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POST
/
v1
/
chat
POST /v1/chat
curl --request POST \
  --url https://api.example.com/v1/chat \
  --header 'Content-Type: application/json' \
  --data '
{
  "messages": [
    {}
  ],
  "sessionId": "<string>"
}
'

Documentation Index

Fetch the complete documentation index at: https://docs.aris247.com/llms.txt

Use this file to discover all available pages before exploring further.

​
Request

curl -X POST \
  "https://dqgynnlsclfbqysauesf.supabase.co/functions/v1/api-router/v1/chat" \
  -H "Content-Type: application/json" \
  -H "X-ARIS-API-Key: aris_yourkey" \
  -d '{
    "messages": [
      {"role": "user", "content": "Show me 3-bedroom homes under $500k in Austin"}
    ],
    "sessionId": "session_abc123"
  }'

​
Body parameters

​
messages
array
required
Conversation history. Each item has role (user, assistant, system) and content (string). Most recent message last.
​
sessionId
string
Reuse across turns to maintain conversation memory (preferences, prior listings). A new one is generated if omitted.

​
Response

Content-Type: text/event-stream The response is a Server-Sent Events (SSE) stream in OpenAI-compatible delta format: 
data: {"choices":[{"delta":{"content":"I found"},"index":0}]}

data: {"choices":[{"delta":{"content":" 3 homes"},"index":0}]}

data: [DONE]

​
Consuming the stream

const response = await fetch(url, { method: "POST", headers, body });
const reader = response.body.getReader();
const decoder = new TextDecoder();
let content = "";

while (true) {
  const { done, value } = await reader.read();
  if (done) break;
  const text = decoder.decode(value);
  for (const line of text.split("\n")) {
    if (line.startsWith("data: ")) {
      const payload = line.slice(6).trim();
      if (payload === "[DONE]") break;
      const parsed = JSON.parse(payload);
      const delta = parsed.choices?.[0]?.delta?.content;
      if (delta) content += delta;
    }
  }
}

​
Listing data in the stream

Property listings are embedded in the stream using HTML comment markers: 
<!--PROPERTIES: [{"listingId":"a123","address":"123 Main St",...}] -->
The ARIS widget parser extracts these automatically. If building a custom client, look for <!--PROPERTIES: markers in the accumulated content.

​
Intent classification

The AI automatically classifies each message and routes to the appropriate tool: property_search · property_question · general_question · correction · contact_info · scheduling · small_talk · off_topic · follow_up · comparison · affordability · negotiation · location_info