Create and assign interviews

import requests

url = "https://eu.app.clarifeye.ai/api/v1/projects/{project_id}/interviews/assign/"

payload = {
    "assignee_ids": ["3fa85f64-5717-4562-b3fc-2c963f66afa6"],
    "invite_emails": ["[email protected]"],
    "topic": "Q4 planning and roadmap review",
    "write_scope": "local",
    "campaign_name": "Q4 expert workshop wave"
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    assignee_ids: ['3fa85f64-5717-4562-b3fc-2c963f66afa6'],
    invite_emails: ['[email protected]'],
    topic: 'Q4 planning and roadmap review',
    write_scope: 'local',
    campaign_name: 'Q4 expert workshop wave'
  })
};

fetch('https://eu.app.clarifeye.ai/api/v1/projects/{project_id}/interviews/assign/', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

curl --request POST \
  --url https://eu.app.clarifeye.ai/api/v1/projects/{project_id}/interviews/assign/ \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "assignee_ids": [
    "3fa85f64-5717-4562-b3fc-2c963f66afa6"
  ],
  "invite_emails": [
    "[email protected]"
  ],
  "topic": "Q4 planning and roadmap review",
  "write_scope": "local",
  "campaign_name": "Q4 expert workshop wave"
}
'

[
  {
    "id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "name": "<string>",
    "created_by": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "created_by_email": "[email protected]",
    "type": "<string>",
    "type_additional_parameters": {},
    "chat_history": [
      {}
    ],
    "chat_memory": {},
    "local_documents": [
      "3c90c3cc-0d44-4b50-8888-8dd25736052a"
    ],
    "assigned_to": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "assigned_by": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "assigned_to_email": "[email protected]",
    "assigned_by_email": "[email protected]",
    "is_pending_invite": true,
    "topics": [
      {
        "title": "<string>",
        "description": "<string>",
        "skill_id": "<string>"
      }
    ],
    "campaign": {
      "id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
      "name": "<string>"
    },
    "import_info": {
      "participants": [
        "<string>"
      ],
      "interview_date": "2023-12-25",
      "error": "<string>"
    },
    "created_at": "2023-11-07T05:31:56Z",
    "updated_at": "2023-11-07T05:31:56Z"
  }
]

{
  "error": "User not found"
}

{
  "error": "Authentication credentials were not provided."
}

{
  "error": "You do not have permission to perform this action."
}

{
  "error": "Not found."
}

Interviews

Create and assign interviews

Create and assign one interview per assignee. Admin only.

Provide existing project members via assignee_ids and/or new people to invite via invite_emails (at least one is required). Invitees are added as non-admin Contributors. A separate interview is created for each assignee and the response is the list of created interviews.

write_scope defaults to local. A global write scope requires every assignee to already be a project admin and cannot be combined with invite_emails.

campaign_id / campaign_name group the created interviews under an interview campaign (e.g. a workshop wave). campaign_id picks an existing campaign of the project; campaign_name reuses the project’s campaign with that name (case-insensitive) or creates it.

POST

projects

{project_id}

interviews

assign

Create and assign interviews

import requests

url = "https://eu.app.clarifeye.ai/api/v1/projects/{project_id}/interviews/assign/"

payload = {
    "assignee_ids": ["3fa85f64-5717-4562-b3fc-2c963f66afa6"],
    "invite_emails": ["[email protected]"],
    "topic": "Q4 planning and roadmap review",
    "write_scope": "local",
    "campaign_name": "Q4 expert workshop wave"
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    assignee_ids: ['3fa85f64-5717-4562-b3fc-2c963f66afa6'],
    invite_emails: ['[email protected]'],
    topic: 'Q4 planning and roadmap review',
    write_scope: 'local',
    campaign_name: 'Q4 expert workshop wave'
  })
};

fetch('https://eu.app.clarifeye.ai/api/v1/projects/{project_id}/interviews/assign/', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

curl --request POST \
  --url https://eu.app.clarifeye.ai/api/v1/projects/{project_id}/interviews/assign/ \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "assignee_ids": [
    "3fa85f64-5717-4562-b3fc-2c963f66afa6"
  ],
  "invite_emails": [
    "[email protected]"
  ],
  "topic": "Q4 planning and roadmap review",
  "write_scope": "local",
  "campaign_name": "Q4 expert workshop wave"
}
'

[
  {
    "id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "name": "<string>",
    "created_by": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "created_by_email": "[email protected]",
    "type": "<string>",
    "type_additional_parameters": {},
    "chat_history": [
      {}
    ],
    "chat_memory": {},
    "local_documents": [
      "3c90c3cc-0d44-4b50-8888-8dd25736052a"
    ],
    "assigned_to": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "assigned_by": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "assigned_to_email": "[email protected]",
    "assigned_by_email": "[email protected]",
    "is_pending_invite": true,
    "topics": [
      {
        "title": "<string>",
        "description": "<string>",
        "skill_id": "<string>"
      }
    ],
    "campaign": {
      "id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
      "name": "<string>"
    },
    "import_info": {
      "participants": [
        "<string>"
      ],
      "interview_date": "2023-12-25",
      "error": "<string>"
    },
    "created_at": "2023-11-07T05:31:56Z",
    "updated_at": "2023-11-07T05:31:56Z"
  }
]

{
  "error": "User not found"
}

{
  "error": "Authentication credentials were not provided."
}

{
  "error": "You do not have permission to perform this action."
}

{
  "error": "Not found."
}

Authorizations

Authorization

string

header

required

Use Authorization: Bearer

Path Parameters

project_id

string<uuid>

required

UUID of the project

Body

application/json

assignee_ids

string<uuid>[]

UUIDs of existing project members to interview (must be tech/contributor members).

invite_emails

string<email>[]

Email addresses of people to invite on the fly as non-admin Contributors and assign an interview.

topic

string

The interview focus. Used to auto-name the interview and seed its first question.

write_scope

enum<string>

default:local

Whether interview edits stay local to the conversation or write to the shared knowledge store.

Available options:

local,

global

campaign_id

string<uuid> | null

Existing campaign to group the created interviews under (must belong to the project). Wins over campaign_name when both are sent.

campaign_name

string

Campaign to group the created interviews under, by name: reuses the project's campaign with that name (case-insensitive) or creates it.

Response

Interviews created and assigned

string<uuid>

read-only

name

string | null

Interview title (auto-generated from the topic when not provided).

created_by

string<uuid>

read-only

UUID of the user who created the interview.

created_by_email

string<email> | null

read-only

Email of the user who created the interview (the importer, for imported interviews).

type

string

Conversation type: "interview" (standard), "guided-interview" (multi-topic), or "imported-interview" (a read-only transcript of an interview recorded outside the platform, created via the import-transcript endpoint).

type_additional_parameters

object

Free-form parameters associated with the conversation type.

chat_history

object[]

Ordered list of transcript entries (messages, tool calls, etc.).

chat_memory

object

Assistant memory state accumulated over the conversation.

local_documents

string<uuid>[]

read-only

UUIDs of documents scoped locally to this interview.

assigned_to

string<uuid> | null

read-only

UUID of the assigned user (null while a pending invite has not yet joined).

assigned_by

string<uuid> | null

read-only

UUID of the user who created the assignment.

assigned_to_email

string<email> | null

read-only

Assignee email, falling back to the invite email for not-yet-joined invitees.

assigned_by_email

string<email> | null

read-only

is_pending_invite

boolean

read-only

True when assigned to someone who has not yet joined the project.

topics

object[]

read-only

Guided interviews only: the ordered topic agenda seeded at assign time, with per-topic progress. Empty for every other interview type.

Show child attributes

campaign

object | null

Campaign this interview belongs to; null for ad hoc interviews.

Show child attributes

import_info

object | null

Parse-pipeline state of an imported external transcript (interviews of type "imported-interview"). Null on every other interview type. The raw submitted transcript is never returned — the parsed chat_history is the transcript.

Show child attributes

status

enum<string> | null

read-only

Null for imported interviews until their transcript parse completes.

Available options:

pending,

in_progress,

completed

write_scope

enum<string>

Whether edits stay local to the conversation or write to the shared knowledge store.

Available options:

local,

global

created_at

string<date-time>

read-only

updated_at

string<date-time>

read-only

List interviews Retrieve interview content