Cohere
by Cohere Inc.
Generate text with Command models, create embeddings for semantic search, rerank search results, classify text, and summarise documents using Cohere's NLP API.
Sådan bruger agenter Cohere
- ✓Agent embeds user queries and document chunks for RAG retrieval using Cohere's embed-english model
- ✓Agent reranks vector search results to improve relevance before passing context to an LLM
- ✓Agent classifies incoming support messages by category using few-shot examples
- ✓Agent summarises long documents or articles before forwarding them to downstream nodes
- ✓Agent uses Command-R+ to reason over retrieved context and generate grounded responses
Agenthandlinger
Input: message, model, systemPrompt, chatHistory, temperature, maxTokens
Returnerer: text, finishReason, inputTokens, outputTokens
Input: texts, model, inputType
Returnerer: embeddings, embeddingCount, model
Input: query, documents, topN, model
Returnerer: results, topDocument, topScore
Input: inputs, examples
Returnerer: classifications, labels
Input: text, length, format, extractiveness
Returnerer: summary
Eksempel på workflows
RAG pipeline with reranking
Embed a query, retrieve candidates from Pinecone, rerank with Cohere, then generate a response with Command-R+.
Om Cohere
- Leverandør
- Cohere Inc.
- Pris Tjek altid detaljer med udbyderen
- Gratis / Betalt — Free trial includes limited API calls. Production pricing is usage-based per token/request.
- Godkendelse
- API-nøgle
- Hastighedsgrænse Tjek altid detaljer med udbyderen
- 100 anmodninger / minut
- Kompatible noder
- AgentResource
- Hjemmeside
- https://cohere.com
Byg et AI-workflow med Cohere
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