Cohere

api.cohere.com

Community

Cohere provides enterprise AI models for text generation, semantic search, and content analysis. It offers chat completion, text embeddings, document reranking, and text classification through a unified API.

Auth

api_key

Pricing

free

Spec version

1.0

Base URL

https://api.cohere.com

Crawl failures

1

Last verified

2026-03-01 11:53:14

Health

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Capabilities

chat

communication

Generate conversational responses using Cohere's language models. Supports multi-turn dialogue, tool use, document grounding, and structured JSON output.

Detail: https://api.cohere.com/capabilities/chat

chat_stream

communication

Generate conversational responses as a real-time stream of server-sent events for token-by-token display.

Detail: https://api.cohere.com/capabilities/chat_stream

classify_text

communication

Classify text inputs into predefined categories using few-shot examples. Useful for sentiment analysis, topic tagging, and content moderation.

Detail: https://api.cohere.com/capabilities/classify_text

embed_text

communication

Generate vector embeddings for text inputs, useful for semantic search, clustering, and classification tasks.

Detail: https://api.cohere.com/capabilities/embed_text

rerank_documents

communication

Reorder a list of documents by relevance to a search query, improving search result quality for RAG pipelines.

Detail: https://api.cohere.com/capabilities/rerank_documents

Agent Preview

This is what an AI agent sees when it discovers this service via the Gateway:

Service: Cohere
Description: Cohere provides enterprise AI models for text generation, semantic search, and content analysis. It offers chat completion, text embeddings, document reranking, and text classification through a unified API.
Auth: api_key
Capabilities:
  - chat: Generate conversational responses using Cohere's language models. Supports multi-turn dialogue, tool use, document grounding, and structured JSON output.
  - chat_stream: Generate conversational responses as a real-time stream of server-sent events for token-by-token display.
  - classify_text: Classify text inputs into predefined categories using few-shot examples. Useful for sentiment analysis, topic tagging, and content moderation.
  - embed_text: Generate vector embeddings for text inputs, useful for semantic search, clustering, and classification tasks.
  - rerank_documents: Reorder a list of documents by relevance to a search query, improving search result quality for RAG pipelines.