> ## 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.

# List extraction flows

> List all extraction flows for the project, ordered by most recently updated.




## OpenAPI

````yaml /api-reference/openapi-full.yaml get /projects/{project_id}/extraction-flows/
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>`


    ## Organization API Key Authentication

    The user-provisioning endpoints authenticate with an **org-scoped API key**
    instead of a user token:

    - `Authorization: Api-Key <key>`


    The key is minted internally by Clarifeye (not self-service) and is scoped
    to a single

    organization — it can only act on the organization whose UUID matches the
    `{id}` in the

    request path. The email domains a key may pre-create accounts for are
    configured by

    Clarifeye on the organization (`allowed_provisioning_domains`). Once you
    have a key and

    your domains are set, call `POST /organizations/{id}/provision-user/` to
    pre-create users

    and `POST /organizations/{id}/deprovision-user/` to remove them.


    ## 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` (contact Clarifeye to
    enable this permission)


    **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
  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: 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: Api-Key <key>`). The organization is resolved from the
      key.
  - name: Organization API Keys
    description: >
      Superuser management of org-scoped provisioning API keys. Minting and
      revoking

      are superuser-only; org admins can list/retrieve/reveal 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 cohesion guide, 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}/extraction-flows/:
    get:
      tags:
        - Extraction Flows
      summary: List extraction flows
      description: >
        List all extraction flows for the project, ordered by most recently
        updated.
      operationId: listExtractionFlows
      parameters:
        - $ref: '#/components/parameters/ProjectId'
      responses:
        '200':
          description: Successful response
          content:
            application/json:
              schema:
                type: array
                items:
                  $ref: '#/components/schemas/ExtractionFlow'
        '401':
          $ref: '#/components/responses/Unauthorized'
        '403':
          $ref: '#/components/responses/Forbidden'
        '404':
          $ref: '#/components/responses/NotFound'
components:
  parameters:
    ProjectId:
      name: project_id
      in: path
      required: true
      description: UUID of the project
      schema:
        type: string
        format: uuid
  schemas:
    ExtractionFlow:
      type: object
      properties:
        id:
          type: string
          format: uuid
        name:
          type: string
        publish_mode:
          $ref: '#/components/schemas/ExtractionFlowPublishMode'
        dag:
          $ref: '#/components/schemas/ExtractionFlowDag'
        tpuf_namespaces:
          type: object
          description: >-
            Per-namespace-type TurboPuffer namespace mapping populated on
            publish.
        last_pushed_to_tpuf:
          type: string
          format: date-time
          nullable: true
        created_at:
          type: string
          format: date-time
        updated_at:
          type: string
          format: date-time
    ExtractionFlowPublishMode:
      type: string
      enum:
        - auto_publish
        - manual_publish
      description: >
        - `auto_publish` — runs automatically push extracted data to downstream
        indexes.

        - `manual_publish` — publishing is triggered explicitly via the
        `publish` action.
    ExtractionFlowDag:
      type: object
      description: |
        DAG describing the extractor pipeline. PATCH replaces the stored DAG
        verbatim — there is no node-level patch endpoint.
      required:
        - name
        - nodes
      properties:
        name:
          type: string
          example: extraction_flow
        nodes:
          type: array
          items:
            $ref: '#/components/schemas/ExtractionFlowDagNode'
    Error:
      type: object
      properties:
        error:
          type: string
          description: Error message
      example:
        error: User not found
    ExtractionFlowDagNode:
      type: object
      description: |
        A single node in an extraction flow's DAG. Each node binds an extractor
        class + version to a position in the pipeline. Node names must be unique
        within a DAG; the editor auto-numbers collisions (e.g. `tag_extractor`,
        `tag_extractor_1`).
      required:
        - node_name
        - extractor
        - acceptable_versions
        - processing_version
        - inputs
        - outputs
      properties:
        node_name:
          type: string
          description: Unique identifier of the node within its DAG.
          example: tag_extractor
        extractor:
          type: string
          description: >
            Extractor class. Known values include `ParsingExtractor`,

            `BlocksExtractor`, `ChunksExtractor`, `TagExtractor`,

            `ObjectExtractor`, `DocumentTagExtractor`,
            `DocumentFilterExtractor`,

            `ChunkTagFilterExtractor`.
          example: TagExtractor
        extractor_id:
          type: string
          format: uuid
          description: >-
            ID of the extractor instance configured in the project. Optional on
            input.
        acceptable_versions:
          type: array
          items:
            type: string
          description: Extractor version IDs accepted for cache reuse.
        processing_version:
          type: string
          description: >-
            Extractor version used for new computations. Must appear in
            `acceptable_versions`.
        inputs:
          type: object
          additionalProperties:
            type: string
          description: |
            Map of input slot name to upstream table reference. Send as `{}` on
            create / edit — the backend fills it via `resolve_dag_tables()`.
        outputs:
          type: object
          additionalProperties:
            type: string
          description: |
            Map of output slot name to produced table reference. Send as `{}` on
            create / edit — the backend fills it.
        depends_on:
          type: array
          items:
            type: string
          description: |
            Names of upstream nodes this node depends on. Each entry must match
            another node's `node_name` in the same DAG.
        filter_items_type:
          type: string
          description: >-
            Only set for `DocumentFilterExtractor` / `ChunkTagFilterExtractor`
            nodes.
        params:
          type: object
          description: >-
            Free-form extractor parameters. Optional; usually populated by the
            backend from the extractor version.
  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>'
    TokenAuth:
      type: apiKey
      in: header
      name: Authorization
      description: 'Use Authorization: Token <token>'

````

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