Chat API

The Chat API enables real-time conversations with AI agents for analytics and data exploration.

The Chat API is available on Premium and Enterprise plans.

</InfoBox>

Endpoint

The endpoint has the following structure:

https://ai.{cloudRegion}.cubecloud.dev/api/v1/public/{accountName}/agents/{agentId}/chat/stream-chat-state

Copy the exact Chat API URL from your agent settings (Chat API URL field) in <Btn>Admin → Agents</Btn>.

Overview

The Chat API enables real-time streaming conversations with Cube's AI agents. This endpoint allows applications to integrate AI-powered analytics conversations directly into their user interfaces.

Authentication

<WarningBox> Accounts are limited to 10,000 non-ephemeral external users. To increase this limit, please contact support. </WarningBox> <InfoBox> All users created using this API are ephemeral by default and will be removed after `sessionSettings.ephemeralTtlSeconds` (1 week by default). If users need to be persisted, pass `isEphemeral: false` in `sessionSettings`. Ephemeral users are guaranteed to not live longer than `sessionSettings.ephemeralTtlSeconds`. </InfoBox>

Pass your API key directly to the Chat API endpoint. The session will be created automatically based on the externalId provided:

javascript

// Copy the Chat API URL from your agent settings (Admin → Agents → Chat API URL field)
const CHAT_API_URL = 'YOUR_CHAT_API_URL';

const response = await fetch(
  CHAT_API_URL,
  {
    method: 'POST',
    headers: {
      'Content-Type': 'application/json',
      'Authorization': 'Api-Key ${API_KEY}',
    },
    body: JSON.stringify({
      input: 'What were the total sales last month?',
      sessionSettings: {
        externalId: '[email protected]',
        email: '[email protected]', // optional
        userAttributes: [ // optional
          {
            name: 'city',
            value: 'San Francisco'
          }
        ]
      }
    }),
  }
);

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

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

Request Body Fields:

Field	Type	Required	Description
`input`	string	No	The user's message or question. If omitted returns current state of thread with provided chatId.
`chatId`	string	No	Chat thread ID. If omitted, a new thread is created automatically. If provided, it should match the previously returned `chatId` from a message with id `__cutoff__` sent as the `state.chatId` field.
`sessionSettings.externalId`	string	No	Unique identifier for the external user, lowercase and without spaces. Either `externalId` or `internalId` should be provided.
`sessionSettings.internalId`	string	No	Email address of an internal Cube Cloud user. Either `externalId` or `internalId` should be provided.
`sessionSettings.email`	string	No	User's email address
`sessionSettings.userAttributes`	array	No	Array of `{name, value}` pairs for row-level security. Not allowed with `internalId`.
`sessionSettings.groups`	string[]	No	Array of group names the user belongs to. Not allowed with `internalId`.
`sessionSettings.securityContext`	object	No	Custom security context object passed to Cube queries. Not allowed with `internalId`.
`activeBranchName`	string	No	Name of a development branch to use for the chat session. When provided, queries run against the specified branch instead of the main branch.
`isDefaultBranch`	boolean	No	Whether the specified `activeBranchName` is the default branch. Defaults to `true` when `activeBranchName` is not set, and `false` when it is. Set to `true` if passing the main/production branch name.

When using internalId, the user must already exist in Cube Cloud. You cannot specify roles, groups, userAttributes, or securityContext with internalId — the internal user's existing permissions are used instead.

</InfoBox>

User Attributes

User attributes allow you to pass contextual information about the user to the AI agent. This enables personalized responses and automatic data filtering based on user permissions through row-level security policies.

<InfoBox> User attributes must first be configured in your Cube admin panel before they can be used. See the [User Attributes documentation](/product/administration/users-and-permissions/user-attributes) for setup instructions. </InfoBox>

Supported Fields:

externalId (optional): Unique identifier for the external user. Either externalId or internalId should be provided.
internalId (optional): Email address of an internal Cube Cloud user. The user must already exist. Either externalId or internalId should be provided.
email (optional): User's email address
userAttributes (optional): Array of key-value pairs containing user metadata. Only available with externalId.

User Attribute Structure:

javascript

{
  name: 'string',    // Must match an attribute name configured in admin panel
  value: 'string'    // Attribute value (e.g., 'San Francisco', 'Engineering')
}

How User Attributes Work:

Row-Level Security: Automatically filter data based on user attributes through access policies
Personalized Responses: AI agent can tailor responses based on user context
Access Control: Restrict data access to only what the user should see

Example Use Cases:

Filter sales data by user's assigned territory
Show only customers from user's city
Limit financial data based on user's department
Personalize dashboards by user role

The attributes passed during session generation become available as userAttributes.{attributeName} for use in access policies.

Endpoint Reference

POST

https://ai.{cloudRegion}.cubecloud.dev/api/v1/public/{accountName}/agents/{agentId}/chat/stream-chat-state

Copy the complete Chat API URL from your agent settings (Chat API URL field) in <Btn>Admin → Agents</Btn>.

</InfoBox>

Path Parameters

cloudRegion (string): The cloud region identifier (e.g., "gcp-us-central1")
accountName (string, required): The account identifier (e.g., "acme"). It is in your account URL, e.g. https://acme.cubecloud.dev
agentId (string, required): The AI agent identifier (e.g., "1"). You can find it in <Btn>Admin → Agents → Click on Agent row in the table</Btn>.

Request Body

input (string): User message or query to send to the AI agent, e.g. "What is our revenue last month?". If omitted, returns current state of thread with provided chatId.
chatId (string): Chat thread ID. If omitted, a new thread is created automatically. If provided, it should match the previously returned chatId from a message with id __cutoff__.
sessionSettings (object, required): Session configuration for the user
- externalId (string): Unique identifier for the external user. Either externalId or internalId should be provided.
- internalId (string): Email address of an internal Cube Cloud user. The user must already exist. Either externalId or internalId should be provided.
- email (string): User's email address
- userAttributes (array): Array of {name, value} pairs for row-level security. Not allowed with internalId.
- groups (string[]): Array of group names for user. Not allowed with internalId.
- securityContext (object): Custom security context object passed to Cube queries. Not allowed with internalId.
activeBranchName (string): Name of a development branch to use for the chat session. When provided, queries run against the specified branch instead of the main branch.
isDefaultBranch (boolean): Whether the specified activeBranchName is the default branch. Defaults to true when activeBranchName is not set, and false when it is. Set to true if passing the main/production branch name.

Response Format

<InfoBox> The API returns streaming JSON responses. Each line contains a separate JSON object representing a chat message or state update. </InfoBox>

Response Fields

id (string): Unique message identifier
role (string): Message sender: "user" or "assistant"
content (string): Message content (streamed incrementally for assistant messages)
thinking (string): Agent's internal reasoning process (visible in development mode)
toolCall (object): Information about tool calls made by the agent during processing
- name (string): Name of the tool being called
- input (string): JSON string containing the input parameters for the tool
- result (string): JSON string containing the tool's response (only present when tool call is complete)
graphPath (string[]): Identifies which node of the agent graph produced this message. For example, ["cube_data_analyst_agent"] for the main agent node or ["cube_data_analyst_agent", "tools"] for tool calls. Messages with graphPath[0] === "final" represent the final consolidated answer.
isDelta (boolean): Whether this is an incremental content update
isInProcess (boolean): Whether the message is still being generated
sort (number): Message ordering sequence number
state (object): Current streaming state information

Response Examples

The API returns a series of JSON objects, each on a separate line. Here's what a typical conversation looks like:

Initial State Message:

json

{
  "id": "__cutoff__",
  "role": "assistant",
  "state": {
    "isStreaming": false
  },
  "sort": 0
}

User Message Echo:

json

{
  "id": "1732512345678-message",
  "role": "user",
  "content": "Show me revenue trends for the last 6 months",
  "isDelta": false,
  "sort": 1
}

Assistant Response Start:

json

{
  "id": "cdfe1a84-08d7-40b9-8b1c-e7e3a698647e",
  "role": "assistant",
  "content": "",
  "thinking": "",
  "graphPath": ["cube_data_analyst_agent"],
  "isStructuredResponse": false,
  "isInProcess": true,
  "isDelta": true,
  "sort": 2
}

Thinking Process:

json

{
  "id": "cdfe1a84-08d7-40b9-8b1c-e7e3a698647e",
  "role": "assistant",
  "content": "",
  "thinking": "The user wants to see revenue trends for the last 6 months. I need to query the revenue data and create a visualization.",
  "graphPath": ["cube_data_analyst_agent"],
  "isStructuredResponse": false,
  "isInProcess": true,
  "isDelta": true,
  "sort": 3
}

Content Streaming:

json

{
  "id": "cdfe1a84-08d7-40b9-8b1c-e7e3a698647e",
  "role": "assistant",
  "content": "I'll help you analyze revenue trends for the last 6 months. Let me query the data and create a visualization.",
  "thinking": "",
  "graphPath": ["cube_data_analyst_agent"],
  "isStructuredResponse": false,
  "isInProcess": true,
  "isDelta": true,
  "sort": 4
}

Tool Call Initiated:

json

{
  "id": "4849adb2-b55d-4afe-946b-fc117bcadaf5",
  "role": "assistant",
  "toolCall": {
    "name": "cubeMeta",
    "input": "{\"searchQuery\":\"revenue trends\"}"
  },
  "isInProcess": true,
  "graphPath": ["cube_data_analyst_agent", "tools"],
  "isStructuredResponse": false,
  "isDelta": false,
  "sort": 5
}

Tool Call Result:

json

{
  "id": "4849adb2-b55d-4afe-946b-fc117bcadaf5",
  "role": "assistant",
  "toolCall": {
    "name": "cubeMeta",
    "input": "{\"searchQuery\":\"revenue trends\"}",
    "result": "{\"cubes\":[{\"name\":\"Revenue\",\"measures\":[\"Revenue.totalRevenue\",\"Revenue.monthlyGrowth\"]}]}"
  },
  "isInProcess": false,
  "graphPath": ["cube_data_analyst_agent", "tools"],
  "isStructuredResponse": false,
  "isDelta": false,
  "sort": 6
}

SQL Query Tool Call:

json

{
  "id": "a1b2c3d4-e5f6-7890-ab12-cd34ef567890",
  "role": "assistant",
  "toolCall": {
    "name": "cubeSqlApi",
    "input": "{\"query\":\"SELECT Revenue.totalRevenue, Revenue.month FROM Revenue WHERE Revenue.dateRange BETWEEN '2024-01-01' AND '2024-06-30' ORDER BY Revenue.month\"}"
  },
  "isInProcess": true,
  "graphPath": ["cube_data_analyst_agent", "tools"],
  "isStructuredResponse": false,
  "isDelta": false,
  "sort": 7
}

SQL Query Result:

json

{
  "id": "a1b2c3d4-e5f6-7890-ab12-cd34ef567890",
  "role": "assistant",
  "toolCall": {
    "name": "cubeSqlApi",
    "input": "{\"query\":\"SELECT Revenue.totalRevenue, Revenue.month FROM Revenue WHERE Revenue.dateRange BETWEEN '2024-01-01' AND '2024-06-30' ORDER BY Revenue.month\"}",
    "result": "{\"data\":[{\"Revenue.totalRevenue\":1800000,\"Revenue.month\":\"2024-01\"},{\"Revenue.totalRevenue\":1950000,\"Revenue.month\":\"2024-02\"},{\"Revenue.totalRevenue\":2300000,\"Revenue.month\":\"2024-03\"},{\"Revenue.totalRevenue\":2100000,\"Revenue.month\":\"2024-04\"},{\"Revenue.totalRevenue\":2250000,\"Revenue.month\":\"2024-05\"},{\"Revenue.totalRevenue\":2400000,\"Revenue.month\":\"2024-06\"}],\"annotation\":{\"measures\":{\"Revenue.totalRevenue\":{\"title\":\"Total Revenue\",\"type\":\"number\"}},\"dimensions\":{\"Revenue.month\":{\"title\":\"Month\",\"type\":\"time\"}}}}"
  },
  "isInProcess": false,
  "graphPath": ["cube_data_analyst_agent", "tools"],
  "isStructuredResponse": false,
  "isDelta": false,
  "sort": 8
}

Final Complete Message:

json

{
  "id": "cdfe1a84-08d7-40b9-8b1c-e7e3a698647e",
  "role": "assistant",
  "content": "I'll help you analyze revenue trends for the last 6 months. Let me query the data and create a visualization.\n\nBased on your revenue data, here are the key trends:\n\n📈 **Overall Growth**: 15% increase over the 6-month period\n💰 **Peak Month**: March 2024 with $2.3M revenue\n📊 **Steady Growth**: Consistent month-over-month growth of 2-3%\n\nWould you like me to break this down by product category or region?",
  "thinking": "",
  "graphPath": ["cube_data_analyst_agent"],
  "isStructuredResponse": false,
  "isInProcess": false,
  "isDelta": false,
  "sort": 9
}

Final State Update:

json

{
  "id": "__state__",
  "role": "assistant",
  "state": {
    "messages": [{
      "lc": 1,
      "type": "constructor",
      "id": ["langchain_core", "messages", "HumanMessage"],
      "kwargs": {
        "content": "Show me revenue trends for the last 6 months"
      }
    }]
  },
  "isDelta": false,
  "sort": 10
}

Getting the Final Assistant Message

When consuming the streamed NDJSON response, you may want to extract only the final answer that the agent produced — for example, to display it in a chat UI or to store it for later reference.

The agent graph emits many intermediate messages (thinking steps, tool calls, incremental deltas, state updates, etc.). To isolate the final answer, filter the streamed messages using these two conditions:

role === "assistant" — only assistant messages.
graphPath[0] === "final" and graphPath.length <= 2 — messages produced by the "final" node of the agent graph.

The last message that satisfies both conditions is the final answer.

javascript

// Collect all streamed messages first
const messages = [];

for await (const line of readLines(response.body)) {
  if (line) {
    messages.push(JSON.parse(line));
  }
}

// Filter for final-answer messages
const finalMessages = messages.filter(
  (msg) =>
    msg.role === "assistant" &&
    Array.isArray(msg.graphPath) &&
    msg.graphPath[0] === "final" &&
    msg.graphPath.length <= 2
);

// The last one is the definitive final answer
const finalAnswer = finalMessages[finalMessages.length - 1];
console.log("Final answer:", finalAnswer?.content);

The graphPath property is an array of strings that traces the path through the agent's internal execution graph. Intermediate nodes (e.g., ["cube_data_analyst_agent"] or ["cube_data_analyst_agent", "tools"]) produce working messages, while the "final" node emits the consolidated response that should be presented to the user.

</InfoBox>

Tool Calls

When the AI agent performs actions like querying data or searching metadata, tool calls are included in the response stream. These provide transparency into the agent's reasoning and data retrieval process.

<InfoBox> All tool results are returned as **JSON strings** within the `toolCall.result` field, not as parsed JSON objects. You must parse these strings to access the structured data. </InfoBox>

Key Points:

toolCall.input - JSON string containing tool parameters
toolCall.result - JSON string containing tool response (only present when isInProcess: false)
Both input and result contain escaped JSON that requires parsing
Results may contain nested JSON structures, especially for complex data queries
Error responses are also JSON strings with consistent error formatting

Parsing Example:

javascript

// Parse the tool result JSON string
const toolResult = JSON.parse(message.toolCall.result);

if (toolResult.error) {
  console.error('Tool error:', toolResult.error);
} else {
  // Handle successful result based on tool type
  if (message.toolCall.name === 'cubeSqlApi') {
    const data = toolResult.data;
    const annotation = toolResult.annotation;
    // Process query results...
  }
}

cubeMeta

Searches cube metadata and schema information

The cubeMeta tool returns cube schema information as a JSON string. When successful, the result contains:

json

{
  "toolCall": {
    "name": "cubeMeta",
    "input": "...",
    "result": "..."
  }
}

Input Structure:

json

{
  "searchQuery": "sales pipeline revenue"
}

Input Fields:

searchQuery (string): Search query for data model

Result Structure:

json

{
  "cubes": [
    {
      "name": "sales_pipeline_view",
      "type": "view",
      "title": "Sales Pipeline View",
      "members": [
        {
          "name": "sales_pipeline_view.company_name",
          "title": "Company Name",
          "description": "Name of the company/prospect",
          "type": "string"
        },
        {
          "name": "sales_pipeline_view.deal_amount",
          "title": "Deal Amount",
          "description": "Total deal value",
          "type": "number"
        },
        {
          "name": "sales_pipeline_view.stage",
          "title": "Sales Stage",
          "description": "Current stage of the deal (Lead, Demo, Negotiation, Won, Lost, etc.)",
          "type": "string"
        },
        {
          "name": "sales_pipeline_view.count",
          "title": "Deal Count",
          "description": "Total number of deals",
          "type": "number",
          "aggType": "count"
        }
      ]
    },
    {
      "name": "revenue_view",
      "type": "view",
      "title": "Revenue View",
      "members": [
        {
          "name": "revenue_view.total_amount",
          "title": "Total Revenue",
          "description": "Sum of all revenue",
          "type": "number",
          "aggType": "sum"
        },
        {
          "name": "revenue_view.month",
          "title": "Revenue Month",
          "description": "Month of revenue recognition",
          "type": "time"
        },
        {
          "name": "revenue_view.is_recurring",
          "title": "Is Recurring Revenue",
          "description": "Whether this is recurring or one-time revenue",
          "type": "boolean"
        }
      ]
    }
  ],
  "searchQuery": "sales pipeline revenue"
}

Result Fields:

cubes (array): Available cube/view definitions with members
searchQuery (string): The original search query used

cubeSqlApi

Executes SQL queries against cube data

The cubeSqlApi tool executes SQL queries and returns data with metadata. The input typically includes additional context fields:

json

{
  "toolCall": {
    "name": "cubeSqlApi",
    "input": "...",
    "result": "..."
  }
}

Input Structure:

json

{
  "sqlQuery": "SELECT deals_view.company_name, deals_view.deal_name FROM deals_view WHERE deals_view.stage = 'Negotiation' LIMIT 10",
  "queryTitle": "Sales Pipeline Overview",
  "description": "Retrieving deal information from the deals view for current negotiations",
  "userRequest": "show me current deals in negotiation",
  "memoryId": "a1b2c3d4-5e6f-7g8h-9i0j-k1l2m3n4o5p6",
  "vegaSpec": "vega lite v5 visualization spec as JSON string"
}

Input Fields:

sqlQuery (string): The SQL query to execute
queryTitle (string): Human-readable title for the query
description (string): Detailed description of what the query does
userRequest (string): Original user request that triggered this query
memoryId (string): Reference to previous analysis or context
vegaSpec (string): Vega-Lite v5 visualization specification as JSON string (when visualization is generated)

Result Structure:

json

{
  "sqlQuery": "SELECT deals_view.company_name, deals_view.name AS deal_name...",
  "queryTitle": "Current Deals Overview",
  "description": "Retrieving deals showing company names, deal names, stages...",
  "userRequest": "show me deals",
  "schema": [
    {
      "name": "company_name",
      "column_type": "String"
    },
    {
      "name": "deal_name", 
      "column_type": "String"
    },
    {
      "name": "stage",
      "column_type": "String"
    },
    {
      "name": "tenant_name",
      "column_type": "String"
    },
    {
      "name": "activity_score",
      "column_type": "Double"
    },
    {
      "name": "deal_count",
      "column_type": "Int64"
    }
  ],
  "data": [
    ["Acme Corp", "Enterprise Solution", "Negotiation", "acme-workspace", "245", "1"],
    ["Beta Industries", "Analytics Platform", "Testing", "beta-analytics", "189", "1"],
    ["Gamma LLC", "Data Pipeline", "Demo", "gamma-data", "156", "1"]
  ],
  "totalRows": 25,
  "uuid": "a1b2c3d4-5e6f-7g8h-9i0j-k1l2m3n4o5p6",
  "vegaSpec": "vega lite v5 visualization spec as JSON string"
}

Result Fields:

sqlQuery (string): The executed SQL query
queryTitle (string): Human-readable title for the query
description (string): Detailed description of what the query does
userRequest (string): Original user request that triggered this query
schema (array): Column definitions with name and column_type for each field
data (array): Query result rows as arrays of values
totalRows (number): Total number of rows returned
uuid (string): Unique identifier for this query result
vegaSpec (string): Vega-Lite v5 visualization specification as JSON string (when visualization is generated)

Loading all Results

<WarningBox> Query results in cubeSqlApi `toolCall.result.data` are limited to **100 rows** by default. Use `totalRows` to check if more data is available. </WarningBox>

If you need to load all the data, you need to use sqlQuery from the results to make a call to the Cube API.

Displaying charts

The cubeSqlApi tool call returns vegaSpec that can be used to display data.

Note that it doesn't contain data. You need to use the data from toolCall.result.data.

Styling charts

When rendering Vega charts, you can apply custom styling to match the look and feel of your application. This includes adjusting colors, fonts, and other visual elements.

Here's a configuration example that mimics Cube's default styling:

json

{
  // Your Vega configuration

  "config": {
    "background": "#ffffff",
    "padding": 16,
    "view": {
      "stroke": "transparent"
    },
    "axis": {
      "domainColor": "#E0E0E0",
      "gridColor": "#F5F5F5",
      "grid": true,
      "labelFont": "Inter, sans-serif",
      "labelFontSize": 12,
      "labelColor": "#43436B",
      "titleFont": "Inter, sans-serif",
      "titleFontSize": 12,
      "titleColor": "#43436B",
      "titlePadding": 8
    },
    "numberFormat": "s",
    "timeFormat": "%Y-%m",
    "format": {
      "number": {
        "format": "s",
        "formatType": "number"
      },
      "time": {
        "format": "%Y-%m",
        "formatType": "time"
      }
    },
    "legend": {
      "labelFont": "Inter, sans-serif",
      "titleFont": "Inter, sans-serif",
      "labelColor": "#43436B",
      "titleColor": "#43436B",
      "labelFontSize": 12,
      "titleFontSize": 12,
      "titlePadding": 8,
      "padding": 8
    },
    "line": {
      "strokeWidth": 3,
      "strokeCap": "round",
      "point": true
    },
    "text": {
      "color": "#43436B"
    },
    "point": {
      "filled": true,
      "size": 60
    },
    "range": {
      "category": [
        "#4E79A7",
        "#F28E2B",
        "#E15759",
        "#76B7B2",
        "#59A14F",
        "#EDC948",
        "#B07AA1",
        "#FF9DA7",
        "#9C755F",
        "#BAB0AC"
      ],
      "heatmap": [
        "#eff6ff",
        "#1e40af"
      ]
    },
    "scale": {
      "band": {
        "padding": 0.1,
        "round": true
      },
      "linear": {
        "nice": true,
        "zero": true
      },
      "ordinal": {
        "type": "band",
        "padding": 0.1
      },
      "time": {
        "type": "utc",
        "nice": true
      },
      "log": {
        "base": 10,
        "domain": {
          "data": "table",
          "field": "x"
        },
        "range": {
          "data": "table",
          "field": "y"
        }
      },
      "range": [
        "#4E79A7",
        "#F28E2B"
      ]
    }
  }
}

Error Handling

When a tool encounters an error, the result field contains structured error information as a JSON string:

Standard Error Format:

When an error occurs, the result property of the toolCall will contain an error property.

json

{
  "toolCall": {
    "name": "cubeMeta",
    "input": "{\"searchQuery\":\"opportunities deals\"}",
    "result": "{\n  \"error\": \"Error: BadRequestError: Bad branch\"\n}"
  },
  "isInProcess": false
}

Abort Endpoint

The Abort endpoint stops an in-progress chat stream. This is useful when the user cancels a request or navigates away while the agent is still generating a response.

Endpoint

POST

https://ai.{cloudRegion}.cubecloud.dev/api/v1/public/{accountName}/agents/{agentId}/chat/abort

The abort URL is derived from the Chat API URL by replacing /stream-chat-state with /abort.

Authentication

Uses the same API key authentication as the Chat API.

Request Body

chatId (string, required): The chat thread ID to abort. This must match the chatId of an active or recently completed chat session.
sessionSettings (object): Same session settings as stream-chat-state to authenticate the request.
- externalId (string): Unique identifier for the external user.

Response

204 No Content: Chat streaming was aborted successfully.
403 Forbidden: The authenticated user does not own the specified chat thread.
404 Not Found: The specified chatId does not exist.

Code Examples

bash

# Derive the abort URL from your Chat API URL by replacing /stream-chat-state with /abort
ABORT_URL="${CHAT_API_URL/stream-chat-state/abort}"

curl -X POST "$ABORT_URL" \
  -H "Content-Type: application/json" \
  -H "Authorization: Api-Key YOUR_API_KEY" \
  -d '{
    "chatId": "CHAT_ID_TO_ABORT",
    "sessionSettings": {
      "externalId": "[email protected]"
    }
  }'

javascript

const CHAT_API_URL = 'YOUR_CHAT_API_URL';
const ABORT_URL = CHAT_API_URL.replace(/\/stream-chat-state$/, '/abort');
const API_KEY = 'YOUR_API_KEY';

const response = await fetch(ABORT_URL, {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': `Api-Key ${API_KEY}`
  },
  body: JSON.stringify({
    chatId: 'CHAT_ID_TO_ABORT',
    sessionSettings: {
      externalId: '[email protected]'
    }
  })
});

if (response.status === 204) {
  console.log('Chat streaming aborted successfully');
}

python

import requests

CHAT_API_URL = "YOUR_CHAT_API_URL"
ABORT_URL = CHAT_API_URL.replace("/stream-chat-state", "/abort")
API_KEY = "YOUR_API_KEY"

response = requests.post(
    ABORT_URL,
    headers={
        "Content-Type": "application/json",
        "Authorization": f"Api-Key {API_KEY}"
    },
    json={
        "chatId": "CHAT_ID_TO_ABORT",
        "sessionSettings": {
            "externalId": "[email protected]"
        }
    }
)

if response.status_code == 204:
    print("Chat streaming aborted successfully")

</CodeTabs>

Code Examples

bash

# Copy YOUR_CHAT_API_URL from your agent settings (Admin → Agents → Chat API URL field)
curl -X POST "YOUR_CHAT_API_URL" \
  -H "Content-Type: application/json" \
  -H "Authorization: Api-Key YOUR_API_KEY" \
  -d '{
    "input": "Show me revenue trends for the last 6 months",
    "sessionSettings": {
      "externalId": "[email protected]"
    }
  }'

javascript

// Copy the Chat API URL from your agent settings (Admin → Agents → Chat API URL field)
const CHAT_API_URL = 'YOUR_CHAT_API_URL';
const API_KEY = 'YOUR_API_KEY';

const response = await fetch(
  CHAT_API_URL,
  {
    method: 'POST',
    headers: {
      'Content-Type': 'application/json',
      'Authorization': `Api-Key ${API_KEY}`
    },
    body: JSON.stringify({
      input: 'Hello, how can you help me analyze our data?',
      sessionSettings: {
        externalId: '[email protected]',
        email: '[email protected]', // optional
        userAttributes: [ // optional
          {
            name: 'city',
            value: 'San Francisco'
          }
        ]
      }
    })
  }
);

// Handle streaming response
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.trim().split('\n');
  
  lines.forEach(line => {
    if (line) {
      const message = JSON.parse(line);
      console.log('Received:', message);
      
      // Handle different message types
      if (message.role === 'assistant' && message.content) {
        updateChatUI(message);
      }
    }
  });
}

python

import requests
import json

# Copy the Chat API URL from your agent settings (Admin → Agents → Chat API URL field)
CHAT_API_URL = "YOUR_CHAT_API_URL"
API_KEY = "YOUR_API_KEY"

headers = {
    "Content-Type": "application/json",
    "Authorization": f"Api-Key {API_KEY}"
}

data = {
    "input": "What are our top performing products?",
    "sessionSettings": {
        "externalId": "[email protected]",
        "email": "[email protected]",  # optional
        "userAttributes": [  # optional
            {
                "name": "city",
                "value": "San Francisco"
            }
        ]
    }
}

response = requests.post(CHAT_API_URL, headers=headers, json=data, stream=True)

for line in response.iter_lines():
    if line:
        message = json.loads(line.decode('utf-8'))
        print("Received:", message)

</CodeTabs>

Error Handling

204 No Content: (Abort endpoint only) Chat streaming was aborted successfully.
400 Bad Request: Invalid request body or parameters. Check required fields and data types.
401 Unauthorized: Invalid or missing API key. Verify your API key is correct and has the necessary permissions.
403 Forbidden: (Abort endpoint only) The authenticated user does not own the specified chat thread.
404 Not Found: Agent, tenant, or chat thread not found. Verify the Chat API URL from your agent settings and the chatId.
500 Internal Server Error: Server processing error. Contact support if the issue persists.