Add analytics to any OpenAI compatible chat

With Inkeep's Analytics API, you can log your AI chat conversations to:

Get Inkeep's analytics and reporting for the chats
Provide and track "Thumbs up/down" feedback
Power "Share" or "Saved Chats" experiences

The Inkeep Analytics API is designed to be flexible and can log any OpenAI-compatible conversation, including those with tool calls or custom functionality.

If you're using Inkeep's Chat API to create your own chat UX or custom copilot, you should use the Analytics API to enable the same reporting as provided by the @inkeep/cxkit-react component library.

Note

Only an API key generated through the API integration can be used. API keys from other integration are not supported.

Get an API key

Log in to the Inkeep Dashboard
Navigate to the Projects section and select your project
Open the Integrations tab
Click Create Integration and choose API from the options
Enter a Name for your new API integration.
Click on Create
A generated API key will appear that you can use to authenticate API requests.

Log a conversation

Initial message

To log a new conversation, make a POST request to the /conversations endpoint.

const initialConversationData = {
  id: "conv_1234", // optional
  type: "openai",
  messages: [
    {
      role: "user",
      content: "Can I log any OpenAI-compatible conversation?",
    },
    {
      role: "assistant",
      content:
        "Yes, our analytics engine is agnostic. You can log full conversations of your agent or custom copilot, even if not all interactions hit Inkeep's API endpoint.",
    },
  ],
  properties: {
    // Add any custom properties here
  },
  userProperties: {
    // Add any user-specific properties here
  },
};
 
let currentConversation = await fetch(
  "https://api.analytics.inkeep.com/conversations",
  {
    method: "POST",
    headers: {
      Authorization: "Bearer YOUR_API_KEY",
      "Content-Type": "application/json",
    },
    body: JSON.stringify(initialConversationData),
  }
).then((response) => {
  if (!response.ok) {
    throw new Error(`HTTP error! status: ${response.status}`);
  }
  return response.json();
});
 
console.log(currentConversation);

Follow-up messages

To log additional messages in an existing conversation, include the id returned from the initial submission:

const continueConversationData = {
  id: currentConversation.id,
  type: "openai",
  messages: [
    ...currentConversation.messages,
    // Add new messages
    {
      role: "user",
      content: "Does that mean it supports logging tool calls?",
    },
    {
      role: "assistant",
      content:
        "Yup, Inkeep's Analytics API is fully compatible with OpenAI chat completions endpoints, including tool calling.",
    },
  ],
};
 
currentConversation = await fetch(
  "https://api.analytics.inkeep.com/conversations",
  {
    method: "POST",
    headers: {
      Authorization: "Bearer YOUR_API_KEY",
      "Content-Type": "application/json",
    },
    body: JSON.stringify(continueConversationData),
  }
).then((response) => {
  if (!response.ok) {
    throw new Error(`HTTP error! status: ${response.status}`);
  }
  return response.json();
});
 
console.log(currentConversation);

Note

You can provide your own IDs for conversations and messages, or Inkeep will auto-generate them. For logging continuous exchanges in a conversation, make sure to retain and use the same conversation ID and always include the entire message history. POST /conversation works like an upsert operation.

Submit feedback

Use the /feedback endpoint to log 👍 / 👎 feedback from your UI.

const feedbackData = {
  type: "positive", // or "negative"
  messageId: "{assistant_message_id}", // e.g. currentConversation.messages[1].id
  reasons: [
    {
      label: "accurate_code_snippet",
      details: "The code worked perfectly.",
    },
  ],
  userProperties: {
    // Add any user-specific properties here
  },
};
 
fetch("https://api.analytics.inkeep.com/feedback", {
  method: "POST",
  headers: {
    Authorization: "Bearer YOUR_API_KEY",
    "Content-Type": "application/json",
  },
  body: JSON.stringify(feedbackData),
})
  .then((response) => response.json())
  .then((data) => console.log(data));

Monitor

To view analytics for your logged conversations and feedback:

Go to portal.inkeep.com
Navigate to Projects and select the relevant one
View the Chat Sessions, Insights, and Analytics tabs

You can use the GET /conversations endpoint to retrieve logged conversations and power "Share" or "Saved Chats" features.

Here's an example of how to fetch a specific conversation:

fetch(
  "https://api.analytics.inkeep.com/conversations/{existing_conversation_id}",
  {
    method: "GET",
    headers: {
      Authorization: "Bearer YOUR_API_KEY",
    },
  }
)
  .then((response) => response.json())
  .then((data) => {
    // Use the conversation data to rehydrate your UI
    console.log(data);
  });

The response will contain detailed information about the conversation:

{
  "id": "conv_123456789",
  "type": "openai",
  "createdAt": "2024-07-11T10:15:30.123Z",
  "updatedAt": "2024-07-11T10:16:45.678Z",
  "projectId": "proj_987654321",
  "integrationId": "intg_246813579",
  "properties": {
    "source": "web_chat"
  },
  "userProperties": {
    "userId": "user_135792468"
  },
  "messages": [
    {
      "id": "msg_1",
      "type": "openai",
      "conversationId": "conv_123456789",
      "createdAt": "2024-07-11T10:15:30.123Z",
      "updatedAt": "2024-07-11T10:15:30.123Z",
      "role": "user",
      "content": "Can I log any OpenAI-compatible conversation?",
      "name": null,
      "links": null,
      "properties": {},
      "userProperties": {}
    },
    {
      "id": "msg_2",
      "type": "openai",
      "conversationId": "conv_123456789",
      "createdAt": "2024-07-11T10:15:40.456Z",
      "updatedAt": "2024-07-11T10:15:40.456Z",
      "role": "assistant",
      "content": "Yes, our analytics engine is agnostic. You can log full conversations of your agent or custom copilot, even if not all interactions hit Inkeep's API endpoint.",
      "name": null,
      "links": null,
      "properties": {},
      "userProperties": {}
    },
    {
      "id": "msg_3",
      "type": "openai",
      "conversationId": "conv_123456789",
      "createdAt": "2024-07-11T10:16:15.789Z",
      "updatedAt": "2024-07-11T10:16:15.789Z",
      "role": "user",
      "content": "Does that mean it supports logging tool calls?",
      "name": null,
      "links": null,
      "properties": {},
      "userProperties": {}
    },
    {
      "id": "msg_4",
      "type": "openai",
      "conversationId": "conv_123456789",
      "createdAt": "2024-07-11T10:16:45.678Z",
      "updatedAt": "2024-07-11T10:18:45.678Z",
      "role": "assistant",
      "content": "Yup, Inkeep's Analytics API is fully compatible with OpenAI chat completion endpoints, including tool calling.",
      "name": null,
      "links": null,
      "properties": {},
      "userProperties": {}
    }
  ],
  "messagesOpenAIFormat": [
    {
      "role": "user",
      "content": "Can I log any OpenAI-compatible conversation?"
    },
    {
      "role": "assistant",
      "content": "Yes, Inkeep's analytics engine is agnostic. You can log full conversations of your agent or custom copilot, even if not all interactions hit Inkeep's API endpoint."
    },
    {
      "role": "user",
      "content": "Does that mean it supports logging tool calls?"
    },
    {
      "role": "assistant",
      "content": "Yup, Inkeep's Analytics API is fully compatible with OpenAI chat completions endpoints, including tool calling."
    }
  ]
}

This response includes all extended details about the conversation and its messages, including any properties you associated with it.

The messagesOpenAIFormat property provides the messages of the conversation in a format compatible with OpenAI's chat completions API. You can use this to implement Share a chat, Saved Chats, or any other functionality that requires retrieving an existing chat.

Here's how:

Share a chat - Create an entry point in your application or UI that parses a query parameter, e.g. ?chatId=<id>. Then, use the GET /conversations/{id} endpoint to get the last state of a conversation and hydrate the chat UI in your own application. If you want to be able to "fork" shared chats, then simply use a different id when logging the continuation of a shared conversation to POST /conversations. This will log it as a separate conversation from the original.
Saved Chats - Whenever a user creates a new conversation, associate that id with the user in your database or application. This way, you have a relationship of chats<>user and can display a user's history in your UI. You can also store that relationship in a user's browser session for unauthenticated contexts.

Log usage events

In addition to logging conversations and feedback, you can also track specific usage events related to conversations or messages using the /events endpoint.

For example, you may want to track events like:

message:copied: When a user copies a message
message:code_snippet:copied: When a user runs a code snippet from a message
conversation:shared: When a user shares a conversation

When logged, they will be incorporated in the Inkeep Analytics reporting.

The below shows an example of how to log these events.

log-event.js

// Message event
const eventData = {
  type: "message:copied",
  entityType: "message" // 'message' or 'conversation'
  messageId: "{message_id}",
};
 
fetch('https://api.analytics.inkeep.com/events', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify(eventData)
})
.then(response => response.json())
.then(data => console.log(data));
 
// Conversation Event
const conversationEventData = {
  type: "conversation:shared",
  entityType: "conversation"
  conversationId: "{conversation_id}",
};
 
fetch('https://api.analytics.inkeep.com/events', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify(conversationEventData)
})
.then(response => response.json())

Add analytics to any OpenAI compatible chat

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