Cohere AI

gem 'cohere-ai', '~> 1.1.0'

require 'cohere-ai'

client = Cohere.new(
  credentials: { api_key: ENV['COHERE_API_KEY'] },
  options: { server_sent_events: true }
)

result = client.chat(
  { model: 'command', message: 'Hi!' }
)

{ 'response_id' => '59aac3ec-74c8-4b65-a80c-d4c1916d2511',
  'text' =>
  "Hi there! I'm Coral, an AI-assistant chatbot ready to help you with whatever you need. Is there anything I can assist you with today? \n" \
    "\n" \
    "If you'd like, I can also provide you with a list of some common topics that I can help with if you're looking for ideas. \n" \
    "\n" \
    "Just let me know if there's anything I can do to help make your day easier!",
  'generation_id' => '8a72b85c-ed29-4258-bd52-82b81be2353b',
  'token_count' => { 'prompt_tokens' => 64, 'response_tokens' => 82, 'total_tokens' => 146, 'billed_tokens' => 135 },
  'meta' => { 'api_version' => { 'version' => '1' },
              'billed_units' => { 'input_tokens' => 53, 'output_tokens' => 82 } },
  'tool_inputs' => nil }

require 'cohere-ai'

client = Cohere.new(
  credentials: { api_key: ENV['COHERE_API_KEY'] },
  options: { server_sent_events: true }
)

require 'cohere-ai'

client = Cohere.new(
  credentials: {
    address: 'https://api.cohere.ai',
    api_key: ENV['COHERE_API_KEY']
  },
  options: { server_sent_events: true }
)

result = client.chat(
  { model: 'command', message: 'Hi!' }
)

{ 'response_id' => '59aac3ec-74c8-4b65-a80c-d4c1916d2511',
  'text' =>
  "Hi there! I'm Coral, an AI-assistant chatbot ready to help you with whatever you need. Is there anything I can assist you with today? \n" \
    "\n" \
    "If you'd like, I can also provide you with a list of some common topics that I can help with if you're looking for ideas. \n" \
    "\n" \
    "Just let me know if there's anything I can do to help make your day easier!",
  'generation_id' => '8a72b85c-ed29-4258-bd52-82b81be2353b',
  'token_count' => { 'prompt_tokens' => 64, 'response_tokens' => 82, 'total_tokens' => 146, 'billed_tokens' => 135 },
  'meta' => { 'api_version' => { 'version' => '1' },
              'billed_units' => { 'input_tokens' => 53, 'output_tokens' => 82 } },
  'tool_inputs' => nil }

client.chat(
  { model: 'command', stream: true, message: 'Hi!' }
) do |event, raw|
  puts event
end

{ 'is_finished' => false,
  'event_type' => 'stream-start',
  'generation_id' => '0672df6f-736e-4536-8ad1-36bc808a114d' }

{ 'is_finished' => false,
  'event_type' => 'text-generation',
  'text' => 'Hi' }

{ 'is_finished' => true,
  'event_type' => 'stream-end',
  'response' => {
    'response_id' => '7dca6bf9-8a21-4f81-9e4e-2c5b8eb8c767',
    'text' => "Hi there! How can I help you today? I'm glad to assist you with any questions or tasks you have in mind, and I'm always happy to have a friendly conversation too. Go ahead and let me know how I can make your day better!",
    'generation_id' => '0672df6f-736e-4536-8ad1-36bc808a114d',
    'token_count' => {
      'prompt_tokens' => 64, 'response_tokens' => 52, 'total_tokens' => 116, 'billed_tokens' => 105
    },
    'tool_inputs' => nil
  },
  'finish_reason' => 'COMPLETE' }

result = client.chat(
  { model: 'command', stream: true, message: 'Hi!' }
)

[{ 'is_finished' => false, 'event_type' => 'stream-start', 'generation_id' => '7f0349ef-a823-4779-801a-6e0a56c016a9' },
 { 'is_finished' => false, 'event_type' => 'text-generation', 'text' => 'Hi' },
 # ...
 { 'is_finished' => false, 'event_type' => 'text-generation', 'text' => '?' },
 { 'is_finished' => true,
   'event_type' => 'stream-end',
   'response' =>
   { 'response_id' => 'f4135de4-3631-4f7c-98be-deb50b7f986b',
     'text' =>
     "Hi there! How can I assist you today? I'm programmed to provide helpful, fact-based responses and engage in conversations on a wide range of topics. Feel free to ask me anything, and we'll see how I can help you out! \n" \
       "\n" \
       'Do you have any requests or questions that I can help with?',
     'generation_id' => '7f0349ef-a823-4779-801a-6e0a56c016a9',
     'token_count' => { 'prompt_tokens' => 64, 'response_tokens' => 65, 'total_tokens' => 129, 'billed_tokens' => 118 },
     'tool_inputs' => nil },
   'finish_reason' => 'COMPLETE' }]

result = client.chat(
  { model: 'command', stream: true, message: 'Hi!' }
) do |event, raw|
  puts event
end

client.generate(
  { stream: true,
    truncate: 'END',
    return_likelihoods: 'NONE',
    prompt: 'Please explain to me how LLMs work' }
) do |event, raw|
  puts event
end

result = client.generate(
  { truncate: 'END',
    return_likelihoods: 'NONE',
    prompt: 'Please explain to me how LLMs work' }
)

{ 'id' => '9caef8a6-07fb-465c-a003-5fd7c7bbccbd',
  'generations' =>
  [{ 'id' => '11b043ab-6d9c-415f-90b0-6a802a3807f7',
     'text' =>
     " LLMs, or Large Language Models, are a type of neural network architecture designed to understand and generate human-like language. They are trained by feeding them massive amounts of text data and adjusting their internal parameters to predict the next word in a sequence accurately, given the words that came before it. This process is known as language modeling.\n" \
       "\n" \
       "There are two main types of LLMs: autoregressive and generative models. Autoregressive models, such as the long short-term memory (LSTM) network and the gated recurrent unit (GRU), predict the next word in a sequence by relying solely on the past context. On the other hand, generative models, such as the variational autoencoder (VAE) and the generative adversarial network (GAN), can generate new data similar to the training data.\n" \
       "\n" \
       "One of the key features of LLMs is their ability to capture long-range dependencies in text, which means they can understand and generate sentences that rely on information from words far away in the sequence. This is particularly useful for tasks like language translation, summarization, and question-answering, where understanding the context is crucial.\n" \
       "\n" \
       "To improve the accuracy and performance of LLMs, researchers and engineers often use techniques like pre-training and transfer learning. During pre-training, the LLM is trained on a large and diverse dataset, such as books, articles, and websites, to learn general language patterns and relationships. Once the LLM is pre-trained, it can be fine-tuned on specific tasks with smaller datasets related to the task, such as medical texts or legal documents. This way, the LLM can leverage its knowledge of language understanding while adapting to the specific domain or task at hand.\n" \
       "\n" \
       "Overall, LLMs have had a significant impact on the field of natural language processing, allowing researchers to build more sophisticated models that can understand and generate language in ways that were previously impossible. However, it is important to note that LLMs are sophisticated tools that require large amounts of data, computational power, and careful tuning to achieve their full potential. Moreover, they can also inherit the biases present in the training data, highlighting the importance of data diversity and responsible LLM development and usage. \n" \
       "\n" \
       'Would you like me to go into more detail about any specific aspect of LLM functionality? ',
     'finish_reason' => 'COMPLETE' }],
  'prompt' => 'Please explain to me how LLMs work',
  'meta' => { 'api_version' => { 'version' => '1' },
              'billed_units' => { 'input_tokens' => 8, 'output_tokens' => 476 } } }

result = client.embed(
  { texts: ['hello', 'goodbye'],
    model: 'embed-english-v3.0',
    input_type: 'classification' }
)

{ 'id' => '5d77f09a-3518-44d3-bac3-f868b3e036bc',
  'texts' => ['hello', 'goodbye'],
  'embeddings' =>
  [[0.016296387,
    -0.008354187,
    # ...
    -0.01802063,
    0.009765625],
   [0.04663086,
    -0.023239136,
    # ...
    0.0023212433,
    0.0052719116]],
  'meta' =>
  { 'api_version' => { 'version' => '1' }, 'billed_units' => { 'input_tokens' => 2 } },
  'response_type' => 'embeddings_floats' }

result = client.rerank(
  { return_documents: false,
    max_chunks_per_doc: 10,
    model: 'rerank-english-v2.0',
    query: 'What is the capital of the United States?',
    documents: [
      'Carson City is the capital city of the American state of Nevada.',
      'The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean. Its capital is Saipan.',
      'Washington, D.C. (also known as simply Washington or D.C., and officially as the District of Columbia) is the capital of the United States. It is a federal district.',
      'Capital punishment (the death penalty) has existed in the United States since beforethe United States was a country. As of 2017, capital punishment is legal in 30 of the 50 states.'
    ] }
)

{ 'id' => 'ba2100fe-69d2-41d6-8680-810948af872d',
  'results' =>
  [{ 'index' => 2, 'relevance_score' => 0.98005307 },
   { 'index' => 3, 'relevance_score' => 0.27904198 },
   { 'index' => 0, 'relevance_score' => 0.10194652 },
   { 'index' => 1, 'relevance_score' => 0.0721122 }],
  'meta' =>
  { 'api_version' => { 'version' => '1' }, 'billed_units' => { 'search_units' => 1 } } }

result = client.classify(
  {
    truncate: 'END',
    inputs: [
      'Confirm your email address',
      'hey i need u to send some $'
    ],
    examples: [
      {
        text: "Dermatologists don't like her!",
        label: 'Spam'
      },
      {
        text: 'Hello, open to this?',
        label: 'Spam'
      },
      {
        text: 'I need help please wire me $1000 right now',
        label: 'Spam'
      },
      {
        text: 'Nice to know you ;)',
        label: 'Spam'
      },
      {
        text: 'Please help me?',
        label: 'Spam'
      },
      {
        text: 'Your parcel will be delivered today',
        label: 'Not spam'
      },
      {
        text: 'Review changes to our Terms and Conditions',
        label: 'Not spam'
      },
      {
        text: 'Weekly sync notes',
        label: 'Not spam'
      },
      {
        text: 'Re: Follow up from today’s meeting',
        label: 'Not spam'
      },
      {
        text: 'Pre-read for tomorrow',
        label: 'Not spam'
      }
    ]
  }
)

{ 'id' => '1d0c322e-9ab7-4a80-b601-720e7592dde5',
  'classifications' =>
  [{ 'classification_type' => 'single-label',
     'confidence' => 0.8082329,
     'confidences' => [0.8082329],
     'id' => '44b2e358-83f1-4b9b-a6f1-e8d9c823f0ba',
     'input' => 'Confirm your email address',
     'labels' =>
     { 'Not spam' => { 'confidence' => 0.8082329 },
       'Spam' => { 'confidence' => 0.19176713 } },
     'prediction' => 'Not spam',
     'predictions' => ['Not spam'] },
   { 'classification_type' => 'single-label',
     'confidence' => 0.9893421,
     'confidences' => [0.9893421],
     'id' => '53ad6d6e-872f-4185-b3d6-6d03fe55f4c4',
     'input' => 'hey i need u to send some $',
     'labels' =>
     { 'Not spam' => { 'confidence' => 0.01065793 },
       'Spam' => { 'confidence' => 0.9893421 } },
     'prediction' => 'Spam',
     'predictions' => ['Spam'] }],
  'meta' =>
  { 'api_version' => { 'version' => '1' }, 'billed_units' => { 'classifications' => 2 } } }

result = client.detect_language(
  { texts: ['Hello world', "'Здравствуй, Мир'"] }
)

{ 'id' => '82b111d4-ba6d-4f60-9536-883b42f3d86d',
  'results' =>
  [{ 'language_code' => 'en', 'language_name' => 'English' },
   { 'language_code' => 'ru', 'language_name' => 'Russian' }],
  'meta' => { 'api_version' => { 'version' => '1' } } }

result = client.summarize(
  { text: "Ice cream is a sweetened frozen food typically eaten as a snack or dessert. It may be made from milk or cream and is flavoured with a sweetener, either sugar or an alternative, and a spice, such as cocoa or vanilla, or with fruit such as strawberries or peaches. It can also be made by whisking a flavored cream base and liquid nitrogen together. Food coloring is sometimes added, in addition to stabilizers. The mixture is cooled below the freezing point of water and stirred to incorporate air spaces and to prevent detectable ice crystals from forming. The result is a smooth, semi-solid foam that is solid at very low temperatures (below 2 °C or 35 °F). It becomes more malleable as its temperature increases.\n\nThe meaning of the name \"ice cream\" varies from one country to another. In some countries, such as the United States, \"ice cream\" applies only to a specific variety, and most governments regulate the commercial use of the various terms according to the relative quantities of the main ingredients, notably the amount of cream. Products that do not meet the criteria to be called ice cream are sometimes labelled \"frozen dairy dessert\" instead. In other countries, such as Italy and Argentina, one word is used fo\r all variants. Analogues made from dairy alternatives, such as goat's or sheep's milk, or milk substitutes (e.g., soy, cashew, coconut, almond milk or tofu), are available for those who are lactose intolerant, allergic to dairy protein or vegan." }
)

{ 'id' => '5189bed8-2d12-47d8-8ae7-cf60788cf507',
  'summary' =>
  'Ice cream is a popular frozen dessert made from milk or cream, sweeteners, and spices like vanilla or cocoa, or fruit like strawberries. It is cooled below the freezing point of water and stirred to incorporate air spaces, resulting in a smooth semi-solid foam. While the name applies to just one variety in some countries, like the US, it refers to all variants in others, like Italy. Additionally, there are dairy alternatives available for those who are lactose intolerant or vegan. Ice cream is regulated by governments based on the quantities of its main ingredients.',
  'meta' =>
  { 'api_version' => { 'version' => '1' },
    'billed_units' => { 'input_tokens' => 321, 'output_tokens' => 111 } } }

result = client.tokenize(
  { text: 'tokenize me! :D', model: 'command' }
)

{ 'tokens' => [10_002, 2261, 2012, 8, 2792, 43],
  'token_strings' => ['token', 'ize', ' me', '!', ' :', 'D'],
  'meta' => { 'api_version' => { 'version' => '1' } } }

result = client.detokenize(
  { tokens: [10_104, 12_221, 1315, 34, 1420, 69], model: 'command' }
)

{ 'text' => ' Anton Mun🟣;🥭^', 'meta' => { 'api_version' => { 'version' => '1' } } }

result = client.request(
  'v1/dataset',
  request_method: 'GET', server_sent_events: false
)

result = client.request(
  'v1/dataset',
  { name: 'prompt-completion-dataset',
    data: File.read('./prompt-completion.jsonl'),
    dataset_type: 'prompt-completion-finetune-input' },
  request_method: 'POST', server_sent_events: false
)

result = client.request(
  'v1/connectors',
  request_method: 'GET', server_sent_events: false
)

result = client.request(
  'v1/connectors',
  { name: 'test-connector',
    url: 'https://example.com/search',
    description: 'A test connector' },
  request_method: 'POST', server_sent_events: false
)

client = Cohere.new(
  credentials: { api_key: ENV['COHERE_API_KEY'] },
  options: { server_sent_events: true }
)

client.chat(
  { model: 'command', stream: true, message: 'Hi!' }
  server_sent_events: true
) do |event, raw|
  puts event
end

result = client.chat(
  { model: 'command',
    chat_history: [
      { role: 'USER', message: 'Hi, my name is Purple.' },
      { role: 'CHATBOT', message: "Hi Purple! It's nice to meet you." }
    ],
    message: "What's my name?" }
)

{ 'response_id' => 'a2009c24-fee3-465e-9945-a85edcdcb3cf',
  'text' =>
  "Your name is Purple. Isn't it an enchanting name? \n" \
    "\n" \
    "Would you like me to help you with anything else? If you have any questions or need assistance with a particular task, feel free to let me know. I'm here to help!",
  'generation_id' => 'e1630c10-f773-4ced-8760-19199004653a',
  'token_count' => { 'prompt_tokens' => 91, 'response_tokens' => 51, 'total_tokens' => 142, 'billed_tokens' => 124 },
  'meta' => { 'api_version' => { 'version' => '1' },
              'billed_units' => { 'input_tokens' => 73, 'output_tokens' => 51 } },
  'tool_inputs' => nil }

result = client.request(
  'v1/chat',
  { model: 'command', message: 'Hi!' },
  request_method: 'POST', server_sent_events: true
)

require 'faraday/net_http'

client = Cohere.new(
  credentials: { api_key: ENV['COHERE_API_KEY'] },
  options: { connection: { adapter: :net_http } }
)

client = Cohere.new(
  credentials: { api_key: ENV['COHERE_API_KEY'] },
  options: { connection: { request: { timeout: 5 } } }
)

client = Cohere.new(
  credentials: { api_key: ENV['COHERE_API_KEY'] },
  options: {
    connection: {
      request: {
        timeout: 5,
        open_timeout: 5,
        read_timeout: 5,
        write_timeout: 5
      }
    }
  }
)

require 'cohere-ai'

begin
  client.chat(
    { model: 'command', message: 'Hi!' }
  )
rescue Cohere::Errors::CohereError => error
  puts error.class # Cohere::Errors::RequestError
  puts error.message # 'the server responded with status 500'

  puts error.payload
  # { model: 'command',
  #   message: 'Hi!'
  #   ...
  # }

  puts error.request
  # #<Faraday::ServerError response={:status=>500, :headers...
end

require 'cohere-ai/errors'

begin
  client.chat(
    { model: 'command',
      messages: [{ role: 'user', content: 'hi!' }] }
  )
rescue CohereError => error
  puts error.class # Cohere::Errors::RequestError
end

CohereError

MissingAPIKeyError
BlockWithoutServerSentEventsError
IncompleteJSONReceivedError

RequestError