Ender Turing

This API gives you an AI “analysis chat” over your conversation data. Think of it as a stateful assistant: you create a chat once, then keep asking follow-up questions in the same thread.

<code>GET /api/v1/ender-chat</code>: list existing chat sessions (history/inbox view).

<code>POST /api/v1/ender-chat</code>: create a new chat and send the first question.

<code>GET /api/v1/ender-chat/{chat_id}</code>: fetch one chat with full messages and current processing state.

<code>POST /api/v1/ender-chat/{chat_id}</code>: send next question in an existing chat.

<code>PATCH /api/v1/ender-chat/{chat_id}</code>: rename/deactivate/update chat metadata.

- <code>GET /api/v1/ender-chat</code>: list existing chat sessions (history/inbox view).
- <code>POST /api/v1/ender-chat</code>: create a new chat and send the first question.
- <code>GET /api/v1/ender-chat/{chat_id}</code>: fetch one chat with full messages and current processing state.
- <code>POST /api/v1/ender-chat/{chat_id}</code>: send next question in an existing chat.
- <code>PATCH /api/v1/ender-chat/{chat_id}</code>: rename/deactivate/update chat metadata.

2. Important behavior (very important for integrations)

<code>POST /ender-chat</code> and <code>POST /ender-chat/{chat_id}</code> return quickly after queueing work.

You must poll <code>GET /ender-chat/{chat_id}</code> to see progress and responses.

- <code>is_active = true</code>
- <code>workflow_state = waiting_for_user</code>

- Processing is asynchronous.
- <code>POST /ender-chat</code> and <code>POST /ender-chat/{chat_id}</code> return quickly after queueing work.
- You must poll <code>GET /ender-chat/{chat_id}</code> to see progress and responses.
- The next question is accepted only when:
 - <code>is_active = true</code>
 - <code>workflow_state = waiting_for_user</code>

Poll chat until <code>workflow_state</code> becomes <code>waiting_for_user</code>.

Read the newest AI response in <code>messages</code>.

Send a follow-up question to the same <code>chat_id</code>.

1. Create a chat with the first question.
2. Read returned <code>chat_id</code>.
3. Poll chat until <code>workflow_state</code> becomes <code>waiting_for_user</code>.
4. Read the newest AI response in <code>messages</code>.
5. Send a follow-up question to the same <code>chat_id</code>.
6. Repeat.

4. Human-friendly integration tips

Always save <code>chat_id</code> client-side after create.

Show a “thinking” state while the workflow is not <code>waiting_for_user</code>.

If the user sends a message too early, handle <code>400</code> and retry after polling.

Use <code>PATCH /ender-chat/{chat_id}</code> to rename chats so history is readable.

Keep questions focused and specific; broad questions often need multiple iterations.

- Always save <code>chat_id</code> client-side after create.
- Show a “thinking” state while the workflow is not <code>waiting_for_user</code>.
- If the user sends a message too early, handle <code>400</code> and retry after polling.
- Use <code>PATCH /ender-chat/{chat_id}</code> to rename chats so history is readable.
- Keep questions focused and specific; broad questions often need multiple iterations.

<code>404 Chat session not found</code>: wrong or deleted <code>chat_id</code>.

<code>400 Chat session is not active</code>: chat was deactivated.

<code>400 Chat session is not ready for user input</code>: still processing previous question.

<code>400 project_id and unassigned_only cannot be used together</code> on the list endpoint.

- <code>404 Chat session not found</code>: wrong or deleted <code>chat_id</code>.
- <code>400 Chat session is not active</code>: chat was deactivated.
- <code>400 Chat session is not ready for user input</code>: still processing previous question.
- <code>400 project_id and unassigned_only cannot be used together</code> on the list endpoint.

I can also turn this into ready-to-paste endpoint descriptions for your Help Center article format if you want.

Ender GPT Chats API - Generative Analytics

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Ender GPT Chats API - Generative Analytics

1. What each endpoint is for

2. Important behavior (very important for integrations)

3. Typical flow

4. Human-friendly integration tips

5. Common errors to expect