> ## 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 object extractors > List all `ObjectExtractor` rows in the project, newest first. ## OpenAPI ````yaml /api-reference/openapi-full.yaml get /projects/{project_id}/object-extractors/ 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 ` - `Authorization: Bearer ` ## Organization API Key Authentication The user-provisioning endpoints authenticate with an **org-scoped API key** instead of a user token: - `Authorization: Api-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 `). 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}/object-extractors/: get: tags: - Object Extractors summary: List object extractors description: List all `ObjectExtractor` rows in the project, newest first. operationId: listObjectExtractors parameters: - $ref: '#/components/parameters/ProjectId' - $ref: '#/components/parameters/Limit' - $ref: '#/components/parameters/Offset' responses: '200': description: Successful response content: application/json: schema: allOf: - $ref: '#/components/schemas/PaginatedResponse' - type: object properties: results: type: array items: $ref: '#/components/schemas/ObjectExtractor' '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 Limit: name: limit in: query description: Maximum number of results per page schema: type: integer default: 100 minimum: 1 maximum: 1000 Offset: name: offset in: query description: Number of results to skip for pagination schema: type: integer default: 0 minimum: 0 schemas: PaginatedResponse: type: object properties: count: type: integer description: Total number of results next: type: string format: uri nullable: true description: URL to next page of results previous: type: string format: uri nullable: true description: URL to previous page of results results: type: array items: {} ObjectExtractor: type: object description: | Extracts structured data (instances of a Pydantic model) from chunks or blocks of documents. properties: id: type: string format: uuid readOnly: true name: type: string description: Human-readable name. example: Contract clauses brief: type: string description: Short description shown in the UI. example: Extract obligations and effective dates from contracts. llm_model: type: string example: gpt-4o extractable_object: type: string nullable: true description: >- Display name of the object class (auto-derived from `extractable_pydantic_class` if omitted). example: ContractClause extractable_pydantic_class: type: string description: Python source of the Pydantic model used as the extraction schema. example: | from pydantic import BaseModel from typing import Optional class ContractClause(BaseModel): clause_type: str text: str effective_date: Optional[str] = None extraction_prompt: type: string example: >- Extract every distinct contractual obligation as a separate ContractClause object. document_ids: type: array items: type: string format: uuid description: >- Documents to extract from. Empty array means "all documents in the project". example: - b3c1d2e4-5f6a-4b7c-8d9e-0a1b2c3d4e5f document_ranges: type: object nullable: true description: >- Optional per-document page-range filter (`{document_id: [start_page, end_page]}`). compute_alerts: type: boolean default: false example: false add_anchoring_object: type: boolean default: false example: true filtered_on_block_types: type: boolean nullable: true block_types: type: array items: type: string nullable: true example: - text - table extract_single_object: type: boolean default: false block_grouping_config: type: object nullable: true pre_execution_filter: type: object nullable: true description: Filter applied to the source chunks/blocks before extraction runs. alerts_additional_instructions: type: string nullable: true alerts_llm_model: type: string nullable: true extraction_mode: type: string enum: - standard - agentic default: standard agentic_config: type: object nullable: true description: Configuration for `agentic` extraction mode. import_mode: type: boolean writeOnly: true default: false description: >- Bulk-import flag. When `true`, the create endpoint skips auto-version creation. created_at: type: string format: date-time readOnly: true updated_at: type: string format: date-time readOnly: true prompt_generation_status: type: string nullable: true readOnly: true deployed_extractable_pydantic_class: type: string nullable: true readOnly: true deployed_extraction_prompt: type: string nullable: true readOnly: true deployed_llm_model: type: string nullable: true readOnly: true extracted_objects_table: type: string format: uuid nullable: true readOnly: true description: ID of the warehouse `Table` where extracted objects are stored. alerts_table: type: string format: uuid nullable: true readOnly: true object_name: type: string readOnly: true blocks_table_version_info: type: object nullable: true readOnly: true chunks_table_version_info: type: object nullable: true readOnly: true table_version_updates: type: object nullable: true readOnly: true versions: type: array readOnly: true items: $ref: '#/components/schemas/ObjectExtractorVersion' default_version: allOf: - $ref: '#/components/schemas/ObjectExtractorVersion' nullable: true readOnly: true latest_version: allOf: - $ref: '#/components/schemas/ObjectExtractorVersion' nullable: true readOnly: true ObjectExtractorVersion: type: object description: > Immutable snapshot of an `ObjectExtractor`'s version-bearing configuration. New version rows are created automatically on PATCH when any of these fields differs from the latest version. properties: id: type: string format: uuid readOnly: true name: type: string readOnly: true created_at: type: string format: date-time readOnly: true updated_at: type: string format: date-time readOnly: true is_default: type: boolean readOnly: true description: Whether this version is the default version used by `run`. extractable_pydantic_class: type: string description: Python source of the Pydantic model used as the extraction schema. example: | from pydantic import BaseModel from typing import Optional class ContractClause(BaseModel): clause_type: str text: str effective_date: Optional[str] = None extraction_prompt: type: string example: >- Extract every distinct contractual obligation as a separate ContractClause object. llm_model: type: string example: gpt-4o add_anchoring_object: type: boolean example: true filtered_on_block_types: type: boolean nullable: true block_types: type: array items: type: string nullable: true example: - text - table extract_single_object: type: boolean example: false block_grouping_config: type: object nullable: true description: >- Optional configuration controlling how blocks are grouped before extraction. alerts_additional_instructions: type: string nullable: true extraction_mode: type: string enum: - standard - agentic default: standard nullable: true agentic_config: type: object nullable: true description: Configuration for `agentic` extraction mode. 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 ' TokenAuth: type: apiKey in: header name: Authorization description: 'Use Authorization: Token ' ```` This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.