Cohere API Tutorial: Getting Started With Cohere Models

In the rapidly evolving field of AI, large language models (LLMs) have revolutionized text interaction and generation. Since OpenAI's ChatGPT launch in November 2022, a surge of new LLMs has emerged daily. Cohere Command stands out as a leading choice for developers and businesses. Cohere provides advanced tools to integrate the power of foundational models into diverse applications.

This guide explores Cohere's API, detailing its capabilities, benefits, and practical implementation. While we'll briefly touch on LLMs, a more comprehensive understanding can be gained through dedicated LLM courses.

Cohere and LLMs

LLMs are sophisticated AI systems that process and generate human-quality text. Trained on massive datasets, they identify complex patterns, understand linguistic nuances, and produce coherent responses. Their applications span translation, text completion, summarization, and interactive conversations.

Cohere is a key player, offering a user-friendly API that simplifies access to these LLM capabilities for data scientists.

What is Cohere?

Founded in 2019, Cohere is a Canadian AI solutions provider. It's a prominent LLM player, often compared to OpenAI GPT and Anthropic Claude. Cohere primarily develops and offers foundational language generation models accessible via its API.

Source: Cobus Greyling, Large Language Model Landscape, Medium

Cohere offers three main model types:

• Cohere Command: The Command R family offers high scalability, performance, and accuracy. It's a top performer in the LMSYS Chatbot Arena.
• Cohere Embed: A leading text representation model, enhancing search accuracy, retrieval-augmented generation (RAG), classification, and clustering.
• Cohere Rerank: Significantly improves the semantic quality of keyword or vector search systems without requiring a complete overhaul.

Cohere models are accessible through:

1. The Playground interface.
2. APIs in Python and other languages.

Cohere also provides a ChatGPT-like chat interface powered by Command R .

Cohere Playground

The Cohere Playground offers a user-friendly interface for interacting with Cohere models, similar to GPT. Users can experiment with model capabilities, generating text and analyzing behavior. Its intuitive design facilitates rapid prototyping and testing. The Playground is free for exploration and experimentation (until production use). Registration on Cohere's website is required. The interface, shown below, is similar to OpenAI's playground, allowing model selection and tasks like Chat, Classify, Embed, and Generate.

Cohere Playground Dashboard

While ideal for testing, application development requires programmatic access via the Cohere API.

Cohere API

Accessing the Cohere API involves:

1. Installing the Cohere library (!pip install cohere).
2. Obtaining an API key (production or trial).
3. Making API calls.

API Key and Call Example

The image below shows how to obtain an API key. The following code demonstrates a basic API call:

import cohere

co = cohere.Client('your_token_here')
message = "What is Machine Learning?"
response = co.chat(
  message=message,
  model="command",
  temperature=0.3
)

answer = response.text
print(answer)

The response object contains detailed metadata accessible via response.dict().

Multi-turn Conversations

For chatbots, maintaining conversation context is crucial. Cohere's API handles this using the chat_history parameter or, more efficiently, the conversation_id. Consistent use of conversation_id automatically incorporates previous messages for context. chat_history and conversation_id are mutually exclusive.

Cohere Pricing

Comparing Cohere Command R with OpenAI GPT-4 Turbo and Anthropic Claude Opus (as of May 2024):

Model	$ / million input tokens	$ / million output tokens
Cohere Command R	.00	.00
Anthropic Claude Opus	.00	.00
OpenAI GPT-4 Turbo	.00	.00

Cohere offers a cost advantage, but GPT-4 Turbo and Claude Opus often demonstrate superior performance.

Conclusion

Cohere provides competitive LLMs at a lower cost, suitable for developers and businesses. This guide covered accessing Cohere via the Playground and API. Further exploration can be done through additional resources on using the Cohere API and developing LLM applications.

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