> ## Documentation Index
> Fetch the complete documentation index at: https://docs.clarifeye.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Retry a failed turn (async)

> Answer again the user message the conversation's last turn failed to answer
(its `chat_history` ends with a `turn_error` entry), and return `202 Accepted`;
poll the `poll` endpoint as after `send_message`.

The `turn_error` entry is removed and the message is not sent again: the tool
calls the failed turn completed stay in the history, so they are not redone.
A conversation on the V1 assistant drops the failed turn and sends its message
again instead.

A turn fails, and is closed by a `turn_error` entry, when the model provider
stays unavailable after the automatic retries, or on an unexpected error.
The entry carries `category` (`provider_unavailable`, `provider_declined` or
`unexpected`), a user-facing `content` and an `error_ref`.

**Access Control:** as `send_message`.




## OpenAPI

````yaml /api-reference/openapi-full.yaml post /projects/{project_id}/playground-conversations/{conversation_id}/retry-turn/
openapi: 3.0.3
info:
  title: Clarifeye Platform API — Full API Documentation
  description: >
    Complete REST API reference for the Clarifeye Platform.


    Documents every endpoint exposed by the platform — the public surface plus

    the advanced surface: pipeline customization (extraction flows, pipeline

    runs, warehouse tables, document tag/metadata configuration), the pre-MCP

    AI surface (agent settings, playground conversations, conversation-scoped

    feedback views, notifications), and the impersonation header. New AI

    integrations should consume knowledge via MCP rather than the

    conversation/agent-settings endpoints documented here.


    ## Authentication

    All endpoints require authentication. Include the Authorization header in
    every request using either format:

    - `Authorization: Token <token_key>`

    - `Authorization: Bearer <token_key>`


    ## Service accounts and API keys

    Integrations authenticate with an **API key** of a **service account**:

    - `Authorization: Bearer <key>` (keys start with `cfk_`)


    A service account is an ordinary member (role `member`) of one organization
    that cannot log

    in. Organization admins create it and mint its keys on the organization's
    *Service

    accounts* page (`/organizations/{id}/service-accounts/`,
    `/organization-api-keys/`), and

    give it access to knowledge stores with ordinary store permissions. A key is
    valid on every

    endpoint and acts as its service account: it reaches exactly the stores,
    with exactly the

    rights, the account was given. An account can hold several keys (each with
    its own name,

    optional expiry and revocation), so a key can be rotated without changing
    identity.


    A refused key answers **403** with one of: `Invalid API key.`, `API key
    revoked.`,

    `API key expired.`, `API key disabled.` (the service account is disabled).


    Any valid key may also call `POST /organizations/{id}/provision-user/` and

    `POST /organizations/{id}/deprovision-user/` for its own organization (the
    `{id}` in the

    path must be the key's organization). The email domains these may pre-create
    accounts for

    are configured by Clarifeye on the organization
    (`allowed_provisioning_domains`).


    ## Impersonation


    Certain endpoints support user impersonation for creating or listing data on
    behalf of other users.

    This is useful for integrating external systems that need to attribute
    actions to specific users.


    **Header:** `X-Impersonate-Email`


    **Required Permission:** `CAN_IMPERSONATE_OTHER_USERS` (for a person,
    contact Clarifeye to enable it; org admins grant it to a service account on
    the organization's Service accounts page)


    **Behavior:**

    - If the header is provided and the impersonator has the required
    permission, the action is performed as the target user

    - If the target user is not found, the request proceeds as the original
    authenticated user

    - If the target user does not have access to the project, the request
    proceeds as the original authenticated user

    - If the impersonator lacks the `CAN_IMPERSONATE_OTHER_USERS` permission,
    the header is ignored


    **With an API key** the request fails instead (**403**) whenever
    impersonation cannot

    happen: missing permission, unknown target, target without access to the
    store, target that

    is itself a service account, or an endpoint outside a store. A key never
    silently acts as

    its own service account when impersonation was asked for.
  version: 1.0.0
  contact:
    name: Clarifeye Support
servers:
  - url: https://eu.app.clarifeye.ai/api/v1
    description: EU
  - url: https://us.app.clarifeye.ai/api/v1
    description: US
security:
  - BearerAuth: []
  - TokenAuth: []
tags:
  - name: Users
    description: Manage users within a project
  - name: Invitations
    description: Manage project invitations
  - name: Documents
    description: Manage documents within a project
  - name: Agent Settings
    description: Manage AI agent configurations
  - name: Conversations
    description: Create and interact with AI-powered conversations
  - name: Interviews
    description: Assign and review structured interview conversations
  - name: Meetings
    description: >-
      Meetings Clara attends as a bot (Recall.ai) — live transcript, live
      insights, recording, and calendar scheduling (CLA-1843). Store admins
      only.
  - name: Feedback
    description: >-
      Submit and review feedback — standalone (content-only), agent-submitted
      (MCP), or linked to a conversation message
  - name: Tools
    description: Execute configured AI tools with custom parameters
  - name: Tables
    description: Perform CRUD operations on warehouse tables
  - name: Notifications
    description: Manage project-scoped notifications for users
  - name: Extraction Flows
    description: >-
      Manage extraction flows (auto-sync DAGs) — list, run, inspect statistics,
      update, and publish
  - name: Object Extractors
    description: |
      Extract structured data (instances of a Pydantic model) from chunks or
      blocks of documents. Update auto-creates a new `ObjectExtractorVersion`
      when version-bearing fields change.
  - name: Tag Extractors
    description: |
      Apply hierarchical metadata tags to chunks or documents using an LLM.
      Update auto-creates a new `TagExtractorVersion` when version-bearing
      fields change.
  - name: Chunks Extractors
    description: |
      Segment parsed documents into chunks for downstream processing.
      Update auto-creates a new `ChunksExtractorVersion` when version-bearing
      fields change.
  - name: Parsing Extractors
    description: |
      Convert source documents to text blocks via the parsing pipeline.
      Update auto-creates a new `ParsingExtractorVersion` when version-bearing
      fields change.
  - name: Document Filter Extractors
    description: |
      Restrict a downstream pipeline branch to documents matching a filter.
      Update auto-creates a new version when the filter changes.
  - name: Chunk Tag Filter Extractors
    description: |
      Restrict a downstream pipeline branch to chunks carrying specific tags.
      Update auto-creates a new version when the filter changes.
  - name: Document Tag Extractors
    description: |
      Apply a flat set of metadata tags to each document. Update auto-creates
      a new version when version-bearing fields change.
  - name: Tag Alerts Extractors
    description: |
      Run LLM-based alerts over already-extracted tag rows. Update auto-creates
      a new version when version-bearing fields change.
  - name: Object Alerts Extractors
    description: >
      Run LLM-based alerts over already-extracted object rows. Update
      auto-creates

      a new version when version-bearing fields change.
  - name: Imported Object Extractors
    description: |
      Hold objects imported from an external system (rather than extracted by
      an LLM). Useful for hydrating the warehouse with data produced outside
      the platform.
  - name: Pipeline Runs
    description: >-
      Inspect pipeline runs queued by extraction flows or other pipeline
      triggers — list runs and fetch the details/status of a single run
  - name: User Provisioning
    description: >
      Pre-create and de-provision org users via an org-scoped API key

      (`Authorization: Bearer <key>`). The organization is resolved from the
      key.
  - name: Organization API Keys
    description: |
      Management of org-scoped provisioning API keys. Org admins can mint, list,
      retrieve, update, reveal, and revoke their own org's keys.
  - name: Design System Templates
    description: Reference/example files attached to a design template.
  - name: Artifacts
    description: |
      Knowledge-store artifact catalog — list artifacts, create/edit custom
      artifacts, manage scope membership, read and publish versions, configure
      the store map, and export/import the whole catalog. For type-aware
      reads and edits of artifact content, prefer the
      `read-write-*-artifact` tool endpoints.
paths:
  /projects/{project_id}/playground-conversations/{conversation_id}/retry-turn/:
    post:
      tags:
        - Conversations
      summary: Retry a failed turn (async)
      description: >
        Answer again the user message the conversation's last turn failed to
        answer

        (its `chat_history` ends with a `turn_error` entry), and return `202
        Accepted`;

        poll the `poll` endpoint as after `send_message`.


        The `turn_error` entry is removed and the message is not sent again: the
        tool

        calls the failed turn completed stay in the history, so they are not
        redone.

        A conversation on the V1 assistant drops the failed turn and sends its
        message

        again instead.


        A turn fails, and is closed by a `turn_error` entry, when the model
        provider

        stays unavailable after the automatic retries, or on an unexpected
        error.

        The entry carries `category` (`provider_unavailable`,
        `provider_declined` or

        `unexpected`), a user-facing `content` and an `error_ref`.


        **Access Control:** as `send_message`.
      operationId: retryConversationTurn
      parameters:
        - $ref: '#/components/parameters/ProjectId'
        - $ref: '#/components/parameters/ConversationId'
        - $ref: '#/components/parameters/ImpersonateEmail'
      responses:
        '202':
          description: Retry accepted and enqueued; poll for progress
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ConversationTurnPoll'
        '400':
          description: The last turn did not fail, so there is nothing to retry
        '401':
          $ref: '#/components/responses/Unauthorized'
        '403':
          $ref: '#/components/responses/Forbidden'
        '404':
          $ref: '#/components/responses/NotFound'
        '409':
          description: A turn is already in progress for this conversation
components:
  parameters:
    ProjectId:
      name: project_id
      in: path
      required: true
      description: UUID of the project
      schema:
        type: string
        format: uuid
    ConversationId:
      name: conversation_id
      in: path
      required: true
      description: UUID of the conversation
      schema:
        type: string
        format: uuid
    ImpersonateEmail:
      name: X-Impersonate-Email
      in: header
      required: false
      description: >
        Email of the user to impersonate. Requires `CAN_IMPERSONATE_OTHER_USERS`
        permission.

        If the target user is not found or does not have access to the project,
        the request

        proceeds as the authenticated user. Contact Clarifeye to enable this
        permission.
      schema:
        type: string
        format: email
  schemas:
    ConversationTurnPoll:
      type: object
      description: >
        In-flight turn state returned by the async `send_message` (202) and
        `poll`

        endpoints for playground and Work-with-Clara conversations.
      properties:
        id:
          type: string
          format: uuid
        turn_status:
          type: string
          enum:
            - idle
            - running
            - failed
          description: Lifecycle of the current chat turn
        turn_error:
          type: string
          description: >
            User-facing reason when turn_status is failed (empty otherwise).
            Never

            the raw exception: the `error_ref` in the `streaming_error` payload
            finds it.
        turn_events:
          type: array
          description: >
            Accumulated message-level events for the current turn. Each item
            mirrors

            a former SSE frame: `{type_streaming, payload}` where type_streaming
            is

            one of streaming_in_progress, streaming_error, streaming_completed,
            or

            quick_replies_ready (Clara only). A `streaming_error` payload
            carries

            `category` (`provider_unavailable`, `provider_declined`,
            `unexpected`),

            `error_ref` and `content`; the turn is then closed in `chat_history`
            by a

            `turn_error` entry, answerable with `retry-turn`.
          items:
            type: object
            properties:
              type_streaming:
                type: string
              payload:
                type: object
        updated_at:
          type: string
          format: date-time
          description: Last activity timestamp; doubles as the turn staleness heartbeat
    Error:
      type: object
      properties:
        error:
          type: string
          description: Error message
      example:
        error: User not found
  responses:
    Unauthorized:
      description: Unauthorized - missing or invalid authentication
      content:
        application/json:
          schema:
            $ref: '#/components/schemas/Error'
          example:
            error: Authentication credentials were not provided.
    Forbidden:
      description: Forbidden - insufficient permissions
      content:
        application/json:
          schema:
            $ref: '#/components/schemas/Error'
          example:
            error: You do not have permission to perform this action.
    NotFound:
      description: Not found - resource does not exist
      content:
        application/json:
          schema:
            $ref: '#/components/schemas/Error'
          example:
            error: Not found.
  securitySchemes:
    BearerAuth:
      type: http
      scheme: bearer
      description: >
        Use `Authorization: Bearer <token>`. The token is either a user token /
        OAuth access

        token, or a service-account API key (`cfk_...`). A key is valid on every
        endpoint and

        acts as its service account, an organization member with per-store
        permissions.

        Refused keys answer 403 with `Invalid API key.`, `API key revoked.`,

        `API key expired.` or `API key disabled.`.
    TokenAuth:
      type: apiKey
      in: header
      name: Authorization
      description: 'Use Authorization: Token <token>'

````

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