": "id", "type": "uuid", "nullable": false},
          {"name": "email", "type": "varchar",  
               
               
        
      
      
         
         ...
      
    
  

Update Data Source

curl -X PUT https://core.interactor.com/api/v1/data-sources/ds_abc \
  -H "Authorization: Bearer <token>" \
  -H "Content-Type: application/json" \
  -d '{
    "description": "Updated description with more context"
  }'

Delete Data Source

curl -X DELETE https://core.interactor.com/api/v1/data-sources/ds_abc \
  -H "Authorization: Bearer <token>"

Refresh Schema

Re-extract the schema if your database structure changed:

curl -X POST https://core.interactor.com/api/v1/data-sources/ds_abc/refresh-schema \
  -H "Authorization: Bearer <token>"

Execute Query

Run a query directly against the data source:

curl -X POST https://core.interactor.com/api/v1/data-sources/ds_abc/query \
  -H "Authorization: Bearer <token>" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "SELECT * FROM customers WHERE created_at > $1 LIMIT 10",
    "parameters": ["2026-01-01"]
  }'

Response:

{
  "data": {
    "columns": ["id", "email", "name", "created_at"],
    "rows": [
      ["uuid-1", "[e-mail]", "John Doe", "2026-01-15T10:00:00Z"],
      ["uuid-2", "[e-mail]", "Jane Smith", "2026-01-16T11:00:00Z"]
    ],
    "row_count": 2,
    "execution_time_ms": 45
  }
}

Semantic Mappings

Add synonyms and descriptions to help the assistant understand your schema better:

curl -X PATCH https://core.interactor.com/api/v1/data-sources/ds_abc/semantic-mappings \
  -H "Authorization: Bearer <token>" \
  -H "Content-Type: application/json" \
  -d '{
    "mappings": {
      "customers": {
        "description": "Customer accounts and profiles",
        "synonyms": ["users", "clients", "accounts", "members"]
      },
      "customers.created_at": {
        "description": "When the customer signed up",
        "synonyms": ["signup date", "registration date", "joined date"]
      },
      "orders": {
        "description": "Customer purchase orders",
        "synonyms": ["purchases", "transactions", "sales"]
      },
      "orders.total_amount": {
        "description": "Total order value in USD",
        "synonyms": ["order total", "purchase amount", "sale value"]
      }
    }
  }'

This helps the assistant translate natural language questions like:

• "How many users signed up last month?" → SELECT COUNT(*) FROM customers WHERE created_at >= '2026-01-01'
• "What's the total sales this week?" → SELECT SUM(total_amount) FROM orders WHERE created_at >= '2026-01-14'

---

Knowledge Base Search

Search for external services that assistants can connect to:

Search Services

curl -X POST https://core.interactor.com/api/v1/knowledge-base/services/search \
  -H "Authorization: Bearer <token>" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "calendar scheduling",
    "limit": 5
  }'

Response:

{
  "data": {
    "services": [
      {
        "id": "google_calendar",
        "name": "Google Calendar",
        "description": "Calendar and scheduling service",
        "auth_type": "oauth2",
        "capabilities": ["create_event", "list_events", "update_event", "delete_event"]
      },
      {
        "id": "microsoft_calendar",
        "name": "Microsoft Outlook Calendar",
        "description": "Microsoft 365 calendar service",
        "auth_type": "oauth2",
        "capabilities"   
      
    
  

Lookup Service

curl -X POST https://core.interactor.com/api/v1/knowledge-base/services/lookup \
  -H "Authorization: Bearer <token>" \
  -H "Content-Type: application/json" \
  -d '{"service_id": "google_calendar"}'

Get Service Details

curl https://core.interactor.com/api/v1/knowledge-base/services/google_calendar \
  -H "Authorization: Bearer <token>"

Get Service OAuth Config

curl https://core.interactor.com/api/v1/knowledge-base/services/google_calendar/oauth \
  -H "Authorization: Bearer <token>"

---

Complete Implementation Example

TypeScript Implementation

import { InteractorClient } from './interactor-client';

export class AgentManager {
  private client: InteractorClient;

  constructor(client: InteractorClient) {
    this.client = client;
  }

  // ============ Assistants ============

  async createAssistant(config: {
    name: string;
    title: string;
    description?: string;
    instructions: string;
    modelConfig?: {
      provider?: 'openai';
      model?: string;
      temperature?: number;
    };
    enabledTools?: string[];
  }): Promise<Assistant> {
    return this.client.request('POST', '/agents/assistants', {
      name: config.name,
      title: config.title,
      description: config.description,
      : config.,
      : config.,
      : config.
    });
  }

   (): <[]> {
     result =  ..<{ : [] }>(
      ,
      
    );
     result.;
  }

   (: ): <> {
     ..(, );
  }

   (: , : <>): <> {
     ..(, , updates);
  }

   (: ): <> {
     ..(, );
  }

  

   (
    : ,
    : ,
    ?: <, >
  ): <> {
     ..(, , {
      : ,
      metadata
    });
  }

   (?: {
    ?: ;
    ?: ;
    ?:  | ;
  }): <[]> {
     params =  ();
     (filters?.) params.(, );
     (filters?.) params.(, filters.);
     (filters?.) params.(, filters.);

     query = params.();
     result =  ..<{ : [] }>(
      ,
      
    );
     result.;
  }

   (: ): <> {
     ..(, );
  }

   (: ): <> {
     ..(, );
  }

  

   (: , : ): <> {
     ..(, , {
      content,
      : 
    });
  }

   (: , ?: {
    ?: ;
    ?: ;
  }): <{ : []; :  }> {
     params =  ();
     (options?.) params.(, options..());
     (options?.) params.(, options.);

     query = params.();
     ..(
      ,
      
    );
  }

  

   (: {
    : ;
    : ;
    : <, >;
    : ;
    : ;
  }): <> {
     ..(, , {
      : tool.,
      : tool.,
      : tool.,
      : tool.,
      : tool.
    });
  }

   (): <[]> {
     result =  ..<{ : [] }>(, );
     result.;
  }

   (: ): <> {
     ..(, );
  }

  

   (: {
    : ;
    :  |  |  |  | ;
    : <, >;
    ?: ;
  }): <> {
     ..(, , config);
  }

   (): <[]> {
     result =  ..<{ : [] }>(
      ,
      
    );
     result.;
  }

   (: ): <> {
     ..(, );
  }

   (: ): <> {
     ..(, );
  }

   (
    : ,
    : ,
    ?: []
  ): <> {
     ..(, , {
      query,
      parameters
    });
  }

   (
    : ,
    : <, { ?: ; ?: [] }>
  ): <> {
     ..(, , {
      mappings
    });
  }
}


  {
  : ;
  : ;
  : ;
  ?: ;
  : {
    : ;
    : ;
    : ;
  };
  : [];
  : ;
}

  {
  ?: ;
  ?: ;
  ?: ;
  ?: {
    ?: ;
    ?: ;
    ?: ;
  };
  ?: [];
}

  {
  : ;
  : ;
  : ;
  :  | ;
  ?: <, >;
  : ;
  : ;
  ?: ;
}

  {
  : ;
  :  |  |  | ;
  : ;
  ?: [];
  : ;
}

  {
  : ;
  : ;
  : <, >;
  ?: ;
}

  {
  : ;
  : ;
  : ;
  : <, >;
  : ;
  : ;
}

  {
  : ;
  : ;
  : ;
  :  |  | ;
  :  |  | ;
  ?: [];
  : ;
}

  {
  : ;
  : [];
}

  {
  : ;
  : ;
  : ;
}

  {
  : [];
  : [][];
  : ;
  : ;
}

Chat Interface Example

// Example: Building a chat interface
async function chat(userId: string, assistantId: string) {
  const agentManager = new AgentManager(interactorClient);

  // Get or create a room for this user
  let rooms = await agentManager.listRooms({
    userId,
    assistantId,
    status: 'active'
  });

  let room: Room;
  if (rooms.length > 0) {
    room = rooms[0];
  } else {
    room = await agentManager.createRoom(assistantId, userId, {
      user_name: 'John',
      context: 'general_support'
    });
  }

  // Send a message
  await agentManager.sendMessage(room.id, 'How do I reset my password?');

  // Wait for response (in real app, use streaming)
  await new Promise(resolve => setTimeout(resolve, 3000));

  // Get messages
  const { messages } = await agentManager.getMessages(room.);

  
   ( msg  messages) {
    .();
  }
}

---

Webhook Events

Subscribe to agent events for real-time updates:

Event	Description
agent.room.message	New message in a room
agent.room.closed	Room was closed

Note: Additional events like agent.tool.invoked may be available depending on your Interactor version. Check the interactor-webhooks skill or your API documentation for the complete list of available events.

See interactor-webhooks skill for webhook setup and SSE streaming.

---

Best Practices

DO

• Keep instructions focused - Clear, specific instructions produce better results
• Use semantic mappings - Help assistants understand your data schema
• Secure tool callbacks - Always verify signatures on tool callbacks
• Use read-only database users - Limit data source connections to read-only access
• Monitor tool usage - Track which tools are being called and their success rates
• Test conversations - Verify assistant behavior before deploying to users
• Use metadata - Pass user context (name, plan, etc.) to personalize responses

DON'T

• Don't expose sensitive data - Be careful what tools can access
• Don't use write access - Keep data sources read-only
• Don't skip signature verification - Always verify tool callback signatures
• Don't overload with tools - Only enable tools the assistant actually needs
• Don't use vague instructions - Specific instructions produce better results

---

Error Handling

Agent-Specific Errors

Common error patterns you may encounter:

Error Code	HTTP Status	Description	Resolution
assistant_not_found	404	Assistant doesn't exist	Check assistant ID
room_not_found	404	Room doesn't exist	Check room ID
room_closed	400	Room is already closed	Create a new room
tool_not_found	404	Tool doesn't exist	Check tool ID
tool_callback_failed	500	Tool callback returned error	Check your callback endpoint
data_source_disconnected	400	Database connection failed	Check connection settings
query_execution_failed	400	SQL query failed	Check query syntax

Note: Error codes and formats may vary. Always check the response body for detailed error messages. Standard HTTP status codes apply (4xx for client errors, 5xx for server errors).

---

Rate Limiting

The AI Agents API uses rate limiting to ensure fair usage and system stability.

Rate Limit Headers

Every API response includes these headers:

Header	Type	Description
X-RateLimit-Limit	integer	Max requests allowed in window
X-RateLimit-Remaining	integer	Requests remaining in current window
X-RateLimit-Reset	integer	Unix timestamp (UTC) when window resets
X-RateLimit-Resource	string	Which limit bucket this applies to

Example Response Headers:

HTTP/1.1 200 OK
X-RateLimit-Limit: 100
X-RateLimit-Remaining: 95
X-RateLimit-Reset: 1705752000
X-RateLimit-Resource: agents:messages

Default Rate Limits

Limits vary by plan. Typical defaults:

Resource	Free	Pro	Enterprise
Assistants (create)	10/min	60/min	300/min
Rooms (create)	100/min	600/min	3000/min
Messages (send)	60/min/room	300/min/room	1000/min/room
Tool registrations	20/min	100/min	500/min
Data source queries	100/min	500/min	2000/min
API calls (global)	1000/min	10000/min	100000/min

Check Your Limits: View your actual limits in the Interactor dashboard under Settings → API → Rate Limits, or call GET /api/v1/account/limits.

Rate Limit Response (HTTP 429)

When rate limited:

HTTP/1.1 429 Too Many Requests
X-RateLimit-Limit: 100
X-RateLimit-Remaining: 0
X-RateLimit-Reset: 1705752000
Retry-After: 30
Content-Type: application/json

{
  "error": {
    "code": "rate_limit_exceeded",
    "message": "Rate limit exceeded for agents:messages",
    "resource": "agents:messages",
    "retry_after": 30
  }
}

Handling Rate Limits

Implementation with proper header parsing:

interface RateLimitInfo {
  limit: number;
  remaining: number;
  resetAt: Date;
  resource: string;
}

function parseRateLimitHeaders(headers: Headers): RateLimitInfo {
  return {
    limit: parseInt(headers.get('X-RateLimit-Limit') || '0'),
    remaining: parseInt(headers.get('X-RateLimit-Remaining') || '0'),
    resetAt: new Date(parseInt(headers.get('X-RateLimit-Reset') || '0') * 1000),
    resource: headers.get('X-RateLimit-Resource') || 'unknown'
  };
}

async function withRateLimitHandling<T>(
  fn: () => Promise<Response>,
  maxRetries: number = 3
): Promise<T> {
  for (let attempt = 0; attempt < maxRetries; attempt++) {
     response =  ();
     rateLimit = (response.);

    
    .();

     (response.) {
       response.();
    }

     (response. === ) {
       retryAfter = (response..() || );
      .();
        ( (resolve, retryAfter * ));
      ;
    }

    
      ();
  }

    ();
}


  (): <> {
   response =  (, {
    : ,
    : { : , :  },
    : .({ content, :  })
  });

   rateLimit = (response.);

  
   (rateLimit. < rateLimit. * ) {
     waitTime = .((rateLimit..() - .()) / );
    .();
  }

   response.();
}

---

Troubleshooting

Common Issues

Tool Callback Not Receiving Requests

Symptoms: Assistant says it's calling a tool, but your callback endpoint never receives the request.

Checklist:

1. ✓ Verify callback_url is publicly accessible (not localhost)
2. ✓ Check firewall/security group allows inbound HTTPS
3. ✓ Ensure endpoint returns 200 status within 30 seconds
4. ✓ Verify SSL certificate is valid (no self-signed in production)

Debug: Check Interactor dashboard for tool execution logs.

Tool Callback Signature Verification Failing

Symptoms: All tool callbacks return 401 Unauthorized.

Checklist:

1. ✓ Verify callback_secret matches what you registered
2. ✓ Ensure you're reading raw request body (not parsed JSON)
3. ✓ Check signature header name: X-Interactor-Signature
4. ✓ Verify HMAC algorithm is SHA256

Debug:

// Log for debugging (remove in production)
console.log('Received signature:', signature);
console.log('Payload:', payload);
console.log('Expected:', `sha256=${crypto.createHmac('sha256', secret).update(payload).digest('hex')}`);

Data Source Connection Failed

Symptoms: Data source status shows "disconnected" or "error".

Checklist:

1. ✓ Verify database host is reachable from Interactor's servers
2. ✓ Check credentials are correct
3. ✓ Ensure database user has SELECT permissions
4. ✓ Verify SSL/TLS settings match your database configuration
5. ✓ Check if IP allowlisting is required

Common Fixes:

-- Grant read-only access to Interactor user
GRANT SELECT ON ALL TABLES IN SCHEMA public TO interactor_readonly;
GRANT USAGE ON SCHEMA public TO interactor_readonly;

Assistant Not Using Tools

Symptoms: Assistant responds without using available tools when it should.

Checklist:

1. ✓ Verify tool is in enabled_tools array for the assistant
2. ✓ Check tool description is clear about when to use it
3. ✓ Ensure instructions mention when to use tools
4. ✓ Verify tool parameters schema is valid JSON Schema

Fix: Update assistant instructions to be explicit:

"When users ask about products, ALWAYS use the search_products tool to find current information."

Messages Not Appearing in Room

Symptoms: Sent messages don't show up when listing messages.

Checklist:

1. ✓ Verify room status is "active" (not "closed")
2. ✓ Check message was acknowledged (201 response)
3. ✓ Ensure you're querying the correct room ID
4. ✓ Wait for async processing (use streaming for real-time)

High Latency on Responses

Symptoms: Assistant takes a long time to respond.

Possible Causes:

1. Tool callbacks taking too long → Optimize your callback endpoints
2. Large context window → Close old rooms, start fresh conversations
3. Complex instructions → Simplify system prompt
4. Data source queries slow → Add indexes, optimize queries

Monitor:

const start = Date.now();
await sendMessage(roomId, content);
console.log(`Message sent in ${Date.now() - start}ms`);

---

Security & Compliance

Data Retention

Data Type	Default Retention	Configurable
Messages	90 days	Yes (30-365 days)
Room metadata	Until room deleted	N/A
Tool execution logs	30 days	Yes (7-90 days)
Assistant configurations	Indefinite	N/A

Enterprise: Contact support for custom retention policies and data residency requirements.

Configure retention in your Interactor dashboard under Settings → Data Management → Retention Policies.

Data Deletion (GDPR/CCPA)

To delete user data for compliance with GDPR "Right to Erasure" or CCPA:

Delete all rooms for a user:

# 1. List all rooms for the user
curl "https://core.interactor.com/api/v1/agents/rooms?namespace=user_123" \
  -H "Authorization: Bearer <token>"

# 2. Delete each room (also deletes messages)
curl -X DELETE "https://core.interactor.com/api/v1/agents/rooms/room_xyz" \
  -H "Authorization: Bearer <token>"

Bulk deletion via API:

curl -X POST https://core.interactor.com/api/v1/data/delete-user-data \
  -H "Authorization: Bearer <token>" \
  -H "Content-Type: application/json" \
  -d '{
    "namespace": "user_123",
    "include_messages": true,
    "include_tool_logs": true,
    "confirmation": "DELETE_ALL_DATA_FOR_user_123"
  }'

Response:

{
  "data": {
    "deletion_id": "del_abc123",
    "status": "processing",
    "estimated_completion": "2026-01-20T13:00:00Z",
    "items_to_delete": {
      "rooms": 5,
      "messages": 142,
      "tool_logs": 23
    }
  }
}

Important: Data deletion is asynchronous. Poll the deletion status endpoint to confirm completion before responding to user deletion requests.

Secret Rotation

Rotate callback_secret for tools without downtime:

Step 1: Add new secret (dual-secret mode):

curl -X PATCH https://core.interactor.com/api/v1/tools/tool_abc/secrets \
  -H "Authorization: Bearer <token>" \
  -H "Content-Type: application/json" \
  -d '{
    "add_secret": "new_secret_value_here",
    "deprecate_old_after_hours": 24
  }'

Step 2: Update your callback handler to accept both secrets:

function verifyWithRotation(
  payload: string,
  signature: string,
  secrets: string[]
): boolean {
  const signatureValue = signature.replace('sha256=', '');

  for (const secret of secrets) {
    const expected = crypto
      .createHmac('sha256', secret)
      .update(payload)
      .digest('hex');

    if (crypto.timingSafeEqual(
      Buffer.from(signatureValue),
      Buffer.from(expected)
    )) {
      return true;
    }
  }

  return false;
}

// Use both secrets during rotation
const SECRETS = [
  process.env.TOOL_CALLBACK_SECRET_NEW!,
  process.env.TOOL_CALLBACK_SECRET_OLD!
];

const isValid = verifyWithRotation(payload, signature, SECRETS);

Step 3: After transition period, remove old secret:

curl -X PATCH https://core.interactor.com/api/v1/tools/tool_abc/secrets \
  -H "Authorization: Bearer <token>" \
  -H "Content-Type: application/json" \
  -d '{
    "remove_deprecated": true
  }'

PII Handling

Do NOT include PII in:

• Tool names or descriptions
• Assistant names
• Log messages

DO use:

• Namespaces for user identification (e.g., user_123)
• Encrypted metadata for sensitive context
• Room metadata (encrypted at rest) for PII when necessary

// Bad - PII in tool parameters
{ "user_email": "[e-mail]" }

// Good - Use references
{ "user_id": "user_123" }  // Look up email in your backend

---

Observability & Correlation IDs

Request Correlation

Every API request returns a correlation ID for tracing:

Response Headers:

X-Request-Id: req_abc123xyz
X-Trace-Id: trace_789def

Include these in support requests and logging:

async function apiRequest(path: string, options: RequestInit = {}) {
  const response = await fetch(`https://core.interactor.com/api/v1${path}`, {
    ...options,
    headers: {
      ...options.headers,
      'Authorization': `Bearer ${token}`,
      'X-Client-Request-Id': crypto.randomUUID() // Your own correlation ID
    }
  });

  const requestId = response.headers.get('X-Request-Id');
  const traceId = response.headers.get('X-Trace-Id');

  // Log for debugging
  console.log(`[${path}] Request: ${requestId}, Trace: ${traceId}`);

  return { response, requestId, traceId };
}

Logging Recommendations

import { Logger } from 'your-logging-library';

const logger = new Logger({
  service: 'my-app',
  version: process.env.APP_VERSION
});

// Include correlation IDs in all agent-related logs
async function sendMessageWithLogging(roomId: string, content: string) {
  const correlationId = crypto.randomUUID();

  logger.info('Sending message to AI agent', {
    correlationId,
    roomId,
    contentLength: content.length
  });

  try {
    const { response, requestId } = await apiRequest(
      `/agents/rooms/${roomId}/messages`,
      {
        method: 'POST',
        body: JSON.stringify({ content, role: 'user' })
      }
    );

    if (!response.ok) {
      logger.error('Message send failed', {
        correlationId,
        requestId,
        status: response.status
      });
      throw new Error();
    }

     data =  response.();

    logger.(, {
      correlationId,
      requestId,
      : data..
    });

     data;
  }  (error) {
    logger.(, {
      correlationId,
      : error.
    });
     error;
  }
}

Metrics to Track

Metric	Description	Alert Threshold
agent.messages.sent	Messages sent to assistants	N/A (volume)
agent.messages.latency_ms	Time to first token	> 5000ms
agent.tool_calls.total	Tool invocations	N/A (volume)
agent.tool_calls.errors	Failed tool callbacks	> 5% error rate
agent.tool_calls.latency_ms	Tool callback duration	> 10000ms
agent.rooms.active	Currently active rooms	Depends on scale
agent.rate_limits.hits	429 responses received	> 10/min

Dashboard Integration

Export metrics to your monitoring system:

import { metrics } from 'your-metrics-library';

// Track message latency
const sendStart = Date.now();
await sendMessage(roomId, content);
metrics.histogram('agent.messages.latency_ms', Date.now() - sendStart, {
  assistant_id: assistantId
});

// Track tool callback performance
app.post('/api/tools/:toolName', async (req, res) => {
  const start = Date.now();
  try {
    const result = await handleToolCallback(req);
    metrics.increment('agent.tool_calls.total', { tool: req.params.toolName, status: 'success' });
    res.json({ result });
  } catch (error) {
    metrics.increment('agent.tool_calls.errors', { tool: req.params.toolName });
    throw error;
  } finally {
    metrics.histogram('agent.tool_calls.latency_ms', Date.now() - start, {
      tool: req.params.toolName
    });
  }
});

---

Message Limits & Attachments

Message Size Limits

Content Type	Max Size	Notes
Text message	32 KB	UTF-8 encoded
Metadata object	16 KB	JSON serialized
Tool result	64 KB	JSON serialized
Total request	128 KB	Including headers

Messages exceeding these limits return 413 Payload Too Large.

Handling Large Content

For content that may exceed limits:

const MAX_MESSAGE_SIZE = 32 * 1024; // 32 KB

function truncateForAssistant(content: string): string {
  if (content.length <= MAX_MESSAGE_SIZE) {
    return content;
  }

  // Truncate with indicator
  const truncated = content.slice(0, MAX_MESSAGE_SIZE - 100);
  return truncated + '\n\n[Content truncated. Full content available via reference ID: ref_xxx]';
}

// For large documents, summarize or chunk
async function sendLargeDocument(roomId: string, document: string) {
  if (document.length <= MAX_MESSAGE_SIZE) {
    return sendMessage(roomId, document);
  }

  // Store full document and send reference
  const docId = await storeDocument(document);

  return sendMessage(roomId,
    `I have a document to analyze (${document.length} characters). ` +
     +
    
  );
}

Attachment Support

API Note: File attachment support varies by Interactor version. Check your API documentation or contact support for availability.

If supported, the typical pattern:

# 1. Upload attachment
curl -X POST https://core.interactor.com/api/v1/attachments \
  -H "Authorization: Bearer <token>" \
  -F "file=@document.pdf" \
  -F "purpose=message_attachment"

# Response:
# { "data": { "id": "att_xyz", "url": "https://...", "expires_at": "..." } }

# 2. Reference in message
curl -X POST https://core.interactor.com/api/v1/agents/rooms/room_xyz/messages \
  -H "Authorization: Bearer <token>" \
  -H "Content-Type: application/json" \
  -d '{
    "content": "Please analyze this document",
    "role": "user",
    "attachments": ["att_xyz"]
  }'

Supported file types (when available):

• Documents: PDF, DOCX, TXT, MD
• Images: PNG, JPG, GIF, WEBP
• Data: CSV, JSON, XML

Max file size: 10 MB per file, 25 MB total per message.

---

API Reference & Testing

OpenAPI Specification

The AI Agents API follows OpenAPI 3.0 specification. Access the spec at:

https://core.interactor.com/api/v1/openapi.json
https://core.interactor.com/api/v1/openapi.yaml

Generate Client Libraries:

# TypeScript
npx openapi-typescript-codegen \
  --input https://core.interactor.com/api/v1/openapi.json \
  --output ./generated/interactor-client

# Python
pip install openapi-python-client
openapi-python-client generate \
  --url https://core.interactor.com/api/v1/openapi.json

Testing Your Integration

1. Use the Sandbox Environment:

# Sandbox base URL
export INTERACTOR_URL="https://sandbox.interactor.com"

# Sandbox credentials (from dashboard)
export INTERACTOR_SANDBOX_TOKEN="sandbox_token_here"

2. Test Tool Callbacks Locally:

Use a tunnel service to expose your local endpoint:

# Using ngrok
ngrok http 3000

# Register tool with ngrok URL
curl -X POST https://sandbox.interactor.com/api/v1/tools \
  -H "Authorization: Bearer $INTERACTOR_SANDBOX_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "test_tool",
    "description": "Test tool for development",
    "parameters": {"type": "object", "properties": {}},
    "callback_url": "https://abc123.ngrok.io/api/tools/test"
  }'

3. Verify Webhook Signatures in Tests:

import { describe, it, expect } from 'vitest';
import crypto from 'crypto';

describe('Tool Callback Verification', () => {
  const SECRET = 'test_secret';

  it('should verify valid signature', () => {
    const payload = JSON.stringify({ tool_name: 'test', parameters: {} });
    const signature = 'sha256=' + crypto
      .createHmac('sha256', SECRET)
      .update(payload)
      .digest('hex');

    const result = verifyToolCallback(payload, signature, SECRET);
    expect(result.valid).toBe(true);
  });

  it('should reject invalid signature', () => {
    const payload = JSON.stringify({ tool_name: 'test', parameters: {} });
    const signature = 'sha256=invalid';

    const result = verifyToolCallback(payload, signature, );
    (result.).();
  });

  (,  {
     payload = .({ : , : {} });
     oldTimestamp =  (.() - ).(); 
     signature =  + crypto
      .(, )
      .(payload)
      .();

     result = (payload, signature, oldTimestamp, , );
    (result.).();
    (result.).();
  });
});

4. Integration Test Example:

import { describe, it, expect, beforeAll, afterAll } from 'vitest';

describe('AI Agents Integration', () => {
  let assistantId: string;
  let roomId: string;

  beforeAll(async () => {
    // Create test assistant
    const assistant = await createAssistant({
      name: `test_${Date.now()}`,
      title: 'Test Assistant',
      instructions: 'You are a test assistant. Always respond with "Test OK".'
    });
    assistantId = assistant.id;
  });

  afterAll(async () => {
    // Cleanup
    if (roomId) await closeRoom(roomId);
    if (assistantId) await deleteAssistant(assistantId);
  });

  it('should create a room and exchange messages', async () => {
    // Create room
    const room = await createRoom(assistantId, 'test_user');
    roomId = room.id;
    expect(room.status).toBe();

    
     sent =  (roomId, );
    (sent.).();

    
      ( (r, ));

    
     { messages } =  (roomId);
    (messages.).();

     assistantMessage = messages.( m. === );
    (assistantMessage).();
    (assistantMessage?.).();
  });
});

---

Output Format

When implementing AI agents, provide this summary:

## AI Agent Implementation Report

**Date**: YYYY-MM-DD
**Assistant**: support_assistant

### Configuration
| Setting | Value |
|---------|-------|
| Model | gpt-4o |
| Temperature | 0.7 |
| Tools | search_products, create_ticket |

### Tools Registered
| Tool | Callback URL | Status |
|------|--------------|--------|
| search_products | https://app.com/api/tools/search | ✓ Active |
| create_ticket | https://app.com/api/tools/ticket | ✓ Active |

### Data Sources Connected
| Name | Type | Status |
|------|------|--------|
| sales_database | PostgreSQL | ✓ Connected |

### Implementation Checklist
- [ ] Assistant created with instructions
- [ ] Tools registered with callbacks
- [ ] Tool callback signature verification
- [ ] Data sources connected
- [ ] Semantic mappings configured
- [ ] Room management implemented
- [ ] Message streaming setup
- [ ] Error handling implemented

### Next Steps
1. Test conversations with sample queries
2. Set up webhooks for real-time updates (see `interactor-webhooks` skill)
3. Implement streaming for real-time responses

---

Related Skills

• interactor-auth: Setup authentication (prerequisite)
• interactor-sdk: TypeScript/JavaScript SDK for API integration
• interactor-credentials: Agents can use credentials to access external services
• interactor-workflows: Combine AI agents with automated workflows
• interactor-webhooks: Real-time message streaming and event subscriptions