Interaction API (Beta)

Enable real-time conversational AI with Convai’s Interaction API. Send text messages to your AI character and receive natural, streaming responses using Server-Sent Events (SSE).

This API is available only on the Professional Plan and above.

Overview

The Interaction API provides real-time conversational capabilities via a lightweight REST + SSE interface. It allows your application to send user messages and receive streaming character responses with minimal latency.

This API supports continuous conversation context through session IDs and streams all outputs as Server-Sent Events (SSE) for smooth, live feedback.

Authentication

All API requests require authentication using an API key in the header:

X-API-Key: your_api_key_here

Endpoint

POST https://live.convai.com/connect/stream

Send a text query to an AI character and receive a streaming response.

Request Format: multipart/form-data

Parameter

Type

Description

character_id*

UUID

Unique identifier for the AI character

text_input*

string

Your text query/message to the character

character_session_id

string

Session ID to continue an existing conversation

Example Requests

curl -X POST https://live.convai.com/connect/stream \
  -H "X-API-Key: YOUR_API_KEY" \
  -F "character_id=7bd3274c-1745-11ee-a3af-42010a400002" \
  -F "text_input=Hello, how are you?" \
  --no-buffer

import httpx
import json

async with httpx.AsyncClient(timeout=30.0) as client:
    async with client.stream(
        'POST',
        'https://live.convai.com/connect/stream',
        headers={'X-API-Key': 'YOUR_API_KEY'},
        data={
            'character_id': '7bd3274c-1745-11ee-a3af-42010a400002',
            'text_input': 'Hello, how are you?'
        }
    ) as response:
        async for line in response.aiter_lines():
            if line.startswith('data: '):
                data = json.loads(line[6:])
                if data.get('type') == 'bot-llm-text':
                    print(data['data']['text'], end='', flush=True)

const formData = new FormData();
formData.append('character_id', '7bd3274c-1745-11ee-a3af-42010a400002');
formData.append('text_input', 'Hello, how are you?');

const response = await fetch('https://live.convai.com/connect/stream', {
  method: 'POST',
  headers: { 'X-API-Key': 'YOUR_API_KEY' },
  body: formData,
});

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

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

  const chunk = decoder.decode(value);
  const lines = chunk.split('\n');

  for (const line of lines) {
    if (line.startsWith('data: ')) {
      const data = JSON.parse(line.slice(6));
      if (data.type === 'bot-llm-text') {
        console.log(data.data.text);
      }
    }
  }
}

Response: Server-Sent Events (SSE) stream

data: {"type": "connection-started", "message": {"session_id": "abc123", "transport": "sse", "character_session_id": "def456"}}

data: {"label": "rtvi-ai", "type": "bot-llm-started"}

data: {"label": "rtvi-ai", "type": "bot-llm-text", "data": {"text": "Hello"}}

data: {"label": "rtvi-ai", "type": "bot-llm-text", "data": {"text": "! I'm doing great, thank you for asking."}}

data: {"label": "rtvi-ai", "type": "bot-transcription", "data": {"text": "Hello! I'm doing great, thank you for asking."}}

data: {"label": "rtvi-ai", "type": "bot-llm-stopped"}

data: {"type": "connection-stoppped"}

Important Points

The request body must be multipart/form-data format. Use -F flag in cURL (not -d).
Skip character_session_id to start a new conversation. Add it to continue an existing conversation.
Character Session IDs are strings. Do not send -1 or other placeholder values.
Responses are streamed via Server-Sent Events (SSE). Set timeout to 30+ seconds.
All interactions are subject to content moderation policies. Repeated violations may result in API key suspension.
Requests are rate-limited per API key. Implement exponential backoff for rate limit errors.

Resume Conversation

To maintain conversation context, save the character_session_id from the first response and include it in subsequent requests.

Example Requests

First Request:

curl -X POST https://live.convai.com/connect/stream \
  -H "X-API-Key: YOUR_API_KEY" \
  -F "character_id=7bd3274c-1745-11ee-a3af-42010a400002" \
  -F "text_input=My name is Alice" \
  --no-buffer

Response includes:

{"type": "connection-started", "message": {"character_session_id": "9a98ab9b-5a6c-406e-9721-cc5bb0d527bb", ...}}

Second Request (with session ID):

curl -X POST https://live.convai.com/connect/stream \
  -H "X-API-Key: YOUR_API_KEY" \
  -F "character_id=7bd3274c-1745-11ee-a3af-42010a400002" \
  -F "text_input=What is my name?" \
  -F "character_session_id=9a98ab9b-5a6c-406e-9721-cc5bb0d527bb" \
  --no-buffer

Bot remembers: "Your name is Alice."

import httpx
import json
import asyncio

session_id = None

async def chat(message):
    global session_id

    data = {
        'character_id': '7bd3274c-1745-11ee-a3af-42010a400002',
        'text_input': message,
    }

    if session_id:
        data['character_session_id'] = session_id

    async with httpx.AsyncClient(timeout=30.0) as client:
        async with client.stream(
            'POST',
            'https://live.convai.com/connect/stream',
            headers={'X-API-Key': 'YOUR_API_KEY'},
            data=data,
        ) as response:
            async for line in response.aiter_lines():
                if line.startswith('data: '):
                    msg = json.loads(line[6:])

                    if msg.get('type') == 'connection-started':
                        session_id = msg['message']['character_session_id']
                    elif msg.get('type') == 'bot-llm-text':
                        print(msg['data']['text'], end='', flush=True)
            print()

# Usage
await chat('My name is Alice')
await chat('What is my name?')  # Bot remembers: "Your name is Alice"

let sessionId = null;

async function chat(message) {
  const formData = new FormData();
  formData.append('character_id', '7bd3274c-1745-11ee-a3af-42010a400002');
  formData.append('text_input', message);

  if (sessionId) {
    formData.append('character_session_id', sessionId);
  }

  const response = await fetch('https://live.convai.com/connect/stream', {
    method: 'POST',
    headers: { 'X-API-Key': 'YOUR_API_KEY' },
    body: formData,
  });

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

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

    buffer += decoder.decode(value, { stream: true });
    const lines = buffer.split('\n');
    buffer = lines.pop();

    for (const line of lines) {
      if (line.startsWith('data: ')) {
        const data = JSON.parse(line.slice(6));

        if (data.type === 'connection-started') {
          sessionId = data.message.character_session_id;
        } else if (data.type === 'bot-llm-text') {
          process.stdout.write(data.data.text);
        }
      }
    }
  }
  console.log();
}

// Usage
await chat('My name is Alice');
await chat('What is my name?');  // Bot remembers: "Your name is Alice"

Response Message Types

connection-started

Sent when the connection is established.

{
  "type": "connection-started",
  "message": {
    "session_id": "550e8400-e29b-41d4-a716-446655440000",
    "transport": "sse",
    "character_session_id": "660e8400-e29b-41d4-a716-446655440001"
  }
}

Fields:

session_id: Unique identifier for this connection
transport: Transport type (always "sse")
character_session_id: Save this to continue the conversation in future requests

bot-llm-started

Sent when the LLM starts generating a response.

{
  "label": "rtvi-ai",
  "type": "bot-llm-started"
}

bot-llm-text

Bot response text, streamed in chunks as they are generated.

{
  "label": "rtvi-ai",
  "type": "bot-llm-text",
  "data": {
    "text": "Hello there!"
  }
}

Fields:

text: A chunk of the bot's response text

bot-transcription

Complete transcription of the bot's response (sent after all text chunks).

{
  "label": "rtvi-ai",
  "type": "bot-transcription",
  "data": {
    "text": "Hello there! Complete response text."
  }
}

Fields:

text: The complete bot response text

bot-llm-stopped

Sent when the LLM finishes generating.

{
  "label": "rtvi-ai",
  "type": "bot-llm-stopped"
}

connection-stoppped

Sent when the response is complete and connection is closing.

{
  "type": "connection-stoppped"
}

Error Responses

All endpoints return standard HTTP error codes:

Status Code

Description

400

Bad Request - Invalid parameters

401

Unauthorized - Invalid or missing API key

404

Not Found - Character not found

422

Unprocessable Entity - Validation error

429

Too Many Requests - Rate limit exceeded

500

Internal Server Error

Error Response Format:

{
  "detail": "Error message describing what went wrong"
}

Example:

{
  "detail": "Invalid API key"
}

Conclusion

The Interaction API (Beta) enables dynamic, real-time communication with your Convai characters over text. By combining streaming responses, context persistence, and SSE-based delivery, it provides a responsive and low-latency conversational experience suitable for chat, games, and interactive AI applications.

Last updated 4 months ago

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hashtagOverview

hashtagAuthentication

hashtagEndpoint

hashtagExample Requests

hashtagResume Conversation

hashtagExample Requests

hashtagResponse Message Types

hashtagconnection-started

hashtagbot-llm-started

hashtagbot-llm-text

hashtagbot-transcription

hashtagbot-llm-stopped

hashtagconnection-stoppped

hashtagError Responses

hashtagConclusion

Overview

Authentication

Endpoint

Example Requests

Resume Conversation

Example Requests

Response Message Types

connection-started

bot-llm-started

bot-llm-text

bot-transcription

bot-llm-stopped

connection-stoppped

Error Responses

Conclusion