aid: cohere url: https://raw.githubusercontent.com/api-evangelist/cohere/refs/heads/main/apis.yml apis: - aid: cohere:chat-api name: Cohere Chat API tags: - Artificial Intelligence - Chat - Conversational AI - Large Language Models - Text Generation image: https://kinlane-productions2.s3.amazonaws.com/apis-json/apis-json-logo.jpg baseURL: https://api.cohere.com humanURL: https://docs.cohere.com/reference/chat properties: - url: https://docs.cohere.com/reference/chat type: Documentation - url: openapi/cohere-chat-api-openapi.yml type: OpenAPI - type: NaftikoCapability url: capabilities/chat-chat.yaml description: The Cohere Chat API enables developers to integrate large language model text generation capabilities into their applications through a conversational interface. It supports multi-turn conversations, tool use with JSON schema definitions, retrieval-augmented generation, and streaming responses. The API is available via the v2 endpoint and works with Cohere's Command family of models. - aid: cohere:embed-api name: Cohere Embed API tags: - Artificial Intelligence - Embeddings - Natural Language Processing - Semantic Search - Vector Search image: https://kinlane-productions2.s3.amazonaws.com/apis-json/apis-json-logo.jpg baseURL: https://api.cohere.com humanURL: https://docs.cohere.com/reference/embed properties: - url: https://docs.cohere.com/reference/embed type: Documentation - url: openapi/cohere-embed-api-openapi.yml type: OpenAPI - type: NaftikoCapability url: capabilities/embed-embed.yaml description: The Cohere Embed API generates vector embeddings from text and images, enabling semantic search, clustering, and classification use cases. It supports multilingual content and can process both text and image inputs using the Embed v3 model family. Developers can use these embeddings to build retrieval systems, recommendation engines, and other applications that require understanding semantic similarity between content. - aid: cohere:rerank-api name: Cohere Rerank API tags: - Artificial Intelligence - Information Retrieval - Relevance - Reranking - Search image: https://kinlane-productions2.s3.amazonaws.com/apis-json/apis-json-logo.jpg baseURL: https://api.cohere.com humanURL: https://docs.cohere.com/reference/rerank properties: - url: https://docs.cohere.com/reference/rerank type: Documentation - url: openapi/cohere-rerank-api-openapi.yml type: OpenAPI - type: NaftikoCapability url: capabilities/rerank-rerank.yaml description: The Cohere Rerank API takes a query and a list of text documents and returns them ordered by relevance with assigned relevance scores. It is commonly used as a second-stage ranker in retrieval-augmented generation pipelines to improve the quality of search results before passing them to a language model. The API supports multilingual reranking and can significantly improve the precision of search and retrieval systems. - aid: cohere:classify-api name: Cohere Classify API tags: - Artificial Intelligence - Classification - Natural Language Processing - Text Analysis image: https://kinlane-productions2.s3.amazonaws.com/apis-json/apis-json-logo.jpg baseURL: https://api.cohere.com humanURL: https://docs.cohere.com/reference/classify properties: - url: https://docs.cohere.com/reference/classify type: Documentation - url: openapi/cohere-classify-api-openapi.yml type: OpenAPI - type: NaftikoCapability url: capabilities/classify-classify.yaml description: The Cohere Classify API performs text classification by assigning labels to input text based on provided examples. It can be used for sentiment analysis, content moderation, topic categorization, and other classification tasks. Developers provide a set of labeled examples along with texts to classify, and the API returns predicted labels with confidence scores for each input. - aid: cohere:embed-jobs-api name: Cohere Embed Jobs API tags: - Artificial Intelligence - Batch Processing - Embeddings - Vector Search image: https://kinlane-productions2.s3.amazonaws.com/apis-json/apis-json-logo.jpg baseURL: https://api.cohere.com humanURL: https://docs.cohere.com/reference/list-embed-jobs properties: - url: https://docs.cohere.com/reference/list-embed-jobs type: Documentation - url: openapi/cohere-embed-jobs-api-openapi.yml type: OpenAPI - type: NaftikoCapability url: capabilities/embed-jobs-embed-jobs.yaml description: The Cohere Embed Jobs API allows developers to create and manage batch embedding jobs for processing large volumes of text data asynchronously. Rather than embedding texts one at a time, developers can submit datasets for bulk embedding and monitor job progress. This is useful for initializing vector databases, processing large document collections, and other scenarios where embedding large amounts of content is needed. - aid: cohere:datasets-api name: Cohere Datasets API tags: - Artificial Intelligence - Data Management - Datasets - Fine-Tuning image: https://kinlane-productions2.s3.amazonaws.com/apis-json/apis-json-logo.jpg baseURL: https://api.cohere.com humanURL: https://docs.cohere.com/reference/list-datasets properties: - url: https://docs.cohere.com/reference/list-datasets type: Documentation - url: openapi/cohere-datasets-api-openapi.yml type: OpenAPI - type: NaftikoCapability url: capabilities/datasets-datasets.yaml description: The Cohere Datasets API provides endpoints for uploading, managing, and retrieving datasets used with other Cohere services such as fine-tuning and embed jobs. Developers can create datasets from files, list existing datasets, retrieve dataset metadata, and delete datasets they no longer need. The API supports various data formats and validates uploaded data against expected schemas. - aid: cohere:models-api name: Cohere Models API tags: - Artificial Intelligence - Machine Learning - Models image: https://kinlane-productions2.s3.amazonaws.com/apis-json/apis-json-logo.jpg baseURL: https://api.cohere.com humanURL: https://docs.cohere.com/reference/list-models properties: - url: https://docs.cohere.com/reference/list-models type: Documentation - url: openapi/cohere-models-api-openapi.yml type: OpenAPI - type: NaftikoCapability url: capabilities/models-models.yaml description: The Cohere Models API allows developers to list and retrieve information about available Cohere models, including the Command, Embed, and Rerank model families. It provides details such as model names, versions, supported endpoints, context lengths, and capabilities. This API is useful for programmatically discovering which models are available and selecting the appropriate model for a given task. - aid: cohere:tokenize-api name: Cohere Tokenize API tags: - Artificial Intelligence - Natural Language Processing - Text Processing - Tokenization image: https://kinlane-productions2.s3.amazonaws.com/apis-json/apis-json-logo.jpg baseURL: https://api.cohere.com humanURL: https://docs.cohere.com/reference/tokenize properties: - url: https://docs.cohere.com/reference/tokenize type: Documentation - url: openapi/cohere-tokenize-api-openapi.yml type: OpenAPI - type: NaftikoCapability url: capabilities/tokenize-tokenize.yaml description: The Cohere Tokenize API splits input text into tokens using the tokenizer associated with a specified model. It returns both the token strings and their corresponding token IDs. This is useful for understanding how text will be processed by Cohere models, estimating token counts for billing purposes, and debugging input formatting issues. - aid: cohere:detokenize-api name: Cohere Detokenize API tags: - Artificial Intelligence - Natural Language Processing - Text Processing - Tokenization image: https://kinlane-productions2.s3.amazonaws.com/apis-json/apis-json-logo.jpg baseURL: https://api.cohere.com humanURL: https://docs.cohere.com/reference/detokenize properties: - url: https://docs.cohere.com/reference/detokenize type: Documentation - url: openapi/cohere-detokenize-api-openapi.yml type: OpenAPI - type: NaftikoCapability url: capabilities/detokenize-detokenize.yaml description: The Cohere Detokenize API converts a sequence of token IDs back into their corresponding text string using the tokenizer for a specified model. It is the inverse operation of the Tokenize API and is useful for inspecting model outputs at the token level, debugging tokenization behavior, and reconstructing text from token representations. common: - type: GitHubOrganization url: https://github.com/cohere-ai - type: LinkedIn url: https://www.linkedin.com/company/cohere-ai - type: JSONLD url: json-ld/cohere-context.jsonld - type: JSONSchema url: json-schema/cohere-chat-message-schema.json - type: JSONSchema url: json-schema/cohere-embedding-schema.json - type: JSONSchema url: json-schema/cohere-model-schema.json - type: JSONSchema url: json-schema/cohere-dataset-schema.json - type: Features data: - Command at $1/$2 per MTok input/output - Command-light at $0.30/$0.60 - Command R at $0.50/$1.50 - Command R+ 08-2024 at $2.50/$10 - Command R+ 04-2024 at $3/$15 - Aya Expanse multilingual at $0.50/$1.50 - Embed v3 with English/multilingual - Rerank for relevance scoring - 'Production keys: 10K req/min Chat, 2K Embed, 10K Rerank' - 'Trial keys: 20/min Chat, 100/min Embed' - Connectors for RAG over data sources - Tool use and function calling - Compass for unstructured data search - Available on AWS Bedrock, Azure, Oracle Cloud - Fine-tuning for Command and Aya - OpenAI-compatible Chat Completions endpoint sources: - https://cohere.com/pricing updated: '2026-05-04' modified: '2026-05-19' description: Generates a text response to a user message and streams it down, token by token.