> ## Documentation Index > Fetch the complete documentation index at: https://docs.trieve.ai/llms.txt > Use this file to discover all available pages before exploring further. # Clone Dataset > Clones a dataset and creates a new dataset with the same configuration and chunks. The auth'ed user must be an owner of the organization to clone a dataset. ## OpenAPI ````yaml post /api/dataset/clone openapi: 3.0.3 info: title: Trieve API description: >- Trieve OpenAPI Specification. This document describes all of the operations available through the Trieve API. contact: name: Trieve Team url: https://trieve.ai email: developers@trieve.ai license: name: BSL url: https://github.com/devflowinc/trieve/blob/main/LICENSE.txt version: 0.13.0 servers: - url: https://api.trieve.ai description: Production server - url: http://localhost:8090 description: Local development server security: [] tags: - name: Invitation description: Invitation endpoint. Exists to invite users to an organization. - name: Auth description: Authentication endpoint. Serves to register and authenticate users. - name: User description: User endpoint. Enables you to modify user roles and information. - name: Organization description: >- Organization endpoint. Enables you to modify organization roles and information. - name: Dataset description: >- Dataset endpoint. Datasets belong to organizations and hold configuration information for both client and server. Datasets contain chunks and chunk groups. - name: Chunk description: >- Chunk endpoint. Think of chunks as individual searchable units of information. The majority of your integration will likely be with the Chunk endpoint. - name: Chunk Group description: >- Chunk groups endpoint. Think of a chunk_group as a bookmark folder within the dataset. - name: Crawl description: Crawl endpoint. Used to create and manage crawls for datasets. - name: File description: >- File endpoint. When files are uploaded, they are stored in S3 and broken up into chunks with text extraction from Apache Tika. You can upload files of pretty much any type up to 1GB in size. See chunking algorithm details at `docs.trieve.ai` for more information on how chunking works. Improved default chunking is on our roadmap. - name: Events description: >- Notifications endpoint. Files are uploaded asynchronously and events are sent to the user when the upload is complete. - name: Topic description: >- Topic chat endpoint. Think of topics as the storage system for gen-ai chat memory. Gen AI messages belong to topics. - name: Message description: >- Message chat endpoint. Messages are units belonging to a topic in the context of a chat with a LLM. There are system, user, and assistant messages. - name: Stripe description: >- Stripe endpoint. Used for the managed SaaS version of this app. Eventually this will become a micro-service. Reach out to the team using contact info found at `docs.trieve.ai` for more information. - name: Health description: Health check endpoint. Used to check if the server is up and running. - name: Metrics description: Metrics endpoint. Used to get information for monitoring - name: Analytics description: Analytics endpoint. Used to get information for search and RAG analytics - name: Experiment description: Experiment endpoint. Used to create and manage experiments paths: /api/dataset/clone: post: tags: - Dataset summary: Clone Dataset description: >- Clones a dataset and creates a new dataset with the same configuration and chunks. The auth'ed user must be an owner of the organization to clone a dataset. operationId: clone_dataset parameters: - name: TR-Organization in: header description: The organization id to use for the request required: true schema: type: string format: uuid requestBody: description: JSON request payload to clone a dataset content: application/json: schema: $ref: '#/components/schemas/CloneDatasetRequest' required: true responses: '200': description: Dataset cloned successfully content: application/json: schema: $ref: '#/components/schemas/Dataset' '400': description: Service error relating to cloning the dataset content: application/json: schema: $ref: '#/components/schemas/ErrorResponseBody' '404': description: Dataset not found content: application/json: schema: $ref: '#/components/schemas/ErrorResponseBody' components: schemas: CloneDatasetRequest: type: object required: - dataset_to_clone - dataset_name properties: clone_chunks: type: boolean description: >- Parameter to Clone Chunks from the original dataset to the new dataset. defaults to true. nullable: true dataset_name: type: string description: Name of the dataset. dataset_to_clone: type: string format: uuid description: The id of the dataset you want to clone. tracking_id: type: string description: >- Optional tracking ID for the dataset. Can be used to track the dataset in external systems. Must be unique within the organization. Strongly recommended to not use a valid uuid value as that will not work with the TR-Dataset header. nullable: true example: dataset_name: My Dataset dataset_to_clone: 00000000-0000-0000-0000-000000000000 organization_id: 00000000-0000-0000-0000-000000000000 server_configuration: AIMON_RERANKER_TASK_DEFINITION: >- Your task is to grade the relevance of context document(s) against the specified user query. BM25_AVG_LEN: 256 BM25_B: 0.75 BM25_ENABLED: true BM25_K: 0.75 DISTANCE_METRIC: cosine EMBEDDING_BASE_URL: https://api.openai.com/v1 EMBEDDING_MODEL_NAME: text-embedding-3-small EMBEDDING_QUERY_PREFIX: '' EMBEDDING_SIZE: 1536 FREQUENCY_PENALTY: 0 FULLTEXT_ENABLED: true INDEXED_ONLY: false LLM_BASE_URL: https://api.openai.com/v1 LLM_DEFAULT_MODEL: gpt-3.5-turbo-1106 LOCKED: false MAX_LIMIT: 10000 MESSAGE_TO_QUERY_PROMPT: >+ Write a 1-2 sentence semantic search query along the lines of a hypothetical response to: N_RETRIEVALS_TO_INCLUDE: 8 PRESENCE_PENALTY: 0 QDRANT_ONLY: false RAG_PROMPT: >- Use the following retrieved documents to respond briefly and accurately: SEMANTIC_ENABLED: true STOP_TOKENS: - |+ - |+ SYSTEM_PROMPT: You are a helpful assistant TEMPERATURE: 0.5 USE_MESSAGE_TO_QUERY_PROMPT: false Dataset: type: object required: - id - name - created_at - updated_at - organization_id - server_configuration - deleted properties: created_at: type: string format: date-time description: Timestamp of the creation of the dataset deleted: type: integer format: int32 description: >- Flag to indicate if the dataset has been deleted. Deletes are handled async after the flag is set so as to avoid expensive search index compaction. id: type: string format: uuid description: >- Unique identifier of the dataset, auto-generated uuid created by Trieve name: type: string description: Name of the dataset organization_id: type: string format: uuid description: Unique identifier of the organization that owns the dataset server_configuration: description: Configuration of the dataset for RAG, embeddings, BM25, etc. tracking_id: type: string description: >- Tracking ID of the dataset, can be any string, determined by the user. Tracking ID's are unique identifiers for datasets within an organization. They are designed to match the unique identifier of the dataset in the user's system. nullable: true updated_at: type: string format: date-time description: Timestamp of the last update of the dataset example: created_at: '2021-01-01 00:00:00.000' id: e3e3e3e3-e3e3-e3e3-e3e3-e3e3e3e3e3e3 name: Trieve organization_id: e3e3e3e3-e3e3-e3e3-e3e3-e3e3e3e3e3e3 server_configuration: AIMON_RERANKER_TASK_DEFINITION: >- Your task is to grade the relevance of context document(s) against the specified user query. BM25_AVG_LEN: 256 BM25_B: 0.75 BM25_ENABLED: true BM25_K: 0.75 DISTANCE_METRIC: cosine EMBEDDING_BASE_URL: https://embedding.trieve.ai EMBEDDING_MODEL_NAME: jina-base-en EMBEDDING_QUERY_PREFIX: '' EMBEDDING_SIZE: 768 FREQUENCY_PENALTY: 0 FULLTEXT_ENABLED: true INDEXED_ONLY: false LLM_BASE_URL: https://api.openai.com/v1 LLM_DEFAULT_MODEL: gpt-4o LOCKED: false MAX_LIMIT: 10000 MESSAGE_TO_QUERY_PROMPT: >+ Write a 1-2 sentence semantic search query along the lines of a hypothetical response to: N_RETRIEVALS_TO_INCLUDE: 8 PRESENCE_PENALTY: 0 QDRANT_ONLY: false RAG_PROMPT: >- Use the following retrieved documents to respond briefly and accurately: SEMANTIC_ENABLED: true STOP_TOKENS: - |+ - |+ SYSTEM_PROMPT: You are a helpful assistant TEMPERATURE: 0.5 USE_MESSAGE_TO_QUERY_PROMPT: false tracking_id: foobar-dataset updated_at: '2021-01-01 00:00:00.000' ErrorResponseBody: type: object required: - message properties: message: type: string example: message: Bad Request ````