> ## 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 conversations > Retrieve all conversations for a project with optional filtering. **Access Control:** - Admins see all conversations (including shared ones) - Regular users see only conversations they created (including their own shared ones) - Shared conversations from other users are not shown in the list but are accessible via direct URL **Impersonation:** - When using impersonation, returns conversations created by the impersonated user **Filtering:** - Tags filtering uses OR logic (matches any of the provided tags) - Text filtering uses AND logic (combined with tag filters) ## OpenAPI ````yaml /api-reference/openapi-full.yaml get /projects/{project_id}/playground-conversations/ 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}/playground-conversations/: get: tags: - Conversations summary: List conversations description: > Retrieve all conversations for a project with optional filtering. **Access Control:** - Admins see all conversations (including shared ones) - Regular users see only conversations they created (including their own shared ones) - Shared conversations from other users are not shown in the list but are accessible via direct URL **Impersonation:** - When using impersonation, returns conversations created by the impersonated user **Filtering:** - Tags filtering uses OR logic (matches any of the provided tags) - Text filtering uses AND logic (combined with tag filters) operationId: listConversations parameters: - $ref: '#/components/parameters/ProjectId' - $ref: '#/components/parameters/ImpersonateEmail' - name: tags in: query description: >- Filter by tags (OR logic). Can be specified multiple times or comma-separated. schema: type: array items: type: string style: form explode: true example: - analysis - review - name: no_tags in: query description: Set to "true" to filter for conversations with no tags schema: type: string enum: - 'true' - 'false' - name: text in: query description: Search text within chat history (case-insensitive) schema: type: string - name: include_archived in: query description: >- Set to "true" to include archived conversations in results. Defaults to false (active conversations only). schema: type: string enum: - 'true' - 'false' - $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/Conversation' '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 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 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: {} Conversation: type: object properties: id: type: string format: uuid name: type: string type: type: string created_by: type: string format: uuid description: ID of the user who created the conversation chat_history: type: array items: $ref: '#/components/schemas/ChatMessage' agent_settings: type: string format: uuid agent_settings_name: type: string created_at: type: string format: date-time updated_at: type: string format: date-time message_count: type: integer tool_call_count: type: integer tokens: type: object properties: input: type: integer output: type: integer total: type: integer tags: type: array items: type: string conversation_instructions: type: string nullable: true is_shared: type: boolean description: Whether the conversation is shared with all workspace members default: false can_send_messages: type: boolean description: > Whether the current user can send messages to this conversation. For shared conversations, only the creator and admins can send messages. is_archived: type: boolean description: Whether the conversation has been soft-archived default: false archived_at: type: string format: date-time nullable: true description: Timestamp when the conversation was archived, null if not archived ChatMessage: type: object description: > A message in the conversation. The `query_id` groups all messages from a single user interaction (user message, assistant response, tool calls). properties: role: type: string enum: - user - assistant content: type: string type: type: string enum: - message - tool_call - reasoning_flow query_id: type: integer description: > Unique identifier for this query. All messages from one interaction share the same query_id. Use this value when submitting feedback on a specific message. user_id: type: string format: uuid used_tokens_input: type: integer used_tokens_output: type: integer timestamp: type: string format: date-time tool_type: type: string description: Type of tool (only for tool_call messages) input_parameters: type: object description: Tool input parameters (only for tool_call messages) results: type: array items: {} description: Tool results (only for tool_call messages) 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.